Mathematics and Computer Science

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A Cancelable Biometric Based Security Protocol for Online Banking System
(International Journal of Computer Science and Information Security, 2020-06) Tom, Joshua J.; Alese, Boniface K.; Thompson, Aderonke F.
The internet revolution has brought significant benefits to humanity. Undeniably, most businesses in both the public and private sectors now provide their services online through the internet. One of the businesses that have embraced the use of the internet to provide services to their customers is the banking sector. Banks obtain competitive advantage and increased productivity through the adoption of online banking. Bank customers enjoy online banking as it provides them with anytime, anywhere banking experience. Away from the benefits is the issue of security of customer transaction data and customer privacy. Many authors have proposed various solutions to address the online banking security problem but while some focus solely on client authentication, others dwell only on security of the data transfer channels. In this paper, we propose a cancellable biometric based authentication protocol which guarantees secure mutual authentication, customer privacy and offer a secure end-to-end transmission of customer transaction data. The protocol in this paper is designed using Biohashing, a biometric template protection technique and dual cryptographic algorithm that combines Advanced Encryption Standard (AES) and Data Encryption Standard algorithms. With these, we realized strong authentication and secure transaction information exchange protocol for online banking
A Context-Adaptive Ranking Model for Effective Information Retrieval System
(International Journal of Information Science, 2018) Agbele, Kehinde K.; Ayetiran, Eniafe; Babalola, Olusola
Abstract When using Information Retrieval (IR) systems, users often present search queries made of ad-hoc keywords. It is then up to information retrieval systems (IRS) to obtain a precise representation of user’s information need, and the context of the information. Context-aware ranking techniques have been constantly used over the past years to improve user interaction in their search activities for improved relevance of retrieved documents. Though, there have been major advances in context-adaptive systems, there is still a lack of technique that models and implements context-adaptive application. The paper addresses this problem using DROPT technique. The DROPT technique ranks individual user information needs according to relevance weights. Our proposed predictive document ranking model is computed as measures of individual user search in their domain of knowledge. The context of a query determines retrieved information relevance. Thus, relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. We demonstrate the ranking task using metric measures and ANOVA, and argue that it can help an IRS adapted to a user's interaction behaviour, using context to improve the IR effectiveness.
A Dependable Model for Attaining Maximum Authentication Security Procedure in a Grid Based Environment
(Trends in Applied Sciences Research, 2012) Agbele, Kehinde K.; Azeez, N. A.; Abidoye, A. P.; Adesina, A. O.
Grid computing is an emergent computing innovation which offers endless access to computing infrastructure across various organizations (academia and industry). Since this technology allows aggregation of various computer systems for usage by different users to run applications, the information stored on it which may be sensitive and private, remains vulnerable. According to related research on the attribute based access control for grid computing there is no adequate and appropriate security mechanism to authorize and authenticate users before accessing information on a grid system. The issue of security in grid technology has not been fully addressed even though it is a precondition for optimizing grid usability. Having realized the paucity of security guarantees, this research work focuses on developing a model for securing data and applications deployed on a grid on the basis of double identity authentication and public key. The implementation of the model has undoubtedly guaranteed the security of sensitive information on a grid vis-a-vis strict adherence to security policies and protocols.
A Mathematical Model for the Transmission of HIV/AIDS with Early Treatment
(Journal of Advances in Mathematics and Computer Science, 2021) Akinwumi, T. O.; Olopade, I. A.; Adesanya, A. O.; Alabi, M. O.
In this paper, a mathematical model for the transmission of HIV/AIDS with early treatment is developed and analyzed to gain insight into early treatment of HIV/AIDS and other epidemiological features that cause the progression from HIV to full blown AIDS. We established the basic reproduction number which is the average number of new secondary infection generated by a single infected individual during infectious period. The analysis shows that the disease free equilibrium is locally and globally asymptotically stable whenever the threshold quantity is less than unity i.e. Numerical analysis shows that the early treatment of latently infected individuals reduces the dynamical progression to full blown AIDS. The result also showed that immunity boosted substances increase the red blood cells, sensitivity analysis of basic reproduction number with respect to parameters showed that effective contact rate must not exceed 0.3 to avoid endemic stage.
A Multiple Linear Regression Model for Analyzing and Predicting Educational Development in Nigeria
(NIPES Journal of Science and Technology Research, 2021-03) Orogun, A.O.; Ariyo, O.E; Ajayi, O.O.; Onyekwelu, B.
