Accepted Papers
  • Tracing Origins of Shuffling Genetic Sequences with Fast Biological Databases Scanning on GPU
    Mohamed Issa, Zagazig University,Egypt
    The data from next generation sequencing technologies has led to an explosion in the genome and protein sequence data available in the public databases. This data provides unique opportunities to study the molecular mechanisms of gene evolution: how new genes and proteins originate and how they diversify. A major challenge is to retrace the origin of extant genes or proteins, by searching the existing databases for related sequences and identifying evolutionary similarities. We have developed a new method, called GT-GPU (Gene Tracer with scanning biological databases on GPUs), designed especially to study the origin of new genes that might represent novel functions or phenotypic innovations. Gene Tracer takes advantage of the parallel processing power of GPUs to rapidly scan a biological sequences databases and find sequences that are similar to an input query sequence. GT-GPU is a highly efficient software solution to an important biological problem. A major advantage of our software is that it can be used to study important genetic events involving recombination of different ancestor sequences, such as gene fusion, retro-transposition or lateral gene transfer.
  • DNA-based design of Advanced Encryption Standard (AES)
    Mona Sabry, Taymoor Nazmy, Mohamed Hashem and M.Essam Khalifa,Ain Shams University,Egypt
    DNA cryptography is a new promising direction in cryptography research that emerged with the progress in DNA computing field. Traditional cryptographic systems have long legacy and are built on a strong mathematical and theoretical basis. So, an important perception needs to be developed that the DNA cryptography is not to negate the tradition, but to create a bridge between existing and new technology. The power of DNA computing will strengthen the existing security systems by opening up a new possibility of a hybrid cryptographic system. In our work, we are presenting the DNA-based implementation to “Advanced Encryption Standard” [AES]. We built our algorithm with all its specifications on DNA basis instead of bits in a way of making the algorithm a suitable candidate for implementation on DNA computers. Our algorithm kept the same security strength and robustness of the standard algorithm.
  • Ka-Band Substrate Integrated Waveguide Bend, Power Divider and Circulator
    Rahali Bouchra and Feham Mohammed,STIC laboratory -University Tlemcen,Algeria
    The Substrate Integrated Waveguide (SIW) technology is an attractive approach for the design of high performance microwave and millimeter wave components. It combines the advantages of planar technology, such as low fabrication costs, with the low loss inherent to the waveguide solution. In this study, a substrate integrated waveguide bend, power divider and circulator are conceived and optimized in Ka- band [26.5-40] GHz by Ansoft HFSS code. Thus, through this modeling, design considerations and results are discussed and presented. Attractive features including compact size and planar form make these devices structure easily integrated in planar circuits.
  • Solving Linear Systems Involved in Convex Programming Problems
    Yixun Shi,Bloomsburg University of Pennsylvania,USA
    Many interior point methods for convex programming solve an (n+m) by (n+m) linear system in each iteration. In this paper, two iterative methods for solving linear systems are combined together and embedded into interior point methods. Based on that, a hybrid algorithm for solving convex programming problems is proposed.
  • Uncertain Unstructured Data Management: Put All Apple In Nine Basket
    Manoj Kumar Jain and Manoj Jain,Tata Consultancy Services,India
    In recent era, “Big Data” has become a new universal term. Big Data is renovating science, engineering, medicine, healthcare, finance, business, and ultimately society itself. Big data has already takes place in the industry and, is altering the uncertain unstructured data management dramatically within the industry and its core business processes. It’s going to significantly impact on business and data management practices within the company [1]. The continued declining costs of storage and computing power will make big data attractive [3][4]. Dealing with big data requires your data management practices to understand and embrace the new reality. We hear the term “unstructured data” often. It’s evolved up as the enormous challenge of big data and often cited as the reason why traditional relational databases don’t meet the needs of Big Data. But the above specified point doesn’t describe the challenges faced by organization with unstructured data. While most research paper is only highlighting three Vs. of big data, but I believe there are “Nine V’s for uncertain unstructured Big Data Management, in this paper we are classifying the uncertain Unstructured Big Data Management into nine V’s
  • SAHI vs. Selenium: A Comparative Analysis
    Thanuja Janarthana Naidu, Nor Asyikin Basri and Saravanan Nagenthram,MIMOS Bhd,Malaysia
    Functional testing for wireless based graphic user interfaces is one of the most routine and basic quality verification and validation on telecommunication products. These tests are often done based on requirements and specifications set and defined by product designers and original equipment manufacturers. As manual testing consumes considerable resource, having various time-to-market periods and user scenarios, automation is vital for testing. There are several tools that could perform automation, so we have conducted a study on two of the most commonly used web automation testing tools to allow test engineers and web and wireless software developers to make an informed decision on which tools to use based on their needs and resource. Which tool would give the best user experience? Which is easier to learn and maintain? Which tool needs lesser test resources and how convenient would the setup be for multiple iteration testing cycles? These, among other questions are answered during the course of this white paper.
