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IJACSA Volume 9 Issue 12

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: Validation of the Proposed Hardness Analysis Technique for FPGA Designs to Improve Reliability and Fault-Tolerance

Abstract: Reliability and fault tolerance of FPGA systems is a major concern nowadays. The continuous increase of the system’s complexity makes the reliability evaluation extremely difficult and costly. Redundancy techniques are widely used to increase the reliability of such systems. These techniques provide a large area & time overheads which cause more power consumption and delay, respectively. An experimental evaluation method is proposed to find critical nodes of the FPGA-based designs, named “hardness analysis technique” under the proposed RASP-FIT tool. After finding the critical nodes, the proposed redundant model is applied to those locations of the design and the code is modified. The modified code is functionally equivalent and is more hardened to the soft-errors. An experimental set-up is developed to verify and validate the criticality of these locations found by using hardness analysis. After applying redundancy to those loca-tions, the reliability is evaluated concerning failure rate reduction. Experimental results on ISCAS’85 combinational benchmarks show that a min-max range of failure reduction (14%-85%) is achieved compared to the circuit without redundancy under the same faulty conditions, which improves reliability.

Author 1: Abdul Rafay Khatri
Author 2: Ali Hayek
Author 3: Josef B¨orcs¨ok

Keywords: Dependability; fault injection; fault tolerance; reli-ability; single event effects

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Paper 2: Utilization of a Neuro Fuzzy Model for the Online Detection of Learning Styles in Adaptive e-Learning Systems

Abstract: After conducting a historical review and establi-shing the state of the art of the various approaches regarding the design and implementation of adaptive e–learning systems—taking into consideration the characteristics of the user, in particular their learning styles and preferences in order to focus on the possibilities for personalizing the ways of utilizing learning materials and objects in a manner distinct from what e–learning systems have traditionally been, which is to say designed for the generic user, irrespective of individual knowledge and learning styles— the authors propose a system model for the classification of user interactions within an adaptive e–learning platform, and its analysis through a mechanism based on backpropagation neural networks and fuzzy logic, which allow for automatic, online identification of the learning styles of the users in a manner which is transparent for them and which can also be of great utility as a component of the architecture of adaptive e–learning systems and knowledge-management systems. Finally, conclusions and recommendations for future work are established.

Author 1: Luis Alfaro
Author 2: Claudia Rivera
Author 3: Jorge Luna-Urquizo
Author 4: Elisa Castaneda
Author 5: Francisco Fialho

Keywords: e-Learning; learning style identification; backpro-pagation neural network; fuzzy logic; neuro fuzzy systems

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Paper 3: An Optimal Control Load Demand Sharing Strategy for Multi-Feeders in Islanded Microgrid

Abstract: For the operation of autonomous microgrid (MG), an essential task is to meet the load demand sharing using multiple distributed generation (DG) units. The conventional droop control methods and its numerous variations have been developed in the literature in order to realize proportional power sharing amongst such multiple DG units. However, the conventional droop control strategies are subjected to power sharing error because of non-trivial feeder impedances of medium-voltage MGs. Further, complex MGs configurations (mesh or looped networks) usually make to reactive power sharing and system voltage regulation more challenging. This paper presents an optimal control strategy in order to perform the proportional power sharing and voltage regulation for multiple feeders in islanded AC MGs. The case study simulation for optimizing the power sharing and voltage regulations in proposed control strategy has been verified through using MATLAB/Simulink systems.

Author 1: Muhammad Zahid Khan
Author 2: Muhammad Mansoor Khan
Author 3: Xu Xiangming
Author 4: Umar Khalid
Author 5: Muhammad Ahmed Usman Rasool

Keywords: Optimal control; power sharing; voltage regulation; MG

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Paper 4: Modeling of the Consensus in the Allocation of Resources in Distributed Systems

Abstract: When it comes to processes distributed in process nodes that access critical resources shared in the modality of distributed mutual exclusion, it is important to know how these are managed and the order in which the demand for resources is resolved by the processes. Being in a shared environment, it is necessary to comply with certain rules, for instance, access to resources must be achieved through mutual exclusion. In this work, through an aggregation operator, a consensus mechanism is proposed to establish the order of allocation of resources to the processes. The consensus is understood as the agreement that must be achieved for the allocation of all the resources requested by each process. To model this consensus, it must be taken into account that the processes can form group of processes or be independent, the state of the nodes where each of them is located, the computational load, the number of processes, the priorities of the processes, CPU usage, use of main memory, virtual memory, etc. These characteristics allow the evaluation of the conditions to agree on the order in which allocations of resources to processes will be made.

Author 1: Federico Agostini
Author 2: David L. La Red Martínez
Author 3: Julio C. Acosta

Keywords: Aggregation operators; communication between groups of processes; mutual exclusion, operating systems; processor scheduling

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Paper 5: 3D Printing of Personalized Archwire Groove Model for Orthodontics: Design and Implementation

Abstract: In traditional dental treatment, archwires are bent by orthodontists using standard methods. However, the standard models cater to patients with common oral problems, and are unsuitable for personalized orthodontic treatment, which is highly desired in many cases. A method to prepare a personalized archwire groove model is, undoubtedly, useful for orthodontic treatment in clinical diagnosis. In this study, a three-dimensional (3D) printing technology is demonstrated to achieve the personalized archwire groove model in a rapid, computed tomography image compatible manner, to assist orthodontists. This method is expected to improve the efficiency and accuracy of archwire bending and the resultant product can distribute the uniform dentofacial stress, improve the wearing comfort of the patient and further shorten the period of treatment and repair of the tooth.

Author 1: Gang Liu
Author 2: He Qin
Author 3: Haiyan Zhen
Author 4: Bin Liu
Author 5: Xiaolong Wang
Author 6: Xinyao Tao

Keywords: 3D Printing; personalized; archwire groove model; orthodontic treatment

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Paper 6: Software vs Hardware Implementations for Real-Time Operating Systems

Abstract: In the development of the embedded systems a very important role is played by the real-time operating system (RTOS). They provide basic services for multitasking on small microcontrollers and the support to implement the deadlines imposed by critical systems. The RTOS used can have important consequences in the performance of the embedded system. In order to eliminate the overhead generated by RTOS, the RTOS primitives have begun to be implemented in hardware. Such a solution is the nMPRA architecture (Multi Pipeline Register Architecture - n degree of multiplication) that implements in hardware of all primitives of an RTOS. This article makes a comparison between software RTOS and nMPRA systems in terms of response time to an external event. For comparison, we use three of the most commonly used RTOS in developing embedded systems: FreeRTOS, uC/OS-III and Keil RTX. These RTOSs are executed on a microcontroller that works at the same frequency as the implementations of the nMPRA architecture on a FPGA system.

Author 1: Nicoleta Cristina GAITAN
Author 2: Ioan Ungurean

Keywords: Embedded system; real time operating systems; microcontrollers; FPGA

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Paper 7: A Two-Level Fault-Tolerance Technique for High Performance Computing Applications

Abstract: Reliability is the biggest concern facing future extreme-scale, high performance computing (HPC) systems. Within the current generation of HPC systems, projections suggest that errors will occur with very high rates in future systems. Thus, it is fundamental that we detect errors that can cause the failure of important applications, such as scientific ones. In this paper, we have presented a two-level fault-tolerance approach for the detection and classification of errors for Compute United Device Architecture (CUDA)-based Graphics Processing Units (GPUs). In the first level, it detects the existence of errors by using software redundancy that applies design diversity. In the second level, it investigates the problematic software version and re-executes it on a different hardware component to classify whether the error is a permanent hardware error or a software error. We implemented our approach to run on GPUs and conducted proof of concept experiments by running three versions of matrix multiplications with different error scenarios and results show the feasibility of the proposed approach.

Author 1: Aishah M. Aseeri
Author 2: Mai A. Fadel

Keywords: High performance computing; fault tolerance; graphics processing units (GPUS); error detection; n-version programming (NVP); multi-GPU; reliability

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Paper 8: Sensual Semantic Analysis for Effective Query Expansion

Abstract: The information has evolved rapidly over the World Wide Web in the past few years. To satisfy information needs, users mostly submit a query via traditional search engines, which retrieve results on the basis of keyword matching principle. However, a keyword-based search cannot recognize the meanings of keywords and the semantic relationship among the terms in the user’s query; thus, this technique cannot retrieve satisfactory results. The expansion of an initial query with relevant meaningful terms can solve this issue and enhance information retrieval. Generally, query expansion methods consider concepts that are semantically related to query terms within the ontology as candidates in expanding the initial query. An analysis of the correct sense of query terms, rather than only considering semantic relations, is necessary to overcome language ambiguity problems. In this work, we proposed a query expansion framework on the basis of query sense analysis and semantics mining using computer science domain ontology, followed by working prototype of the system. The experts analyzed the results of system prototype over test dataset and Web data, and found a remarkable improvement in the overall search performance. Furthermore, the proposed framework demonstrated better mean average precision and recall values than the baseline method.

Author 1: Muhammad Ahsan Raza
Author 2: M. Rahmah
Author 3: A. Noraziah
Author 4: Mahmood Ashraf

Keywords: Semantic computing; information retrieval; computational intelligence; ontology; term sense disambiguation

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Paper 9: Reading the Moving Text in Animated Text-Based CAPTCHAs

Abstract: Having based on hard AI problems, CAPTCHA (Completely Automated Public Turing test to tell the Computers and Humans Apart) is a hot research topic in the field of computer vision and artificial intelligence. CAPTCHA is a challenge-response test conducted to single out humans and bots. It is ubiquitously implemented on the web since its introduction. As text-based CAPTCHAs are successfully broken by various researchers therefore several design variants have been proposed and implemented in order to further strengthen it. Animated Text-based CAPTCHAs are one of the design variant of it and are based on the difficulty of reading the moving text. They are based on zero knowledge per frame principle. Although it’s still easy for humans to read animated text but it’s a challenge for machines. As proposals for animated CAPTCHAs are on the rise so there is a strong need to scrutinize their strength against automated attacks. In this research, such CAPTCHAs are investigated to verify their robustness against automated attacks. The proposed methods proved that these CAPTCHAs are vulnerable and they do not guarantee the robustness against automated attacks. The proposed frame selection, noise removal, segmentation and recognition methods have successfully decoded these CAPTCHAs with an overall precision, segmentation accuracy and recognition rate of up to 53.8%, 92.9% and 93.5% respectively.

Author 1: Syed Safdar Ali Shah
Author 2: Riaz Ahmed Shaikh
Author 3: Rafaqat Hussain Arain

Keywords: Bots; CAPTCHAs; ANNs; animations; image processing; HIPs; machine learning

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Paper 10: Improvement of the Vertical Handover Decision and Quality of Service in Heterogeneous Wireless Networks using Software Defined Network

Abstract: The development of wireless networks brings people great convenience. More state-of-the-art communication protocols of wireless networks are getting mature. People attach more importance to the connections between heterogeneous wireless networks as well as the transparency of transmission quality guarantees. Wireless networks are an emerging solution based on users' access to information and services, regardless of their geographic location. The success of these networks in recent years has generated great interest from individuals, businesses and industry. Although there are several access technologies available to the user such as IEEE standards (802.11, and 802.16). SDN is a new network paradigm used to simplify network management, reducing the complexity of network technology. The following work aims to expose a simulation implemented under OMNeT 4.6 ++, to improve the Handover performance between two technologies WiFi and WiMAX. This paper proposes a decision algorithm for a heterogeneous vertical handover between WiFi access points and WiMAX network. The inputs to the algorithm are WiFi RSS, bit rate, jitter, and estimated TCP end-to-end delay.

Author 1: Fatima Laassiri
Author 2: Mohamed Moughit
Author 3: Noureddine Idboufker

Keywords: Heterogeneous network; Vertical Handover; WiMAX; WiFi; IEEE 802.16; IEEE 802.11; OMNeT4.6;

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Paper 11: The Utilization of Feature based Viola-Jones Method for Face Detection in Invariant Rotation

Abstract: Faces in an image consists of complex structures in object detection. The components of a face, which includes the eyes, nose and mouth of a person differs from that of ordinary objects, thus making face detecting a complex process. Some of the challenges encounter posed in face detection of unconstrained images includes background variation, pose variation, facial expression, occlusion and noise. Current research of Viola-Jones (V-J) face detection is limited to only 45 degrees in-plane rotation. This paper proposes only one technique for the V-J detection face in unconstrained images, which V-J face detection with invariant rotation. The technique begins by rotating the given image file with each step 30 degrees until 360 degrees. Each step of adding 30 degrees from origin, V-J face detection is applied, which covers more angles of a rotated face in unconstrained images. Robust detection in rotation invariant used in the above techniques will aid in the detecting of rotated faces in images. The images that have been utilized for testing and evaluation in this paper are from CMU dataset with 12 rotations on each image. Therefore, there are 12 test patterns generated. These images have been measured through the correct detection rate, true positive and false positive. This paper shows that the proposed V-J face detection technique in unconstrained images have the ability to detect rotated faces with high accuracy in correct detection rate. To summarize, V-J face detection in unconstrained images with proposed variation of rotation is the method utilized in this paper. This proposed enhancement improves the current V-J face detection method and further increase the accuracy of face detection in unconstrained images.