This paper explores the application of machine learning for predicting educational development in Nigeria, to determine its progress or regress in Ondo State. Numerous factors impact the performance of educational organizations, viz; infrastructure, learning condition, student ability, the immediacy of teachers, methods of educating and learning, research centers, grounds areas, and so forth served as the variable used for the prediction. The data for the study was obtained from Nigeria Education Digest Statistics Indicator 2005-2016, Ondo State Demographic Digest Statistics 2009. The study developed a predictive model using multiple linear regression, which considers the various factors that determines the progress of education in Nigeria. The result of the evaluation of the model shows that a somewhat rise in the educational development in the country, with regards to the feature attributes considered. The model showed that literacy rate has a higher correlation coefficient of 0.22.
A Naive Bayes approach to fraud prediction in loan default
(IOP Conf. Series: Journal of Physics: Conf. Series, 2019) Eweoya, Ibukun; Adebiyi, A A; Azeta, A A; Chidozie, F; Agono, F O; Guembe, B
The essence of granting loans to individuals and corporate beneficiaries is to boost the economy while the lenders make profit from the interest that accrues to the lending. However, due to non-compliance to basic rules, fraud is prevalent in credit administration and traditional methods of detecting fraud have failed. Furthermore, they are time-consuming and less accurate. This work uses a supervised machine learning approach, specifically the Naïve Bayes to predict fraudulent practices in loan administration based on training and testing of labeled dataset. Previous works either predict credit worthiness or detect loan fraud but not predicting fraud in credit default. The approach employed in this work yielded 78 % accuracy.
A Neuro-Fussy Based Model for Diagnosis of Monkeypox Diseases
(International Journal of Computer Science Trends and Technology (IJCST), 2018) Tom, Joshua J.; Anebo, Nlerum P.
The largest vertebrate viruses known, infecting humans, and other vertebrates are poxviruses including cowpox, vaccinia, variola (smallpox), and monkeypox viruses. Monkeypox was limited to the rain forests of central and western Africa until 2003. A smallpox-like viral infection caused by a virus of zoonotic origin, monkeypox belongs to the genus Orthopoxvirus, family Poxviridae, and sub-family Chordopoxvirinae. Monkeypox has a clinical presentation like ordinary forms of smallpox, including flulike symptoms, fever, malaise, back pain, headache, and characteristic rash. In view of the eradication of smallpox, such symptoms in a monkepox endemic region should be carefully diagnosed. The problem in diagnosing monkeypox lies in the fact that it is clinically indistinguishable from other pox-like illnesses making virus differentiation difficult. In this paper, we present a neuro-fuzzy based model for early diagnosis of monkeypox virus with a differentiation from other pox families.
A Novel Document Ranking Algorithm That Supports Mobile Healthcare Information Access Effectiveness
(Academic Journals Inc., 2011) Agbele, Kehinde K.; Adesina, Ademola O.; Azeez, Nureni A.; Abidoye, Ademola P.; Febba, Ronald
This study presented DROPT; an acronym for Document ranking Optmization algorithm approach, a new idea for the effectiveness of meaningful retrieval results from the information source. Proposed method extracted the frequency of query keyword terms that appears within the user context of Frequently Asked Questions (FAQ) systems on HIV/AIDS content related-documents. The SMS messages were analyzed and then classified, with the aim of constructing a corpus of SMS related to HIV/AIDS. This study presented a novel framework of Information Retrieval Systems (IRS) based on the proposed algorithm. The developed DROPT procedure was used as an evaluation measure. This “Term Frequency-Inverse Document Frequency (TFIDF)” method was applied to obtain the experimental result that was found promising in ranking documents not only the order in which the relevant documents were retrieved, but also both the terms of the relevant documents in feedback and the terms of the irrelevant documents in feedback might be useful for relevance feedback, especially to define its fitness function (mean weight).
A novel routing algorithm for energy optimization in wireless sensor networks
(Research Journal of Information Technology, 2012) Abidoye, Ademola P.; Azeez, Nureni A.; Adesina, Ademola O.; Agbele, Kehinde K.
