University of Ilorin, Nigeria

EDUCATION

Ph.D. Statistics

RESEARCH, TEACHING, or OTHER INTERESTS

Statistics and Probability, Economics and Econometrics, General Energy

Scopus Publications

Affective e-learning approaches, technology and implementation model: A systematic review
Marion Olubunmi Adebiyi, Abayomi Aduragba Adebiyi, Deborah Olaniyan, and Bajeh Amos Orenyi
Institute of Advanced Engineering and Science
A systematic literature study including articles from 2016 to 2022 was done to evaluate the various approaches, technologies, and implementation models involved in measuring student engagement during learning. The review’s objective was to compile and analyze all studies that investigated how instructors can gauge students’ mental states while teaching and assess the most effective teaching methods. Additionally, it aims to extract and assess expanded methodologies from chosen research publications to offer suggestions and answers to researchers and practitioners. Planning, carrying out the analysis, and publishing the results have all received significant attention in the research approach. The study’s findings indicate that more needs to be done to evaluate student participation objectively and follow their development for improved academic performance. Physiological approaches should be given more support among the alternatives. While deep learning implementation models and contactless technology should interest more researchers. And, the recommender system should be integrated into e-learning system. Other approaches, technologies, and methodology articles, on the other hand, lacked authenticity in conveying student feeling.


Comparative Analysis of Feature Selection Methods for Software Bug Classification
Bajeh Amos Orenyi, Olowe Oluwambo Tolulope, and Asani Emmanuel Tobi
IEEE
Software bug classification is a critical task in software engineering aimed at identifying defects early to improve software quality and reliability. Despite its importance, effectively classifying software defects remains a challenge, necessitating the use of advanced techniques such as feature selection. This research presents a comprehensive study on feature selection methods for software defect classification, to evaluate their effectiveness in enhancing classification accuracy. The study investigates the impact of feature selection methods (filter-based, wrapper-based, and embedding) on model performance using classification algorithms such Naïve Bayes, Support Vector Machines, K-Nearest Neighbour, and Random Forest. The studies are carried out using publicly accessible software defect datasets, and conventional evaluation measures such as accuracy, precision, recall, and F1-score are used to evaluate the effectiveness of each feature selection strategy. The findings of the study confirm the effectiveness of ensemble methods in bug severity classification, with Random Forest achieving notable accuracy rates for different datasets. Additionally, the study highlights the superiority of wrapper feature selection techniques over filter methods, demonstrating their ability to select informative features for defect severity classification. The findings of this work give useful information for practitioners in selecting and implementing feature selection approaches when developing defect classification models, ultimately contributing to the enhancement of software quality and reliability.


Strengthening Bioinformatics and Genomics Analysis Skills in Africa for Attainment of the Sustainable Development Goals: Report of the 2nd Conference of the Nigerian Bioinformatics and Genomics Network
Itunuoluwa Isewon, Chisom Soremekun, Marion Adebiyi, Charles Adetunji, Adewale Joseph Ogunleye, Amos Orenyi Bajeh, Emmanuel Oluwatobi Asani, Babatunde Gbadamosi, Opeyemi Soremekun, Brenda Udosen,et al.
American Society of Tropical Medicine and Hygiene
ABSTRACT. The second conference of the Nigerian Bioinformatics and Genomics Network (NBGN21) was held from October 11 to October 13, 2021. The event was organized by the Nigerian Bioinformatics and Genomics Network. A 1-day genomic analysis workshop on genome-wide association study and polygenic risk score analysis was organized as part of the conference. It was organized primarily as a research capacity building initiative to empower Nigerian researchers to take a leading role in this cutting-edge field of genomic data science. The theme of the conference was “Leveraging Bioinformatics and Genomics for the attainments of the Sustainable Development Goals.” The conference used a hybrid approach—virtual and in-person. It served as a platform to bring together 235 registered participants mainly from Nigeria and virtually, from all over the world. NBGN21 had four keynote speakers and four leading Nigerian scientists received awards for their contributions to genomics and bioinformatics development in Nigeria. A total of 100 travel fellowships were awarded to delegates within Nigeria. A major topic of discussion was the application of bioinformatics and genomics in the achievement of the Sustainable Development Goals (SDG3—Good Health and Well-Being, SDG4—Quality Education, and SDG 15—Life on Land [Biodiversity]). In closing, most of the NBGN21 conference participants were interviewed and interestingly they agreed that bioinformatics and genomic analysis of African genomes are vital in identifying population-specific genetic variants that confer susceptibility to different diseases that are endemic in Africa. The knowledge of this can empower African healthcare systems and governments for timely intervention, thereby enhancing good health and well-being.


