Adesesan . B Adeyemo

University of Ibadan · Department of Computer Science

Network threats can be classified into major network threats and minor network threats. Minor network threats are the network threats that have little or no negative impacts on information systems. Existing Information Security Management processes have ignored minor network threats because of the perception that they were non-harmful. However, rec...

The causes of the difference in the academic performance of students in tertiary institutions has for a long time been the focus of study among higher education managers, parents, government and researchers. The cause of this differential can be due to intellective, non-intellective factors or both. From studies investigating student performance an...

Purpose Collaborative-based national cybersecurity incident management benefits from the huge size of incident information, large-scale information security devices and aggregation of security skills. However, no existing collaborative approach has been able to cater for multiple regulators, divergent incident views and incident reputation trust is...

Recommender system is a type of information filtering system that is designed to curtail the difficulties of information overload by automatically suggesting relevant items to users tailored to their preferences. Bayesian personalised smart linear methods (BPRSLIM) is a variant of item-based collaborative filtering technique used in information fil...

Recommender system is a type of information filtering system that is designed to curtail the difficulties of information overload by automatically suggesting relevant items to users tailored to their preferences. Bayesian personalised smart linear methods (BPRSLIM) is a variant of item-based collaborative filtering technique used in information fil...

In this study, a predictive model using Multi-layer Perceptron of Artificial Neural Network architecture was developed to predict customer churn in a financial institution. Previous researches have used supervised machine learning classifiers such as Logistic Regression, Decision Tree, Support Vector Machine, K-Nearest Neighbors, and Random Forest....

In this study, a predictive model using Multi-layer Perceptron of Artificial Neural Network architecture was developed to predict customer churn in a financial institution. Previous researches have used supervised machine learning classifiers such as Logistic Regression, Decision Tree, Support Vector Machine, K-Nearest Neighbors, and Random Forest....

In Threat Modelling, Threat Prioritization is used to rate and rank threats according to the significances of their negative impacts on system assets. The low-significant threats are known as Major Threats, while the high-significant threats are known as Minor Threats. Existing works on Threat Management have concentrated on combating the Major Thr...

Industrial pollution is often considered to be one of the prime factors contributing to air, water and soil pollution. Sectoral pollution loads (ton/yr) into different media (i.e. air, water and land) in Lagos were estimated using Industrial Pollution Projected System (IPPS). These were further studied using Artificial neural Networks (ANNs), a dat...

As markets have become increasingly saturated, companies have acknowledged that their business strategies need to focus on identifying those customers who are most likely to churn. It is becoming common knowledge in business, that retaining existing customers is the best core marketing strategy to survive in industry. In this research, both descrip...

Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall, evaporation and wind speed. This was carried out using Arti...

Identifying customers who are more likely to respond to new product offers is an important issue in direct marketing. In direct marketing, data mining has been used extensively to identify potential customers for a new product (target selection). Using historical purchase data, a predictive response model with data mining techniques was developed t...

Nigeria is a country that has always posed a paradox to the international community in terms of its level of development vis-a-vis its economic potential. This is also reflected in the low ranking index it gets in international surveys despite the effort to develop its infrastructure and human capital. Nigeria has the fastest growing and most lucra...

This paper applies forensic data mining to determine the true status of employees and thereafter provide useful evidences for proper administration of administrative rules in a Typical Nigerian Teaching Service. The conventional technique of personnel audit was studied and a new technique for personnel audit was modeled using Artificial Neural Netw...

In this paper we present an evaluation of the factors that contribute to the academic performance of students admitted into the university. The variables of interest are the entry qualification and admission mode and how these factors affect the academic performance of the students. The evaluation was carried out using computer software that implem...

The detection of hydrocarbon content from geophysical data has always been an important practical issue in the interpretation of geophysical oil prospecting data. This paper reviews the literature on well log lithology and neuron-computing technology. An Unsupervised Self Organizing Map (SOM) of neural networks for the determination of oil well lit...

In the last few years open source software products have become mature alternatives to commercially developed software and systems but do not seem to be a viable commercial option for leading software vendors because of its freely available source code. However, market trends seem to paint a different picture. While open source software has matured...