Wireless sensor networks (WSNs) have become an interesting area to researchers in recent times due to the low cost of sensor nodes, wide application areas and with low or no cost of maintenance after deployment in a target area. Sensor nodes are expected to remain in operation for a longer time without human intervention. However, due to the small size and cost of these nodes, they have been equipped with small batteries with limited energy source. This has been a major constraint to WSNs, since in most cases sensor nodes are deployed in large number where it may be difficult or impossible to replace the batteries of each node when they run out of supplying power. In this study, a novel Routing Algorithm for Energy Optimization in WSNs (RAEO) has been proposed to reduce communication distance among the nodes by transmitting sensed data through the shortest path from source node to the base station along the neighbouring nodes. The simulation results show that our approach reduces energy consumption during data transmission and increases networks lifetime compared with MECN and SPIN protocols. Finally, the proposed algorithm reduces protocol propagation delay and packets loss during data transmission.
A Query-Based SMS Translation in Information Access System
(International Journal of Soft Computing and Engineering (IJSCE), 2011-11) Agbele, Kehinde K.; Adesina, Ademola O.; Nureni, Azeez A.; Abidoye, Ademola P.
Mobile technology has contributed to the evolution of several media of communication such as chats, emails and short message service (SMS) text. This has significantly influenced the traditional standard way of expressing views from letter writing to a high-tech form of expression known as texting language. In this paper we investigated building a mobile information access system based on SMS queries. The difficulties with SMS communication were explored in terms of the informal communication passage and the associated difficulty in searching and retrieving results from an SMS-based web search engine under its non-standardization. The query is a pre-defined phrase-based translated English version of the SMS. The SMS machine tool normalization algorithm (SCORE) was invented for the query to interface with the best ranked and highly optimized results in the search engine. Our results, when compared with a number of open sources SMS translators gave a better and robust performance of translation of the normalized SMS.
A Systematic Literature Review of Mobile Cloud Computing
(International Journal of Multimedia and Ubiquitous Engineering, 2015) Eweoya, Ibukun; Olawande, Daramola
Mobile cloud computing (MCC) is a relatively new concept that leverages the combination of cloud technology, mobile computing, and wireless networking to enrich the usability experiences of mobile users. Many field of application such as mobile health, mobile learning, mobile commerce and mobile entertainment are now taking advantage of MCC technologies. Since MCC is new, there is need to advance research in MCC in order to deepen practice. Currently, what exist are mostly descriptive literature reviews in the area of MCC. In this paper, a systematic literature review (SLR), which offers a structured, methodical, and rigorous approach to the understanding of the trend of research in MCC, and the least and most researched issue is presented. The objective of the study is to provide a credible intellectual guide for upcoming researchers in MCC to help them identify areas in MCC research where they can make the most impact. The SLR was limited to peer-reviewed conference papers and journal articles published from 2002 to 2014. The study reveals that privacy, security and trust in MCC are the least researched, whereas issues of architecture, context awareness and data management have been averagely researched, while issues on operations, end users, service and applications have received a lot of attention in the literature.
A SYSTEMATIC MAPPING STUDY OF CLOUD COMPUTING MIDDLEWARE, STACKS, TOOLS, DELIVERY NETWORKS
(International Journal of Mechanical Engineering and Technology (IJMET), 2019-05) Odun-Ayo, Isaac; Samuel, Victoria; Eweoya, Ibukun; Oyom, Paul
Cloud computing is presently playing a significant role in the provisioning of vital services in information technology. A unique aspect of cloud computing is the cloud middleware and other related entities which supports applications and networks. Determining a particular research area especially in terms of cloud middleware and services at all levels could be a cumbersome process for a researcher, hence the need for reviews and paper surveys that identify research gaps. The purpose of this paper was to conduct a systematic mapping study of cloud computing middleware, stacks, tools and services at all layers. The focus was on three facets of studies, the research facet, topic facet and contribution facet. The results showed that there were more publications on tool in the contribution facet with tool, model, method and process having 18.10%, 13.79%, 6.03% and 8.62% respectively. In addition, evaluation and solution research had the largest number of articles in terms of tool with 14.17% and 26.77% respectively. A most striking aspect of the systematic map is that solution research has the highest frequencies of publication in relation to all aspects of the topics extracted for the study. This study clearly identified gaps in the field of cloud computing middleware, which should stimulate interest for further studies by both researchers and industry practitioners.