Author 1: Tioh Keat Soon
Author 2: Abd Samad Hasan Basari
Author 3: Nuzulha Khilwani Ibrahim
Author 4: Burairah Hussin
Author 5: Ariff Idris
Author 6: Noorayisahbe Mohd Yaacob
Author 7: Mustafa Almahdi Algaet
Author 8: Norazira A. Jalil

Keywords: Face detection; V-J face detection; unconstrained images; bicubic interpolation; SIFT

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Paper 12: A Correlation based Approach to Differentiate between an Event and Noise in Internet of Things

Abstract: Internet of Things (IoT) is considered a huge enhancement in the field of information technology. IoT is the integration of physical devices which are embedded with electronics, software, sensors, and connectivity that allow them to interact and exchange data. IoT is still in its beginning so it faces a lot of obstacles ranging from data management to security concerns. Regarding data management, sensors generate huge amounts of data that need to be handled efficiently to have successful employment of IoT applications. Detection of data anomalies is a great challenge that faces the IoT environment because, the notion of anomaly in IoT is domain dependent. Also, the IoT environment is susceptible to a high noise rate. Actually, there are two main sources of anomalies, namely: an event and noise. An event refers to a certain incident which occurred at a specific time, whereas noise denotes an error. Both event and noise are considered anomalies as they deviate from the remaining data points, but actually they have two different interpretations. To the best of our knowledge, no research exists addressing the question of how to differentiate between an event and noise in IoT. As a result, in this paper, an algorithm is proposed to differentiate between an event and noise in the IoT environment. At first, anomalies are detected using exponential moving average technique, then the proposed algorithm is applied to differentiate between an event and noise. The algorithm uses the sensors’ values and correlation existence between sensors to detect whether the anomaly is an event or noise. Moreover, the algorithm was applied on a real traffic dataset of size 5000 records to evaluate its effectiveness and the experiments showed promising results.

Author 1: Dina ElMenshawy
Author 2: Waleed Helmy

Keywords: Anomaly detection; event; IoT; noise

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Paper 13: An Improvement of Performance Handover in Worldwide Interoperability for Microwave Access using Software Defined Network

Abstract: The WiMAX network designates in common language of a set of standards and techniques of the world of Wireless Metropolitan Area Networks (WMAN). The standard IEEE 802.16 or WiMAX allows the wireless connection of companies or individuals over long distances at high speed. WiMAX provides an appropriate response for some rural or hard-to-reach areas, which today lack access to Broadband Internet for cost reasons. This technology aims to introduce a complementary solution to the Digital Subscriber Line (DSL) and cable networks on the one hand, and to interconnect WiFi hotspots, on the other hand WiMAX is mainly based on a star topology although mesh topology is possible. Communication can be done in Line of Sight (LOS) or not (NLOS).Software Defined Network (SDN) is a new network paradigm used to simplify network management. It reduces the complexity of network technology.The following article aims to expose a simulation implemented under Omnet4.6++, to improve Handover performance and QoS (End-to-end delay, latency, jitter, MoS and lost packet), by implemented an algorithm in SDN controller. The simulation is tested in WIMAX architecture, and results have been collected from two scenarios with and without SDN controller to proof that this algorithm is more preferment to guarantee a better QOS in Handover.

Author 1: Fatima Laassiri
Author 2: Mohamed Moughit
Author 3: Noureddine Idboufker

Keywords: WiMAX; SDN; QoS; handover; openflow; OMNeT 4.6 ++

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Paper 14: Cryptography using Random Rc4 Stream Cipher on SMS for Android-Based Smartphones

Abstract: Messages sent using the default Short Message Service (SMS) application have to pass the SMS Center (SMSC) to record the communication between the sender and recipient. Therefore, the message security is not guaranteed because it may read by irresponsible people. This research proposes the RC4 stream cipher method for security in sending SMS. However, RC4 has any limitation in the Key Scheduling Algorithm (KSA) and Pseudo Random Generation Algorithm (PRGA) phases. Therefore, this research developed RC4 with a random initial state to increase the randomness level of the keystream. This SMS cryptography method applied the processes of encryption against the sent SMS followed by decryption against the received SMS. The performance of the proposed method is evaluated based on the time of encryption and decryption as well as the average correlation value. Based on the time, it shows that the length of the SMS characters sent affects the time of encryption and decryption. Meanwhile, the best correlation value achieved 0.00482.

Author 1: Rifki Rifki
Author 2: Anindita Septiarini
Author 3: Heliza Rahmania Hatta

Keywords: Cryptography; SMS security; RC4 stream cipher; random initial state; correlation value

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Paper 15: Improvement of the Handover and Quality of Service on Software Defined Wireless Networks

Abstract: The Wireless Fidelity (WiFi) is the business name given to the 802.11b and 802.11g IEEE standard by the WiFi Alliance, formerly known as Weca industry with more than 200 member companies dedicated to supporting the growth of wireless LANs. This standard is currently one of the most used standards in the world. The theoretical data rates of 802.11b are 11 Mb/s and 54 Mb/s for 802.11g. This article presents Handover's improvement performance and quality of service (QoS) parameters and they are: end-to-end delay, latency, jitter, lost packets, and Mean Opinion Score (MoS), under networks Wi-Fi with the help of the OMNeT 4.6 ++, by implementation of a new algorithm at the level of the SDN controller that allows handover management without breaking the connection by respecting the priority per class of traffic. The realization of this work is based on the intra-Wi-Fi mobility, that it is adopted by a macro mobility of level 3 and it is MIPv6 as well as it exploited the protocol of Voice over IP that it is SIP, and the implementation of SDN rules on the OpenFlow protocol.

Author 1: Fatima Laassiri
Author 2: Mohamed Moughit
Author 3: Noureddine Idboufker

Keywords: SDN; Wi-Fi; QoS; OpenFlow protocol; handover; SDN controller; OpenFlow switch

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Paper 16: A Mapping Approach for Fully Virtual Data Integration System Processes

Abstract: Nowadays, organizations cannot satisfy their information needs from one data source. Moreover, multiple data sources across the organization fuels the need for data integration. Data integration system’s users pose queries in terms of an integrated schema and expect accurate, unambiguous, and complete answers. So the data integration system is not limited to, getting the answers to the queries from the sources, but also it is extended to detect and resolve the data quality problems appeared due to the integration process. The most crucial component in any data integration system is the mappings constructed between the data sources and the integrated schema. In this paper a new mapping approach is proposed to map not only the elements of the integrated schema as done by the existing approaches, but also it maps other elements required in detecting and resolving the duplicates. It provides a means to facilitate future extensibility and changes to both the sources and the integrated schema. The proposed approach provides a linkage between the fundamental components required to provide accurate and unambiguous answers to the users’ queries from the integration system.

Author 1: Ali Z El Qutaany
Author 2: Osman M. Hegazi
Author 3: Ali H. El Bastawissy

Keywords: Data integration; inconsistency detection; inconsistency resolution; mapping; virtual data integration

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Paper 17: Automation of Combinatorial Interaction Test (CIT) Case Generation and Execution for Requirements based Testing (RBT) of Complex Avionics Systems

Abstract: In the field of avionics, most of the software systems are either safety critical or mission critical. These systems are developed with high quality standards strictly following the relevant guidelines and procedures. Due to the high criticality of the systems, it is mandatory that the verification and validation of these systems are done with utmost importance and only then any system is cleared for flight trials. The verification and validation activities need to be very exhaustive and hence take a considerable amount of time in the software development lifecycle. This paper describes about the innovative approach towards automation of Combinatorial Interaction Test case generation and execution for Requirements Based Testing of complex avionics systems for achieving test adequacy in a highly time efficient and cost efficient manner.

Author 1: P Venkata Sarla
Author 2: Balakrishnan Ramadoss

Keywords: Avionics; combinatorial interaction testing; requirement specifications; requirements based testing; safety critical; validation; verification

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Paper 18: Smart Surveillance System using Background Subtraction Technique in IoT Application

Abstract: This paper presents a development of a security system based on Internet-of-Things (IoT) technology, where an IoT device, Raspberry Pi has been used. In the developed surveillance system, a camera works as a sensor to detect motion, and automatically capture the video of the view of area where the motion is detected. The motion is detected by image processing techniques; background subtraction technique. The technique is applied by comparing two different captured images using Pi NoIR camera. The system can be controlled from anywhere using Telegram application, and users will receive alert message with video using the application. The user can also play a siren from anywhere once detecting suspicious object can access images and videos using Telegram application. This can frighten the thief if the crime is suspected in home or office. Users can also deactivate and activate the system from anywhere at any time using the Telegram. The functionality tests have been done to ensure the developed product can work properly. Besides, tests to identify a suitable video length to be transmitted to the user and to identify the adequate location of the security in order to minimize false detection as well as false alert have been performed. The project is an IoT-based which significantly in line with the Industrial Revolution 4.0, supporting the infrastructure of Cyber-Physical System.

Author 1: Norharyati binti Harum
Author 2: Mohanad Faeq Ali
Author 3: Nurul Azma Zakaria
Author 4: Syahrulnaziah Anawar

Keywords: Internet of things; raspberry pi; motion detection; home security system; surveillance system: ir4.0

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Paper 19: The Degree to which Private Education Students at Princess Nourah Bint Abdulrahman University have Access to Soft Skills from their Point of View and Educational Body

Abstract: The study aimed at identifying the degree of ownership of special education students in the Department of Special Education, Faculty of Education, Princess Nourah University for soft skills from their point of view and the consideration of the educational body and its relation to some variables (level of study, specialization, teaching experience). The study consisted of (26) faculty members in the Department of Special Education, and the second consisted of (287) female students of the Department of Special Education at different levels and specializations, and the data using the Statistical Package for Social Sciences analysis (SPSS). The results of the statistical analysis of the study data indicated that the total score of students' possession of soft skills according to their point of view was low, except for some of the paragraphs in which the estimate was high. The degree of possession of soft skills from the point of view of faculty members was also low, and the results of the study also indicated that there were differences between the students due to specialization and the level of the school tend to favor the higher level of the study, while there were differences according to the view of the faculty for the higher experience, while the results did not indicate a difference attributed to R faculty members. The study recommended increasing the interest in soft skills for female students in particular, and for female students in general, by including these skills in the study courses and through the various student activities.

Author 1: Saeb Kamel Allala
Author 2: Ola Mohy Aldeen Abusukkar

Keywords: Soft skills; special education students; faculty members; Princess Nourah Bint Abdulrahman University

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Paper 20: FTL Algorithm using Warm Block Technique for QLC+SLC Hybrid NAND Flash Memory

Abstract: When applying the existing flash translation layer technique to a mixed NAND flash storage device composed of Quad Level Cell and Single Level Cell, because the characteristics of a semiconductor chip are not taken into consideration, the data are stored indiscriminately, and thus the performance and stability are not guaranteed. Therefore, this study proposes a flash translation layer algorithm using the warm block technique in a NAND flash storage device that combines a large capacity Quad Level Cell and a high performance Single Level Cell. The warm block technique avoids overloading of the read/write/erase operations in the Quad Level Cell flash memory by efficiently placing hot data that are frequently updated on a long-living Single Level Cell. It was confirmed experimentally that the lifetime extension and performance of hybrid NAND flash memory are improved using the warm block technique.

Author 1: Wanil Kim
Author 2: Seok-Bin Seo
Author 3: Jin-Young Kim
Author 4: Se Jin Kwon

Keywords: Quad level cell; single level cell; composed flash memory; flash translation layer

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Paper 21: Energy-Efficient Security Threshold Determination Method for the Enhancement of Interleaved Hop-By-Hop Authentication

Abstract: Wireless sensor networks allow attackers to inject false reports by compromising sensor nodes due to the use of wireless communication, the limited energy resources of the sensor nodes, and deployment in an open environment. The forwarding of false reports causes false alarms at the Base Station and consumes the energy of the sensor nodes unnecessarily. As a defense against false report injection attacks, interleaved hop-by-hop authentication was proposed. In interleaved hop-by-hop authentication, the security threshold is a design parameter that influences the number of Message Authentication Codes; the sensor nodes must verify, based on the security requirements of the application and the node density of the network. However, interleaved hop-by-hop authentication fails to defend against false report injection attacks when the number of compromised sensor nodes exceeds the security threshold. To solve this problem, in this paper we propose a security scheme that adjusts the security threshold according to the network situation using an evaluation function. The proposed scheme minimizes the energy consumption of the sensor nodes and reinforces security.

Author 1: Ye Lim Kang
Author 2: Tae Ho Cho

Keywords: Component; wireless sensor networks; false report injection attack; network security; interleaved hop-by-hop authentication

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Paper 22: WordNet based Implicit Aspect Sentiment Analysis for Crime Identification from Twitter

Abstract: Crime analysis has become an interesting field that deals with serious public safety issues recognized around the world. Today, investigating Twitter Sentiment Analysis (SA) is a continuing concern within this field. Aspect based SA, the process by which information can be extracted, analyzed and classified, is applied to tweet datasets for sentiment polarity classification to predict crimes. This paper addresses the aspect identification task involving implicit aspect implied by adjectives and verbs for crime tweets. The proposed hybrid model is based on WordNet semantic relations and Term-Weighting scheme, to enhance training data for (1) Crime Implicit Aspect sentences detection (IASD) and (2) Crime Implicit Aspect Identification (IAI). The performance is evaluated using three classifiers Multinomial Naïve Bayes, Support Vector Machine and Random Forest on three Twitter crime datasets. The obtained results demonstrate the effectiveness of WN synonym and definition relations and prove the importance of verbs in training data enhancement for crime IASD and IAI.

