Latest Articles Rss

Implementation of CONCEIVER++: An Object-Oriented Program Understanding System

Problem statement: Understanding on computer program is a complex cognitive activity. It is ability and also a difficult task especially for novice programmer. The object-oriented languages has widely used in education and industry recently. In programming it is important to have such software which can aid programmers or students to code the program. But, available program understanding systems using the plan based approach usually are developed for non-object-oriented programming languages. Reviewed from the available system also showed that none of the plan formalisms used is for an object-oriented language. Specifically, problem arises when the existing system is not usable for teaching programming purposes. Program understanding system with plan for object-oriented does not exist was the main reason why this research is being carried out. Approach: Method used on developed the program understanding system named CONCEIVER++ is Unified Approach (UA). The process involved from UA for developing and testing the system is iterative development and continuous testing. The process must be iterate and reiterate until satisfied with the system. In order to test the quality assurance of the system is by choosing the black box testing strategies. Results: The object-oriented program understanding system has been successfully implemented. The implementation is tested with an example of Java programming code. The binary search tree for control flow graph and linked list for plan has been generated. Results of understanding the meaning or semantic of the program codes also has been produced. The black box testing had shows that all statements of line of code of the example program have been recognized and the correctness output has been checked. Conclusion: The understanding module of CONCEIVER++, which are code/CFG processor, plan processor and recognition engine has been tested. All line of codes (or nodes) has been recognized and got correct meaning using the developed module.

A New Smooth Support Vector Machine and Its Applications in Diabetes Disease Diagnosis

Problem statement: Research on Smooth Support Vector Machine (SSVM) is an active field in data mining. Many researchers developed the method to improve accuracy of the result. This study proposed a new SSVM for classification problems. It is called Multiple Knot Spline SSVM (MKS-SSVM). To evaluate the effectiveness of our method, we carried out an experiment on Pima Indian diabetes dataset. The accuracy of previous results of this data still under 80% so far. Approach: First, theoretical of MKS-SSVM was presented. Then, application of MKS-SSVM and comparison with SSVM in diabetes disease diagnosis were given. Results: Compared to the SSVM, the proposed MKS-SSVM showed better performance in classifying diabetes disease diagnosis with accuracy 93.2%. Conclusion: The results of this study showed that the MKS-SSVM was effective to detect diabetes disease diagnosis and this is very promising compared to the previously reported results.

Swarm Negative Selection Algorithm for Electroencephalogram Signals Classification

Problem statement: The process of epilepsy diagnosis from EEG signals by a human scorer is a very time consuming and costly task considering the large number of epileptic patients admitted to the hospitals and the large amount of data needs to be scored. Therefore, there is a strong need to automate this process. Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. DWT used to analyze EEG signals at different frequency bands and statistics over the set of the wavelet coefficients were calculated to introduce the feature vector for SNS classifier. The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. Thus, adapted negative selection is employed to create a set of self-tolerant ALCs. Whereas, PSO is used to evolve these ALCs away from self patterns towards non-self space and to maintain diversity and generality among the ALCs. Results: The experimental results proved that the proposed method reveals very promising performance in classifying EEG signals. A comparison with many previous studies showed that the presented algorithm has better results outperforming those reported by earlier methods. Conclusion: The technique was approved to be robust and effective in detecting and localizing epileptic seizure in EEG recording. Hence, the proposed system can be very helpful to make faster and accurate diagnosis decision.

Static Segmentation of the Lips for Follow-Up

Problem statement: The objective of this study particularly aims the static segmentation of the lips. Approach: For that, we proposed algorithms for the determination of certain characteristic points of the lips, as well as a method of optimal slope allowing to trace the cubic ones forming external contours of the lips. Results: Finally to make sure of the performance of our algorithms, we also used a manual determination of the characteristic points. Conclusion: The results obtained showed the rigor of our algorithms and that by comparing the results obtained by the manual determination with those of the semi-automatic determination.

Optimal Thyristor Control Series Capacitor Neuro-Controller for Damping Oscillations

This study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive �pseudo-linear regression. Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks are used in the design-the identifier/model network to identify the dynamics of the power system and the controller network to provide optimal damping. By applying this controller to the TCSC devices the damping of inter-area modes of oscillations in a multi-machine power system will be handled properly. Results: The effectiveness of the proposed optimal controller is demonstrated on two power system problems. The first case involves TCSC supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a complex system to provide a very good solution to oscillation damping control problem in the Southern Malaysian Peninsular Power Grid. Conclusion: Finally, several fault and load disturbance simulation results are presented to stress the effectiveness of the proposed TCSC controller in a multi-machine power system and show that the proposed intelligent controls improve the dynamic performance of the TCSC devices and the associated power network.

Simulated Annealing with Deterministic Decisions

Problem statement: Simulated Annealing (SA) algorithms have been used in solving a wide range of discrete optimization problems for many years, with well know drawbacks like the computational time and difficulties related to the parameters settings. One of the other issues that open the door for research is the acceptance decision that provides for hill climbing; the standard SA algorithms use a stochastic method which fails to justify the acceptance of a cost increasing solutions while rejecting mildly cost increasing ones. Approach: To resolve this dilemma, the reversible deformation mechanism we developed earlier replaced the stochastic decision with a deterministic one; by deforming the problem structure and gradually reforming it towards the original one. This provides for hill climbing in the real domain while applying a simple downhill search in the virtual sense. Unlike the standard SA algorithm, the number of iterations must be known in advance and it is the only stopping criteria, because the scaling functions parameters are selected based on the number of iterations. Results: This method had produced better solutions and the new enhancement to the algorithm improves the overall performance by examining each state more thoroughly through a set of perturbations and thus securing a move towards a better neighborhood, the same set of tests used in the original methods are repeated for comparison. Conclusion: The significance of this research comes from eliminating the unpredictability of the stochastic decisions in the standard SA algorithms which might yield less than acceptable solutions in some cases.

Omega Network Hash Construction

Problem statement: Cryptographic hash functions are important cryptographic primitives. They are commonly used for data integrity checking and data authentication. Most of the cryptographic hash functions are based on the Merkle-Damg�rd construction. The basic Merkle-Damg�rd construction runs over the input sequentially, which can lead to problems when the input size is large since the computation time increases linearly. Approach: Therefore, an alternative architecture which can reduce the computation time is needed, especially in today�s world where multi-core processors and multithreaded programming are common. An Omega Network Hash Construction (ONHC) run parallel in multi-core machine has been proposed as an alternative to the existing hash constructions. Result: The ONHC performed better than the Merkle-Damg�rd construction. ONHC permutation architecture also showed improved security strength in term of digest value randomness when compared to Merkle-Damg�rd construction. Conclusion: Therefore, it is believed that the proposed ONHC is a valuable structure that can improve the performance of any hash function that can run on top of it.

Server Optimization Using Heuristic Algorithms for Dynamic-Split-and-Merge Scheme in Wireless Multicast

Problem statement: In order to minimize the overall network traffic in a multiserver system, the number of users served by each server (and hence the group size) should remain constant. As the underlying traffic fluctuates, a split and merge scheme is implemented in a physical server to achieve load balancing. Approach: Minimizing the number of servers during the merge operation is NP hard and to achieve these two algorithms namely FFD bin packing algorithm and LL algorithm were proposed to find the near optimal values of destination servers. Results: The performance of these algorithms were analyzed and compared based on several parameters. Conclusion: Results showed that LL algorithm outperforms FFD algorithm.

Vision Based Reconstruction Multi-Clouds of Scale Invariant Feature Transform Features for Indoor Navigation

Problem statement: Navigation for visually impaired people needs to exploit more approaches for solving problems it has, especially in image based methods navigation. Approach: This study introduces a new approach of an electronic cane for navigation through the environment. By forming multi clouds of SIFT features for the scene objects in the environment using some considerations. Results: The system gives an efficient localization within the weighted topological graph. Instead of building a metric (3D) model of the environment, it helps the blind person to navigate more confidently. The work efforts towards conceptualizing environment on the basis of the human compatible representation so formed. Such representation and the resulting conceptualization would be useful for enabling blind persons to be cognizant of their surroundings. The identification of different scenes to the blind person has done by clouds of three or two objects. These clouds grouped the stored objects into meaningful groups used in localization of a cane with single web camera as an external sensor. Conclusion: The approach is useful to divide the space environment into meaning partitions and helps to detect sites and objects needed from the blind person in very sufficient way with in the map.

Does the Size of Personalized Menus Affect User Performance?

Problem statement: To date, researchers have personalized graphical user interfaces for individual users to reduce visual search time. Little research, however, has been directed at understanding the factors which cause approaches to personalization to have positive effects at one time and negative ones at others. Approach: The study reported here investigated empirically the effects of content size on 5 different personalized menu types: Adaptable, adaptive split, adaptive/adaptable highlighted, adaptive/adaptable minimized and mixed-initiative menus. More specifically, it compared the usability of these five types with regard to task accomplishment time and frequency of error-occurrence. In order to carry out this comparative investigation, we conducted two independent experiments, on small menus (17 items) and large ones (29 items) respectively. These were tested dependently using 30 subjects each. Results: Results showed that the adaptable type was surprisingly the most efficient overall of the small menus and the least efficient of the large ones. Conclusion: Conversely, the minimized type was the slowest of the small menus and the fastest of the large ones. Finally, errors were reduced in adaptable and minimized small menus by 50 and 62% respectively, whilst being increased in the large adaptable one.

Information Hiding: A Generic Approach

Problem statement: Privacy and security over communication channels are of primary concerns. Due to their complexity and diversity, there is a need for continuous improvements of the adopted solutions. In this study, we consider two of the adopted ones, namely, steganogrphy and cryptography and propose a new information hiding system. Approach: The proposed system was based on a generic approach that incorporates text-based steganography and cryptography methods in a way that permits their combined or stand alone adoption. Thus, achieving message encryption incorporated with its concealing inside another unsuspicious one. Furthermore, two steganography methods (the inter-word spaces method and syntactic methods) had been combined with a hybrid text-encoding in a form of binary representation of terns rewriting systems. Results: An information hiding system had been implemented. The system offered encrypting and hiding dynamic and static text within a cover-text. The conducted experiments using static texts had shown a non-noticeable increase (0.02%) in the size of their respective stego-texts. For the dynamic texts, cover- texts with a size proportional to the length of the secret messages were needed. Conclusion: A generic model for information hiding with a respective implementation framework had been used as an effective tool to develop a hybrid and scalable steganography system that combined good features from the existing ones.

Bluetooth Wireless Monitoring, Managing and Control for Inter Vehicle in Vehicular Ad-Hoc Networks

Problem statement: The car users expect more and more accessories available in their cars, but the accessories available needed manage by driver manually and not properly manage by smart system. All these accessories are able to control by user manually using different and standalone controllers. Besides, the controller itself uses RF technology which is not existed in mobile devices. So there is lack of a comprehensive and integrated system to manage, control and monitor all the accessories inside the vehicle by using a personal mobile phone. Design and development of an integrated system to manage and control all kind of inter vehicle accessories, improving the efficiency and functionality of inter vehicle communications for the car users. Approach: The proposed system was based on Microcontroller, Bluetooth and Java technology and in order to achieve the idea of an intelligence car with ability to uses personal mobile hand phone as a remote interface. Development strategies for this innovation are includes two phases: (1) java based application platform-designed and developed for smart phones and PDAs (2) hardware design and implementation of the receiver side-compatible smart system to managing and interconnection between all inside accessories based on monitoring and controlling mechanisms by Bluetooth media. Results: The designed system included hardware and software and the completed prototype had tested successfully on the real vehicles. During the testing stage, the components and devices were connected and implemented on the vehicle and the user by installing the system interface on a mobile phone is able to monitor and manage the vehicle accessories, the efficiency, adaptively and range of functionality of the system has proved with the various car accessories. Conclusion: This study involved design a new system to decrease the hot temperature inside a car that affecting the health of the car driver and the car driver is able to control some of the car accessories by using mobile phone. Once the car was equipped with the Bluetooth module and control system, the car accessories is able to connect with microcontroller and control by the mobile application.

Formalized Model of Stabile Reengineering Information System Functional Elements (Business Processes)

The process of reengineering the functional elements of management information system must presented as stable, in which all the kernel functional components of the management information system should be saved. Problem statements: There is no formalized models for stabile reengineering for the functional structure (functional elements) for various information systems types, therefore the process of reengineering is not stabile and may be it finished with failure reengineering process or failure information system. Approach: The information system development Approach and the mathematical methods to formalized the detailed mathematical model for the information systems stabile reengineering, and at different stages of IS reengineering. Results: All process of stabile reengineering at the various stages of it was formalized in mathematical models. Conclusion: The developed models helps the system analyst to define if the reengineering process for the functional structure of information system will be stabile and effective or not, and if it more feasible than creating new information system.

Towards the Development of Speaker-Dependent and Speaker-Independent Hidden Markov Model-Based Thai Speech Synthesis

Problem statement: Tone distortion in Thai languages can deteriorate not only the intelligibility of speech but also its naturalness. Therefore, the correctness of tone must be carefully taken into account in continuous speech synthesis. The preliminary work confronted this problem when applying HMM-based speech synthesis to Thai. Approach: This study presented a study on speaker-dependent and speaker-independent Hidden Markov Model (HMM)-based Thai speech synthesis. In the speaker-dependent system, we developed a simple tone-separated tree structure in the tree-based context clustering process of the training stage to treat the tone distortion problem. In the speaker-independent system or averaged-voice-model system, a number of tonal features are extracted and applied with the Speaker Adaptive Training (SAT) and Shared Decision Tree (STC) techniques to release the tone distortion problem. Results: Our objective evaluation revealed that the proposed features could make the F0 contour closer to the target speaker�s real contour. The results from our subjective test also revealed that the proposed tonal features could improve the tone intelligibility of all speech-model scenarios of male and female. Conclusion: By applying our approach, the problem of tone distortion can be relieved effectively. The better tone correctness can improve the intelligibility and the naturalness of speech significantly.

A Context-Aware Mobile Organizer for University Students

Problem statement: With the expansion of mobile devices, the usage of context-aware mobile applications is becoming very popular. Approach: One of mobile applications that are useful for university students is the university mobile organizer. University Mobile Organizer is a software that acts like an assistant for students in their universities� activities. Results: However, this application was not used widely by the students. In this research, we explored students� problems and requirements in their university activities and then proposed a context-aware university mobile organizer that will be useful for them. Conclusion/Recommendations: Based on these requirements, a proper framework for implementing a university mobile organizer is developed. Lastly, the software is implemented based on the framework that has been developed.

Challenges of Hidden Data in the Unused Area Two within Executable Files

Problem statement: The executable files are one of the most important files in operating systems and in most systems designed by developers (programmers/software engineers), and then hiding information in these file is the basic goal for this study, because most users of any system cannot alter or modify the content of these files. There are many challenges of hidden data in the unused area two within executable files, which is dependencies of the size of the cover file with the size of hidden information, differences of the size of file before and after the hiding process, availability of the cover file after the hiding process to perform normally and detection by antivirus software as a result of changes made to the file. Approach: The system designed to accommodate the release mechanism that consists of two functions; first is the hiding of the information in the unused area 2 of PE-file (exe.file), through the execution of four process (specify the cover file, specify the information file, encryption of the information, and hiding the information) and the second function is the extraction of the hiding information through three process (specify the steno file, extract the information, and decryption of the information). Results: The programs were coded in Java computer language and implemented on Pentium PC. The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file (exe.file). Conclusion: Features of the short-term responses were simulated that the size of the hidden data does depend on the size of the unused area2 within cover file which is equal 20% from the size of exe.file before hiding process, most antivirus systems do not allow direct write in executable file, so the approach of the proposed system is to prevent the hidden information to observation of these systems and the exe.file still function as usual after the hiding process.

Indoor Navigation and Localization for Visually impaired people Using Weighted Topological Map

Problem Statement: Image base methods are a new approach for solving problems of navigations for visually impaired people. Approach: The study introduced a new approach of an electronic cane for blind people using the environment represented as a weighted topological graph instead, each node contains images taken at some poses in the work space, instead of building a metric (3D) model of the environment. Results: By computing weights between already stored images and the real scene of the environment and take some considerations like sessions. The system gives advices for the blind person to select the right direction in indoor navigate depending on weights and session, where a mono camera cane-held gives information in front of the visually impaired person. Conclusion: A cane that has the ability of getting SIFT feature for an object or site from a sequence of live images using the suggested approach is very satisfactory, The session and weight, speed up the system and gives a wide range indoor navigation and may be used to outdoor. Experimental results demonstrated a good performance of proposed method, the identification of different scenes to the blind person done by constructing the weighted visual environment graph to the system. The proposed scheme is using SIFT features to represent the objects and the sites.

