IJACSA Volume 9 Issue 6 - thesai.org

IJACSA Volume 9 Issue 6

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

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Paper 1: Generating Classification Rules from Training Samples

Abstract: In this paper, we describe an algorithm to extract classification rules from training samples using fuzzy membership functions. The algorithm includes steps for generating classification rules, eliminating duplicate and conflicting rules, and ranking extracted rules. We have developed software to implement the algorithm using MATLAB scripts. As an illustration, we have used the algorithm to classify pixels in two multispectral images representing areas in New Orleans and Alaska. For each scene, we randomly selected 10 per cent of the samples from our training set data for generating an optimized rule set and used the remaining 90 per cent of samples to validate the extracted rules. To validate extracted rules, we built a fuzzy inference system (FIS) using the extracted rules as a rule base and classified samples from the training set data. The results in terms of confusion matrices are presented in the paper.

Author 1: Arun D. Kulkarni

Keywords: Fuzzy membership functions; classification; rule extraction; multispectral images

Paper 2: Robust Control of a 3D Space Robot with an Initial Angular Momentum based on the Nonlinear Model Predictive Control Method

Abstract: This paper considers robust control problems for a 3D space robot of two rigid bodies connected by a universal joint with an initial angular momentum. It is particularly difficult to measure an initial angular momentum in parameters of space robots since the value of an initial angular momentum depends on the situations. Hence, the main purpose of this paper is to develop a robust controller with respect to initial angular momenta for the 3D space robot. First, a mathematical model, some characteristics, and two types of control problems for the 3D space robot are presented. Next, for the robust attitude stabilization control problem of the 3D space robot, a numerical simulation is performed by using the nonlinear model predictive control method. Then, for the robust trajectory tracking control problem of the 3D space robot, another numerical simulation is carried out. As a result, it turns out that this approach can realize robust control on initial angular momenta for the two control problems. In addition, computation amount is reduced by this approach and real-time control of the 3D space robot can be achieved.

Author 1: Tatsuya Kai

Keywords: 3D space robot; universal joint; initial angular momentum; nonlinear model predictive control; robustness; attitude stabilization control; trajectory tracking control

Paper 3: Link Prediction Schemes Contra Weisfeiler-Leman Models

Abstract: Link prediction is of particular interest to the data mining and machine learning communities. Until recently all approaches to the problem used embedding-based methods which leverage either node similarities or latent group memberships towards link prediction. Chen and Zhang recently developed a class of non-embedding approaches called Weisfeiler-Leman (WL) Models. WL-Models extract subgraphs around links and then encode subgraph patterns via adjacency matrices using the so-called Palette-WL algorithm. A training stage then learns nonlinear graph topological features for link prediction. Chen and Zhang compared two WL-Models – a linear regression model (“WLLR”) and a neural networks model (“WLNM”) – against 12 different common link prediction schemes. In this paper, all author claims are validated for WLLR. Additionally, WLLR is tested against 22 additional embedding-based link prediction techniques arising from common neighbor-, path- and random walk-based schemes. WLLR is shown not to be superior when calculable. In fact, in 80% of the datasets where comparisons were possible, one of our added implementations proved superior.

Author 1: Katie Brodhead

Keywords: Weisfeiler-Leman; link prediction; machine learning; linear regression; common walk; path-based; random walk; stochastic block; matrix factorization

Paper 4: Methodology for Selecting the Preferred Networked Computer System Solution for Dynamic Continuous Defense Missions

Abstract: This paper presents a methodology for addressing the challenges and opportunities in defining and selecting the preferred Networked Computer System (NCS) solution in response to specified United States Defense mission planning requirements. The identified set of mission requirements are aligned with existing computer system capabilities allowing them to be acquired and processed as candidates to be included as part of the preferred NCS solution. In performing the proper selection process, decision making process is required in being able to properly select the preferred NCS by utilizing associated models for analysis. The models will then be applied towards NCS mission planning in analyzing an NCS solution’s effectiveness in terms of operational availability, mission reliability, capability sustainment and lifecycle cost. The analysis and models were developed in response to the need to develop defense mission planning capability solutions by utilizing existing computer systems enabling the Department of Defense acquisition professionals to perform a practical approach in selecting and defining the preferred NCS for satisfying a mission.

Author 1: San Diego

Author 2: Jeff Tian

Author 3: Jerrell T. Stracener

Keywords: Mission reliability; sustainment reliability; operational availability; basic reliability; networked computer system; system of systems

Paper 5: Multi Focus Image Fusion using Combined Median and Average Filter based Hybrid Stationary Wavelet Transform and Principal Component Analysis

Abstract: Poor illumination, less background contrast and blurring effects makes the medical, satellite and camera images difficult to visualize. Image fusion plays the vital role to enhance image quality by resolving the above issues and reducing the image quantity. The combination of spatial and spectral technique Discrete Wavelet Transform and Principal Component Analysis (DWT-PCA) decrease processing time and reduce number of dimensions but down sampling causes lack of shift invariance that results in poor quality final fused image. At first this work uses combined median and average filter that eliminates noise in the image which is caused by illumination, camera circuitry and sensor at preprocessing stage. Then, hybrid Stationary Wavelet Transform and Principal Component Analysis (SWT-PCA) technique is implemented to increase output image accuracy by eliminating down sampling and is not influenced by artifacts and blurring effects. Further, it can overcome the trade-off of Heisenberg’s uncertainty principle by improving accuracy in both domains, time (spatial) as well as frequency (spectral). The proposed combined median and average filter with hybrid SWT-PCA algorithm measures quality parameters, such as peak signal to noise ratio (PSNR), mean squared error (MSE) and normalized cross correlation (NCC) and improved results depict the superiority of the algorithm than existing techniques.

Author 1: Tian Lianfang

Author 2: Jameel Ahmed Bhutto

Author 3: Du Qiliang

Author 4: Bhawani Shankar

Author 5: Saifullah Adnan

Keywords: Image fusion; Heisenberg’s uncertainty principle; combined median and average filter; Haar wavelet; Stationary Wavelet Transform and Principal Component Analysis (SWT-PCA)

Paper 6: Study of Face Recognition Techniques: A Survey

Abstract: With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.

Author 1: Madan Lal

Author 2: Kamlesh Kumar

Author 3: Rafaqat Hussain Arain

Author 4: Abdullah Maitlo

Author 5: Sadaquat Ali Ruk

Author 6: Hidayatullah Shaikh

Keywords: Face recognition; illuminations; partial occlusion; pose invariance

Paper 7: MapReduce Programs Simplification using a Query Criteria API

Abstract: A Hadoop HDFS is an organized and distributed collection of files. It is created to store a huge part of data and then retrieve it and analyze it efficiently in a less amount of time. To retrieve and analyze data from the Hadoop HDFS, MapReduce Jobs must be created directly using some programming languages like Java or indirectly using some high level languages like HiveQL and PigLatin. Everyone knows that creating MapReduce programs using programming languages is a difficult task that requires a remarkable effort for their creation and also for their maintenance. Writing MapReduce code by hand needs a lot of time, introduce bugs, harm readability, and impede optimizations. Profiles working in the field of big data always try to avoid hard and long programs in their work. They are always looking for much simpler alternatives like graphical interfaces or reduced scripts like PIG Latin or even SQL queries. This article proposes to use a MapReduce Query API inspired from Hibernate Criteria to simplify the code of MapReduce programs. This API proposes a set of predefined methods for making restrictions, projections, logical conditions and so on. An implementation of the Word Count example using the Query Criteria API is illustrated in this paper.

Author 1: Boulchahoub Hassan

Author 2: Khalil Namir

Author 3: Amina Rachiq

Author 4: Labriji Elhoussin

Author 5: Benabbou Fouzia

Keywords: Hadoop; HDFS; MapReduce

Paper 8: Modelling of Thermal Storage in Damaged Composite Structures using Time Displaced Gradient Field Technique (TDGF)

Abstract: This paper presents a new approach to composite surface characterization using Gradient Field time displacement. The new technique employs calculation of thermally charged regions within a composite structure as a result of each area gradient and then correlates the regions (storage areas) using a time displaced (Lag) model. The resulting data show that a rate-dependent model is fit to describe the behavior of damaged areas within a composite structure, which act as energy storage elements. The rate of dissipation of stored energy per region contributes to the shape and area of the resulting correlated Lag curve.

Author 1: Mahmoud Zaki Iskandarani

Keywords: Gradient norm; edge detection; gray level mapping; segmentation; rate-dependent; lag; thermal images

Paper 9: Evaluating M-Learning in Saudi Arabia Universities using Concerns-Based Adoption Model Level of use Framework

Abstract: Numerous studies have evaluated aspects of m-learning use in Saudi Arabia, mostly focused on technology use and its impact on students, or technology challenges and promises. Few studies have explored features of m-learning use and engagement among university faculty members. This paper presents a new methodology for evaluating the status of m-learning from faculty members’ perspectives in Saudi Arabia by investigating level of use using Concerns-Based Adoption Model framework. Concerns-Based Adoption Model is well established in the United States of America and in research investigating innovation adoption in education, including recent efforts in the Middle East (Jordan and Saudi Arabia). The outcome of such research, including this study, promotes better use and engagement with m-learning and provides a better understanding of advantages, disadvantages and barriers. The outcomes of this research study can reflect positively on universities’ status in the future and help in reforming policies and practices for developing the use of m-learning in Saudi Arabia.

