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Real-time Watermarking Algorithm of H.264/AVC Video Stream

Lotfi Abdi1, Faten Ben Abdallah2, and Aref Meddeb2

1National Engineering School of Tunis, University of Tunis-El Manar, Tunisia

2National Engineering School of Sousse, University of Sousse, Tunisia

Abstract: Due to the extensive use of digital media applications, digital productions are easily copied and manipulated. Therefore, multimedia security and copyright protection is becoming important. Digital watermarking is an excellent tool to ensure security and protection of multimedia data by embedding some information into the digital production. For real time applications, such as IP-TV and digital TV broadcasting, a low complexity algorithm should be adopted, when video residing in a server has to be broadcasted by different stations and under different broadcasting rights. In this paper, a low complexity video watermarking scheme for H.264 has been presented. Our contribution is to attain lower complexity in embedding procedure and extracting watermark. At the same time, we avoid a bit-rate increase (BIR) and improve the runtime-efficiency and embedding capacity without sacrificing quality. The watermark is embedded into a video sequence by modifying the number of nonzero-quantized AC coefficients in a 4×4 block of I frames. The experimental results show that the proposed method can prevent a BIR and improve the runtime-efficiency and embedding capacity without sacrificing the perceptual quality.

Keywords: H264/AVC, video watermarking, compressed domain, bit-rate preservation.

Received September 9, 2014; accepted May 24, 2015

 
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Towards A UML Profile for Context-Awareness Domain

Mohamed-Salah Benselim1 and Hassina Seridi-Bouchelaghem2

1Department of Management Science, University of “08 Mai 45”, Algeria

2Department of Computer Science, University of Badji Mokhtar, Algeria

Abstract: Defining Unified Modelling Language (UML) profiles allows adaptation of the UML metamodel for specific domain, area, platform, etc. Context awareness is one of particular domains that need to be well adapted when we use UML language to model specific situations of users and applications. Therefore, it is necessary to create specific modelling notations for this particular domain. In this paper, we present an extension of the UML notations as a profile used for context-aware applications development in ubiquitous computing environment. The proposed UML context-aware profile is a package of specific profiles that extend the standard notations of three UML diagrams chosen according to different views of a system (use case diagram, sequence diagram and activity diagram). For each diagram, we propose UML extension mechanisms such as stereotypes, constraints and tagged values that can model any contextual situation by an adequate graphic representation.  Each element of the context of use should be able to be represented by this UML profile. To demonstrate the feasibility of our work, an example in medical field is shown by using StarUML software modelling platform. This work will complete the list of extended notations (class diagram) presented in previous work in order to propose a more complete UML profile.

Keywords: Software engineering, ubiquitous computing, UML, profile, extension, context-aware, modelling, metamodelling.

Received February 10, 2014; accepted December 23, 2014

 

 
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Software Defect Prediction in Large Space Systems through Hybrid Feature Selection and Classification

Shomona Jacob1 and Geetha Raju2

1SSN College of Engineering, Anna University, India

2College of Engineering, Anna University, India

Abstract: Data mining and machine learning techniques have been used in several scientific applications including software fault predictions in large space systems. State-of the-art research revealed that existing space systems succumb to enigmatic software faults leading to critical loss of life and capital. This article presents a novel approach to solve this issue of overlooking software faults by utilizing both features selection and classification techniques to accurately predict software defects in aerospace systems. The main objective was to identify the preeminent feature selection and prediction technique that enhanced the software fault prediction accuracy with the optimal set of features. The investigations affirmed that a novel hybrid feature selection method revealed the most optimal set of predictive features although no particular predictive technique was suitable to predict faults in all space system datasets. Besides, the exploration of data mining techniques in fault

prediction on the NASA Lunar space system software data clearly portrayed the improved fault prediction accuracy (~82% to ~98%) with the feature set selected by the proposed hybrid feature selection method. Also, the random sub sampling method revealed an improved mean Matthew’s Correlation Coefficient (MCC) and accuracy ranging from ~0.7 to ~0.9 and ~86% to ~98% respectively. This we believe generates further scope for future investigations on the most contributing space system features for fault prediction thus enabling design of aerospace systems with minimal faults and enhanced performance.