A SYSTEMATIC MAPPING STUDY OF CLOUD COMPUTING MIDDLEWARE, STACKS, TOOLS, DELIVERY NETWORKS
(International Journal of Mechanical Engineering and Technology (IJMET), 2019-05) Odun-Ayo, Isaac; Samuel, Victoria; Eweoya, Ibukun; Oyom, Paul
Cloud computing is presently playing a significant role in the provisioning of vital services in information technology. A unique aspect of cloud computing is the cloud middleware and other related entities which supports applications and networks. Determining a particular research area especially in terms of cloud middleware and services at all levels could be a cumbersome process for a researcher, hence the need for reviews and paper surveys that identify research gaps. The purpose of this paper was to conduct a systematic mapping study of cloud computing middleware, stacks, tools and services at all layers. The focus was on three facets of studies, the research facet, topic facet and contribution facet. The results showed that there were more publications on tool in the contribution facet with tool, model, method and process having 18.10%, 13.79%, 6.03% and 8.62% respectively. In addition, evaluation and solution research had the largest number of articles in terms of tool with 14.17% and 26.77% respectively. A most striking aspect of the systematic map is that solution research has the highest frequencies of publication in relation to all aspects of the topics extracted for the study. This study clearly identified gaps in the field of cloud computing middleware, which should stimulate interest for further studies by both researchers and industry practitioners.
A Systematic Mapping Study of Edge Computing and Internet of Things with the Cloud
(International Journal of Engineering Research and Technology, 2019) Odun-Ayo, Isaac; Eweoya, Ibukun; Toro, Williams; Bogleb, Sherrene
Cloud computing is a business paradigm wherein computers and computing related services are provided by Cloud Service Providers to consumers either as software, development platform, or infrastructure. The integration of edge computing and IoT with Cloud opens a new technological dimension and a vista of research opportunities in this field. To determine the research context specifically in edge computing and IoT in relation to the cloud is a rigorous research process, this is where reviews and paper surveys come to play; as they easily help to discover research gaps. This paper aims to conduct a systematic mapping study of integration of Edge and IoT with the Cloud. A combination of topical, research and contribution facets were used to analyze publications of interest in reputable journals, magazines and conferences. Obtained results showed that most publications were on the topic of Applications in terms of Tool and Model, with 11.21% and 17.76% respectively. They were closely followed by publications on Architecture in terms of Model and Tool with 11.21% and 5.61%. Opinion papers were the least in the aspects of Architectures. In addition, there were more publications on Evaluation and Solution research with respect to Application with 9.92% and 14.5% respectively. Most papers on Ubiquitous Networks were in the area of Validation research with 5.34%. Furthermore, there were more work on Optimization in the areas of Philosophical, Evaluation and Experience studies, with 7.62%, 6.11% and 6.11% respectively. The output of this research is to be of benefit to research community as it readily points out areas of research drought.
AGENT-BASED CONTEXT-AWARE HEALTHCARE INFORMATION RETRIEVAL USING DROPT APPROACH
(IJIR International Science Press, 2012-12) Agbele, Kehinde K.; Adesina, Ademola; Daniel, Ekong; Dele, Seluwa
As the volume of information available on the Web information systems is growing continuously, browsing this content becomes a tedious task given the presentation of data that does meet user's aims and needs. In this paper, to satisfy user needs, an agent-based paradigm is an appropriate solution which gives outputs suitable to the user in the form of highly ranked documents. Conversely, patient care and a health condition commonly require collaboration between healthcare providers. The emergence of agent's technology motivates radical changes of how information is obtained. This paper addresses this problem by proposing a novel DROPT (Document Ranking OPTimization) measure for information retrieval results to validate the effectiveness of the information management tasks. We propose information retrieval system architecture, which main components are contextaware agent’s technology to meet users' information needs.
Algorithm for information retrieval optimization
(IEEE, 2016-10-13) Agbele, Kehinde K.; Ayetiran, Eniafe F.; Aruleba, Kehinde D.; Ekong, Daniel O.
When using Information Retrieval (IR) systems, users often present search queries made of ad-hoc keywords. It is then up to the information retrieval systems (IRS) to obtain a precise representation of the user's information need and the context (preferences) of the information. To address this problem, we investigate optimization of IRS to individual information needs in order of relevance. The goal of this article is to develop algorithms that optimize the ranking of documents retrieved from IRS according to user search context. In particular, the ranking task that led the user to engage in information-seeking behaviour during search tasks. This article discusses and describes a Document Ranking Optimization (DROPT) algorithm for IR in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this article, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (w ij ) of keywords in the document index vector, calculated as a function of the frequency of a keyword k j across a document. The purpose of the DROPT technique is to reflect how human users can judge the context changes in IR result rankings according to information relevance. This article shows that it is possible for the DROPT technique to overcome some of the limitations of existing traditional (tf × idf) algorithms via adaptation. The empirical evaluation using metrics measures on the DROPT technique carried out through human user interaction shows improvement over the traditional relevance feedback technique to demonstrate improving IR effectiveness.
