IJACSA Volume 6 Issue 6 - thesai.org

IJACSA Volume 6 Issue 6

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: Intrusion Detection and Countermeasure of Virtual Cloud Systems - State of the Art and Current Challenges

Abstract: Clouds are distributed Internet-based platforms that provide highly resilient and scalable environments to be used by enterprises in a multitude of ways. Cloud computing offers enterprises technology innovation that business leaders and IT infrastructure managers can choose to apply based on how and to what extent it helps them fulfil their business requirements. It is crucial that all technical consultants have a rigorous understanding of the ramifications of cloud computing as its influence is likely to spread the complete IT landscape. Security is one of the major concerns that is of practical interest to decision makers when they are making critical strategic operational decisions. Distributed Denial of Service (DDoS) attacks are becoming more frequent and effective over the past few years, since the widely publicised DDoS attacks on the financial services industry that came to light in September and October 2012 and resurfaced in the past two years. In this paper, we introduce advanced cloud security technologies and practices as a series of concepts and technology architectures, from an industry-centric point of view. This is followed by classification of intrusion detection and prevention mechanisms that can be part of an overall strategy to help understand, identify and mitigate potential DDoS attacks on business networks. The paper establishes solid coverage of security issues related to DDoS and virtualisation with a focus on structure, clarity, and well-defined blocks for mainstream cloud computing security solutions and platforms. In doing so, we aim to provide industry technologists, who may not be necessarily cloud or security experts, with an effective tool to help them understand the security implications associated with cloud adoption in their transition towards more knowledge-based systems.

Author 1: Andrew Carlin

Author 2: Mohammad Hammoudeh

Author 3: Omar Aldabbas

Keywords: Cloud Computing Security; Distributed Denial of Service; Intrusion Detection; Intrusion Prevention; Virtualisation

Paper 2: Optimal Design of PMSA for SBW Application

Abstract: In this paper a new topology of Permanent Magnet Synchronous Actuator (PMSA) is used for steer-by-wire application. The magnetic field patterns are determined from finite element modeling, for different rotor positions and supply currents, using FEMM software. The designed actuator geometric is, then, optimized using Genetic Algorithm in order to ameliorate its electromagnetic characteristics, and its resulting torque. Finally, a thermal analysis is achieved for the initial and the optimized actuators. The obtained results show a clear improvement of the actuator electromagnetic characteristics and heat distribution.

Author 1: Rached BEN MEHREZ

Author 2: Lilia EL AMRAOUI

Keywords: Genetic Algorithms (GA); Permanent Magnet Synchronous Actuator (PMSA); finite elements analysis; Steer-By-Wire application (SBW); Thermal study; Optimization

Paper 3: Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing

Abstract: Big data dictate their requirements to the hardware and software. Simple migration to the cloud data processing, while solving the problem of increasing computational capabilities, however creates some issues: the need to ensure the safety, the need to control the quality during data transmission, the need to optimize requests. Computational cloud does not simply provide scalable resources but also requires network infrastructure, unknown routes and the number of user requests. In addition, during functioning situation can occur, in which you need to change the architecture of the application — part of the data needs to be placed in a private cloud, part in a public cloud, part stays on the client.

Author 1: Evgeny Nikulchev

Author 2: Evgeniy Pluzhnik

Author 3: Dmitry Biryukov

Author 4: Oleg Lukyanchikov

Author 5: Simon Payain

Keywords: Cloud Infrastructure; Big Data; Distributed Databases; Hybrid Clouds

Paper 4: Intelligent Wireless Indoor Monitoring System based on ARM

Abstract: This paper proposed an intelligent wireless indoor monitoring system based on STM32F103. The system compromises a master and terminals, which communicates through a CC1101 433M wireless unit. Using ENC28J60 and SIM900A to access Ethernet, the system can intelligent push information to cloud server, therefore we can observe and control terminals remotely. This paper present an algorithm based on MCU ID for terminal code recognition. The algorithm can intelligently discriminate terminals through code matching code between master and terminals, though hardware and software of terminals is similar. The experiment demonstrates that the proposed system is robust stability, real-time and obtains accurate warning information.

Author 1: Jia Chunying

Author 2: Zhang Liping

Author 3: Chen Yuchen

Keywords: STM32; CC1101; Intelligent Monitoring; ID; Corresponding Code Discrimination

Paper 5: Markovian Process and Novel Secure Algorithm for Big Data in Two-Hop Wireless Networks

Abstract: This paper checks the correctness of our novel algorithm for secure, reliable and flexible transmission of big data in two-hop wireless networks using cooperative jamming scheme of attacker location unknown through Markovian process. Big data has to transmit in two-hop from source-to-relay and relay-to-destination node by deploying security in physical layer. Based on our novel algorithm, the nodes of the network can be identifiable, the probability value of the data absorbing nodes namely capture node C, non-capture node NC, eavesdropper node E, in each level depends upon the present level to the next level, the probability of transition between two nodes is same at all times in a given time slot to ensure more secure transmission of big data. In this paper, maximum probability for capture nodes is considered to justify the efficient transmission of big data through Markovian process.