Empirical Analysis of Data Sampling-Based Ensemble Methods in Software Defect Prediction
Abdullateef O. Balogun, Babajide J. Odejide, Amos O. Bajeh, Zubair O. Alanamu, Fatima E. Usman-Hamza, Hammid O. Adeleke, Modinat A. Mabayoje, and Shakirat R. Yusuff
Springer International Publishing



An Empirical Study on Data Sampling Methods in Addressing Class Imbalance Problem in Software Defect Prediction
Babajide J. Odejide, Amos O. Bajeh, Abdullateef O. Balogun, Zubair O. Alanamu, Kayode S. Adewole, Abimbola G. Akintola, Shakirat A. Salihu, Fatima E. Usman-Hamza, and Hammed A. Mojeed
Springer International Publishing



An Integrated IDS Using ICA-Based Feature Selection and SVM Classification Method
Roseline Oluwaseun Ogundokun, Sanjay Misra, Amos O. Bajeh, Ufuoma Odomero Okoro, and Ravin Ahuja
Springer International Publishing



Software defect prediction using wrapper feature selection based on dynamic re-reranking strategy
Abdullateef Oluwagbemiga Balogun, Shuib Basri, Luiz Fernando Capretz, Saipunidzam Mahamad, Abdullahi Abubakar Imam, Malek A. Almomani, Victor Elijah Adeyemo, Ammar K. Alazzawi, Amos Orenyi Bajeh, and Ganesh Kumar
MDPI AG
Finding defects early in a software system is a crucial task, as it creates adequate time for fixing such defects using available resources. Strategies such as symmetric testing have proven useful; however, its inability in differentiating incorrect implementations from correct ones is a drawback. Software defect prediction (SDP) is another feasible method that can be used for detecting defects early. Additionally, high dimensionality, a data quality problem, has a detrimental effect on the predictive capability of SDP models. Feature selection (FS) has been used as a feasible solution for solving the high dimensionality issue in SDP. According to current literature, the two basic forms of FS approaches are filter-based feature selection (FFS) and wrapper-based feature selection (WFS). Between the two, WFS approaches have been deemed to be superior. However, WFS methods have a high computational cost due to the unknown number of executions available for feature subset search, evaluation, and selection. This characteristic of WFS often leads to overfitting of classifier models due to its easy trapping in local maxima. The trapping of the WFS subset evaluator in local maxima can be overcome by using an effective search method in the evaluator process. Hence, this study proposes an enhanced WFS method that dynamically and iteratively selects features. The proposed enhanced WFS (EWFS) method is based on incrementally selecting features while considering previously selected features in its search space. The novelty of EWFS is based on the enhancement of the subset evaluation process of WFS methods by deploying a dynamic re-ranking strategy that iteratively selects germane features with a low subset evaluation cycle while not compromising the prediction performance of the ensuing model. For evaluation, EWFS was deployed with Decision Tree (DT) and Naïve Bayes classifiers on software defect datasets with varying granularities. The experimental findings revealed that EWFS outperformed existing metaheuristics and sequential search-based WFS approaches established in this work. Additionally, EWFS selected fewer features with less computational time as compared with existing metaheuristics and sequential search-based WFS methods.


Ensemble models for predicting warts treatment methods




Cascade Generalization Based Functional Tree for Website Phishing Detection
Abdullateef O. Balogun, Kayode S. Adewole, Amos O. Bajeh, and Rasheed G. Jimoh
Springer Singapore



Optimized Decision Forest for Website Phishing Detection
Abdullateef O. Balogun, Hammed A. Mojeed, Kayode S. Adewole, Abimbola G. Akintola, Shakirat A. Salihu, Amos O. Bajeh, and Rasheed G. Jimoh
Springer International Publishing