  • Logic Descriptions of Vague Ontology Concepts for Exact Reasoning
    Mustapha Bourahla,University of M'sila,Algeria.
    Ontologies representing knowledge, are expressed in well-defined formal languages for example, Ontology Web Language (OWL2), which are based on expressive description logics (as SROIQ(D) for OWL2). The ontology concepts are language adjectives referring the meaning of classes of objects. If the meaning is deficient (imprecise) we will face the problem of vague concepts. In this paper we propose a vagueness theory to express the vague concepts in OWL2 and an extension of the Tableau algorithm for reasoning over vague ontologies.
  • Weed classification : A survey on Different algorithms and Their Performances
    Anita Dixit1 and Dr. Nagathna Hegde2,1SDM College of Engineering and Technology,India and 2 Vasavi College of Engineering,India
    Weeds are one of the important factors which affect the yield of the crops. Detection of weeds in between the crops is very difficult task .Detecting the weed and spraying chemicals is tough task in terms of time consuming and cost intensive when it performed manually. Here site specific weed control is used to reduce the herbicide. This paper aims to classify weeds from crops using image processing techniques. Images of the crops are taken through remote sensing satellite. multi spectral satellite images are processed and classified through one of the algorithms discussed here different algorithms discussed are Bayesian, Decision Tree and SVM classifiers.
  • Frequency Measurements In Numeric Relay
    Prathibha and A.D Srinivasan,SJCE,India.
    Frequency is one of the most important parameters in power system operation because it can reflect the dynamic energy balance between load and generating power. So frequency is always regarded as an index of the operating practices and utilities can know the system energy balance situations by observing frequency variations. Frequency may vary very fast in the transient events such that it is difficult to track it accurately. Modern power systems are prone to harmonics and noise. Hence developing a reliable method that can measure frequency in presence of harmonics and noise is essential. With the advent of the microprocessor, more and more microprocessor-based equipments have been extensively used in frequency relays. Using such equipments is known to provide accurate, fast responding, economic and flexible solutions to measurement problems. To find the best algorithm for the implementation is a challenging job. Therefore in this project work, a precise digital algorithm based on recursive Discrete Fourier Transforms (DFT) to measure the frequency of a sinusoidal signal in presence of harmonics is proposed and it is compared with Zero Crossing Detection (ZCD) Technique to validate the claimed benefits of DFT. The proposed algorithm smartly detects the errors that arise when frequency deviates from the applied frequency. The simulation is done using MATLAB and simulated program for proposed algorithm is used for hardware implementation using PIC Microcontroller and TMS-DSP Processor.
  • Attacks on Digital Image Watermarks in the Discrete Wavelet Transform Domain
    Andreja Samcovic,University of Belgrade,Serbia
    In the last few years, a large number of schemes have been proposed for hiding copyright marks and other information in digital images. Watermaking is a potential method for protection of ownership rights on digital images. This paper presents a number of attacks that enable the information hidden by them to be removed or otherwise rendered unusable.
  • Effects of GOP on Multiview Video Coding over Error Prone Environment
    Abdulkareem Ibrahim and Abdul Sadka,Brunel University ,UK
    In this paper, an investigation of the effects of group of pictures on H.264 multiview video coding content over an error prone environment with varying packet loss rates is presented. We analyse the bitrate performance for different GOP and error rates to see the effects on the quality of the reconstructed multiview video. However, by analysing the multiview video content it is possible to identify an optimum GOP size depending on the type of application used. A comparison is demonstrated for the performances between widely known H.264 data partitioning error resilience technique and multi-layer data partitioning technique with different error rates and GOP in terms of their perceived quality. Our simulation results turned out that Multi-layer data partitioning technique shows a better performance at higher error rates with different GOP. Further experiments in this work have shown the effects of GOP in terms of visual quality and bitrate for different multiview video sequences.
