IJACSA Volume 7 Issue 10 - thesai.org

IJACSA Volume 7 Issue 10

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: Encryption Algorithms for Color Images: A Brief Review of Recent Trends

Abstract: The recent years have witnessed rapid developments in the field of image encryption algorithms for secure color image processing. Image encryption algorithms have been classified in different ways in the past. This paper reviews the different image encryption algorithms developed during the period 2007-2015, highlighting their contrasting features. At the same time a broad classification of the said algorithms into: (1) full encryption algorithm and (2) partial encryption algorithm, each further sub-classified with respect to their domain orientations (spatial, frequency and hybrid domains) have been attempted. Efforts have also been made to cover different algorithms useful for color images of various color spaces like Red-Green-Blue (RGB), Hue-Saturation-Intensity (HSI), Cyan-Magenta-Yellow (CMY) etc. Chaotic cryptosystems, various transforms like wavelets, affine transforms etc. and visual cryptography systems are being discussed in detail.

Author 1: Anuja P Parameshwaran

Author 2: Wen-Zhan Song

Keywords: RGB; HIS; CMY; Chaotic cryptosystem; wavelets; affine transforms and visual cryptography

Paper 2: Characterizing the 2016 U.S. Presidential Campaign using Twitter Data

Abstract: This paper models the 2016 U.S. presidential campaign in the context of Twitter. The study analyzes the presidential candidates’ Twitter activity by crawling their real-time tweets. More than 16,000 tweets were observed in this work. We study the interactions between the politicians and their Twitter followers in the retweet and favorite networks. The most frequently mentioned unigrams are presented, which serve the best featuring the political focuses of a candidate. The mention network among the politicians was constructed by parsing the content of their tweets. In this paper, we also study the Twitter profile of the users who follow the presidential candidates. The gender ratio among the Twitter subscribers is examined using the government’s census data. We also investigate the geography of Twitter supporters for each candidate.

Author 1: Ignasi Vegas

Author 2: Tina Tian

Author 3: Wei Xiong

Keywords: Twitter; social networks; data mining

Paper 3: Pentaho and Jaspersoft: A Comparative Study of Business Intelligence Open Source Tools Processing Big Data to Evaluate Performances

Abstract: Regardless of the recent growth in the use of “Big Data” and “Business Intelligence” (BI) tools, little research has been undertaken about the implications involved. Analytical tools affect the development and sustainability of a company, as evaluating clientele needs to advance in the competitive market is critical. With the advancement of the population, processing large amounts of data has become too cumbersome for companies. At some stage in a company’s lifecycle, all companies need to create new and better data processing systems that improve their decision-making processes. Companies use BI Results to collect data that is drawn from interpretations grouped from cues in the data set BI information system that helps organisations with activities that give them the advantage in a competitive market. However, many organizations establish such systems, without conducting a preliminary analysis of the needs and wants of a company, or without determining the benefits and targets that they aim to achieve with the implementation. They rarely measure the large costs associated with the implementation blowout of such applications, which results in these impulsive solutions that are unfinished or too complex and unfeasible, in other words unsustainable even if implemented. BI open source tools are specific tools that solve this issue for organizations in need, with data storage and management. This paper compares two of the best positioned BI open source tools in the market: Pentaho and Jaspersoft, processing big data through six different sized databases, especially focussing on their Extract Transform and Load (ETL) and Reporting processes by measuring their performances using Computer Algebra Systems (CAS). The ETL experimental analysis results clearly show that Jaspersoft BI has an increment of CPU time in the process of data over Pentaho BI, which is represented by an average of 42.28% in performance metrics over the six databases. Meanwhile, Pentaho BI had a marked increment of the CPU time in the process of data over Jaspersoft evidenced by the reporting analysis outcomes with an average of 43.12% over six databases that prove the point of this study. This study is a guiding reference for many researchers and those IT professionals who support the conveniences of Big Data processing, and the implementation of BI open source tool based on their needs.

Author 1: Victor M. Parra

Author 2: Ali Syed

Author 3: Azeem Mohammad

Author 4: Malka N. Halgamuge

Keywords: Big Data; BI; Business Intelligence; CAS; Computer Algebra System; ETL; Data Mining; OLAP

Paper 4: Diagnosing Coronary Heart Disease using Ensemble Machine Learning

Abstract: Globally, heart disease is the leading cause of death for both men and women. One in every four people is afflicted with and dies of heart disease. Early and accurate diagnoses of heart disease thus are crucial in improving the chances of long-term survival for patients and saving millions of lives. In this research, an advanced ensemble machine learning technology, utilizing an adaptive Boosting algorithm, is developed for accurate coronary heart disease diagnosis and outcome predictions. The developed ensemble learning classification and prediction models were applied to 4 different data sets for coronary heart disease diagnosis, including patients diagnosed with heart disease from Cleveland Clinic Foundation (CCF), Hungarian Institute of Cardiology (HIC), Long Beach Medical Center (LBMC), and Switzerland University Hospital (SUH). The testing results showed that the developed ensemble learning classification and prediction models achieved model accuracies of 80.14% for CCF, 89.12% for HIC, 77.78% for LBMC, and 96.72% for SUH, exceeding the accuracies of previously published research. Therefore, coronary heart disease diagnoses derived from the developed ensemble learning classification and prediction models are reliable and clinically useful, and can aid patients globally, especially those from developing countries and areas where there are few heart disease diagnostic specialists.

Author 1: Kathleen H. Miao

Author 2: Julia H. Miao

Author 3: George J. Miao

Keywords: accuracy; adaptive Boosting algorithm; AUC; classifier; classification error; coronary heart disease; diagnosis; ensemble learning; F-score; K-S measure; machine learning; precision; prediction; recall; ROC; sensitivity; specificity

Paper 5: Backstepping Control of Induction Motor Fed by Five-Level NPC Inverter

Abstract: In this paper we will present a contribution to the backstepping control for induction motor (IM) based on the principle of Field Orientated Control (FOC). This law is established step by step while ensuring the stability of the machine in the closed loop, by a suitable choice of the function Lyapunov, In addition it is executed to assure the convergence the error´s speed tracking at all initials conditions are possible. Both the speed and the rotor flux are supposed obtained by sensors. The control of the IM by five-level NPC inverter generally uses Pulse-width modulation techniques (PWM). Finally, we represent some of the simulation results by simulations in Matlab/Simulink environment.

Author 1: Ali BOUCHAIB

Author 2: Abdellah MANSOURI

Author 3: Rachid TALEB

Keywords: Backstepping control; Five-level NPC inverter; Field orientated control; Induction motor

Paper 6: On Standards for Application Level Interfaces in SDN

Abstract: In this paper, authors discuss application level interfaces for Software Defined Networks. While the Application Programming Interfaces for the interaction with the hardware are widely described in Software Defined Networks, the software interfaces for applications received far less attention. However, it is obvious that interfaces to software applications are very important. Actually, application level interfaces should be one of the main elements in Software Defined Networks. It is a core feature. In this article, we want to discuss the issues of standardization of software interfaces for applications in Software Defined Networks area. Nowadays, there are several examples of unified Application Program Interfaces in the telecommunications area. Is it possible to reuse this experience for Software Defined Networks or Software Defined Networks standards are radically different? This is the main question discussed in this paper.