Heterogeneous Ensemble with Combined Dimensionality Reduction for Social Spam Detection
Abdulfatai Ganiyu Oladepo, Amos Orenyi Bajeh, Abdullateef Oluwagbemiga Balogun, Hammed Adeleye Mojeed, Abdulsalam Abiodun Salman, and Abdullateef Iyanda Bako
International Association of Online Engineering (IAOE)
This study presents a novel framework based on a heterogeneous ensemble method and a hybrid dimensionality reduction technique for spam detection in micro-blogging social networks. A hybrid of Information Gain (IG) and Principal Component Analysis (PCA) (dimensionality reduction) was implemented for the selection of important features and a heterogeneous ensemble consisting of Naïve Bayes (NB), K Nearest Neighbor (KNN), Logistic Regression (LR) and Repeated Incremental Pruning to Produce Error Reduction (RIPPER) classifiers based on Average of Probabilities (AOP) was used for spam detection. The proposed framework was applied on MPI_SWS and SAC’13 Tip spam datasets and the developed models were evaluated based on accuracy, precision, recall, f-measure, and area under the curve (AUC). From the experimental results, the proposed framework (that is, Ensemble + IG + PCA) outperformed other experimented methods on studied spam datasets. Specifically, the proposed method had an average accuracy value of 87.5%, an average precision score of 0.877, an average recall value of 0.845, an average F-measure value of 0.872 and an average AUC value of 0.943. Also, the proposed method had better performance than some existing methods. Consequently, this study has shown that addressing high dimensionality in spam datasets, in this case, a hybrid of IG and PCA with a heterogeneous ensemble method can produce a more effective method for detecting spam contents.


Data Sampling-Based Feature Selection Framework for Software Defect Prediction
Abdullateef O. Balogun, Fatimah B. Lafenwa-Balogun, Hammed A. Mojeed, Fatimah E. Usman-Hamza, Amos O. Bajeh, Victor E. Adeyemo, Kayode S. Adewole, and Rasheed G. Jimoh
Springer International Publishing



Application of Internet of Thing and Cyber Physical System in Industry 4.0 Smart Manufacturing
Oluwakemi Christiana Abikoye, Amos Orenyi Bajeh, Joseph Bamidele Awotunde, Ahmed Oloduowo Ameen, Hammed Adeleye Mojeed, Muyideen Abdulraheem, Idowu Dauda Oladipo, and Shakirat Aderonke Salihu
Springer International Publishing



Internet of Robotic Things: Its Domain, Methodologies, and Applications
Amos Orenyi Bajeh, Hammed Adeleye Mojeed, Ahmed Oloduowo Ameen, Oluwakemi Christiana Abikoye, Shakirat Aderonke Salihu, Muyideen Abdulraheem, Idowu Dauda Oladipo, and Joseph Bamidele Awotunde
Springer International Publishing



Exploring the Constructive Alignment of Pedagogical Practices in Science and Engineering Education in Sub-Saharan African Universities: A Nigerian Case Study
David Olubiyi Obada, Olayinka Adewumi, Chika Yinka-Banjo, Amos Bajeh, and Razak Alli-Oke
International Association of Online Engineering (IAOE)
Improved pedagogical approaches in teaching science and engineering are crucial to solving the most pressing technological challenges faced in most developing countries. Despite the avalanche of programs to train faculty members to fill this need, there is a need to conceptualize benchmarks for evaluating how teaching should be delivered to students in our institutions. The aim of this paper is to understand how science and engineering courses can be taught in a more effective manner in our universities, especially in developing countries, using the backward design approach. Several case studies of undergraduate science and engineering courses were outlined and the backward design approach was used to put them in context. Questions generated by the conceptual framework guided the analyses and these components constructively aligned with each other.


Impact of feature selection methods on the predictive performance of software defect prediction models: An extensive empirical study
Abdullateef O. Balogun, Shuib Basri, Saipunidzam Mahamad, Said J. Abdulkadir, Malek A. Almomani, Victor E. Adeyemo, Qasem Al-Tashi, Hammed A. Mojeed, Abdullahi A. Imam, and Amos O. Bajeh
MDPI AG
Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and many FS methods have been proposed in the context of software defect prediction (SDP). Moreover, many empirical studies on the impact and effectiveness of FS methods on SDP models often lead to contradictory experimental results and inconsistent findings. These contradictions can be attributed to relative study limitations such as small datasets, limited FS search methods, and unsuitable prediction models in the respective scope of studies. It is hence critical to conduct an extensive empirical study to address these contradictions to guide researchers and buttress the scientific tenacity of experimental conclusions. In this study, we investigated the impact of 46 FS methods using Naïve Bayes and Decision Tree classifiers over 25 software defect datasets from 4 software repositories (NASA, PROMISE, ReLink, and AEEEM). The ensuing prediction models were evaluated based on accuracy and AUC values. Scott–KnottESD and the novel Double Scott–KnottESD rank statistical methods were used for statistical ranking of the studied FS methods. The experimental results showed that there is no one best FS method as their respective performances depends on the choice of classifiers, performance evaluation metrics, and dataset. However, we recommend the use of statistical-based, probability-based, and classifier-based filter feature ranking (FFR) methods, respectively, in SDP. For filter subset selection (FSS) methods, correlation-based feature selection (CFS) with metaheuristic search methods is recommended. For wrapper feature selection (WFS) methods, the IWSS-based WFS method is recommended as it outperforms the conventional SFS and LHS-based WFS methods.