Keywords: Classification, data mining, hybrid feature selection, NASA datasets, prediction, software defects.

Received November 21, 2013; accepted June 12, 2014

 
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QoS Adaptation for Publish/Subscribe Middleware in Real-Time Dynamic Environments

Basem Almadani1, Shadi Abudalfa1, and Shuang-Hua Yang2

1Computer Engineering Department, King Fahd University of Petroleum and Minerals, KSA

2Computer Science Department, Loughborough University, UK

Abstract: Automatic Quality of Service (QoS) adaptation is promising approaches in developing real-time systems built on publish/subscribe middleware, and its importance increased when developing huge real-time distributed systems in dynamic environments. In this paper we proposed a new approach by building a closed loop QoS adaptive control for adapting some QoS polices automatically in publish/subscribe middleware. We use some techniques of artificial intelligence to automate QoS adaptation and improve the performance of the real-time systems in dynamic environments. The proposed approach improves the performance of the real-time system by saving its computing capabilities and making it more stable. Experimental results shown in this paper illustrate the effectiveness of the proposed approach. Keywords: Publish/subscribe middleware,QoS, adaptation, DDS, real-time, dynamic environments, clustering, online kmeans.

Received April 4, 2014; accepted May 24, 2015

 
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Efficient Adaptive Frequent Pattern Mining Techniques for Market Analysis in Sequential and Parallel Systems

Sherly Kuriakose1 and Raju Nedunchezhian2

1Department of Information Technology, Rajagiri School of Engineering and Technology, India

2Department of Computer Science and Engineering, Coimbatore Institute of Technology, India

Abstract: The classical applications of Association Rule Mining (ARM) are market analysis, network traffic analysis, and web log analysis where strategic decisions are made by analyzing the frequent itemsets from a large pool of data. Datasets in such domains are constantly updated and as they require an efficient Frequent Pattern Mining (FPM) algorithm which is capable of extracting the required information. Several incremental algorithms have been proposed to generate frequent patterns, but they are ineffective with very large datasets and do not provide the user interaction to adjust the minimum support value. This paper first presents an efficient interactive sequential FPM algorithm that uses the knowledge gained in the previous mining steps to incrementally mine the updated database with fewer complexities. Then to further reduce the time complexity it proposes an efficient interactive and incremental parallel mining algorithm .It also prepares incremental frequent patterns, without generating local frequent itemsets with less communication and synchronization overheads.

Keywords: Association rule, frequent pattern mining, interactive mining, incremental mining, parallel mining.

Received June 30, 2014; accepted August 31, 2014

 
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Pair Programming: A Teaching and Learning Tool for Defending Student’s Mental Energy

Pandarinathan Radhakrishnan1, Selvadurai Kanmani2, and Malaiyappan Nandhini3

1Department of Computer Science and Engineering, Pondicherry Central University, India

2Department of Information Technology, Pondicherry Engineering College, India

3Department of Computer Science, Pondicherry University, India

Abstract: Energy is an essential requirement to do any assigned tasks successfully. Mental Energy (ME) is the intellectual power for effective performance of cognitive tasks. This paper discusses the level of ME of the student learning to develop software program using Pair Programming (PP) and compares with the student learning to develop software program using traditional method. Subjective perception of ME was correlated with various elements of program correctness. PP and Solo Programmers (SP) were the two student groups took part in this experimental study. Both groups were asked to do programming assignments as Task 1 (T1) and Task 2 (T2) consecutively without break. Both tasks were given with equal level of software complexity and graded by an automatic tool. The grades were analyzed using non-parametric statistical methods. The results show that, PP group performed both T1 and T2 with high level of program's correctness, scoring almost equal marks in both the tasks. But, the performance of the SP group had more difference between T1 and T2 in program correctness and they scored comparatively less marks in T2 than in T1. The confirmatory analysis by means of questionnaire shown positive correlation over the hypothesis, which implies that, the ME level of PP students remained undiminished until T2, thus proving that PP methodology has more advantage than traditional method (SP) of learning software program.