Author 1: Yousef Ibrahim Daradkeh

Author 2: Mujahed Aldhaifallah

Author 3: Dmitry Namiot

Author 4: Manfred Sneps-Sneppe

Keywords: SDN; REST API; Northbound interface; application

Paper 7: Impact of Domain Modeling Techniques on the Quality of Domain Model: An Experiment

Abstract: The unified modeling language (UML) is widely used to analyze and design different software development artifacts in an object oriented development. Domain model is a significant artifact that models the problem domain and visually represents real world objects and relationships among them. It facilitates the comprehension process by identifying the vocabulary and key concepts of the business world. Category list technique identifies concepts and associations with the help of pre defined categories, which are important to business information systems. Whereas noun phrasing technique performs grammatical analysis of use case description to recognize concepts and associations. Both of these techniques are used for the construction of domain model, however, no empirical evidence exists that evaluates the quality of the resultant domain model constructed via these two basic techniques. A controlled experiment was performed to investigate the impact of category list and noun phrasing technique on quality of the domain model. The constructed domain model is evaluated for completeness, correctness and effort required for its design. The obtained results show that category list technique is better than noun phrasing technique for the identification of concepts as it avoids generating unnecessary elements i.e. extra concepts, associations and attributes in the domain model. The noun phrasing technique produces a comprehensive domain model and requires less effort as compared to category list. There is no statistically significant difference between both techniques in case of correctness.

Author 1: Hiqmat Nisa

Author 2: Salma Imtiaz

Author 3: Muhammad Uzair Khan

Author 4: Saima Imtiaz

Keywords: Domain Model; UML; Experiment; Noun Phrasing Technique; Category List Technique

Paper 8: A New Selection Operator - CSM in Genetic Algorithms for Solving the TSP

Abstract: Genetic Algorithms (GAs) is a type of local search that mimics biological evolution by taking a population of string, which encodes possible solutions and combines them based on fitness values to produce individuals that are fitter than others. One of the most important operators in Genetic Algorithm is the selection operator. A new selection operator has been proposed in this paper, which is called Clustering Selection Method (CSM). The proposed method was implemented and tested on the traveling salesman problem. The proposed CSM was tested and compared with other selection methods, such as random selection, roulette wheel selection and tournament selection methods. The results showed that the CSM has the best results since it reached the optimal path with only 8840 iterations and with minimum distance which was 79.7234 when the system has been applied for solving Traveling Salesman Problem (TSP) of 100 cities.

Author 1: Wael Raef Alkhayri

Author 2: Suhail Sami Owais

Author 3: Mohammad Shkoukani

Keywords: Genetic Algorithm; Traveling Salesman Problem; Genetic Algorithm Operators; Clustering; Selection Operator

Paper 9: Automatic Detection of Omega Signals Captured by the Poynting Flux Analyzer (PFX) on Board the Akebono Satellite

Abstract: The Akebono satellite was launched in 1989 to observe the Earth’s magnetosphere and plasmasphere. Omega was a navigation system with 8 ground stations transmitter and had transmission pattern that repeats every 10 s. From 1989 to 1997, the PFX on board the Akebono satellite received signals at 10.2 kHz from these stations. Huge amounts of PFX data became valuable for studying the propagation characteristics of VLF waves in the ionosphere and plasmasphere. In this study, we introduce a method for automatic detection of Omega signals from the PFX data in a systematic way, it involves identifying a transmission station, calculating the delay time, and estimating the signal intensity. We show the reliability of the automatic detection system where we able to detect the omega signal and confirmed its propagation to the opposite hemisphere along the Earth’s magnetic field lines. For more than three years (39 months), we detected 43,734 and 111,049 signals in the magnetic and electric field, respectively, and demonstrated that the proposed method is powerful enough for the statistical analyses.

Author 1: I Made Agus Dwi Suarjaya

Author 2: Yoshiya Kasahara

Author 3: Yoshitaka Goto

Keywords: Auto-detection; Satellite; Signal processing; Wave Propagation; Plasmasphere

Paper 10: A New Methodology in Study of Effective Parameters in Network-on-Chip Interconnection’s (Wire/Wireless) Performance

Abstract: Network-on-Chip (NoC) paradigm has been proposed as an alternative bus-based schemes to achieve high performance and scalability in System-on-Chip (SoC) design. Performance analysis and evaluation of on-chip interconnect architectures are widely considered. Time latency and throughput are two very critical parameters which play vital role to improve the system performance. In this work, these two elements are evaluated in both wire and wireless approaches under different conditions for networks contain 64,512 and 1024 number of cores. There are number of parameters those have direct and indirect effects on the delay and throughput, among all, these four are chosen: routing algorithm, buffer size, virtual channel and subnet. Thus this work is clustered into two general parts, in the first section the effect of algorithms and buffer size are calculated and then later on in second part when switching from wire approach to wireless, it’s shown that, virtual channel and subnet are able to influence the performance of a network on chip positively under some circumstances. We don't concentrate on approach and techniques here. Our target in this paper is to determine the critical points, trade-off and study the effect of mentioned parameters on entire system. Evaluation is done by means of Booksim and Noxim simulators which are based on system C.

Author 1: Mostafa Haghi

Author 2: Kerstin Thurow

Author 3: Norbert Stoll

Author 4: Saed Moradi

Keywords: network on chip; on-chip interconnection; buffer size; virtual channel; subnet

Paper 11: Determining the Types of Diseases and Emergency Issues in Pilgrims During Hajj: A Literature Review

Abstract: Introduction: Every year 2-3 million pilgrims with different background and most of them are elderly from 184 countries in the world congregate in the holy place ‘Haram’ at Makkah in Saudi Arabia to perform Hajj. During the pilgrimage, they come across a great deal of rough and tough environment, physical hassle and mental stress. Due to the hardship of travel, fluctuation of weather, continuous walking during religious rites at specific time and sites, many pilgrims injury, feel tired, sick, and exhausted. These may also create complications and overburden the physiological functions including heart, chest, abdominal, and kidney of those who suffer from chronic diseases. Besides the problem of diseases, crowds could cause some other significant problems including missing and lost pilgrims, injuries, and even death. Objective: To determine the common health problems e.g. diseases and emergency incidents encountered by pilgrims during Hajj was the main objective of this study. Methods: An extensive literature review to determine the common health problems and emergency incidents during Hajj was conducted through a systematic literature review. Numerous scholarly databases were used to search for articles published related to health problems and emergency incidents during Hajj from 2008 to 2016. Eligible articles included case reports, experimental and non-experimental studies. Only thirty articles out of two hundred and sixty articles had met the specific inclusion criteria. Results: The analysis revealed that respiratory diseases include pneumonia, influenza, and asthma (73.33%) were the main health problems encountered by the pilgrims during Hajj followed by heat stroke or heat attack, sunlight effects (16.67%), cardiovascular disease, heart disease (10%). The analysis also revealed that emergency incidents include traffic accidents, and trauma was 3.33%. Notwithstanding the information given above, according to the analysis, the common health problems during Hajj are mainly divided into two categories: non-communicable diseases (62.5%) and communicable diseases (37.5%). IBM’s statistical package for the social sciences (SPSS) version 22 was used to analysis the result. Conclusion: Both communicable and non-communicable health issues are the most common health problems encountered by pilgrims during Hajj. But, due to lack of existing studies associated with this research area, a definite conclusion could not be made. However, our findings demonstrated the necessity of new research to find solutions to pilgrims’ health problems during Hajj.