Author 1: Mohammed Al Masarweh

Keywords: Concern Based Adoption Model (CBAM); evaluation; M-learning; Saudi Universities; level of use; mobile phone

Paper 10: Automatic Arabic Image Captioning using RNN-LSTM-Based Language Model and CNN

Abstract: The automatic generation of correct syntaxial and semantical image captions is an essential problem in Artificial Intelligence. The existence of large image caption copra such as Flickr and MS COCO have contributed to the advance of image captioning in English. However, it is still behind for Arabic given the scarcity of image caption corpus for the Arabic language. In this work, an Arabic version that is a part of the Flickr and MS COCO caption dataset is built. Moreover, a generative merge model for Arabic image captioning based on a deep RNN-LSTM and CNN model is developed. The results of the experiments are promising and suggest that the merge model can achieve excellent results for Arabic image captioning if a larger corpus is used.

Author 1: Huda A. Al-muzaini

Author 2: Tasniem N. Al-yahya

Author 3: Hafida Benhidour

Keywords: AI; image caption; natural language processing; neural network; deep learning convolutional neural network; recurrent neural network; long short-term memory

Paper 11: Use of Technology and Financial Literacy on SMEs Practices and Performance in Developing Economies

Abstract: Micro, Small and Medium Enterprises (SMEs) practices in developing economies experience a unique set of challenges to attain their success. With a view of analyzing double impact of SME financial literacy and use of technology on practice of record keeping and risk management as echoed on firm performance, the partial least square structural equation modelling was used to configure the perceived impact of these variables. The results posit a significant relationship between the firm use of technology to its practice of record keeping and performance, a significant positive association of financial literacy and firm risk management practices. Nevertheless the study found insignificant association of financial literacy and firm book keeping practice; it offers unleashed dual practical role of financial literacy and use of technology for improving SMEs financial practices in developing economies.

Author 1: Juma Buhimila Mabula

Author 2: Han Dong Ping

Keywords: Technology use; financial literacy; book keeping; risk management; developing economies

Paper 12: Experimental Study of Spatial Cognition Capability Enhancement with Building Block Learning Contents for Disabled Children

Abstract: In this research, we develop learning teaching materials using building blocks for children with disabilities, and verify learning effect. It is important to prepare input equipment according to children with disabilities and to prepare learning materials according to the ability you have learned. Therefore, this time we developed a teaching material using building blocks to improve spatial recognition capability using touch pad and tablet as input device. It is decided to measure the effect by comparing the scores learned by actually combining the input device and the learning material. Through experiments with participants of disabled children, it is found that the learning contents are effective and appropriate for improvement of their spatial recognition capability.

Author 1: Kohei Arai

Author 2: Taiki Ishigaki

Author 3: Mariko Oda

Keywords: Experiment; slope surfaces; interaction between two surfaces

Paper 13: Improved Langley and Ratio Langley Methods for Improving Sky-Radiometer Accuracy

Abstract: Improved Langley Method (ILM) is proposed to improve the calibration accuracy of the sky-radiometer. The ILM uses that the calibration coefficients of other arbitrary wavelengths can be presumed from the calibration coefficients in a certain reference wave length, and improves the calibration accuracy of a full wave length region by Ratio Langley Method (RLM) in long wavelength paying attention to calibration accuracy being good comparatively was proposed. Specifically, the calibration coefficient of other wavelengths was presumed by the RLM from the calibration factor by ILM in 0.87 micrometer. The numerical simulation based on measured data of solar direct and aureole when the calibration error of the proposed method was evaluated about the case where ±3% and ±5% of measurement error is superimposed on the measurement data solar direct and aureole, the maximum with error was 0.0014 and 0.0428, and they of ILM were 0.011 and 0.0489. Therefore, the proposed calibration method is robust for a measurement error compared with ILM, and was understood that highly precise calibration is possible over full wavelength. When the standard deviation of a calibration coefficients estimated the accuracy of the proposed calibration method based on the measured data of the sky-radiometer for 15 days which fits calibration among the measured data for four years or more, it was 0.02016, and since it was smaller than the standard deviation 0.03858 of the calibration coefficients by ILM, the predominance of the proposed calibration method has been confirmed.

Author 1: Kohei Arai

Keywords: Calibration; Langley plot; improved Langley method; ratio Langley method; aerosol optical depth; volume spectrum

Paper 14: Wireless Sensor Network and Internet of Things in Precision Agriculture

Abstract: Internet of Things is one of the most popular subjects nowadays where sensors and smart devices facilitate the provision of information and communication. In IoT, one of the main concepts is wireless sensor networks in which data is collected from all the sensors in a network characterized by low power consumption and a wide range of communication. In this study, an architecture to monitor soil moisture, temperature and humidity on small farms is provided. The main motivation for this study is to decrease water consumption whilst increasing productivity on small agricultural farms and precisions on them. This motivation is further propelled by the fact that agriculture is the backbone of some towns and most villages in most of the countries. Furthermore, some countries depend on farming as the main source of income. Putting the above-mentioned factors into consideration, the farm is divided into regions; the proposed system monitors soil moisture, humidity and temperature in the respective regions using wireless sensor networks, internet of things and sends a report to the end user. The report contains, as part of the information, a 10-day weather forecast. We believe that with the above information, the end user (farmer) can more efficiently schedule farm cultivation, harvesting, irrigation, and fertilization.

Author 1: Farzad Kiani

Author 2: Amir Seyyedabbasi

Keywords: Wireless sensor network; internet of things; smart agriculture applications; precision agriculture

Paper 15: Rule Based Artificial Intelligent System of Cucumber Greenhouse Environment Control with IoT Technology

Abstract: The method proposed here allows control cucumber greenhouse environment based on IoT technology. IoT sensors are to measure the room and air temperature, relative humidity, CO2 content, water supply, liquid fertilizer, water content. The basic system is rule based system. All the required rules to control the cucumber greenhouse environment are proposed here. Through regressive analysis between IoT sensor data and the harvest cucumber quality, it is found that the proposed rule based system is appropriate to control the cucumber greenhouse environment.

Author 1: Kohei Arai

Author 2: Yoshikazu Saitoh

Keywords: Temperature; relative humidity; CO2 content; water supply; liquid fertilizer; rule-based system; IoT; artificial intelligence; expert system

Paper 16: Pedestrian Detection Approach for Driver Assisted System using Haar based Cascade Classifiers

Abstract: Object detection and tracking with the aid of computer vision is a most challenging task in the context of Driver Assistant System (DAS) for vehicles. This paper presents pedestrians detection techique using Haar-Like Features. The main aim of this research is to develop a detection system for vehicle drivers that will intimate them in advance for pedestrian’s movement when they are crossing the zebra region or passing nearby to it along the road. For this purpose, dataset of 1000 images have been taken via CCTV camera which was mounted for road monitoring. A Haar based cascade classifiers have been implemented over images. And system is trained for positive (with people) and negative (without people) image samples, respectively. After testing, the obtained results show that it attained 90% accuracy while pedestrian detection. The proposed work provides significant contribution in order to reduce the road accidents as well as ensure the safety measurement for road management.

Author 1: M. Ameen Chhajro

Author 2: Kamlesh Kumar

Author 3: M. Malook Rind

Author 4: Aftab Ahmed Shaikh

Author 5: Haque Nawaz

Author 6: Rafaqat Hussain Arain

Keywords: Pedestrian; Haar based classifier; positive and negative samples; computer vision; object detection

Paper 17: MapReduce Performance in MongoDB Sharded Collections

Abstract: In the modern era of computing and countless of online services that gather and serve huge data around the world, processing and analyzing Big Data has rapidly developed into an area of its own. In this paper, we focus on the MapReduce programming model and associated implementation for processing and analyzing large datasets in a NoSQL database such as MongoDB. Furthermore, we analyze the performance of MapReduce in sharded collections with huge dataset and we measure how the execution time scales when the number of shards increases. As a result, we try to explain when MapReduce is an appropriate processing technique in MongoDB and also to give some measures and alternatives to take when MapReduce is used.

Author 1: Jaumin Ajdari

Author 2: Brilant Kasami

Keywords: NoSQL; big data; MapReduce; sharding; MongoDB

Paper 18: Demand Response Programs Significance, Challenges and Worldwide Scope in Maintaining Power System Stability

Abstract: In order to cope up the continuously increasing electric demand, Governments are forced to invest on Renewable Energy (RE) sources due to scarcity of fossil fuels (such as coal, gas and oil), high costs associated with it and emission of greenhouse gases. However, stochastic nature of RE sources like wind and PV threaten the reliability and stability of power system. Demand Response (DR) is an alternative solution to address the issues of economic constraints, integration challenges of RE, and dependency on fossil fuels. It is an aspect of Demand Side Management (DSM) that converts consumer’s passive role to active by changing energy consumption pattern to reduce peak load. DR plays the role in deferring the investment on building new power plants, eliminating transmission losses and making the society green. This work analyzes initialization of different DR programs due to slumping technology costs and recognition of users’ behavior in electricity market. Moreover, this paper points out the problems associated with DR and its project implementation across USA, China and developed cities of Europe.