Author 1: Hajar El Hannach
Author 2: Mohammed Benkhalifa

Keywords: Implicit aspect based sentiment analysis; information retrieval; machine learning; supervised approaches; frequency model; WordNet; crime detection; hate crime twitter sentiment (HCTS)

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Paper 23: 3D Mapping based-on Integration of UAV Platform and Ground Surveying

Abstract: Development in aerial photogrammetry technology has contributed a notable impact to the area of large-scale mapping. Nowadays, unmanned aerial vehicle (UAV) platform has become a significant tool in aerial mapping. Generating 3D mapping using photos acquired from UAV is more preferable due to its low cost and flexible operation. Therefore, this study aims to develop a technique for 3D mapping with an integration of UAV aerial photos and detailed ground survey. The produced 3D mapping has RMSE(x) = 0.279, RMSE(y) = 0.215, and RMSE (z) = 1.341 using 25 randomly selected sample points. Besides that, the result shows the location parameters i.e. x, y and z were also positively correlated, t-test(x) = 0.961, t-test(y) = 0.250 and t-test (z) = 1.885, respectively.

Author 1: Muhammad Yazid Abu Sari
Author 2: Abd Wahid Rasib
Author 3: Hamzah Mohd Ali
Author 4: Abdul Razak Mohd Yusoff
Author 5: Muhammad Imzan Hassan
Author 6: Khairulnizam M.Idris
Author 7: Asmala Ahmad
Author 8: Rozilawati Dollah

Keywords: 3D mapping; UAV platform; ground survey; aerial photo

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Paper 24: Triangle Shape Feature based on Selected Centroid for Arabic Subword Handwriting

Abstract: Features are normally modelled based on color, texture and shape. However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Therefore, features based on shape are suitable to be used for recognizing Arabic subword handwriting since each of the character has various characteristics such as diacritics, thinning and strokes. These characteristics can contribute to particular a shape that is unique and can represent Arabic subword handwriting. Currently, geometry shape such as triangle has been adopted to extract useful features based on triangle properties without implicating any triangle form. In order to increase classification accuracy, these properties have been categorized into several zones where the number of features produced is directly proportional to the number of zones. Nevertheless, shape representation does not implicate any triangle properties such as ratio of side, angle and gradient. By using shape representation, it helps in reducing the number of features. Thus, this paper presents feature based on triangle shape that can represent the identity of Arabic subword handwriting. The method based on triangle shape identifies three main coordinates of triangle formed based on selected centroids. The AHDB dataset is used as a testing data. The Support Vector Machine (SVM) and Random Forest (RF), respectively were used to measure the accuracy of the proposed method using triangle shape as a feature. The accuracy results have shown better outcome with 77.65% (SVM) and 76.43% (RF), which prove the feature based on triangle shape is applicable for Arabic subword handwriting recognition.

Author 1: Nur Atikah Arbain
Author 2: Mohd Sanusi Azmi
Author 3: Azah Kamilah Muda
Author 4: Amirul Ramzani Radzid
Author 5: Azrina Tahir

Keywords: Arabic subword; feature extraction; random forest; support vector machine; triangle geometry

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Paper 25: Efficient Reduction of Overgeneration Errors for Automatic Controlled Indexing with an Application to the Biomedical Domain

Abstract: Studies on MetaMap and MaxMatcher has shown that both concept extraction systems suffer from overgeneration problems. Over-generation occurs when the extraction systems mistakenly select an irrelevant concept. One of the reasons for these errors is that these systems use the words to weight the terms of the concepts. In this paper, an Integer Linear Programming model is used to select the optimal subset of extracted concept mentions covering the largest number of important words in the document to be indexed. Then each concept mentions that this set is mapped to a unique concept in UMLS using an information retrieval model.

Author 1: Samassi Adama
Author 2: Brou Konan Marcellin
Author 3: Gooré Bi Tra
Author 4: Prosper Kimou

Keywords: Concept extraction; concept recognition; automatic controlled indexing; controlled vocabulary; information retrieval

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Paper 26: Optimizing the Behaviour of Web Users Through Expectation Maximization Algorithm and Mixture of Normal Distributions

Abstract: The proposed work is to analyse the user’s behaviour in web access. Worldwide, the web users are browsing through different websites every second. Aim of this paper is to identify the behaviour of user's in a time bound using an Expectation Maximization (EM) algorithm and the maximum likelihood estimates of the model parameters. A novel approach based on Mixture normal distribution is used to discuss the percentage of user along with web page frequency.

Author 1: R. Sujatha
Author 2: D. Nagarajan
Author 3: P. Saravanan
Author 4: J. Kavikumar

Keywords: EM algorithm; maximum likelihood; mixture normal distribution; web page frequency

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Paper 27: Application of Fuzzy Analytical Hierarchy Process based on Geometric Mean Method to Prioritize Social Capital Network Indicators

Abstract: Vietnam is striving to develop dynamically and overcome many human resource challenges. As the economy expands, the demand for jobs and human resource development has become increasingly critical. The pressures from reform and international integration are forcing many changes. New graduates must provide proof of their academic capabilities, while also actively developing their social capital to support their job search process. In fact, social capital is an essential capital for personal development as well as professional development of new graduates. This paper applies Fuzzy Analytical Hierarchy Process based on Geometric Mean Methodology to evaluate factors for measuring the social capital of graduates at Ho Chi Minh City Open University in Vietnam. The research results highlight the important role of social networks for graduates, in which a linking network is the most important, a bonding network is the second most important, and a bridging network is the third most important. In addition, the research shows that trust plays an even more important role than networks; and specific belief is more important than general belief.

Author 1: Vy Dang Bich Huynh
Author 2: Phuc Van Nguyen
Author 3: Quyen Le Hoang Thuy To Nguyen
Author 4: Phong Thanh Nguyen

Keywords: Education; human resource; fuzzy analytic hierarchy process, geometric mean; social capital network

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Paper 28: Position-based Selective Neighbors

Abstract: In this paper, we propose a routing protocol, named Position-based Selective Neighbors (PSN), for controlling the Route Request (RREQ) propagation in Mobile Ad-hoc Networks (MANETs). PSN relies on the Residual Energy (RE) and the Link Lifetimes (LLT) factors to select the better end-to-end paths between mobile nodes. The key concept is to consider the RE and the LLT to find the best neighboring nodes to forward the received RREQs. A Simulation has been performed to compare PSN with other pioneering routing protocols. Experimental results show that PSN performs better than its competitors. Indeed, our protocol increases the network life time and reduces the network overhead. Furthermore, it reduces the overhead generated by the redundant RREQ, while maintaining good reachability among the mobile nodes.

Author 1: Sofian Hamad
Author 2: Taoufik Yeferny
Author 3: Salem Belhaj

Keywords: Mobile Ad-hoc network (MANET); routing protocol; energy aware; link life time; AODV

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Paper 29: Comparative Study of Data Sending Methods for XML and JSON Models

Abstract: Data exchange between different devices and applications has become a necessity nowadays. Data is no longer stored locally on the device, but in the cloud. In order to communicate with the cloud and exchange data, web services are being used. To keep the communication consistent across different devices and platforms, the data needs to be formatted using a standard data format, such as JSON or XML. This paper compares both standards and provides an in depth analysis of their performance. In order to perform the analysis a web API was built in the PHP framework Laravel, which was then tested with the help of the API development environment called Postman for different number of transferred items.

Author 1: Anca-Raluca Breje
Author 2: Robert Gyorödi
Author 3: Cornelia Gyorödi
Author 4: Doina Zmaranda
Author 5: George Pecherle

Keywords: XML; JSON; data model; data transfer; application programming interface

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Paper 30: Abnormal Region Extraction from MR Brain Images using Hybrid Approach

Abstract: Automatic brain abnormality segmentation from magnetic resonance images is a key task that is performed by computer aided algorithm or manual extraction by a medical expert. The regions are often partitioned based on the similarities of intensities that persist in a particular region. MR brain image segmentation is a critical step that helps to identify the abnormal region. Accurate identification of this abnormal region helps the radiologist and surgeons in surgical process and research. Through this paper we present a hybrid approach of algorithms based on clustering approach like region and edge based algorithm involved in segmenting abnormal region from MR brain images. The method is an integration of region based (pillar K-means) and edge based (level set) segmentation algorithm that aims to segment the abnormal region precisely. Experimental results show that the proposed approach could attain segmentation efficiency of 89.2%, mitigating the segmentation errors that were prevalent with region or edge based algorithms.

Author 1: Nikhil Gala
Author 2: Kamalakar Desai

Keywords: Clustering algorithm; hybrid approach; MR brain image segmentation; level set; pillar k-means; segmentation errors

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Paper 31: Linear Intensity-Based Image Registration

Abstract: The accurate detection and localization of lesion within the prostate could greatly benefit in the planning of surgery and radiation therapy. Although T2 Weighted Imaging (T2WI) Magnetic Resonance Imaging (MRI) provides an infinite amount of anatomical information, which ease and improve diagnosis and patient treatment, however, modality specific image artifacts, such as the occurrences of intensity inhomogeneity are still obvious and can adversely affect quantitative image analysis. Conventional high resolution T2WI has been restricted in this respect. On the contrary, Apparent Diffusion Coefficient (ADC) map has been seen as capable to tackle T2WI limitation when a functional assessment of the prostate capable to provide added value compared to T2WI alone. Likewise, it has been shown that diagnosis using ADC map combined with T2WI significantly outperforms T2WI alone. Therefore, to obtain high accuracy detection and localization, a combination of high-resolution anatomic and functional imaging is extremely important in clinical practice. This strategy relies on accurate intensity based image registration. However, registration of anatomical and functional MR imaging is really challenging due to missing correspondences and intensity inhomogeneity. To address this problem, this study researches the used of applying linear geometric transform to the corresponding point to accurately mapping the images for precise alignment and accurate detection. Transformation type is crucial for the success of image registration. The selection of transformation type is influenced by the type and severity of the geometric differences between corresponding images, the accuracy of the control point between images, its density and organization of the control points. A transformation type is selected to reflect geometric differences between two images in image registration. Often, the selection of the suitable transformation type for image registration is undeniably challenging. To make this selection as effective as possible, an experimental mechanism has to be carried out to determine its suitability. These transformations types are Affine, similarity, rigid and translation. Additionally, intensity based image registration is implemented to optimize the similarity metric mean square error through regular step gradient descent optimizer. Accuracies evaluation for each transformation type has been carried out through mean square error (MSE) and peak signal noise ratio (PSNR). The results have been presented in a chart form together with a comparison table.

Author 1: Yasmin Mumtaz Ahmad
Author 2: Shahnorbanun Sahran
Author 3: Afzan Adam
Author 4: Syazarina Sharis Osman

Keywords: Lineargeo metric transformation; image registration; point correspondence

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Paper 32: Using Game Theory to Handle Missing Data at Prediction Time of ID3 and C4.5 Algorithms

Abstract: The raw material of our paper is a well known and commonly used type of supervised algorithms: decision trees. Using a training data, they provide some useful rules to classify new data sets. But a data set with missing values is always the bane of a data scientist. Even though decision tree algorithms such as ID3 and C4.5 (the two algorithms with which we are working in this paper) represent some of the simplest pattern classification algorithms that can be applied in many domains, but with the drawback of missing data the task becomes harder because they may have to deal with unknown values in two major steps: at training step and at prediction step. This paper is involved in the processing step of databases using trees already constructed to classify the objects of these data sets. It comes with the idea to overcome the disturbance of missing values using the most famous and the central concept of the game theory approach which is the Nash equilibrium.

Author 1: Halima Elaidi
Author 2: Zahra Benabbou
Author 3: Hassan Abbar

Keywords: Decision tree; ID3; C4.5; missing data; game theory; Nash equilibrium

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Paper 33: Optimizing Power-Based Indoor Tracking System for Wireless Sensor Networks using ZigBee

Abstract: Evolution of wireless and digital communication gives birth to the smaller but powerful battery-equipped devices which are easy to maintain and perform the desired tasks. ZigBee is a Wireless Personal Area Network (WPAN) used for home or indoor automation, collecting data for medical research by using the low power digital radios to handle the low data rate. In ZigBee network, sensor nodes are heterogeneously deployed and continuously moving. To detect and tracking of those sensor nodes are challenging in terms of accuracy, calculation time and energy consumption. In this paper, proposed system uses the Received Signal Strength Indication (RSSI) protocol for localization, trilateration for fetching the exact coordinates of sensor nodes and these protocols helps to overcome the problem which eventually led to prolonged sensor network, accurate localization.

Author 1: Ahmad H. Mahafzah
Author 2: Hesham Abusaimeh

Keywords: Indoor tracking; ZigBee; wireless personal area network; localization; trilateration

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Paper 34: Heterogeneous Ensemble Pruning based on Bee Algorithm for Mammogram Classification

Abstract: In mammogram, masses are primary indication of breast cancer; and it is necessary to classify them as malignant or benign. In this classification task, Computer Aided Diagnostic (CAD) system by using ensemble learning is able to assist radiologists to have better diagnosis of mammogram images. Ensemble learning consists of two steps, generating multiple base classifiers and then combining them together. However, combining all base classifier in the ensemble model increases the computational cost and time. Therefore, ensemble pruning is an important step in ensemble learning to select the ensemble’s members. Due to huge subsets of combination in the ensemble, selecting the proper ensemble subset is desirable. The objective of this paper is to select the optimal ensemble subset by using Bee Algorithm (BA). A pool of different classifier models such as Support vector machine, k-nearest neighbour and linear discriminant analysis classifiers have been trained using different samples of training data and 12 groups of features. Then, by using this pool of classifier models, BA was used to exploit and explore random uniform combination subsets of the trained classifiers. As a result, the best subset will be selected as the optimal ensemble. The mammogram image dataset that was used to test the model has been collected from Hospital Kuala Lumpur (HKL) and consists of 263 benign and malignant masses. The proposed method gives 77 % of Area Under Curve(AUC), 83% of accuracy, 93% of specificity and 60% of sensitivity.