An Artificial Neural Networks-Based on-Line Monitoring Odor Sensing System

Problem statement: There have been many works for odor recognition using different sensor arrays and pattern recognition techniques in last decades. Approach: Although an odor is usually recorded utilizing language expression, it is too difficult for laymen to associate actual odor with that expression. Results: The odor sensing system should be extended to new areas since its standard style where the output pattern from multiple sensors with partially overlapped specificity is recognized by a neural network or multivariate analysis. Conclusion/Recommendations: In this study, we have developed odor sensing system with the capability of the discrimination among closely similar 20 different odor patterns and proposed an on-line classification method using a handheld odor meter (OMX-GR sensor) and neural network.

Optimizing Feature Construction Process for Dynamic Aggregation of Relational Attributes

Problem statement: The importance of input representation has been recognized already in machine learning. Feature construction is one of the methods used to generate relevant features for learning data. This study addressed the question whether or not the descriptive accuracy of the DARA algorithm benefits from the feature construction process. In other words, this paper discusses the application of genetic algorithm to optimize the feature construction process to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). Approach: The DARA algorithm was designed to summarize data stored in the non-target tables by clustering them into groups, where multiple records stored in non-target tables correspond to a single record stored in a target table. Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm. Since, the study addressed the question whether or not the descriptive accuracy of the DARA algorithm benefits from the feature construction process, the involved task includes solving the problem of constructing a relevant set of features for the DARA algorithm by using a genetic-based algorithm. Results: It is shown in the experimental results that the quality of summarized data is directly influenced by the methods used to create patterns that represent records in the (n�p) TF-IDF weighted frequency matrix. The results of the evaluation of the genetic-based feature construction algorithm showed that the data summarization results can be improved by constructing features by using the Cluster Entropy (CE) genetic-based feature construction algorithm. Conclusion: This study showed that the data summarization results can be improved by constructing features by using the cluster entropy genetic-based feature construction algorithm.

Clinical Assessment of Watermarked Medical Images

Problem statement: Digital watermarking provides security to medical images. Watermarking in Region Of Interest (ROI) however distorts medical images but it is known that the resulting loss of fidelity is visually imperceptible. Approach: Clinical assessment will objectively evaluate the distortion on medical images to see whether or not medical diagnosis is altered. We used 75 medical images consisting of x-rays, ultrasound and CT scans. Digital watermarking was inserted in ROI and ROI/Region Of Non Interest (RONI) in all of them. Three assessors were randomly assigned 225 images, each receiving 75, a mixture of watermarked and non watermarked images. Results: Chi square test was used and p<0.05 was considered significant. There was no significant difference between original images and those watermarked in ROI or ROI/RONI. There was no comment on image quality in all the images assessed. Conclusion/Recommendations: Digital watermarking does not alter medical diagnosis when assessed by clinical radiologists. The quality of the watermarked images was also unchanged.

A Modified Conjugate Gradient Formula for Back Propagation Neural Network Algorithm

Problem statement: The Conjugate Gradient (CG) algorithm which usually used for solving nonlinear functions is presented and is combined with the modified Back Propagation (BP) algorithm yielding a new fast training multilayer algorithm. Approach: This study consisted of determination of new search directions by exploiting the information calculated by gradient descent as well as the previous search direction. The proposed algorithm improved the training efficiency of BP algorithm by adaptively modifying the initial search direction. Results: Performance of the proposed algorithm was demonstrated by comparing it with the Neural Network (NN) algorithm for the chosen test functions. Conclusion: The numerical results showed that number of iterations required by the proposed algorithm to converge was less than the both standard CG and NN algorithms. The proposed algorithm improved the training efficiency of BP-NN algorithms by adaptively modifying the initial search direction.

New Constructive Neural Network Architecture for Pattern Classification

Problem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The constructive neural network training is performed via feed forward paradigm under supervised training considerations. These supervised methods often make the network size grow exponentially, or, the network lacks generalization. To address these problems a new method for learning in constructive neural networks is necessary. Approach: To address these issues a new Multicategory Tiling architecture was chosen for its simple topology and an improved adaptive resonance theory unsupervised training algorithm was used with proper weight setting to train the constructive networks on binary sequence patterns. The results and performance of the new algorithm was compared with existing constructive neural network architectures and tabulated. Results: The new architecture with improved training algorithm offer faster convergence in learning, the nodes required for storage are less and the generalization of pattern classification was achieved in comparison with existing algorithms. Conclusion: Constructive neural networks could be trained using unsupervised algorithm to achieve better performance in comparison with existing supervised algorithms.

Vibration equations of Thick Rectangular Plates Using Mindlin Plate Theory

Problem statement: Rectangular steel plates are widely used in various steel structures and steel industries. For a proper design of steel plate structures and efficient use of material, the behavior, strength, buckling and post-buckling characteristics of plates should be accurately determined. Approach: Considering the significance of this matter, lateral vibration of thick rectangular plates was studied on the basis of mindlin plate theory. The exact characteristic equations for a plate which is single supported in two opposite edges are available in the literature. S-C-S-F boundary condition which covers all possible situations is selected in this study. Results: The plate frequencies were calculated for this boundary condition for a wide range of plate sizes and thicknesses. The plate mode shapes were obtained for different cases and the effect of changes in boundary conditions; size ratio and thickness on the vibration behavior of rectangular steel plates are studied. Conclusion/Recommendations: Since the results of this study is exact and without any approximation, the presented values can be used as a proper criteria to evaluate the error value of approximate methods which are used by engineers for design of steel plates. These results can provide a good gridline for efficient design and prevention of using high safety factors. Considering the wide range of steel rectangular plates, more sizes and thicknesses of plates can be studied. The behavior of plates with other boundary conditions can also be studied for future research.

A Fragile Watermarking Scheme for Image Authentication with Tamper Localization Using Integer Wavelet Transform

Problem statement: In recent years, as digital media are gaining wider popularity, their security related issues are becoming greater concern. Method for authenticating and assuring the integrity of the image is required. Image authentication is possible by embedding a layer of the authentication signature into the digital image using a digital watermark. In some applications tamper localization is also required. Approach: In this study, we proposed a fragile image authentication system with tamper localization in wavelet domain. In this scheme, secret data to be embedded is a logo. Watermark was generated by repeating logo image so that size of watermark matches with the size of HH sub-band of integer wavelet transform. To provide additional level of security, the generated watermark was scrambled using a shared secret key. Integer Haar wavelet transform was applied to obtain wavelet coefficients. Watermark was embedded into the coefficients using odd-even mapping. Results: Experimental results demonstrated that proposed scheme detected and localized tampering at pixel level. Proposed scheme was tested with images of various sizes and tampering of various sizes. It provided good results for tamperings ranges from single pixel to a block of pixels. Conclusion: Watermarking was done in wavelet domain; conventional watermarking attacks were not possible. The resolution of tamper localization was achieved at pixel level. The watermarked image�s quality was still maintained while providing pixel-level tampering accuracy. Proposed scheme can be used in insurance, forensics departments.

A Constitutive Model for Multi-Line Simulation of Granular Material Behavior Using Multi-Plane Pattern

Problem statement: Improper understanding of material behavior prevents the efficient and correct usage of available materials and consequently, increases the construction and maintenance costs and even unsuitable construction. Considering the necessity of exact investigation about material behavior, several researches have been carried out in this field but the majority of these researches did not propose a general method for prediction of granular material behavior. Furthermore, many of the methods proposed by researchers are not able to present the properties such as the orientation of failure mechanism of propagating plasticity in materials. Approach: In this study, a general method was proposed for multi-laminate simulation to predict the behavior of materials. The general applicability of this method for prediction of granular material is one of its significant advantages. The study was carried out in the framework of multi-plane pattern which is able to predict anisotropic behavior, consider the effect of stress and strain axis rotations in plasticity, consider the semi-micro mechanical history and finally predict the orientation of failure mechanism. The method was presented in a matter that there is no limitation for different shapes of stress-strain curves. Results: It was concluded that using this method, fundamental properties of material such as material fracture, orientation of failure, anisotropic behavior of material, separation of behavior in several planes and rotation of principle axis of stress and strain during nonlinear behavior can be determined. Conclusion/Recommendations: This method can be used for complicated material behavior simulation under seismic loading, cyclic loading or fatigue effects. For future works, the method can be extended by increasing the number of planes. Higher-order equations can also be used to have a more accurate approximation of stress-strain curve.

A Policy-Based Admission Control Scheme for Voice over IP Networks

Problem statement: In Voice Over IP (VOIP) network, when more calls are admitted to the network, more voice packet traffic is created. Since bandwidth is always limited, this may result network congestion and/or may affect voice quality. Thus, we needed a mechanism for improving the Quality of Service (QoS) by controlling VOIP calls admission. Approach: Given a specified bandwidth and a constant background data rate, we attempted to explore the effect of Open Window and Leaky Bucket admission schemes on VoIP calls quality. These policy-based admission controls were simulated using NS-2 Simulator. The inter-arrival time distribution for the network background data traffic was assumed to be deterministic with a Constant Bit Rate (CBR). Voice packets traffic inter-arrival time is assumed to have an exponential distribution. Each voice call has a rate of 64 kbps for duration of 120 min. Results: Various performance measures of VoIP calls and packet traffic were evaluated including: packet loss, packet drop rate, delay, jitter and call rejection rate. Performance results of the experiment are summarized in a power ratio index which presented the impact of a collection of performance parameters on VoIP service quality. Conclusion: Implementing a policy based admission scheme on VoIP network will improve its QoS and the degree of improvement depends on the network setting parameters. If threshold rate for call admission is set above network ceiling bandwidth, leaky bucket will result a higher and unacceptable jitter. Overall, leaky bucket scheme was considered inferior when compared to open window for improving QoS of VoIP.

Application of a Database in the Monitoring of Workstations in a Local Area Network

Problem statement: Computer hardware fault management and repairs can be a big challenge, especially if the number of staff available for the job is small. The task becomes more complicated if remote sites are managed and an engineer or technician has to be dispatched. Approach: Availability of relevant information when needed could ease the burden of maintenance by removing uncertainties. Such required information could be accumulated in a database and accessed as needed. Results: This study considered such a database, to assist a third party hardware maintenance firm keep track of its operations, including the machines that it services, together with their owners. A software application was developed in Java programming language, in the form of a database, using Microsoft Access as the database management system. It was designed to run on a local area network and to allow remote workstations to log on to a central computer in a client/server configuration. With this application it was possible to enter fault reports into the database residing on the central computer from any workstation on the network. Conclusion/Recommendations: The information generated from this data can be used by the third party hardware maintenance firm to speed up its service delivery, thus putting the firm in a position to render more responsive and efficient service to the customers.

Boosting Kernel Discriminative Common Vectors for Face Recognition

Problem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the feature selection and the classifier training were conducted by KDCV and AdaBoost.M2 respectively. To reduce the dependency between classifier outputs and to speed up the learning, each classifier was trained in the different feature space which was obtained by applying KDCV to a small set of hard-to-classify training samples. The proposed method BKDCV possessed several appealing properties. First, like all Kernel methods, it handled non-linearity in a disciplined manner. Second by introducing pair-wise class discriminant information into discriminant criterion, it further increased the classification accuracy. Third, by calculating significant discriminant information, within class scatter space, it also effectively contracted with the small sample size problem. Fourth, it constituted a strong ensemble based KDCV framework by taking advantage of boosting and KDCV techniques. Conclusion: This new method was applied on extended Yale B face database and achieves better classification accuracy. Experimental results demonstrated the promising performance of the proposed method as compared to the other methods.

Statistical Part-of-Speech Tagger for Traditional Arabic Texts

Problem statement: This study presented the development of an Arabic part-of-speech tagger that can be used for analyzing and annotating traditional Arabic texts, especially the Quran text. Approach: It is a part of a project related to the computerization of the Holy Quran. One of the main objectives in this project was to build a textual corpus of the Holy Quran. Results: Since an appropriate textual version of the Holy Quran was prepared and morphologically analyzed in other stages of this project, we focused in this work on its annotation by developing and using an appropriate tagger. The developed tagger employed an approach that combines morphological analysis with Hidden Markov Models (HMMs) based-on the Arabic sentence structure. The morphological analysis is used to reduce the size of the tags lexicon by segmenting Arabic words in their prefixes, stems and suffixes; this is due to the fact that Arabic is a derivational language. On another hand, HMM is used to represent the Arabic sentence structure in order to take into account the linguistic combinations. For these purposes, an appropriate tagging system has been proposed to represent the main Arabic part of speech in a hierarchical manner allowing an easy expansion whenever it is needed. Each tag in this system is used to represent a possible state of the HMM and the transitions between tags (states) are governed by the syntax of the sentence. A corpus of some traditional texts, extracted from Books of third century (Hijri), is manually morphologically analyzed and tagged using our developed tagset. Conclusion/Recommendations: It is then used for training and testing this model. Experiments conducted on this dataset gave a recognition rate of about 96% and thus are very promising compared to the data size tagged till now and used in the training. Since our Holy Quran corpus is still under revision, we did not make significant experiments on it. However, preliminary tests conducted on the seven verses of AL-Fatiha showed an encouraging accuracy rate.

A Performance Study of Reactive Multicast Routing Protocols in Virtual Class Room Using Mobile Ad Hoc Network

Problem statement: A great deal of excitement has recently propelled Mobile Learning to the forefront of educational technology. The exponential growth of mobile technology in the recent years, increase in the availability of high-bandwidth network, advances in wireless technologies and popularity of handheld devices, have opened up new accessibility opportunities for education. Approach: Virtual class room using MANET had been proposed to enhance the m-Learning opportunities in a residential institution. Results: This environment transferred both large and small volume of data to the particular group members. Generally multicasting supports group oriented computing. Such a group oriented service required a suitable multicast routing protocol. Two standard multicast routing protocols were implemented and analyzed for tree (MAODV) and mesh (ODMRP) based approach. The performances of group learning module of VCR had been analyzed using MAODV and ODMRP routing protocols for parameters such as network traffic, the node speed and the network area. Conclusion/Recommendations: Our results showed that many scenarios in VCR environment, MAODV achieved a higher packet delivery ratio than ODMRP.

Enhanced Utility Accrual Scheduling Algorithms for Adaptive Real Time System

Problem statement: This study proposed two utility accrual real time scheduling algorithms named as Preemptive Utility Accrual Scheduling (PUAS) and Non-preemptive Utility Accrual Scheduling (NUAS) algorithms. These algorithms addressed the unnecessary abortion problem that was identified in the existing algorithm known as General Utility Scheduling (GUS). It is observed that GUS is inefficient for independent task model because it simply aborts any task that currently executing a resource with lower utility when a new task with higher utility requests the resource. The scheduling optimality criteria are based on maximizing accrued utility accumulated from execution of all tasks in the system. These criteria are named as Utility Accrual (UA). The UA scheduling algorithms are design for adaptive real time system environment where deadline misses are tolerable and do not have great consequences to the system. Approach: We eliminated the scheduling decision to abort a task in GUS and proposed to preempt a task instead of being aborted if the task is preemptive able. We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. This is followed by the NUAS and GUS algorithms. Conclusion: Simulation results revealed that the proposed algorithms were more efficient than the existing algorithm, producing with higher accrued utility ratio and less abortion ratio making it more suitable and efficient for real time application domain.

An Improved Lazy Release Consistency Model

Problem statement: A network of workstations, viewed as a distributed shared memory system can be used to develop and test parallel algorithms. Approach: For implementing parallel algorithms on such DSMs shared memory consistency model plays a vital role. Results: However on a LAN, strict consistency models like Sequential Consistency model (SC) are not useful since the communication is slow. In such environments relaxed models like Entry Consistency (EC), Release Consistency (RC) or their variations such as Lazy Release Consistency (LRC) are generally used. Conclusion/Recommendations: In this study an Improved Lazy Release Consistency (ILRC) model is proposed. This model is studied with standard parallel algorithms. In many cases the ILRC model is proved to work better than the LRC model.

Fixed Representative Colors Feature Extraction Algorithm for Moving Picture Experts Group-7 Dominant Color Descriptor

Problem statement: MPEG-7 has defined a set of color descriptors for the multimedia contents; one of these descriptors is the Dominant Color Descriptor (DCD). The DCD adopted the Generalized Lloyd Algorithm (GLA) as a feature extraction technique. However, using this algorithm in image retrieval systems may produce perceptually irrelevant images in the ranked results. Approach: In this study, we proposed a new technique for the extraction of the DCD called Fixed Representative Colors Feature Extraction Algorithm (FRCFE). This technique is based on converting the original image colors to a set of predefined colors in the RGB color space. Also, we developed an image retrieval system to measure the effectives of this technique. Results: Experimental results revealed that FRCFE provides better accurate and perceptually relevant image retrieval for the MPEG-7 DCD than GLA in the chosen dataset. Conclusion: Mapping the original image colors to a set of predefined colors preserved the main features of the image and can produce more accurate results when used in image retrieval systems.

