Tinuke Omolewa Oladele
@unilorin.edu.ng
Associate Professor, Faculty of Communication and Information Sciences
University of Ilorin
RESEARCH, TEACHING, or OTHER INTERESTS
Multidisciplinary, Computer Science, Artificial Intelligence, Computer Science Applications
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Tunde Taiwo Adeniyi, Oladele Tinuke Omolewa, and Jide Kehinde Adeniyi
Universitas Ahmad Dahlan
Oluwafisayo Babatope Ayoade, Tinuke Omolewa Oladele, Agbotiname Lucky Imoize, Jerome Adetoye Adeloye, Joseph Bambidele Awotunde, Segun Omotayo Olorunyomi, Oulsola Theophilius Faboya, and Ayorinde Oladele Idowu
European Alliance for Innovation n.o.
INTRODUCTION: The human blood as a collection of tissues containing Red Blood Cells (RBCs), circular in shape and acting as an oxygen carrier, are frequently deformed by multiple blood diseases inherited from parents. These hereditary diseases of blood involve abnormal haemoglobin (Hb) or anemia which are major public health issues. Sickle Cell Disease (SCD) is one of the common non-communicable disease and genetic disorder due to changes in hematological conditions of the RBCs which often causes the inheritance of mutant Hb genes by the patient..
 OBJECTIVES: The process of manual valuation, predictions and diagnosis of SCD necessitate for a passionate time spending and if not done properly can lead to wrong predictions and diagnosis. Machine Learning (ML), a branch of AI which emphases on building systems that improve performance based on the data they consume is appropriate. Despite previous research efforts in predicting with single ML algorithm, the existing systems still suffer from high false and wrong predictions.
 METHODS: Thus, this paper aimed at performing comparative analysis of individual ML algorithms and their ensemble models for effective predictions of SCD (elongated shapes) in erythrocytes blood cells. Three ML algorithms were selected, and ensemble models were developed to perform the predictions and metrics were used to evaluate the performance of the model using accuracy, sensitivity, Receiver Operating Characteristics-Area under Curve (ROC-AUC) and F1 score metrics. The results were compared with existing literature for model(s) with the best prediction metrics performance..
 RESULTS: The analysis was carried out using Python programming language. Individual ML algorithms reveals that their accuracies show MLR=87%, XGBoost=90%, and RF=93%, while hybridized RF-MLR=92% and RF-XGBoost=99%. The accuracy of RF-XGBoost of 99% outperformed other individual ML algorithms and Hybrid models. 
 CONCLUSION: Thus, the study concluded that involving hybridized ML algorithms in medical datasets increased predictions performance as it removed the challenges of high variance, low accuracy and feature noise and biases of medical datasets. The paper concluded that ensemble classifiers should be considered to improve sickle cell disease predictions.
Oladele Tinuke Omolewa, Emmanuel Jadesola Adeioke, Oladele Oluwabunmi Titilope, Adewole Kayode Sakarivan, and Adeniyi Jide Kehinde
IEEE
Security of lives and properties is of high essence to a nation's growth and development. With the increase of global terrorist invasions, levels of national internal border security need to be increased. Thus, the need to deploy technologies such as biometric for further fortification cannot be underrated. Research has shown that biometrics technology - as an authentication technique has a broad-spectrum application in fields ranging from banking, medicine, airlines and so on. Unlike the conventional means of security checks, which basically entail physical/manual verification. Biometric techniques such as Face recognition, Fingerprint, DNA are more reliable and capable of uniquely identifying individuals in the verification process. The porous nature of the nation's border enables unauthorized immigrants gain access to the country which poses a high level of security threat. In this paper, a biometric based border control system is developed to reduce the rate of illegal immigrants into the country. C# programming language was employed to implement the proposed biometric based border control system. The various stages of biometric authentication were incorporated. The proposed system is recommended for controlling illegal immigrants at the Nigerian border.