Author 1: K. Thiagarajan

Author 2: K. Saranya

Author 3: A. Veeraiah

Author 4: B. Sudha

Keywords: big data; two-hop transmission; security in physical layer; cooperative jamming; energy balance; Markov process

Paper 6: Towards GP Sentence Parsing of V+P+CP/NP Structure

Abstract: Computational linguistics can provide an effective perspective to explain the partial ambiguity during machine translation. The structure of V+Pron+CP/NP has the ambiguous potential to bring Garden Path effect. If Tell+Pron+NP structure has considerable higher observed frequencies than Tell+Pron+CP structure, the former is regarded as the preferred structure and has much lower confusion quotient. It is possible for the grammatical unpreferred Tell+Pron+CP structure to replace the ungrammatical preferred Tell+Pron+NP, which results in the processing breakdown. The syntactic details of GP processing can be presented by the computational technologies. Computational linguistics is proved to be effective to explore the Garden Path phenomenon.

Author 1: Du Jiali

Author 2: Yu Pingfang

Keywords: artificial intelligence; computational linguistics; machine learning; local ambiguity; garden path sentences

Paper 7: Application of GLBP Algorithm in the Prediction of Building Energy Consumption

Abstract: Using BP neural network in past to predict the energy consumption of the building resulted in some shortcomings. Aiming at these shortages, a new algorithm which combined genetic algorithm with Levenberg-Marquardt algorithm (LM algorithm) was proposed. The proposed algorithm was used to improve the neural network and predict the energy consumption of buildings. First, genetic algorithm was used to optimize the weight and threshold of Artificial Neural Network (ANN). Levenberg-Marquardt algorithm was adopted to optimize the neural network training. Then the predicting model was set up in terms of the main effecting factors of the energy consumption. Furthermore, a public building power consumption data for one month is collected by establishing a monitoring platform to train and test the model. Eventually, the simulation result proved that the proposed model was qualified to predict short-term energy consumption accurately and efficiently.

Author 1: Dinghao Lv

Author 2: Bocheng Zhong

Author 3: Jing Luo

Keywords: BP Neural network; Building energy consumption; Genetic algorithm; Levenberg-Marquardt algorithm

Paper 8: Smart Transportation Application using Global Positioning System

Abstract: Significant increase is noticed in the utilization of mobile applications for different purposes in the past decade. These applications can improve any individual’s way of life in many aspects such as communication, collaborative work, learning, location services, data collection, exploring, testing and analysis. One of the most interesting mobile applications is using it for tracking by having personal locators. These locators can track children, people on work, the elderly for personal protection etc. The intention behind developing this mobile application is to provide a smart transportation system to it users and to track their movements. Some of the essential features of this application are • Getting familiar with the shortest path from source to destination in advance. • Aware of approximate time of arrival to destination. • Knowing the capacity of vehicle used for transportation. • Short Message Service.

Author 1: Nouf Mohammad Al Shammary

Author 2: Abdul Khader Jilani Saudagar

Keywords: communication; global positioning system; smart application; tracking; transportation

Paper 9: Adoption of e-Government in Pakistan: Supply Perspective

Abstract: Electronic Government, also known as e-Government, is a convenient way for citizens to access e- services and to conduct business with the government using the Internet. It saves citizens and the government both time and money. This study examined adoption of e-Government supply side by looking at the UTAUT as a model of technology acceptance. Furthermore, specific variables that were proposed to moderate relationships within the UTAUT were analyzed including locus of control, perceived organizational support, affective and normative commitment, and procedural justice. Data from one sample indicated that in general, the UTAUT model was supported, however, the moderators proved non-significant. Implications are discussed for the technology acceptance process as technologies are implemented within countries and suggestions for future research in this area are discussed. This research sought to demonstrate the robustness of trust-based UTAUT to address e-Government adoption concerns. As a consequence, it was the responsibility of the researcher to select research questions, operational variables, research approaches, and research techniques, within the scope of the study. The research hypotheses formulated in this study were based on the technology acceptance literature covering the original UTAUT model with the inclusion of the trust construct. This quantitative study was conducted with help of Unified Theory of Acceptance and Use of Technology (UTAUT) model.

Author 1: Zulfiqar Haider

Author 2: Chen Shuwen

Author 3: Dr. Farah Lalani

Author 4: Dr. Aftab Ahmed Mangi

Keywords: e-Government; adoption; Supply; UTAUT model; Pakistan

Paper 10: Building a Robust Client-Side Protection Against Cross Site Request Forgery

Abstract: In recent years, the web has been an indispensable part of business all over the world and web browsers have become the backbones of today's systems and applications. Unfortunately, the number of web application attacks has increased a great deal, so the matter of concern is securing web applications. One of the most serious cyber-attacks has been by cross site request forgery (CSRF). CSRF has been recognized among the major threats to web applications and among the top ten worst vulnerabilities for web applications. In a CSRF attack, an attacker takes liberty be authorized to take a sensitive action on a target website on behalf of a user without his knowledge. This paper, providing an overview about CSRF attack, describes the various possible attacks, the developed solutions, and the risks in the current preventive techniques. This paper comes up with a highly perfect protection mechanism against reflected CSRF called RCSR. RCSR is a tool gives computer users with full control on the attack. RCSR tool relies on specifying HTTP request source, whether it comes from different tab or from the same one of a valid user, it observes and intercepts every request that is passed through the user’s browser and extracts session information, post the extracted information to the Server, then the server create a token for user's session. We checked the working of RCSR extension, our evaluation results show that it is working well and it successfully protects web applications against reflected CSRF.