Author 1: Ashwaq Qasem
Author 2: Siti Norul Huda Sheikh Abdullah
Author 3: Shahnorbanun Sahran
Author 4: Dheeb Albashish
Author 5: Rizuana Iqbal Hussain
Author 6: Shantini Arasaratnam

Keywords: Ensemble learning; ensemble pruning; bee algorithm; mammogram; breast cancer

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Paper 35: CNNSFR: A Convolutional Neural Network System for Face Detection and Recognition

Abstract: In recent years, face recognition has become more and more appreciated and considered as one of the most promising applications in the field of image analysis. However, the existing models have a high level of complexity, use a lot of computational resources and need a lot of time to train the model. That is why it has become a promising field of research where new methods are being proposed every day to overcome these difficulties. We propose in this paper a convolutional neural network system for face recognition with some contributions. First we propose a CRelu module, second we use the module to propose a new architecture model based on the VGG deep neural network model. Thirdly we propose a two stage training strategy improved by a large margin inner product and a small dataset and finally we propose a real time face recognition system where face detection is done by a multi-cascade convolution neural network and the recognition is done by the proposed deep convolutional neural network.

Author 1: Lionel Landry SOP DEFFO
Author 2: Elie TAGNE FUTE
Author 3: Emmanuel TONYE

Keywords: Convolutional neural network; face recognition; VGG model; CReLU module; deep learning; architecture

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Paper 36: A Proposed Methodology on Predicting Visitor’s Behavior based on Web Mining Technique

Abstract: The evolution of the internet in recent decades enlarge the website's reports with the records of user’s activities and behaviors that registered in the web server which can be created automatically in the web access log file. The feedback concerning the user’s activities, performance and any problem that may be occur including the cyber security approaches of the web server represents the principal raison of applying the web mining technique. In this paper, we proposed a methodology on predicting users behavior based on the web mining technique by creating and executing analysis applications using a Deep Log Analyzer tool that applied on the web server access log of our faculty website. Furthermore, an associated programmed application has been developed which employs the extracted data into dynamic visualizations reports(tables, graphs, charts) in order to help the web system administrator to increase the web site effectiveness, we had creating a suitable access patterns that permits to identify the interacting users behaviors and the interesting usage patterns such as the occurred errors, potential visitors, navigation activities, behavioral analysis, diagnostic study, and security alerts for intrusion prevention. Moreover, the obtained results achieved the aim of producing a dynamic monitoring by extracting investigation summaries which analyses the discovered access patterns that registered in the faculty web server in order to improve the web site usability by tracking the user’s behaviors and the browsing activities. Our proposed tool will highlight providing a security alerts against the malicious users by predicting the malicious behaviors taking into consideration all the discovered vulnerabilities by detecting the corrupted links used by the abnormal visitors.

Author 1: Abdel Karim Kassem
Author 2: Bassam Daya
Author 3: Pierre Chauvet

Keywords: Web server; log file; web mining; behavior; pattern; web usage mining; visualizations; vulnerabilities; security

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Paper 37: Lightweight and Optimized Multi-Layer Data Hiding using Video Steganography

Abstract: The ever-escalating attacks on the internet network are due to rapid technological growth. In order to surmount such challenges, multi-layer security algorithms were developed by hybridizing cryptography and steganography techniques. Consequently, the overall memory size became enormous while hybridizing these techniques. On the other side, the least significant bit (LSB) and modified LSB replacing approaches could provide the variability as detected by steganalysis technique, most found to be susceptible to attack too due to numerous reasons. To overcome these issues, in this paper a lightweight and optimized data hiding algorithm is proposed which consume less memory, provide less variability, and robust against histogram attacks. The proposed steganography system was achieved in two stages. First, data was encrypted using lightweight BORON cipher that only consumed less memory as compared to conventional algorithm such as 3DES, AES. Second, the encrypted data was hidden in the complemented or non-complemented form to obtain minimal variability. The performance of the proposed technique was evaluated in terms of avalanche effect, visual quality, embedding capacity and peak signal to noise ratio (PSNR). The results revealed that the lightweight BORON cipher could produce approximate same avalanche effect as the AES algorithm produced. Furthermore, the value of PSNR had shown much improvement in comparison to optimization algorithm GA.

Author 1: Samar kamil
Author 2: Masri Ayob
Author 3: Siti Norul Huda Sheikh Abdullah
Author 4: Zulkifli Ahmad

Keywords: Video steganography; least significant bit technique; optimized data hiding; cloud computing; boron cipher

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Paper 38: Hyper Parameter Optimization using Genetic Algorithm on Machine Learning Methods for Online News Popularity Prediction

Abstract: Online news is a media for people to get new information. There are a lot of online news media out there and a many people will only read news that is interesting for them. This kind of news tends to be popular and will bring profit to the media owner. That’s why, it is necessary to predict whether a news is popular or not by using the prediction methods. Machine learning is one of the popular prediction methods we can use. In order to make a higher accuracy of prediction, the best hyper parameter of machine learning methods need to be determined. Determining the hyper parameter can be time consuming if we use grid search method because grid search is a method which tries all possible combination of hyper parameter. This is a problem because we need a quicker time to make a prediction of online news popularity. Hence, genetic algorithm is proposed as the alternative solution because genetic algorithm can get optimal hypermeter with reasonable time. The result of implementation shows that genetic algorithm can get the hyper parameter with almost the same result with grid search with faster computational time. The reduction in computational time is as follows: Support Vector Machine is 425.06%, Random forest is 17%, Adaptive Boosting is 651.06%, and lastly K - Nearest Neighbour is 396.72%.

Author 1: Ananto Setyo Wicaksono
Author 2: Ahmad Afif Supianto

Keywords: Hyper parameter; genetic algorithm; online news; popularity; machine learning

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Paper 39: Classification based on Clustering Model for Predicting Main Outcomes of Breast Cancer using Hyper-Parameters Optimization

Abstract: Breast cancer is a deadly disease in women. Predicting the breast cancer outcomes is very useful in determining the efficient treatment plan for the new breast cancer patients. Predicting the breast cancer outcomes (also called Prognosis) are done based on the previous patient’s data, which show the patient’s characteristics and how the doctors treated the patient. In this paper we propose a new efficient model for predicting the main outcomes; Survival Rate, Disease Free Survival, and Recurrence detection; of breast cancer. The proposed model utilizes two techniques to increase the accuracy of the predictive results. The first technique is applying the classification model on various data clusters rather than the full dataset. In such steps, the data is grouped in different clusters according to the similarity of the main characteristics, then the classification model is applied on these clusters. The second technique is using the Hyper-Parameters Optimization (also called Hyper-Parameters Tuning) to increase the accuracy of the classification model. In this step, the proposed model uses Hyper-Parameters Optimization to find a tuple of hyper-parameters that yields on the optimal model which minimizes a predefined loss function on given dataset. The experimental study shows in detail how utilizing such two techniques results in an efficient prediction model producing accurate results.

Author 1: Ahmed Attia Said
Author 2: Laila A.Abd-Elmegid
Author 3: Sherif Kholeif
Author 4: Ayman Abdelsamie Gaber

Keywords: Breast cancer; Survival Rate (SR); Disease Free Survival (DFS); recurrence detection; egy; prediction; data mining; classification; clustering; hyper-parameters optimization

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Paper 40: Morphological Features Analysis for Erythrocyte Classification in IDA and Thalassemia

Abstract: Iron Deficiency Anemia (IDA) and Thalassemia is a common disease in the world population. In hospital routine, those diseases are being recognized based on level of hemoglobin in Complete Blood Count (CBC) result. Then, visual experts will conduct examination under the light microscope which is subjected to human error. In this research, we suggested a methodology via machine learning to classify and characterize erythrocyte related with IDA and Thalassemia. We employ some image pre-processing techniques on the blood smear images to enhance edges and reduce image noise such as gamma correction and morphological processing. Then, every single erythrocyte image will segment the background and foreground by using Otsu’s threshold method. Here, we have considered nine types of erythrocyte such as teardrop, echinocyte, elliptocyte, microcytic, hypochromic, target cell, acanthocyte, sickle cell and normal cell to be classified and portray based on their morphological features. Later, these 24 and 31 features from Hue’s moment, Zernike moment, Fourier descriptor and geometrical features are confirmed as potential features for each condition by calculating one-way ANOVA. Next, the rank of subset features is done based on their information gain value from maximum to minimum. Each of subset is separated by incremental of five features. Here, we compare the performance for each subset with five selected classifiers namely logistic regression, radial basis function network, multilayer perceptron, Naïve Bayes Classifier and Classification and Regression Tree. The best subsets from 31 features provide the highest result of classification with 83.5% accuracy, 83.5% sensitivity and 83.3% positive predictive value respectively via logistic regression compared to other classifiers. This study could be extended by using image dataset from other blood based disease for future work.

Author 1: Izyani Ahmad
Author 2: Siti Norul Huda Sheikh Abdullah
Author 3: Raja Zahratul Azma Raja Sabudin

Keywords: (Iron Deficiency Anemia) IDA; Thalassemia; erythrocyte; morphological features; classifier; information gain; logistic regression

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Paper 41: Enhanced Analytical Hierarchy Process for U-Learning with Near Field Communication (NFC) Technology

Abstract: Integration of current Virtual Learning Environment (VLE) system with the Near Field Communication (NFC) technology provides Ubiquitous Learning Environment (ULE) in education. The utilization of NFC technology in U-Learning concept will help to improve accessibility and encourage collaborative learning methods in the education sector. In this paper, we conduct a study to investigate eleven (11) adoptions factors of U-Learning with NFC and ranking them using Analytical Hierarchy Process (AHP) a multicriteria decision-making (MCDM) approach. We also utilized Technology Acceptance Model (TAM), Technology Readiness (TR), and combination of TAM and TR (TRAM) as theoretical framework. We have identified TRAM as the best tool based on literature review and utilized the theory to propose an NFC-Enabled Ubiquitous Technology model. The model was utilized to design a questionnaire for survey about user acceptance. Results from the online survey were analyzed using AHP in an absolute measurement approach method. Results from AHP show that optimism is the most influencing factor in adoption of U-Learning using NFC technology followed by innovativeness and accessibility. Finally, this paper contributes in designing an NFC research model.

Author 1: Huzaifa Marina Osman
Author 2: Manmeet Mahinderjit Singh
Author 3: Manuel Serafin Plasencia
Author 4: Azizul Rahman Mohd Shariff
Author 5: Anizah Abu Bakar

Keywords: Ubiquitous learning (U-Learning); virtual learning; multi criteria decision making (MCDM); Analytical Hierarchy Process (AHP)

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Paper 42: Automation Lecture Scheduling Information Services through the Email Auto-Reply Application

Abstract: The study program of information systems is one of the largest studies programs at Indonesian Computer University (UNIKOM). In the process of scheduling lectures in the study program of information systems, it has already information systems of used desktop-based lecture scheduling. Lecture schedules that have been created are then informed through various media such as trust online, social media, email and bulletin board. With so many media which are used in the delivery of lecturers schedule it is expected that lecturers, students and laboratory staff can obtain schedule information properly. However, this also frequently causes problems in learning activities like misplaced of room, time, class, and so on. This usually occurs because the schedule in one of the communication media about lecture schedule is not updated when there is a change of schedule, so there are differences in the schedule information among lectures, students and laboratory staff. To overcome these problems, it needs a service center of lecture schedules information to facilitate lecturers, students and laboratory staff in obtaining the latest lecture schedules information. Related to this, in this study we propose a design of email auto-reply application that will be the service center of lecturer schedules information. In this study, the research method is the method of object-oriented approach and the method of prototype system development. In building email auto-reply application, we are using the Java programming language with MySQL database. With the applications, it is expected that lecturers, students and laboratory staff can obtain the latest lecture schedule easily and from the same source, so different lecture schedules among lectures, students and laboratory staff do not happen again.

Author 1: Syahrul Mauluddin
Author 2: Leonardi Paris Hasugian
Author 3: Andri Sahata Sitanggang

Keywords: Email; auto-reply; service center; lecture schedule; java programming

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Paper 43: RSSI and Public Key Infrastructure based Secure Communication in Autonomous Vehicular Networks

Abstract: Autonomous Vehicular Ad hoc Networks (A-VANET) is also known as intelligent transportation systems. A-VANET ensures timely and accurate communications between vehicle to vehicle and Vehicle to Roadside Unit (RSU) to improve road safety and enhance the efficiency of traffic flow. Due to open wireless boundary and high mobility, A-VANET is vulnerable to several security threats especially impersonation, denial of service, pollution attacks. This paper presents a novel Received Signal Strength Indicator (RSSI) based public key infrastructure (PKI) to address the above-mentioned attacks. Each incoming signal will be authenticated based on RSSI value and digital signal (obtained using PKI) is utilized for cryptography and communication within the insecure channel. The proposed solution is verified with and without the presence of attacker by evaluating the packet delivery ratio and packet overhead.

