Rafiu Mope Isiaka- P.hD (Computer Science)
- Managing Director at Kwara State University
Rafiu Mope Isiaka
- P.hD (Computer Science)
- Managing Director at Kwara State University
About
31
Publications
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Publications
Publications (31)
Class-imbalanced learning presents critical challenges in machine learning, largely because data in most domains are naturally imbalanced. Although resampling techniques have been widely applied to address this issue, their effectiveness has been inconsistent and sometimes flawed, owing to artificial assumptions. In this study, we move beyond hype...
Accurate classification of fecal images offers a non-invasive, scalable method for diagnosing enteric diseases such as Coccidiosis, Salmonellosis, and Newcastle disease, overcoming limitations associated with traditional diagnostic approaches that are often time-intensive, costly, and reliant on expert interpretation. This study presents the develo...
The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway is a crucial regulator of cellular metabolism, proliferation, and survival. It is frequently dysregulated in metabolic, cardiovascular, and neoplastic disorders. Despite the advancements in multi-omics technology, existing methods often fail to provide real-time, pathway-specific insights f...
The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway is a crucial regulator of cellular metabolism, proliferation, and survival. It is frequently dysregulated in metabolic, cardiovascular, and neoplastic disorders. Despite the advancements in multi-omics technology, existing methods often fail to provide real-time, pathway-specific insights f...
The abundance of data obtained from microarray experiments presents challenges related to the number of variables and the presence of random fluctuations. Despite the efforts that had been made by previous researchers, emphasizing how data mining aids the implementation of models to facilitate informed prediction, gaps are evident which requires im...
Image restoration plays a vital role in image processing and pattern recognition in producing better recognition accuracy. It was observed that, most of the traditional restoration algorithms were meant for removing a single type of noise and efforts have been made towards the use of partial differential equation model (PDE), to restore different t...
Artificial Intelligence (AI) technologies, including cognitive computing, machine learning (ML), and deep learning (DL), have the potential to transform healthcare. They enhance patient care, improve symptom differentiation, address medication adherence issues, and facilitate continuous patient support. AI's promise in electronic health records (EH...
Pelican Optimization Algorithm-based Convolutional Neural Network (POA-CNN) method for the automated identification of pulmonary disorders such as COVID-19 and pneumonia is proposed in this research. The method makes use of several processing layers in order to comprehend the representation of stratified data. The three primary phases of the model...
An enhanced mobile deep learning model based on images is presented in this paper to identify Newcastle poultry disease. A dataset of manually annotated and labeled images of the disease was utilized to pre-train an image-based Convolutional Neural Network (CNN). An Android smartphone app was developed to communicate with the model. A local server...
Different encryption algorithms such as Advanced Encryption Standard (AES), Rivest, Shamir, Adleman (RSA) were proposed to protect the privacy of the data. However, most of these existing methods are vulnerable to a brute-force attack because the cipher text remains unintelligible until the original data is found. Consequently, this problem prompte...
Document recognition is required to convert handwritten and text documents into digital equivalents, making them more easily accessible and convenient to store. This study combined feature extraction techniques for recognizing Yorùbá documents in an effort to preserve the cultural values and heritages of the Yorùbá people. Ten Yorùbá documents were...
In preserving individual privacy in data publishing, several efforts have been made by scholars globally to develop an individual privacy preserving model and hybridized models which harness the strength of the individual model to increase privacy preservation in data Publishing (PPDP). The Differential homomorphic model (DHM) was among the hybridi...
Intrusion detection is extremely important for online applications and for determining whether there has been a hostile entrance into the website. The aim of this research is to provide a machine learning technique for detecting intrusion in a web application. Machine learning models such as C-means, Decision Tree and Support Vector Machine were ut...
Network intrusion, such as denial of service, probing attacks, and phishing, comprises some of the complex threats that have put the online community at risk. The increase in the number of these attacks has given rise to a serious interest in the research community to curb the menace. One of the research efforts is to have an intrusion detection me...
Following the identification of Coronavirus Disease 2019 (COVID-19) in Wuhan, China in December 2019, AI researchers have teamed up with a health specialist to combat the virus. This study explores the medical and non-medical areas of COVID-19 that AI has impacted: the prevalence of the AI technologies adopted across all stages of the pandemic, the...