Author 1: Abdalla AlAmeen

Keywords: Security; Reflected CSRF; client-side protection; tab ID; token

Paper 11: Content -based Image Retrieval for Image Indexing

Abstract: Content-based image retrieval has attained a position of overwhelming dominance in computer vision with the advent of digital cameras and explosion of images in the Internet and Clouds. Finding the most relevant images in a short time is a challenging job with many big cloud sites competing in image search in terms of accuracy and recall. This paper addresses an image retrieval system employing color information indexing. The system is organized with the hue components of the HSV color model. To assess the precision of the image retrieval system, experiments have been carried out on a database consisting of 450 images drawn by Japanese traditional painters, namely Sharaku, Hokusai, Hiroshige, and the images obtained from the World Wide Web (WWW) multicolor natural scenes. In order to query the database, the user specifies an object on which the same color attributes are evaluated and all similar looking images are exposed as the outcomes of the query.

Author 1: Md. Al-Amin Bhuiyan

Keywords: color indexing; HSV color model; color histogram; Minkowski distance metric; fuzzy clustering; Color Quantization

Paper 12: Multiple-Published Tables Privacy-Preserving Data Mining: A Survey for Multiple-Published Tables Techniques

Abstract: With large growth in technology, reduced cost of storage media and networking enabled the organizations to collect very large volume of information from huge sources. Different data mining techniques are applied on such huge data to extract useful and relevant knowledge. The disclosure of sensitive data to unauthorized parties is a critical issue for organizations which could be most critical problem of data mining. So Privacy preserving data mining (PPDM) has become increasingly popular because it solves this problem and allows sharing of privacy sensitive data for analytical purposes. A lot of privacy techniques were developed based on the k-anonymity property. Because of a lot of shortcomings of the k-anonymity model, other privacy models were introduced. Most of these techniques release one table for research public after they applied on original tables. In this paper the researchers introduce techniques which publish more than one table for organizations preserving individual's privacy. One of this is (a, k) – anonymity using lossy-Join which releases two tables for publishing in such a way that the privacy protection for (a, k)-anonymity can be achieved with less distortion, and the other one is Anatomy technique which releases all the quasi-identifier and sensitive values directly in two separate tables, met l-diversity privacy requirements, without any modification in the original table.

Author 1: Abou_el_ela Abdo Hussein

Author 2: Nagy Ramadan Darwish

Author 3: Hesham A. Hefny

Keywords: Data mining; privacy; sensitive attribute; quasi-identifier Anatomy

Paper 13: An Automated Graphical User Interface based System for the Extraction of Retinal Blood Vessels using Kirsch’s Template

Abstract: The assessment of Blood Vessel networks plays an important role in a variety of medical disorders. The diagnosis of Diabetic Retinopathy (DR) and its repercussions including micro aneurysms, haemorrhages, hard exudates and cotton wool spots is one such field. This study aims to develop an automated system for the extraction of blood vessels from retinal images by employing Kirsch’s Templates in a MATLAB based Graphical User Interface (GUI). Here, a RGB or Grey image of the retina (Fundus Photography) is used to obtain the traces of blood vessels. We have incorporated a range of Threshold values for the blood vessel extraction which would provide the user with greater flexibility and ease. This paper also deals with the more generalized implementation of various MATLAB functions present in the image processing toolbox of MATLAB to create a basic image processing editor with different features like noise addition and removal, image cropping, resizing & rotation, histogram adjust, separately viewing the red, green and blue components of a colour image along with brightness control, that are used in a basic image editor. We have combined both Kirsch’s Template and various MATLAB Algorithms to obtain enhanced images which would allow the ophthalmologist to edit and intensify the images as per his/her requirement for diagnosis. Even a non technical person can manage to identify severe discrepancies because of its user friendly appearance. The GUI contains very commonly used English Language viz. Load, Colour Contrast Panel, Image Clarity etc that can be very easily understood. It is an attempt to incorporate maximum number of image processing techniques under one GUI to obtain higher performance. Also it would provide a cost effective solution towards obtaining high definition and resolution images of blood vessel extracted Retina in economically backward regions where costly machine like OCT (Optical Coherence Tomography), MRI (Magnetic Resonance Imaging) are not available. Hence an early detection of irregularity will be possible especially in rural areas.

Author 1: Joshita Majumdar

Author 2: Souvik Tewary

Author 3: Shreyosi Chakraborty

Author 4: Debasish Kundu

Author 5: Sudipta Ghosh

Author 6: Sauvik Das Gupta

Keywords: Blood Vessel Extraction; Retinal Images; Kirsch’s Templates; Image Processing; Graphical User Interface

Paper 14: An Artificial Neural Network Application for Estimation of Natural Frequencies of Beams

Abstract: In this study, natural frequencies of the prismatical steel beams with various geometrical characteristics under the four different boundary conditions are determined using Artificial Neural Network (ANN) technique. In that way, an alternative efficient method is aimed to develop for the solution of the present problem, which provides avoiding loss of time for computing some necessary parameters. In this context, initially, first ten frequency parameters of the beam are found, where Bernoulli-Euler beam theory was adopted, and then natural frequencies are computed theoretically. With the aid of theoretically obtained results, the data sets are formed and ANN models are constructed. Here, 36 models are developed using primary 3 models. The results are found from these models by changing the number and properties of the neurons and input data. The handiness of the present models is examined by comparing the results of these models with theoretically obtained results. The effects of the number of neurons, input data and training function on the models are investigated. In addition, multiple regression models are developed with the data, and adjusted R-square is examined for determining the inefficient input parameters