  • Dual security in Digital Image Steganography using 14 squares Algorithm
    Milind Deshkar and Pravin Kulkarni,RCERT, India.
    In this paper the technique of cryptography and steganography. is proposed to hide useful data. Firstly, the data is encrypted using the proposed substitution cipher algorithm, and then the cipher text is embedded in the carrier image. We will be using only 2-bit combination at an instant. An index variable is found and then depending on its value, the selection of the bit position of the carrier image is decided and embedded. We get 2-levels of security due to both cryptography and steganography methods.
  • Email Encryption using Neural Cryptography
    Sudip Sahana1 and Prabhat Mahanti2,1BIT,India and 2UNB,Canada
    Tremendous growth of data and the astounding computational and analytical capacities started a number of trends in scalable machine learning techniques. To figure out the genuine behavior of very large unlabled real data, we require some refined scalable clustering algorithms. The size of the kernel matrix is the real problem while dealing with very large datasets. One approach to handle this problem is to consider the big data of size N as data streams and apply kernel fuzzy c-means clustering on currently available data of size n (n<<N). We propose an efficient sampling based streaming kernel fuzzy c-means clustering approach (sstKFCM) which further reduces the time and space consumption by requiring computations on only 2p2 elements (where p<<n). Our method presents a significant speedup on the previous streaming clustering algorithms using sampling techniques, without any significant penalty on accuracy. The effectiveness of proposed sstKFCM clustering approach over recently proposed stKFCM clustering is evaluated on two large benchmark datasets in terms of computational time and accuracy.
    The application was developed using agile methodology. It, met its objectives and successfully passed 91% of the final system test, recording that some limitations were discovered, the application needs further testing and can be implemented for particular company or university using their own maps or editing the maps in OSM (open street maps).
  • Studies On The Electrical Characteristics Of The Thermal Plant Electrostatic Precipitator
    Sharath Kumar M D and A.D. Srinivasan, SJCE, India.
    The Electrostatic Precipitators (ESP) have been used over half a century to control particulate emissions in many industries. ESP is the most efficient device to capture fly ash. They have a very high collection efficiency which can handle large exhaust gas volumes at high temperatures. Research is taken up at different dimensions (both simulation and experimental) involving study of V-I characteristics, effect of electrode configurations, load and ambient conditions on the working of ESP. Among them, studies involving V-I characteristics of an ESP have gained more importance. The performance of an ESP can be determined by V-I characteristics which will reflect upon the collection efficiency. In this paper, a new approach based on Finite Difference Method (FDM) is proposed for the simulation of V-I characteristics of an ESP under clean air and dust loaded conditions. Further, V-I measurements for one of the ESPs were conducted by the author at Raichur Thermal Power Station (RTPS) in India and the simulated results were compared with the measured ones. The clean air simulation result is validated with the published experimental data of Penny & Matick’s method. Also the present simulation for dust and clean air were verified with different values of electrode spacing and radius.
  • Molecular Dynamics Simulation Model Of Afm-Based Nanomachining
    Rapeepan Promyoo and Hazim El-Mounayri,IUPUI,USA
    This paper is designed to analyze the performance of a Hopfield neural network for storage and recall of fingerprint images. The study implements a form of unsupervised learning. The paper first discusses the storage and recall via hebbian learning and the problem areas or the efficiency issues involved and then the performance enhancement via the pseudo-inverse learning. Performance is measured with respect to storage capacity, recall of distorted or noisy patterns i.e. association of a noisy version of a stored pattern to the original stored pattern for testing the accretive behavior of the network and association of new or noisy / distorted patterns to some stored pattern.
  • Performance Analysis of Hopfield Neural Network as Associative Memory for Finger print Images.
    Manu Pratap Singh,Dr.B. R. Ambedkar University, India.
