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p-Index From 2021 - 2026
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All Journal Scientific Journal of Informatics Journal of Information Technology and Computer Science Journal of Information Technology and Computer Engineering International Journal of Applied Sciences and Smart Technologies
Oladimeji, Olayanju
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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A Comprehensive Survey On Cloud Computing Simulators Oladimeji, Oladosu Oyebisi; Oyeyiola, Dasola; Oladimeji, Olayanju; Oyeyiola, Pelumi
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.28878

Abstract

Cloud Computing is one of the upcoming technologies which has gotten the attention of many researchers and investor. But cloud computing still faces challenges because it is not economical and impractical for research institutions and industries to set up a physical cloud for research and experiments on it (cloud computing). Due to this, the researchers have chosen to test their contributions with simulators. Therefore, the purpose of this study is to perform a survey on existing cloud simulators. These cloud simulators aid in modeling cloud application through the creation of virtual machine, data Centre, and other thing which can be easily added and configured to it in order to provide stress free analysis. Till this present time, many cloud simulators with various features have been proposed and available for use. In this paper a comprehensive study has been performed on major cloud simulators by highlighting their features, strength and weakness through analysis. After which comparative analysis was done on the simulation, from the study, none of the simulators have the feature to simulate mobile cloud computing issues. This study has not been published anywhere else.
A Comprehensive Survey On Cloud Computing Simulators Oladimeji, Oladosu Oyebisi; Oyeyiola, Dasola; Oladimeji, Olayanju; Oyeyiola, Pelumi
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.28878

Abstract

Purpose: Cloud Computing is one of the upcoming technologies which has gotten the attention of many researchers and investor.  But cloud computing still faces challenges because it is not economical and impractical for research institutions and industries to set up a physical cloud for research and experiments on it (cloud computing). Due to this, the researchers have chosen to test their contributions with simulators. Therefore, the purpose of this study is to perform a survey on existing cloud simulators. Methods: These cloud simulators aid in modeling cloud application through the creation of virtual machine, data Centre, and other things which can be easily added and configured to it in order to provide stress free analysis. Result: Till this present time, many cloud simulators with various features have been proposed and available for use. Novelty: In this paper, a comprehensive study has been performed on major cloud simulators by highlighting their features, strengths, and weakness through analysis. After which comparative analysis was done on the simulation, from the study, none of the simulators have the feature to simulate mobile cloud computing issues. This study has not been published anywhere else.
Promoting Interest in Learning Yorùbá Language Using Mobile Game Oladimeji, Oladosu; Olorunfemi, Temitope; Oladimeji, Olayanju
Journal of Information Technology and Computer Science Vol. 5 No. 3: Desember 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (917.533 KB) | DOI: 10.25126/jitecs.202053232

Abstract

This paper describes acute areas in which technology plays a role in language and culture revitalization. It was discovered that in order for people to learn a new language, they must express interest in that language. This work presents a new way of arousing the interest of people in learning Yorùbá language through the use of mobile game thereby promoting and revitalizing Yorùbá language and culture. The mobile application was evaluated using questionnaire to selected participants who have the mobile game developed installed on their phones and explored the application, and then rated based on some criteria such as extensibility, ease of use and user interest in learning Yorùbá Language after playing the game. The results showed that 76% of respondents rated the game ease of use as above average, 70% and 90% of the respondents rated the extensibility of the game and interest in learning Yorùbá after playing game above average respectively. This technology-based application will serve as an interesting and fun-filled approach of getting people to express interest in learning native indigenous language individually and as a group.
Predicting Survival of Heart Failure Patients Using Classification Algorithms Oladimeji, Oladosu Oyebisi; Oladimeji, Olayanju
JITCE (Journal of Information Technology and Computer Engineering) Vol. 4 No. 02 (2020)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.4.02.90-94.2020

Abstract

Heart failure is a situation that occurs when the heart is unable to pump enough blood to meet the needs of other organs in the body. It is responsible for the annual death of approximately 17 million people worldwide. Series of studies have been done to predict heart failure survival with promising results. Hence, the purpose of this study is to increase the accuracy of previous works on predicting heart failure survival by selecting significant predictive features in order of their ranking and dealing with class imbalance in the classification dataset. In this study, we propose an integrated method using machine learning. The proposed method shows promising results as it performs better than previous works and this study confirms that dealing with imbalanced dataset properly increases accuracy of a model. The model was evaluated based on metrics such as F-measure, Precision-Recall curve and Receiver Operating Characteristic Area Under Curve. This discovery has the potential to impact on clinical practice, when health workers aim at predicting if a patient will survive heart failure. Attention may be focused on mainly serum creatinine, ejection fraction, smoking status and age.
A Deep Learning Model for Identical National Flag Recognition in Selected African Countries Aworinde, Halleluyah Oluwatobi; Oladimeji, Oladosu; Adebayo, Segun; Akinwunmi, Akinwale; Sakpere, Aderonke Busayo; Oladimeji, Olayanju
International Journal of Applied Sciences and Smart Technologies Volume 05, Issue 02, December 2023
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v5i2.6452

Abstract

The national flags are among the symbolic representations of a country. They make us understand the country of interest in a particular issue. Therefore, they are commonly used in both private and government organizations. It has been discovered in recent times that the younger generation mostly and idly and spend its time online; hence, knowing little about national flags. Additionally, some national flags (particularly in West Africa) are identical in nature. The likeness is in terms of layout, colours, shapes and objects on the national flags. Hence, there is a need to have a model for flag recognition. In this paper, national flag images of some West African countries were gathered to form a dataset. After this, the images were preprocessed by cropping out the irrelevant parts of the images. VGG-16 was used to extract necessary features and to develop the deep learning model. This contrasted with the existing handcrafted feature extraction and traditional machine learning techniques used on this subject matter. It was observed from this study that the proposed approach performed excellently well in predicting national flags; with an Accuracy of 98.20%, and an F1 score of 98.16%. In the future, it would be interesting to incorporate the national flag recognition into Human-Computer Interaction System. For instance, it could be used as flag recognition in some mobile and web applications for individuals with colour blindness. This research work presents a robust model because of nature of the dataset used in this work compared to previous works.
Co-Authors Adebayo, Segun Akinwunmi, Akinwale Aworinde, Halleluyah Oluwatobi Oladimeji, Oladosu Oladimeji, Oladosu Oyebisi Olorunfemi, Temitope Oyeyiola, Dasola Oyeyiola, Pelumi Sakpere, Aderonke Busayo