Open Access Case study

Digital Collaborative Framework for Students’ Industrial Work Experience Scheme and Sustainability in Federal Polytechnic Offa, Nigeria

AbdulAkeem O. Otunola, Abdullateef O. Alabi, A. T. Abdullateef, M. K. Lawal, N. O. Olanipekun

Asian Journal of Research in Computer Science, Volume 7, Issue 1, Page 21-31
DOI: 10.9734/ajrcos/2021/v7i130171

Graduate training is one of the core courses offered in all polytechnics systems in Nigeria, each polytechnic gives orientation programmes and deploys students for industrial training once a year. These processes of pen on paper method throw serious challenges because of time authorization and time frame. Placement of undergraduate students looking for relevant Industrial Training (IT) attachment is becoming worrisome. This research tends to provide a web based solution called Digital Collaborative Framework (DCF) for Students’ Industrial Work Experience Scheme (SIWES) and sustainability in Federal Polytechnic Offa, Nigeria. This is to bridge the gap between educational institutions and the industries subject to training and re-training perspectives. The stakeholders can easily turn DCF into e-administrative tools, then allow students to get industrial placement relevant to their field of studies. The research proposed to develop a productive web application using Codeigniter Php framework. This research will serve as a cloud database to students, staff and other stakeholders and create access to examine, monitor and measure students’ performance at the end of the (SIWES) scheme.

Open Access Case study

Data Analytic Solution for Heterogeneous Transportation Management Network System: A Case Study of Kwara State, Nigeria

A. Aroyehun Kayode, Abdullateef O. Alabi, T. Salaudeen Ganiyat

Asian Journal of Research in Computer Science, Volume 7, Issue 1, Page 32-49
DOI: 10.9734/ajrcos/2021/v7i130172

When the transportation system of any States in Nigeria is effective, it positively contributes to effective economy growth and infrastructural facilities; saves stress and generate revenue to the authorities. This is the desire of every ministry of Transportation for State in Nigeria although a number of constraints usually make it not attainable. The transportation system presently operated by the Ministry of Transportation, Kwara was studied and found to be suffering, cumbersome, exploitative and fall short in all standards of a good transportation network system. Therefore this paper seeks to present the results of the research carried out to Big Data Analytic Solution (BDAS) for the management of the transport companies’ network system within Kwara State. The research adopts a transportation frame work design solution, MySQL for data migration and Php framework ‘codeigniter’ for productive server for the full development. The phase testing is carried out and presents the improved version for the improvement in routes schedules, company’s services and driver’s registration and user booking.

The system will serve as open access to heterogeneous communities in Kwara State, Nigeria and make easy booking for passengers, assist communities in management of transportation systems within kwara state, Nigeria.

Open Access Original Research Article

A Threshold-based Tournament Resource Allocation in Cloud Computing Environment

I. P. Oladoja, O. S. Adewale, S. A. Oluwadare, E. O. Oyekanmi

Asian Journal of Research in Computer Science, Volume 7, Issue 1, Page 1-13
DOI: 10.9734/ajrcos/2021/v7i130169

Cloud computing environments provide an apparition of infinite computing resources to cloud users so that they can increase or decrease resource consumption rate according to their demands. In the Cloud, computing resources need to be allocated and scheduled in a way that providers can achieve high resource utilization and users can meet their applications’ performance requirements with minimum expenditure. Due to these different intentions, there is the need to develop a scheduling algorithm to outperform appropriate allocation of tasks on resources. The paper focuses on the resource optimization using a threshold-based tournament selection probability for virtual machines used in the execution of tasks. The proposed approach was designed to create metatask and the proposed algorithm used was Median-Based improved Max-Min algorithm. The experimental results showed that the algorithm had better performance in terms of makespan, utilization of resources and throughput. The load balance of tasks was also fairly distributed on the two datacenters.

Open Access Original Research Article

Extracting a Bounded Region from a Map Using Flood Fill Algorithm

S. M. Abdullah Al Shuaeb, Md. Kamruzzaman, Mohammad Hazrat Ali

Asian Journal of Research in Computer Science, Volume 7, Issue 1, Page 14-20
DOI: 10.9734/ajrcos/2021/v7i130170

Extracting the needed portion from a bounded region is an important task in image processing. Editing a map and extracting a region from the map is challenging. It is useful in some contexts to have a region in a separate sheet. In this image processing, we have used the Flood Fill algorithm to extract a region from the image map. To achieve that goal, we had worked in our study to separate a bounded region on a map. Usually, a scanned map may contain a lot of useless information. So we have to process the image to remove useless information from the map. We had quantized the image to a binary one. In the second phase, we have applied a gray color to separate the desired position from a map. Our main objective of the study to extract a bounded region from mapping an image that contains useless information and removes it. We have experimented with several maps and it works successfully.

Open Access Original Research Article

Framework for Prioritizing Contact Tracing and Mass Testing of COVID-19 Using Graph Theory

Obed Appiah, Dominic Otoo, Christopher Bombie Ninfaakang

Asian Journal of Research in Computer Science, Volume 7, Issue 1, Page 50-66
DOI: 10.9734/ajrcos/2021/v7i130173

Contact tracing has become one of the most useful tools for fighting the novel Corona Virus (COVID-19) pandemic worldwide. The underlining philosophy of contact tracing is determining people who have been in contact with infected persons and thus isolate them from becoming agents of onward transmission of the virus.  Slow tracing of contacts and inconsistent or inaccurate information provided by patients usually leads to the spread of the virus along a trajectory at the healthcare systems' blindside. This has led to the proposal of app-based contact tracing solutions.  This paper proposes an SQL-based framework that transforms simple interaction data entries into interaction graphs and applies graph theory to prioritize the contact tracing process. The framework returns nodes or individual IDs together with values called Risk_Points to enable individuals' selection for isolation and treatment. Results on simulated data show that the proposed framework can help slow the virus's rate of transmission.