Object-oriented measures as testability indicators: An empirical study




Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
Amos Orenyi Bajeh, Oluwakemi Christiana Abikoye, Hammed Adeleye Mojeed, Shakirat Aderonke Salihu, Idowu Dauda Oladipo, Muyideen Abdulraheem, Joseph Bamidele Awotunde, Arun Kumar Sangaiah, and Kayode S. Adewole
Elsevier



An Approach for Journal Summarization Using Clustering Based Micro-Summary Generation
Hammed A. Mojeed, Ummu Sanoh, Shakirat A. Salihu, Abdullateef O. Balogun, Amos O. Bajeh, Abimbola G. Akintola, Modinat A. Mabayoje, and Fatimah E. Usman-Hamzah
Springer International Publishing



SMOTE-Based Homogeneous Ensemble Methods for Software Defect Prediction
Abdullateef O. Balogun, Fatimah B. Lafenwa-Balogun, Hammed A. Mojeed, Victor E. Adeyemo, Oluwatobi N. Akande, Abimbola G. Akintola, Amos O. Bajeh, and Fatimah E. Usman-Hamza
Springer International Publishing



Search-Based Wrapper Feature Selection Methods in Software Defect Prediction: An Empirical Analysis
Abdullateef O. Balogun, Shuib Basri, Said A. Jadid, Saipunidzam Mahamad, Malek A. Al-momani, Amos O. Bajeh, and Ammar K. Alazzawi
Springer International Publishing



Memetic approach for multi-objective overtime planning in software engineering projects




Software defect prediction: Analysis of class imbalance and performance stability




Software development practices and problems in Malaysian small and medium software enterprises: A pilot study
Malek Ahmad Theeb Almomani, Shuib Basri, Ahmad Kamil B. Mahmood, and Amos Orenyi Bajeh
IEEE
This paper presents an empirical study that investigates Software Process Improvement (SPI) current practices amongst software development Small and Medium Enterprises (SMEs) in Malaysia. The empirical study determines the current practices of adoption of SPI and related problems. Six Malaysian software development SMEs were involved in the empirical study. The results of the study showed that the level of adoption of Software Process Improvement in Malaysian software development SMEs is still very much at the low level. Other organisational, software development and project issues were identified as contributing to the low level of SPI adoption in Malaysia.


An empirical validation of coupling and cohesion metrics as testability indicators
Amos Orenyi Bajeh, Shuib Basri, and Low Tang Jung
Springer Berlin Heidelberg

RECENT SCHOLAR PUBLICATIONS

BAYESIAN NON-INFERIORITY TEST BETWEEN TWO BINOMIAL PROPORTIONS
WB Yahya, CP Ezenweke, OR Olaniran, IA Adeniyi, K Jimoh, RB Afolayan, ...
Reliability: Theory & Applications 19 (3 (79)), 689-703 2024



Investigation on Determinants and Choice of Contraceptive Usage among Nigeria Women of Reproductive Age
AW Banjoko, WB Yahya, MK Garba, RB Afolayan, KA Dauda, ...
Journal of Biostatistics and Epidemiology 9 (1), 35-50 2023



The nexus between foreign aid and foreign direct investment in Nigeria: simultaneous equations approach
MK Garba, SB Akanni, AW Banjoko, TC Oladele
Malaysian Journal of Computing (MJoC) 8 (2), 1620-1638 2023



Modelling of Post-COVID-19 Food Production Index in Nigeria using Box-Jenkins Methodology
MK Garba, SB Akanni, KY Kareem, AA Yusuf, SO Jabaru, JS Abolarin, ...
2023



