Universal Journal of Computer Science and Engineering Technology @ 2012, unicse.editor@unicse.org Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet 1- Transmitting Video-on-Demand Effectively , Download pdf. Rachit Mohan Garg, Shipra Kapoor, Kapil Kumar, Mohd. Dilshad Ansari. CSE Deptt, JUIT, INDIA. Abstract—Now-a-days internet has become a vast source of entertainment & new services are available in quick succession which provides entertainment to the users. One of this service i.e. Video-on-Demand is most hyped service in this context. Transferring the video over the network with less error is the main objective of the service providers. In this paper we present an algorithm for routing the video to the user in an effective manner along with a method that ensures less error rate than others. Keywords- Ontology Driven Architecture; Network Coding; VoD service; Cooperative Repair of data packets;   2- Discrete Sine Transform Sectorization for Feature Vector Generation in CBIR, Download pdf. H.B.Kekre, Dhirendra Mishra MPSTME, SVKM’s NMIMS (Deemed-to be-University) Vile Parle West, Mumbai -56,INDIA.   Abstract- We have introduced a novel idea of sectorization of DST transformed components. In this paper we have proposed two different approaches along with augmentation of mean of zero and highest row components of row transformed values in row wise DST transformed image and mean of zero- and highest column components of Column transformed values in column wise DST transformed image for feature vector generation. The sectorization is performed on even-odd plane. We have introduced two new performance evaluation parameters i.e. LIRS and LSRR apart from precision and Recall, the well-known traditional methods. Two similarity measures such as sum of absolute difference and Euclidean distance are used and results are compared. The cross over point performance of overall average of precision and recall for both approaches on different sector sizes are compared. The DST transform sectorization is experimented on even-odd row and column components of transformed image with augmentation and without augmentation for the color images. The algorithm proposed here is worked over database of 1055 images spread over 12 different classes. Overall Average precision and recall is calculated for the performance evaluation and comparison of 4, 8, 12 & 16 DST sectors. The use of Absolute difference as similarity measure always gives lesser computational complexity and better performance. Keywords-CBIR, DST, Euclidian Distance, Sum of Absolute Difference, Precision and Recall, LIRS, LSRR.   3- Colour Guided Colour Image Steganography, Download pdf. R.Amirtharajan, Sandeep Kumar Behera, Motamarri Abhilash Swarup, Mohamed Ashfaaq K and John Bosco Balaguru Rayappan Department of Electronics & Communication Engineering, School of Electrical & Electronics Engineering, SASTRA University, Thanjavur, Tamil Nadu, India   Abstract- Information security has become a cause of concern because of the electronic eavesdropping. Capacity, robustness and invisibility are important parameters in information hiding and are quite difficult to achieve in a single algorithm. This paper proposes a novel steganography technique for digital color image which achieves the purported targets. The professed methodology employs a complete random scheme for pixel selection and embedding of data. Of the three colour channels (Red, Green, Blue) in a given colour image, the least two significant bits of any one of the channels of the color image is used to channelize the embedding capacity of the remaining two channels. We have devised three approaches to achieve various levels of our desired targets. In the first approach, Red is the default guide but it results in localization of MSE in the remaining two channels, which makes it slightly vulnerable. In the second approach, user gets the liberty to select the guiding channel (Red, Green or Blue) to guide the remaining two channels. It will increase the robustness and imperceptibility of the embedded image however the MSE factor will still remain as a drawback. The third approach improves the performance factor as a cyclic methodology is employed and the guiding channel is selected in a cyclic fashion. This ensures the uniform distribution of MSE, which gives better robustness and imperceptibility along with enhanced embedding capacity. The imperceptibility has been enhanced by suitably adapting optimal pixel adjustment process (OPAP) on the stego covers. Keywords- Optimal Pixel Adjustment Process (OPAP); Pixel Value Differencing (PVD); Steganography.   