Unbalance Quantitative Structure Activity Relationship Problem Reduction in Drug Design

Problem statement: Activities of drug molecules can be predicted by Quantitative Structure Activity Relationship (QSAR) models, which overcome the disadvantage of high cost and long cycle by employing traditional experimental methods. With the fact that number of drug molecules with positive activity is rather fewer than that with negatives, it is important to predict molecular activities considering such an unbalanced situation. Approach: Asymmetric bagging and feature selection was introduced into the problem and Asymmetric Bagging of Support Vector Machines (AB-SVM) was proposed on predicting drug activities to treat unbalanced problem. At the same time, features extracted from structures of drug molecules affected prediction accuracy of QSAR models. Hybrid algorithm named SPRAG was proposed, which applied an embedded feature selection method to remove redundant and irrelevant features for AB-SVM. Results: Numerical experimental results on a data set of molecular activities showed that AB-SVM improved AUC and sensitivity values of molecular activities and SPRAG with feature selection further helps to improve prediction ability. Conclusion: Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which could be furthermore improved by performing feature selection to select relevant features from the drug.

Load Allocation Model for Scheduling Divisible Data Grid Applications

Problem statement: In many data grid applications, data can be decomposed into multiple independent sub-datasets and distributed for parallel execution and analysis. Approach: This property had been successfully employed by using Divisible Load Theory (DLT), which had been proved as a powerful tool for modeling divisible load problems in data-intensive grid. Results: There were some scheduling models had been studied but no optimal solution has been reached due to the heterogeneity of the grids. This study proposed a new optimal load allocation based on DLT model recursive numerical closed form solutions are derived to find the optimal workload assigned to the processing nodes. Conclusion/Recommendations: Experimental results showed that the proposed model obtained better solution than other models (almost optimal) in terms of Makespan.

Economic Efficiency Analysis for Information Technology in Developing Countries

Problem statement: The introduction of Information Technology (IT) to government institutions in developing countries bears a great deal of risk of failure. The lack of qualified personnel, lack of financial support and the lack of planning and proper justification are just few of the causes of projects failure. Study presented in this study focused on the justification issue of IT projects through the application of Cost Benefit Analysis (CBA) as part of a comprehensive Economic Efficiency Analysis (EEA) of IT Projects, thus providing management with a decision making tool which highlights existing and future problems and reduces the risk of failure. Approach: Cost-Benefit Analysis (CBA) based on Economic Efficiency Analysis (EEA) was performed on selected IT projects from ministries and key institutions in the government of Jordan using a well established approach employed by the Federal Government of Germany (KBSt approach). The approach was then modified and refined to suit the needs of developing countries so that it captured all the relevant elements of cost and benefits both quantitatively and qualitatively and includes a set of guidelines for data collection strategy. Results: When IT projects were evaluated using CBA, most cases yielded negative Net Present Value (NPV), even though, some cases showed some reduction in operation cost starting from the third year of project life. However, when the CBA was applied as a part of a comprehensive EEA by introducing qualitative aspects and urgency criteria, proper justification for new projects became feasible. Conclusion: The modified EEA represented a systematic approach which was well suited for the government of Jordan as a developing country. This approach was capable of dealing with the justification issue, evaluation of existing systems and the urgency of replacing legacy systems. This study explored many of the challenges and inherited problems existing in the public sectors of developing countries which can not simply be resolved by the introduction of IT projects, but rather require more comprehensive solutions.

Job Type Approach for Deciding Job Scheduling in Grid Computing Systems

Problem statement: Meta-scheduling has become very important due to the increased number of submitted jobs for execution. Approach: We considered the job type in the scheduling decision that was not considered previously. Each job can be categorized into two types namely, data-intensive and computational-intensive in a specific ratio. Job ratio reflected the exact level of the job type in two specific numbers in the form of ratio and was computed to match the appropriate sites for the jobs in order to decrease the job turnaround time. Moreover, the number of jobs in the queue was considered in the batch decision to ensure server-load balancing. Results: The new factor that we considered namely, the job ratio can reduce the job turnaround time by submitting jobs in batches rather than submitting the jobs one by one. Conclusion: Our proposed system can be implemented in any middleware to provide job scheduling service.

Analyzing the Peer to Peer Traffic Aggregation Using an Optimized Method

Problem statement: In the recent years, peer to peer networks have rapidly developed in the distributed and decentralized world of internet. Current research indicated that P2P applications were responsible for a substantial part of Internet traffic. Number of users embracing new P2P technology is also increasing fast. It is therefore important to understand the impact of the new P2P services on the existing Internet infrastructure and on legacy applications. The majority of unidentified traffic originates from Peer-to-Peer (P2P) applications like Napster, Gnuttella. Identification of P2P traffic seem to fail because their existence by using arbitrary ports. Approach: Proposed scheme concentrated on the factors and characteristics of P2P communications with payload issues on P2P application based on network traffic collection. The method used here was based on a set of heuristics derived from the robust properties of P2P traffic. Results: System demonstrated the method with current traffic data obtained from internet service providers. It had been found that flow sizes Vs holding times, behavior of P2P users Vs total active users were also analyzed and results of a heavy-tail analysis were described. Finally, system discussed the popularity distribution properties of P2P applications. Conclusion/Recommendations: This study suggested a very interesting and important result from a traffic dimensioning point of view: The ratio of active users and total users is almost constant. Results showed that unique properties of P2P application traffic seem to fade away during aggregation and characteristics of traffic will be similar to that of other non-P2P traffic aggregation.

Performance Evaluation of Stable Weight-Based on Demand Routing Protocol for Mobile Ad Hoc Network

Problem statement: A MANET is an autonomous collection of mobile users that communicate over relatively bandwidth constrained wireless links. Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. Approach: A Stable Weight-based On demand Routing Protocol (SWORP) that uses the weight-based route strategy to select a stable route was created by Wang. But SWORP only evaluated in a limited setting of simulation, more simulation parameter have to test with SWORP to evaluate how far this protocol can go on. In this project, SWORP was implemented in simulation environment with two other routing protocols, AODV and DSR. Results: These three protocols were implemented in Network Simulator 2 (NS2) and the performance was compare with performance metrics, end-to-end delay, number of packet drop and packet delivery ratio. Conclusion: As expected, SWORP had outperformed AODV and DSR in the overall routing performance.

A Hybrid Architecture Approach for Quantum Algorithms

Problem statement: In this study, a general plan of hybrid architecture for quantum algorithms is proposed. Approach: Analysis of the quantum algorithms shows that these algorithms were hybrid with two parts. First, the relationship of classical and quantum parts of the hybrid algorithms was extracted. Then a general plan of hybrid structure was designed. Results: This plan was illustrated the hybrid architecture and the relationship of classical and quantum parts of the algorithms. This general plan was used to increase implementation performance of quantum algorithms. Conclusion/Recommendations: Moreover, simulation results of quantum algorithms on the hybrid architecture proved that quantum algorithms can be implemented on the general plan as well.

Initial Hybrid Method for Analyzing Software Estimation, Benchmarking and Risk Assessment Using Design of Software

Problem statement: Estimation models in software engineering are used to predict some important attributes of future entities such as development effort, software reliability and programmers productivity. Among these models, those estimating software effort have motivated considerable research in recent years. Approach: In this study we discussed an available work on the effort estimation methods and also proposed a hybrid method for effort estimation process. As an initial approach to hybrid technology, we developed a simple approach to SEE based on use case models: The �use case point�s method�. This method is not new, but has not become popular although it is easy to understand and implement. We therefore investigated this promising method, which was inspired by function points analysis. Results: Reliable estimates can be calculated by using our method in a short time with the aid of a spreadsheet. Conclusion: We are planning to extend its applicability to estimate risk and benchmarking measures.

A Genetic Algorithm for the Segmentation of Known Touching Objects

Problem statement: Segmentation is the first and fundamental step in the process of computer vision and object classification. However, complicate or similar colour pattern add complexity to the segmentation of touching objects. The objective of this study was to develop a robust technique for the automatic segmentation and classification of touching plastic bottles, whose features were previously stored in a database. Approach: Our technique was based on the possibility to separate the two objects by means of a segment of straight line, whose position was determined by a genetic approach. The initial population of the genetic algorithm was heuristically determined among a large set of cutting lines, while further generations were selected based on the likelihood of the two objects with the images stored in the database. Results: Extensive testing, which was performed on random couples out of a population of 50 bottles, showed that the correct segmentation could be achieved in success rates above 90% with only a limited number of both chromosomes and iterations, thus reducing the computing time. Conclusion: These findings proved the effectiveness of our method as far as touching plastic bottles are concerned. This technique, being absolutely general, can be extended to any situation in which the properties of single objects were previously stored in a database.

A New Approach of Adaptive Network-based Fuzzy Inference System Modeling in Laser Processing-A Graphical User Interface Based

Problem statement: The power of Artificial Intelligent (AI) becomes more authoritative when the system is programmed to cater the need of complex applications. MATLAB 2007B, integrating artificial intelligent system and Graphical User Interface (GUI) has reduced researchers� fear-to-model factor due to unfamiliarity and phobia to produce program codes. Approach: In this study, how GUI was developed on Matlab to model laser machining process using Adaptive Network-based Fuzzy Inference System (ANFIS) was presented. Laser cutting machine is widely known for having the most number of controllable parameters among the advanced machine tools, hence become more difficult to engineer the process into desired responses; surface roughness and kerf width. Mastering both laser processing and ANFIS programming are difficult task for most researchers, especially for the difficult to model processes. Therefore, a new approach was ventured, where GUI was developed using MATLAB integrating ANFIS variables to model the laser processing phenomenon, in which the numeric and graphical output can be easily printed to interpret the results. Results: To investigate ANFIS variables� characteristic and effect, error was analyzed via Root Mean Square Error (RMSE) and Average Percentage Error (APE). The RMSE values were then compared among various trained variables and settings to finalize best ANFIS predictive model. The results found was very promising and proved that, even a person with shallow knowledge in both artificial intelligence and laser processing can actually train the experimental data sets loaded into GUI, test and optimize ANFIS variables to make comparative analysis. Conclusion: The details of modeled work with prediction accuracy according to variable combinations were premeditated on another paper. The findings were expected to benefit precision machining industries in reducing their down time and cost as compared to the traditional way of trial and error method.

Graphical Browsing of Email Data: A Usability Based Comparative Study

Problem statement: With the rapid growth of the number of email messages and the diverse use of email, people have become overwhelmed by the large volumes of email archives. As a result, email tools that facilitate the browsing of email messages are highly required. This study described an empirical study that aimed to investigate whether the usability of email client can be improved by incorporating graphical visualization techniques to browse email data. Approach: Two email visualization approaches, called LinearVis and MatrixVis, were developed for this empirical study which presented email messages based on a dateline together with other email information. The usability of each approach was compared to atypical email tool in terms of locating messages. Results: The results demonstrated that LinearVis was the most usable email approach in terms of browsing email messages whereas MatrixVis was found to be the least usable email condition. Conclusion: The results showed that usability of email clients can be significantly improved by presenting graphically email messages with only a small volume of hidden email data. Results also indicated that usability of the graphical representations, that hide large volume of email data, can be negatively affected.

A Survey of Compute Intensive Algorithms for Ribo Nucleic Acids Structural Detection

Problem statement: Finding an accurate RNA structural alignment from primary sequence due to it is time consuming and computationally NP-hard problem is a major bioinformatics challenge. According to our investigation majority of current researches were concerned on achieving faster execution time, improving space complexity and better cache management. Recently one research introduced cache-efficient Chip Multiprocessor (CMP) algorithms with good speed-up to exploit parallelism in detection the critical path length. Our contribution in this article was a comprehensive survey of methods for solving RNA secondary structure prediction with Pseudoknots (PK) and sequence alignment in bioinformatics. The aim was to highlight the challenges related issues which would provide sufficient information to assist the new coming researchers in this field as well as a good reference guide for bioinformatics professionals. Approach: We computed various algorithms that predicted an RNA molecules secondary structure from primary sequence, without pseudoknots from one side and pseudoknotted RNA secondary structure in the other side. Furthermore, we also reviewed and compared in two tables the methods that developed for RNA structural predictions. Results: Our findings of this survey confirmed that Dynamic Programming (DP) method via CMP algorithms can be used to predict the RNA secondary structure with simple PK and it gives good results. Conclusion: The methods for predicting RNA's structural are coming in two groups: Firstly, pseudoknotted RNA structural problem is computationally complex and secondly, common methods significantly gave not accurate enough results for predicting pseudoknotted RNA.

Integer Factorization: Solution via Algorithm for Constrained Discrete Logarithm Problem

Problem statement: During the last thirty years many public-key cryptographic protocols based on either the complexity of integer factorization of large semiprimes or the Discrete Logarithm Problem (DLP) have been developed. Approach: Although several factorization algorithms with sub-exponential complexity had been discovered, the recent RSA factoring challenge demonstrated that it was still necessary to use several thousand computers working in a coordinated effort for several months to factor an integer n that was a product of two primes. Results: In this study it was demonstrated how to find integer factors of n using an algorithm for a constrained DLP. Several numerical examples illustrate details of the algorithms. One of these algorithms has O(³√n) complexity; and, if the search was balanced, it has complexity O(n^1/3/log^1/αn), where alpha>1. Conclusion/Recommendations: A specific algorithm is a method that after a finite number of well-defined and executable steps provably delivers a solution to a class of problems.

Utility Independent Privacy Preserving Data Mining on Vertically Partitioned Data

Problem statement: Driven by mutual benefits, or by regulations that require certain data to be published, there has been a demand for the exchange and publication of data among various parties. Data publishing has been ubiquitous in many domains such as medical, business and education. Detailed person-specific data, present in the centralized server or in the distributed environment, in its original form often contains sensitive information about individuals, and publishing such data immediately violates individual privacy. The main problem in this regard is to develop method for publishing data in a more hostile environment so that the published data remains practically useful while individual privacy is preserved. There are n parties, each having a private database, want to jointly conduct a data mining operation on the union of their databases. How could these parties accomplish this without disclosing their database to the other parties or any third party? Approach: To address this issue, we developed a simple technique of transforming the categorical and numeric sensitive data using a mapping table and graded grouping technique, respectively. The typical data mining tasks such as classification, clustering and association rule mining were performed on both the original and transformed tables. The rules/results/patterns of both the tables were compared and the utility of the transformed data was evaluated. Results: The evaluation results demonstrated that the proposed approach was able to achieve cent percent utility for any type of mining task as compared to the original table. The classification accuracy of Adult data set obtained, with education as class variable was 40.08% and the same accuracy was obtained even after transformation. Similarly the number of rules generated for the given confidence 0.9, was the same for both the original and transformed table and equal to 10. Conclusion: The association rules involving categorical sensitive attributes were checked manually for privacy breach. We found that it is not possible to guess the actual sensitive values from the rules, even though there was no information loss. The results can be interpreted only with the concern of data owner or data publisher.

A Platform to Develop a Secure Instant Messaging Using Jabber Protocol

Problem statement: Open Source technologies are interesting in that they allow free experimentation and integration by anyone and anywhere. A Jabber user can control presence with very little effort. Another user, regardless of external platform, must subscribe to your presence. You have the choice of rejecting or accepting the subscription at the time it is submitted. Approach: Other applications of this system were yet to be discovered. Jabber is a work in progress; the community learns and creates applications of the protocol/platform on an almost daily basis. This study aimed to implement a security algorithm for developed instant messaging. Results: The objective was to make sure that flow of data from client application or computer is not tapped by a hacker and also to make it difficult for a network data sniffer to explore the situation. In this study there were many aspects must be understood such as: Jabber protocol, programming language and security aspect. For this reason it was proposed to develop a new secure connection and makes sure that the connection between clients and server is safe and secure when the instant massage had been transferred using jabber protocol. Conclusion/Recommendations: To develop a new secure connection for instance message using jabber protocol or other names, the Extensible messaging and presence protocol had been used. To make it secure the open secure socket layer will be used for general-purpose encryption. In this study the methodology used to solve security threats like: The ability to control access to IM applications, audit and archive IM conversation, the ability to lockout unauthorized IM and peer-to-peer file sharing connections and Encryption.