Author 1: K Balan
Author 2: L. F. Abdulrazak
Author 3: A. S. Khan
Author 4: A. A. Julaihi
Author 5: S. Tarmizi
Author 6: K. S. Pillay
Author 7: H. Sallehudin

Keywords: Autonomous; vehicular ad hoc networks; public key infrastructure; received signal strength indicator

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Paper 44: Weighted Minkowski Similarity Method with CBR for Diagnosing Cardiovascular Disease

Abstract: This study implements Case-Based Reasoning (CBR) to make the early diagnosis of cardiovascular disease based on the calculation of the feature similarity of old cases. The features used to match old cases with new ones were age, gender, risk factors and symptoms. The diagnostic process was carried out by entering the case feature into the system, and then the system searched cases having similar features with the new case (retrieve). The level of similarity of each similar case was calculated using weighted Minkowski method. Cases with the highest level of similarity would be adopted as new case solutions. If the value of similarity was <0,8, the revision would be conducted by an expert. The tests result conducted by the expert showed that the system was able to perform the diagnosis correctly. The test results are performed on the sensitivity of 100% and specificity of 83,33%. Meanwhile, the accuracy of 95,83% and the error rate of 4,17% is so that this research is relevant enough to be implemented in the medical area.

Author 1: Edi Faizal
Author 2: Hamdani Hamdani

Keywords: CBR; cardiovascular; similarity; weighted Minkowski

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Paper 45: BYOD Implementation Factors in Schools: A Case Study in Malaysia

Abstract: The Bring Your Own Device (BYOD) initiative has been implemented widely in developed countries as a mechanism to prepare the students for the 4th industrial revolution. Success stories of the initiative vary depending on factors pertaining to its implementation. This study aims to identify the key factors to implement BYOD in schools for educational purposes. The research employed a mix-method approach by means of a survey. The data was collected from teachers through questionnaires and and from the school management through interviews. The respondents included 204 teachers from 5 schools in Putrajaya and Dengkil. Principals, senior assistants, ICT teachers and technicians from three schools were interviewed. They represented the school management group. A descriptive statistical analysis is conducted using SPSS statistical software. The research has identified four key factors for the successful implementation of BYOD in Malaysian schools. Two of the factors are related to the Cyber Security Policy at the schools - enforcing a secure network infrastructure and safety control requirement in the implementation of BYOD at schools. These security-related factors are important for the schools from the very beginning. They can be further categorized according to the implementation stages: pre-, during and post-adoption; cost allocation, preparation of controls and training to support BYOD's implementation at schools are the corresponding factors to each stage. On the other hand, the other two key factors are related to the schools’ readiness - ensuring the successful implementation of BYOD whereby the school management group is willing and prepared to tackle any arising BYOD-related issues in the future.

Author 1: Yusri Hakim bin Yeop
Author 2: Zulaiha Ali Othman
Author 3: Siti Norul Huda Sheikh Abdullah
Author 4: Umi Asma’ Mokhtar
Author 5: Wan Fariza Paizi Fauzi

Keywords: Cybersecurity awareness; cybersecurity education; safety; school cybersecurity policy

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Paper 46: A Schedule Optimization of Ant Colony Optimization to Arrange Scheduling Process at Certainty Variables

Abstract: This research aims to get optimal collision of schedule by using certainty variables. Courses scheduling is conducted by ant colony algorithm. Setting parameters for intensity is bigger than 0, visibility track is bigger than 0, and evaporation of ant track is 0.03. Variables are used such as a number of lecturers, courses, classes, timeslot and time. Performance of ant colony algorithms is measured by how many schedules same time and class collided. Based on executions, with a total of 175 schedules, the average of a cycle is 9 cycles (exactly is 9.2 cycles) and an average of time process is 29.98 seconds. Scheduling, in nine experiments, has an average of time process of 19.99 seconds. Performance of ant colony algorithm is given scheduling process more efficient and predicted schedule collision.

Author 1: Rangga Sidik
Author 2: Mia Fitriawati
Author 3: Syahrul Mauluddin
Author 4: A.Nursikuwagus

Keywords: Ant colony; optimization; scheduling; process; certainty variables

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Paper 47: Towards Secure Risk-Adaptable Access Control in Cloud Computing

Abstract: The emergence of pervasive cloud computing has supported the transition of physical data and machine into virtualization environment. However, security threat and privacy have been identified as a challenge to support the widespread adoption of cloud among user. Moreover, user awareness on the importance of cloud computing has increase the needs to safeguard the cloud by implementing access control that works on dynamic environment. Therefore, the emergence of Risk-Adaptable Access Control (RAdAC) as a flexible medium in handling exceptional access request is a great countermeasure to deal with security and privacy challenges. However, the rising problem in safeguarding users' privacy in RAdAC model has not been discussed in depth by other researcher. This paper explores the architecture of cloud computing and defines the existing solutions influencing the adoption of cloud among user. At the same time, the obscurity factor in protecting privacy of user is found within RAdAC framework. Similarly, the two-tier authentication scheme in RAdAC has been proposed in responding to security and privacy challenges as shown through informal security analysis.

Author 1: Salasiah Abdullah
Author 2: Khairul Azmi Abu Bakar

Keywords: Security; privacy; cloud computing; risk-adaptable access control; authentication

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Paper 48: Shape based Image Retrieval Utilising Colour Moments and Enhanced Boundary Object Detection Technique

Abstract: The need for automatic object recognition and retrieval have increased rapidly in the last decade. In content-based image retrieval (CBIR) visual cues such as colour, texture, and shape are the most prominent features used. Texture features are not considered as a significant discriminator unless it is integrated with colour features. Colour-based image retrieval uses global and/or local features has proved its ability to retrieve images with a high degree of accuracy. In contrast, shape-based retrieval is still suffering from numerous unsolved problems such as precise edge detection, overlapping objects, and high cost of feature extraction. In this paper, global colour features are utilized to discriminate unrelated images. Furthermore, a novel hybrid approach is proposed, consisting of a combination of boundary-based shape descriptor (BBSD) and region-based shape descriptor (RBSD), image retrieval. An enhanced object boundary detection (EBOD) is proposed, which uses canny edge detector to detect shape boundaries, with morphological opening to remove isolated nodes. Subsequently, morphological closing is utilized to solidify objects within the target image to enhance shape-based features representation. Finally, shape features are extracted and Euclidean distance measure with different threshold values to measure the similarity between feature vectors is adopted. Five semantic categories of WANG image database are selected to test the proposed approach. The results of experiments are promising, when compared with most common related approaches.

Author 1: Jehad Q Alnihoud

Keywords: Boundary Based Shape Descriptor (BBSD); Region Based Shape Descriptor (RBSD); CBIR, EBOD; edge detectors

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Paper 49: Evaluating the Applicability of a Social Content Management Framework: A Case Analysis

Abstract: Social media platform plays an important role in engaging customers. The social content resulting from social media interactions between the organisations and the customers need a proper management. Therefore, in this work, a framework for social content management is introduced to support the management of social content. This framework is developed based on two main concepts. The first is the existing concepts that are present in content management, whilst the second concept is derived from the theory of service science. This approach is adopted to cater for existing concepts in enterprise content management, that are relevant to social content management and also to cater for the concept of value co-creation which forms the basis of engagement between the organisations and the customers. The applicability of the proposed social content management framework needs to be evaluated in order to determine the extent of its applicability in practical situations. Therefore, the main focus of this article is to report the usability of the proposed framework against the practices of the government agencies of Malaysia in managing the social content. The evaluation method used is based on the score of system usability scale. The results from the evaluation revealed that the proposed framework is usable and is deemed practical to be used in organisations.

Author 1: Wan Azlin Zurita Wan Ahmad
Author 2: Muriati Mukhta
Author 3: Yazrina Yahya

Keywords: Service science; social content; social content management; social media; value co-creation

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Paper 50: An Efficient Rule based Decision Support System using Semantic Web Technology

Abstract: The Semantic Web technology is an efficient mechanism to query or infer knowledge on a global scale using the internet by providing logical reasoning through rule based system. In this paper application of semantic web technology is discussed in context of agriculture knowledge management and delivery. In agriculture, adoption of newly developed technology is essential to enhance crop production. However, timely dissemination of authenticated agriculture information for decision making at larger scale to diversified end user has always been a challenge due to several reasons. One of the reasons is storing and delivering agriculture knowledge in machine readable form. In this paper a frame work based on semantic web is presented for collection, storing and updating of agricultural information at centralized location and delivering knowledge through intelligent decision support system through semantic web. The frame work utilizes rule based system for querying information from agriculture knowledge base.

Author 1: Jawed Naseem
Author 2: S. M. Aqil Burney
Author 3: Nadeem Mehmood

Keywords: Agriculture information; semantic web; rule based system; intelligent DSS

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Paper 51: A Type-2 Fuzzy in Image Extraction for DICOM Image

Abstract: Eradication of a desired portion of an image is a very important role in image processing and is also called feature extraction. This is mainly concern about reducing the number of possessions required to portray a large set of data and also reduce memory space requirement and power of data processing. Perfectly optimized feature extraction is an essential process for an effective design construction. Though there are many tools are available for extracting a feature, Type-2 Fuzzy Logic plays a vital role in producing good results. In this paper, weighted arithmetic operator is proposed using Yager triangular norms and proved the properties of the triangular norms using proposed operator. Also, the paper relates the properties to feature extraction. Also Brain has been extracted from patient MRI DICOM image using MATLAB based on Type-2 Fuzzy setting.

Author 1: D Nagarajan
Author 2: M.Lathamaheswari
Author 3: J.Kavikumar
Author 4: Hamzha

Keywords: Feature extraction; MRI image; type-2 fuzzy; MATLAB; triangular norms; mathematical properties

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Paper 52: A Personalized Hybrid Recommendation Procedure for Internet Shopping Support

Abstract: Lately, recommender systems (RS) have offered a remarkable breakthrough to users. It lessens the user time cost thereby delivering faster and better results. After purchasing a product there are recommendations according to the different comments provided by users. Within a short span of product utilization and quality, the users receive a product recommendation. But this doesn’t work out good so as to make it much better;feedbacks, commands and reviews are fetched on the basis of in-depth commands, globally like and normal keys. Recommendation systems are crucially important for the delivery of personalized product to users. With personalized recommendation to product, users can enjoy a variety of targeted recommendations such as online product; the current paper suggests hybrid recommendation system (HRS) that makes use of rating and review to recommend any product to user. The main objective of this paper is to personalize recommendation of product that have become extremely effective revenue drivers for online shopping business. Despite the great benefits, deploying personalized recommendation services typically requires the collection of users’ personal data for processing and analytics, which undesirably makes users. To implement product recommendations following are incorporated that is retrieving personal data, Logical Language based Rule Generation (LLRG), ranking and Hybrid recommendation system. The stages in the suggested recommendation system include, Data Gathering, preprocessing, filtering and Ranking. The Ranking algorithm ranks the products in relation to the sales count. The top list displays the product having greatest count number. In the LLRG strategy, the logic rule generation methodology retrieves useful and mandatory data from reviews, commands, products original state and thereafter comes the recommendation. The HRS enforces two techniques, namely, location based and the other being heterogeneous domain based. Also the recommendations presented to the user are in context to the user’s activities, choices and conduct that are in accord with user’s personal likings and aids in decision making. When comparing the outcome, it is clear that the suggested method is superior than the traditional with regard to clarity, effective recommendation and coverage rate. It’s evaluated that Hybrid Recommendation System yields in greater results compared with rest of the existing recommendation techniques. We, also identity to some future research directions.

Author 1: R. Shanthi
Author 2: S.P. Rajagopalan

Keywords: Web mining; web search; products; ranking; recommendation system; hybrid approach; e-commerce; online shopping market

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Paper 53: Integration of REST-Based Web Service and Browser Extension for Instagram Spam Detection

Abstract: In this paper, a REST-based Web Service developed in previous work was integrated with a newly developed browser extension that works in modern browser (Firefox and Google Chrome) using Greasemonkey. It uses previous collected datasets which comprised of 17.000 postings and comments from 10 Indonesian actresses whom followers are more than 10 million on Instagram. The performance of the developed web services has been evaluated and the average response time is 1678.133ms using AWS platform located in Ohio (US East 2). The proposed work is working as expected and in accuracy test, it has reached 63.125% in overall, 72% for non-stemmed data and 70% for stemmed data using 1000 test data with a processing time needed for classification is under 2s. The new extension works in Firefox and Chrome and it can utilize the web services to classify spam comments in Instagram.

Author 1: Antonius Rachmat Chrismanto
Author 2: Willy Sudiarto Raharjo
Author 3: Yuan Lukito

Keywords: Instagram; spam comments; REST service; web service testing; browser extension

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Paper 54: Spectral Efficiency of Massive MIMO Communication Systems with Zero Forcing and Maximum Ratio Beamforming

Abstract: The massive multiple-input-multiple-output (MIMO) is a key enabling technology for the 5G cellular communication systems. In massive MIMO (M-MIMO) systems few hundred numbers of antennas are deployed at each base station (BS) to serve a relatively small number of single-antenna terminals with multiuser, providing higher data rate and lower latency. In this paper, an M-MIMO communication system with a large number of BS antennas with zero-forcing beamforming is proposed for the improved spectral efficiency performance of the system. The zero forcing beamforming technique is used to overcome the interference that limits the spectral efficiency of M-MIMO communication systems. The simulation results authenticate the improvement in the spectral efficiency of M-MIMO system. The spectral efficiency value using zero-forcing beamforming is near to the spectral efficiency value with the no-interference scenario.