4- Reference Point Based Multi-Objective Optimization Using Hybrid Artificial Immune System, Download pdf. Waiel F. Abd El-Wahed, Elsayed M. Zaki and Adel M. El-Refaey Faculty of Computers & Information, Menoufia University, Shebin El-Kom, Egypt Abstract- During the last decade, the field of Artificial Immune System (AIS) is progressing slowly and steadily as a branch of Computational Intelligence (CI).There has been increasing interest in the development of computational models inspired by several immunological principles. Although there are advantages of knowing the range of each objective for Pareto-optimality and the shape of the Pareto- optimal frontier itself in a problem for an adequate decision-making, the task of choosing a single preferred Pareto optimal solution is also an important task. In this paper, a Reference Point Based Multi-Objective Optimization Using hybrid Artificial intelligent approach based on the clonal selection principle of Artificial Immune System (AIS) and Neural Networks is proposed. And, instead of one solution, a preferred set of solutions near the reference points can be found. Modified Multi-objective Immune System Algorithm (MISA) is proposed with real parameters value not binary coded parameters, uniform and non uniform mutation operator is applied to the clones produced. Real parameter MISA works on continuous search space. Keywords- Artificial Immune System, Neural Networks, Reference point approach, interactive multi- objective method, multi-objective optimization. Clonal Selection.   5- Distributing Arabic Handwriting Recognition System Based on the Combination of Grid Meta-Scheduling and P2P Technologies (Omnivore) , Download pdf. Hassen Hamdi, Maher Khemakhem Mir@cl Lab, FSEGS, University of Sfax, BP 1088, 3018 Sfax, Tunisia.   Abstract- Character recognition is one of the oldest fields of research. It is the art of automating both the process of reading and keyboard input of text in documents. A major part of information in documents is in the form of alphanumeric text. Significant movement has been made in handwriting recognition technology over the last few years. Up until now, Arabic handwriting recognition systems have been limited to small and medium size of documents to recognize. The facility of dealing with large database (large scale), however, opens up many more applications. Our idea consists to use a strong and complimentary approach which needs enough computing power. We have used a distributed Arabic handwriting system based on the combination of Grid meta-scheduling and Peer–to-Peer (P2P) technologies such as Omnivore. Obtained results confirm that our approach present a very interesting framework to speed up the Arabic optical character recognition process and to integrate (combine) strong complementary approaches which can lead to the implementation of powerful handwriting OCR systems . Keywords- Large scale handwriting OCR; P2P; Grid Meta-Scheduling; Omnivore; cluster.   6- Detection of Cardiac Infarction in MRI C-SENC Images, Download pdf. Ahmad O. Algohary, Ahmed M. El-Bialy, Ahmed H. Kandil and Nael F. Osman Senior Biomed. S/W Eng. Diagnosoft Inc, Cairo Intl Office, Egypt.   Abstract- Composite Strain Encoding (C-SENC) is an Magnetic Resonance Imaging (MRI) technique for acquiring simultaneous viability and functional and images of the heart. It combines two imaging techniques, Delayed Enhancement (DE) and Strain Encoding (SENC). In this work, a novel multi-stage method is proposed to identify ventricular infarction in the functional and viability images provided by C- SENC MRI. The proposed method is based on sequential application of Otsu’s thresholding, morphological opening, square boundary tracing and the subtractive clustering algorithm. This method is tested on images of ten patients with and without myocardial infarction (MI). The resulting clustered images are compared with those marked up by expert cardiologists who assisted in validating results coming from the proposed method. Infarcted tissues are correctly identified using the proposed method with high levels of sensitivity and specificity. Keywords- Infarction; C-SENC MRI; Delayed Enhancement; styling; insert.   7- Automatic Model Based Methods to Improve Test Effectiveness, Download pdf. Izzat Alsmadi, Samer Samarah, Ahmad Saifan and Mohammed G. AL Zamil Department of Computer Information Systems, Yarmouk University, Irbid, Jordan.   Abstract- Software testing covers a large percent of the software development expenses. However, formal methods are applied, usually, to improve or ensure the correctness of the requirements, design, code, or testing. In order to utilize formal methods particularized to different cases, the subject matter needs to be written in a formal language or syntax. In this research, several model based methods are investigated and experimented in order to reduce testing expenses, improve test coverage, and the effectiveness of the testing process. Formal models are generated from the application during runtime. For this purpose a tool is developed to automatically derive the formal syntax from the application at runtime. Later on, the formal model is used in improving test effectiveness. In addition, the model is used to find some possible dynamic problems in the application that might be hard to be discovered by traditional testing methods. Finally, a test monkey tool is proposed in order to test the application for deadlock or progress problems and test the application ability to reject invalid test cases as well. Keywords- software engineering, software testing, model based verification, user interface verification, Interface model, GUI specification, software verification, formal methods.   