Jide Kehinde Adeniyi, Tinuke Omolewa Oladele, Ayodele Adebiyi, Marion Adebiyi, and Tunde Taiwo Adeniyi
Insight Society
Adeniyi Jide Kehinde, Oladele Tinuke Omolewa, Akande Oluwatobi Noah, and Adeniyi Tunde Taiwo
Institute of Advanced Engineering and Science
<span lang="EN-US">Hand geometry has been a biometric trait that has attracted attention from several researchers. This stems from the fact that it is less intrusive and could be captured without contact with the acquisition device. Its application ranges from forensic examination to basic authentication use. However, restrictions in hand placement have proven to be one of its challenges. Users are either instructed to keep their fingers separate or closed during capture. Hence, this paper presents an approach to hand geometry using finger measurements that considers both closed and separate fingers. The system starts by cropping out the finger section of the hand and then resizing the cropped fingers. 20 distances were extracted from each finger in both separate and closed finger images. A comparison was made between Manhattan distance and Euclidean distance for features extraction. The support vector machine (SVM) was used for classification. The result showed a better result for Euclidean distance with a false acceptance ratio (FAR) of 0.6 and a false rejection ratio (FRR) of 1.2.</span>
Moshood A. Hambali, Tinuke O. Oladele, Kayode S. Adewole, Arun Kumar Sangaiah, and Wei Gao
Springer Science and Business Media LLC
Kayode S. Adewole, Muiz O. Raheem, Oluwakemi C. Abikoye, Adeleke R. Ajiboye, Tinuke O. Oladele, Muhammed K. Jimoh, and Dayo R. Aremu
Springer International Publishing
Tinuke Omolewa Oladele, Roseline Oluwaseun Ogundokun, Adekanmi Adeyinka Adegun, Emmanuel Abidemi Adeniyi, and Ayobami Tayo Ajanaku
Institute of Advanced Engineering and Science
<span>Stores today still make use of manual approaches to keeping inventory which could be cumbersome. Having a computerized inventory system would make inventory management more efficient and effective. In this chapter, an Inventory Management System using Association Rule was developed which will ensure proper record keeping and keep items in stocks updated. ANGULARJS, a JavaScript framework, was used for the implementation of the system, PHP (hypertext pre-processor) was used for the backend of the system development as well as the database management, HTML was used alongside CSS for the system interface design and NoSQL database was the database used for this research. In conclusion, a computerized inventory system that had been improved using the Association Rule method was the resulting product useful for creating transactions, updating items in stock, record keeping, generating reports for decision making, and lastly, the system will make the stores more effective.</span>
Tinuke Omolewa Oladele, Roseline Oluwaseun Ogundokun, Sanjay Misra, Jide Kehinde Adeniyi, and Vivek Jaglan
IOP Publishing
Abstract Diagnosis takes a definitive role in the course of determining about clarifying patients as either having or not having the disorder. This method is relatively sluggish and tedious. Various fact-finding and data-mining methods are part of the approach of this article. In the development of the Collaborative Neuro-Fuzzy Expert System diagnosis platform, Neural Networks and Fuzzy Logic, which are artificial intelligence methods, have been merged together. Oral interviews were conducted with medical professionals whose experience was caught in the Expertise Developed Fuzzy Proficient Scheme. With Microsoft Visual C # (C Sharp) Programming Language and Microsoft SQL (Structured Query Language) Server 2012 to handle the database, the Neuro-Fuzzy Expert Framework diagnostic software was introduced. To capture the predominant signs, questionnaires were administered to the patients and filled out by the doctors on behalf of the patients.