Genome Sequence Analysis: A Survey

Problem statement: Sequence analysis problems are NP hard and need optimal solutions. Interesting problems include duplicate sequence detection, sequence matching by relevance, sequence analysis using approximate comparison in general or using tools i.e., Matlab and multi-lingual sequence analysis. The usefulness of these operations is highlighted and future expectations are described. Approach: This study described the concepts, tools, methodologies, algorithms being used for sequence analysis. The sequences contained precious information that needed to be mined for useful purposes. There was high concentration required to model the optimal solution. The similarity and alignments concepts can not be addressed directly with one technique or algorithm, a better performance was achieved by the comprehension of different concepts. Results: We had compared different approaches using exemplary data and found that ClustalW2 is fairly good tool in terms of analysis. We assigned different weight values for relevant features and obtained score 95 in comparison phenomenon and 45 in alignment. Conclusion: Different techniques and approaches had been evaluated and compared.

Bluetooth Wireless Network Authentication Using Radio Frequency Communication Protocol
Problem statement: Bluetooth has emerged as very popular ad hoc network standard today. Bluetooth network applications include wireless synchronization, e-mail/internet/intranet access using local personal computer connections, hidden computing through automated applications and networking. Due to this ability, it is not impossible for the network to receive any attack. Approach: In this study, we developed an algorithm to build new software that secures connections between two Bluetooth platforms, which included authentication, authorization and confidentiality. There is no authentication when using the protocol in connecting the Bluetooth platform. When there is no security, so that all users can directly connect to the server without any permission because n most of the application nowadays that refers to RFCOMM protocol is not. Results: The test environment for the non-secure connections is also being setting up before build the software. The purpose of this study was to build a secured Bluetooth application in connecting Bluetooth Platform using Radio Frequency Communication (RFCOMM) protocol. Conclusion: Furthermore focusing on setting up the test environment for a non-secure connection application.

Bluetooth Wireless Network Authentication Using Radio Frequency Communication Protocol
Problem statement: Bluetooth has emerged as very popular ad hoc network standard today. Bluetooth network applications include wireless synchronization, e-mail/internet/intranet access using local personal computer connections, hidden computing through automated applications and networking. Due to this ability, it is not impossible for the network to receive any attack. Approach: In this study, we developed an algorithm to build new software that secures connections between two Bluetooth platforms, which included authentication, authorization and confidentiality. There is no authentication when using the protocol in connecting the Bluetooth platform. When there is no security, so that all users can directly connect to the server without any permission because n most of the application nowadays that refers to RFCOMM protocol is not. Results: The test environment for the non-secure connections is also being setting up before build the software. The purpose of this study was to build a secured Bluetooth application in connecting Bluetooth Platform using Radio Frequency Communication (RFCOMM) protocol. Conclusion: Furthermore focusing on setting up the test environment for a non-secure connection application.

Utility-Based Policy Management System for Virtual Organization
Problem statement: Policy issues have become a challenge within Virtual Organizations (VOs) that integrate participants and resources, spanning multiple physical institutions. Each of the VO classes has different goals that hope to be achieved by providing policies. The main question in this regard is that �how such policies can help the entire VO participants achieve their goals�. Approach: As a first step to address this question, we developed and evaluated a policy management framework within a specialized context, namely Utility based Policy Management System (U-PMS). We proposed an approach for policy federation, in which a group of VO participants agreed to adopt common standards to provide a common infrastructure that unifies the way the policies were applied in VO. Results: The evaluation results demonstrated that the proposed approach was able to manage VO policies and achieve higher utility for VO participant through its management functions. It outperforms the related system by 9.99% for acceptance function and 5.77% for conflict resolution and 4.65% for policy merging. Conclusion: We observed that the utility of VO participants� can be improved through managing the applied polices in VO.

Throughput-Delay Trade-Off for Slotted Aloha Multiple Access with Capture Effect
Problem statement: Medium Access Control (MAC) protocols are one of most important research issues in communication and networking. There have been proposed several MAC protocols in wireless as well in wired networks. Approach: ALOHA-based protocol is the simplest one, being able to provide prompt access, reliable channels and support for quality of service. However its limited capacity, low throughput and excessive delays make it not suitable for several applications. Results: So there had been many efforts devoted to increase its performance, one of them is the capture effect. With capture effect, the packets arriving with the highest power had a good chance to be detected accurately, even when other packets were present. Conclusion: In this study, a throughput-delay trade-off was investigated to improve the network performance. The capture threshold was assigned to the highest throughout/time delay ratio. Therefore, the capture threshold which provided a high throughput and low time delay was selected by a central node.

Computer-Aided Design Data Extraction Approach to Identify Product Information
Problem statement: Many approaches have been proposed in previous such as AUTOFEAT algorithm, feature recognition, Intelligent Feature Recognition Methodology (IFRM), a part recognition algorithm and graph theory-based approach in order to solve the integration issue between CAD and CAM. However, there is no direct connection from CAD database and machine database. Therefore, comparison among the approaches has been conducted because to recognize the suitable approach is the importance tasks before this research can be proceed for the next stage. Approach: This study focused on CAD data extraction approach to identify product information. CAD data referred as Computer-Aided Design (CAD) data extracted from the CAD drawing which contained the drawing of product that be produce by manufacturing. CAD data consisted of geometric and non-geometric data. Geometric data contained lines, curves and vertex. While non-geometric data include texts, colors and layers. The extracted CAD data were needed to generate the product information which is useful information for the machine in production field to produce the product for the manufacturing same as depicted in the CAD drawing. Basically, the product information consisted of product details such as length, thickness, wideness and radius of the product, processes information for the machine to process the product such as taper, cutting, drilling and punching. In addition, product information also contained type of materials for the product. Results: As a result, feature recognition is the most suitable approach can be applied for this research. Thus, the approach was selected to precede the next stage. Conclusion: Conclusion from the comparison among the approaches is in term of accuracy of extracted data is not accurate when the drawing is incomplete drawing or contains the noise such as unwanted lines or any shapes cross the object in the drawing.

An Efficient Method for Fetal Electrocardiogram Extraction from the Abdominal Electrocardiogram Signal
Problem statement: FECG (Fetal Electrocardiogram) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labor. Approach: Conventional techniques were often unable to achieve the extraction of FECG from the Abdominal ECG (AECG) in satisfactorily level. A new methodology by combining the Artificial Neural Network (ANN) and Correlation (ANNC) approach had been proposed in this study. Results: The accuracy of the proposed method for FECG extraction from the AECG signal was about 100% and the performance of the method for FHR extraction is 93.75%. Conclusions/Recommendations: The proposed approach involved the FECG extraction even though the MECG and FECG are overlapped in the AECG signal so that the physician and clinician can make the correct decision for the well-being of the fetus and mother during the pregnancy period.

Accelerated Search for Gaussian Generator Based on Triple Prime Integers
Problem statement: Modern cryptographic algorithms are based on complexity of two problems: Integer factorization of real integers and a Discrete Logarithm Problem (DLP). Approach: The latter problem is even more complicated in the domain of complex integers, where Public Key Cryptosystems (PKC) had an advantage over analogous encryption-decryption protocols in arithmetic of real integers modulo p: The former PKC have quadratic cycles of order O (p²) while the latter PKC had linear cycles of order O(p). Results: An accelerated non-deterministic search algorithm for a primitive root (generator) in a domain of complex integers modulo triple prime p was provided in this study. It showed the properties of triple primes, the frequencies of their occurrence on a specified interval and analyzed the efficiency of the proposed algorithm. Conclusion: Numerous computer experiments and their analysis indicated that three trials were sufficient on average to find a Gaussian generator.

Memory Tracing
Problem statement: Students completing introductory computing courses did not know how to program at the expected level. Seeking the underlying problem, we came to believe that students were focusing only on results and not connecting with the inner workings of their code. This left them poorly prepared to master increasingly complex problems. Approach: We hoped that by promoting memory tracing as a core competence as early as possible in introductory programming courses we would hone the understanding and skills of our students and improve their chances for succeeding in computer science. We emphasized a basic and manual approach to memory tracing--in the classroom, in conjunction with homework assignments and on exams--to help our students gain the ability to write good programs, test them and, should it become necessary, debug them. Results: Having received gratifying results from our approach in our own classes, we had moved to get the word out as quickly as possible to motivate other educators to implement it. We described how we derived benefit from memory tracing in the various contexts and we presented the details of our method for teaching students how to best use this technique. Conclusion/Recommendations: Training students early on to actively carry out a manual memory trace of programs (as opposed to relying on debuggers or print statements) will help them develop their coding skill and comfort, quite apart from any facility for finding and fixing errors. Although experienced programmers trace intuitively, beginning students do not; they need to be trained. Therefore we felt that tracing should be an explicit, emphasized component of the introductory courses.

Information Extraction from Hypertext Mark-Up Language Web Pages

TCP Optimal Performance in Wireless Networks Applications

Distributed Clusterhead Architecture for Mobile Ad Hoc Networks

Analytic Performability Model of Vertical Handoff in Wireless Networks
Problem statement: The next generation wireless systems should be designed to support heterogeneous traffic with seamless mobility. A single network alone cannot cope up with such heterogeneous requirements. Hence it is desirable to interoperate between diverse and complementary Radio Access Technologies (RATs). In such system, user will switch between different Radio Access Technologies (RATs) to satisfy the User/application requirement and this process is known as Vertical Handoff (VHO). The process of network switching had three phases, network discovery, handoff decision and execution. The decision phase played a crucial role in resource utilization and user/application Quality of Service (QoS) requirement. Hence it was essential to model and evaluate the handoff decision system along with VHO system model. Approach: The traditional performance models were optimistic models and would evaluate the system performance under ideal condition by ignoring failures and recovery in the system. The availability models were conservative models and would assess the availability/reliability of the system. The performabality models were combined models of performance and reliability. The performablity models were more realistic models of the system due to the simultaneous consideration of performance and reliability. Here the VHO process of a next generation wireless system was modeled and evaluated by an analytic performablity model and performance of decision system is evaluated through the sensitivity analysis of VHO decision parameter. Results: In VHO performance evaluation, the metrics of performance evaluation are handoff dropping probability and new call blocking probability. The dynamics of these metrics are depends on set of wireless network parameter such as Available Bandwidth (ABW), users, Bit Error Rate (BER) and network traffic. The ABW, BER and network traffic is also parameter for VHO decisions. The results of performance evaluation are used to develop a novel intelligent vertical handoff decision technique to achieve optimum tradeoff between set of handoff decision criteria. Finally, sensitivity analysis of system parameters on four traffic classes and two vertical handoff decision algorithms along with intelligent vertical handoff decision method were presented. Conclusion: The results of sensitivity analysis depicted that the VHO process in next generation wireless system needs intelligent criteria based technique at the decision making phase of VHO process.

Novel Method of the Combination of Forecasts Based on Rough Sets
Problem statement: A study in Analytic Hierarchy Process (AHP) had shown the problem of quantify the qualitative and the side Combined. Approach: So that problems were better resolved. The rough sets theory and AHP was introduced in the study, furthermore, these were united to create a completely new method of combination forecasts. Results: The results of numerical examples were shown to illustrate the interval AHP models reflecting the uncertainty of evaluations in nature. Conclusion: Therefore our method can be analyzed in order to make the best decision-making and makes combination forecast more objective. Further, the proposed procedure generates a set of easily understood rules that can be readily applied in knowledge-based.

Strengthening of Corrosion-Damaged Reinforced Concrete Beams with Glass Fiber Reinforced Polymer Laminates
Problem statement: This study showed the results of an experimental investigation on the strengthening of corrosion damaged reinforced concrete beams with unidirectional cloth glass fiber reinforced polymer (UDCGFRP) laminates. Approach: All the beam specimens 1502503000 mm were cast and tested for the present investigation. One beam specimen was neither corroded nor strengthened to serve as a reference. Two beams were corroded to serve as a corroded control. A reinforcement mass loss of approximately 10 and 25% were used to define medium and severe degrees of corrosion. The remaining two beams corroded and strengthened with GFRP. Results: The test parameters included first crack load, first crack deflection, yield load, yield deflection, service load, service deflection, ultimate load and ultimate deflection. Based on the results it was found that GFRP Laminates had beneficial effects even at the corrosion-damaged stage. Conclusion/Recommendations: The UDCGFRP laminated beams showed distinct enhancement in ultimate strength and ductility by 72.37 and 49.49% respectively.

Digital Recognition using Neural Network
Problem statement: Handwriting number recognition is a challenging problem researchers had been research into this area for so long especially in the recent years. In our study there are many fields concern with numbers, for example, checks in banks or recognizing numbers in car plates, the subject of digit recognition appears. A system for recognizing isolated digits may be as an approach for dealing with such application. In other words, to let the computer understand the Arabic numbers that is written manually by users and views them according to the computer process. Scientists and engineers with interests in image processing and pattern recognition have developed various approaches to deal with handwriting number recognition problems such as, minimum distance, decision tree and statistics. Approach: The main objective for our system was to recognize isolated Arabic digits exist in different applications. For example, different users had their own handwriting styles where here the main challenge falls to let computer system understand these different handwriting styles and recognize them as standard writing. Result: We presented a system for dealing with such problem. The system started by acquiring an image containing digits, this image was digitized using some optical devices and after applying some enhancements and modifications to the digits within the image it can be recognized using feed forward back propagation algorithm. The studies were conducted on the Arabic handwriting digits of 10 independent writers who contributed a total of 1300 isolated Arabic digits these digits divided into two data sets: Training 1000 digits, testing 300 digits. An overall accuracy meet using this system was 95% on the test data set used. Conclusion: We developed a system for Arabic handwritten recognition. And we efficiently choose a segmentation method to fit our demands. Our system successfully designs and implement a neural network which efficiently go without demands, after that the system are able to understand the Arabic numbers that was written manually by users.

A Computer Simulation Model for Automated Quantification of Luteinizing Hormone Secretion
Problem statement: An automated software package is developed for quantifying Luteinizing Hormone (LH) release from pituitary gonadotropes in response to short pulses of Gonadotropin-Releasing Hormone (GnRH). Approach: These computer programs were designed to accommodate the release mechanism that consists of three stages, namely; (1) Production of different concentrations of effectors (such as receptor-hormone binds, G protein interactions, inositol 1,4,5-trisphosphate IP3), (2) Release of Ca2+ from the endoplasmic reticulum ER and finally (3) Release of LH through pumping of Ca2+ in and out of the cytosol. Results: The programs were coded in C++ computer language and implemented on Pentium PC. The designed model was intended to help in explaining the characteristics of LH release in response to various duration and different concentrations of GnRH pulses in the presence and absence of external Ca2+. Conclusion: Features of short-term responses were simulated and fairly understood using receptor binding, dimerization, interaction of the dimerized receptor with a G protein, production of an effector that opens voltage sensitive channels in cell membrane and finally opens the Ca2+ channels in the ER and the Ca2+-dependent release of LH. Also, prediction of the varying concentrations of Ca2+ effects and comparison with experimental data was made possible.

Solving the Near-Far Problem in Dynamic Frequency Hopping-Optical Code Division Multiple Access using Power Control
Problem statement: In this study, a distributed power control algorithm is proposed for Dynamic Frequency Hopping Optical-CDMA (DFH-OCDMA) system. Approach: In general, the DFH-OCDMA can support higher number of simultaneous users compared to other OCDMA techniques. However, the performance of such system degrades significantly as the received power does lower than its minimum threshold. Results: This may obviously occur in a DFH-OCDMA network with near-far problem which consist of different fiber lengths among the users, that resulting to unequal power attenuation. The power misdistribution among simultaneous active users at the star coupler would degrade the Bit Error Rate (BER) performance for users whose transmitting signals with longer fiber lengths. In order to solve these problems, we propose an adaptive distributed power control technique for DFH-OCDMA to satisfy the target Signal to Noise Ratio (SNR) for all users. Conclusion: Taking into account the noise effects of Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN) and shot noise, the system can support 100% of users with power control as compared to 33% without power control when the initial transmitted power was -1dBm with 30 simultaneous users.

A Multi-form Multiple Choice Editor Exam Tool Based on HTML Website and Artificial Intelligence Techniques
Problem statement: The educators argue that in the post modern world changes in the nature of work, globalization, the information revaluation and today's social challenges will all impact on educational priorities and thus will require a new mode of assessment. Approach: The objectives of this study were to: (1) Present a novel software package tool to create multiple choice and true/false exam forms. (2) Provide exams key solutions automatically (3) Meet special instructors' needs by allowing to easily incorporating multimedia elements into the exam questions, as well as the word processor editing functions and (4) Save both instructors time and money. Results: The multiform exam can be created randomly from question database or manually with shuffled answers for each question. The tool was built based on website and HTML interface using the multimedia applications, two different languages English/Arabic inserted to be used on the same time, efficient Artificial Intelligence techniques and Algorithms are used. The tool had been designed, implemented and tested by experienced instructors, with the result that efficiency, accountability and saving time improved. Conclusion/Recommendations: The transform from paper to electronic resulted in greatly enhanced user satisfaction. Editor exam tool can be used via internet without the need to download and install it to users machine, its a time saving system when multiple versions of random exams are required. This should highly motivated, instructors and teachers to utilize technology and IT to enhance exams and performance.