AN ANALYSIS OF THE NETWORKED READINESS INDEX DATA OF SOME SUB-SAHARAN AFRICA COUNTRIES
(Nigeria Computer Society, 2016-07) Oriogun, P. K.; Adesanya, A. O.; Omolofe, B.; Yara, P. O.; Ogunrinde, R. B.; Akinwumi, Titilayo O.
African governments and businesses must accept the concept of Internet of Everything (IoE) by being fully digitized with highly robust computer network security in order to embrace modern technologies in the form of cloud, mobile, social and analytics. They must also realize the importance attached to achieving societal and economic transformation by fully understanding the connection between people, process, data and things in order to create the needed opportunities for African citizens. A country’s Networked Readiness is an ideal indicator of a country’s ability to implement and take a competitive advantage of Information Communication Technologies (ICTs). In this article we investigate 6 sub-Saharan Africa countries (Botswana, Mauritius, Namibia, Nigeria, South Africa and Zimbabwe) in terms of their Networked Readiness Index (NRI) rankings as published in the Global Information Technology Reports (GITR) from 2002 – 2015. We developed a number of statistical models for predicting the NRI for these countries for the next 9 years based on the NRI rankings of these countries in the previous 9 years. Our predictive models for NRI rankings suggest that on average over next the 9 years, the hierarchical ordering is namely, Mauritius (1st), South Africa (2nd), Zimbabwe (3rd), Namibia (4th), Botswana (5th) and Nigeria (6th) respectively. We conclude that in terms of Networked Readiness in Africa during the period of our predictions, data security will be crucial in three areas: confidentiality, integrity and availability. Furthermore, we are of the opinion that programmable security infrastructure (software-based security environment) will have the ability to secure dynamically a particularly sensitive data flow across the network on demand and according to the organization’s security policy.
An empirical investigation of acceptance, adoption and the use of E-agriculture in Nigeria
(Heliyon, 2021-07) Eweoya, Ibukun; Okuboyejo, Senanu R.; Odetunmibi, Oluwole A.; Odusote, Babafemi O.
Agriculture is one of the major forces to reckon with in the employment rate and overall economy of any nation. E-agriculture is not yet fully known to all farmers in Nigeria, hence affecting adversely production and the overall business chain. The acceptance and adoption of e-agriculture can make life better and advance the economy faster. This work investigated the acceptance of e-agriculture together with its adoption in Nigeria using questionnaires for data collection. This study seeks to discover to which extent e-agriculture is adopted by diverse categories of people with basic interest on the direct determinants of usage intention and behavior; direct determinant of user behavior, and impact moderators. The Unified Theory of Acceptance and Use of Technology model was adopted and SmartPLS 3.0 was used for the analysis of the collected data. The study establishes that performance expectancy, effort expectancy, social influence and habit were discovered as variables that have significant effect on behavioral intention for the acceptance and adoption of e-agriculture while performance expectancy was discovered to be the most significant factor that influences the usage of e-agriculture in Nigeria. It is recommended that new factors like, quality of service, privacy concerns, and enhanced farmer support can be added as new factors in future works.
An optimized Lesk-based algorithm for word sense disambiguation
(De Gruyter: Open Computer Science, 2018-10-05) Ayetiran, Eniafe Festus; Agbele, Kehinde
Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents based on the theory underlying topic models. The knowledge resource adopted is the English WordNet enriched with linguistic knowledge from Wikipedia and Semcor corpus. Besides the algorithm’s e ciency, we also evaluate its e ectiveness using two datasets; a general domain dataset and domain-speci c dataset. The algorithm achieves a superior performance on the general domain dataset and superior performance for knowledge-based techniques on the domain-specific dataset.
ANCAEE: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks
(Scientific Research, 2011-08-31) Abidoye, Ademola P.; Azeez, Nureni A.; Adesina, Ademola O.
One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.

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