Author 1: Mehmet Avcar

Author 2: Kemal Saplioglu

Keywords: natural frequency; beam; ANN; multiple regression; adjusted R-square

Paper 15: Fuzzy C-Means based Inference Mechanism for Association Rule Mining: A Clinical Data Mining Approach

Abstract: Association rule mining has wide variety of research in the field of data mining, many of association rule mining approaches are well investigated in literature, but the major issue with ARM is, huge number of frequent patterns cannot produce direct knowledge or factual knowledge, hence to find factual knowledge and to discover inference, we propose a novel approach AFIRM in this paper followed by two step procedure, first is to discover frequent pattern by Appling ARM algorithm and second is to discover inference by adopting the concept of Fuzzy c-means clustering, for performance analysis, we apply this approach on a clinical dataset (contained symptoms information of patients) and we got highly effected disease in a couple of months or in a session as hidden knowledge or inference.

Author 1: Kapil Chaturvedi

Author 2: Dr. Ravindra Patel

Author 3: Dr. D.K. Swami

Keywords: Association Rule Mining; Fuzzy Inference System; Clinical Data Mining; Preprocessing; Fuzzy clusters

Paper 16: Integration of Qos Aspects in the Cloud Service Research and Selection System

Abstract: Cloud Computing is a business model revolution more than a technological one. It capitalized on various technologies that have proved themselves and reshaped the use of computers by replacing their local use by a centralized one where shared resources are stored and managed by a third-party in a way transparent to end-users. With this new use came new needs and one of them is the need to search through Cloud services and select the ones that meet certain requirements. To address this need, we have developed, in a previous work, the Cloud Service Research and Selection System (CSRSS) which aims to allow Cloud users to search through Cloud services in the database and find the ones that match their requirements. It is based on the Skyline and ELECTRE IS. In this paper, we improve the system by introducing 7 new dimensions related to QoS constraints. Our work’s main contribution is conceiving an Agent that uses both the Skyline and an outranking method, called ELECTREIsSkyline, to determine which Cloud services meet better the users’ requirements while respecting QoS properties. We programmed and tested this method for a total of 10 dimensions and for 50 000 cloud services. The first results are very promising and show the effectiveness of our approach.

Author 1: Manar ABOUREZQ

Author 2: Abdellah IDRISSI

Keywords: Cloud Computing; Cloud Services; Quality of Service; Skyline; Outranking methods; Multi criteria decision; ELECTRE methods; Block-Nested Loops Algorithm

Paper 17: Cyberspace Forensics Readiness and Security Awareness Model

Abstract: The goal of reaching a high level of security in wire- less and wired communication networks is continuously proving difficult to achieve. The speed at which both keepers and violators of secure networks are evolving is relatively close. Nowadays, network infrastructures contain a large number of event logs captured by Firewalls and Domain Controllers (DCs). However, these logs are increasingly becoming an obstacle for network administrators in analyzing networks for malicious activities. Forensic investigators mission to detect malicious activities and reconstruct incident scenarios is extremely complex considering the number, as well as the quality of these event logs. This paper presents the building blocks for a model for automated network readiness and awareness. The idea for this model is to utilize the current network security outputs to construct forensically comprehensive evidence. The proposed model covers the three vital phases of the cybercrime management chain, which are: 1) Forensics Readiness, 2) Active Forensics, and 3) Forensics Awareness.

Author 1: Aadil Al-Mahrouqi

Author 2: Sameh Abdalla

Author 3: Tahar Kechadi

Keywords: Network Forensics; Forensics Readiness; Network Security; Active Forensics; Reactive Forensics; Forensics Awareness and Network Security model

Paper 18: Multi-Biometric Systems: A State of the Art Survey and Research Directions

Abstract: Multi-biometrics is an exciting and interesting research topic. It is used to recognizing individuals for security purposes; to increase security levels. The recent research trends toward next biometrics generation in real-time applications. Also, integration of biometrics solves some of unimodal system limitations. However, design and evaluation of such systems raises many issues and trade-offs. A state of the art survey of multi-biometrics benefits, limitations, integration strategies, and fusion levels are discussed in this paper. Finally, upon reviewing multi-biometrics approaches and techniques; some open points are suggested to be considered as a future research point of interest.

Author 1: Ramadan Gad

Author 2: Nawal El-Fishawy

Author 3: AYMAN EL-SAYED

Author 4: M. Zorkany

Keywords: Biometrics; Multimodal biometric systems; fusion levels; recognition methods; authentication

Paper 19: Application of Image Processing Techniques for TV Broadcasting of Sporting Events

Abstract: In this paper, we describe a system solution thanks to which virtual graphics, the projection of advertising images, logos, match scores and the distance measurements of players on the field may be overlaid on the plan of the different types of sports fields of real tested images. This solution relies on a study of the artificial vision and the Augmented Reality applied to TV broadcasting of sporting events where we have as input the original image to be processed, the image to be projected and the coordinates of the overlay position of the objects on the plan of the field. As an output, we have the overlaid objects in the processed image at the selected position in a more realistic way and in the background.

Author 1: Cheikhrouhu E.

Author 2: Jabri I.

Author 3: Lakhoua M.N.

Author 4: Mlouhi Y.

Author 5: Battikh T.

Author 6: Maalej L.