8- Model Transformations in Model Driven Architecture, Download pdf. Atif Aftab Ahmed Jilani, Muhammad Usman, Zahid Halim FAST-National University of Computer and Emerging Sciences, Islamabad, Pakistan.   Abstract- Transformation is one of the prominent features and the rising research area of Model Driven Architecture since last few years. There are many techniques which have been proposed as a Request for Proposal (RFP) in Query, View and Transformation (QVT). In this paper we have conducted a survey on transformation techniques. The surveyed techniques  include pattern based approaches, transformation languages, transformation rules, Metamodel based approaches etc. This work has summarize, categorized and identified different analysis parameters of these techniques. On the basis of identified parameters we have presented an analysis matrix to describe the strength of different approaches. The major focus of the work is on model to model transformation techniques i.e. from PIM to PSM transformation. Keywords- Model Driven Architecture; Transformation and analysis matrix.   9- Effective Method for Extracting Rules from Fuzzy Decision Trees based on Ambiguity and Classifiability, Download pdf. Hesham A. Hefny, Ahmed S. Ghiduk, Ashraf Abdel Wahab, Mohammed Elashiry Dept. of Computer and Information Sciences, Cairo University, Egypt.   Abstract- Crisp Decision trees (CDT) algorithms have been the most widely employed methodologies for symbolic knowledge acquisition. There are many methodologies have been presented to address the problems of the continuous data, multi-valued data, missing data, uncertainty data and noisy features. Recently, due to the widespread use of the fuzzy representation, a lot of researchers have utilized the fuzzy representation in decision trees to overcome the preceding problems. Fuzzy decision trees (FDT) are generalization for the CDT. FDTs are built by using fuzzy or crisp attributes and classes which often need pruning to reduce their size. FDTs have been successfully used to extract knowledge in uncertain classification problems. In this paper, we present a technique to build FDT by employing the ambiguity of attributes and classifiability of instance. Our technique builds a reduced FDT which does not need for applying the pruning algorithms to reduce the size. The paper also presents the results of a set of empirical studies conducted on a dataset of UCI Repository of Machine Learning Database that evaluate the effectiveness of our technique compared to Fussy Iterative Dichotomiser 3 (FID3), ambiguity, and FID3 with classifiability techniques. The studies show the effective of our technique in reducing the number of the extracted rules without loosing of the rules accuracy.   Keywords- Fuzzy decision tree; Fuzzy entropy; Fuzzy Ambiguity; Fuzzy rules; Classifiability of Instances.   10- A New Software Data-Flow Testing Approach via Ant Colony Algorithms, Download pdf. Ahmed S. Ghiduk Department of Computer Science, Taif University, Saudi Arabia.   Abstract- Search-based optimization techniques (e.g., hill climbing, simulated annealing, and genetic algorithms) have been applied to a wide variety of software engineering activities including cost estimation, next release problem, and test generation. Several search based test generation techniques have been developed. These techniques had focused on finding suites of test data to satisfy a number of control-flow or data-flow testing criteria. Genetic algorithms have been the most widely employed search-based optimization technique in software testing issues. Recently, there are many novel search-based optimization techniques have been developed such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Immune System (AIS), and Bees Colony Optimization. ACO and AIS have been employed only in the area of control-flow testing of the programs. This paper aims at employing the ACO algorithms in the issue of software data-flow testing. The paper presents an ant colony optimization based approach for generating set of optimal paths to cover all definition-use associations (du-pairs) in the program under test. Then, this approach uses the ant colony optimization to generate suite of test-data for satisfying the generated set of paths. In addition, the paper introduces a case study to illustrate our approach.   Keywords- data-flow testing; path-cover generation, test-data generation; ant colony optimization algorithms. The Universal Journal of Computer Science and Engineering Technology (UniCSE) UniCSE Indexing UniCSE is indexed by:  Ulrich  Google Scholar   DOAJ  CABELL  Docstoc Scribd CiteSeer  OpenJ-Gate  Call for Paper Full Paper Submission: 10 May 2012. Author Notification: 25 May 2012.