Author 1: Muhammad Faizan Tahir

Author 2: Chen Haoyong

Author 3: Idris Ibn Idris

Author 4: Nauman Ali Larik

Author 5: Saif ullah Adnan

Keywords: Demand side management (DSM); demand response (DR); renewable energy (RE); DR programs; wind; PV

Paper 19: Intelligent System for the use of the Scientific Research Information System

Abstract: As part of the digital governance of scientific research of Moroccan universities and national research institutions, the Ministry of Higher Education, Scientific Research and Executive Training has shown great interest in setting up the Moroccan Information System for Scientific Research (SIMARECH). Despite a great effort that was made for the implementation of SIMARECH in Moroccan universities, difficulties appear in the use of this information system. This prompted Abdelmalek Essaadi University to consider developing an intelligent system to provide remote training for users to use SIMARECH to facilitate the learning process, reduce administrative costs for displacement to national universities and save time training, etc. This article is in the context of a new rapidly expanding learning paradigm in the field of artificial intelligence for education. It encompasses the design and development of a SIMARECH Intelligent Learning System of Global Use and Features to provide customized learning and adapt to different environments as well as the types of learning scenarios for user training of SIMARECH, this system is named ISSIMA (intelligent system for the use of SIMARECH).

Author 1: Khaoula Benmoussa

Author 2: Majida Laaziri

Author 3: Samira Khoulji

Author 4: Mohamed Larbi Kerkeb

Keywords: Moroccan Information System for Scientific Research (SIMARECH); intelligent system; E-learning systems; learning process; interactive learning environments; intelligent tutoring systems

Paper 20: Generating Relational Database using Ontology Review

Abstract: A huge amount of data is being generated every day from different sources. Access to these data can be very valuable for decision-making. Nevertheless, the extraction of information of interest remains a major challenge given a large number of heterogeneous databases. Building shareable and (re)usable data access mechanisms including automated verification and inference mechanisms for knowledge discovery needs to use a common knowledge model with a secure, coherent, and efficient database. For this purpose, an ontology provides an interesting knowledge model and a relational database provides an interesting storage solution. Many papers propose methods for converting ontology to a relational database. This paper describes issues, challenges, and trends derived from the evaluation of 10 methods using 23 criteria. Following this study, this paper shows that none of the methods are complete as well as the conversion process does not use the full expressivity of ontology to derive a complete relational schema including advanced constraints and modification procedures. Thus, more work must be done to decrease the gap between ontologies, a relation database.

Author 1: Christina Khnaisser

Author 2: Luc Lavoie

Author 3: Anita Burgun

Author 4: Jean-Francois Ethier

Keywords: Ontology; relational database; database modeling; knowledge model; ontology to relational database

Paper 21: State Transition Testing Approach for Ad hoc Networks using Ant Colony Optimization

Abstract: Nowadays, telecommunication software organizations are challenged to provide high-quality software to customers within their estimated time and budget in order to stay competitive within the market. Because quality is a defining aspect of the product, it is essential for a project manager to stay alert throughout the project lifecycle. Quality has a direct bearing on customer satisfaction, and if a company produces high-quality products, satisfied customers will rank it highly in customer satisfaction surveys. Additionally, dissatisfied customers are more vocal in their criticisms. Therefore, testing is an important step to produce more reliable systems. In this paper we address two important aspects of software testing for ad hoc network protocols. The first one is by integrating a high-level testing approach based on state transition on top of a network simulator in order to fill a perceived gap in existing network simulators. The second one is reducing testing effort by eliminating redundant test cases, in order to effectively improve the result accuracy of existing network simulators. In this paper, we implemented an automated state transition testing approach for wireless network routing protocols, using an improved Ant Colony Optimization (ACO) algorithm. The expected result is to provide maximum coverage in terms of states and transitions.

Author 1: Ahmed Redha Mahlous

Author 2: Anis Zarrad

Author 3: Taghreed Alotaibi

Keywords: Component; ant colony; simulation; optimization; state transition; ad hoc routing protocol

Paper 22: Verifiable Search Over Updatable Encrypted Data in Cloud Computing

Abstract: With all the benefits from cloud computing, there are negative influences for the data trust and integrity since clients lose control over the outsourced data in clouds. We propose a verification scheme that supports keywords based search among the encrypted data which is updatable. During the verification process the outsourced cloud data are protected from being inferred by the cloud server. Additionally, if the cloud server returns wrong or incomplete search results the clients will be able to detect such failures. A novel concept in our scheme is the ability of clients to update their outsourced data and to ensure the data’s correctness. With our scheme, the data’s update efficiency is high and the client’s computational cost is low, which makes our scheme very suitable for resource constrained devices.

Author 1: Selasi Kwame Ocansey

Author 2: Changda Wang

Author 3: Wolali Ametepe

Author 4: Qinbao Xu

Author 5: Yu Zeng

Keywords: Cloud computing; verification; outsourced data; update; correctness; search results

Paper 23: An Effective Virtual Reality based Remedy for Acrophobia

Abstract: Virtual reality (VR) Exposure Therapy with sophisticated technology has been used in the Psychological treatment. The goal is to design a virtual environment using HCI (HMD) device with an interactive and immersive realistic 3D graphic scenes for exposure therapy of acrophobia that allows patient to sense height and gets used to the fearful feelings .The degree of fear is then used to evaluate the effectiveness of the system before and after therapy with the help of comparison. One may feel a little uneasy and perhaps accelerated heart rate, excessive sweating and shortness of breath, etc. are some of the most common physical symptoms of anxiety upon exposure to height. This extreme or irrational fear of height is called “Acrophobia”. The HMI based simulation is used which used the body sensation elucidation as physical symptoms of anxiety upon exposure to height to predict the results. The test reveals that anxiety level decreases from 16% at first level exposure and 8% at last level exposure. It is concluded from the results that VR exposure therapy is more effective than real exposure therapy and also the post test for VR exposure therapy were significantly better than post real exposure results. This system provides cost effective solution for rehabilitation environment.

Author 1: Maria Abdullah

Author 2: Zubair Ahmed Shaikh

Keywords: HMI; virtual reality (VR); HMD; acrophobia; VR exposure therapy; cognitive behavioral therapy; 3D VR environment

Paper 24: Design of Miniaturized Multiband Microstrip Patch Antenna using Defected Ground Structure

Abstract: The recent developments in communication and antenna engineering demands compact and multiband antennas. Microstrip antenna is one of the most useful antennas for wireless communication because of its inherent features like low profile, light weight and easy fabrication. This design is aimed at miniaturized Microstrip Patch Antenna (MSA), without deteriorating its other parameters, such as gain, bandwidth, directivity and return loss. A significant amount of 89% miniaturization has been made possible by careful and meticulous investigation of slots insertion in patch and ground of MSA antenna. Dielectric substrate used in this design is polyester which has shown better result. As the focus of this design is to miniaturize the MSA, the technique used here is Defected Ground Structure (DGS), along with Defected Patch Structure (DPS) which actually shifted the resonant frequencies to the lower range without increasing its physical dimensions. Besides this shorting pin is also introduced between patch and ground, which also contributed in the enhancement of parameters like gain and return loss. The position of pin played an important role in the acquirement of better performance and radiation at desirable frequency band. Different shapes have been designed on Ground and Patch to obtain enhanced results. With the use of DGS, the designed antenna started radiation at multiple frequency bands. The frequency bands generated by this designed antenna are in the range of L band and S band of IEEE standard which made it apposite to use in variety of applications.

Author 1: Mudasar Rashid

Author 2: Mehre E Munir

Author 3: Khalid Mahmood

Author 4: Jehanzeb Khan

Keywords: Miniaturization; multiband; defected ground structure (DGS); defected patch structure (DPS); directivity; gain

Paper 25: Movement Direction Estimation on Video using Optical Flow Analysis on Multiple Frames

Abstract: This study proposed a model for determining the movement direction of the object based on the optical flow features. To increase the speed of computational time, optical flow features derived into a Histograms of Oriented Optical Flow (HOOF). We extracted them locally on the grid with a certain size. Moreover, to determine the movement direction we also analyzed multiple frames at once. Based on the experiment results, showing that the value of accuracy, precision, and recall of the movement detection is good, amounting to 93% for accuracy, 73.07% for precision and 84.25% for recall. Furthermore, the results of testing using the best parameter shows the value of accuracy of 98.1%, 35.6% precision, 41.2% recall, and direction detection error rate (DDER) 25,28%. The results of this study are expected to provide benefits in video analysis studies such as the riots detection and abnormal movement in public places.