Keywords: Augmented Reality; Filtering; Sports field Homography; Image Processing

Paper 20: A Conceptual Framework of Analytical CRM in Big Data Age

Abstract: Traditionally, analytical CRM (A-CRM) mainly relies on the use of structured data from a data warehouse where data are extracted, transformed, loaded from operation systems such as ERP, SCM or operational CRM. In recent years of rising big data trend, recognized shifts in E-commerce have taken place from internet-enable commerce (I-commerce), to mobile commerce (M-commerce), and now to ubiquitous commerce (U-commerce). As theses paradigm shifts imply that ubiquitous computing improves considerably companies’ access to information by allowing them to acquire information at anytime, anywhere. Give this changes on data collection shifts due to ubiquitous computing, however, current A-CRM framework in literature seems not too matched to this change. There is only a handful studies published on CRM in ubiquitous computing environment fitting what big data age requires. Consequently, the objective of this study attempts to propose a conceptual framework of A-CRM. Built by conceptual framework approach, this framework provides valuable directions, definitions and guidelines to practitioners preparing the successful big data marketing in big data age.

Author 1: Chien-hung Liu

Keywords: CRM; Analytical CRM; Big Data; CRM Framework

Paper 21: Design of High Precision Temperature Measurement System based on Labview

Abstract: Using the LabVIEW software platform, a high precision temperature measuring device is designed based on the principle of the thermocouple. The system uses the STM32 MCU as the main control chip, using AD7076 analog digital converter. The converter has 8 channel, synchronous sampling, and bipolar input. Improving the precision of temperature measurement by cold end compensation, fitting and other measures. The test results show that, the device temperature measurement precision can reach ±0.1 °C, has the advantages of small size, high precision, and reliable performance, this high precision temperature measurement can be widely used in industrial production.

Author 1: Weimin Zhu

Author 2: Jin Liu

Author 3: Haima Yang

Author 4: Chaochao Yan

Keywords: LabVIEW; AD7076; thermocouple; cold end temperature compensation; Temperature measurement

Paper 22: Reasoning Method on Knowledge about Functions and Operators

Abstract: In artificial intelligence, there are many methods for knowledge representation. One of the effective models is the Computational Object Knowledge Base model (COKB model), which can be used to represent the total knowledge and to design the knowledge base component of practical intelligent systems. Besides, reasoning methods also play an important role in knowledge base systems. In fact, a popular form of knowledge domain is knowledge about function and operations. These knowledge domains have many practical applications, especially in educational applications, such as Solid Geometry, Analytic Geometry. However, the current methods cannot reason on knowledge about Function and Operators. In this paper, we will present a reasoning method to solve problems on COKB model. These problems are related to knowledge about Functions and Operators. Also, this method has been applied to design some intelligent systems in education. Using this reasoning method, systems can solve problems in some educational knowledge domains automatically with their solutions are step-by-step.

Author 1: Nhon V. Do

Author 2: Hien D. Nguyen

Author 3: Thanh T. Mai

Keywords: knowledge representation; knowledge based system; intelligent problem solver; automated reasoning

Paper 23: An Efficient Algorithm to Automated Discovery of Interesting Positive and Negative Association Rules

Abstract: Association Rule mining is very efficient technique for finding strong relation between correlated data. The correlation of data gives meaning full extraction process. For the discovering frequent items and the mining of positive rules, a variety of algorithms are used such as Apriori algorithm and tree based algorithm. But these algorithms do not consider negation occurrence of the attribute in them and also these rules are not in infrequent form. The discovery of infrequent itemsets is far more difficult than their counterparts, that is, frequent itemsets. These problems include infrequent itemsets discovery and generation of interest negative association rules, and their huge number as compared with positive association rules. The interesting discovery of association rules is an important and active area within data mining research. In this paper, an efficient algorithm is proposed for discovering interesting positive and negative association rules from frequent and infrequent items. The experimental results show the usefulness and effectiveness of the proposed algorithm.

Author 1: Ahmed Abdul-WahabAl-Opahi

Author 2: Basheer Mohamad Al-Maqaleh

Keywords: Association rule mining; negative rule and positive rules; frequent and infrequent pattern set; apriori algorithm

Paper 24: Technical Issues and Challenges in Building Human Body Sensor Networks

Abstract: In this research work, an exploration is done for identification of critical technical issues, problems, challenges in area of wireless body network sensors, which are continuous emerging as integral part of health monitoring systems. All this is possible due to the concept of ‘Internet of Things’ [5], in which day to day consumer devices, equipment are connected onto the network enabling information gathering and management of many vital signals. The first section gives introduction to wireless network developments in recent context, and then it is followed by discussion on existing work done in context of physical, Media access control and other aspects like energy consumption and security of such systems. The tabular summary on the gaps, limitations of Wireless body area network is done and based on this work; future directions are also suggested. Care has been taken to solicit high impact general paper for conducting this systematic study.

Author 1: Meghna Garg

Author 2: Manik Gupta

Keywords: Body Sensor Networks; MAC; Health Monitoring Systems; Internet of Things; Health Cloud; wireless biomedical sensor; wearable sensors; Energy optimization; motion-powered piezoelectric effect; Power consumption; time synchronization; Bandwidth utilization; memory; distributed storage; key management

Paper 25: Vague Set Theory for Profit Pattern and Decision Making in Uncertain Data

Abstract: Problem of decision making, especially in financial issues is a crucial task in every business. Profit Pattern mining hit the target but this job is found very difficult when it is depends on the imprecise and vague environment, which is frequent in recent years. The concept of vague association rule is novel way to address this difficulty. Merely few researches have been carried out in association rule mining using vague set theory. The general approaches to association rule mining focus on inducting rule by using correlation among data and finding frequent occurring patterns. In the past years data mining technology follows traditional approach that offers only statistical analysis and discovers rules. The main technique uses support and confidence measures for generating rules. But since the data have become more complex today, it’s a requisite to find solution that deals with such problems. There are certain constructive approaches that have already reform the ARM. In this paper, we apply concept of vague set theory and related properties for profit patterns and its application to the commercial management to deal with Business decision making problem.