Fully Homomorphic Encryption (FHE) supports realistic computations on encrypted data and hence it is widely proposed to be used in cloud computing to protect the integrity and privacy of data stored in the cloud. The existing symmetric-based FHE schemes suffer from insecurity against known plaintext/ciphertext attacks and generate a large ciphertex...
Aims: This work aim is to develop an enhanced predictive system for Coronary Heart Disease (CHD). Study Design: Synthetic Minority Oversampling Technique and Random Forest. Methodology: The Framingham heart disease dataset was used, which was collected from a study in Framingham, Massachusetts, the data was cleaned, normalized, rebalanced. Classifi...
Encryption schemes that allow computation to be performed on an encrypted data are required in modern real-world applications. This technology is a necessity for cloud computing, processing resources and share storage, in order to preserve integrity and privacy of data. The existing partial and fully homomorphic encryption (PHE and FHE) for both as...
span>Support Vector Machine (SVM) is currently an efficient classification technique due to its ability to capture nonlinearities in diagnostic systems, but it does not reveal the knowledge learnt during training. It is important to understand of how a decision is reached in the machine learning technology, such as bioinformatics. On the other hand...
Feature extraction is a proficient method for reducing dimensions in the analysis and prediction of cancer classification. Microarray procedure has shown great importance in fetching informative genes th at needs enhancement in diagnosis. Microarray data is a challenging task due to high dimensional-low sample dataset with a lot of noisy or irrelev...
Purpose: The purpose of this research is to apply
ant colony optimization (ACO), a nature inspired
computational (NIC) technique to achieve optimal
feature subset selection, for the purpose of data
dimensionality reduction, which will remove
redundancy, provide a reduced storage space,
improve memory utilization and subsequently,
classification tas...
Efficient e-learners activities model is essential for real time identifications and adaptive responses. Determining the most effective Neuro-Fuzzy model amidst plethora of techniques for structure and parameter identifications is a challenge. This paper illustrates the implication of system identification techniques on the performance of Adaptive...
Instructional design (ID) models are proven prescriptive techniques for qualitative lessons that could guarantee learning. Existing Learning Management Systems (LMS) miss-out the roles of this important quality control mechanism by providing a mere plane and passive platform for content authoring, thus becomes vulnerable for poor instructional desi...
The intent of this paper is to determine the extent to which fuzzy model could suitably modelled learner activities in E-learning system. However, the paucity of public dataset that meet the exact requirement of this work poses challenges, which necessitate dataset simulation. The detail approach used for the dataset simulation and the fuzzy model...
Short Message Service (SMS) is the most powerful tool in terms of communication especially for mobile users. It does not limit anyone regardless of high- or low-end mobile phones for as long as they can receive and send messages anytime, anywhere. It was revealed that, lack of adequate communication technology in an organization leads to a number o...
The development of network technologies and application has promoted network attack both in number and severity. The last few years have seen a dramatic increase in the number of attacks, hence, intrusion detection has become the mainstream of information assurance. A computer network system should provide confidentiality, integrity and assurance a...
![Fig 1: Key elements of an e-Governance Architecture Adapted from [10].](profile/Adewole-S/publication/277411310/figure/fig1/AS:651864592896000@1532428038018/Key-elements-of-an-e-Governance-Architecture-Adapted-from-10_Q320.jpg)
![Fig 2: Input to Output Fuzzification process adapted from [21].](profile/Adewole-S/publication/277411310/figure/fig2/AS:651864592887808@1532428038123/nput-to-Output-Fuzzification-process-adapted-from-21_Q320.jpg)
Information and communication technology (ICT) has become one of the core elements of managerial reform for creating the best efficiency and comparative advantages. However, the entire citizens both in the developed and developing countries are still facing a critical issue concerning what criteria should be used for evaluating and assessing the su...
Questions
Questions (2)
Because of the challenges with the quality of internet access in this part of the world, it is essential to develop an offline e-learning system that can sychronise learners offline activities with the online version when the next internet connection is made. SCORM and IMS LD are packaging techniques with online servers. Is it possible to play the lesson offline and synchronize data?
Learner's extent of courseware exploration (quantitatively and qualitatively) need to be determined in this research for adaptiveness and administrative actions.