Author 1: Achmad Solichin

Author 2: Agus Harjoko

Author 3: Agfianto Eko Putra

Keywords: Video analysis; movement direction; optical flow; Histograms of Oriented Optical Flow (HOOF); multiple frames

Paper 26: Secure user Authentication and File Transfer in Wireless Sensor Network using Improved AES Algorithm

Abstract: The WSN technology is a highly efficient and effective way of gathering highly sensitive information and is often deployed in mission-critical applications, which makes the security of its data transmission of vital significance. However, the previous research paper failed to distinguish the role of centralized server for it being the main controller of the entire network. The decision of nodes communicating with each other in the previous research paper was based on the information received from the adjacent node. However, the proposed research paper will take into account the centralized server to develop a new technique to prevent the black node from joining the wireless sensor network. Key distribution technique along with the implementation of improved AES algorithm double key encryption will play an important role in transferring the data between authorized nodes securely and preventing unauthorized user from accessing it.

Author 1: Ishu Gupta

Author 2: S.N Panda

Author 3: Harsh SadaWarti

Author 4: Jatin Gupta

Keywords: Wireless sensor networks (WSN); centralized server; black node; encryption; security; key distribution technique

Paper 27: Design of Android-Based Remote Patient Monitoring System

Abstract: Efficient real-time monitoring systems for Patients with critical health condition have been always helpful for making timely decisions to save the lives. In such systems, the useful monitored factors include SPO2 (Oxygen Saturation in Blood), heart rate as well as temperature. Further, there are hundreds of patients in ICUs under monitoring systems in different hospitals and in different regions under fewer doctors/consultants on the move. Under above facts, a prototype for continuous monitoring of patient’s health statistics such as SPO2 and temperature along with a bed-side desk using a PC/Laptop (bio instrumentation) working as Server Database with an application layer top transfer data on Android Application Server is successfully developed. This Android application accessing real-time monitored factors using Server Database allows the consultant to monitor patient’s vitals data using his smart phone on move being at any hospital or city that creates easiness to handle any emergency and reduces Patient risks.

Author 1: Salman ul Mouzam Abbasi

Author 2: Muhammad Daud

Author 3: Salman Ali

Author 4: Abdul Qadir Ansari

Keywords: Monitoring system; SPO2; temperature; android application; bio instrumentation

Paper 28: Urdu Word Segmentation using Machine Learning Approaches

Abstract: Word Segmentation is considered a basic NLP task and in diverse NLP areas, it plays a significant role. The main areas which can be benefited from Word segmentation are IR, POS, NER, sentiment analysis, etc. Urdu Word Segmentation is a challenging task. There can be a number of reasons but Space Insertion Problem and Space Omission Problems are the major ones. Compared to Urdu, the tools and resources developed for word segmentation of English and English like other western languages have record-setting performance. Some languages provide a clear indication for words just like English which having space or capitalization of the first character in a word. But there are many languages which do not have proper delimitation in between words e.g. Thai, Lao, Urdu, etc. The objective of this research work is to present a machine learning based approach for Urdu word segmentation. We adopted the use of conditional random fields (CRF) to achieve the subject task. Some other challenges faced in Urdu text are compound words and reduplicated words. In this paper, we tried to overcome such challenges in Urdu text by machine learning methodology.

Author 1: Sadiq Nawaz Khan

Author 2: Khairullah Khan

Author 3: Wahab Khan

Author 4: Asfandyar Khan

Author 5: Fazali Subhan

Author 6: Aman Ullah Khan

Author 7: Burhan Ullah

Keywords: Part-of-speech (POS); NER; word segmentation; information retrieval; Natural Language Processing (NLP); conditional random fields (CRF)

Paper 29: A Systematic Review of Cyber Security and Classification of Attacks in Networks

Abstract: Cyber security plays an important role to secure the people who use internet via different electronic devices in their daily life. Some causes occurred all over world that people face problems when they connect their devices and system via internet. There are some highly sensitive data like biotechnology and military assets which are highly threatened by the hackers; cyber security plays a vital role in securing such data. Misusing the internet becomes a current issue in different sectors of life especially in social media, universities and government organizations. Internet is very useful for students in study institutes and employees who work in different organizations. Internet source gives the facility to people to fetch some information via internet. However, they must be protected when use the internet and secure for any unauthorized access. In this paper we have covered the different aspect of cyber security and Network security in the modern era. We have also tried to cover the threats in Intranet of organizations.

Author 1: Muhammad Kashif

Author 2: Sheraz Arshad Malik

Author 3: Muhammad Tahir Abdullah

Author 4: Muhammad Umair

Author 5: Prince Waqas Khan

Keywords: Cyber security; internet; intranet; network security; cybercrime and security alludes

Paper 30: Data Mining: Web Data Mining Techniques, Tools and Algorithms: An Overview

Abstract: Web data mining became an easy and important platform for retrieval of useful information. Users prefer World Wide Web more to upload and download data. As increasing growth of data over the internet, it is getting difficult and time consuming for discovering informative knowledge and patterns. Digging knowledgeable and user queried information from unstructured and inconsistent data over the web is not an easy task to perform. Different mining techniques are used to fetch relevant information from web (hyperlinks, contents, web usage logs). Web data mining is a sub discipline of data mining which mainly deals with web. Web data mining is divided into three different types: web structure, web content and web usage mining. All these types use different techniques, tools, approaches, algorithms for discover information from huge bulks of data over the web.

Author 1: Muhammd Jawad Hamid Mughal

Keywords: Web data mining; hyperlinks; usage logs; contents; patterns

Paper 31: Power Management of a Stand-Alone Hybrid (Wind/Solar/Battery) Energy System: An Experimental Investigation

Abstract: In this manuscript, a hybrid wind/solar/battery energy system is proposed for a stand-alone applications. Wind-solar energy sources are used as power generation source in the proposed hybrid energy system (HES), whereas battery is used as energy storing system in order to manage the power flow among various power generation sources and energy storing system. Power management control strategy is also presented for a suggested hybrid system. Through the real load demand and practical weather data (proposed area is Jamshoro, Sindh Pakistan), the system performance is verified under different situations. It is observed that the hybrid system produces maximum power in summer season as compared to other seasons throughout the year. Moreover, the power generated from wind and solar energy contributes 77.88% and 22.12%, respectively. However, it is clearly observed that the HES is cost effective and can be used in remotely rural areas which are isolated from power grid. In future work, the HES can be integrated with the power grid in order to meet the load demand during shortage of power.

Author 1: Saindad Mahesar

Author 2: Mazhar H. Baloch

Author 3: Ghulam S. Kaloi

Author 4: Mahesh Kumar

Author 5: Aamir M. Soomro

Author 6: Asif A. Solangi

Author 7: Yasir A. Memon

Keywords: Hybrid; stand-alone; wind; solar; battery; power management; Pakistan

Paper 32: Text Separation from Graphics by Analyzing Stroke Width Variety in Persian City Maps

Abstract: Text segmentation is a live research field with vast new areas to be explored. Separating text layer from graphics is a fundamental step to exploit text and graphics information. The language used in the map is a challenging issue in text layer separation problem. All current methods are proposed for non-Persian language maps. In Persian, text strings are composed of one or more subwords. Each subword is also composed of one to several letters connected together. Therefore, the components of the text strings in Persian are more diverse in terms of size and geometric form than in English. Thus, the overlapping of the Persian text and the lines usually produces a complex structure that the existing methods cannot handle with the necessary efficiency. For this purpose, the stroke width variety of the input map is calculated, and then the average line width of graphics is estimated by analyzing the content of stroke width. After finding the average width of graphical lines, we classify the complex structure into text and graphics in pixel level. We evaluate our method on some variety of full crossing text and graphics in Persian maps and show that some promising results in terms of precision and recall (above 80% and 90%, respectively) are obtained.

Author 1: Ali Ghafari-Beranghar

Author 2: Ehsanollah Kabir

Author 3: Kaveh Kangarloo

Keywords: Document image analysis; text/graphics separation; stroke width; raster map; Farsi; Persian; text segmentation; text label

Paper 33: Impact of Anaphora Resolution on Opinion Target Identification

Abstract: Opinion mining is an interesting area of research because of its wide applications in the decision-making process. Opinion mining aims to extract user’s perception from the text and to create a fast and accurate summary of people’s opinion about anything. In this study, we have worked on opinion target identification and the impact of anaphora resolution on opinion target extraction. Anaphora resolution can be utilized to detect opinion target in sentences having prepositions instead of nouns. We empirically evaluated the impact of anaphora resolution using benchmark datasets. We have achieved accuracy such as precision: 88.14 recall: 71.45 and f-score: 72.12, respectively.