Author 1: Vivek Badhe

Author 2: Dr. R.S Thakur

Author 3: Dr. G.S Thakur

Keywords: Association Rule Mining; Vague Association Rule Mining; Profit Pattern Mining

Paper 26: Using Moore Dijkstra Algorithm with Multi-Agent System to Find Shortest Path over Network

Abstract: finding the shortest path over network is very difficult and it is the target for much research, after many researches get the result in many of algorithm and many a mount based on the performance for these algorithm .Shortest paths problems are familiar problems in computer science and mathematics. In these problems, edge weights may represent distances, costs, or any other real-valued quantity that can be added along a path, and that one may wish to minimize. Thus, edge weights are real numbers and the specific operations used are addition to compute the weight of a path and minimum to select the best path weight. In this paper we use the Dijkstra's algorithm with new technique to find the shortest path over network to reduce the time we need to find the best path, in this paper we use node for network with the same value which can be use it to find the shortest path but this depend on the number of transition for every node when the node have high number then the node have the high priority to choose it by using this method we descries the time to find the short path .to make this algorithm more distinguish apply multi-agent system ( Automata with multiplicities ) to find the short path.

Author 1: Basem Alrifai

Author 2: Hind Mousa Al-Hamadeen

Keywords: multi-agent system; shortest paths problems; Dijkstra Algorithm; Automata with multiplicities

Paper 27: Erp Systems Critical Success Factors

Abstract: The Enterprise Resources Planning (ERP) systems are one of the highly complex systems in the information systems field; the implementations of this type of systems need a long time, high cost, and a lot of resources. Many factors affect the successful implementation of ERP system. The critical success factors (CSFs) can be categorized as general, ICT related and software engineering or system life cycle (SLC) related. This paper is a survey paper that identifies ERP systems CSFs in general and software engineering CSFs in specific. Also an agile methodology for ERP systems' implementations will be presented. Many existing ERP systems were surveyed and presented from ICT / software engineering point of view.

Author 1: Islam K. Sowan

Author 2: Radwan Tahboub

Keywords: ERP; Information and Communication Technology; System Life Cycle; Critical success factors; Agile methodology

Paper 28: Boosted Decision Trees for Lithiasis Type Identification

Abstract: Several urologic studies showed that it was important to determine the lithiasis types, in order to limit the recurrence residive risk and the renal function deterioration. The difficult problem posed by urologists for classifying urolithiasis is due to the large number of parameters (components, age, gender, background ...) taking part in the classification, and hence the probable etiology determination. There exist 6 types of urinary lithiasis which are distinguished according to their compositions (chemical components with given proportions), their etiologies and patient profile. This work presents models based on Boosted decision trees results, and which were compared according to their error rates and the runtime. The principal objectives of this work are intended to facilitate the urinary lithiasis classification, to reduce the classification runtime and an epidemiologic interest. The experimental results showed that the method is effective and encouraging for the lithiasis type identification.

Author 1: Boutalbi Rafika

Author 2: Farah Nadir

Author 3: Chitibi Kheir Eddine

Author 4: Boutefnouchet

Author 5: Tanougast Camel

Keywords: urinary lithiasis; classification; Boosting; Decision Trees

Paper 29: Meteosat Images Encryption based on AES and RSA Algorithms

Abstract: Satellite image Security is playing a vital role in the field of communication system and Internet. This work is interested in securing transmission of Meteosat images on the Internet, in public or local networks. To enhance the security of Meteosat transmission in network communication, a hybrid encryption algorithm based on Advanced Encryption Standard (AES) and Rivest Shamir Adleman (RSA) algorithms is proposed. AES algorithm is used for data transmission because of its higher efficiency in block encryption and RSA algorithm is used for the encryption of the key of the AES because of its management advantages in key cipher. Our encryption system generates a unique password every new session of encryption. Cryptanalysis and various experiments have been carried out and the results were reported in this paper, which demonstrate the feasibility and flexibility of the proposed scheme.

Author 1: Boukhatem Mohammed Belkaid

Author 2: Lahdir Mourad

Author 3: Cherifi Mehdi

Keywords: AES; RSA; MSG; satellite; encryption; keys

Paper 30: On a Flow-Based Paradigm in Modeling and Programming

Abstract: In computer science, the concept of flow is reflected in many terms such as data flow, control flow, message flow, information flow, and so forth. Many fields of study utilize the notion, including programming, communication (e.g., Shannon-Weaver communication model), software modeling, artificial intelligence, and knowledge representation. This paper focuses on two approaches that explicitly assert a flow-based paradigm: flow-based programming (FBP) and flowthing modeling (FM). The first is utilized in programming and the latter in modeling (e.g., software development). Each produces a diagrammatic representation, and these are compared. The purpose is to promote progress in a flow-based paradigm and its utilization in the area of computer science. The resultant analysis highlights the fact that FBP and FM can benefit from each other’s methodology.