Keywords: ME, extreme programming (XP), PP, solo programming, automatic grading.

Received December 26, 2013; accepted October 8, 2014

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Compression of Medical Images through DPCM Coding of Multi resolution and Multidirectional Subbands

Sudha Varadhan Krishnan and Sudhakar Radhakrishnan

Department of Electronics and Communication Engineering, Mahalingam College of Engineering and Technology, India

Abstract: This paper proposes a compression scheme for medical images through differential pulse code modulation coding of multi resolution and multidirectional subbands. Multi resolution representation of the medical images are obtained through laplacian pyramid which successfully decorrelates the image and thus reduces the redundant information by representing the image by a coarse signal at a lower resolution with several detail signals at successively higher resolutions. This multi scale transform is followed by directional transform to gather the nearby basis functions at the same scale in to linear structures. Thus each image is decomposed in to low pass subband and several band pass directional subbands that are encoded through DPCM. The proposed scheme was tested on various medical images and numerical results in this work shows the potential of various directional filter banks in the compression of medical images.

Keywords: Medical images, image compression, multi resolution, multi direction subbands, directional filter banks.

 

Received June 12, 2013; accepted April 27, 2014

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An Approach for Identifying Failure-Prone State of Computer System

Yun-Fei Jia and Renbiao Wu

Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, China

 Abstract: Controlled experiment can help us to better understand the root origin and evolution of software aging. Detection and/or quantification of software aging is an important research issue. The experimental observations may be obscure, although it may implicate much useful information. In this paper, we first report the memory thrashing phenomenon observed in our controlled experiment, and find the vibration frequency of available memory may be a potential indicator of aging. We then characterize and measure the vibration frequency by using amplitude spectrum analysis. Accordingly, a metric is proposed to measure the aging extent implicated in the vibration frequency by using power spectrum analysis. Finally, we propose an approach for online aging detection based on sliding window fourier transform. The metric is calculated for each “window” to evaluate the severity of aging at a given time instant.

Keywords: Software aging, software maintenance, fourier analysis.

 

Received March 20, 2014; accepted February 10, 2015

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Global Software Development Geographical Distance Communication Challenges

Areej Al_Zaidi and Rizwan Qureshi

Faculty of Computing and Information Technology, King Abdulaziz University, Saudi Arabia

 Abstract: Global Software Development (GSD) is a major direction in software engineering. There is interest in applying scrum practices in distributed projects. Project stakeholder distribution in GSD is represented by geographical distance, which generates challenges for communication. This paper is written to evaluate the effect of scrum practices in mitigating geographical distance-based communication challenges. We also suggest some mitigation strategies those are supported by our survey respondents. This study finds that scrum provides advantage in mitigating geographical distance-based GSD communication challenges. This research is a reference guide for other researchers to validate and extend current knowledge about scrum practices i.e., how it can be used to mitigate geographical distance-based communication challenges in GSD.

Keywords: GSD, communication challenges, scrum, geographical distance-based, mitigation strategies, survey.

 
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            Artificial Immune Algorithm for Handwritten Arabic Word Recognition

Hassiba Nemmour and Youcef Chibani

Faculty of Electronic and Computer Sciences, University of Sciences and Technology Houari Bouemediene,

Algeria

 Abstract: In this work, a system for solving handwritten Arabic word recognition is proposed. The aim is focused on holistic word recognition, which is devoted to recognize averaged size lexicons by using a single classifier. Presently, we investigate the applicability of the Artificial Immune Recognition System (AIRS) to achieve the recognition task. For the feature generation step, Ridgelet transform and pixel density features are combined to highlight both linear singularities and topological traits of Arabic words. Experiments are conducted on a vocabulary of twenty-four words extracted from the IFN/ENIT dataset. The results show that feature combination improves the recognition accuracy with more than 1%. The comparison with Support Vector Machine (SVM) classifier highlights the effectiveness of AIRS. This latter achieves comparable and sometimes better performance than SVM and can be extended to recognize any number of classes.