Author 1: Shah Murtaza Rashid Al Masud

Author 2: Asmidar Abu Bakar

Author 3: Salman Yussof

Keywords: Hajj; pilgrims; health; communicable diseases; non-communicable diseases; emergency

Paper 12: Energy Efficient Routing Protocol for Maximizing Lifetime in Wireless Sensor Networks using Fuzzy Logic and Immune System

Abstract: Energy limitations has become fundamental challenge for designing wireless networks systems. One of the important and interested features is network lifetime. Many works have been developed to maximize wireless sensor network lifetime, in which one of the important work is routing. This paper proposes a new adaptive routing technique for prolonging the lifetime in wireless sensor networks by using Fuzzy-Immune System. The artificial immune system is used to solve the packet LOOP problem and to control route direction. While fuzzy logic system is used to determine the optimal path for sending data packets. The proposed routing technique seeks to determine the optimal route path from source to destination so that energy consumption is balanced. The proposed routing technique is compared with classical method. Simulation results demonstrate that the proposed technique shows significant increase in network lifetime of about 0.93. The proposed technique proved that energy consumption is well managed.

Author 1: Safaa Khudair Leabi

Author 2: Turki Younis Abdalla

Keywords: routing; fuzzy logic; artificial immune system; network lifetime; wireless sensor networks

Paper 13: A System Framework for Smart Class System to Boost Education and Management

Abstract: The large number of reasonably priced computers, Internet broadband connectivity and rich education content has created a global phenomenon by which information and communication technology (ICT) has used to remodel education. E-learning can be explained as the use of available information, computational and communication technologies to assist learning practice. In the modern world, education has become more universal, and people are looking for learning with simplicity and interest. Students are looking for more interactive and attractive learning style rather than old traditional style. Using technological learning, we can enhance the education system. We can deliver quality education to students as well as we can ease and uniform the process of education by using the modern technologies and methods. In this paper, we propose a smart class model to manage the entire educational activities and hence to enhance the quality of education.

Author 1: Ahmad Tasnim Siddiqui

Author 2: Mehedi Masud

Keywords: E-Learning; smart class system; quality education; higher education; enhanced education

Paper 14: A Coreference Resolution Approach using Morphological Features in Arabic

Abstract: Coreference resolution is considered one of the challenges in natural language processing. It is an important task that includes determining which pronouns are referring to which entities. Most of the earlier approaches for coreference resolution are rule-based or machine learning approaches. However, these types of approaches have many limitations especially with Arabic language. In this paper, a different approach to coreference resolution is presented. The approach uses morphological features and dependency trees instead. It has fivestages, which overcomes the limitations of using annotated datasets for learning or a set of rules. The approach was evaluatedusing our own customized annotated dataset and “AnATAr” dataset. The evaluation show encouraging results with average F1 score of 89%.

Author 1: Majdi Beseiso

Author 2: Abdulkareem Al-Alwani

Keywords: Coreference resolution; Anaphora; Alternative Approach; Arabic NLP; morphological features

Paper 15: User Intent Discovery using Analysis of Browsing History

Abstract: The search engine can retrieve the information from the web by using keyword queries. The responsibility of search engines is getting the relevant results that met with users’ search intents. Nowadays, all search engines provide search log of the user (queries logs, click information besides browsing history). The main objective of this work is to provide features that can help users during their web search by categorizing related browsing URLs together. That will be done by identifying intent groups for each URLs category, then identifying intent-segments for each intent group. Upon clustering the query categories, groups, and intent segments search engines can improve the representation of users’ search context behind the current query, this would help search engines to discover the user’s intents during the web search. Through the use of the normalized discounted cumulative gain (NDCG), the experimental results show the proposed method can improve the performance of the search engine.

Author 1: Wael K. Abdallah

Author 2: Aziza S. Asem

Author 3: Mohammed Badr Senousy

Keywords: component; Information Retrieval; Search Engines; Users’ Search Intents; Search Log and Browsing History

Paper 16: A Multi-Task Distributed Vision System Embedded on a Hex-Rotorcraft UAV

Abstract: In this paper, are presented the general architecture and implementation of a multi-task distributed vision system designed and embedded onboard a Hex-Rotorcraft UAV. The system uses multiple cheap heterogeneous cameras in order to perform various tasks such as: ground target pedestrian detection, tracking, creating panoramic images, video stabilization and streaming multiple data/video feeds over a wireless secure channel. In what follows, are discussed this multi-agent architecture designed to provide our UAV with an embedded intelligent vision system using autonomous agents entrusted with managing the previously listed functionalities. In addition to the cheap set of USB and module cameras, the presented vision system is composed of a Local Data Processing Module connected to each camera and a Central Module used to control the overall system, process the regrouped data and streams it to the ground station. The overall vision system has been tested in real flights and is still under improvements.

Author 1: Nadir Younes

Author 2: Boukhdir Khalid

Author 3: Moutaouakkil Fouad

Author 4: Hicham Medromi

Keywords: multi-agent architecture; image processing; real-time systems; target detection; panoramic images; target following; unmanned aerial vehicles (UAVs); vision systems

Paper 17: Trending Challenges in Multi Label Classification

Abstract: Multi label classification has become a very important paradigm in the last few years because of the increasing domains that it can be applied to. Many researchers have developed many algorithms to solve the problem of multi label classification. Nerveless, there are still some stuck problems that need to be investigated in depth. The aim of this paper is to provide researchers with a brief introduction to the problem of multi label classification, and introduce some of the most trending challenges.

Author 1: Raed Alazaidah

Author 2: Farzana Kabir Ahmad

Keywords: Challenges; Correlations among labels; Multi Label Classification

Paper 18: AAODV (Aggrandized Ad Hoc on Demand Vector): A Detection and Prevention Technique for Manets

Abstract: Security is a major concern that needs to be addressed in Mobile Adhoc Networks because of its vulnerable feature that includes infrastructureless environment, dynamic topology, and randomized node movement making MANETs prone to various network attacks. Synergetic attacks have raucous effects on MANETs as compared to particular single attack. Various algorithms and protocols have been designed and developed to meet the increasing demand of MANET security but there is still a room for improvement in order to make it more reliable and hassle-free communication. An AggrandizedAODV is presented in this paper to detect and prevent various synergistic and non-synergistic attacks.

Author 1: Abdulaziz Aldaej

Author 2: Tariq Ahamad

Keywords: MANET; AODV; Grayhole; Blackhole

Paper 19: Named Entity Recognition System for Postpositional Languages: Urdu as a Case Study

Abstract: Named Entity Recognition and Classification is the process of identifying named entities and classifying them into one of the classes like person name, organization name, location name, etc. In this paper, we propose a tagging scheme Begin Inside Last -2 (BIL2) for the Subject Object Verb (SOV) languages that contain postposition. We use the Urdu language as a case study. We compare the F-measure values obtained for the tagging schemes IO, BIO2, BILOU and BIL2 using Hidden Markov Model (HMM) and Conditional Random Field (CRF). The BIL2 tagging scheme results are better than the other three tagging schemes using the same parameters including bigram and context window. With HMM, the F-measure values for IO, BIO2, BILOU, and BIL2 are 44.87%, 44.88%, 45.14%, and 45.88%, respectively. With CRF, the F-measure values for IO, BIO2, BILOU, and BIL2 are 35.13%, 35.90%, 37.85%, and 38.39%, respectively. The F-measure values for BIL2 are better than those of previously reported techniques

Author 1: Muhammad Kamran Malik

Author 2: Syed Mansoor Sarwar

Keywords: IOB tagging; BIO tagging; BILOU tagging; IOE tagging; BIL2 tagging; NER for Resource-poor languages

Paper 20: Symbolism in Computer Security Warnings: Signal Icons & Signal Words

Abstract: Security warning is often encountered by the end users when they use their system. It is a form of communication to notify the users of possible consequences in the future. These threats have always been evolved with the advancement of technologies. The attacks threaten the end users with many harmful effects such as malware attacks. However, security warning keeps being ignored due to various reasons. One of the reasons is lack of attention towards warnings. The end users feels burden and treat security task as a secondary rather than primary task. To divert user’s mind to read and comprehend the security warnings, it is important to capture the user’s attention. Signal words and signal icons are important in the security warning as it is the elements that could help user to heed the warnings. A survey study has been conducted with 60 participants in regards to the perception towards attractiveness and understanding of the signal words and icons. It can be revealed that end users significantly feel that the icon with the exclamation marks is attractive and easy to understand. However, only one of three hypotheses is proven to be significant.