Effects of Foreign Direct Investment on Economic Growth: Evidence from Nigeria and Rwanda
RB Garba, MK, Sikiru, AO, Banjok, AW and Afolayan
Kabale University Interdisciplinary Research Journal (KURJ) 1 (4), 67 - 78 2022



Modelling determinants of antenatal care services utilization in Nigeria
AW Banjoko, MK Garba, RB Afolayan, NF Gatta
Kabale University Interdisciplinary Research Journal 1 (4), 4-13 2022



Assessment of the impacts of oil prices on nigeria economy using COBB-douglas production function
G Mohammed Kabir, SA Omotayo
Malaysian Journal of Computing (MJoC) 7 (1), 938-951 2022



Modelling Effects of some Factors that Contribute to Cereals Yields in Nigeria using Toda-Yamamoto Techniques
MK Garba, SB Akanni, WB Yahya, KY Kareem, RB Afolayan
SLU Journal of Science and Technology 1 (1), 50-56 2020



On Seemingly Unrelated Regression and Single Equation Estimators under Heteroscedastic Error and NonGaussian Responses
RB Afolayan, AW Banjoko, MK Garba, WB Yahya
FUOYE Journal of Engineering and Technology 5 (2) 2020



On the use of Linear Programming Model Approach in Profit Optimization of a Product Mix Company
MK Garba, AW Banjoko, WB Yahya, NF Gatta
Islamic University Multidisciplinary Journal (IUMJ). 7(2) 7 (2), 299 – 305 2020



Econometric analysis of the effects of land size on cereals production in Nigeria
SB Akanni, M Garba, A Banjoko, R Afolayan
Islamic University Multidisciplinary Journal 2020



Weighted support vector machine algorithm for efficient classification and prediction of binary response data.
AW Banjoko, WB Yahya, MK Garba, KO Abdulazeez
Journal of Physics: Conference Series (ICoAIMS 2019) 136, 1 - 7 2019



Applications of some Exponential Related Distributions
WB Umar, M. A., Jimoh, J. O., Garba, M. K., Afolayan, R. B. and Yahya
Edited Proceedings of the Professional Statisticians Society of Nigeria 2019



Multiclass response feature selection and cancer tumour classification with support vector machine
AW Banjoko, WB Yahya, MK Garba
Journal of Biostatistics and Epidemiology 5 (2), 91-104 2019



Robust Regression Methods for Solving Non-Spherical Problem in Linear Regression
NF Gatta, WB Yahya, MK Garba
Sretech Journal Publications 2019



ON THE STRENGTH OF AGREEMENT BETWEEN INITIAL AND FINAL ACADEMIC PERFORMANCES OF STUDENTS IN A NIGERIA UNIVERSITY SYSTEM
AW Banjoko, WB Yahya, HS Abiodun, RB Afolayan, MK Garba, ...
ABACUS (Mathematics Science Series) 45 (1) 2018



On the Strength of Agreement between Initial and Final Academic performances in a Nigerian University System
A Banjoko, W Yahya, HS Abiodun, R Afolayan, M Garba, KO Olorede, ...
ABACUS, Mathematical Association of Nigeria 2018



Structural Relationships of Exchange Rates of Naira to Some Foreign Currencies
MK Garba, WB Yahya, HT Babaita, AW Banjoko, AQ Amobi
Edited Conference Proceedings of the 1st International Conference of the 2017



Environmental pollution potential of tannery sludge from challawa industrial area of Kano State, Nigeria
M Garba, M Mohammed
IOSR J Appl Chem (IOSR-JAC [Internet] 10 (7), 28-34 2017



Modeling structural relationships of exchange rates, of Naira to foreign currencies
MK Garba, WB Yahya, HT Babaita, AW Bankooko, AQ Amobi
Nigerian Statistical Society 1, 41-47 2017

MOST CITED SCHOLAR PUBLICATIONS

Profit Maximization in a product mix company using linear programming
WB Yahya, MK Garba, AE Ige, S. O. and Adeyosoye
European Journal of Business and Management 4 (17), 126-131 2012
Citations: 37



Investigations of certain estimators for modelling panel data under violations of some basic assumptions
MK Garba, BA Oyejola, WB Yahya
Mathematical Theory and Modeling 3 (10), 47-53 2013
Citations: 21



Efficient Support Vector Machine Classification of Diffuse Large B-Cell Lymphoma and Follicular Lymphoma mRNA Tissue Samples
AW Banjoko, WB Yahya, MK Garba, OR Olaniran, KA Dauda, KO Olorede
Annals Computer Science Series 13 (2), 69-79 2015
Citations: 15