    The present paper explains briefly about the intelligent agents and its importance in the artificial intelligence. It discusses about an application which has used a hybrid agent, as combination of the task agent and intelligent agent which performs tasks intelligently to reduce the efforts and saves the time of the user, reminds the user of the scheduled meetings as well as autonomously emails the scheduled meetings so that the user can also gets the schedule in his inbox. Adding such kind of intelligent agents in the real time application can reduce a lot of time and effort by not doing useless tasks and only concentrating on the work which is important.
  • Year 2038 Problem : Y2K38
    Rawoof Ahamed and Saran Raj,Dhanalakshmi College of Engineering of Anna University, India
    Our world has been facing many problems but few seemed to be more dangerous. The most famous bug was Y2K. Then Y2K10 somehow, these two were resolved. now we are going to face Y2K38 bug. This bug will affect most embedded systems and other systems also which use signed 32 bit format for representing the date and time. From 1,january,1970 the number of seconds represented as signed 32 bit format.Y2K38 problem occurs on 19,january,2038 at 03:14:07 UTC (Universal Coordinated Time).After this time all bits will be starts from first i.e. the date will change again to 1,january,1970. There are no proper solutions for this problem.
  • 2D/3D topology in a GIS: Model of Multilevel Road Network
    Bessaa Brahim, Belhadj Aissa Mostefa and Belhadj Aissa Aichouche,USTHB,Algeria
    Representation of environmental reality in computer systems for action, management and decision requires the most realistic modeling possible entities constituting the landscape. However one of the problems encountered in 2D GI is the inability to model these entities according to their three-dimensional representation. In this context, we are interested in this work to the topological model of multilevel roads and we proposed a 2D/3D model to integrate in a GIS and facilitate the analysis of queries in car navigation.
  • Genetic Algorithm for Uncertainty Reduction in Data mining Task
    K.Sankar1 and V.Venkatachalam2 ,1Sri Venkateswara college of Engineering and Technology, India. and2 The KAVERY Engineering College, India.
    Ant Colony System (ACS) is competitive with other nature-inspired algorithms on some relatively simple problems. This project proposes an ant colony optimization algorithm for tuning generalization of fuzzy rule. The use of Ant Colony Optimization (ACO) for classification is investigated in depth, with the development of the AntMiner+ algorithm. AntMiner+ builds rule based classifiers, with a focus on the predictive accuracy and comprehensibility of the final models. The key differences between the proposed AntMiner+ and previous AntMiner versions are the usage of the better performing MAX-MIN ant system, a clearly defined and augmented environment for the ants to walk through, with the inclusion of the class variable to handle multi-class problems, and the ability to include interval rules in the rule list.
  • Network Performance Optimization through 6 to 4 tunnel Header Compression
    Dipti Chauhan and Sanjay Sharma,Maulana Azad National Institute of Technology,India.
    IPv6 is the next generation internet protocol which will eventually replace IPv4. These two protocols are not compatible with each other and it will take time to migrate towards IPv6, until then both the protocols need to coexist for a long time. The main overhead involved with both the protocols is header length of 20 bytes in case of IPv4 and of 40 bytes in case of IPv6. This will affect the network performance specially over tunneling mechanism where one header is encapsulated inside another. Header compression can be applied to compress the excess protocol headers to improve the performance of network. In this paper a study of header compression is applied over 6 to 4 tunnels to improve the performance of network and to enable smooth interoperation of internet.
  • Implementation and Performance Evaluation of Hybrid Multipath Routing Protocol for MANETs
    Jay Kumar Jain and Sanjay Sharma,Maulana Azad National Institute of Technology,India.
    Mobile ad hoc networks (MANETs) is a kind of distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary manner, During the last decade, the demand for ubiquitous data access and spontaneous data exchange has increased significantly and with predictions to grow even further in the future. To satisfy this increasing demand new protocols standards and products addressing wireless networking have emerged. Due to the dynamic network topology and resource constraints, designing an efficient routing algorithm in MANETs is challenging. We propose a new algorithm for MANET called Hybrid Multipath Progressive Routing Protocol for MANET (HMPRP). In this algorithm we improve the performance of a famous MANET routing protocols, known, the Ad-hoc On-demand Distance Vector routing protocol and use of their preferred properties to formulate a new Hybrid routing protocol using the received signal strength. The proposed routing algorithm will optimize the bandwidth usage of MANETs by reducing routing overload and overhead. HMPRP algorithm also extends the battery life of the mobile devices by reducing the required number of operations for route determination and for packet forwarding. This routing algorithm compared with the standard AODV, OLSR, and ZRP protocol.