Author 1: Nur Farhana Samsudin

Author 2: Zarul Fitri Zaaba

Author 3: Manmeet Mahinderjit Singh

Author 4: Azman Samsudin

Keywords: security; signal icons; signal words; usable security; usability; warning

Paper 21: Cross Site Scripting: Detection Approaches in Web Application

Abstract: Web applications have become one of the standard platforms for service releases and representing information and data over the World Wide Web. Thus, security vulnerabilities headed to various type of attacks in web applications. Amongst those is Cross Site Scripting also known as XSS. XSS can be considered as one of the most popular type of threat in web security application. XSS occurs by injecting the malicious scripts into web application, and it can lead to significant violations at the site or for the user. This paper highlights the issues (i.e. security and vulnerability) in web application specifically in regards to XSS. In addition, the future direction of research within this domain is highlighted.

Author 1: Abdalla Wasef Marashdih

Author 2: Zarul Fitri Zaaba

Keywords: Web Application Security; Security; Software Security; Security Vulnerability; Cross Site Scripting; XSS; Genetic Algorithm; GA

Paper 22: A Parallel Fuzzy-Genetic Algorithm for Classification and Prediction

Abstract: One of the top challenging problems in data mining domain is the distributed data mining (DDM) and mining multi-agent data. In distributed environment, classical techniques require that the distributed data be first collected in a data warehouse which is usually either ineffective or infeasible. Hence, mining over decentralized data sources can overcome such issues. Rule-based classifiers involve sharp cutoffs for continuous attributes. Fuzzy Logic System (FLS) has features that make it an adequate tool for addressing this shortcoming effectively and efficiently. In this paper, a framework for a Parallel Fuzzy-Genetic Algorithm (PFGA) has been developed for classification and prediction over decentralized data sources. The model parameters are evolved using two nested genetic algorithms (GAs). The outer GA evolves the fuzzy sets whereas the inner GA evolves the fuzzy rules. During optimization, best rules are only distributed among agents to construct the overall optimized model. Several experiments have been conducted over many benchmark datasets. The experiment results show that the developed model has good accuracy and more efficient in performance and comprehensibility of linguistic rules compared to some models implemented in KEEL software tool.

Author 1: Hassan Abounaser

Author 2: Ihab Talkhan

Author 3: Ahmed Fahmy

Keywords: Fuzzy Classification; Rule-Base; Fuzzy Logic System (FLS); Genetic Algorithm; Distributed Data Mining (DDM)

Paper 23: Web Accessibility Challenges

Abstract: Despite the importance of web accessibility in recent years, websites remain partially or completely inaccessible to certain sectors of the population. This is due to several reasons, including web developers’ little or no experience in accessibility and the lack of accurate information about the best ways to quickly and easily identify accessibility problems using different Accessibility Evaluation Methods (AEMs). This paper surveys accessibility literature and presents a general overview of the primary challenges of accessibility barriers on websites. In this sense, we critically investigate main challenges forms related to accessibility including standards and guidelines (WCAG 2.0), during website’s design and development and during evaluation. Finally, a set of recommendations such as enforcing accessibility legislations are presented to overcome some challenges.

Author 1: Hayfa.Y. Abuaddous

Author 2: Mohd Zalisham Jali

Author 3: Nurlida Basir

Keywords: component; Website Accessibility; Disabilities; Accessibility challenges; WCAG 2.0; Accessibility automated tools

Paper 24: Tri-Band Fractal Patch Antenna for GSM and Satellite Communication Systems

Abstract: Due to their smaller size and light weighted structures patch antennas are accustomed in modern communication Technology. With additional size in reduction, micro strip antennas are commonly used in handsets, GPS receivers etc. This paper presents a novel design of fractal shape patch antenna using U-slot on patch and defected ground structure. Due to slots on patch and ground, tri-band resonating response is attained with maximum gain and directivity of 4.22dB and 6.51dBi showing high impedance bandwidth and radiation efficiency. The antenna showed good VSWR of 1.63 to 1.02 thus, showing high efficiency. As evident in the simulation results, the proposed antenna has been found useful for W-LAN, GSM, Radio Satellite, Fixed Satellite Services (RSS) & (FSS) and satellite communication systems.

Author 1: Saad Hassan Kiani

Author 2: Shahryar Shafique Qureshi

Author 3: Khalid Mahmood

Author 4: Mehr-e- Munir

Author 5: Sajid Nawaz Khan

Keywords: miniaturization; directivity; gain; slots; Bandwidth; VSWR

Paper 25: Strength of Crypto-Semantic System of Tabular Data Protection

Abstract: The strength of the crypto-semantic method (CSM) of text data protection based on the use of lexicographical systems in the form of applied linguistic corpora within the formally defined restrictions of selected spheres of applied uses has been analyzed. The levels of cryptographic strength provided by the crypto-semantic method of data protection with due regard of a cryptanalyst’s resource capabilities are determined. The conditions under which the CSM provides absolute guarantee of text data protection from confidentiality compromise are determined.

Author 1: Hazem (Moh'd Said) Abdel Majid Hatamleh

Author 2: Hassan Mohammad

Author 3: Roba mohmoud ali aloglah

Author 4: Saleh Ebrahim Alomar

Keywords: cipher key; cryptographic; data protection; crypto-semantic; lexicographical systems

Paper 26: New Speech Enhancement based on Discrete Orthonormal Stockwell Transform

Abstract: S-transform is an effective time-frequency representation which gives simultaneous frequency and time distribution information alike the wavelet transforms (WT). However, the ST redundantly doubles the dimension of the original data set and the Discrete Orthonormal S-Transform (DOST) can decrease the redundancy of S-transform farther. So, this paper aims to propose a new method to remove additive background noise from noisy speech signal using DOST which supplies a multi-resolution analysis (MRA) spatial-frequency representation of image processing and signal analysis. Hence, the performances of the applied speech enhancement technique have been evaluated objectively and subjectively in comparison with respect to many other methods in four background noises at different SNR levels.

Author 1: Safa SAOUD

Author 2: Souha BOUSSELMI

Author 3: Mohamed BEN NASER

Author 4: Adnane CHERIF

Keywords: MRA; Stockwell Transform; DOST; DWT; speech enhancement

Paper 27: SDME Quality Measure based Stopping Criteria for Iterative Deblurring Algorithms

Abstract: Deblurring from motion problem with or without noise is ill-posed inverse problem and almost all inverse problem require some sort of parameter selection. Quality of restored image in iterative motion deblurring is dependent on optimal stopping point or regularization parameter selection. At optimal point reconstructed image is best matched to original image and for other points either data mismatch occurs and over smoothing is resulted. The methods used for optimal parameter selection are formulated based on correct estimation of noise variance or with restrictive assumption on noise. Some methods involved heavy computation and produce delay in final output. In this paper we propose the method which calculate visual image quality of reconstructed image with the help of Second derivative like measure of enhancement (SDME) and helps to efficiently decide optimal stopping condition which has been checked for leading image deblurring algorithm. It do not require any estimation of noise variance or no heavy computation are needed. Simulation has been done for various images including standard images for different degradation and noise condition. For test leading deblurring algoritham of Blind and Semi-Blind deblurring of Natural Images using Alternate direction method of minimizer (ADMM) is considered. The obtained results for synthetically blurred images are good even under noisy condition with ? ISNR average values 0.2914 dB. The proposed whiteness measures seek powerful solution to iterative deblurring algorithms in deciding automatic stopping criteria.