Keywords: Arabic word recognition, immune systems, ridgelet transform, SVMs.

Received January 28, 2014; accepted June 10, 2015

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UCOM Offline Dataset-An Urdu Handwritten Dataset Generation

Saad Bin Ahmed1, Saeeda Naz2,3, Salahuddin Swati4, Muhammad Razzak1, Arif Umar2, and Akbar Khan4

1College of Public Health and Health Informatics, King Saud Bin Abdul Aziz University for Health

Sciences, Saudi Arabia

2Department of Information Technology, Hazara University, Pakistan

3GGPGC No.1, Higher Education Department, Pakistan

4COMSATS Institute of Information Technology, Pakistan

 Abstract: A benchmark database for character recognition is an essential part for efficient and robust development. Unfortunately, there is no comprehensive handwritten dataset for Urdu language that would be used to compare the state of the art techniques in the field of optical character recognition. In this paper, we present a new and publically available dataset comprising 600 pages of handwritten Urdu text written in Nasta’liq style in conjunction with detailed ground truth for the evaluation of handwritten Urdu character recognition. This dataset contains text lines written in Nasta’liq style by limited individuals on A4 size paper. The acquired data on page was scanned and text lines were segmented. UCOM database covers all Urdu characters and ligatures with different variation in addition to Urdu numeric data. We have considered that ligature consists of up to five characters in this dataset. The UCOM dataset can be used for handwritten character recognition as well as writer identification. We proposed and evaluated the strength of Recurrent Neural Networks (RNN) on UCOM offline database sample text line.

Keywords: RNN, optical character recognition, cursive, offline handwriting.

Received April 22, 2014; accepted October 26, 2014

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Enhanced Constrained Artificial Bee Colony Algorithm for Optimization Problems

Soudeh Babaeizadeh and Rohanin Ahmad

Department of Mathematical Sciences, Universiti Teknologi Malaysia, Malaysia

Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm that has attracted great deal of attention from researchers in recent years with the advantage of less control parameters and strong global optimization ability. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. This drawback can be even more significant when constraints are also involved. To address this issue, an Enhanced Constrained ABC algorithm (EC-ABC) is proposed for Constrained Optimization Problems (COPs) where two new solution search equations are introduced for employed bee and onlooker bee phases respectively. In addition, both chaotic search method and opposition-based learning mechanism are employed to be used in population initialization in order to enhance the global convergence when producing initial population. This algorithm is tested on several benchmark functions where the numerical results demonstrate that the EC-ABC is competitive with state of the art constrained ABC algorithm.

Keywords: ABC, constrained optimization, swarm intelligence, search equation.

Received November 11, 2014; accepted March 2, 2015

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Extending Information System Models to the Health Care Context: An Empirical Study and Experience from Developing Countries

Osama Alfarraj1 and Ahed Abugabah2

1Computer Science Department, King Saud University, Saudi Arabia

2College of Technological Innovation, Zayed University, UAE

 

Abstract: This study aims to evaluate Hospital Information Systems (HIS) and their impact on end-user performance and the health care services in two developing countries. A survey methodology was used to gather empirical data for model validation and hypothesis testing. A correlation and factor analysis were conducted to test the reliability and validity of the study instrument. The structural equation modelling technique was also used to evaluate the measurement and the structural models. The results confirmed the significance of the integrated model in explaining user performance and demonstrated that our model can better represent factors associated with user performance and health care services; our model was able to explain 74% of the variance in user performance and 52% of the variance in the health care services. The study indicated the need to consider the context of the HIS when using models like the Technology Acceptance Model (TAM) and the information systems success model. Some information systems factors have become more relevant, such as System Quality (SQ) and Task-Technology Fit (TTF). Others have different implications, including ease of use and usefulness, indicating the need to adapt these models based on the context of the system under study.

Keywords: Health care informatics, hospital information systems, information system models, user performance, health care service quality.

