Faculty of Information and Communication Technology

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Use of electronic information resources by university lecturers in Edo State, Nigeria
(2013) Uwaifo, S. O; Eiriemiokhale, K. A.
The limited access to up-to-date materials in university libraries in Nigeria is a main problem that impedes research and teaching. In the last couple of years, lecturers in Nigerian tertiary institutions have increasingly demanded and preferred access to electronic sources delivery and networked information from their respective libraries. The objectives of this study are to: i. identify the benefits the university lecturers in Edo State derive from using electronic information resources; ii. find out the available facilities for using electronic information resources by the university lecturers in Edo State. The study concludes that the university lecturers in Edo State derive several benefits from the use of electronic information resources. However, the available facilities for using electronic information resources are not encouraging. Except for the fact that university lecturers have personal computers at home coupled with handheld devices and the universities’ e-libraries, the universities do not have departmental computer laboratories not to talk of personal computer at their offices. The researchers provided the following recommendations: i. The university managements should provide well equipped computer laboratories for all the departments and provide personal computers in the university lecturers’ offices. ii. The university managements should provide funds for subscription to more primary and secondary electronic sources. Reasonable investment should be made on the university’s e-library so as to be able to subscribe to several databases and provide internet services to lecturers free of charge. iii. There is the urgent need for all the universities in Edo State to be properly funded by their financiers (federal and state governments as well as private organizations). Huge financial investment in ICTs by the universities will positively impact on the lecturers.
Use of Electronic Information Resources by University Lecturers in Edo State, Nigeria
(PNLA Quarterly, the official publication of the Pacific Northwest Library Association, 2013-07) Dr. Stephen Osahon Uwaifo; Kennedy Arebamen Eiriemiokhale
The limited access to up-to-date materials in university libraries in Nigeria is a main problem that impedes research and teaching. In the last couple of years, lecturers in Nigerian tertiary institutions have increasingly demanded and preferred access to electronic sources delivery and networked information from their respective libraries (Covi & Cragin, 2004). Timely information is required by all categories of people in the different organizations of the society and one of such organizations is the university. University lecturers equip students with skills in reading, inquiry and independent thinking and strive to develop students’ creativity, insight and analytical skills. All these necessitate seeking and use of information from various sources such as books, journals, periodicals, to mention a few. University education is changing rapidly (Toner, 2008). Bennet (2003) identified a major shift in education- The revolution in information technology is changing delivery of education. This dramatic change includes the way in which information is provided to the university community. Universities through a number of ways embrace the electronic provision of information to facilitate study programmes and research. With the integration of online information services, electronic books, electronic document delivery services and digital libraries in its library systems, university lecturers can now access information from various sources.
Development of an Intrusion Detection System in a Computer Network.
(International Journal of Computers & Technology., 2014-03-14) Babatunde, R. S., Adewole K. S., Abdulsalam S. O. and Isiaka R. M. (2014)
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 against denial of service. While firewalls do provide some protection, they do not provide full protection. This is because not all access to the network occurs through the firewall. This is why firewalls need to be complemented by an intrusion detection system (IDS).An IDS does not usually take preventive measures when an attack is detected; it is a reactive rather than proactive agent. It plays the role of an informant rather than a police officer. In this research, an intrusion detection system that can be used to deny illegitimate access to some operations was developed. The IDS also controls the kind of operations performed by users (i.e. clients) on the network. However, unlike other methods, this requires no encryption or cryptographic processing on a per-packet basis. Instead, it scans the various messages sent on a network by the user. The system was developed using MicrosoftVisual Basic.
Development of Fingerprint Biometric Attendance System for Non-Academic Staff in a Tertiary Institution.
(Computer Engineering and Intelligent Systems., 2014-04-13) Adewole, K. S., Abdulsalam S. O., Babatunde R. S., Shittu T. M. and Oloyede M. O. (2014)
Institutions, companies and organisations where security and net productivity is vital, access to certain areas must be controlled and monitored through an automated system of attendance. Managing people is a difficult task for most of the organizations and maintaining the attendance record is an important factor in people management. When considering the academic institute, taking the attendance of non-academic staff on daily basis and maintaining the records is a major task. Manually taking attendance and maintaining it for a long time adds to the difficulty of this task as well as wastes a lot of time. For this reason, an efficient system is proposed in this paper to solve the problem of manual attendance. This system takes attendance electronically with the help of a fingerprint recognition system, and all the records are saved for subsequent operations. Staff biometric attendance system employs an automated system to calculate attendance of staff in an organization and do further calculations of monthly attendance summary in order to reduce human errors during calculations. In essence, the proposed system can be employed in curbing the problems of lateness, buddy punching and truancy in any institution, organization or establishment. The proposed system will also improve the productivity of any organization if properly implemented.
Adoption and use of electronic information resources by medical science students of the University of Benin, Benin City, Nigeria
(The Association of Information Professionals of Nigeria., 2015) Kennedy A. EIRIEMIOKHALE; James A. Aiyefelehin
Local Binary Pattern and Ant Colony Optimization Based Feature Dimensionality Reduction Technique for Face Recognition Systems.
