https://www.ajol.info/index.php/jcsia/issue/feed Journal of Computer Science and Its Application 2021-04-04T07:30:11+00:00 Dr. A.S. Sodiya sinaronke@yahoo.co.uk Open Journal Systems <p>The journal provides a multidisciplinary forum for the publication of original research and technical papers, short communications, state-of-art computing and review papers on advances, techniques, practice, and applications of Computer Science.</p><p>Other websites associated with this journal: <a title="http://www.publication.ncs.org.ng/" href="http://www.publication.ncs.org.ng/" target="_blank">http://www.publication.ncs.org.ng/</a></p> https://www.ajol.info/index.php/jcsia/article/view/205397 An enhanced algorithm for scheduling dependent tasks in cloud computing environment 2021-03-31T06:24:28+00:00 H. Hamza hafsatmadawaki@yahoo.com A.F.D Kana donfackkana@abu.edu.ng M.Y. Tanko tymohammed45@gmail.com S. Aliyu aliyusalisu@abu.edu.ng <p>Cloud computing is a model that aims to deliver a reliable, customizable and scalable computing environment for end-users. Cloud computing is one of the most widely used technologies embraced by sectors and academia, offering a versatile and effective way to store and retrieve documents. The performance and efficiency of cloud computing services always depend upon the performance of the execution of user tasks submitted to the cloud system. Scheduling of user tasks plays a significant role in improving the performance of cloud services. Accordingly, many dependent task scheduling algorithms have been proposed to improve the performance of cloud services and resource utilization; however, most of the techniques for determining which task should be scheduled next are inefficient. This research provided an enhanced algorithm for scheduling dependent tasks in cloud that aims at improving the overall performance of the system. The Dependent tasks were represented as a directed acyclic graph (DAG) and the number of dependent tasks and their total running time were used as a heuristic for determining which path should be explored first. Best first search approach based on the defined heuristic was used to traverse the graph to determine which task should be scheduled next. The results of the simulation using WorkflowSim toolkit showed an average improvement of 18% and 19% on waiting time and turnaround time were achieved respectively.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205398 An improved percentage rate accuracy in predicting mortality in hepatitis-c using an artificial neural network 2021-03-31T06:35:44+00:00 Daniel Matthias matthias.daniel@ust.edu.ng I.N. Davies isobodavies@yahoo.com O. Olumide olumide.owolabi@uniabuja.edu.ng <p>Background accurate prediction of mortality in Hepatitis-C (Hep C) is essential for policy action and planning. While studies have used artificial intelligent technique (e.g., artificial neural network (ANN)), their appropriateness to predicting mortality in hepatitis-c has been debated. This study presents an improved percentage rate accuracy that is capable of predicting whether a patient suffering from Hepatitis-C Virus (HCV) is likely to survive or die. The constructive research method was adopted for this study, while an Object Oriented Design Approach was adopted for the systems structural design. The Artificial Neural Network system was implemented using java programming language with many program modules and four (4) design classes namely; the Driver class that runs the application program, the Neural Network class, the Neuron and the Layer classes. The network was trained using back propagation machine learning algorithm, a learning rate of 0.8 and a learning error of 0.05. While the weights used for the training were random numbers ranging from -1.0 to +1.0. The maximum number of training sessions was set to 10000 assuming the network does not converge to the leaning error of 0.05. The result of the network showed 85% accuracy in predicting cases of the patients with positive hepatitis C virus that may survive and also 50% accuracy in predicting cases of patients with positive Hepatitis-C Virus (HCV) that may likely to die given the provided data. Neural network is a powerful classification and prediction tools that can help in predicting the outcome of Hepatitis-C virus (HCV) infections. Recommending experiment on the network architecture with a view to either increase the hidden layers or increasing the number of units in the hidden layer. Also, more extensive testing and training should be carried out to achieve the desired result.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205399 Empirical evaluation of basic Information and Communication Technology (ICT) skills of final year students of Federal College of Education (Technical), Omoku 2021-03-31T06:43:29+00:00 Onyedimekwu Okechi okesonab@gmail.com Oruan K. Memoye okesonab@gmail.com <p>This research work titled “Empirical Evaluation of Basic Information and Communication Technology (ICT) Skills of Final Year Students of Federal College of Education (Technical), Omoku” used UNESCO ICT-Competency Framework for Teachers version 3, 2018 as a conceptual framework to assess basic ICT skills and competency level of students. It employed evaluative survey design using questionnaire as the instrument of data collection, designed and administered to all the 51 Part-Time final year students. Analysis of the research result using SPSS Version 20 shows that 4 (7%) of the students lack basic ICT skills, 13 (25%) of them are average in the use of ICT tools and 14 (27%) of them have above average ICT skills. A mean of 3.7 shows that 74% of the students agree that their ICT Instructors possesses the requisite professional skills and competencies to teach. Since 25% of the students can averagely use ICT tools, the researcher recommends that the Government should implement the Monitory and Evaluation of its huge investment in ICT in Education by making sure ICT Facilities are used for teaching and learning in schools.