Author 1: BiBi Saqia

Author 2: Khairullah Khan

Author 3: Aurangzeb Khan

Author 4: Wahab Khan

Author 5: Fazali Subhan

Author 6: Muhammad Abid

Keywords: Opinion mining; machine learning; evaluative expression; anaphora resolution; opinion targets

Paper 34: A Novel Multiple Session Payment System

Abstract: A wireless smartphone can be designed to process a financial payment efficiently. A user can just swipe his/her credit/debit card over the counter and all the processing needed shall be done seamlessly. A smartphone is a popular device to carry around. It is a hassle to carry and keep track on so many physical debit/credit cards in a wallet. An electronic debit/credit card on a smartphone is a more convenient alternative. This research project will embark on an electronic debit/credit card on a smartphone and migrate to an IoT money. A novel session payment system using IoT money has been introduced to minimise debit/credit card risk. The scope of this paper is confined to the security model for an easy payment system based on Internet of Things (IoT). Previously, each IoT money is unique and used once only on one-time payment. The session payment system will ease the burden on protecting the database of the payment system. This paper will extend the use of one-time payment to a multiple session payment system using an IoT money note.

Author 1: Mohanad Faeq Ali

Author 2: Nur Azman Abu

Author 3: Norharyati Harum

Keywords: Easy payment system; internet of things; secure payment system

Paper 35: Real-Time Concept Feedback in Lectures for Botho University Students

Abstract: This is a mixed methodology study which focused on developing a real-time concept feedback system for Botho University students. The study takes advantage of the tablets distributed freely by the institution to ameliorate the problem of lack of understanding of module concepts during lecture lessons. The system addresses issues of providing real-time feedback as the lecture is ongoing without disturbing other students, thus upholding effective class participation and interaction without the need of voicing own concerns loud to the lecturer, and in turn the lecturer is able to view the students’ interactions and address them. The real-time concept feedback system was used to test student comprehension of concepts, improve participation, engagement and attendance. The study identified many factors affecting students’ participation and interaction in a traditional class which inhibits understanding of concepts; hence, the development of the application to address such. It concluded that real-time concept feedback systems are vital in addressing students understanding in lecture sessions, thus upholding the importance of ICTs in education.

Author 1: Alpheus Wanano Mogwe

Keywords: Real-time feedback systems; interactive technology; e-learning; information technology; understanding of concepts

Paper 36: Swarm Optimization based Radio Resource Allocation for Dense Devices D2D Communication

Abstract: In Device to Device (D2D) communication two or more devices communicate directly with each other in the in-band cellular network. It enhances the spectral efficiency due to cellular radio resources (RR) are shared among the cellular users and D2D users. If the RR sharing is not legitimate properly, it causes interference and inefficient use. Therefore, management of RR between cellular users and D2D users is required to control the interference and inefficient use of RR. In D2D enabled cellular network, D2D users have a good signal to noise ratio (SNR) compared with cellular users due to the short distances and dedicated path. Using this advantage, an efficient RR allocation algorithm based on swarm optimization is proposed in this paper, that allows utmost spatial reuse in multi-users and OFDMA networks. The algorithm determines the required RR on the request of D2D users following the indicator variable. It enhances the capacity (Bit/Hz), overall system throughput and spectral efficiency with respect to sub-carriers in OFDMA networks. The performance of the proposed algorithm is evaluated via MATLAB simulations.

Author 1: O. Hayat

Author 2: R. Ngah

Author 3: Siti Z. Mohd Hashim

Keywords: Device to device (D2D) communication; radio resources (RR) allocation; OFDMA networks; sub-channels and sub-carriers; cellular users and D2D users

Paper 37: An Efficient Link Prediction Technique in Social Networks based on Node Neighborhoods

Abstract: The unparalleled accomplishment of social networking sites, such as Facebook, LinkedIn and Twitter has modernized and transformed the way people communicate to each other. Nowadays, a huge amount of information is being shared by online users through these social networking sites. Various online friendship sites such as Facebook and Orkut, allow online friends to share their thoughts or opinions, comment on others’ timeline or photos, and most importantly, meet new online friends who were known to them before. However, the question remains as to how to quickly propagate one’s online network by including more and more new friends. For this, one of the easy methods used is list of ‘Suggested Friends’ provided by these online social networking sites. For suggestion of friends, prediction of links for each online user is needed to be made based on studying the structural properties of the network. Link prediction is one of the key research directions in social network analysis which has attracted much attention in recent years. This paper discusses about a novel efficient link prediction technique LinkGyp and many other commonly used existing prediction techniques for suggestion of friends to online users of a social network and also carries out experimental evaluations to make a comparative analysis among each technique. Our results on three real social network datasets show that the novel LinkGyp link prediction technique yields more accurate results than several existing link prediction techniques.

Author 1: Gypsy Nandi

Author 2: Anjan Das

Keywords: Link prediction; online social networks; common neighbors; Jaccard’s coefficient; Adamic/Adar; preferential attachment; FriendLink

Paper 38: Heterogeneous Buffer Size Impact on UDP Performance for Real-Time Video Streaming Application

Abstract: Communication specifically in real-time (RTC) is a terminology which insinuates any live media transmission that occurs inside time limits. In this paper, heterogeneous buffer sizes in random are utilized on different routers and for different ranges to examine their effect on the performance of network for user datagram protocol’s (UDP) video streaming application. It appeared through numerical results that packet switches heterogeneous buffer sizes as a rule influence the general performance of the network. By thinking about bigger range of buffer sizes, throughput improves but End-to-End delay also increases which is customarily not commendable for RTC applications. On the contrary, throughput decreases on account of considering low range of buffer sizes; however, End-to-End delay additionally diminishes. In this manner, the middle of the road scope of buffer sizes range from 30 to 20, recommended for ideal throughput and an adequate lower End-to-End delay.

Author 1: Sarfraz Ahmed Soomro

Author 2: M. Mujtaba Shaikh

Author 3: Nasreen Nizamani

Author 4: Ehsan Ali Buriro

Author 5: Khalil M. Zuhaib

Keywords: Real-time communication; buffer size; user datagram protocol; video streaming

Paper 39: FPGA based Synthesize of PSO Algorithm and its Area-Performance Analysis

Abstract: Digital filters are the most significant part of signal processing that are used in enormous applications such as speech recognition, acoustic, adaptive equalization, and noise and interference reduction. It would be of great benefit to implement adaptive FIR filter because of self-optimization property, linearity and frequency stability. Designing FIR filter involves multi-modal optimization problems whereas conservative gradient optimization technique is not useful to design the filter. Hence, Particle Swarm Optimization (PSO) algorithm is more flexible and optimization technique based on population of particles in search space and alternative approach for linear phase FIR filter design. PSO improves the solution characteristic by giving a novel method for updating swarm’s position and velocity vector. Set of optimized filter coefficients will be generated by PSO algorithm. In this paper, PSO based FIR Low pass filter is efficiently designed in MATLAB and further Xilinx System Generator tool is used to efficiently design, synthesize and implement FIR filter in FPGA using SPARTEN 3E kit. For an example specifications, output of PSO algorithm is obtained that is set of optimized coefficients whose response is approximating to the ideal response. Hence, functional verification of the proposed algorithm has been performed and the error between obtained filter and ideal filter is minimized successfully. This work demonstrates the effectiveness of the PSO algorithms in parallel processing environment as compared to the Remez Exchange algorithm.

Author 1: Bharat Lal Harijan

Author 2: Farrukh Shaikh

Author 3: Burhan Aslam Arain

Author 4: Tayab Din Memon

Author 5: Imtiaz Hussain Kalwar

Keywords: Particle swarm optimization (PSO); Remez Exchange Algorithm; FPGA implementation; FIR filter

Paper 40: A Comparative Evaluation of Dotted Raster-Stereography and Feature-Based Techniques for Automated Face Recognition

Abstract: Automated face recognition systems are fast becoming a need for security-related applications. Development of a fool-proof and efficient face recognition system is a challenging domain for researchers. This paper presents comparative evaluation of two candidate techniques for automated face recognition application, viz. dotted Raster-stereography and feature-based system. The relevant performance parameters — accuracy, precision, sensitivity and specificity – measured for the two techniques using IPRL Database of images are reported. The results suggest that dotted Raster-stereography based face recognition system has better accuracy, precision, sensitivity and specificity, and hence is a preferred choice as compared with feature-based system for such sensitive applications where high face recognition accuracy is required. On the other hand, feature-based technique is faster in terms of the training and testing times required. Hence such applications where volume of face recognition work is large and high speed is required with some compromise in accuracy being acceptable then feature-based technique may also be the technique of choice.

Author 1: Muhammad Wasim

Author 2: S. Talha Ahsan

Author 3: Lubaid Ahmed

Author 4: Syed Faisal Ali

Author 5: Fauzan Saeed

Keywords: Raster-stereography; dotted raster-stereography; feature based; face recognition; IPRL

Paper 41: Empirical Evaluation of Modified Agile Models

Abstract: Empirical evaluation is one of the widely accepted validation method in the domain of software engineering which investigates the proposed technique via practical experience and reflects its benefits and limitations. Due to various advantages, agile models have been taking over the conventional software development methodologies since last two decades. However besides the benefits, various limitations have been noticed as well by the researchers and software industry in agile family. To achieve the maximum benefits it is vital to fix the limitations by customizing the development structure of agile models. This paper deals with the empirical analysis of modified agile models called Simplified Extreme Programing (SXP) and Simplified Feature Driven Development (SFDD), which are the modified forms of Extreme Programing (XP) and Feature Driven Development (FDD). SXP was presented to eliminate the issues of conventional XP such as, lack of documentation, poor architectural structure and less focus on design. SFDD was proposed to take care of reported issues in FDD such as explicit dependency on experienced staff, little or no guidance for requirement gathering, rigid nature to accommodate requirement changes and heavy development structure. This study evaluates SXP and SFDD through implementing client oriented projects and discusses the results with empirical analysis.