Author 1: Mayana Shah

Author 2: U. D. Dalal

Keywords: Image deblurring; stopping point; Point Spread Function; Second derivative like measure of enhancement

Paper 28: Real Time Monitoring of Human Body Vital Signs using Bluetooth and WLAN

Abstract: The technology of telemedicine is emerging and advancing day by day, it is capable of taking the field of healthcare to a whole new level of personalization. A person can keep a close check on his/her health's critical signs and can receive suitable feedback if required,- to help maintain the best of health status with the help of Wireless Body Area Network (WBAN) concept. The sensor nodes can wirelessly communicate with any smart phone through an Android application to continuously monitor and have complete access to the medical data of the patient. Moreover it also aims to maintain an efficient electronic medical record of the person. Moreover, the consultant and the caretaker of the patient can have this important information remotely through an internet connection and provide with significant advice which encapsulates the term -smart first aid technology. In the proposed framework miniaturized sensors are worn on the body and non-intrusively monitor a person’s physiological state. The body vital signs (e.g.: heart rate, temperature etc.) are recorded through the sensor nodes and transmit to the smart phone via Bluetooth, where the data of vital signs is stored and will further transmitted to remote locations if needed.

Author 1: Najeed Ahmed Khan

Author 2: M. Ajmal Sawand

Author 3: Marium Hai

Author 4: Arwa Khuzema

Author 5: Mehak Tariq

Keywords: Telemedicine; smartphone; Vital signs; remote locations; photoplethysmography; e-health; medical telemetry

Paper 29: Analyzing Distributed Generation Impact on the Reliability of Electric Distribution Network

Abstract: With proliferation of Distribution Generation (DG) and renewable energy technologies the power system is becoming more complex, with passage of time the development of distributed generation technologies is becoming diverse and broad. Power system reliability is one of most vital area in electric power system which deals with continuous supply of power and customer satisfaction. Distribution network in power system contributed up to 80% of reliability problems. This paper analyzes the impact of Wind Turbine Generator (WTG) as a distribution generation source on reliability of distribution system. Injecting single WTG and close to load point has positive impact on reliability, while injecting multiple WTGs at single place has adverse impact on distribution system reliability. These analyses are performed on bus 2 of Roy Billinton Test System (RBTS).

Author 1: Sanaullah Ahmad

Author 2: Sana Sardar

Author 3: Babar Noor

Author 4: Azzam ul Asar

Keywords: Distribution Generation; Electric Power System Reliability; Wind Turbine Generator; Interruptions; Reliability Assessment

Paper 30: An Efficient and Robust High Efficiency Video Coding Framework to Enhance Perceptual Quality of Real-Time Video Frames

Abstract: Different level of compression on real-time video streaming has successfully reduced the storage space complexities and bandwidth constraints in the recent times. This paper aims to design and develop a novel concept towards the enhancement of perceptual quality of a real-time video frames. The proposed model has been experimented considering multi-level compression operation using H.265 where .avi moving frames standards play a crucial role. The study also applies a novel concept of High-efficiency video coding (HEVC) for adaptive live video streaming over a mobile network. The proposed study aims to formulate a multi-level optimization for HEVC to enhance the performance of both encoding and decoding mechanisms at the client as well as server side to ensure higher compression rate. The experimental outcomes also show that the proposed protocol achieves better performance ratio and overall; throughput in comparison with conventional H.263, H.264 by enhancing the perceptual quality of .avi format real-time video frames.

Author 1: Murthy SVN

Author 2: Sujatha B K

Keywords: H.265; HEVC; Video Coding; Compression

Paper 31: Time-Saving Approach for Optimal Mining of Association Rules

Abstract: Data mining is the process of analyzing data so as to get useful information to be exploited by users. Association rules is one of data mining techniques used to detect different correlations and to reveal relationships among data individual items in huge data bases. These rules usually take the following form: if X then Y as independent attributes. An association rule has become a popular technique used in several vital fields of activity such as insurance, medicine, banks, supermarkets… Association rules are generated in huge numbers by algorithms known as Association Rules Mining algorithms. The generation of huge quantities of Association Rules may be time-and-effort consuming this is the reason behind an urgent necessity of an efficient and scaling approach to mine only the relevant and significant association rules. This paper proposes an innovative approach which mines the optimal rules from a large set of Association Rules in a distributive processing way to improve its efficiency and to decrease the running time.

Author 1: Mouhir Mohammed

Author 2: Balouki Youssef

Author 3: Gadi Taoufiq

Keywords: MDPREF Algorithm; Association Rules mining; Data partitioning; Optimization (profitability, efficiency and Risks) ; Bagging

Paper 32: On the Improved Nonlinear Tracking Differentiator based Nonlinear PID Controller Design

Abstract: This paper presents a new improved nonlinear tracking differentiator (INTD) with hyperbolic tangent function in the state-space system. The stability and convergence of the INTD are thoroughly investigated and proved. Through the error analysis, the proposed INTD can extract differentiation of any piecewise smooth nonlinear signal to reach a high accuracy. The improved tracking differentiator (INTD) has the required filtering features and can cope with the nonlinearities caused by the noise. Through simulations, the INTD is implemented as a signal’s derivative generator for the closed-loop feedback control system with a nonlinear PID controller for the nonlinear Mass-Spring-Damper system and showed that it could achieve the signal tracking and differentiation faster with a minimum mean square error.

Author 1: Ibraheem Kasim Ibraheem

Author 2: Wameedh Riyadh Abdul-Adheem

Keywords: Nonlinear tracking differentiator; PID; Nonlinear mass-spring-damper; Lyapunov theory; Measurement noise

Paper 33: Automated Imaging System for Pigmented Skin Lesion Diagnosis

Abstract: Through the study of pigmented skin lesions risk factors, the appearance of malignant melanoma turns the anomalous occurrence of these lesions to annoying sign. The difficulty of differentiation between malignant melanoma and melanocytic naive is the error-bone problem that usually faces the physicians in diagnosis. To think through the hard mission of pigmented skin lesions diagnosis different clinical diagnosis algorithms were proposed such as pattern analysis, ABCD rule of dermoscopy, Menzies method, and 7-points checklist. Computerized monitoring of these algorithms improves the diagnosis of melanoma compared to simple naked-eye of physician during examination. Toward the serious step of melanoma early detection, aiming to reduce melanoma mortality rate, several computerized studies and procedures were proposed. Through this research different approaches with a huge number of features were discussed to point out the best approach or methodology could be followed to accurately diagnose the pigmented skin lesion. This paper proposes automated system for diagnosis of melanoma to provide quantitative and objective evaluation of skin lesion as opposed to visual assessment, which is subjective in nature. Two different data sets were utilized to reduce the effect of qualitative interpretation problem upon accurate diagnosis. Set of clinical images that are acquired from a standard camera while the other set is acquired from a special dermoscopic camera and so named dermoscopic images. System contribution appears in new, complete and different approaches presented for the aim of pigmented skin lesion diagnosis. These approaches result from using large conclusive set of features fed to different classifiers. The three main types of different features extracted from the region of interest are geometric, chromatic, and texture features. Three statistical methods were proposed to select the most significant features that will cause a valuable effect in diagnosis; Fisher score method, t-test, and F-test. The selected features of high-ranking score based on the statistical methods are used for the diagnosis of the two lesion groups using Artificial Neural Network (ANN), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) as three different classifiers proposed. The overall System performance was then measured in regards to Specificity, Sensitivity and Accuracy. According to the different approaches that will be mentioned later the best result was showen by the ANN designed with the feature selected according to fisher score method enables a diagnostic accuracy of 96.25% and 97% for dermoscopic and clinical images respectively.