Received August 30, 2014; accepted June 14, 2015

 
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A Comparative Study on Various State of the Art Face Recognition Techniques under Varying Facial Expressions

  Steven Lawrence Fernandes, Josemin Bala

Department Electronics and Communication Engineering, Karunya University, India

Abstract: Through face we can know the emotions and feelings of a person. It can also be used to judge a person’s mental aspect and psychomatic aspects. There are 5 state of the art approaches for recognizing faces under varying facial expressions. These 5 approaches are overlapping Discrete Cosine Transform (DCT), Hierarchical Dimensionality Reduction (HDR), Local and Global combined Computational Features (LGCF), Combined Statistical Moments (CSM), and Score Level Fusion Techniques (SLFT). Matlab code has been developed for all the 5 systems and tested using common set of train and test images. The train and test images are considered from standard public face databases ATT, JAFFE, and FEI. The key contribution of this article is, we have developed and analyzed the 5 state of the art approaches for recognizing faces under varying facial expressions using a common set of train and test images. This evaluation gives us the exact face recognition rates of the 5 systems under varying facial expressions. The face recognition rate of overlap DCT on ATT database was 95% and FEI 99% which was better than HDR, LGCM, CSM and SLFT. But the face recognition rate of CSM on JAFE database, which contains major facial expression variations, was 100% which was better than overlap DCT, HDR, LGCM, and SLFT.

Keywords: Face recognition, DCT, HDR, low-computational features, statistical moments, SLFT.

Received April 30, 2014; accepted June 2, 2014

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New Replica Server Placement Strategies using Clustering Algorithms and SOM Neural Network in CDNs

Ghazaleh Eslami1*, Abolfazl Toroghi Haghighat1, Saeed Farokhi2

1Department of Computer Engineering, Islamic Azad University, Iran

2Department of Mechanical Engineering, Tehran University, Iran

Abstract: Many service providers distribute various kinds of content over the internet. Content Distribution Networks (CDNs) use replication of either entire website or most used objects to bring content close to the users and improve communication delay.  In order to deliver web contents, CDNs should decide where to place replica servers and how many replicas are needed.  In this paper, a linear programming formulation for web server replica placement has been provided.  We also present new algorithms using K-means, Fuzzy c-means clustering and SOM Neural network to place web server replicas. Our objective is to find best replica server sites, which minimize distance between replicas and clients- to keep replicas. We compare our algorithms with Greedy algorithm. We have considerable enhancement in terms of load balancing and Runtime.  

 Keywords: Distributed systems, server placement, clustering algorithms, CDN.

 Received January 6, 2014; accepted June 10, 2015

 
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Effects of Network Structures and Fermi Function’s Parameter β in Promoting Information Spreading on Dynamic Social Networks

Abdulla Ally and Ning Zhang

Business School, University of Shanghai for Science and Technology, China

 Abstract: Network represents a multitude of interactions through which information spreads within a society. Indeed, people are connected according to the way they interact with one another and the resulting network significantly determines the efficiency and speed of information spreading. This paper aimed at examining how topological structures of dynamic social network ks and  ermi function’s parameter β influence information spreading. In order to carry out this study preciously, two models were proposed to enerate a variety of network structures. To study the spreading process, the models were integrated with an epidemic Susceptible-Infected-Recovered (SIR) model and designed in such a way that nodes rewire network edges according to Fermi function which depends on a parameter β. By studying the number of recovered nodes generated in the spreading process and the number of cquainted nodes that are receiving information in each time step, the results suggested that network structure and both positive and negative β play an important role in promoting information spreading. These results give a good indication that the structure of a society influences the spreading process. More specifically, the structure of dynamic interactions is a good promoter of information spreading. Moreover, it is proposed that rewiring more than three edges of random network could yield no significant advantages in promoting information spreading. The present study likely enriches our knowledge and provides more insight on information spreading.

Keywords: Dynamic social network, information spreading, network structure, rewiring.

 Receive October 18, 2014; accepted December 16, 2014

 
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