Author 1: Shabib Aftab

Author 2: Zahid Nawaz

Author 3: Faiza Anwer

Author 4: Muhammad Salman Bashir

Author 5: Munir Ahmad

Author 6: Madiha Anwar

Keywords: Agile models; SXP; SFDD; Modified XP; modified FDD; empirical evaluation; comparative analysis

Paper 42: Information System Evaluation based on Multi-Criteria Decision Making: A Comparison of Two Sectors

Abstract: In this article, our purpose is to introduce the results of a new approach to assess the information system success. It is based on the DeLone and McLean model and was applied on two domains. The chosen domains are banking sector being the most customer of information technology and construction industry as the least computer-intensive sector. The work methodology used to evaluate the information system performance is a combined approach of the two most popular multi-criteria decision making techniques: AHP and TOPSIS. Based on the results of this technique applied on studied sectors, we can obtain a horizontal comparison at the sector level and optimize the choice of the best system.

Author 1: Ansar DAGHOURI

Author 2: Khalifa MANSOURI

Author 3: Mohammed QBADOU

Keywords: Information system success; multi criteria decision; AHP and TOPSIS methods; criteria

Paper 43: A Survey of Energy Aware Cloud’s Resource Allocation Techniques for Virtual Machine Consolidation

Abstract: As the demand for cloud computing environment is increasing, new techniques for making cloud computing more environment-friendly are being proposed with an aim to convert traditional cloud computing into green cloud computing. A standout amongst the most imperative complications in cloud computing is streamlining of energy utilization because its importance is increasing rapidly. There are numerous strategies and algorithms used to limit the energy utilization in the cloud. Methods incorporate DVFS, UP-VMC, Utility based MFF, HCT, AVVMC, ACO, and ESWCT. In this survey, a review of energy-aware techniques is presented for making virtual machines more energy efficient in a cloud computing. Working on each technique is briefly explained. A comparative analysis is also given for comparing multiple efficient techniques with respect to performance metrics.

Author 1: Asif Farooq

Author 2: Tahir Iqbal

Author 3: Muhammad Usman Ali

Author 4: Zunnurain Hussain

Keywords: Cloud computing; energy aware; green cloud computing

Paper 44: Ant Colony System for Dynamic Vehicle Routing Problem with Overtime

Abstract: Traditionally, in a VRP the vehicles return to depot before the end of the working time. However, in reality several constraints can occur and prevent the vehicles from being at the depot on time. In the dynamic case, we are supposed to answer the requests the same day of their arrival. Nevertheless, it is not always easy to find a solution, which ensures the service while respecting the normal working time. Therefore, allowing the vehicle to use additional time to complete their service may be very useful especially if we have a large demand with a limited number of vehicles. In this context, this article proposes a mathematical modeling with an Ant Colony System (ACS) based approach to solve the dynamic vehicle routing problem (DVRP) multi-tours with overtime. To test the algorithm, we propose new data sets inspired from literature benchmarks. The competitiveness of the algorithm is proved on the classical DVRP.

Author 1: Khaoula OUADDI

Author 2: Youssef BENADADA

Author 3: Fatima-Zahra MHADA

Keywords: Dynamic vehicle routing problem (DVRP); multi-tours; mathematical modeling; hybrid; Ant Colony System (ACS); overtime

Paper 45: Multi-Class Breast Cancer Classification using Deep Learning Convolutional Neural Network

Abstract: Breast cancer continues to be among the leading causes of death for women and much effort has been expended in the form of screening programs for prevention. Given the exponential growth in the number of mammograms collected by these programs, computer-assisted diagnosis has become a necessity. Computer-assisted detection techniques developed to date to improve diagnosis without multiple systematic readings have not resulted in a significant improvement in performance measures. In this context, the use of automatic image processing techniques resulting from deep learning represents a promising avenue for assisting in the diagnosis of breast cancer. In this paper, we present a deep learning approach based on a Convolutional Neural Network (CNN) model for multi-class breast cancer classification. The proposed approach aims to classify the breast tumors in non-just benign or malignant but we predict the subclass of the tumors like Fibroadenoma, Lobular carcinoma, etc. Experimental results on histopathological images using the BreakHis dataset show that the DenseNet CNN model achieved high processing performances with 95.4% of accuracy in the multi-class breast cancer classification task when compared with state-of-the-art models.

Author 1: Majid Nawaz

Author 2: Adel A. Sewissy

Author 3: Taysir Hassan A. Soliman

Keywords: Breast cancer classification; Convolutional Neural Network (CNN); deep learning; medical image processing; histopathological images

Paper 46: A Comparative Study of Engineering Students Pedagogical Progress

Abstract: Students’ pedagogical progress plays a pivotal role in any educational institute in order to pursue imperative education. Educational institutes, Universities, Colleges implement various performance measures in order to keep analyzing and tracking progress of students to cultivate benefits of education in a better way. There are several data mining techniques to apply on education in order to build constructive educational strategies and solutions. This study aims to analyze and track engineering under graduate student’s records to judge quality education, student motivation towards learning, and student pedagogical progress to maintain education at high quality level and predicting engineering student’s forthcoming progress. Different engineering discipline students’ (of three different cohorts) data have been analyzed for tracing current as well as future pedagogical progress based on their sessional (pre-examination) marks. In this research, the classification techniques by k-nearest neighbor, Naïve Bayes and decision trees are applied to evaluate different engineering technologies student’s performance and also there are different methodologies that can be used for data classification.

Author 1: Khalid Mahboob

Author 2: Syed Abbas Ali

Author 3: Danish Ur Rehman Khan

Author 4: Fayyaz Ali

Keywords: Pedagogical progress; classification; k-nearest neighbor; Naïve Bayes; decision trees; engineering students

Paper 47: Student’s Opinions on Online Educational Games for Learning Programming Introductory

Abstract: Use of educational games is an approach that has potential to change the existing educational method. This is due to games popularity among younger generation as well as engagement and fun features of games compared to conventional learning method. In addition, games are among the most widespread media amongst younger generation or so-called “digital natives” apart from movie, music and internet technology. Game play activities is an important issue to be thoroughly understood due to the facts that many of them are addicted to game play activity. In contrast, conventional learning approaches are not interesting enough to the younger generation. Thus, integration of games technology into education is potentially believed to increase student interest and motivation to learn. This study developed and evaluates an online educational game for learning Programming Introductory course at a university in Malaysia. A total of 180 undergraduate students from computer and engineering background participate in the study. Findings shows that about 80% of students have positive attitude towards the games with around 84% of them find that the games is a fun way to learn, at the same time, an average of 80% agreed that the game provide them with opportunity to learn. Furthermore, about 75% of the students agreed that the game make them able to do self-assessment for Programming course. It was interesting to find that almost 85% of the student said that they will want to use educational games as their future learning approach. Despite many more evidence will be needed especially in Malaysia context, this study is important to rationalize that games can be one of the new learning approaches in the future.

Author 1: Roslina Ibrahim

Author 2: Nor Zairah A. Rahim

Author 3: Doris Wong H. Ten

Author 4: Rasimah C.M Yusoff

Author 5: Nurazean Maarop

Author 6: Suraya Yaacob

Keywords: Educational games; programming introductory; undergraduate; games evaluation

Paper 48: Accident Detection and Smart Rescue System using Android Smartphone with Real-Time Location Tracking

Abstract: A large number of deaths are caused by Traffic accidents worldwide. The global crisis of road safety can be seen by observing the significant number of deaths and injuries that are caused by road traffic accidents. In many situations the family members or emergency services are not informed in time. This results in delayed emergency service response time, which can lead to an individual’s death or cause severe injury. The purpose of this work is to reduce the response time of emergency services in situations like traffic accidents or other emergencies such as fire, theft/robberies and medical emergencies. By utilizing onboard sensors of a smartphone to detect vehicular accidents and report it to the nearest emergency responder available and provide real time location tracking for responders and emergency victims, will drastically increase the chances of survival for emergency victims, and also help save emergency services time and resources.