Author 1: Mariam Ahmed Sheha

Author 2: Amr Sharwy

Author 3: Mai S. Mabrouk

Keywords: component; Pigmented Skin lesions; Color Space; Bounding box; local range; SVM; local range; KNN; ANN; Experimental models

Paper 34: Improved Association Rules Mining based on Analytic Network Process in Clinical Decision Making

Abstract: Association Rules Mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a problem of concern, as conventional mining algorithms often produce too many rules for decision makers to digest. In order to overcome this problem in clinical decision making, this paper concentrates on using Analytic Network Process method to improve the process of extracting rules. The rules provided by association rules, through group decision making of physicians and health experts, are used to organize and evaluate related features by analytic network process. The proposed method has been applied in the completed blood count based on real database. It generated interesting association rules useable and useful for medical diagnosis.

Author 1: Shakiba Khademolqorani

Keywords: Clinical Data Mining; Clinical Decision Making; Association Rules Mining; Analytic Network Process

Paper 35: A Novel Position-based Sentiment Classification Algorithm for Facebook Comments

Abstract: With the popularisation of social networks, people are now more at ease to share their thoughts, ideas, opinions and views about all kinds of topics on public platforms. Millions of users are connected each day on social networks and they often contribute to online crimes by their comments or posts through cyberbullying, identity theft, online blackmailing, etc. Mauritius has also registered a surge in the number of cybercrime cases during the past decade. In this study, a trilingual dataset of 1031 comments was extracted from public pages on Facebook. This dataset was manually categorised into four different sentiment classes: positive, negative, very negative and neutral, using a novel sentiment classification algorithm. Out of these 1031 comments, it was found that 97.8% of the very negative sentiments, 70.7% of the negative sentiments and 77.0% of the positive sentiments were correctly extracted. Despite the added complexity of our dataset, the accuracy of our system is slightly better than similar works in the field. The accuracy of the lexicon-based approach was also much higher than when we used machine learning techniques. The outcome of this research work can be used by the Mauritius Police Force to track down potential cases of cybercrime on social networks. Decisive actions can then be implemented in time.

Author 1: Khunishkah Surroop

Author 2: Khushboo Canoo

Author 3: Sameerchand Pudaruth

Keywords: sentiment analysis; Facebook; cybercrime; emoticons

Paper 36: Medical Image Fusion Algorithm based on Local Average Energy-Motivated PCNN in NSCT Domain

Abstract: Medical Image Fusion (MIF) can improve the performance of medical diagnosis, treatment planning and image-guided surgery significantly through providing high-quality and rich-information medical images. Traditional MIF techniques suffer from common drawbacks such as: contrast reduction, edge blurring and image degradation. Pulse-coupled Neural Network (PCNN) based MIF techniques outperform the traditional methods in providing high-quality fused images due to its global coupling and pulse synchronization property; however, the selection of significant features that motivate the PCNN is still an open problem and plays a major role in measuring the contribution of each source image into the fused image. In this paper, a medical image fusion algorithm is proposed based on the Non-subsampled Contourlet Transform (NSCT) and the Pulse-Coupled Neural Network (PCNN) to fuse images from different modalities. Local Average Energy is used to motivate the PCNN due to its ability to capture salient features of the image such as edges, contours and textures. The proposed approach produces a high quality fused image with high contrast and improved content in comparison with other image fusion techniques without loss of significant details on both levels: the visual and the quantitative.

Author 1: Huda Ahmed

Author 2: Emad N. Hassan

Author 3: Amr A. Badr

Keywords: Medical image fusion; pulse-coupled neural network; local average energy; non-subsampled contourlet transform

Paper 37: Dynamic Inertia Weight Particle Swarm Optimization for Solving Nonogram Puzzles

Abstract: Particle swarm optimization (PSO) has shown to be a robust and efficient optimization algorithm therefore PSO has received increased attention in many research fields. This paper demonstrates the feasibility of applying the Dynamic Inertia Weight Particle Swarm Optimization to solve a Non-Polynomial (NP) Complete puzzle. This paper presents a new approach to solve the Nonograms Puzzle using Dynamic Inertia Weight Particle Swarm Optimization (DIW-PSO). We propose the DIW-PSO to optimize a problem of finding a solution for Nonograms Puzzle. The experimental results demonstrate the suitability of DIW-PSO approach for solving Nonograms puzzles. The outcome results show that the proposed DIW-PSO approach is a good promising DIW-PSO for NP-Complete puzzles.

Author 1: Habes Alkhraisat

Author 2: Hasan Rashaideh

Keywords: Non-Polynomial Complete problem; Nonograms puzzle; Swarm theory; Particle swarms; Optimization; Dynamic Inertia Weigh

Paper 38: Conceptual Modeling in Simulation: A Representation that Assimilates Events

Abstract: Simulation is often based on some type of model of the evolved portion of the world being studied. The underlying model is a static description; the simulation itself is executed by generating events or dynamic aspects into the system. In this context, this paper focuses on conceptual modeling in simulation. It is considered the most important aspect in simulation modelling, at the same time it is thought the least understood The paper proposes a new diagrammatic language as a modeling representation in simulation and as a basis for a theoretical framework for associated notions such as events and flows. Specifically, operational semantics using events to define fine-grained activities are assimilated into the representation, resulting in an integration of the static domain description and the dynamic chronology of events (so-called process level). The resulting unified specification facilitates understanding of the simulation procedure and enhances understanding of basic notions such as things (entities), events, and flows (activities).

Author 1: Sabah Al-Fedaghi

Keywords: events; flow; conceptual modeling; simulation; diagrammatic language

Paper 39: Performance Improvement of Threshold based Audio Steganography using Parallel Computation

Abstract: Audio steganography is used to hide secret information inside audio signal for the secure and reliable transfer of information. Various steganography techniques have been proposed and implemented to ensure adequate security level. The existing techniques either focus on the payload or security, but none of them has ensured both security and payload at same time. Data Dependency in existing solution was reluctant for the execution of steganography mechanism serially. The audio data and secret data pre-processing were done and existing techniques were experimentally tested in Matlab that ensured the existence of problem in efficient execution. The efficient least significant bit steganography scheme removed the pipelining hazard and calculated Steganography parallel on distributed memory systems. This scheme ensures security, focuses on payload along with provisioning of efficient solution. The result depicts that it not only ensures adequate security level but also provides better and efficient solution.