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205400 Examining E-learning as an alternative solution to conventional learning during and post Covid-19 in Nigeria. 2021-03-31T06:55:26+00:00 Christopher Ubaka Ebelogu Christopher@uniabuja.edu.ng Virginia Ebere Ejiofor Christopher@uniabuja.edu.ng Aliyu Omeiza Christopher@uniabuja.edu.ng Lucy Hassana Audu Christopher@uniabuja.edu.ng <p>It is no longer news that the novel Corona Virus pandemic (COVID-19) is ravaging and still destroying the world, killing so many people and sending economies in different countries into recession. COVID-19 came as a thief in the night in the household of traditional schooling. Gradually, the face-to-face traditional way of teaching and learning was immediately put on hold and all parties running to their shelves for cover as measure to avert the spread of the dreaded virus. What came up as a viable alternative to face-to-face or conventional mode of teaching-learning in school and higher institution is E-learning. So many of these educational institutions had to resort to learning through some E-learning platforms which include ZOOM, YouTube, Google Meet, Google Classroom, Duo, Free Conference Call, etc. This established the fact that majority of the organizations have made an instant switch to online collaboration inclusive of schooling systems. This paper therefore sort to examine how Nigerian schools are reshaping the schooling/education system as to align with the alternative model of teaching-learning most essentially as E-learning rest on major pillars which are undoubtedly deficient in Nigeria and amongst Nigerians. There are challenges to overcome in achieving the e-learning phenomenon in Nigeria, many students without reliable internet access, power supply and technology struggle to participate in digital activities, which hinder online learning. The paper was approached in an E-learning subscriber or user point of view around FCT Abuja metropolis which includes teachers and learners (students/pupils). Questionnaires were distributed to the E-learning users and also the teachers of E-learning. Data were collected and analyzed using percentage method and Likert method to arrive at a conclusion and useful recommendations were made to enhance e-learning during and post COVID-19 in the various educational institutions in Nigeria.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205402 Face mask detection application and dataset 2021-03-31T07:06:15+00:00 Daniel Matthias matthias.daniel@ust.edu.ng Chidozie Managwu chidozie.managwu@gmail.com O. Olumide olumide.owolabi@uniabuja.edu.ng <p>The COVID–19 pandemic is, without any doubt, changing our world in ways that are beyond our wildest imagination. In a bid to curb the spiraling negative fallouts from the virus that has resulted in a large number of casualties and security concerns. The World Health Organization, amongst other safety protocols, recommended the compulsory wearing of face masks by individuals in public spaces. The problem with the enforcement of this and other relevant safety protocols, all over the world, is the reluctance and outright refusal of citizens to comply and the inability of relevant agencies to monitor and enforce compliance. This paper explores the development of a CCTV–enabled facial mask recognition software that will facilitate the monitoring and enforcement of this protocol. Such models can be particularly useful for security purposes in checking if the disease transmission is being kept in check. A constructive research methodology was adopted, where a pre-trained deep convolutionary neural network (CNN) (mostly eyes and forehead regions) used and the most probable limit (MPL) was use for the classification process. The designed method uses two datasets to train in order to detect key facial features and apply a decision-making algorithm. Experimental findings on the Real-World-Masked-Face-Dataset indicate high success in recognition. A proof of concept as well as a development base are provided towards reducing the spread of COVID-19 by allowing people to validate the face mask via their webcam. We recommend that the use of the app and to further investigate the development of highly robust detectors by training a deep learning model with respect to specified face-feature categories or to correctly and incorrectly wear mask categories.