Author 1: Asif Ali
Author 2: Imran Ali Qureshi
Author 3: Abdul Latif Memon
Author 4: Sajjad Ali Memon
Author 5: Erum Saba

Keywords: Massive MIMO; Base station; channel capacity; Spectral efficiency; latency; cellular communication; beamforming techniques; throughput; mobile communication

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Paper 55: Cluster Based Routing Protocols for Wireless Sensor Networks: An Overview

Abstract: Energy consumption of nodes in Wireless Sensor Networks (WSNs) is a very critical issue, particularly in scenarios where the energy of nodes cannot be recharged. Optimal routing approaches play a key role in energy utilization, so there is great importance of energy efficient routing protocols in WSNs. Energy efficient routing protocols in WSNs are categorized into four schemes, namely (i) communication model, (ii) topology based model, (iii) reliable routing, and (iv) network structure. Network structure category is further divided into flat and cluster-based approaches. This work focuses on a subtype of “network structure” scheme known as clustered based routing protocols, which are mainly used in WSNs for reduction in energy consumption. This work reviews and provides an overview of prominent cluster based energy efficient routing protocols on the basiss of some primary performance metrics such as (i) energy efficiency, (ii) algorithm complexity, (iii) scalability, (iv) data delivery delay, and (v) clustering approach. Finally, this work discusses some latest research trends with respect to cluster based energy efficient routing protocols in WSNs.

Author 1: Muhammad Nadeem Akhtar
Author 2: Arshad Ali
Author 3: Zulfiqar Ali
Author 4: Muhammad Adnan Hashmi
Author 5: Muhammad Atif

Keywords: Wireless sensor networks; network structure; clustering protocols; energy efficiency

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Paper 56: An Empirical Investigation on a Tool-Based Boilerplate Technique to Improve Software Requirement Specification Quality

Abstract: The process of producing software requirements specification (SRS) is known to be challenging due to the amount of effort, skills and experience needed in writing good quality SRS. A tool-based boilerplate technique is introduced to provide assistance in identifying essential requirements for a generic information management system and translating them into standard requirements statements in the SRS. This paper presents an empirical investigation to evaluate the usability of the prototype. Results showed that the tool-based boilerplate technique has high usability, usefulness and ease of use.

Author 1: Umairah Anuar
Author 2: Sabrina Ahmad
Author 3: Nurul Akmar Emran

Keywords: Empirical investigation; usability; software requirements

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Paper 57: New 3D Objects Retrieval Approach using Multi Agent Systems and Artificial Neural Network

Abstract: Content-based 3D object retrieval is a substantial research area that has drawn a significant number of scientists in last couple of decades. Due to the rapid advancement of technology, 3D models are more and more accessible yet it is hard to find, the models we are searching for. This created the need for efficient and robust retrieval methods, allowing the extraction of relevant matches from the human perspective. Hence, in this paper we are proposing a new framework for 3D object retrieval that starts with a pre-treatment consisting of an Artificial Neural Network (ANN) algorithm with Histogram of features, allowing us to extract a representative value for each category of the database. These values are used for the Multi Agents System (MAS). In this phase, we are classifying these categories according to their relevance to the request object. This sets a distinguishing weight for each object of the database allowing us to extract the right matches. Experiments have proven the stringent of this approach.

Author 1: Basma Sirbal
Author 2: Mohcine Bouksim
Author 3: Khadija Arhid
Author 4: Fatima Rafii Zakani
Author 5: Taoufiq Gadi

Keywords: 3D object retrieval; 3D image processing; distributed artificial intelligence; multi-agent systems; artificial neural network (ANN)

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Paper 58: Multi-Attributes Web Objects Classification based on Class-Attribute Relation Patterns Learning Approach

Abstract: The amount of Web data increases with the proliferation of a variety of Web objects, primarily in the form of text, images, video, and music data files. Each of these published objects has some properties that support defining its class properties. Because of their diversity, using these attributes to learn and generate patterns for precise classification is very complicated. Even learning a set of attributes that clearly categorize the categories is very important. Existing attribute learning methods only learn attributes that are closely related to multiple similar objects, but if similar class objects have different attributes, this problem is difficult to learn and classify them. In this paper, a Multi-attributes Web Objects Classification (MA-WOC) based on Class-attribute Relation Patterns Learning Approach is being proposed, which generates a class-attribute with its multi relations patterns. The MA-WOC calculates the relationship probabilities of the attributes and the associated values of the class to understand the degree of association of the construction of classification pattern. To evaluate the effectiveness of the classifier, this will compare to an existing classifier that supports a multi-attribute data set, which shows improvisation of precision with a significant minimum Hamming loss. To evaluate the effectiveness of MA-WOC classification a comparison among the classifiers that are supported to the multi-attribute dataset are being performed to measure the accuracy and hamming loss.

Author 1: Sridhar Mourya
Author 2: P.V.S. Srinivas
Author 3: M. Seetha

Keywords: Classification; multi-attributes; web objects; attribute learning; distinct-class relation

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Paper 59: Improved Design of an Adaptive Massive MIMO Spherical Antenna Array

Abstract: Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.

Author 1: Mouloud Kamali
Author 2: Adnen Cherif

Keywords: Adaptive spherical antenna; beam division multiple access BDMA; massive multiple input multiple output MIMO; millimeter-wave mm-wave

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Paper 60: Monitoring, Detection and Control Techniques of Agriculture Pests and Diseases using Wireless Sensor Network: A Review

Abstract: Wireless sensor network technology is widely used in the western world for improving agriculture output. However, in the developing countries, the adaptation of technology is very slow due to various factors such as cost and unawareness of farmers with the technology. There are reports in the literature related to the precision agriculture and hopefully, this paper will add to the knowledge of the use of Wireless sensor network (WSN) for monitoring agriculture fields for pest detection. The literature related to pest monitoring and detection using wireless sensor networking technologies are reviewed. Then, the advanced sensing technologies are currently in use for the detection of a pest has been described. The existing techniques about pest detection and disease monitoring are evaluated on the basis of some key parameters such as the type of sensors used, their cost, processing tools, etc. Finally, the sensing technologies and the possibility of using third generation sensing technology for monitoring and detection of cotton crops are analyzed.

Author 1: S. Azfar
Author 2: A.Nadeem
Author 3: A.B. Alkhodre
Author 4: K.Ahsan
Author 5: N. Mehmood
Author 6: T.Alghmdi
Author 7: Y.Alsaawy

Keywords: Component; pest monitoring and detection; Wireless Sensor Network; pests; agriculture; sensing technology

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Paper 61: Improved Discrete Differential Evolution Algorithm in Solving Quadratic Assignment Problem for best Solutions

Abstract: The combinatorial optimization problems are very important in the branch of optimization or in the field of operation research in mathematics. The quadratic assignment problem (QAP) is in the category of facilities location problems and is considered as one of the significant complex’s combinatorial optimization problems since it has many applications in the real world. The QAP is involved in allocating N facilities to N locations with specified distances amid the locations and the flows between the facilities. The modified discrete differential evolution algorithm has been presented in this study based on the crossover called uniform like a crossover (ULX). The proposed algorithm used to enhance the QAP solutions through finding the best distribution of the N facilities to N locations with the minimized total cost. The employed criteria in this study for the evaluation of the algorithm were dependent on the accuracy of the algorithm by using the relative percent deviation (PRD). The proposed algorithm was applied to 41 different sets of the benchmark QAPLIB, while the obtained results indicated that the proposed algorithm was more efficient and accurate compared with Tabu Search, Differential Evolution, and Genetic algorithm.

Author 1: Asaad Shakir Hameed
Author 2: Burhanuddin Mohd Aboobaider
Author 3: Ngo Hea Choon
Author 4: Modhi Lafta Mutar

Keywords: Quadratic assignment problem; combinatorial optimization problems; differential evolution algorithm

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Paper 62: A Novel Image Encryption Approach for Cloud Computing Applications

Abstract: In this paper, a novel image encryption approach is proposed in the context of cloud computing applications. A fast special transform based on non-equispaced grid technique is introduced and applied as the first time in image encryption applications. By Combining with Fractional Fourier Transform (FRFT) instead of Discrete Fourier Transform (DFT), a good framework for image encryption is opened to enhance data security degree. The both image encipherment and decipherment process are analyzed based on random phase matrix. The time complexity effort of this novel approach is examined and evaluated. Comparative study with traditional encryption algorithms will prove the efficiency and robustness of our proposed technique.

Author 1: Saleh ALTOWAIJRI
Author 2: Mohamed AYARI
Author 3: Yamen EL TOUATI

Keywords: Cloud computing; image encryption; fourier transform; random phase function

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Paper 63: Repetitive Control based on Integral Sliding Mode Control of Matched Uncertain Systems

Abstract: This paper proposed an integral sliding mode control scheme based on repetitive control for uncertain repetitive processes with the presence of matched uncertainties, external disturbances and norm-bounded nonlinearities. A new method based on the combination of repetitive control and sliding mode approach is studied in order to use the robustness sensibility property of the sliding mode control to matched uncertainties and disturbances and to cancel gradually tracking error for periodic processes. A sufficient condition of the existence of sliding mode is studied based on basic repetitive control and a sliding mode controller is synthesized through linear matrix inequalities, which guarantees the stability along the periods of the controlled closed-loop process and the reachability of the sliding surface is ensured. Then, an adaptive integral sliding mode controller is synthesized to improve performances of the proposed control scheme. The effectiveness of the proposed controlled design schemes is proved by the use of a third order uncertain mechanical system and the simulation results using the new approaches give good performances.

Author 1: Nizar TOUJENI
Author 2: Chaouki MNASRI
Author 3: Moncef GASMI

Keywords: Repetitive control; 2D systems; matched uncertainties; integral sliding mode control; sliding surface; linear matrix inequality; reachability

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Paper 64: Towards end-to-end Continuous Monitoring of Compliance Status Across Multiple Requirements

Abstract: Monitoring compliance status by an organization has been historically difficult due to the growing number of compliance requirements being imposed by various standards, frameworks, and regulatory requirements. Existing practices by organizations even with the assistance of security tools and appliances is mostly manual in nature as there is still a need for a human expert to interpret and map the reports generated by various solutions to actual requirements as stated in various compliance documents. As the number of requirements increases, this process is becoming either too costly or impractical to manage by the organization. Aside from the numerous requirements, multiple of these documents actually overlap in terms of domains and actual requirements. However, since current tools do not directly map and highlight overlaps as well as generate detailed gap reports, an organization would perform compliance activities redundantly across multiple requirements thereby increasing cost as well. In this paper, we present an approach that attempts to provide an end-to-end solution from compliance document requirements to actual verification and validation of implementation for audit purposes with the intention of automating compliance status monitoring as well as providing the ability to have continuous compliance monitoring as well as reducing the redundant efforts that an organization embarks on for multiple compliance requirements. This research thru enhancing existing security ontologies to model compliance documents and applying information extraction practices would allow for overlapping requirements to be identified and gaps to be clearly explained to the organization. Thru the use of secure systems development lifecycle, and heuristics the research also provide a mechanism to automate the technical validation of compliance statuses thereby allowing for continuous monitoring as well as mapping to the enhanced ontology to allow reusability via conceptual mapping of multiple standards and requirements. Practices such as unit testing and continuous integration from secure systems development life cycle are incorporated to allow for flexibility of the automation process while at the same time using it to support the mapping between compliance requirements.

Author 1: Danny C Cheng
Author 2: Jod B. Villamarin
Author 3: Gregory Cu
Author 4: Nathalie Rose Lim-Cheng

Keywords: Compliance management, continuous compliance monitoring; ontology mapping; natural language processing; secure systems development lifecycle

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Paper 65: Cloud Computing Auditing

Abstract: Cloud Computing is a new form of IT system and infrastructure outsourcing as an alternative to traditional IT Outsourcing (ITO). Hence, migration to cloud computing is rapidly growing among organizations. Adopting this technology brings numerous positive aspects, although imposing different risks and concerns to organization. An organization which officially deputes its cloud computing services to outside (offshore or inshore) providers and implies that it outsources its functions and process of its IT to external BPO services providers. Therefore, customers of cloud must evaluate and manage the IT infrastructure construction and the organization’s IT control environment of BPO vendors [25]. Since cloud is an internet-based technology, cloud auditing would be very critical and challengeable in such an environment. This paper focuses on practices related to auditing processes, methods, techniques, standards and frameworks in cloud computing environments.

Author 1: Mohammad Moghadasi
Author 2: Seyed Majid Mousavi
Author 3: Gábor Fazekas

Keywords: Cloud computing; cloud auditing; IT outsourcing

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Paper 66: Recommender System based on Empirical Study of Geolocated Clustering and Prediction Services for Botnets Cyber-Intelligence in Malaysia

Abstract: A recommender system is becoming a popular platform that predicts the ratings or preferences in studying human behaviors and habits. The predictive system is widely used especially in marketing, retailing and product development. The system responds to users preferences in goods and services and gives recommendations via Machine Learning algorithms deployed catered specifically for such services. The same recommender system can be built for predicting botnets attack. Via our Integrated Cyber-Evidence (ICE) Big Data system, we build a recommender system based on collected data on telemetric Botnets networks traffics. The recommender system is trained periodically on cyber-threats enriched data from Coordinated Malware Eradication & Remedial Platform system (CMERP), specifically the geolocations and the timestamp of the attacks. The machine learning is based on K-Means and DBSCAN clustering. The result is a recommendation of top potential attacks based on ranks from a given geolocations coordinates. The recommendation also includes alerts on locations with high density of certain botnets types.