(Journal of Advances in Mathematics and Computer Science, 2015-04-13) Babatunde, R.S, Olabiyisi, S. O., Omidiora, E. O. and Ganiyu, R. A. (2015)
Feature dimensionality reduction is the process of minimizing the number of features in high dimensional feature space. It encompasses two vital approaches: feature extraction and feature selection. In face recognition domain, widely adopted face dimensionality reduction techniques include Principal component analysis, Discrete wavelet transform, Linear discriminant analysis and Gabor filters. However, the performances of these techniques are limited by strict requirement of frontal face view, sensitivity to signal shift and sample size, computational intensiveness amongst others. In this paper, a feature dimensionality reduction technique that employed Local binary pattern for feature extraction and Ant colony optimization algorithms for the selection of optimal feature subsets was developed. The developed technique identified and selected the salient feature subsets capable of generating accurate recognition. The average training time, recognition time and recognition rate obtained from the experiment on locally acquired face data using cross-validation evaluation approach indicate an efficient performance of the potential combination of both methods in a two-level technique for dimensionality reduction
: Assessing the performance of Random Partitioning and K-Fold Cross Validation methods of evaluation of a Face Recognition System.
(Journal of Advances in Image and Video Processing, 2015-06-08) Babatunde, R. S, Olabiyisi S. O, Omidiora E. O, Ganiyu, R. A. and Isiaka, R. M. (2015)
Face recognition has been an active research area in the pattern recognition and computer vision domains due to its many potential applications in surveillance, credit cards, passport and security. However, the problem of correct method of partitioning the face data into train and test set has always been a challenge to the development of a robust face recognition system. The performance of the System was tested on locally acquired face database when the face database was randomly partitioned and when k-fold Cross Validation partition was used. The face database was captured under the condition of significant variations of rotation, illumination and facial expression. Quantitative evaluation experimental results showed that Random Sampling technique has a higher average recognition rate (96.7%) than Cross Validation partition method (95.3%). However, recognition time in Cross Validation is faster (0.36 secs) than that of Random Sampling (0.38 secs).
Use of statistical records for library management at University of Ilorin
(Information Technology Application Group International, Nigeria, 2016) Eiriemiokhale, K. A.; Isiwele-Ishola, R. O.; Ishola, M. T.
Purpose: The study examined the use of statistical records for library management at the University of Ilorin, Kwara State. Design/Methodology/Approach: The descriptive survey research design was adopted for the study. Questionnaire was used to collect data from 40 library staff (professionals & paraprofessionals). Data obtained were analyzed using frequency counts and percentages. Findings: The results revealed that library statistics are used for reference analysis, selection and acquisition ofinformation resources, planning and decision making, preparation of library budget and determining the extent of library use Implication: The study admonished that statistics should be collected appropriately in order to enhance the growth and management of the library.Experts should be in charge of ZCX interpretation, compilation, analysis and distribution of statistical data. Originality/Value: The study will be off help to librarians because statistics will help them to plan library operations.
Handwritten Character Recognition using Brainnet Library,
(Annals. Computer Science Series Journal, Published by Faculty of Computers and Applied Computer Science, Tibiscus University of Trinisoara, Romania., 2016-02-15) Babatunde, A. N., Abikoye, O.C., Babatunde, R.S. and Kawu, R.O. (2016)
Handwriting has continued to persist as a means of communication and recording information in dayto- day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a PDA, in postal addresses on envelopes, in amounts in bank checks, in handwritten fields in forms, etc. An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described, and a method, called, diagonal based feature extraction is used for extracting the features of the handwritten alphabets. This project implements this methodology using BrainNet Library. Ten data sets, each containing 26 alphabets written by various people, are used for training the neural network and 130 different handwritten alphabetical characters are used for testing. The proposed recognition system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the conventional horizontal and vertical methods of feature extraction. This system, if modified will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.
A novel approach to outliers removal in a noisy numeric dataset for efficient Mining.
(Published by Faculty of Computing and Information Systems, University of Ilorin., 2016-02-16) Ajiboye, A. R, Adewole, K. S., Babatunde, R. S. and Oladipo, I. D. (2016):
Data pre-processing is a key task in the data mining process. The task generally consumes the largest portion of the total data engineering effort while unveiling useful patterns from datasets. Basically, data mining is about fitting descriptive or predictive models from data. However, the presence of outlier sometimes reduces the reliability of the models created. It is, therefore, essential to have raw data properly pre-processed before exploring them for mining. In this paper, an algorithm that detects and removes outliers in a numeric dataset is proposed. In order to establish the effectiveness of the proposed algorithm, the clean data obtained through the implementation of the proposed approach is used to create a prediction model. Similarly, the clean data obtained through the use of one of the existing techniques is also used to create a prediction model. Each of the models created is simulated using a set of untrained data and the error associated with each model is measured. The resulting outputs from the two approaches reveal that, the prediction model created using the output from the proposed algorithm has an error of 0.38, while the prediction model created using the cleaned data from the clustering method gives an error of 0.61. Comparison of the errors associated with the models created using the two approaches shows that, the proposed algorithm is suitable for cleaning numeric dataset. The results of the experiment also unveils that, the proposed approach is efficient and can be used as an alternative technique to other existing cleaning methods.