Author 1: Muhammad Shoaib

Author 2: Zakir Khan

Author 3: Danish Shehzad

Author 4: Tamer Dag

Author 5: Arif Iqbal Umar

Author 6: Noor Ul Amin

Keywords: Steganography; LSB; Steganalysis; Parallel; Pipelining; Processing Efficient; Real time; Security

Paper 40: A Hybrid Algorithm based on Invasive Weed Optimization and Particle Swarm Optimization for Global Optimization

Abstract: In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the nature- inspired algorithm which is inspired by colonial behavior of weeds. Particle Swarm Optimization is a swarm base Algorithm that uses the swarm intelligence to guide the solution to the goal. IWO algorithm is the algorithm which is not benefit from swarm intelligence and PSO converges to the local optimums quickly. In order to benefit from swarm intelligence and avoidance from trapping in local solutions, new hybrid algorithm IWO and PSO has been proposed. To obtain the required results, the experiment on a set of benchmark functions was performed and compared with other algorithms. The findings based on the non-parametric tests and statistical analysis showed that HIWOPSO is a more preferable and effective method in solving the high-dimensional functions.

Author 1: Zeynab Hosseini

Author 2: Ahmad Jafarian

Keywords: Invasive weed optimization; Particle Swarm Optimization; Global optimization; Hybrid algorithm

Paper 41: A New Internal Model Control Method for MIMO Over-Actuated Systems

Abstract: A new design method internal model control is proposed for multivariable over-actuated processes that are often encountered in complicated industrial processes. Due to the matrix that is adopted to describe over-actuated system is not square, many classical multivariable control methods can be hardly applied in such system. In this paper, based on method of virtual outputs, a new internal model control method is proposed. The proposed method is applied to shell standard control problem (3 inputs and 2 outputs). The simulation results show that the robust controller can keep the set inputs without overshoot, steady state error, input tracking performance and disturbance rejection performance, the results are satisfactory have proved the effectiveness and reliability of the proposed method.

Author 1: Ahmed Dhahri

Author 2: Imen Saidi

Author 3: Dhaou Soudani

Keywords: internal model control (IMC); over-actuated multivariable system; inverse model; method of virtual outputs; disturbances rejections, stability; state error

Paper 42: Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics

Abstract: High Efficiency Video Coding (HEVC) or H.265 is currently the latest standard in video coding. While this new standard promises improved performance over the previous H.264/AVC standard, the complexity has drastically increased due to the various new improved tools added. The splitting of the 64x64 Largest Coding Unit (LCU) into smaller CU sizes forming a quad tree structure involves a significant number of operations and comparisons which imposes a high computational burden on the encoder. In addition, the improved Motion Estimation (ME) techniques used in HEVC inter prediction in order to ensure greater compression also contribute to the high encoding time. In this paper, a set of standard thresholds are identified based on the Mean Square (MS) of the residuals. These thresholds are used to terminate the CU splitting process and to skip some of the inter modes processing. In addition, CUs with large MS values are split at a very early stage. Experimental results show that the proposed method can effectively reduce the encoding time by 62.2% (70.8% for ME) on average, compared to HM 10, yielding a BD-Rate of only 1.14%.

Author 1: Kanayah Saurty

Author 2: Pierre C. Catherine

Author 3: Krishnaraj M. S. Soyjaudah

Keywords: HEVC; inter prediction; early termination scheme; complexity reduction; prediction residuals

Paper 43: Recovering and Tracing Links between Software Codes and Test Codes of the Open Source Projects

Abstract: One of the most important controversial issues in the design and implementation of software is the functionality of the designed system. With impressive efforts of different software teams in the field of the system, the primary concern of the developers is its proper and error free functioning of the whole system. Therefore, various tests are defined and designed to help software teams to produce error free software or software with minimum error rate. It is difficult but important to find a proper link between written test class and the class under the test. Discovering these links is useful for programmers to perform the Regression Test more efficiently. In this paper, we are trying to propose a model for the recovery of traceable links between test classes and the classes under the test. The presented model comprises four sections. Firstly, we retrieve the name of similar classes between the test class and source class. Afterward, we extract the complexity, Cyclomatic and design metrics from the source codes and the test classes. Finally, after creating a train set, we implement the data mining algorithms to find the potential relationship between unit tests and the classes under the test. One of the advantages of this method is its language independence; furthermore, the preliminary results show that the proposed method has a good performance.

Author 1: Amir Hossein Rasekh

Author 2: Amir Hossein Arshia

Author 3: Seyed Mostafa Fakhrahmad

Author 4: Mohammad Hadi Sadreddini

Keywords: Unit Testing; Source Code; Similarity; Software Engineering; Open Source; Data Mining

Paper 44: Software Requirements Conflict Identification: Review and Recommendations

Abstract: Successful development of software systems re-quires a set of complete, consistent and clear requirements. A wide range of different stakeholders with various needs and backgrounds participate in the requirements engineering process. Accordingly, it is difficult to completely satisfy the requirements of each and every stakeholder. It is the requirements engineer’s job to trade-off stakeholders’ needs with the project resources and constraints. Many studies assert that failure in understanding and managing requirements in general, and requirement conflicts in particular, are one of the main problems of exceeding cost and allocated time which in turn results in project failure. This paper aims at investigating the different reasons of re-quirements conflicts and the different types of requirements conflicts. It providing an overview of existing research works on identifying conflicts; and discussing their limitations in order to yield suggestions for improvement. Objective: To provide an overview of existing research studies on identifying software requirements conflict and identifying limitations and areas for improvement. Method: A comparative literature was conducted by assessing 20 studies dated from 2001 to 2014.

Author 1: Maysoon Aldekhail

Author 2: Azzedine Chikh

Author 3: Djamal Ziani

Keywords: software requirements; requirements engineering; requirements conflicts

Paper 45: Time Emotional Analysis of Arabic Tweets at Multiple Levels

Abstract: Sentiment and emotional analyses have recently become effective tools to discover peoples attitudes towards real-life events. While Many corners of the emotional analysis research have been conducted, time emotional analysis at expression and aspect levels is yet to be intensively explored. This paper aims to analyse people emotions from tweets extracted during the Arab Spring and the recent Egyptian Revolution. Analysis is done on tweet, expression and aspect levels. In this research, we only consider surprise, happiness, sadness, and anger emotions in addition to sarcasm expression. We propose a time emotional analysis framework that consists of four components namely annotating tweets, classifying at tweet/expression levels, clustering on some aspects, and analysing the distributions of people emo-tions,expressions, and aspects over specific time. Our contribution is two-fold. First, our framework effectively analyzes people emotional trends over time, at different fine-granularity levels (tweets, expressions, and aspects) while being easily adaptable to other languages. Second, we developed a lightweight clustering algorithm that utilizes the short length of tweets. On this problem, the developed clustering algorithm achieved higher results compared to state-of-the-art clustering algorithms. Our approach achieved 70.1% F-measure in classification, compared to 85.4% which is the state of the art results on English. Our approach also achieved 61.45% purity in clustering.

Author 1: Amr M. Sayed

Author 2: Samir AbdelRahman

Author 3: Reem Bahgat

Author 4: Aly Fahmy

Keywords: Emotional Analysis; Sentiment Analysis; Cluster-ing; Two-Step Classification; Time Analysis

Paper 46: Towards Multi-Stage Intrusion Detection using IP Flow Records

Abstract: Traditional network-based intrusion detection sys-tems using deep packet inspection are not feasible for modern high-speed networks due to slow processing and inability to read encrypted packet content. As an alternative to packet-based intrusion detection, researchers have focused on flow-based intrusion detection techniques. Flow-based intrusion detection systems analyze IP flow records for attack detection. IP flow records contain summarized traffic information. However, flow data is very large in high-speed networks and cannot be processed in real-time by the intrusion detection system. In this paper, an efficient multi-stage model for intrusion detection using IP flows records is proposed. The first stage in the model classifies the traffic as normal or malicious. The malicious flows are further analyzed by a second stage. The second stage associates an attack type with malicious IP flows. The proposed multi-stage model is efficient because the majority of IP flows are discarded in the first stage and only malicious flows are examined in detail. We also describe the implementation of our model using machine learning techniques.