Author 1: Nazri Ahmad Zamani
Author 2: Aswami Fadillah Mohd Ariffin
Author 3: Siti Norul Huda Sheikh Abdullah

Keywords: Botnets; recommender system; predictive analytics; Big Data; cyber-threat intelligence; K-Means; DBSCAN

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Paper 67: Cyber Romance Scam Victimization Analysis using Routine Activity Theory Versus Apriori Algorithm

Abstract: The advance new digital era nowadays has led to the increasing cases of cyber romance scam in Malaysia. These technologies have offered both opportunities and challenge, depending on the purpose of the user. To face this challenge, the key factors that influence the susceptibility to cyber romance scam need to be identified. Therefore, this study proposed cyber romance scam models using statistical method and Apriori techniques to explore the key factors of cyber romance scam victimization based on the real police report lodged by the victims. The relationship between demographic variables such as age, education level, marital status, monthly income and independent variables such as level of computer skills and the level of cyber-fraud awareness has been investigated. Then, the result of this study was compared with Routine Activity Theory (RAT). This study found that those between the ages of 25 and 45 years were likely to be the victims of cyber romance scams in Malaysia. The majority of the victims are educated and having a Diploma. In addition, this research shows that married people are more likely to be the victims of cyber romance scams. Study shows that non-income individuals are also vulnerable to being the victims because the study shows that 17 percent of respondents who are the victims are from this group. As expected, those who work and have monthly income between RM2001 and above are more likely to be targeted and become a victim of cyber romance scams. The study also shows that those who lack computer skills and less levels of cyber-fraud awareness are more likely to be victims of cyber romance scams.

Author 1: Mohd Ezri Saad
Author 2: Siti Norul Huda Sheikh Abdullah
Author 3: Mohd Zamri Murah

Keywords: Cybercrime; love-scam; routine activity theory

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Paper 68: Deep Learning-Based Model Architecture for Time-Frequency Images Analysis

Abstract: Time-frequency analysis is an initial step in the design of invariant representations for any type of time series signals. Time-frequency analysis has been studied and developed widely for decades, but accurate analysis using deep learning neural networks has only been presented in the last few years. In this paper, a comprehensive survey of deep learning neural network architectures for time-frequency analysis is presented and compares the networks with previous approaches to time-frequency analysis based on feature extraction and other machine learning algorithms. The results highlight the improvements achieved by deep learning networks, critically review the application of deep learning for time-frequency analysis and provide a holistic overview of current works in the literature. Finally, this work facilitates discussions regarding research opportunities with deep learning algorithms in future researches.

Author 1: Haya Alaskar

Keywords: Convolutional neural network; time-frequency; spectrogram; scalograms; Hilbert-Huang transform; deep learning; sound signals; biomedical signals

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Paper 69: Construction of TVET M-Learning Model based on Student Learning Style

Abstract: Mobile learning or m-learning is emerging as the innovation of virtual learning that used mobile devices for teaching and learning which can be accessed readily at hand anywhere either in classroom or group. Whereas preliminary study showed that Technical and Vocational Education and Training (TVET) institution were still using the conventional learning, where the students were not getting much exposure at all towards m-learning. In fact, this research discussed about the development and validating the usability of TVET m-learning model based on the user requirements that categorized into three main aspects: devices, users and social. The research scope focused on TVET students as the target users. While, user-centered design (UCD) method has been used in this research through four phases which were analyzing the user requirements, designing model, developing prototype and evaluating usability. Based on the usability evaluation results showed that TVET m-learning model is acceptable and compatible as a guideline of m-learning development for the TVET students. This TVET m-learning model brings benefits in improving the quality of teaching and learning in TVET institutions especially the public training skills institutions to achieve the nation goals in order to become a successful developing country and produce skilled workers in the future as well.

Author 1: Azmi S
Author 2: Mat Noor S.F
Author 3: Mohamed H

Keywords: M-learning; technical and vocational education and training (TVET); user-centered design (UCD)

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Paper 70: Recurrence Relation for Projectile Simulation Project and Game based Learning

Abstract: Huge Gap has been observed on study of projectile simulation models relating it to speed of camera or frame per seconds. The objective of this paper is to explore and investigate time driven simulation models to mimic projectile trajectory; with an intent to highlight importance of game programming on native platforms. The proposed projectile recurrence relation and extensive mathematical modeling based on Triangular Series is an innovative outcome of project and game based learning used in BSCS-514 Computer Graphics Course at Department of Computer Science (DCS) University of Karachi (UOK). Box2D Replica of Popular 2D Mobile Game Angry Bird has been created on desktop to have an in depth mathematical and programming insight of commercial physics engine and discrete event simulation. Analysis has also been performed to answer certain key questions for progressive projectile trajectory for e.g. (1) With What angle, projectile should be launched? (2) What is the maximum height it will reach? (3) How long it will take for landing? (4) What will be its velocity to reach a desired height? (4) Where it will hit? (5) How it will bounce? The above stated questions are important to answer so that projectile motion within engineering, Gaming and other CAD Applications can be taught and programmed correctly specially on native platforms like OpenGL. Besides reporting Numerical results, a successful projectile based game making has been compiled and reported to validate the significance of project based learning in classrooms and labs.

Author 1: Humera Tariq
Author 2: Tahseen Jilani
Author 3: Ebad Ali
Author 4: Syed Faraz
Author 5: Usman Amjad

Keywords: Projectile; game programming; simulation; angry birds; linear drag; trajectory; impulse

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Paper 71: Embedded Feature Selection Method for a Network-Level Behavioural Analysis Detection Model

Abstract: Feature selection in network-level behavioural analysis studies is used to represent the network datasets of a monitored space. However, recent studies have shown that current behavioural analysis methods at the network-level have several issues. The reduction of millions of instances, disregarded parameters, removed similarities of most of the traffic flows to reduce information noise, insufficient number of optimised features and ignore instances which are not an entity are amongst the other issue that have been identified as the main issues contributing to the inability to predict zero-day attacks. Therefore, this paper aims to select the optimal features that will improve the prediction and behavioural analysis. The training dataset will be trained to use the embedded feature selection method which incorporates both the filter and wrapper method. Correlation coefficient, r and weighted score, wj will be used. The accepted or selected features will be optimised uses Beta distribution functions, β, to find its maximum likelihood, Ɩmax. The final selected features will be trained by the Bayesian Network classifier and tested through several testing datasets. Finally, this method was compared to several other feature selection methods. Final results show the proposed selection method’s performance against other datasets consistently outperform other methods.

Author 1: Mohammad Hafiz Mohd Yusof
Author 2: Mohd Rosmadi Mokhtar
Author 3: Abdullah Mohd. Zain
Author 4: Carsten Maple

Keywords: Feature selection; intrusion detection; behavioural analysis

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Paper 72: Solving Dynamic Programming Problem by Pipeline Implementation on GPU

Abstract: In this paper, we show the effectiveness of a pipeline implementation of Dynamic Programming (DP) on GPU. As an example, we explain how to solve a matrix-chain multiplication (MCM) problem by DP on GPU. This problem can be sequentially solved in O(n3) steps by DP where n is the number of matrices, because its solution table is of size n × n and each element of the table can be computed in O(n) steps. A typical speedup strategy for this is to parallelize the O(n) step computation of each element, which can be easily achieved by parallel prefix computation, i.e., an O(log n) step computation with n threads in a tournament fashion. By such a standard parallelizing method, we can solve the MCM problem in O(n2 log n) steps with n threads. In our approach, we solve the MCM problem on GPU in a pipeline fashion, i.e., we use GPU cores for supporting pipeline-stages so that many elements of the solution table are partially computed in parallel at one time. Our implementation determines one output value per one computational step with n threads in a pipeline fashion and constructs the solution table totally in O(n2) steps with n threads.

Author 1: Susumu Matsumae
Author 2: Makoto Miyazaki

Keywords: Dynamic programming; pipeline implementation; GPGPU

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Paper 73: FPGA based Hardware-in-the-Loop Simulation for Digital Control of Power Converters using VHDL-AMS

Abstract: This paper presents a new approach for complex system design, allowing rapid, efficient and low-cost prototyping. Using this approach can simplify designing tasks and go faster from system modeling to effective hardware implementation. Designing multi-domain systems require different engineering competences and several tools, our approach gives a unique design environment, based on the use of VHDL-AMS modeling language and FPGA device within a single design tool. This approach is intended to enhance hardware-in-the-loop (HIL) practices with a more realistic simulation which improve the verification process in the system design flow. This paper describes the implementation of a software/hardware platform as effective support for our methodology. The feasibility and the benefits of the presented approach are demonstrated through a practical case study of a power converter control. The obtained results show that the developed method achieves significant speed-up compared with conventional simulation methods, using minimum resources and minimum latency.

Author 1: Abdelouahab Djoubair Benhamadouche
Author 2: Adel Ballouti
Author 3: Farid Djahli
Author 4: Abdeslem Sahli

Keywords: Hardware-in-the-Loop (HIL) simulation; Field-Programmable Gate Array (FPGA); VHDL-AMS; power converter; digital controller

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Paper 74: Partial Greedy Algorithm to Extract a Minimum Phonetically-and-Prosodically Rich Sentence Set

Abstract: A phonetically-and-prosodically rich sentence set is so important in collecting a read-speech corpus for developing phoneme-based speech recognition. The sentence set is usually searched from a huge text corpus of million sentences using the optimization methods. One of the commonly used optimization methods for this case is a Least-to-Most Greedy (LTMG) algo-rithm. It is effective in minimizing the number of phoneme-units. Unfortunately, it does not distribute their frequencies. In this paper, a new method called Partial LTMG algorithm (PLTMG) is proposed to search an optimum set containing triphones and prosodies those are distributed in a near-uniform fashion. Testing on an Indonesian text corpus of ten million sentences crawled from some websites of newspapers and novels shows that the proposed method is not only capable of minimizing both phoneme-units and prosodies but also effective in distributing their frequencies.

Author 1: Fahmi Alfiansyah
Author 2: Suyanto

Keywords: Automatic speech recognition; minimum sentence set; prosody; speech corpus; triphone

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Paper 75: NB-IoT Pervasive Communications for Renewable Energy Source Monitoring

Abstract: Renewable sources like solar and wind energy have seen a drastic increase in the market, especially in developing countries where electricity prices are high and QoS and QoE, both are at their lowest. In this paper, we innovate by proposing a paradigm of smart off-grid from sensing using an Internet of Things (IoT) based smart meter for continuous monitoring, to reporting a daily user on their smart devices using IoT middleware. Our proposed smart off-grid system keeps track of the performance and faults of the off-grid equipment. Under communication technology scrutiny, we model 3GPP Narrow Band IoT (NB-IoT) collision and success probability of grouping smart meter communications to avoid random access channel (RACH) congestion. The proposed smart off-grid communications outperform existing systems and achieve 1.3 to 20 times higher SINR, more than 30 Mbps data rate in 4G, three times higher data rate in NB-IoT, 25% fewer collisions and 25% higher success rate.

Author 1: Farooque Hassan Kumbhar

Keywords: NB-IoT; smart off-grid; RACH; 4G LTE

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Paper 76: The SMH Algorithm : An Heuristic for Structural Matrix Computation in the Partial Least Square Path Modeling

Abstract: The Structural equations modeling with latent’s variables (SEMLV) are a class of statistical methods for modeling the relationships between unobservable concepts called latent variables. In this type of model, each latent variable is described by a number of observable variables called manifest variables. The most used version of this category of statistical methods is the partial least square path modeling (PLS Path Modeling). In PLS Path Modeling, the specification of the relashonships between the unobservable concepts, knows as structural relationships, is the most important thing to know for practical purposes. In general, this specification is obtained manually using a lower triangular binary matrix. To obtain this lower triangular matrix, the modeler must put the latent variables in a very precise order, otherwise the matrix obtained will not be triangular inferior. Indeed, the construction of such a matrix only reflects the links of cause and effect between the latent variables. Thus, with each ordering of the latent variables corresponds a precise matrix.The real problem is that, the more the number of studied concepts increases, the more the search for a good order in which it is necessary to put the latent variables to obtain a lower triangular matrix becomes more and more tedious. For five concepts, the modeler must test 5! = 120 possibilities. However, in practice, it is easy to study more than ten variables, so that the manual search for an adequate order to obtain a lower triangular matrix extremely difficult work for the modeler. In this article, we propose an heuristic way to make possible an automatic computation of the structural matrix in order to avoid the usual manual specifications and related subsequent errors.