Compact Fluorescent Lamps and Electricity Consumption Trend in Residential Building in Ilorin, Nigeria
BF Sule, KR Ajao, HA Ajimotokan, MK Garba
International Journal of Energy Sector Management 5 (2), 162-168 2011
Citations: 15



Improved Bayesian feature selection and classification methods using bootstrap prior techniques
OR Olaniran, SF Olaniran, WB Yahya, AW Banjoko, MK Garba, LB Amusa, ...
Faculty of Computer and Applied Computer Science, Tibiscus University of 2016
Citations: 13



Weighted support vector machine algorithm for efficient classification and prediction of binary response data.
AW Banjoko, WB Yahya, MK Garba, KO Abdulazeez
Journal of Physics: Conference Series (ICoAIMS 2019) 136, 1 - 7 2019
Citations: 12



Empirical Comparison of the Kruskal Wallis Statistic and its Parametric Counterpart
OA Samuel, E Gayawan, MK Garba
Journal of Modern Mathematics and Statistics, Pakistan 3 (2), 38-42 2009
Citations: 10



Multiclass Sequential Feature Selection and Classification Method for Gene Expression Data
WB Yahya, GT Aremu, MK Garba
Journal of Applied Science and Technology (JAST) 20 (1 & 2), 50-61 2015
Citations: 8



On the use of Linear Programming Model Approach in Profit Optimization of a Product Mix Company
MK Garba, AW Banjoko, WB Yahya, NF Gatta
Islamic University Multidisciplinary Journal (IUMJ). 7(2) 7 (2), 299 – 305 2020
Citations: 6



Multiclass response feature selection and cancer tumour classification with support vector machine
AW Banjoko, WB Yahya, MK Garba
Journal of Biostatistics and Epidemiology 5 (2), 91-104 2019
Citations: 6



Determinants of customers’ bank selection decision in North Eastern Nigeria (Evidence from Bauchi State)
M Garba, L Garba, A Usman
Nigerian Journal of Management Technology & Development 8 (1), 154-162 2017
Citations: 5



On Seemingly Unrelated Regression and Single Equation Estimators under Heteroscedastic Error and NonGaussian Responses
RB Afolayan, AW Banjoko, MK Garba, WB Yahya
FUOYE Journal of Engineering and Technology 5 (2) 2020
Citations: 4



Econometric analysis of the effects of land size on cereals production in Nigeria
SB Akanni, M Garba, A Banjoko, R Afolayan
Islamic University Multidisciplinary Journal 2020
Citations: 4



Pembuktian Kasus Malpraktek Di Indonesia
L Nadriana
Lex Publica 2 (1), 239-254 2015
Citations: 4



The nexus between foreign aid and foreign direct investment in Nigeria: simultaneous equations approach
MK Garba, SB Akanni, AW Banjoko, TC Oladele
Malaysian Journal of Computing (MJoC) 8 (2), 1620-1638 2023
Citations: 3



Modelling Effects of some Factors that Contribute to Cereals Yields in Nigeria using Toda-Yamamoto Techniques
MK Garba, SB Akanni, WB Yahya, KY Kareem, RB Afolayan
SLU Journal of Science and Technology 1 (1), 50-56 2020
Citations: 3



Modeling structural relationships of exchange rates, of Naira to foreign currencies
MK Garba, WB Yahya, HT Babaita, AW Bankooko, AQ Amobi
Nigerian Statistical Society 1, 41-47 2017
Citations: 3



Assessment of the impacts of oil prices on nigeria economy using COBB-douglas production function
G Mohammed Kabir, SA Omotayo
Malaysian Journal of Computing (MJoC) 7 (1), 938-951 2022
Citations: 2



Probabilistic Analysis of Peak Daily Rainfall for Prediction Purposes in Selected Areas of Northern Nigeria
AW Salami, AS Aremu, AM Ayanshola, TS Abdulkadir, MK Garba
Nigerian Journal of Technological Research (NJTR) 11 (1), 54-59 2016
Citations: 2



A Test Procedure for Ordered Hypothesis of Population Proportions Against a Control.
WB Yahya, OR Olaniran, MK Garba, I Oloyede, AW Banjoko, KA Dauda, ...
Turkiye Klinikleri Journal of Biostatistics 8 (1) 2016
Citations: 2