  • Influencing Factors of Actual Use of Mobile Learning Connected with E-learning
    Young Ju Joo1, Sunyoung Joung2, Eugene Lim1, Miran Choi1 and Eui Kyoung Shin1,1Ewha Womans University ,The Republic of Korea and 2 Kookmin University,The Republic of Korea
    The purpose of current study is to propose discriminated management strategies for mobile learning environments after observing the effects of mobile self-efficacy on performance expectancy, effort expectancy, and social influence on intention of use; and those of facilitating conditions and intention of use on learners' actual use of mobile learning by adding mobile self-efficacy to the UTAUT model proposed by Venkatesh et al.(2003). To achieve the research purpose, we established hypotheses: whether mobile self-efficacy, performance expectancy, effort expectancy, social influence, and facilitating conditions affect intention of use; whether intention of use affect actual use by adding mobile self-efficacy to the UTAUT model. According to the current research results, the higher the mobile self-efficacy and performance expectancy, the higher becomes the intention of using mobile learning services. It was confirmed that the factors gave the significant indirect effects on the actual use by mediating the intention of use. It was also confirmed that the intention of use directly affect actual use. However, the current research reported that effort expectancy, social influence, and facilitation conditions did not give significant effects on the intention of using mobile learning services. The current research results will give lots of contributions in designing mobile learning environments.
  • Arabic Digit Recognition by Adaptive Network Based Fuzzy Inference System
    Samiya Silarbi,University of science and technology of oran mohamed boudiaf USTO-MB,Algeria
    This paper presents the application of Adaptive Network Based Fuzzy Inference System ANFIS on spoken Arabic digit recognition. The primary tasks of fuzzy modeling are structure identification and parameter optimization: the former determines the numbers of membership functions and fuzzy if-then rules while the latter identifies a feasible set of parameters under the given structure. However, the increase of input dimension, rule numbers will have an exponential growth and there will cause problem of “rule disaster”. Thus, determination of an appropriate structure becomes an important issue where subtractive clustering is applied to define an optimal initial structure and obtain small number of rules. The appropriate learning algorithm is performed on spoken Arabic digit dataset supervised type, a pre-processing of the acoustic signal and extracting the coefficients MFCCs parameters relevant to the recognition system. Finally, hybrid learning combines the gradient decent and least square estimation LSE of parameters network. The results obtained show the effectiveness of the method in terms of recognition rate and number of fuzzy rules generated.
  • Mobile Web-Based Student Integrated Information System
    Maria Cecilia Cantos, Lorena Rabago and Bartolome Tanguilig Iii,Technological Institute of the Philippines,Philippines
    This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in Lucena City, Philippines. The system was developed to help the students to check their academic result every end of the semester, make self-enlistment that would assist the students to manage their academic status that can be viewed in their mobile phones. This system would also help the dean to predict how many number of sections to be created for the next semester. Hill climbing algorithm was used as basis of the processes of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, and the prediction of number of sections to be created, in which this algorithm can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database
  • Towards A Spatiotemporal Decision Support System for Epidemiological Surveillance
    1,2 Fatima-zohra Younsi, 1Djamila Hamdadou, 2Omar Boussaid and 1Bouziane Beldjilali ,1University of Oran, Oran, Algeria and 2University of Lumière Lyon , France
    The sudden appearance and large scale disease is a signal of the onset of an epidemic. Given the very rapid spread of this latter, public health decision makers are mobilizing to fight and stop it by setting disposal several tools and media control. Despite the efforts, very few of these diseases are tackled. Indeed, health officials need a real geo-making tool for monitoring and surveillance. At present, there are many approaches and tools allowing to achieve a real epidemio-survaillence systems, but each approach has its own advantages and limits. The main goal of our paper is to propose a decision support system for disease surveillance based on two models. The first based on mathematical model and social network analysis to understand the mechanism of epidemic spread in a population. While the second based on a spatiotemporal analysis and visualization data on a region map.