Distributed Mutual Exclusion Based on Causal Ordering
Problem statement: Causality among events, more formally the causal ordering relation, is a powerful tool for analyzing and drawing inferences about distributed systems. The knowledge of the causal ordering relation between processes helps designers and the system itself solve a variety of problems in distributed systems. In distributed algorithms design, such knowledge helped ensure fairness and liveness in distributed algorithms, maintained consistent in distributed databases and helped design deadlock-detection algorithm. It also helped to build a checkpoint in failure recovery and detect data inconsistencies in replicated distributed databases. Approach: In this study, we implemented the causal ordering in Suzuki-Kasamis token based algorithm in distributed systems. Suzuki-Kasamis token based algorithm in distributed algorithm that realized mutual exclusion among n processes. Two files sequence numbers were used one to compute the number of requests sent and the other to compute the number of entering in critical section. Results: The causal ordering was guaranteed between requests. If a process Pi requested the critical section before a process Pj, then the process Pi will enter its critical section before the process Pj. Conclusion: The algorithm presented here, assumes that if a request req was sent before a request reqs, then the request req will be satisfied before reqs.

Measuring the Software Product Quality during the Software Development Life-Cycle: An ISO Standards Perspective
Problem statement: The International Organization for Standardization (ISO) published a set of international standards related to the software engineering, such as ISO 12207 and ISO 9126. However, there is a set of cross-references between the two standards. Approach: The ISO 9126 on software product quality and ISO 12207 on software life cycle processes had been analyzed to invistigate the relationships between them and to make a mapping from the ISO 9126 quality characteristics to the ISO 12207 activities and vers versa. Results: This study presented a set of comments and suggestions to improve the ISO 9126. Conclusion: The weaknesses of the cross-references between the two ISO standards had been highlighted. In addition, this study provided a number of comments and suggestions to be taken into account on the next version of the ISO 9126 international standard.

Binary Merge Coding for Lossless Image Data Compression
Problem statement: Image processing applications were drastically increasing over the years. In such a scenario, the fact that, the digital images need huge amounts of disk space seems to be a crippling disadvantage during transmission and storage. So, there arises a need for data compression of images. Approach: This study proposed a novel technique called binary merge coding for lossless compression of images. This method was based on spatial domain of the image and it worked under principle of Inter-pixel redundancy reduction. This technique was taken advantage of repeated values in consecutive pixels positions. For a set of repeated consecutive values only one value was retained. Results: The proposed binary merge coding achieved the compression rate of the brain image was 1.6572479. Comparatively, it is 100% more than the compression rate achieved by standard JPEG. Conclusion/Recommendations: This technique was simple in implementation and required no additional memory area. The experimental results of binary merge coding were compared with standard JPEG and it showed that, the binary merge coding improved compression rate compared to JPEG. The same algorithm can be extending to color images. This algorithm can also used for lossy compression with few modifications.

System Evolving using Ant Colony Optimization Algorithm
Problem statement: The goal of automatic programming system is to create, in an automated way, a computer program that enables a computer to solve a problem. It is difficult to build an automatic programming system: They require carefully designed specification languages and an intimate knowledge base. Determine the relevance of mathematical system theory to the problems of automatic programming and find automatic programming methodology, where a computer program evolved to solve problem by using problem�s input output specifications only. Approach: Problem behavior was described as a finite state automata based on its meaning, also problem�s input-output specifications were described in theoretical manner, based on its input and output trajectories information, then a program was evolved to solve the problem. Different implementation languages can be used without significantly affecting existing problem specification. Evolutionary process adapts ant colony optimization algorithm to find good finite state automata that efficiently satisfies input-output specifications. Results: By moving from state to states, each ant incrementally constructs sub- solution in an iterative process. The algorithm converged to the optimal final solution, by accumulating most effective sub-solutions; main problem will appeared in solving problem with little input-output specifications. Fixed and dynamic input-output specifications were used to mimic chaotic behavior of real world. Conclusion: These results indicated that theoretical bases can enhance efficiency and performance of automatic programming system, leading to an increase in the system productivity and letting the concentrate to be done on problem specification only. Also, the collective behavior emerging from the interaction of the different ants had proved effective in solving problem; finally, in dynamic input-output specification chaos theory, especially �butterfly effect�, can be used to control the sensitivity to initial configuration of trajectory information.

Multimodal Face and Ear Images
Problem statement: The study presented in this study to combined face and ear algorithms as an application of human identification. Biometric system to the detection and identification of human faces and ears developed a multimodal biometric system using eigenfaces and eigenears. Approach: The proposed system used the extracted face and ear images to develop the respective feature spaces via the PCA algorithm called eigenfaces and eigenears, respectively. The proposed system showed promising results than individual face or ear biometrics investigated in the experiments. Results: The final achieve was then used to affirm the person as genuine or an impostor. System was tested on several databases and gave an overall accuracy of 92.24% with FAR of 10% and FRR of 6.1%. Conclusion: The results display if we combined face and ear is a good technique because it offered a high accuracy and security.

Iris Recognition Using Discrete Cosine Transform and Artificial Neural Networks
Problem statement: This study presented an efficient Iris recognition system. Approach: The design used the discrete cosine transform for feature extraction and artificial neural networks for classification. The iris images used in this system were obtained from the CASIA database. Results: A robust system for iris recognition was developed. Conclusion: An iris recognition system that produces very low error rates was successfully designed

Skew Detection and Correction Technique for Arabic Document Images Based on Centre of Gravity
Problem statement: Skew detection and correction is the first step process in the document analysis and understanding processing steps. Correction the skewed scanned document image is very important, because it has a direct effect on the reliability and efficiency of the segmentation and feature extraction stages. The noises and the deviation in the document resolution or types are still the main two challenges facing the Arabic skew detection and correction methods. Approach: The proposed method work involved inscribing the text in the document by an arbitrary polygon and derivation of the baseline from polygon�s centroid. Results: The proposed method was implemented on 150 different scanned Arabic documents, from different sources like journals, textbooks, newspapers and the like in addition to handwritten document, with different resolutions and different fonts and it was obtained an accuracy ratio of 87%. Conclusion: The proposed method was efficient, simple and fast, it was not affected by noise and it was proved their suitability to work with documents with different fonts and documents with different resolutions.

Generic Algorithm with Varying Block Sizes to Improve the Capacity of a Wireless Communications Networks

A Light-Weight Service Discovery Protocol for Ad Hoc Networks

An Approach to Modeling Software Safety in Safety-Critical Systems

An Approach to Modeling Software Safety in Safety-Critical Systems

Improvement of the Simplified Fast Transversal Filter Type Algorithm for Adaptive Filtering

Fuzzy Swarm Based Text Summarization

A Control-Oriented Coverage Metric and its Evaluation for Hardware Designs

Optimal Power Control with Overhearing Avoidance for Wireless Sensor Networks

Optimization of Test Scheduling and Test Access for ITC-02 SOC Benchmark Circuits

Real-Time Connect 4 Game Using Artificial Intelligence

Improved Statistical Speech Segmentation Using Connectionist Approach

A Flexible and Reliable Architecture for Mobile Agent Security

Slantlet Transform for Multispectral Image Fusion

MPLS Based Architecture for Mobility and End-to-End QoS Support in Fourth Generation Mobile Networks

Representation of Polygonal Surfaces as Displaced Subdivision Surfaces

Color Image Reconstruction Using A New R'G'I Model

Optimizing Inventory Using Genetic Algorithm for Efficient Supply Chain Management

Novel Moment Features Extraction for Recognizing Handwritten Arabic Letters

Computer Aided Geometric Modeling of Twist Fiber

Empirical Analysis of Virtual Carrier Sense Flooding Attacks Over Wireless Local Area Network

An Arabic Text-To-Speech System Based on Artificial Neural Networks

Performance Enhancement of Underwater Target Tracking by Fusing Data of Array of Global Positioning System Sonobuoys

Agent Based Grid Resource Discovery with Negotiated Alternate Solution and Non-Functional Requirement Preferences

Selective Flooding Based on Relevant Nearest-Neighbor using Query Feedback and Similarity across Unstructured Peer-to-Peer Networks

Generalization Aspect of Neural Networks on Upgrading Assimilation Structure into Accommodating Scheme

Effective Factors on Iranian Consumers Behavior in Internet Shopping: A Soft Computing Approach

Proof-Carrying Code Based Tool for Secure Information Flow of Assembly Programs

Verifying Complex Interaction between Hardware Processes

Incremental DataGrid Mining Algorithm for Mobility Prediction of Mobile Users

Comparative Studies on the Performance of Low Power Transmitters for Wireless Sensor Nodes

Virtual Mobility to Improve Cooperation in Mobile Ad hoc Networks

Three Dimensional Multidirectional Geographical IP Traceback: Direction Ratio Sampling Algorithm

Improving Accuracy and Coverage of Data Mining Systems that are Built from Noisy Datasets: A New Model

Spatial Color Indexing: An Efficient and Robust Technique for Content-Based Image Retrieval

Evaluation of the Severity of Mitral Valvular Regurgitation with Doppler Echocardiography Using Proximal Flow Convergence Method

Predicting Packet Transmission Data over IP Networks Using Adaptive Neuro-Fuzzy Inference Systems

Life Long Learning: Seniors in Second Life Continuum

Advanced Information Technology of Slot-Switching Network Schemes For All-Optical Variable-Length Packet
Problem statement: The purpose of this paper was to investigate all optical packet switching, because it was the key to the success of the future Internet. It can meet the stringent bandwidth requirement of future Internet applications, such as real-time video streaming. Due to the lack of optical random access memory (RAM), however, the all-optical schemes studied in the literature were either not flexible enough to accommodate Internet packets, which were variable-length in nature, or fail to schedule packets at switches to achieve low loss rate. Approach: The aim of this paper was thus to tackle the flexibility and utilization issues in all-optical packet switches, even at the absence of optical RAM. We approached this paper by first studied a new slotted model for all-optical variable-length packet switching, which was called variable-length-packet fixed-length slot (VPFS) switching. Results: We proved by mathematical analysis the theoretical maximum utilizations that can be achieved by the model in two variant schemes. Then we proposed a new scheduling algorithm for shared-fiber-delay-line switches in order to achieve low loss rate when the utilization approaches the maximum. We justified our design by simulation. In our finding, through mathematical analysis and computer simulation, our proposed switching model and scheduling algorithm can be coupled well to achieve good performance for all-optical packet switches. We also found that the selection of the slot size in the network was very critical as it determined the transmission overhead and hence the utilization of the all-optical network. Our research limitation depended on slot size. Although a small slot size was critical for high utilization with our model, it was not always preferable. It was because a small slot size increased the switching and scheduling complexity at the switch. Thus the selection of an optimum slot size for the network was a compromise between utilization and complexity. Conclusion/Recommendations: A fast scheduling algorithm has been studied in order to reduce the scheduling complexity so as to increase the utilization without much penalty. In regard to the practical implications, the VPFS was a promising model to fully utilize the huge capacity of all-optical networks and to accommodate variable-length packets for future Internet traffic. With VPFS, the selection of the slot size was critical, and it was a compromise between the network utilization and scheduling complexity.

Optimal Test Time for System-on-Chip Designs using Fuzzy Logic and Process Algebra
Problem statement: Test scheduling is crucially important for optimal SoC test automation to allocate the limited available test resources. In this study we introduced a fuzzy based engine to allocate test resources. The minimized test application time can be achieved by test pipelining. However the test power consumption incurred during test procedure must be controlled in order not to offend the allowed maximal power dissipation thus avoiding damaging the system under test. Approach: Process algebra is the adept to deal with concurrent behaviors, based on this, the test scheduling scheme for SoC cores concurrent test is outlined by mapping the parallel test actions into concurrent processes. The algorithm for SoC test scheduling based on process algebra under multiple constraints (test power dissipation, test resources and test priorities) and apply a fuzzy based optimum search for a solution to the scheduling problem. Results: The test application time was calculated for three ITC-02 SOC benchmark circuits and the results were compared with other approaches. Conclusion: The results showed for ITC-02 benchmarks circuits prove the effectiveness of our proposed method.

Modified Curvelet Thresholding Algorithm for Image Denoising
Problem statement: This study introduced an adaptive thresholding method for removing additive white Gaussian noise from digital images. Approach: Curvelet transform employed in the proposed scheme provides sparse decomposition as compared to the wavelet transform methods which being nongeometrical lack sparsity and fail to show optimal rate of convergence. Results: Different behaviors of curvelet transform maxima of image and noise across different scales allow us to design the threshold operator adaptively. Multiple thresholds depending on the scale and noise variance are calculated to locally suppress the curvelet transform coefficients so that the level of threshold is different at every scale. Conclusion/Recommendations: The proposed algorithm succeeded in providing improved denoising performance to recover the shape of edges and important detailed components. Simulation results proved that the proposed method can obtain a better image estimate than the wavelet based restoration methods.

Arabic Short Text Compression
Problem statement: Text compression permits representing a document by using less space. This is useful not only to save disk space, but more importantly, to save disk transfer and network transmission time. With the continues increase in the number of Arabic short text messages sent by mobile phones, the use of a suitable compression scheme would allow users to use more characters than the default value specified by the provider. The development of an efficient compression scheme to compress short Arabic texts is not a straight forward task. Approach: This study combined the benefits of pre-processing, entropy reduction through splitting files and hybrid dynamic coding: A new technique proposed in this study that uses the fact that Arabic texts have single case letters. Experimental tests had been performed on short Arabic texts and a comparison with the well known plain Huffman compression was made to measure the performance of the proposed schema for Arabic short text. Results: The proposed schema can achieve a compression ratio around 4.6 bits byte^-1 for very short Arabic text sequences of 15 bytes and around 4 bits byte^-1 for 50 bytes text sequences, using only 8 Kbytes overhead of memory. Conclusion: Furthermore, a reasonable compression ratio can be achieved using less than 0.4 KB of memory overhead. We recommended the use of proposed schema to compress small Arabic text with recourses limited.

Attack of Against Simplified Data Encryption Standard Cipher System Using Neural Networks
Problem statement: The problem in cryptanalysis can be described as an unknown and the neural networks are ideal tools for black-box system identification. In this study, a mathematical black-box model is developed and system identification techniques are combined with adaptive system techniques, to construct the Neuro-Identifier. Approach: The Neuro-Identifier was discussed as a black-box model to attack the target cipher systems. Results: In this study this model is a new addition in cryptography that presented the methods of block (SDES) crypto systems discussed. The constructing of Neuro-Identifier mode achieved two objectives: The first one was to construct emulator of Neuro-model for the target cipher system, while the second was to (cryptanalysis) determine the key from given plaintext-ciphertext pair. Conclusion: Present the idea of the equivalent cipher system, which is identical 100% to the unknown system and that means that an unknown hardware, or software cipher system could be reconstructed without known the internal circuitry or algorithm of it.

Analytical Study on Fundamental Frequency Contours of Thai Expressive Speech Using Fujisaki�s Model
Problem statement: In spontaneous speech communication, prosody is an important factor that must be taken into account, since the prosody effects on not only the naturalness but also the intelligibility of speech. Focusing on synthesis of Thai expressive speech, a number of systems has been developed for years. However, the expressive speech with various speaking styles has not been accomplished. To achieve the generation of expressive speech, we need to model the fundamental frequency (F0) contours accurately to preserve the speech prosody. Approach: Therefore this study proposes an analysis of model parameters for Thai speech prosody with three speaking styles and two genders which is a preliminary work for speech synthesis. Fujisaki�s modeling; a powerful tool to model the F0 contour has been adopted, while the speaking styles of happiness, sadness and reading have been considered. Seven derived parameters from the Fujisaki�s model are as follows. The first parameter is baseline frequency which is the lowest level of F0 contour. The second and third parameters are the numbers of phrase commands and tone commands which reflect the frequencies of surges of the utterance in global and local levels, respectively. The fourth and fifth parameters are phrase command and tone command durations which reflect the speed of speaking and the length of a syllable, respectively. The sixth and seventh parameters are amplitudes of phrase command and tone command which reflect the energy of the global speech and the energy of local syllable. Results: In the experiments, each speaking style includes 200 samples of one sentence with male and female speech. Therefore our speech database contains 1200 utterances in total. The results show that most of the proposed parameters can distinguish three kinds of speaking styles explicitly. Conclusion: From the finding, it is a strong evidence to further apply the successful parameters in the speech synthesis systems or other speech processing technologies.