Moshood A. Hambali, Tinuke O. Oladele, and Kayode S. Adewole
Elsevier BV
Jide Kehinde Adeniyi, Tinuke Omolewa Oladele, Noah Oluwatobi Akande, Roseline Oluwaseun Ogundokun, and Tunde Taiwo Adeniyi
Springer International Publishing
Tinuke Omolewa Oladele, Roseline Oluwaseun Ogundokun, Joseph Bamidele Awotunde, Marion Olubunmi Adebiyi, and Jide Kehinde Adeniyi
Springer International Publishing
Kayode Anthonia Aderonke, Akande Noah Oluwatobi, Saheed O Jabaru, and Oladele O Tinuke
International Association of Online Engineering (IAOE)
Today, Osteoarthritis remains the most prevalent chronic joint disease and a potentially incapacitating joint illness. It is an enduring health problem which cannot be cure though it can be managed. Osteoarthritis remains a serious public health problem because its burden is high, people who live with it have a greater risk of developing anxiety / or depression and if it is not properly managed, it can bring about disability as well as impairing quality of life. This paper presents a statistical correlation between the reported risk factors of Osteoarthritis and its prevalence in Nigeria. Statistical tests were performed to investigate if there is enough evidence for inferring that the risk factors for Osteoarthritis are true for the whole of Nigerian population
Roseline O. Ogundokun, Marion O. Adebiyi, Oluwakemi C. Abikoye, Tinuke O. Oladele, Adewale F. Lukman, Abidemi E. Adeniyi, Adekanmi A. Adegun, Babatunde Gbadamosi, and Noah O. Akande
F1000 Research Ltd
Cumulative grade point average (CGPA) is a system for calculation of GPA scores and is one way to determine a student's academic performance in a university setting. In Nigeria, an employer evaluates a student's academic performance using their CGPA score. For this study, data were collected from a student database of a private school in the south-west geopolitical zone in Nigeria. Regression analysis, correlation analysis, and analysis of variance (F-test) were employed to determine the study year that students perform better based on CGPA. According to the results, it was observed that students perform much better in year three (300 Level) and year four (400 Level) compared to other levels. In conclusion, we strongly recommend the private university to introduce program that will improve the academic performance of students from year one (100 level).
Adegun Adekanmi Adeyinka, Marion Olubunmi Adebiyi, Noah Oluwatobi Akande, Roseline Oluwaseun Ogundokun, Anthonia Aderonke Kayode, and Tinuke Omolewa Oladele
Springer International Publishing
Tinuke O. Oladele, Roseline Oluwaseun Ogundokun, Aderonke Anthonia Kayode, Adekanmi Adeyinka Adegun, and Marion Oluwabunmi Adebiyi
Springer International Publishing
O. D. Olorunfemi, F. O. Oladipo, T. O. Oladele, and O. I. Oladele
Academy of Science of South Africa
The paper examines the attitude of agricultural professionals towards their children or people under their care taking agriculture and agricultural extension as a career in Kwara State, Nigeria. A structured questionnaire was used to elicit information from one hundred and eighty respondents. The findings revealed that the mean age of the agricultural professionals was 39 years. Majority (76.1%) were males, married (86.1%) with about an average of 5 wards each under their custody. Majority of the professionals were observed to have a negative and unfavourable attitude towards their wards taking agriculture as a career. Logistical regression modelling of determinants of agricultural professionals’ attitudes towards their wards taking agriculture as a career revealed that characteristics of professionals that were more likely to have a positive attitude towards their wards taking agriculture as a career include high numbers of wards, higher educational qualification and more years of experience in the agricultural profession. The study recommends an urgent need for agricultural professionals to rise up to the task of ensuring increased participation of youths especially beginning with their wards in taking up a career in agriculture and agricultural extension. Keywords: Agricultural Professionals, attitude, career, agricultural extension
TajudeenO Oladele, AO Akinhanmi, PO Onifade, and NO Ibrahim
Medknow
Sir, The use of licit and illicit substances is a global phenomenon with a lot of adverse effects on physical and mental health. It also has a severe impact on the fabric of the society.[1] Commercial motorcyclists are vulnerable to psychoactive substance use often to their detriment in terms of health hazards and the safety of the commuters.[2] The study aims to describe the prevalence, sociodemographic characteristics, social consequences of alcohol and substance use behaviors, and associated health and psychological sequelae.