Author 1: Sabah Al-Fedaghi

Keywords: flow-based programming; conceptual description; data flow; flowthing model

Paper 31: (AMDC) Algorithm for wireless sensor networks in the marine environment

Abstract: Data compression is known today as one of the most important enabling technologies that form the foundation of the majority of data applications and networks as we know them, including wireless sensor networks and the popular world wide net (internet). Marine data networks are gaining increasing interest in the research community due to the increasing request for data services over the sea. There are a very narrow range of available solutions because of the absence of infrastructure over such vast water surfaces. We have previously proposed applying MANET networks in the marine environment using VHF technology available on the majority of ships and vessels in order to gather different sensor data such as sea depth, temperature, wind speed and direction, etc. and send it to a central server to produce a public information map. We also discusses the gains and drawbacks of our proposal including the problem of low rate data transmission offered by VHF radio limited to 9.6 Kbps. In this paper we investigate the application of appropriate data quantization and compression techniques to the marine sensor data collected in order to reduce the burden on the channel links and achieve better transmission efficiency.

Author 1: Rabab J. Mohsin

Author 2: John Woods

Author 3: Mohammed Q. Shawkat

Keywords: Wireless sensor network, Mobile Ad hoc Network, Very High Frequency, Sensor.

Paper 32: An Adaptive Learning Mechanism for Selection of Increasingly More Complex Systems

Abstract: Recently it has been demonstrated that causal entropic forces can lead to the emergence of complex phenomena associated with human cognitive niche such as tool use and social cooperation. Here I show that even more fundamental traits associated with human cognition such as ‘self-awareness’ can easily be demonstrated to be arising out of merely a selection for ‘better regulators’; i.e. systems which respond comparatively better to threats to their existence which are internal to themselves. A simple model demonstrates how indeed the average self-awareness for a universe of systems continues to rise as less self-aware systems are eliminated. The model also demonstrates however that the maximum attainable self-awareness for any system is limited by the plasticity and energy availability for that typology of systems. I argue that this rise in self-awareness may be the reason why systems tend towards greater complexity.

Author 1: Fouad Khan

Keywords: Adaptive Learning, Complexity, Self-awareness, Good regulator theorem, Adaptive Selection

Paper 33: Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations

Abstract: This paper proposes a methodology to perform emotional states classification by the analysis of EEG signals, wavelet decomposition and an electrode discrimination process, that associates electrodes of a 10/20 model to Brodmann regions and reduce computational burden. The classification process were performed by a Support Vector Machines Classification process, achieving a 81.46 percent of classification rate for a multi-class problem and the emotions modeling are based in an adjusted space from the Russell Arousal Valence Space and the Geneva model.

Author 1: Adrian Rodriguez Aguinaga

Author 2: Miguel Angel Lopez Ramirez

Author 3: Maria del Rosario Baltazar Flores

Keywords: Emotions; Affective Computing; EEG; SVM; Wavelets;

Paper 34: Dynamic wireless charging of electric vehicles on the move with Mobile Energy Disseminators

Abstract: Dynamic wireless charging of electric vehicles (EVs) is becoming a preferred method since it enables power exchange between the vehicle and the grid while the vehicle is moving. In this article, we present mobile energy disseminators (MED), a new concept, that can facilitate EVs to extend their range in a typical urban scenario. Our proposed method exploits Inter-Vehicle (IVC) communications in order to eco-route electric vehicles taking advantage of the existence of MEDs. Combining modern communications between vehicles and state of the art technologies on energy transfer, vehicles can extend their travel time without the need for large batteries or extremely costly infrastructure. Furthermore, by applying intelligent decision mechanisms we can further improve the performance of the method.

Author 1: Leandros A. Maglaras

Author 2: Jianmin Jiang

Author 3: Athanasios Maglaras

Author 4: Frangiskos V. Topalis

Author 5: Sotiris Moschoyiannis

Keywords: Electric vehicle; Dynamic Wireless Charging; IVC; Cooperative Mechanisms

Paper 35: Energy consumption model over parallel programs implemented on multicore architectures

Abstract: In High Performance Computing, energy consump-tion is becoming an important aspect to consider. Due to the high costs that represent energy production in all countries it holds an important role and it seek to find ways to save energy. It is reflected in some efforts to reduce the energy requirements of hardware components and applications. Some options have been appearing in order to scale down energy use and, con-sequently, scale up energy efficiency. One of these strategies is the multithread programming paradigm, whose purpose is to produce parallel programs able to use the full amount of computing resources available in a microprocessor. That energy saving strategy focuses on efficient use of multicore processors that are found in various computing devices, like mobile devices. Actually, as a growing trend, multicore processors are found as part of various specific purpose computers since 2003, from High Performance Computing servers to mobile devices. However, it is not clear how multiprogramming affects energy efficiency. This paper presents an analysis of different types of multicore-based architectures used in computing, and then a valid model is presented. Based on Amdahl’s Law, a model that considers different scenarios of energy use in multicore architectures it is proposed. Some interesting results were found from experiments with the developed algorithm, that it was execute of a parallel and sequential way. A lower limit of energy consumption was found in a type of multicore architecture and this behavior was observed experimentally.