A Novel Database Design for Student Information System
Problem statement: A new system designed, where necessary and alternative solutions given to solve the different problems and the most feasible solution were selected. Approach: This study presents the database design for student information system. Computerization of a system means to change it from a manual to a computer-based, system to automate the work and to provide efficiency, accuracy, timelessness, security and economy. Results: After undertaking an in-depth examination of the Ayub Medical Collage�s (AMC) existing manual student information system and analyzing its short comings, it has been found necessary to remove its deficiencies and provide a suitable solution for presently encountered problem. Conclusion: The proposed algorithm can help the management to exercise an effective and timely decision making.

An Integrated Model for the Versioning of Image Objects
Problem statement: The efficient management and retrieval of the enormous volumes of information generated by many imaging applications is still a challenging problem. Approach: In this study we are particularly interested with the use of object oriented techniques for the management of digital images. Indeed, it is widely accepted that the use of data abstraction in object oriented modeling enables real world objects to be well represented in information systems. Results: Object orientation is well suited for digital images management systems, which require the ability to handle multiple type content. This study proposes a conceptual model, based on object versioning techniques, which represents the semantics in order to allow the continuity and pattern of changes of images to be determined over time. Conclusion/Recommendations: By first storing a generic image object and then storing any changes to the object as versions, a major reduction in storage can be achieved.

Invariant Image Watermarking Using Accurate Zernike Moments
problem statement: Digital image watermarking is the most popular method for image authentication, copyright protection and content description. Zernike moments are the most widely used moments in image processing and pattern recognition. The magnitudes of Zernike moments are rotation invariant so they can be used just as a watermark signal or be further modified to carry embedded data. The computed Zernike moments in Cartesian coordinate are not accurate due to geometrical and numerical error. Approach: In this study, we employed a robust image-watermarking algorithm using accurate Zernike moments. These moments are computed in polar coordinate, where both approximation and geometric errors are removed. Accurate Zernike moments are used in image watermarking and proved to be robust against different kind of geometric attacks. The performance of the proposed algorithm is evaluated using standard images. Results: Experimental results show that, accurate Zernike moments achieve higher degree of robustness than those approximated ones against rotation, scaling, flipping, shearing and affine transformation. Conclusion: By computing accurate Zernike moments, the embedded bits watermark can be extracted at low error rate.

Single Pass Seed Selection Algorithm for k-Means
Problem statement: The k-means method is one of the most widely used clustering techniques for various applications. However, the k-means often converges to local optimum and the result depends on the initial seeds. Inappropriate choice of initial seeds may yield poor results. k-means++ is a way of initializing k-means by choosing initial seeds with specific probabilities. Due to the random selection of first seed and the minimum probable distance, the k-means++ also results different clusters in different runs in different number of iterations. Approach: In this study we proposed a method called Single Pass Seed Selection (SPSS) algorithm as modification to k-means++ to initialize first seed and probable distance for k-means++ based on the point which was close to more number of other points in the data set. Result: We evaluated its performance by applying on various datasets and compare with k-means++. The SPSS algorithm was a single pass algorithm yielding unique solution in less number of iterations when compared to k-means++. Experimental results on real data sets (4-60 dimensions, 27-10945 objects and 2-10 clusters) from UCI demonstrated the effectiveness of the SPSS in producing consistent clustering results. Conclusion: SPSS performed well on high dimensional data sets. Its efficiency increased with the increase of features in the data set; particularly when number of features greater than 10 we suggested the proposed method.

Feature Extraction for Characterization of Breast Lesions in Ultrasound Echography and Elastography
Problem statement: Elastography is developed as a quantitative approach to imaging linear elastic properties of tissues to detect suspicious tumors. We propose an automatic feature extraction method in ultrasound elastography and echography for characterization of breast lesions. Approach: The proposed algorithm was tested on 40 pairs of biopsy proven ultrasound elastography and echography images of which 11 are cystic, 16 benign and 13 malignant lesions. Ultrasound elastography and echography images of breast tissue are acquired using Siemens (Acuston Antares) ultrasound scanner with a 7.3 MHz linear array transducer. The images were preprocessed and subjected to automatic threshold, resulting in binary images. The contours of a breast tumor from both echographic and elastographic images were segmented using level set method. Initially, six texture features of segmented lesions are computed from the two image types followed by computing three strain and two shape features using parameters from segmented lesions of both elastographic and echographic images. Results: These features were computed to assess their effectiveness at distinguishing benign, malignant and cystic lesions. It was found that the texture features extracted from benign and cystic lesions of an elastogram are more distinct than that of an ultrasound image .The strain and shape features of malignant lesions are distinct from that of benign lesions, but these features do not show much variation between benign and cystic lesions. Conclusion: As strain, shape and texture features are distinct for benign, malignant and cystic lesions, classification of breast lesions using these features is under implementation.

Parallel Calculation Sensitivity Function for Multi Tasking Environments
Problem statement: Calculating sensitive functions for a large dimension control system to find the unknowns vectors for a linear system in both single and multi processors, is not considered internally compatible with multi tasking environments, so breaking the process can cost time and memory and it couldn�t be paused, resumed and saved as patterns for later continuity. This study is an attempt to solve this problem in parallel to reduce the time factor needed and increase the efficiency by using parallel calculation sensitivity function for multi tasking environments (PSME) algorithm. Approach: calculate in parallel sensitivity function using n-1 processors where n is a number of linear equations which can be represented as TX = W, where T is a matrix of size n₁�n₂, X = T^-1W, is a vector of unknowns and X/h = T^-1((T/h)-( W/h)) is a sensitivity function with respect to variation of system components h. The algorithm (PSME) divides the mathematical input model into two partitions and uses only (n-1) processors to find the vector of unknowns for original system x = (x₁,x₂,�,x_n)^T and in parallel using (n-1) processors to find the vector of unknowns for similar system (x�)^t = d^tT^-1 = (x₁�,x₂�,�x_n�)^T by using Net-Processors, where d is a constant vector. Finally, sensitivity function (with respect to variation of component X/h_i = (x_i�x_i�) can be calculated in parallel by multiplication unknowns X_i�X_i�, where i = 0,1,�n-1. Results: The running time t is reduced to O(t/n-1) and, the performance of (PSME) was increased by 30-40%. Conclusion: Hence, used (PSME) algorithm reduced the time to calculate sensitivity function for a large dimension control system and the performance was increased.

Swarm-Based Feature Selection for Handwriting Identification
Problem statement: Handwriting identification is the study for identifying or verifying the writer of a given handwritten document. Since the handwriting features are the cornerstone in the writers� classification process, the classifier accuracy is sensitive in terms of how the writers are scored based on the used features. Approach: In this study, we introduced swarm intelligence as a features weighting mechanism to differentiate between the features having high importance and those having low importance in the identification process. The weights obtained from the swarm experiments were used to adjust the features scores and then to identify the most important subset feature for the writers classification process. Results: The experiments results showed that a significance influence of the feature weights in the handwriting identification process. Conclusion: This communication investigated the influence of the feature importance in the handwriting identification process. Binary Particle Swarm Optimization (BPSO) is used as feature selection method and Euclidian Distance (ED) is used as an evaluation function for the BPSO. The BPSO is trained using 956 words of the off-line IAM data (English handwriting) to learn the feature weights. Each word is represented by 29 statistical features.

A Free Educational Java Framework for Graph Algorithms
Problem statement: In the teaching of graph theory algorithms it is important that students can experiment them on numerical instances in order to fully understand their logical meaning and to learn how they can be implemented. Approach: We developed an open source Java framework to help students in their approach to the study of graph algorithms. The framework was implemented so as to be portable and easy to use. In addition, we included a library that anyone can easily use to develop custom algorithms. Results: The framework, which is currently in use at the University of Bologna, and is available on-line, presently includes four basic algorithms in graph theory, for the solution the following problems: shortest spanning tree, shortest paths, maximum flow, and critical path. It includes an intuitive graphical user interface, and gives the users the possibility of performing a "step-by-step" execution. Conclusions: The presented Java framework constitutes a first step towards the implementation of didactical instruments for the teaching of graph theory. Future developments will also include a new major release and an implementation targeting the Microsoft. NET framework.

Land Cover Change Detection Using Texture Analysis
Problem statement: It is an important task to detect land cover changes from remotely sensed data for environmental monitoring. Although there are some applications of visual textures to the land use, they are limited to a few land cover categories with the application of one texture measure. Since land cover types are complex and often the integration of various objects, applying one texture measure to characterize land cover types is not possible. Approach: This study presented two types of texture measures for land cover types and applies them to detect possible land cover changes by discriminant analysis. The texture information of land cover types were modeled by different texture extraction methods, Laws Masks and Gabor filters. Laws Masks were designed to characterize the features in local neighborhoods. Moreover information in multi-channel of the spatial frequency domain was modeled by the Gabor filters with different orientations and spatial periods. The performance of these texture measures to detect land cover changes were evaluated by the discriminant analysis. Based on the transition matrix of land cover, the detection of land cover changes becomes to separate the land cover pair which is possible to derive conversion between them. The discriminant analysis was designed on a statistical test, which determines the contribution of the features attending the discrimination. Results: The experiments showed that this approach is capable of detecting changes and different measures are suitable to detect different changes. Conclusion: The experiment presented a textural guide for the change detection.

Acoustic Echo Cancellation: Dual Architecture Implementation
Problem statement: With the rise in mobile communication, it is becoming more frequent to use a communication device in an enclosed noisy environment, such as a subway or in a lobby. In this setting however, the received microphone is severely degraded by the echo from the speaker and background noise. The audio processing necessary to clarify the desired speech can be broken down into two parts, removal of the acoustic echo and removal of the background noise. Approach: This study proposed an �external-switched� algorithm of a dual architecture implementation for acoustic echo cancellation. Using the orthogonality property of adaptive algorithms to detect convergence, two complete adaptive filters can be run in parallel to take advantage of each filter�s particular configuration. By configuring one filter for fast adaptation and the second for minimizing the steady state error, a system can be designed with the advantages of both without suffering from increased computational cost. Results: A slight performance improvement can be demonstrated with this system; however the greatest advantage is in the reduced filter size and calculation cost. Conclusion: This parallel approach is suitable for systems in which a single approach to acoustic echo cancellation is insufficient. Disadvantages of one algorithm can be mitigated by being able to switch to a more effective algorithm seamlessly.

An Optimization of Design for S4-Duty Induction Motor Using Constraints Normalization Based Violation Technique
Problem statement: Design of Induction motors is an engineering art and needs an extensive experience for obtaining an optimal design solution for a given design problem. An optimized GD² value for the development of S4 Duty, cage induction motor to meet the specifications of a particular designated application (the location of application is kept as trade secret due to IP barrier) is proposed and validated by a physical model. Approach: The Genetic Algorithm (GA) is used to optimize inertia of rotating member as a single objective function for the designated application. A formulation based on the violations of normalized constraints is used here to transform the problem as unconstrained one. Results: The design variables for the developed model for the rating of 30 W for S4 duty operation were examined with the GA operators such as Initial population-15; two point crossover probability-0.8; mutation-0.05; number of generations-50; fitness scaling-rank; selection-Roulette wheel; Conclusion: The GD² value obtained using the GA-constraints normalization technique and from the proto model developed are 26.24 and 33.04 respectively as against the specified value 40.75 kg-cm².

Comparison of Exact Algorithms for Rectilinear Distance Single-Source Capacitated Multi-Facility Weber Problems
Problem statement: The objective of this study is to develop efficient exact algorithms for a single source capacitated multi-facility location problem with rectilinear distance. This problem is concerned with locating m capacitated facilities in the two dimensional plane to satisfy the demand of n customers with minimum total transportation cost which is proportional to the rectilinear distance between the facilities and their customers. Approach: Two exact algorithms are proposed and compared. The first algorithm, decomposition algorithm, uses explicit branching on the allocation variables and then solve for location variable corresponding to each branch as the original Mixed Integer Programming (MIP) formulation with nonlinear objective function of the problem. For the other algorithm, the new formulation of the problem is first created by making use of a well-known condition for the optimal facility locations. The problem is considered as a p-median problem and the original formulation is transformed to a binary integer programming problem. The classical exact algorithm based on this formulation which is branch-and-bound algorithm (implicit branching) is then used. Results: Computational results show that decomposition algorithm can provide the optimum solution for larger size of the studied problem with much less processing time than the implicit branching on the discrete reformulated problem. Conclusion: The decomposition algorithm has a higher efficiency to deal with the studied NP-hard problems but is required to have efficient MIP software to support.

A Novel Algorithmic Cost Estimation Model Based on Soft Computing Technique
Problem statement: Software development effort estimation is the process of predicting the most realistic use of effort required for developing software based on some parameters. It has always characterized one of the biggest challenges in Computer Science for the last decades. Because time and cost estimate at the early stages of the software development are the most difficult to obtain and they are often the least accurate. Traditional algorithmic techniques such as regression models, Software Life Cycle Management (SLIM), COCOMO II model and function points, require an estimation process in a long term. But, nowadays that is not acceptable for software developers and companies. Newer soft computing techniques to effort estimation based on non-algorithmic techniques such as Fuzzy Logic (FL) may offer an alternative for solving the problem. This work aims to propose a new fuzzy logic realistic model to achieve more accuracy in software effort estimation. The main objective of this research was to investigate the role of fuzzy logic technique in improving the effort estimation accuracy by characterizing inputs parameters using two-side Gaussian function which gave superior transition from one interval to another. Approach: The methodology adopted in this study was use of fuzzy logic approach rather than classical intervals in the COCOMO II. Using advantages of fuzzy logic such as fuzzy sets, inputs parameters can be specified by distribution of its possible values and these fuzzy sets were represented by membership functions. In this study to get a smoother transition in the membership function for input parameters, its associated linguistic values were represented by two-side Gaussian Membership Functions (2-D GMF) and rules. Results: After analyzing the results attained by means of applying COCOMO II and proposed model based on fuzzy logic to the NASA dataset and created an artificial dataset, it had been found that proposed model was performing better than ordinal COCOMO II and the achieved results were closer to the actual effort. The relative error for proposed model using two-side Gaussian membership functions is lower than that of the error obtained using ordinal COCOMO II. Conclusion: Based on the achieved results, it was concluded that, using soft computation approaches such as fuzzy logic and their advantages, good predication; adaption; understandability and the accuracy of software effort estimation can be improved and the estimation can be very close to the actual effort. This novelty model will lead researchers to focus on benefits of non-algorithmic models to overcome the estimation problems.

Automated Position System Implementation over Vehicular Ad Hoc Networks in 2-Dimension Space
Problem statement: The real world scenario have changed from the wired connection to wireless connection. Over the years software development has responded to the increasing growth of wireless connectivity in developing network enabled software. The problem arises in the wireless domain due to random packet loss in transport layer and as well as in data link layer for the end to end connection. The basic problem we have considered in this paper is to convert the real world scenario of �Vehicular ad hoc network� into lab oriented problem by used the APS-system and study the result to achieve better performance in wireless domain. Approach: We map the real world physical problem into analytical problem and simulate that analytic problem with respect to real world scenario by Automated Position System (APS) for antenna mounted over the mobile node in 2D space. Results: We quantify the performance and the impact of the packet loss, delay, by the bit error rate and throughput with respect to the real world scenario of VANET in the MAC layer, data link layer and transport layer. Conclusion: We observe that the Directional the Antenna which is mounted over the vehicle gives less bit error in comparison to Isotropic and Discone antenna.

Block Cipher Involving Key Based Random Interlacing and Key Based Random Decomposition
Problem statement: The strength of the block ciphers depend on the degree of confusion and diffusion induced in the cipher. Most of the transformations used for this purpose are well known to every one and can be broken by a crypt analyzer. Therefore, in order to counter attack the crypt analyzer, there is a need for better transformations in addition to the existing one. Approach: We tried to use key based random interlacing and key based random decomposition for this purpose. So that, a crypt analyzer cannot understand how interlacing and decomposition is done in every round unless the key is known. Results: The strength of the cipher is assessed by avalanche effect which is proved to be satisfactory. Conclusion/Recommendations: Key based random interlacing and decomposition can be used for introducing confusion and diffusion in block ciphers. The cryptanalysis carried out in this regard shows that the cipher cannot be broken by any cryptanalytic attack.

Soft Computing in Optimizing Assembly Lines Balancing
As part of manufacturing systems, the assembly line has become one of the most valuable researches to accomplish the real world problems related to them. Many efforts have been made to seek the best techniques in optimizing assembly lines. Problem statement: Since it was published by Salveson in 1955, some methods and techniques have been developed based on mathematical modeling. In recent years, some researches in Assembly Line Balancing (ALB) have been conducted using Soft Computing (SC) approaches. However, there is no comprehensive survey studies conducted regarding the use of SC in ALB problems, which is became the aim of this study. Approach: This study reviewed published literatures and previous related works that applied SC in solving ALB problems. Main outcomes: This study looks into the suitability of SC approaches in several types of ALB problems. Furthermore, this study provides the classification of ALB problems that can facilitate distinguishing those problems as fields of research. Result: This study found that Genetic Algorithms (GAs) are predominantly applied to solve ALB problems compared to other SC approaches. This high suitability in ALB refers to GAs� main characteristics that include its robustness and flexibility. These SC approaches have mostly been applied to simple ALB problems, which are not problems that are covered in a real complex manufacturing environment. Conclusion/Recommendations: This study recommends that future researches in ALB should be conducted with regard to other issues, beyond the simple ALB problems and more practical to the industries. Besides the advantages of GAs, there are still opportunities to use other SC approaches and the hybrid-systems among them that could increase the suitability of these approaches, especially for multi-objective ALB problems. This study also recommends that human involvement in ALB needs to be considered as a problem factor in ALB.

