https://iksp.org/journals/index.php/ijcse/issue/feed iKSP Journal of Computer Science and Engineering 2021-02-11T13:59:56+00:00 Editor in Chief editor.ijcse@iksp.org Open Journal Systems <p><em>iKSP Journal of Computer Science and Engineering (iJCSE)</em> is an Open Access, Blind Peer Reviewd research jornal published biannualy. <em>iJCSE</em> provides readers with a compilation of stimulating and up-to-date articles within the field of computer science and Engineering. The focus of the journal is on high quality research that addresses paradigms, development, applications and implications in the field of computer science. All research articles in <em>iJCSE</em> will undergone rigorous peer review, based on initial editor screening and anonymized refereeing by an expert reviewer.</p> <p>Our peer-review is very fast, highly rigorous and authors are carried along adequately in all the publication processes. We inform authors of the decision on their manuscript(s) within <strong>TWO WEEKS</strong> of submission. Following acceptance, a paper will normally be published in the coming issue.</p> <p>ISSN (Online): 2701-7095<br />ISSN (Print): 2701-7176</p> https://iksp.org/journals/index.php/ijcse/article/view/82 Vehicle Route Prediction through Multiple Sensors Data Fusion 2020-12-18T14:51:15+00:00 Ali Nawaz alinawaztanoli097@gmail.com Attique Ur Rehman alinawaztanoli097@gmail.com Muhammad Tahir Ali alinawaztanoli097@gmail.com Muhammad Abbas alinawaztanoli097@gmail.com <p>Vehicle route prediction is one of the significant tasks in vehicles mobility. It is one of the means to reduce the accidents and increase comfort in human life. The task of route prediction becomes simpler with the development of certain machine learning and deep learning libraries. Meanwhile, the security and privacy issues are always lying in the vehicle communication as well as in route prediction. Therefore, a framework which will reduce these issues in vehicle communication and predict the route of vehicles in crossroads is proposed. Specifically, our proposed framework consists of two modules and both are working in sequence. The first module of our framework using a deep learning for recognizing the vehicle license plate number. Then, the second module using supervised learning algorithm of machine learning for predicting the route of the vehicle by using velocity difference and previous mobility patterns as the features of machine learning algorithm. Experiment results shows that accuracy of our framework.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/95 High Performance Backstepping Control of Induction Motor Fed by 19 Level Asymmetrical Inverter 2020-12-18T15:01:24+00:00 Rachid TALEB rac.taleb@gmail.com Ali BOUCHAIB ali81.bouchaib@gmail.com Abdelhadi NAMOUNE namoune.abdelhadi@gmail.com <p>In this paper we will present a contribution to the backstepping control for induction motor (IM) based on the principle of Field Orientated Control (FOC). This law is established step by step while ensuring the stability of the machine in the closed loop, by a suitable choice of the function Lyapunov. In addition it is executed to assure the convergence the error´s speed tracking at all initials conditions are possible. Both the speed and the rotor flux are supposed obtained by sensors. The control of the IM by 19 level asymmetrical inverter generally uses Pulse-width modulation techniques (PWM). Finally, we represent some of the simulation results by simulations in Matlab/Simulink environment.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/136 Mental Health Diseases Analysis on Twitter using Machine Learning 2021-01-19T12:07:12+00:00 Mehak Faryal mkpheryal@gmail.com Munwar Iqbal munwar.iq@uettaxila.edu.pk Hifsa Tahreem tahreem.1874105@studenti.uniroma.it <p>Twitter is a cutting-edge platform among social networks. It allows microblogging of up to 140 characters for a single post. Due to this feature, it is popular among users. People tweet on a variety of topics, from everyday events to major accidents. Twitter Attitude Analysis gives organizations the ability to screen audiences' behaviour concerning related products and events in real-time. The first step in attitude analysis is the processing of Twitter data before the text. It uses a Twitter dataset that makes NLTK resources available to the public. Most of the existing research on Twitter attitude analysis focuses on removing mood traits. However, the pre-treatment method is used for selection. This study discussed the effect of the word processing method on mood classification. The performance measured in two types of classification activities and summarized. The classification performance of pre-processing methods using different attributes and classifiers in the Twitter dataset retrieved from Twitter Application Programming Interface API. The pre-processing used to remove URL’s removing meaningless numbers or words. Therefore, Twitter data is extracted, and the mood is calculated for tweets on a particular topic. It focuses on tweets about mental health problems caused by the use of social media platforms. We calculate and analyze attitudes from tweets using machine learning algorithms. We implement the machine learning algorithms, including Naive Bayes, Random Forest, Regression, and support vector machine. The results show that classification accuracy improves Twitter F1 ranking while using pre-processing methods to expand acronyms and replace negligence. The function extraction methods are combined with Machine Learning algorithms were found to have the highest accuracy of 92%.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/96 Passivity Based Control for PV Applications by Using a Buck Power Converter 2020-12-21T09:29:59+00:00 Rachid TALEB rac.taleb@gmail.com Maamar SOUAIHIA m.souaihia@univ-chlef.dz Abdelhadi NAMOUNE namoune.abdelhadi@gmail.com Hacene MELLAH h.benbouhenni@gmail.com <p>The use of power converters for everyday applications is becoming more and more important. Current technological applications simultaneously demand a high level of precision and performance, so DC-DC converters have a very important role in systems requiring energy level conversion and adaptation. As part of the work of this paper, we are interested in an analysis of modeling and control law synthesis approaches to ensure stability and a certain level of performance in the entire operating domain. The objective of our research work is therefore to propose a control law whose synthesis is based on a formalized (modeling &amp; control) approach with a view to obtaining a control law adapted to the operating point. The principles used are based on the control and observation by the theory of passivity for the synthesis of control law of buck power converter for PV Applications.