Author 1: Ricardo Isidro-Ramirez

Author 2: Amilcar Meneses Viveros

Author 3: Erika Hernandez Rubio

Keywords: Energy Consumption; Multicore Processors; Paral-lel Programs; Amdahl’s law

Paper 36: Graph-based Semi-Supervised Regression and Its Extensions

Abstract: In this paper we present a graph-based semi-supervised method for solving regression problem. In our method, we first build an adjacent graph on all labeled and unlabeled data, and then incorporate the graph prior with the standard Gaussian process prior to infer the training model and prediction distribution for semi-supervised Gaussian process regression. Additionally, to further boost the learning performance, we employ a feedback algorithm to pick up the helpful prediction of unlabeled data for feeding back and re-training the model iteratively. Furthermore, we extend our semi-supervised method to a clustering regression framework to solve the computational problem of Gaussian process. Experimental results show that our work achieves encouraging results.

Author 1: Xinlu Guo

Author 2: Kuniaki Uehara

Keywords: Semi-supervised learning; Graph-Laplacian; Re-gression; Gaussian Process; Feedback; Clustering

Paper 37: Influence of Nitrogen-di-Oxide, Temperature and Relative Humidity on Surface Ozone Modeling Process Using Multigene Symbolic Regression Genetic Programming

Abstract: Automatic monitoring, data collection, analysis and prediction of environmental changes is essential for all living things. Understanding future climate changes does not only helps in measuring the influence on people life, habits, agricultural and health but also helps in avoiding disasters. Giving the high emission of chemicals on air, scientist discovered the growing depletion in ozone layer. This causes a serious environmental problem. Modeling and observing changes in the Ozone layer have been studied in the past. Understanding the dynamics of the pollutants features that influence Ozone is ex-plored in this article. A short term prediction model for surface Ozone is offered using Multigene Symbolic Regression Genetic Programming (GP). The proposed model customs Nitrogen-di-Oxide, Temperature and Relative Humidity as the main features to predict the Ozone level. Moreover, a comparison between GP and Artificial Neural Network (ANN) in modeling Ozone is presented. The developed results show that GP outperform the ANN.

Author 1: Alaa F. Sheta

Author 2: Hossam Faris

Keywords: Air pollution; Surface Ozone; Multigene Sym-bolic Regression; Genetic Programming; Multilayer perceptron neural network; Prediction.

Paper 38: Video conference Android platform by your mobile phone

Abstract: Video conferencing is a visual and audio communications technology dedicated to Smartphones. It is based on the client-server communication model that this requires many limits since using the server. In this paper, we proposed a new communication model without going through the server (client-client), in addition, this model makes video conference used by mobile multimedia phones.

Author 1: Mr. Mohamed Khalifa

Author 2: Dr. Chaafa Hamrouni

Author 3: Pr. Mahmoud Abdellaoui

Keywords: videoconference; multimedia mobile phone; streaming; Smartphone; Server; Customers.

Paper 39: Implementation of Vision-based Object Tracking Algorithms for Motor Skill Assessments

Abstract: Assessment of upper extremity motor skills often involves object manipulation, drawing or writing using a pencil, or performing specific gestures. Traditional assessment of such skills usually requires a trained person to record the time and accuracy resulting in a process that can be labor intensive and costly. Automating the entire assessment process will potentially lower the cost, produce electronically recorded data, broaden the implementations, and provide additional assessment infor-mation. This paper presents a low-cost, versatile, and easy-to-use algorithm to automatically detect and track single or multiple well-defined geometric shapes or markers. It therefore can be applied to a wide range of assessment protocols that involve object manipulation or hand and arm gestures. The algorithm localizes the objects using color thresholding and morphological operations and then estimates their 3-dimensional pose. The utility of the algorithm is demonstrated by implementing it for automating the following five protocols: the sport of Cup Stacking, the Soda Pop Coordination test, the Wechsler Block Design test, the visual-motor integration test, and gesture recognition.

Author 1: Beatrice Floyd

Author 2: Kiju Lee

Keywords: Vision-based Object Tracking; Motor Skill Assess-ment; Multi-marker Tracking; Computer-based Assessment.

Paper 40: Maximizing Throughput of SW ARQ with Network Coding through Forward Error Correction

Abstract: Over the years, several techniques for improving throughput of wireless communication have been developed in order to cater for the ever increasing demand of high speed network service. However, these techniques can only give little improvement in performance because packets have to be delivered as is. As such researchers have begun thinking outside the box by proposing ideas that require relay nodes to temper packets’ contents in order to improve the throughput of a network. One of the state of the art techniques in this field is called Network Coding (NC). NC is a state of the art technique that allows relay nodes linearly combine two or more packets in a way they can be recovered upon reaching their destination. However, increasing packet size increases possibility of error affecting it. In this paper, the authors decide to investigate whether adding data recovery technique can improve the performance of a network that uses network coding, if it can, by how much can it? Is it worth the trouble? In order to answer these questions, the authors carried out a quantitative analysis of throughput in a Stop-and-Wait Automatic Repeat reQuest (SW-ARQ) data transmission system with Network Coding (NC) and Forward Error Correction (FEC). Vandermonde matrix is chosen as the coding technique for this research because it has both NC and data recovery characteristics. Python programming language is used to develop three Discrete Event Simulations: SW-ARQ without any NC, SW-ARQ with NC and SW-ARQ with NC and FEC. The obtained results show that SW-ARQ with NC and FEC is superior to traditional SW-ARQ in terms of throughput, especially in channels with high error rates.

Author 1: Farouq M. Aliyu

Author 2: Yahya Osais

Author 3: Ismail Keshta

Author 4: Adel Binajjaj

Keywords: Network Coding; Automatic repeat request (ARQ); Stop-and-Wait (SW); Vandermonde Matrix