Sorting N-Elements Using Natural Order: A New Adaptive Sorting Approach
Problem statement: Researchers focused their attention on optimally adaptive sorting algorithm and illustrated a need to develop tools for constructing adaptive algorithms for large classes of measures. In adaptive sorting algorithm the run time for n input data smoothly varies from O(n) to O(nlogn), with respect to several measures of disorder. Questions were raised whether any approach or technique would reduce the run time of adaptive sorting algorithm and provide an easier way of implementation for practical applications. Approach: The objective of this study is to present a new method on natural sorting algorithm with a run time for n input data O(n) to O(nlogm), where m defines a positive value and surrounded by 50% of n. In our method, a single pass over the inputted data creates some blocks of data or buffers according to their natural sequential order and the order can be in ascending or descending. Afterward, a bottom up approach is applied to merge the naturally sorted subsequences or buffers. Additionally, a parallel merging technique is successfully aggregated in our proposed algorithm. Results: Experiments are provided to establish the best, worst and average case runtime behavior of the proposed method. The simulation statistics provide same harmony with the theoretical calculation and proof the method efficiency. Conclusion: The results indicated that our method uses less time as well as acceptable memory to sort a data sequence considering the natural order behavior and applicable to the realistic researches. The parallel implementation can make the algorithm for efficient in time domain and will be the future research issue.

An Algorithm for Localization in Vehicular Ad-Hoc Networks
Positioning a node in Vehicular Ad-Hoc networks is one of the most interested research areas in recent years. In many Ad-Hoc networks such as Vehicular Ad-Hoc networks in which the nodes are considered as vehicles, move very fast in streets and highways. So, to have a safe and fast transport system, any vehicle should know where a traffic problem such as a broken vehicle occurs. GPS is one of the equipments which have been widely used for positioning service. Problem statement: Vehicle can use a GPS receiver to determine its position. But, all vehicles have not been equipped with GPS or they cannot receive GPS signals in some places such as inside of a tunnel. In these situations, the vehicle should use a GPS free method to find its location. Approach: In this study, a new method based on transmission range had been suggested. Results: This algorithm had been compared with a similar algorithm ODAM in same situations. The best performance for Optimized Disseminating Alarm Message (ODAM) is when 40% of nodes are equipped with GPS. Conclusion: We executed our algorithm on this situation and compared it with ODAM results. At the end of this study, we can see our algorithm in compare to ODAM has better results.

Position and Obstacle Avoidance Algorithm in Robot Soccer
Problem statement: Robot soccer is an attractive domain for researchers and students working in the field of autonomous robots. However developing (coding, testing and debugging) robots for such domain is a rather complex task. Approach: This study concentrated on developing position and obstacle avoidance algorithm in robot soccer. This part is responsible for realizing soccer skills such as movement, shoot and goal keeping. The formulation of position and obstacle avoidance was based on mathematical approach. This formula is to make sure that the movement of the robot is valid. Velocity of the robot was calculated to set the speed of the robot. The positioning theory including the coordination of the robot (x,y) was used to find the obstacle and avoid it. Results: Some simulations and testing had been carried out to evaluate the usefulness of the proposed algorithms. The functions for shooting, movement and obstacle avoidance had been successfully implemented. Conclusion: The results showed its possibility could be used as strategy algorithms in real robot soccer competition.

Differential Diagnosis Knowledge Building by Using CUC-C4.5 Framework
Problem statement: The Case Based Reasoning (CBR) method can be implemented in differential diagnosis analysis. C4.5 algorithm has been commonly used to help the method�s knowledge building process. This process is completed by constructing decision tree from previously handled cases data. The C4.5 algorithm itself can be used with an assumption that all the cases has an exact and equal truth value thus have an exact contribution in decision tree building process. However, the decision makers sometimes not sure about the truth of the cases in the cases database, therefore the confidence value can be different for case by case. Besides that, the C4.5 algorithm can only handle cases that are stored in a flat table with data in form of categorized text or in discrete class. This algorithm has not yet explained about how is decision tree building mechanism in situation when the data are stored in relational tables. It also has not yet explained about the process of knowledge building when the data are in the form of number in continuous class. Meanwhile, the observed objects in this research, that is medical record data, are mostly stored in a complex relational database and have common form of categorized text, discrete number, continuous number and image. Therefore, the C4.5 is needed to be improved so it can handle decision building for cases database of medical record. Approach: We develop a knowledge building framework that can handle confidence level difference of cases in cases database. The framework we build also allows the data are stored in relational database. Moreover, our framework can process data in the form of categorized text, discrete number, continuous number and image. This framework is named CUC-C4.5, abbreviated from Complex Uncertain Case C4.5 as it is the improvement from C4.5 algorithm. Results: The CUC-C4.5 framework has been applied on the case of differential diagnosis knowledge building in a group decision support system to handle geriatric patient. This framework was implemented by using PHP and Javascript programming language and MySQL DBMS. Conclusion: The CUC-C4.5 can support differential diagnosis analysis on group decision support system for geriatric assessment.

Embedded Systems Education for Multiple Disciplines
Problem statement: This study described the process and experience of designing and developing an embedded systems first course that serves different disciplines at the University of Jordan together with its associated laboratory. The course serves three different departments with varying requirements and varying student initial background. The stages of the design process of the course and associated labs are explored. Emphasis is given throughout to the notion of systems design without losing track of the details involved in the design process. The design methodology used for the laboratory facilities and the learning outcomes are explored. Approach: The methodology followed in the design process was based on defining clear objectives taking into consideration the different backgrounds of students and departmental requirements. This was followed by defining the course content, designing the lab facilities and choosing the right hardware and software tools. We followed the Demonstrate, Work-to-Know and Design methodology for lab design Results: The course had been running successfully for several years now. Successful innovative projects undertaken by students and their results are reported. Due to its success, numerous senior capstone projects in many departments are now based on embedded systems ideas and notions. Conclusion: Embedded system teaching for multiple disciplines requires diligence and clear understanding of the varying requirements and backgrounds of students. Careful consideration should be given to the objectives, choice of tools and the timeline of the course and associated labs. Projects that tie the concepts together are very important for the success of the course.

Performance of Orthogonal Frequency Division Multiplexing System Based on Mobile Velocity and Subcarrier
Problem statement: Nowadays, the mobile telecommunications industry faces the problem of providing the technology that be able to support a wide variety of services ranging from voice communication with a bit rate of a few kbps to wireless multimedia in which bit rate up to 2 Mbps. Approach: This study introduced a new performance study to enhance the Orthogonal Frequency Division Multiplexing (OFDM) system based on both efficient iterative number of subcarrier estimation techniques and a tracking algorithm was proposed. Result: The performance of system degrades with increase of the mobile velocity or increase of the number of channel fingers. The noiseless received signal at the weakest subcarrier is estimated based on all the detected data symbols using a hard or soft decision. Due to the ﬂexibility of the transform design, the analysis conducted is applicable for other common systems as well. Conclusion: Simulation results showed the proposed algorithm can track the velocity variation very well and perform channel estimation using the most efficient tracking mode.

A Novel Method for Edge Detection Using 2 Dimensional Gamma Distribution
Problem statement: Edge detection is an important field in image processing. Edges characterize object boundaries and are therefore useful for segmentation, registration, feature extraction, and identification of objects in a scene. Approach: This study presented a novel method for edge detection using 2D Gamma distribution. Edge detection is traditionally implemented by convolving the image with masks. These masks are constructed using a first derivative, called gradient or second derivative called Laplacien. Thus, the problem of edge detection is therefore related to the problem of mask construction. We propose a novel method to construct different gradient masks from 2D Gamma distribution. Results: The different constructed masks from 2D Gamma distribution are applied on images and we obtained very good results in comparing with the well-known Sobel gradient and Canny gradient results. Conclusion: The experiment showed that the proposed method obtained very good results but with a big time complexity due to the big number of constructed masks.

History Based Contention Window Control in IEEE 802.11 Mac Protocol in Error Prone Channel
Problem statement: IEEE 802.11 Medium Access Control (MAC) protocol is one of the most implemented protocols in this network. The IEEE 802.11 controls the access to the share wireless channel within competing stations. The IEEE 802.11 DCF doubles the Contention Window (CW) size for decreasing the collision within contending stations and to improve the network performances but it is not good for error prone channel because the sudden CW rest to CW_min may cause several collisions. Approach: The research to date has tended to focus on the current number of active stations that needs complex computations. A novel backoff algorithm is presented that optimizes the CW size with take into account the history of packet lost. Results: Finally, we compare the HBCWC with IEEE 802.11 DCF. The simulation results have shown 24.14, 56.71 and 25.33% improvement in Packet Delivery Ratio (PDR), average end to end delay and throughput compared to the IEEE 802.11 DCF. Conclusion: This study showed that monitoring the last three channel statuses achieve better delay and throughput that can be used for multimedia communications.

Evaluating E-Learning Systems Using E-Traceability Systems
Problem statement: Electronic learning (e-learning) System is an ideal example of these modern learning options. It provides reliable, convenient and easily accessible environment of learning. Since the e-learning is now growing in King Saud University, this new learning approach has to be evaluated and monitored to measure the efficiency and ultimately improves its productivity. The monitoring of the e-learning applications deserves special attention and we need effective methodologies and appropriate guidelines to perform this task. Approach: The development and implementation of an effective and appropriate evaluation approach based on different types of information and analysis of reports offered by an E-Traceability System (ETS) in order to improve and enhance the e-learning system and its performance to make sure it performs its mission as desired. Results: The E-traceability system has been developed, implemented and extensively tested and the evaluation can be done with automatic and easy way. Conclusion: The outcomes of the tests are relevant information delivered by the system concerning any user�s actions in a standard reports format represented as graph diagram. These reports are related to the following main evaluation questions are being performed and they pertain to measure the popularity of the e-learning system, engagement of the participants and interactions between them and it can be used in support services and decision making.

Skin Images Segmentation
Problem statement: Image segmentation is a fundamental step in many applications of image processing. Skin cancer has been the most common of all new cancers detected each year. At early stage detection of skin cancer, simple and economic treatment can cure it mostly. An accurate segmentation of skin images can help the diagnosis to define well the region of the cancer. The principal approach of segmentation is based on thresholding (classification) that is lied to the problem of the thresholds estimation. Approach: The objective of this study is to develop a method to segment the skin images based on a mixture of Beta distributions. We assume that the data in skin images can be modeled by a mixture of Beta distributions. We used an unsupervised learning technique with Beta distribution to estimate the statistical parameters of the data in skin image and then estimate the thresholds for segmentation. Results: The proposed method of skin images segmentation was implemented and tested on different skin images. We obtained very good results in comparing with the same techniques with Gamma distribution. Conclusion: The experiment showed that the proposed method obtained very good results but it requires more testing on different types of skin images.

A Framework for Group Key Management Protocol Assessment Independent of View Synchrony
Problem statement: As group key management extended into the area of large dynamic networks, complex issues emerged involving the many operations that run over several network topologies. The issues that occurred due to multiple topologies were also compounded by differing views of the network, taken at different time slices or positions within the network. This was especially complex when figuring in mobile, ad-hoc networks. View synchrony is the current operational technique, or assumption, applied to group key exchange protocols. However, before this analysis view synchrony was just that, an assumption and the literature for group key exchange lacked an inquiry into what could happen when view synchrony was removed. Current group key management protocols rely on view synchrony and yet all protocols vary in requisite operational descriptions and performance measures. In this study, a framework for group key management protocol operations and performance measures was defined and examined how that framework could be used to compare and contrast existing protocols with and, more importantly, without view synchrony. Approach: Current literature lacked categories by which to quantify the performance metric of the protocols. This study first defined the dynamic key operations that all protocols share. By these definitions, group key management protocols were directly compared. Once definitions existed, this study assembled a list of costs that every protocol requires to establish and share keys across the dynamic group. These results provided an understanding of view synchrony's role and whether or not it should be solely relied on in these current protocols. Results: The prior conclusion that view synchrony was an integral part of all group key management protocols was shattered, when seen through the lens of communication costs and assumptions in wireless ad-hoc networks. View synchrony, as an assumed part of all group key management was previously inconsistently portrayed. The ability to see this before did not exist because a framework upon which to evaluate the costs did not exist. Now, literature can proceed with clearly defined understandings of what values exist in group key management protocols. Conclusion/Recommendations: Better communication in group key management will be a benefit to the entire field. Now that costs can be analyzed, procedure and security can be improved and protocols can be implemented for wireless ad-hoc networks. In addition, it led two authors of this study to create a new protocol, DTEGK, to maximize the most efficient communication, as view synchrony was hindering the effectiveness of previous protocols. Without the hindrance of view synchrony and a quantitative list of defined communication costs, protocols can also now be extended into the wireless, ad-hoc realm of group key management.

Dropping down the Maximum Item Set: Improving the Stylometric Authorship Attribution Algorithm in the Text Mining for Authorship Investigation
Problem statement: Stylometric authorship attribution is an approach concerned about analyzing texts in text mining, e.g., novels and plays that famous authors wrote, trying to measure the authors style, by choosing some attributes that shows the author style of writing, assuming that these writers have a special way of writing that no other writer has; thus, authorship attribution is the task of identifying the author of a given text. In this study, we propose an authorship attribution algorithm, improving the accuracy of Stylometric features of different professionals so it can be discriminated nearly as well as fingerprints of different persons using authorship attributes. Approach: The main target in this study is to build an algorithm supports a decision making systems enables users to predict and choose the right author for a specific anonymous author�s novel under consideration, by using a learning procedure to teach the system the Stylometric map of the author and behave as an expert opinion. The Stylometric Authorship Attribution (AA) usually depends on the frequent word as the best attribute that could be used, many studies strived for other beneficiary attributes, still the frequent word is ahead of other attributes that gives better results in the researches and experiments and still the best parameter and technique that�s been used till now is the counting of the bag-of-word with the maximum item set. Results: To improve the techniques of the AA, we need to use new pack of attributes with a new measurement tool, the first pack of attributes we are using in this study is the (frequent pair) which means a pair of words that always appear together, this attribute clearly is not a new one, but it wasn�t a successive attribute compared with the frequent word, using the maximum item set counters. the words pair made some mistakes as we see in the experiment results, improving the winnow algorithm by combining it with the computational approach, achieved by using the CV statistical tool as a conditional threshold for attribute selecting; by doing so, the frequent pair result improved from 50% error to 0% in the improved frequent pair with a clear higher score result compared with the frequent word attribute. Conclusion/Recommendations: The new CV algorithm results improvement may lead to several new attributes usage that gave unsatisfying results before that might improve the direction for solving some hard cases couldn�t be solved till now.

A Cryptosystem Using the Concepts of Algebraic Geometric Code
Problem statement: Cryptosystem using linear codes was developed in 1978 by Mc-Eliece. Later in 1985 Niederreiter and others developed a modified version of cryptosystem using concepts of linear codes. But these systems were not used frequently because of its larger key size. In this study we were designing a cryptosystem using the concepts of algebraic geometric codes with smaller key size. Error detection and correction can be done efficiently by simple decoding methods using the cryptosystem developed. Approach: Algebraic geometric codes are codes, generated using curves. The cryptosystem use basic concepts of elliptic curves cryptography and generator matrix. Decrypted information takes the form of a repetition code. Due to this complexity of decoding procedure is reduced. Error detection and correction can be carried out efficiently by solving a simple system of linear equations, there by imposing the concepts of security along with error detection and correction. Results: Implementation of the algorithm is done on MATLAB and comparative analysis is also done on various parameters of the system. Attacks are common to all cryptosystems. But by securely choosing curve, field and representation of elements in field, we can overcome the attacks and a stable system can be generated. Conclusion: The algorithm defined here protects the information from an intruder and also from the error in communication channel by efficient error correction methods.