Author 1: Muhammad Fahad Umer

Author 2: Muhammad Sher

Author 3: Imran Khan

Keywords: IP flows; Multi-stage intrusion detection; One-class classification; Multi-class classification

Paper 47: Unsupervised Morphological Relatedness

Abstract: Assessment of the similarities between texts has been studied for decades from different perspectives and for several purposes. One interesting perspective is the morphology. This article reports the results on a study on the assessment of the morphological relatedness between natural language words. The main idea is to adapt a formal string alignment algorithm namely Needleman-Wunsch’s to accommodate the statistical char-acteristics of the words in order to approximate how similar are the linguistic morphologies of the two words. The approach is unsupervised from end to end and the experiments show an nDCG reaching 87% and an r-precision reaching 81%.

Author 1: Ahmed Khorsi

Author 2: Abeer Alsheddi

Keywords: Arabic Language; Computational Linguistics; Morphological Relatedness; Semitic Morphology; Unsupervised Learning

Paper 48: FNN based Adaptive Route Selection Support System

Abstract: This paper presents Fuzzy Neural Network (FNN) based Adaptive Route Selection Support System (ARSSS) for assisting drivers of vehicles. The aim of the proposed ARSSS system is to select path based on shortest possible time. The proposed system intakes traffic information, such as volume to capacity ratio, traffic flow, vehicle queue length and green cycle length, passenger car unit etc using different types of sensor nodes, remote servers, CCTVs and the road information such as path length, signalized junctions, intersection points between source-destination pair are captured using GPS service. A FNN has been employed to select an optimal path having shortest time. The input parameters of FNN are distance, signal point delay, road type and traffic flow whereas the output parameter is path selection probability which paves the way to identify the best suitable path. The simulation result revels that FNN based ARSSS outperforms more accurate than that of other route selection support system (webster delay model) and artificial neural network (ANN) in estimating path delay.

Author 1: Saoreen Rahman

Author 2: M. Shamim Kaiser

Author 3: Mahtab Uddin Ahmmed

Keywords: GPS; Fuzzy Neural Network; Path delay; Signal Point Delay; Webster Delay Formula

Paper 49: Comparison of Inter-and Intra-Subject Variability of P300 Spelling Dictionary in EEG Compressed Sensing

Abstract: In this paper, we propose a new compression method for electroencephalographic signals based on the concept of compressed sensing (CS) for the P300 detection spelling paradigm. The method uses a universal mega-dictionary which has been found not to be patient-specific. To validate the proposed method, electroencephalography recordings from the competition for Spelling, BCI Competition III Challenge 2005 - Dataset II, have been used. To evaluate the reconstructed signal, both quantitative and qualitative measures were used. For qualitative evaluation, we used the classification rate for the observed character based on P300 detection in the case of the spelling paradigm applied on the reconstructed electroencephalography signals, using the winning scripts (Alain Rakotomamonjy and Vincent Guigue). While for quantitative evaluation, distortion measures between the reconstructed and original signals were used.

Author 1: Monica Fira

Author 2: Liviu Goras

Keywords: Biomedical signal processing; Brain-computer interfaces; Compressed sensing; Classification algorithms; Electroencephalography

Paper 50: A Frame Size Adjustment with Sub-Frame Observation for Dynamic Framed Slotted Aloha

Abstract: In this paper, a simple frame size adjustment of dynamic framed slotted Aloha for tag identification in RFID networks is proposed. In dynamic framed slotted Aloha, the reader is required to announce the frame size for every frame. To achieve maximum system efficiency, it is essential to set the frame size according to the number unidentified tags appropriately. The proposed approach utilizes the information from a portion of the frame to adjust the size of the next frame. Simulation results show that the smaller number of observed slots results in faster frame adjustment and higher throughput. Compared to the existing anti-collision algorithms, the proposed approach achieves higher throughput and higher identification rate.

Author 1: Robithoh Annur

Author 2: Suvit Nakpeerayuth

Keywords: anti-collision tag identification; RFID; Framed slot-ted Aloha; frame adjustment

Paper 51: Evaluating Mobile Phones and Web Sites for Academic Information Needs

Abstract: In the last decade, there has been an exponential growth in use of mobile phones among people. Smart phone invention has digitized life of a common man especially after introduction of 3G/4G technology. People are used to use Internet on the move because of this advancement in technology. This advancement has also motivated usability design researchers to propose more usable designs for both smart phones and web sites. This work focuses on evaluation of web usability of mobile phones as well as usability of university web sites. Evaluation is performed on the most popular mobile phones required by the most common mobile users. Selection of the most popular mobile devices, the most common mobile users and their web usage is done by conducting a very detailed survey in the local market. Survey concludes that students and labors are the most common buyers of mobile phones and we choose three mobiles phones from the category of most popular phones that are iPhone (iPhone 4 precisely), Q-Mobile (Q Mobile A35) and Windows phone (Lumia 535). Six participants (three male and three females) are selected for fully detailed and rigorous task-based usability testing with “think aloud” technique. Task scenarios are defined to evaluate the usability of both i.e. smart phones and chosen university web sites. From results of usability testing, we find out that iPhone has better usability design as far as its response time is concerned while Q Mobile ranks second and Microsoft Windows phone takes last position in this ranking. Usability evaluation of university web sites on these mobile phones concludes that web site of Islamia university of Bahawalpur (I.U.B, Bahawalpur) has better mobile usability design and Bahauddin Zakariya university (BZU, Multan) and NFC Institute of Engineering and Technology NFCIET, Multan) second and third respectively and while web site of Institute of Southern Punjab (ISP, Multan) comes last when measured in terms of task completion time. All tests are performed on wireless network when internet download speed is between 3MBPS to 3.2MBPS.

Author 1: Muhammad Farhan

Author 2: Malik Muhammad Saad Missen

Author 3: Nadeem Akhtar

Author 4: Muhammad Ali Nizamani

Author 5: Amnah Firdous

Author 6: Hina Asmat

Keywords: Usability Engineering; Smart Phones; Academic information need

Paper 52: Feasibility Study of Optical Spectroscopy as a Medical Tool for Diagnosis of Skin Lesions

Abstract: Skin cancer is one of the most frequently en-countered types of cancer in the Western world. According to the Skin Cancer Foundation Statistics, one in every five Americans develops skin cancer during his/her lifetime. Today, the incurability of advanced cutaneous melanoma raises the importance of its early detection. Since the differentiation of early melanoma from other pigmented skin lesions is not a trivial task, even for experienced dermatologists, computer aided diagnosis could become an important tool for reducing the mortality rate of this highly malignant cancer type. In this paper, a computer aided diagnosis system based on machine learning is proposed in order to support the clinical use of optical spectroscopy for skin lesions quantification and classification. The focuses is on a feasibility study of optical spectroscopy as a medical tool for diagnosis. To this end, data acquisition protocols for optical spectroscopy are defined and detailed analysis of feature vectors is performed. Different tech-niques for supervised and unsupervised learning are explored on clinical data, collected from patients with malignant and benign skin lesions.

Author 1: Asad Saf

Author 2: Sheikh Ziauddin

Author 3: Alexander Horsch

Author 4: Mahzad Ziai

Author 5: Victor Castaneda

Author 6: Tobias Lasser

Author 7: Nassir Navab

Keywords: Melanoma; Classification; Supervised Learning; Computer–Aided Diagnosis; Machine Learning; Optical Spec-troscopy