Author 1: Arsalan Khan

Author 2: Farzana Bibi

Author 3: Muhammad Dilshad

Author 4: Salman Ahmed

Author 5: Zia Ullah

Author 6: Haider Ali

Keywords: Traffic accidents; accident detection; on-board sensor; accelerometer; android smartphones; real-time tracking; emergency services; emergency responder; emergency victim; SOSafe; SOSafe Go; firebase

Paper 49: Dist-Coop: Distributed Cooperative Transmission in UWSNs using Optimization Congestion Control and Opportunistic Routing

Abstract: One of the real issues in UWSN is congestion control. The need is to plan an optimized congestion control scheme which enhances the network life time and in addition limits the usage of energy in data transmission from source to destination. In this paper, we propose a routing protocol called Dist-Coop in UWSN. Dist-Coop is a distributed cooperation based routing scheme which uses mechanism for optimized congestion control in noisy links of underwater environment. It is compact, energy proficient and high throughput opportunistic routing scheme for UWSN. In this proposed protocol architecture, we present congestion control with cooperative transmission of data packets utilizing relay sensors. The final objective is to enhance the network life time and forward information utilizing cooperation procedure, limiting energy consumption amid transmission of information. At destination node, combining strategy utilized is based on Signal-to-Noise Ratio (SNRC). Simulation results of Dist-Coop scheme indicate better outcomes in terms of energy consumption, throughput and network lifetime in contrast with Co-UWSN and EH-UWSN routing protocols. Dist-Coop has expended substantially less energy and better throughput when contrasted with these protocols.

Author 1: Malik Taimur Ali

Author 2: Saqib Shahid Rahim

Author 3: Mian Ahmed Jan

Author 4: Atif Ishtiaq

Author 5: Sheeraz Ahmed

Author 6: Mukhtar Ahmad

Author 7: Mukhtaj Khan

Author 8: M. Ayub Khan

Keywords: Opportunistic routing; cooperation; congestion control; signal-to-noise ratio

Paper 50: Traffic Predicting Model for Dynamic Spectrum Sharing Over 5G Networks

Abstract: Recently, wireless networks and traffic requirements have been rapidly aggregated in diverse applications in 5G environments. For this reason, researchers have investigated the influences of this growth based on a user’s requirements inside these networks. However, the stream of traffic has been considered a crucial role for the user’s needs over 5G network. In this paper, gigantic data traffic is considered for enabling dynamic spectrum sharing over 5G networks. Thus, various accessing plans are covered to manage the overall network traffic. Additionally, it proposes a traffic predicting model for a technique of managing traffic when multiple requests are received to decrease delays. It has considered different significances related to a large size of traffic practices. Additionally, this work will guide us to enhance traffic solutions within massive requests over outsized networks. Systematically, it has focused on the traffic flow, starting from the accessing steps until passing on requests to suitable spectrum carriers.

Author 1: Ahmed Alshaflut

Author 2: Vijey Thayananthan

Keywords: Component; traffic predictions; software defined multiple access; dynamic spectrum sharing; 5G networks

Paper 51: Implication of Genetic Algorithm in Cryptography to Enhance Security

Abstract: In today’s age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for high level of security. Modern hash function based systems are better than traditional systems but the complex algorithms of generating invertible functions are very time consuming. In traditional systems data is being encrypted with the key but still there are possibilities of eavesdrop the key and altered text. Therefore, key must be strong and unpredictable, so a method has been proposed which take the advantage of theory of natural selection. Genetic Algorithms are used to solve many problems by modeling simplified genetic processes and are considered as a class of optimization algorithms. By using Genetic Algorithm the strength of the key is improved that ultimately make the whole algorithm good enough. In the proposed method, data is encrypted by a number of steps. First, a key is generated through random number generator and by applying genetic operations. Next, data is diffused by genetic operators and then logical operators are performed between the diffused data and the key to encrypt the data. Finally, a comparative study has been carried out between our proposed method and two other cryptographic algorithms. It has been observed that the proposed algorithm has better results in terms of the key strength but is less computational efficient than other two.

Author 1: Muhammad Irshad Nazeer

Author 2: Ghulam Ali Mallah

Author 3: Noor Ahmed Shaikh

Author 4: Rakhi Bhatra

Author 5: Raheel Ahmed Memon

Author 6: Muhammad Ismail Mangrio

Keywords: Secure transmission; symmetric cryptosystems; invertible functions; genetic algorithms; efficient encryption

Paper 52: Airline Sentiment Visualization, Consumer Loyalty Measurement and Prediction using Twitter Data

Abstract: Social media today is an integral part of people’s daily routines and the livelihood of some. As a result, it is abundant in user opinions. The analysis of brand specific opinions can inform companies on the level of satisfaction within consumers. This research focus is on analysis of tweets related to airlines based in four regions: Europe, India, Australia and America for consumer loyalty prediction. Sentiment Analysis is carried out using TextBlob analyzer. The tweets are used to calculate and graphically represent the positive, negative mean sentiment scores and a varying mean sentiment score over time for each airline. The terms with complaints and compliments are depicted using visualization methods. A novel method is proposed to measure consumer loyalty using the data gathered from Twitter. Furthermore, consumer loyalty prediction is performed using Twitter data. Three classifiers are employed, namely, Random Forest, Decision Tree and Logistic Regression. A maximum classification accuracy of 99.05% is observed for Random Forest on 10-fold cross validation.

Author 1: Rida Khan

Author 2: Siddhaling Urolagin

Keywords: Consumer loyalty measurement; consumer loyalty prediction; sentimental visualization; airline consumer analysis

Paper 53: A Proposal for a Technological Solution to Improve user Experience in a Shopping Center based on Indoor Geolocation Services

Abstract: For shopping centers, mobile devices and their associated technologies represent great business opportunities and a way to improve the user experience within their facilities. These types of constructions are usually quite large, multi-story, and with a significant number of shops, services, where the visitors may find themselves having difficulties to have a complete and up-to-date list of the stores, determine which stores and services are those that meet the characteristics or specifications they seek, know the location of the shops or how to reach them. This research studies and contemplates different technologies, tools, and approaches for the development of a technological solution for shopping centers that offers in its functionality a geolocation system in the interior spaces of the buildings. Our technological solution includes a mobile application for the Android operating system implemented by using the native development approach, and a web application for managing data, where the contents and settings of the mobile application will be obtained following the client/server model through a private API. It is worth to mention that the already mentioned system of geolocation in interiors is implemented using WiFi technology and the different Access Points installed in the shopping center, through which users can obtain their position, locate the stores or services of their interest, and receive indications on how to reach them.

Author 1: Luinel Andrade

Author 2: Johan Quintero

Author 3: Eric Gamess

Author 4: Antonio Russoniello

Keywords: Mobile application; web application; geolocation; shopping center; WiFi; access points

Paper 54: Open-Domain Neural Conversational Agents: The Step Towards Artificial General Intelligence

Abstract: Development of conversational agents started half century ago and since then it has transformed into a technology that is accessible in various aspects in everyday life. This paper presents a survey current state-of-the-art in the open domain neural conversational agent research and future research directions towards Artificial General Intelligence (AGI) creation. In order to create a conversational agent which is able to pass the Turing Test, numerous research efforts are focused on open-domain dialogue system. This paper will present latest research in domain of Neural Network reasoning and logical association, sentiment analysis and real-time learning approaches applied to open domain neural conversational agents. As an effort to provide future research directions, current cuttingedge approaches applied to open domain neural conversational agents, current cutting-edge approaches in rationale generation and the state-of-the-art research directions in alternative training methods will be discussed in this paper.

Author 1: Sasa Arsovski

Author 2: Sze Hui Wong

Author 3: Adrian David Cheok

Keywords: Artificial intelligence; deep learning; neural networks; open domain chatbots; conversational agents

Paper 55: Formal Analysis and Verification of Agent-Oriented Supply-Chain Management

Abstract: Managing various relationships among the supply chain processes is known as Supply Chain Management (SCM). SCM is the oversight of finance, information and material as they move in the flow from different suppliers to manufacturer, wholesaler, retailer and customers. The main problem with such software architecture is coordination and reliability while performing activities. Moreover, continuously changing market makes this coordination challenging. For example failure of production facilities, irregularities in meeting deadlines, unavailability of workers at required times. However, in the Agent-Oriented Supply-Chain Management described in [Mark S. Fox, Mihai Barbuceanu, and Rune Teigen “Agent-Oriented Supply-Chain Management”. The International Journal of Flexible Manufacturing Systems, 12 (2000)] the proposed solution claims a remarkable coordination on the basis of an agentoriented software architecture. In this paper, we formally specify architecture and verify it using model checking. We use UPPAAL to formally specify the agents’ behaviour involved in SCM. By model-checking, we prove that the given SCM’s architecture partially fulfills its functional requirements.

Author 1: Muhammad Zubair Shoukat

Author 2: Muhammad Atif

Author 3: Imran Riaz Hasrat

Author 4: Nadia Mushtaq

Author 5: Ijaz Ahmed

Keywords: Supply chain management; agent-oriented supplychain; model checking; formal specification and verification

Paper 56: Effect of TCP Buffer Size on the Internet Applications

Abstract: The development of applications, such as online video streaming, collaborative writing, VoIP, text and video messengers is increasing. The number of such TCP-based applications is increasing due to the increasing availability of the Internet. The TCP protocol, works at the 4th layer of the Internet model and provides many services such as congestion control, reliable communication, error detection and correction. Many new protocols have been proposed such as stream control transmission protocol (SCTP) with more features compared to the TCP. However, due to the wide deployment, TCP is still the most widely used. TCP creates the segments and transmit to the receiver. In order to prevent the errors TCP saves the segments into the sender buffer. Similarly, the data is also saved at the receiver buffer before its transmission to the application layer. The selection of TCP sender and receiver buffer may be varied. It is very important because many applications work on the smartphones that are equipped with a small amount of memory. In many applications such as online video streaming, some errors are possible and it is not necessary to retransmit the data. In such case, a small buffer is useful. However, on text transmission the complete reassembly of message is required by the TCP before transmission to the application layer. In such case, the large buffer size is useful that also minimizes the buffer blocking problem of TCP. This paper provides a detailed study on the impact of TCP buffer size on smart-phone applications. A simple scenario is proposed in NS2 simulator for the experimentation.