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205403 Fault mitigation in real-time cloud computing 2021-03-31T07:11:19+00:00 Osuolale A. Festus aofestus@futa.edu.ng Adewale O. Sunday aofestus@futa.edu.ng Alese K. Boniface aofestus@futa.edu.ng <p>The introduction of computers has been a huge plus to human life in its entirety because it provides both the world of business and private an easy and fast means to process, generate and exchange information. However, the proliferation of networked devices, internet services and the amount of data being generated frequently is enormous. This poses a major challenge, to the procurement cost of high performing computers and servers capable of processing and housing the big data. This called for the migration of organizational and/or institutional data upload to the cloud for high<br>level of productivity at a low cost. Therefore, with high demand for cloud services and resources by users who migrated to the cloud, cloud computing systems have experienced an increase in outages or failures in real-time cloud computing environment and thereby affecting its reliability and availability. This paper proposes and simulates a system comprising four components: the user, task controller, fault detector and fault tolerance layers to mitigate the occurrence of fault combining checkpointing and replication techniques using cloud simulator (CloudSim).</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205404 Internet of Things (IoT) and emerging Wireless Technologies in the 21<sup>st</sup> Century 2021-03-31T07:17:09+00:00 O.C. Ngige ogochukwu.ngige@fiiro.gov.ng C.E. Chibudike ogochukwu.ngige@fiiro.gov.ng D.O. Omotosho ogochukwu.ngige@fiiro.gov.ng <p>This paper accesses the Internet of Things (IoT) in conjunction with the emergence of Wireless Technologies. Internet of Things (IoT) refers to a type of network to connect anything with the Internet, based on stipulated protocols through information sensing equipment to conduct information exchange and communications; in order to achieve smart recognitions, positioning, tracing, monitoring, and administration. This investigates the Internet of Things (IoT) and its incorporation of multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Particularly, it focuses on ZigBee, 6LoWPAN, Bluetooth Low Energy, LoRa, and so on. This enables numerous business opportunities in fields as diverse as e-health, smart cities, and smart homes, among many others. This research briefly discussed about IoT, some of the major evolving and enabling wireless technologies in the IoT, Smart Environnent Application Domain, and Application of IoT. Benefits and Challenges of IoT.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205405 Nigeria at sixty: An analysis of user participation in an online national competition amidst the Covid-19 pandemic 2021-03-31T07:22:34+00:00 Idris Abubakar Umar brossadiq@gmail.com Yazid Ado Ibrahim brossadiq@gmail.com Bashir Salisu Abubakar brossadiq@gmail.com Zainab Magaji Musa brossadiq@gmail.com Muhammad Mahmoud Ahmad brossadiq@gmail.com <p>Activities across the world were halted due to the COVID-19 pandemic in the year 2020. Events such as sports, national celebrations, international exhibitions and conferences were cancelled or postponed due to the restrictions posed by governments to mitigate the pandemic. The Information Communication Technology (ICT) sector being loosely constrained by the restrictions, was mandated to facilitate some of these events. In this research, we made computational analysis, by leveraging an Information Technology (IT) platform (Website) to conduct pre-anniversary competitions in celebration of Nigeria’s 60th Anniversary. The aim of using the website was to gather Information regarding the pre-anniversary competitions to determine user participation in online events across Nigeria. Initially, information about the site was propagated via various media outlet to call for participation. Activities performed by participants across all states of the nation (Nigeria) were recorded, as well as the site activities for a designated period of time. An extensive analysis was conducted using the Google analytics tool. Performance show that much needed to be done to improve and engage citizens in participating in national events, which employ IT platforms as an alternative to the main event during the COVID-19 pandemic.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205406 Pedagogical use of mobile technologies during Coronavirus school closure 2021-03-31T07:27:40+00:00 Edeh Michael Onyema michael.edeh@ccu.edu.ng Ani Ukamaka Eucharia michael.edeh@ccu.edu.ng Faluyi Samuel Gbenga michael.edeh@ccu.edu.ng Akindutire Opeyemi Roselyn michael.edeh@ccu.edu.ng Omachi Daniel michael.edeh@ccu.edu.ng Nnaekwe Uchenna Kingsley michael.edeh@ccu.edu.ng <p>The unplanned closure of schools due to Coronavirus Disease 2019 (COVID-19) left millions of students out of schools. However, the use of mobile technologies offered opportunities for educators and students to engage in remote pedagogical activities during the school closures. The study investigated the effects of the usage of mobile technologies on educators’ and students’ pedagogical activities during the COVID-19 school closure, and on the students’ attitudes towards pedagogical activities during the COVID-19 school closure. A total of 150 questionnaires were administered to participants that consist of educators and students from different levels of education in Nigeria. The samples were selected through simple random sampling technique, and collected data were analyzed using percentages, frequencies, and statistical methods of regression and ANOVA. The results show that the use of mobile technologies had statistically significant effects on the pedagogical activities of students and educators during the COVID-19 school closure, and on the attitudes of students towards pedagogical activities during the COID-19 school closure. Majority of the participants agreed that the use of mobile technologies such as: laptops, mobile phones, mobile apps, MP3, and other PDAs positively influenced their pedagogical activities during the COVID-19 school closure. The study concludes that mobile technologies have become an important and promising pedagogical tool which can be harnessed to enhance ubiquitousness and continued education during and after school closure or outbreak of pandemics.