  • PI-Fuzzy Rule Based Controller Design for Analysis and Performance Evaluation of DC Motor Speed Control
    Victor Dutta 1, Subhramitra Borkakati2, Deepjyoti Bora2 and Shahmeem Akhtar2,1University College of Dublin, Ireland2SMIT Mazitar, India
    This paper presents a proportional-integral (PI) Fuzzy rule based controller using Matlab for speed control of a dc motor. Also an analysis and performance evaluation of the proposed controller design has been carried out and presented in this paper. The fuzzy logic controller is designed using Fuzzy logic toolbox in Matlab, A mathematical model based on fundamental equations governing the operation of a dc motor has been obtained and used to design the motor model in Matlab Simulink. The simulation results of the PI-Fuzzy controller show control potentialities.
  • Comparison of Machine Learning Algorithms Based on Filipino-Vietnamese Speeches
    Hoa T. Le,Thai Nguyen University of Information & Communication Technology,Vietnam
    The people of different races may characterize what language they speak thus; they can identify voices of someone’s race just by listening and talking through conversation. This paper presents an efficient comparison of machine learning algorithm based on Filipino-Vietnamese speeches for tone classification using feature parameter. The system was trained using audio recorded speeches samples. Datasets were taken from multiple sessions involving 10 respondents; 5 (five) of which are Filipinos and 5 (five) Vietnamese. The respondents ask to read the paragraph and record their voices while reading the data. The empirical test shows that during the pre-processing of data records Vietnamese have longer range of duration as compared to Filipinos because of their manners of reading and intensity on accent-bearing syllables. In constructing the speech recognition model, four classification algorithms were used, namely KNN, Naïve-Bayes, SVM and Neural Network (MLP). The Evaluation of training set in terms of accuracy, correctly classified instances and incorrectly classified instances are evaluated the performance of the developed system. As the data established the result found out that SMO and MLP performed better for all the given datasets, with accuracy rates ranging from 99.49% to 99.62% for MLP, and 98.6 % to 99.11% for SMO. However, KNN algorithm turned out to be the lowest rate ranging from 94.748%.
  • A New Top-k Conditional XML Preference Queries
    Shaikhah Alhazmi and Mourad Ykhlef,King Saud University Kingdom of Saudi Arabia
    Preference querying technology is a very important issue in a variety of applications ranging from e-commerce to personalized search engines. Most of recent research works have been dedicated to this topic in the Artificial Intelligence and Database fields. Several formalisms allowing preference reasoning and specification have been proposed in the Artificial Intelligence domain. On the other hand, in the Database field the interest has been focused mainly in extending standard Structured Query Language (SQL) and also eXtensible Markup Language (XML) with preference facilities in order to provide personalized query answering. More precisely, the interest in the database context focuses on the notion of Top-k preference query and on the development of efficient methods for evaluating these queries. A Top-k preference query returns k data tuples which are the most preferred according to the user’s preferences. Of course, Top-k preference query answering is closely dependent on the particular preference model underlying the semantics of the operators responsible for selecting the best tuples. In this paper, we consider the Conditional Preference queries (CP-queries) where preferences are specified by a set of rules expressed in a logical formalism. We introduce Top-k conditional preference queries (Top-k CP-queries), and the operators BestK-Match and Best-Match for evaluating these queries will be presented.
  • Using ANN in Financial Markets Micro-Structure Analysis
    Octavio Salcedo Parra11 and Brayan Reyes2 ,1 Universidad Distrital Francisco Jose de Caldas, Colombia and 2 Intelligent Internet Research Group,Colombia
    The present document presents/displays a model of Neuronal Networks Artificial RNA for the prognosis of the rate of nominal change in Colombia, including flow orders and the differential of the interest rates like variables of entrance to the model. Additionally methodological conclusions from the traditional treatment of the series of time were extracted.
  • Performance Evaluation of Routing Protocol OSPFv3 on the link PE-CE on MPLS/VPN Environments.