Author 1: Imtiaz A. Halepoto

Author 2: Nazar H. Phulpoto

Author 3: Adnan Manzoor

Author 4: Sohail A. Memon

Author 5: Umair A. Qadir

Keywords: TCP; sender buffer; receiver buffer; stream control transmission protocol (SCTP); error detection and correction

Paper 57: Non-Linear Energy Harvesting Dual-hop DF Relaying System over n-µ Fading Channels

Abstract: In this work, we analyze a wireless energy harvest-ing decode-and-forward (DF) relaying network with beamforming that is based on a practical non-linear energy harvesting model over η-μ fading channels. We consider a dual-hop relaying system having multiple antennas at the source and destination only. The single-antenna energy constrained relay assists the source to communicate with the destination. At the relay node, we assume a non-linear energy harvesting receiver which limits the harvested power level with a saturation threshold. By considering a power-splitting based relaying (PSR) protocol and a non-linear energy harvesting receiver, we analyze the system performance in terms of the outage probability and throughput for various antennas combinations and for various values of the fading parameters, η and μ. The η-μ fading model has a few particular cases, viz., Rayleigh, Nakagami-m, and Hoyt. These results are general and can be reduced for different fading scenarios as well as for linear energy harvesting relaying.

Author 1: Ayaz Hussain

Author 2: Nazar Hussain Phulpoto

Author 3: Ubaidullah Rajput

Author 4: Fizza Abbas

Author 5: Zahoor Ahmed Baloch

Keywords: Energy harvesting relay; non-linear energy har-vester; ?-µ fading; power-splitting-based relaying; throughput

Paper 58: Web Scraper Revealing Trends of Target Products and New Insights in Online Shopping Websites

Abstract: Trillions of posts from Facebook, tweets in Twitter, photos on Instagram and e-mails on exchange servers are overwhelming the Internet with big data. This necessitates the development of such tools that can detect the frequent updates and select the required information instantly. This research work aims to implement scraper software that is capable of collecting the updated information from the target products hosted in fabulous online e-commerce websites. The software is implemented using Scrapy and Django frameworks. The software is configured and evaluated across different e-commerce websites. Individual website generates a greater amount of data about the products that need to be scraped. The proposed software provides the ability to search a target product in a single consolidated place instead of searching across various websites, such as amazon.com, alibaba.com and daraz.pk. Furthermore, the scheduling mechanism enables the scraper to execute at a required frequency within a specified time frame.

Author 1: Habib Ullah

Author 2: Zahid Ullah

Author 3: Shahid Maqsood

Author 4: Abdul Hafeez

Keywords: Django QuerySet (DQS); e-commerce; hamming distance algorithm (HDA); Levenshtein distance algorithm (LDA); scraper; scheduling mechanism

Paper 59: Marine Engine Room Alarm Monitoring System

Abstract: Alarms affect operations in most part of the ship. Their impact on modern Engine Control Room operations is no less significant. The state of an alarm system serves as an indication of the extent to which the ship’s operations are under management control. Thus, the design of efficient and reliable alarm monitoring system is vital for safe and sound operations. Although several design techniques have been proposed, all the proposed design methods employ sophisticated and expensive approaches in resolving alarm issues. In this paper, a cheap, yet reliable and efficient alarm design method for engine room device monitoring is presented. The design method employs PLCs and SCADA-based system and adopts certain basic design requirements of alarm monitoring system presented in literary works. Reasons for such a design method are highlighted, and the programming platforms for the design are given. The strengths and weaknesses of some design methods presented in some published works are reported and solutions to such problems are proposed. The proposed design technique, including fault diagnostic algorithm, have been subjected to real-time online testing at the shipyard, specifically ChangjiangWaterway Bureau, China (ship name–Ning Dao 501). The testing results proved that this design technique is reliable, efficient and effective for online engine control room device monitoring.

Author 1: Isaac Tawiah

Author 2: Usman Ashraf

Author 3: Yinglei Song

Author 4: Aleena Akhtar

Keywords: Alarm monitoring system; engine control room; OPC communication; PLCs; SCADA systems

Paper 60: Performance Analysis of Machine Learning Algorithms for Missing Value Imputation

Abstract: Data mining requires a pre-processing task in which the data are prepared, cleaned, integrated, transformed, reduced and discretized for ensuring the quality. Missing values is a universal problem in many research domains that is commonly encountered in the data cleaning process. Missing values usually occur when a value of stored data absent for a variable of an observation. Missing values problem imposes undesirable effect on analysis results, especially when it leads to biased parameter estimates. Data imputation is a common way to deal with missing values where the missing value’s substitutes are discovered through statistical or machine learning techniques. Nevertheless, examining the strengths (and limitations) of these techniques is important to aid understanding its characteristics. In this paper, the performance of three machine learning classifiers (K-Nearest Neighbors (KNN), Decision Tree, and Bayesian Networks) are compared in terms of data imputation accuracy. The results shows that among the three classifiers, Bayesian has the most promising performance.

Author 1: Nadzurah Zainal Abidin

Author 2: Amelia Ritahani Ismail

Author 3: Nurul A. Emran

Keywords: Data Mining; Imputation; Machine Learning; KNearest Neighbors; Decision Tree; Bayesian Networks

Paper 61: Introducing a Cybersecurity Mindset into Software Engineering Undergraduate Courses

Abstract: Cybersecurity is a growing problem globally. Software helps to drive and optimize businesses in every aspect of modern life. Software systems have been under continued attacks by malicious entities, and in some cases, the consequences have been catastrophic. In order to tackle this pervasive problem, emphasis has been placed on educating software developers on how to develop secure systems. The majority of attacks on software systems have been largely due to negligence, lack of education, or incorrect application of cybersecurity defenses. As a result, there is a movement to increase cybersecurity education at all levels: novice, intermediate and expert. At the college level, students can be exposed to cybersecurity skills and principles that will better equip them as they transition into the workforce. A case study is presented which assesses the cybersecurity knowledge of juniors and seniors in a software engineering degree program taught over a one-semester period.

Author 1: Ingrid A. Buckley

Author 2: Janusz Zalewski

Author 3: Peter J. Clarke

Keywords: Cybersecurity; security education, software testing; computer security; defect detection, software maintenance

Paper 62: Trust and Security Concerns of Cloud Storage: An Indonesian Technology Acceptance

Abstract: Cloud drive is a service that offers data storage on the cloud. As the worldwide rapid growth of cloud drive there are ongoing concerns about trust, privacy and security concerns about how the user’s personal information and data are visible to other users or even abused by the cloud drive provider. This study provides empirical evidence about the factors affecting the acceptance of cloud drive users by using seven construct variables which are Trust, Perceived Risk, Perceived Ease of Use, Perceived Usefulness, Security, Behavioural Intention and Subjective Norm. Data were collected from 294 respondents by using online questionnaire. The data analysis method used was Structural Equation Modelling (SEM) analysis. The results of this study show that the factor affecting the intention of using cloud drive are trust, perceived risk and subjective norm.

Author 1: Nurudin Santoso

Author 2: Ari Kusyanti

Author 3: Harin Puspa Ayu Catherina

Author 4: Yustiyana April Lia Sari

Keywords: Cloud drive; structural equation modeling (SEM); trust; security; risk; behavior intention

Paper 63: Dimensions of Open Government Data Web Portals: A Case of Asian Countries

Abstract: Citizen Factors of the open government data are being explored in this study in the selected Asian countries. As per the open data availability countries have been selected on global open data index and well-structured open government data portals of Asian countries. To identify and analyze the differences of selected Asian countries through the principals of open government data which are eight in number, analysis the portal activities and observed the Open government data benefits. In analysis, the datasets of selected countries have been analyzed for the purpose of defining the portal activities. These activities include the Visitants, Suppliers, Applications, Developments, generation of Knowledge and overall resources utilization. Open government data of these countries are examined through web contented analysis, in order to understand the open government data’s status. This study also describes different challenges on how adoption, promotion and acceptance of the open government data and portals have been carried out by Asian countries. Moreover, there are some recommendations according to the key problems and status in the open government data initiatives. Also, the study has limitations regarding the number of countries and future directions emphasize the need for Open Government Data analysis in less developed countries also.

Author 1: Sanad Aarshi

Author 2: Usman Tariq

Author 3: Babur Hayat Malik

Author 4: Fariha Habib

Author 5: Kinza Ashfaq

Author 6: Irm Saleem

Keywords: Transparency; accountability; portal activities; adoption; principals of open government data which are eight in number; benefits of open government data; recommendations