Development of a �Programmable Logic Controller Circuitry� For Optimal Power Distribution in a Manufacturing Industries
Problem statement: In industries the powder demand/consumption is fixed by the power supply agency. However, at times, the demand/Consumption may exceed the fixed level and will result in, the industry paying heavy penalties to the supply agency. In most of the large and medium scale industries, controlling of power consumption is done by monitoring the powder demand indicator unit activated by a microprocessor (�p) circuitry. The major drawback of controlling the consumption using �p circuitry is that the peak value is fixed and cannot be changed in proportion to the fluctuation in load. To address above issue an attempt is made in the present work, to replace the �p circuitry with a PLC circuitry which provides for flexibility, i.e., to change maximum demand level based on the fluctuations in the load through suitable programming in the PLC circuitry. Approach: A detailed literature review was made on the application and functioning of supply controls using �p circuitry along with the associated limitations. The application of PLC circuitry in the place of �p circuitry is reviewed. The methodology of the present research was presented. The experimental work was briefed. Results: The various results were listed and discussed. Major conclusions drawn, based on the present research was shown. Conclusion: The major contribution of the present study lies, in zeroing the frequency of the power consumption, crossing the fixed level, through the design and development of an optimal PLC circuitry resulting in a significant savings in the power consumption.

Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems
Problem statement: The objective of this study is improving channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential to improve the channel estimation for more reliable communications. MIMO-OFDM system was chosen in this study because it has been widely used today due to its high data rate, channel capacity and its adequate performance in frequency selective fading channels. For this purpose a 2�2 system was designed and pilot aided channel estimation with interpolation, is made iterative to enhance BER performance. Approach: First of all, pilots were inserted among subcarriers in transmitter with distances emerged of sampling theory then Least Square (LS) method was chosen for initial channel estimation in pilots at receiver, using applicable proposed receiver, which has simple and usable structure, then channel state information was estimated by linear interpolator in information subcarriers, which uses two adjacent channel estimation in pilots to compute channel in another subcarriers and an LMS iterative algorithm, including a feedback of output is added to system. This algorithm uses the channel estimation of last iteration in current estimation. Results: Adding a LMS iterative algorithm to system, improves the channel estimation performance. Simulation results proved the acceptable BER performance of iterative channel estimation algorithm, which is closed to the ideal channel. Conclusion: The low-complexity proposed receiver including LMS algorithm, has a higher efficiency than conventional methods and it can work in lower amount of SNRs.

UML Diagrams Generator: A New CASE Tool to Construct the Use-Case and Class Diagrams from an Event Table
Problem statement: Building UML diagrams is a very important and time consuming task for both requirements and design phases. However, some of these diagrams, such as use-case and class diagrams can be considered as a transition between the two phases. Approach: Through this study, the event table will be used to derive the use-case and class diagrams. Results: A new CASE tool to automate the proposed approach will be introduced, that is, the UML diagrams generator (UMLdg). Conclusion: It is clearly noted that the proposed CASE tool (UMLdg) gives an ideal and reasonable methodology to construct the intended use-case and class diagrams from any comprehensive event table. Furthermore, this tool will save the time for the building process of such diagrams.

Design and Implementation of Parallel Subunit for Synthesis Mathematical Models
Problem statement: Mathematical modeling of different natural and technical objects and processes is one of the most important directions that needs high performance computing with huge memory. To reduce the computational time and expenses we need to carry out the calculations on specialized subunits. Approach: We described a self-organizing approximation method and introduced a new methodology of structural synthesis of specialized parallel processing subunits for realizing a group method of data handling algorithms. Results: The design procedure of the parallel subunit in addition to the selection of the computing units for this device has been introduced. Conclusion/Recommendations: The Group Method of Data Handling proved to be most effective to solve small and medium-sized problems with continuous output. It was tested on wide range of artificial and real-world problems.

Improving Triple Play Services Using Multi Protocol Label Switching Technology
Problem statement: Traditional IP networks have many limitations such as routing tables, which can be complex and time consuming. These limitations affect the performance of the network in some applications of triple play services (i.e., voice, video and data) which are characterized as time sensitive applications. Thus, Multi Protocol Label Switching (MPLS) technology has been proposed to speed up the traffic flow in the network using labels. Approach: In this study, an experiment using the Network Simulator NS-2 was performed to evaluate the impact of MPLS technology on the Triple Play Services based on the average throughput of the network, total number of packets received at destination nodes and packet loss rates and this is compared to that provided by traditional IP networks. Results: The results showed that MPLS performs better since it utilizes all the available paths to the destinations. Conclusion: MPLS allows Internet Services Providers (ISPs) to provide better triple play services for end-users.

Multiple Constraints for Ant Based Multicast Routing in Mobile Ad Hoc Networks
Problem statement: A Mobile Ad hoc Network (MANET) is one of the challenging environments for multicast. Since the associated overhead is more, the existing studies illustrate that tree-based and mesh-based on-demand protocols are not the best choice. The costs of the tree under multiple constraints are reduced by the several algorithms which are based on the Ant Colony Optimization (ACO) approach. The traffic-engineering multicast problem is treated as a single-purpose problem with several constraints with the help of these algorithms. The main disadvantage of this approach is the need of a predefined upper bound that can isolate good trees from the final solution. Approach: In order to solve the traffic engineering multicast problem which optimizes many objectives simultaneously this study offers a design on Ant Based Multicast Routing (AMR) algorithm for multicast routing in mobile ad hoc networks. Results: Apart from the existing constraints such as distance, delay and bandwidth, the algorithm calculates one more additional constraint in the cost metric which is the product of average-delay and the maximum depth of the multicast tree. Moreover it also attempts to reduce the combined cost metric. Conclusion: By simulation results, it is clear that our proposed algorithm surpasses all the previous algorithms by developing multicast trees with different sizes.

Efficient Approach for Security Information Retrieval by Using Grid
Problem statement: This article communicated an approach for determining the exact location/position of the target(s) (human) by applying Grid (matrix) method. Approach: The Main-Grid in-return further grouped into Mini-Grids; which will provide the target(s) information. To accomplish this idea the whole scenario is divided into three phases. Results: In the first phase data is collected from the targeted area, in second phase data activation/procedure(s) takes place at the target(s), whereas in the third phase data was processed to obtain the required results for the target(s). Conclusion/Recommendations: This study provided details on the first phase. It is faster in gathering data about the exact target location. It is also worth noticing that this approach is efficient, accurate and require very less processing time. The results achieved by this approach are highly reliable.

A Prototype Design for Enhancing Customer Trust in Online Payments
Problem statement: The adoption of mobile device technology can contribute significantly to enhance customers trust in online payment systems. Approach: The perceptions and preferences of online shoppers are influenced by several key factors which serve to both enhance and compromise this trust and in turn affect a customer intentions and behavior in relation to use online payment systems. The first part of the research was a quantitative study to investigate these factors. In the second part of this research, a mobile payment model for online payment systems was proposed. In this model, the customers do not need to trust merchants during the transaction because merchants will not act as an intermediary between customers and the acquirer. Customers can therefore send their financial details without concern of disclosure, or potential misuse by the merchant. Results: In this study, the key factors influencing to adopt mobile payment systems were identify. The proposed model was developed and an analysis of the model architecture against conventional online payment systems was discussed. Conclusion/Recommendations: The significance of this research comes from providing a practical mobile payment model as a possible step towards increasing customer acceptance of online shopping and increasing their trust in online payment systems. The new model focuses on enhancing the feeling of security of the use of an online payment system and satisfying the security requirements.

Comparison Study of Transmission Control Protocol and User Datagram Protocol Behavior over Multi-Protocol Label Switching Networks in Case of Failures
Problem statement: In only a few years, Multi-Protocol Label Switching (MPLS) has evolved from an exotic technology to a mainstream tool used by service providers to create revenue-generating services. MPLS provides a high reliable Label Switched Path (LSP). MPLS failures may degrade the reliability of the MPLS networks. Approach: For that reason, many studies have been conducted to keep the high reliability and survivability of the MPLS networks. Unlike User Datagram Protocol (UDP), Transmission Control Protocol does not perform well in case of like-failure of MPLS networks because of its inability to distinguish packet loss due to link-failure. After the recovery time, TCP takes longer time than UDP to continue as it was before the failure. Results: In terms of packet loss, TCP performs better than UDP. However, the receiving rate of the TCP traffic is much worse than UDP traffic. A need for a mechanism to improve the behavior of TCP after a link failure is needed. This study focused on comparing the behavior of different types TCP as well as UDP traffic over MPLS networks in case of link, node or congestion failures. Conclusion: Although extensions of RSVP-TE protocol support fast recovery mechanism of MPLS networks, the behavior of TCP will be affected during recovery time much more than with UDP.

An �Expert System� For Stereoscopic 3D Visualization (with out the Application of Conventional Attachments to the Eyes) of Computer Acquired and Computer Generated Stereopairs
Problem statement: Though stereoscopic 3D visualization technology has made considerable progress, it was always associated with eye attachments, like wearing color glasses, wearing Polaroid glasses, using timed shutters. Approach: This has considerably retarded the popularity of 3D visualization technology. Though there are discrete references in the literature for developing stereoscopic 3D visualization without application of glasses, these methods involve transferring the attachments to the monitor, direct viewing by straining the eyes, application of color variation. Results: They have not made considerable progress in this direction. An attempt is made in this study to use computer capabilities through generic algorithms to develop the stereoscopic 3D visualization without the application of glasses overcoming the above mentioned limitations. Conclusion/Recommendations: An attempt is made in this study to develop an �Expert System� using computer capabilities to give a satisfactory 3D/depth view of 2D images of 3D environments. Algorithms are developed to process both computer acquired and computer generated stereo pairs for 3D visualization.

Experimental Evaluation of Bottleneck Link Utilization with New-Additive Increase Multiplicative Decrease Congestion Avoidance and Control Algorithm
Problem statement: As the Internet becomes increasingly heterogeneous, the issue of congestion control becomes ever more important. And the link utilization is one of the important things in term of congestion avoidance and control mechanisms. And we can define the utilization as simply the throughput divided by the access rate. And also all the developments for the congestion control and avoidance algorithms interest about the using of network resources and use the links capacity (utilization). Approach: In this research we continued to study the performances of the New-Additive Increase Multiplicative Decrease (AIMD) algorithm as one of the core protocols for TCP congestion avoidance and control mechanism, we want now to evaluate the effect of using the AIMD algorithm after developing it to find a new approach, as we called it the New-AIMD algorithm to measure the bottleneck link utilization and use the NCTUns simulator to get the results after make the modification of the mechanism. And we will use the Droptail mechanism as Active Queue Management (AQM) in the bottleneck router. Results: After implementation of our new approach with different number of flows, we will measure the bottleneck link utilization and we will get high utilization (more than 94%) for bottleneck link with using this mechanism and avoid the collisions in the link. Conclusion: Now and after got this results as high utilization for bottleneck link, we know the New-AIMD mechanism work as well under the giving network condition in the experiments.

Distributed Real Time Architecture for Data Placement in Wireless Sensor Networks
Problem statement: Application scenarios of Wireless Sensor Networks (WSN) create interesting design challenges since the sensor nodes used to collect and communicate data may fail suddenly and unpredictably. The issue of real-time and reliable data delivery is extremely important for taking effective decisions in WSN. Approach: In this study we proposed architecture for reliable and real-time approach for data placement using sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action we have used Action and Relay Stations (ARS). Results: We developed programming model for formal specification of our architecture. Conclusion: Present model not only offers real time sensing and monitoring, but also provides real time dynamic decision making based on the sensed data. Moreover it prolongs network life time.

Bandwidth-Adaptive Scheduling for Quality of Service Enhancement of Real-Time Multimedia Applications in Network Processor Based Router
Problem statement: An explosive growth of multimedia applications in internet has stressed the performance of routers. Hence managing Quality of Service (QoS) enhancement of real-time multimedia applications over IP is a significant and demanding challenge. Approach: To address this issue, Bandwidth Adaptive Stratified Round Robin (BASRR) packet scheduling algorithm has been proposed in this paper for enhancing quality of service of real-time multimedia applications. Embedded Network Processors (NP) have recently emerged with flexibility and speed to reduce the stress of the router by effectively processing the packets. The main objective of this study was to implement the proposed packet scheduling algorithm in a Network Processor (NP) based router for enhancing quality of service of real-time multimedia applications Results: The effectiveness of the BASRR algorithm has been verified by simulations using Intel�s IXP 2400 network processor. The results show that BASRR achieves about 71.25% reduction in jitter compared to SRR when the traffic has uniform distribution of real-time flows and non real-time flows. The reduction in average queuing delay is about 30% compared to SRR for all the types of traffic. Conclusion: The QoS for multimedia applications has been achieved by the proposed non-preemptive Bandwidth Adaptive Stratified Round Robin (BASRR) scheduling algorithm and outperforms the three well-known scheduling algorithms including DRR, WDRR and SRR. The results showed that BASRR is efficient with per packet complexity of O(1) and provides better fairness and reduced delay.

Evaluating Defense Architecture Frameworks for C4I System Using Analytic Hierarchy Process
Problem statement: The Command, Control, Communications, Computers and Intelligence (C4I) Systems provided situational awareness about operational environment and supported in decision making and directed to operative environment. These systems had been used by various agencies like defense, police, investigation, road, rail, airports, oil and gas related department. However, the increase use of C4I system had made it more important and attractive. Consequently interest in design and development of C4I system had increased among the researchers. Many defense industry frameworks were available but the problem was a suitable selection of a framework in design and development of C4I system. Approach: This study described the concepts, tool and methodology being used for evaluation analysis of different frameworks by Analytic Hierarchy Process (AHP). Results: We had compared different defense industry frameworks like Department of Defense Architecture Framework (DODAF), Ministry of Defense Architecture Framework (MODAF) and NATO Architecture Framework (NAF) and found that AHP is fairly good tool in terms of analysis. Conclusion: Different defense industry frameworks such as DODAF, MODAF and NAF had been evaluated and compared using AHP.

Energy Efficient Hidden Markov Model Based Target Tracking Mechanism in Wireless Sensor Networks
Problem statement: Target tracking is a challenging application in Wireless Sensor Networks (WSNs) because it is computation-intensive and requires real-time location processing. This study proposes a practical target tracking system based on the Hidden Markov Model in a distributed signal processing framework. In this framework, wireless sensor nodes perform target detection and tracking, whereas target localization requires the collaborative signal processing between wireless sensor nodes for improving the location accuracy and robustness. Approach: For carrying out target tracking under the constraints imposed by the limited transmission capabilities of the wireless sensor nodes, the HMM model and the particle filter approach are adopted in single wireless sensor node due to their outstanding performance and light computational calculations. Furthermore, a progressive multi sensor localization algorithm is proposed in distributed wireless sensor network considering the tradeoff between the localization accuracy of the target and the resource constraints of sensor nodes. Results: Finally, a real world target tracking experiment had been illustrated for static and mobile targets. Here blind child is considered as the target to be tracked within the sensor network. Conclusion: Mathematical analysis and the real world results showed that the target tracking system based on a distributed WSN make efficient use of the communication resources and achieve accurate target tracking successfully.

New Directions in Cryptanalysis of Block Ciphers
Problem statement: The algebraic expression of the Advanced Encryption Standard (AES) RIJNDAEL S-box involved only 9 terms. The selected mapping for RIJNDAEL S-box has a simple algebraic expression. This enables algebraic manipulations which can be used to mount interpolation attack. Approach: The interpolation attack was introduced as a cryptanalytic attack against block ciphers. This attack is useful for cryptanalysis using simple algebraic functions as S-boxes. Results: In this study, we presented an improved AES S-box with good properties to improve the complexity of AES S-box algebraic expression with terms increasing to 255. Conclusion: The improved S-box is resistant against interpolation attack. We can develop the derivatives of interpolation attack using the estimations of S-box with less nonlinearity.

Unequally Error Protected Wireless Data Transmission Using Channel State Information and Adaptive Encoders
Problem statement: Higher data transmission rate with Quality of Services (QoS) guarantee is an important objective for wireless broadband communication systems. Unlike other communication system, real-time transmission requires high data rate and good error performance to ensure good quality of service. This study describes the design problem of real-time wireless data transmission which provides higher achievable data rate with Unequal Error Protection (UEP). Approach: Real-time data stream was divided equally into two streams, High Priority (HP) and Low Priority (LP) streams depending on their requirements. We considered these two bit streams as being encoded separately by two adaptive encoders. Feedback of Channel State Information (CSI) was used in adaptive physical layer channel for efficient use of the current available bandwidth by controlling the encoders. High code rate were used in both encoders when the channel is good while low code rate is otherwise. The two coded data streams were superimposed together with two different adjustable levels of power to achieve the UEP at the receiver end. Results: In this proposed scheme, same design metrics, namely, time, bandwidth and power were used to increase the transmission efficiency. Conclusion/Recommendations: Results showed that our scheme provided higher error performance for HP stream compared with other schemes that transmit using one power level data stream. The finding can be modified for studying the effects of fading on this system in future research.