    Octavio Salcedo Parra11 and Brayan Reyes2 ,1 Universidad Distrital Francisco Jose de Caldas, Colombia and 2 Intelligent Internet Research Group,Colombia
    First version 3 OSPFv3 have a key role. In the context of VPN, the routing protocol BGP is used to distribute the path client’s, the multi-protocol label switching MPLS is used to send the information packages through the network core in tunnel mode. Originally, only IPv4 was supported and expanded after support OSPFv2 and VPN IPv6. Based on the new specifications in order to support OSPFv3 as a routing protocol PE-CE and the current technological infrastructures begin the process of IPv6 deployment, these elements driving this research which evaluate the performance of routing protocol OSPFv3 on border scenarios MPLS/VPN/IPv6.
  • Multilingual Knowledge Acquisition, A Semantic Space As Pivot Language
    Souhila Boucham 1 and Hassina Aliane 2 ,1 USTHB University,Algeria and 2CERIST,Algeria
    In this paper, we propose an approach for multilingual knowledge acquisition in order to create a semantic space that will serve as pivot language for information retrieval. This language is used as a semantic indexing base adapted to trilingual corpus (Arabic, French and English) to characterize the documentary content by knowledge, not language-dependent documents . It is an entirely statistics-based, unsupervised, and language independent approach to multilingual information retrieval. To our knowledge, today, there is little work in the IRM using a parallel corpus for the translation phase . The proposed approach uses a parallel corpus, it combines surface analysis and statistical technique namely LSI in a novel way to break the terms of LSI down into units which correspond more closely to morphemes (character n-grams candidates of non-fixed length. ). Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. The objective is the integration of this proposed approach with a model of semantic representation of documents and query.
  • Exploring Folksonomy structure for personalizing the result merging process in distributed information retrieval
    Zakaria Saoud, Samir Kechid and Radia Amrouni,USTHB,Algeria
    In this paper we present a new personalized approach that integrates a social profile in distributed search system. The proposed approach exploits the social profile and the different relations between social entities to : (i) make a query expansion, (ii) personalize and improve the result merging process in distributed information retrieval.
  • Reversible Fragile Algorithm for Watermarking Relational Database Based on Multilevel Histogram Modification
    Amal Hamdy, Mohamed Hashem, Amal El-Shershaby and Sawsan Shouman,Ain Shams University,Egypt
    Watermarking is commonly used for content authentication and tamper detection in relational database. For some critical applications, such as medical systems, the fragile watermarking system should be based on a reversible data hiding scheme. Reversibility is the ability to regenerate the original relation from the watermarked relation. This paper proposes a reversible and blinded fragile watermarking technique to detect and localize database tampering using a multilevel histogram modification mechanism. In the proposed scheme more peak points are used for hiding secret bits, the hiding capacity is enhanced compared with those conventional methods based on one or two level histogram modification. Furthermore, the proposed scheme can also characterize the modifications to quantify the nature of tempering attacks based on evaluating the local characteristics of database relation like frequency distribution of bits. The experimental results demonstrate that tampered groups are correctly detected, and non-tampered data recovered with high quality.
  • Competency Model for Information Systems' Specialization Track Utilizing RIASEC and Values Search Models
    Risty Acerado and Lorena Rabago,Technological Institute of the Philippines,Philippines
    The proposed competency assessment framework will guide Information Systems students to identify which among the three of the offered tracks would be more suited for them to pursue according to their knowledge, skills, values and interests. Determining the track of specialization according to the values, interests, and competences of students would lead them to a successful career. The Holland's RIASEC model and the Values Search model of Bronwyn and Holt were used to determine the most dominant interest and most dominant values of the computing experts. Survey questionnaires were sent to industry computing experts particularly to Operations Manager, User Interface Designer, and Application Developer. Based on the survey results, the top three interests of Operations Manager are Social, Investigative, and Conventional; for the User Interface Designer, top three interests are Artistic, Social, and Enterprise; and, for the Application Developer top three interests are Realistic, Investigative, and Conventional. With regards to the dominating values of the computing experts, openness to change and self enhancement are the top values of application developer which both values got the highest score of 24 points. The user interface designer most dominating value is the openness to change which scored 33 points. While the top values of operations manager falls under the category of self-enhancement with a score of 35 points, which means achievement and power are their highest concerns. Based on the results of the survey utilizing RIASEC and Values Search Models, this paper will introduce the competency models for Operations Manager, User Interface Designer, and Application Developers. For future works, competency models can be implemented to an information system that will process the identification of Information Systems track to be recommended to the students.