Author 1: Odilon Yapo M Achiepo
Author 2: Edoete Patrice Mensah
Author 3: Edi Kouassi Hilaire

Keywords: Structural equations modeling; PLS algorithm; la-tents variables; structural matrix; R programming language

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Paper 77: scaleBF: A High Scalable Membership Filter using 3D Bloom Filter

Abstract: Bloom Filter is extensively deployed data structure in various applications and research domain since its inception. Bloom Filter is able to reduce the space consumption in an order of magnitude. Thus, Bloom Filter is used to keep information of a very large scale data. There are numerous variants of Bloom Filters available, however, scalability is a serious dilemma of Bloom Filter for years. To solve this dilemma, there are also diverse variants of Bloom Filter. However, the time complexity and space complexity become the key issue again. In this paper, we present a novel Bloom Filter to address the scalability issue without compromising the performance, called scaleBF. scaleBF deploys many 3D Bloom Filter to filter the set of items. In this paper, we theoretically compare the contemporary Bloom Filter for scalability and scaleBF outperforms in terms of time complexity.

Author 1: Ripon Patgiri
Author 2: Sabuzima Nayak
Author 3: Samir Kumar Borgohain

Keywords: Bloom filter; membership filter; scalable bloom filter, duplicate key filter; hashing; data structure, membership query.

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Paper 78: Discovery of Corrosion Patterns using Symbolic Time Series Representation and N-gram Model

Abstract: There are many factors that can contribute to corrosion in the pipeline. Therefore, it is important for decision makers to analyze and identify the main factor of corrosion in order to take appropriate actions. The factor of corrosion can be analyzed using data mining based on historical datasets collected from monitoring sensors. The purpose of this study is to analyze the trends of corroding agents for pipeline corrosion based on symbolic representation of time series corrosion dataset using Symbolic Aggregation Approximation (SAX). The paper presents the analysis and evaluation of the patterns using N-gram model. Text mining using N-gram model is proposed to mine trend changes from corrosion time series dataset that are transformed as symbolic representation. N-gram was applied for the analysis in order to find significant symbolic patterns that are represented as text. Pattern analysis is performed and the results are discussed according to each environmental factor of pipeline corrosion.

Author 1: Shakirah Mohd Taib
Author 2: Zahiah Akhma Mohd Zabidi
Author 3: Izzatdin Abdul Aziz
Author 4: Farahida Hanim Mousor
Author 5: Azuraliza Abu Bakar
Author 6: Ainul Akmar Mokhtar

Keywords: Pipelines corrosion analysis; Symbolic Aggregation Approximation (SAX) representation; corrosion patterns; corrosion factor

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Paper 79: Impact of Android Phone Rooting on User Data Integrity in Mobile Forensics

Abstract: Modern cellular phones are potent computing de-vices, and their capabilities are constantly progressing. The Android operating system (OS) is widely used, and the number of accessible apps for Android OS phones is unprecedented. The increasing capabilities of these phones imply that they have distinctive software, memory designs, and storage mechanisms. Furthermore, they are increasingly being used to commit crimes at an alarming rate. This aspect has heightened the need for digital mobile forensics. Because of the rich user data they store, they may be relevant in forensic investigations, and the data must be extracted. However, as this study will show, most of the available tools for mobile forensics rely greatly on rooted (Android) devices to extract data. Rooting, as some of the selected papers in this research will show, poses a key challenge for forensic analysts: user data integrity. Rooting per se, as will be seen, is disadvantageous. It is possible for forensic analysts to extract useful data from Android phones via rooting, but the user data integrity during data acquisition from Android devices is a prime concern. In suggesting an alternative rooting technique for data acquisition from an Android handset, this paper determines whether rooting is forensically sound. This is particularly due to the device’s modification, which a root often requires, that may violate the data integrity.

Author 1: Tahani Almehmadi
Author 2: Omar Batarfi

Keywords: Android; rooting; data integrity; mobile forensics

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Paper 80: Neighbour-Cooperation Heterogeneity-Aware Traffic Engineering for Wireless Sensor Networks

Abstract: Extending the operational duration is a major field of interest in Wireless Sensor Networks (WSNs). This lifetime enhancement task challenges researchers to design an energy ef-ficient traffic engineering which minimizes the dissipation energy and retain the expected quality of routing protocols. Network lifetime can be prolonged by balancing the energy optimization throughout the network period over which sensors relay data traffic towards Base Station (BS). Existing techniques of continu-ous and autonomous reporting sensor nodes, offer an opportunity to design the sensing and reporting co-operation between sensor nodes. Nearby nodes with similar reading environment can co-operate with each other to avoid transmission redundant infor-mation. In this paper we propose “Adaptive Inter-Networking Improved (AINI)” multi-hop routing protocol with co-operate sensing of inter and intra cluster communication by exploiting the concept of tripling the sensor nodes. Proposed routing protocol improved the reliability of whole network by improving the reliability of inter-cluster multi-hoping. Sensor nodes use the shortest path to deliver data to CH using intra-cluster multi-hoping and these CHs are accountable to forward this data to BS using inter-cluster multi-hop communication. Proposed routing protocol resolves the certain issues of WSN like network lifetime, network stability and CHs selection technique. To prove the efficiency of our proposed model we compared the simulation results with existing state-of-the art routing protocols such as, LEACH, LEACH-C, SEP, ESEP and DEEC. Experimental results shows the benefits of neighbour cooperation and heterogeneity-aware by the performance of proposed protocol over existing state-of-the-art routing protocols.

Author 1: Christopher Mumpe
Author 2: Da Tang
Author 3: Muhammad Asad
Author 4: Muhammad Aslam
Author 5: Jing Chen
Author 6: Jinsi Zhu
Author 7: Luyuan Jin

Keywords: Wireless Sensor Networks; energy efficient; cluster-ing; multi-hop; routing protocol

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Paper 81: A Proposed Model of Cloud based e-Learning for Najran University

Abstract: For the time being, the educational institutions are keen to use e-learning in their educational environment. This, in turn, will support their learning process and allow the learners to access any service or learning material or information at any time they need it. With all the pros by the e-learning, it still suffers from many problems that are explained clearly in this paper. In contrast, along with the innovation of cloud computing technology as a new paradigm in the IT world. With the establishment of cloud computing, numerous services for numerous fields (e.g., education, business, and government) have been introduced that have greatly facilitated the e-learning. In this paper, it demonstrates how the inclusion of the cloud computing paradigm in the e-learning environment assist positively. A lot of obstacles that are introduced by e-learning have been remedied. It combines the cloud computing in the e-learning system, thus, the proposed E-learning Embracing Cloud Computing Model (ELECCM) has completely developed and performed with all the essential components that are needed for their architecture. The study presents all the procedures that are run in order by the proposed system. Then, a fully functional e-learning system based on cloud computing; with low cost and low technical barriers, is demonstrated and explained clearly.

Author 1: Ibrahim Abdulrab Ahmed
Author 2: Zakir Hussain

Keywords: E-learning; cloud computing; E-learning Embrac-ing Cloud Computing Model (ELECCM); SaaS; PaaS; IaaS

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Paper 82: Web Assessment of Libyan Government e-Government Services

Abstract: Libya has started transferring traditional govern-ment services into e-government services. The e-government initiative involves the use of websites to offer various services such as civil registration, financial transaction and private information handling. Currently, there has not been many studies about the security assessment of the Libyan government websites. Therefore, in this paper, we did a web security assessment of 16 Libyan government websites. The main purpose of this study is to determine the security level of these websites. The web security as-sessment was done in four phases: Reconnaissance, Enumeration and Scanning, Vulnerability assessment (web vulnerabilities and SSL encryption evaluation) and Content Analysis(security and privacy policies). The results showed that 9 websites have high and medium level vulnerabilities. Only 3 websites have A SSL rating. Also, only 3 websites have published security and privacy policies. We found 1 highly unsafe website, 6 unsafe websites, 8 somewhat safe websites and, 1 safe website. Overall, the study indicated the Libyan government websites are adequately secured without major security issues. Since these Libyan government websites deal with sensitive data, adequate security measures should be implemented to reduce the vulnerabilities and to mitigate future cyber security attacks.

Author 1: Mohd Zamri Murah
Author 2: Abdullah Ahmed Ali

Keywords: Libya; e-Government; web security assessment; in-formation security; website vulnerability; penetration testing

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Paper 83: Swarm Eye: A Distributed Autonomous Surveillance System

Abstract: Conventional means such as Global Positioning System (GPS) and satellite imaging are important information sources but provide only limited and static information. In tactical situations rich 3D images and dynamically self-adapting information are needed to overcome this restriction; this information should be collected where it is available. Swarms are sets of interconnected units that can be arranged and coordinated in any flexible way to execute a specific task in a distributed manner. This paper introduces Swarm Eye – a concept that provides a platform for combining the powerful techniques of swarm intelligence, emergent behaviour and computer graphics in one system. It allows the testing of new image processing concepts for a better and well informed decision making process. By using advanced collaboratively acting eye units, the system can observe, gather and process images in parallel to provide high value information. To capture visual data from an autonomous UAV unit, the unit has to be in the right position in order to get the best visual sight. The developed system also provides autonomous adoption of formations for UAVs in an autonomous and distributed manner in accordance with the tactical situation.

Author 1: Faisal Khan
Author 2: Jörn Mehnen
Author 3: Tarapong Sreenuch
Author 4: Syed Alam
Author 5: Paul Townsend

Keywords: Swarm intelligence; distributed surveillance system; bio-inspired algorithm; cooperative UAVs

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Paper 84: A Review of Data Synchronization and Consistency Frameworks for Mobile Cloud Applications

Abstract: Mobile devices are rapidly becoming the predom-inant means of accessing the Internet due to advances in wireless communication techniques. The development of Mobile applications (“apps”) for various platforms is on the rise due to growth in the number of connected devices. Numerous apps rely on cloud infrastructure for data storage and sharing. Apart from advances in wireless communication and device technology, there is a lot of research on special data management techniques that addressed the limitations of mobile wireless computing to make the data appear seamless for accessing and retrieval. This paper is an effort to survey the frameworks that support data consistency and synchronization for mobile devices. These frameworks offer a solution for the unreliable connection prob-lem with customized synchronization and replication processes and hence helps in synchronizing with multiple clients. The frameworks are compared for the parameters of consistency and data models (table, objects or both) support along with techniques of synchronization protocol and conflict resolution. The review paper has produced interesting results from the selected studies in areas such as data consistency, handling offline data, data replication, synchronization strategy. The paper is focused on client-centric data consistency and the offline data synchronization feature of various frameworks.

Author 1: Yunus Parvej Faniband
Author 2: Iskandar Ishak
Author 3: Fatimah Sidi
Author 4: Marzanah A. Jabar

Keywords: Mobile cloud computing; data consistency; mobile back-end as a service; distributed systems; mobile apps

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Paper 85: Performance Evaluation WPAN of RN-42 Bluetooth based (802.15.1) for Sending the Multi-Sensor LM35 Data Temperature and RaspBerry Pi 3 Model B for the Database and Internet Gateway

Abstract: This research will be a test of a multi-sensor data transmission using the Wireless Sensor Network based on Bluetooth RN-42. Accordingly this research, LM35 is a type of Temperature Sensor, furthermore, this research will be used two LM35 sensors installed on the Arduino board and to be processed by Arduino Integrated Development of Environment (IDE) with C++ language. Arduino will be sending of all sensor data from LM35 temperature sensor by Slave RN-42 Bluetooth Configuration to master RN-42 Bluetooth configuration. Furthermore, the temperature data will be sending on Raspberry Pi 3 as an Internet Gateway then data will be sent to the internet and sensor data will be stored in the MySQL database. Furthermore, Sensor data can be accessed by other computers on the internet network using PuTTY with the Raspberry Pi 3 IP Address 192.168.1.145. Moreover, testing is also done by measuring the Signal power of Wireless Personal Area Network with the Receive Signal Strength Indicator variable, so the Bluetooth signal strength in sending multi-sensor data can be known appropriately.

Author 1: Puput Dani Prasetyo Adi
Author 2: Akio Kitagawa

Keywords: RSSI; Bluetooth; Raspberry pi 3; Internet Gateway

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Paper 86: Underwater Optical Fish Classification System by Means of Robust Feature Decomposition and Analysis using Multiple Neural Networks

Abstract: Live fish recognition and classification play a pivotal role in underwater understanding, because it help scientists to control the subsea inventory in order to aid fishery management. However, despite technological progress, fish recognition systems still have many limitations on observing fish. Difficulties in visualizing optical images can arise due to external attenua-tion, scattering properties of water. Optical underwater imaging systems can also have detection problems such as changing appearance/orientation of objects, and changes in the scene. In this paper, we propose a new object classification system for underwater optical images. The proposed method is based on robust feature extraction from fish pattern. A specific pre-processing method is used in order to improve the recognition accuracy. A mean-shift algorithm is charged to segment the images and to isolate objects from background in the raw images. The training data is processed by Principal component analysis (PCA), where we calculate the prior probability inter-features. The decision is given using a combined Bayesian Artificial Neural networks (ANNs). ANNs will calculate non linear relationship of the extracted features, and the posterior probabilities. These probabilities will be verified in the last step in order to keep (or reject) the decision. The comparison of results with state of the art methods shows that the proposed system outperforms most of the solutions in different environmental conditions. The solution simultaneously deals with artificial and reel environment. The results obtained in the simulation indicate that the proposed approach provides a good precision to make distinguish between different fish species. An average accuracy of 94.6% is achieved using the proposed recognition method.

Author 1: Mohcine Boudhane
Author 2: Benayad Nsiri
Author 3: Taoufiq Belhoussine Drissi

Keywords: Fish recognition; Optical image analysis; scene understanding; principal component analysis; non-linear artificial neural networks

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