</p> 2021-03-31T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205465 Web-based health service management for the eye 2021-04-04T07:12:37+00:00 J.C. Onwuzo fzinoz@gmail.com C.E. Osodeke fzinoz@gmail.com E.K. Chigbundu fzinoz@gmail.com B.N. Kalu fzinoz@gmail.com <p>This research was designed for the purpose of patients with eye defects who have difficulty visiting their doctors due to age, distance, or the manual processes involved in the existing system. We designed an approach to assist people get attended to by building a system that allows users register and log into the system, book appointments, view doctors and equipment used or available in the existing system. Joint Application Development (JAD) was the system methodology used, this is because it involves continuous interaction with the users and different designers of the system in&nbsp; development. Quantitative and qualitative research methodology were employed, and method of data collection used were questionnaire, interview, and internet. The resultant website developed using JavaScript, CSS, PHP, HTML, and MySQL allows users register and log in, schedule doctor’s appointment, and book surgery.</p> 2021-04-04T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205466 A fuzzy logic risk control and self-assessment metrics for e-banking operational risk analysis 2021-04-04T07:19:44+00:00 R.E. Ako ochukorita2@gmail.com D. Oghorodi ochukorita2@gmail.com A.E. Okpako ochukorita2@gmail.com <p>Operational risk is the risk of losses arising from the failure or inadequate internal processes, human resources, systems, and external events that affect the bank's operations as defined by Basel Committee on Banking Supervision. Defining a suitable set of risk measurement metrics is considered one of the most important issues for any risk analysis. It enables the quantitative evaluation of the risk exposure level and the effectiveness of internal control system. Risk measurement is needed to provide an effective means to quantify the risk of existing or planned systems to enable understanding of the overall security level and to guide decision making. Given the number of successful attacks against financial Institutions and the sophistication of the tactics used by attackers, existing classical measurement approaches are no longer enough. This study focuses on fuzzy logic-based metric identification to measurement of the risk exposure level, to enable financial institutions to see the overall risk level and security state of their E-banking systems and to assist with decision making. This will provide a newer dimension to risk management by shifting from risk measurement based on probability and classical set theory to Fuzzy Logic (FL) measurement. In this paper fuzzy logic-based metrics is presented and expressed as a function of six factors (triggering events, avoidance, recovery, Undesirable Operational State (UOS), cost of Undesirable Operational State (UOS) occurrence and severity of risk occurrence) as proposed by [1].</p> 2021-04-04T00:00:00+00:00 Copyright (c) https://www.ajol.info/index.php/jcsia/article/view/205467 Detection and prediction of pluvial flood using machine learning techniques 2021-04-04T07:24:35+00:00 K.A. Oladapo oladapokayodeabiodun@gmail.com F.Y. Ayankoya oladapokayodeabiodun@gmail.com F.A. Adekunle oladapokayodeabiodun@gmail.com S.A. Idowu oladapokayodeabiodun@gmail.com <p>The periodical occurrence of emergency situations represents an important issue for mankind. Over the years, the world at large has experienced multiple misadventures both natural and man-made. A recent report showed that flood have affected more individuals than any other category of disaster in the 21st century with the highest percentage of 43% of all disaster events in 2019 and Africa been the second vulnerable continent after Asia. Handling flood risk with the intention of safety and comfort of the citizens as well as saving their environment is one of the major responsibilities of the leadership in each country especially in flood prone areas. Machine learning predictive analytic applications can improve the risk management. So, it is highly important to devise a scientific method for flood risk reduction since it cannot be eradicated. The paper proposes a pluvial flood detection and prediction system based on machine learning techniques. The proposed model will employ a fuzzy rule-based classification to appraise the performance of the machine learning algorithm on pluvial flood conditioning variables.</p> 2021-04-04T00:00:00+00:00 Copyright (c)