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/83 Role of Project Management in Virtual Team’s Success 2020-12-18T14:52:50+00:00 Attique Ur Rehman alinawaztanoli097@gmail.com Ali Nawaz alinawaztanoli097@gmail.com Muhammad Tahir Ali alinawaztanoli097@gmail.com Muhammad Abbas alinawaztanoli097@gmail.com <p>A virtual team is a group of geographically distant people who work together to achieve a shared goal for a common organization. From the past few years this concept has been evolved and has emerged the idea of global project management. Virtual teams have been beneficial in cost reduction, hiring competent work force and improving globalization. Although virtual teams are beneficial for an organization, but they are hard to manage and control successfully. There can be several challenges like cultural issues, different time zones and communication gap. These challenges are not hard to manage, and we can overcome these challenges using effective project management skills. These skills will become the success factors for making virtual teams successful and will be determined by comparison of the survey results of traditional and virtual teams.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/81 A Survey of Requirement Engineering Process in Android Application Development 2020-12-18T14:48:42+00:00 Ali Nawaz alinawaztanoli097@gmail.com Attique Ur Rehman ahattique@gmail.com Muhammad Tahir Ali alinawaztanoli097@gmail.com Muhammad Abbas alinawaztanoli097@gmail.com <p>Mobile application development is the most rapidly growing industry in the world. Nowadays, people totally depend on smart phones for performing daily routine tasks which results in tremendous rises in the expectation of human being from IT industry which increase the requirements of human being. In order to tackle the uncontrolled changes in the requirements, IT experts performed some proper requirement engineering process (REP). Therefore, in this paper we are performing industry survey by asking them several questions related to the REP from android developer in order to understand the REP used in the IT industry. Results we extract from this study is satisfactory used in order to make REP more effective.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/105 Intracranial Brain Haemorrhage Segmentation and Classification 2020-12-21T09:36:18+00:00 Raima Imran raima.imran.ri@gmail.com Noorish Hassan l174002@lhr.nu.edu.pk Rishwan Tariq l174095@lhr.nu.edu.pk Laraib Amjad l174156@lhr.nu.edu.pk Aamir Wali aamir.wali@nu.edu.pk <p>Traumatic brain injuries are categorized as sudden damage to the brain which may be caused by a blow to the head. A traumatic brain injury can cause intracranial bleeding which may lead to Intracranial hemorrhage (ICH). Computerized Tomography (CT) scans are widely used by radiologists in the detection and diagnosis of ICH. A CT scan creates images of the brain which can help detect bleeding and other signs of trauma to the head. However, accurate detection and diagnosis of ICH depend on access to an experienced radiologist. Failure to accurately detect and treat ICH promptly can lead to disability or even death. This project aims to develop an artificially intelligent system capable of detecting, diagnosing ICH, and classifying its sub-types. For this purpose, we will employ the techniques of computer vision and machine learning to train a Fully Convolutional Network (FCN) called u-net on a publicly available data set of head CT scans. The development process will include taking CT scans as input, using u-net as an FCN to perform semantic segmentation to classify the type of ICH, and the region of the brain affected by it. The proposed system will facilitate junior doctors and radiologists by providing them with assistance in the detection of ICH and its subtypes.</p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering https://iksp.org/journals/index.php/ijcse/article/view/92 ALICE Pattern Matching Based Chatbot for Natural Language Communication: System Development and Testing 2020-12-18T15:06:08+00:00 Munaveer Karimeni Peedikayil Tharammal munaveer00@gmail.com Muhammad Nauman Bashir mbashir@mec.edu.om Kamaludin Mohamed Bin Yusof kamalmy@utm.my Sameera Iqbal sameeraiqbal786@hotmail.com <p>The simulation of human processes using Artificial Intelligence (AI) features is finding place in various fields including the e-learning environment. Chatbot system using text and voice, recognizing images, analyzing the sentiments, and generating natural language is latest utility based on AI concepts. The chatbot systems are becoming more common due to their benefits as a support mechanism helping human beings in their day to day tasks. This project aimed at developing and testing a chatbot system to communicate with the education sector users using natural language through android based application creating a smart education environment. The project developed an online chatting platform using Artificial Linguistic Internet Computer Entity (ALICE) Pattern Matching techniques where students could communicate related to their learning activities such as submission deadline of the reports and assignments, student’s information, co-curricular and extracurricular activities. The system design uses a Raspberry Pi 3 which works as Transmission Control Protocol (TCP) server and uses three different types of pattern matching techniques which are keyword detection, symbolic reduction, and synonyms resolution. An android user interface application is also designed which works as TCP client. The system design uses a database for student information system in the Python server. The obtained results are in voice and text format from the android user interface application and are displayed on Python Interpreter. The developed project system can enhance the student engagement in learning activities. This system can also help teachers in saving their time and to support them to utilize their class timings for other co-curricular activities like synchronous and asynchronous activities to support active learning and flipped learning. The proposed system has the potential to test and analyze various factors as use of technology, student learning including impact of student engagements in their learning activities. </p> 2021-02-11T00:00:00+00:00 Copyright (c) 2021 iKSP Journal of Computer Science and Engineering