Implications of System Identification Techniques on ANFIS E-learners Activities Models-A Comparative Study.
(Transactions on Machine Learning and Artificial Intelligence,, 2016-04-11) Isiaka, R. M., Omidiora, E. O. Olabiyisi, S. O., Okediran O.O. and Babatunde, R. S. (2016):
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 Network based Fuzzy Inference System (ANFIS) E-learners Activities models. Expert knowledge and Historical data were used to formulate the system and their performances were compared. Similarly, comparison was made between memberships functions selected for Historical data identification. The efficiencies of the simulated models in MATLAB editor were determined using both classification uncertainty metrics and confusion matrix–based metrics. The classification uncertainty metrics considered are Mean Absolute Error (MAE) and Root Mean-Squared Error (RMSE). The confusion matrix-based metrics used are Accuracy, Precision and Recall. It was discovered that the model based on Experts Knowledge after training outperformed those based on Historical Data. The performances of the Membership Functions after ranking are Sigmoid, Gaussian, Triangular and G-Bells respectively.
Gender Recognition using Local Binary Pattern and Naïve Bayes Classifier
(African Journal Online. Published by Nigeria Computer Society Journal. Journal of Computer Science and its Applications, 2016-10-24) Babatunde, R. S., Abdulsalam, S. O., Yusuff, S. R., and Babatunde, A. N. (2016):
Human face provides important visual information for gender perception. Ability to recognize a particular gender is very important for the purpose of differentiation. Automatic gender classification has many important applications, for example, intelligent user interface, surveillance, identity authentication, access control and human-computer interaction amongst others. Gender recognition is a fundamental task for human beings, as many social functions critically depend on the correct gender perception. Consequently, real-world applications require gender classification on real-life faces, which is much more challenging due to significant appearance variations in unconstrained scenarios. In this study, Local Binary Pattern is used to detect the occurrence of a face in a given image by reading the texture change within the regions of the image, while Naive Bayes Classifier was used for the gender classification. From the results obtained, the gender correlation was 100% and the highest accuracy of the result obtained was 99%.The system can be employed for use in scenarios where real time gender recognition is required.
Internet news: Displacing or complementing mainstream TV in Zaria and Kaduna?
(Department of Mass Communication, Ebonyi State University, Abakaliki, Nigeria., 2017) Agnes Joe SHAIBU
Popularity of Internetnews sources continues to raise concerns over its impact on traditional news sources across the globe, as it is a widely investigated topic in academic researches. Internet use is a global phenomenon, hence this study sought to find out how much of the assertions of Internet use displacing or complementing traditional media apply to Nigerians. The study investigated the extent to which uptake of Internet news had affected use of Television news and the extent of complementarity. The study was premised upon the uses and gratifications and media complementarity theories. 345 respondents purposively sampled were surveyed in Zaria and Kaduna, Nigeria. Findings showed that use ofInternet news complemented respondents’ uptake of mainstream Television news and that Internet news has affected their television news consumption to a minimal extent. The study concluded that Internet news usage was unlikely to displace Television news viewing among sampled respondents. The study recommended that traditional media who were online upload different contents from their offline version.
An Empirical Study on the Traits of Information Literacy Level among Senior Secondary Students in Ilorin, Nigeria
(The University Libraries of the University of Nebraska--Lincoln, Lincoln, Nebraska, USA, 2017) Adeyemi, Ismail Olatunji
This study examined the information literacy level among secondary school students in Ilorin. This study adopted the disproportionate stratified random sampling techniques. The total population for this study 1958 students. The data for the study was collected through structured questionnaires which were distributed randomly to 210 students. However, only 192 copies of the questionnaire were properly filled and returned for analysis and thus form the basis as sample for this study (N=192). The findings of the study revealed that more than half of the respondents can identify lack of knowledge in a subject area. The study also revealed that majority of the respondents can articulate current knowledge on a topic. Furthermore, it also revealed that a large number of the respondents cannot identify specialist search tools. Also, from the study, it was revealed that noteworthy numbers of the respondents do not use Boolean operators in their search for information. Conclusively, the study shows that information literacy skills are essential for every human being because information is vital to everyone and every walk of life. It was recommended that policy makers in education sector should try and introduce information literacy skills as a subject in the secondary school curriculum so as to ensure that the students have the necessary information literacy skills rather than developing these skills through self-education. It was also recommended that teachers that have skills in information literacy skills should be employed as the facilitators in this subject.
An Evaluation of performance of k-NN and Mahalanobis Distance on Local Binary Pattern Feature representation for Access Control in Face Recognition System.
(Computing, Information Systems & Development Informatics Journal, 2017-04-11) Yusuff, S.R., Balogun, F.B., Babatunde, A.N. and Babatunde, R.S. (2017)
A vast majority of the existing face recognition techniques encounter misclassifications when there is a large variation of the subject in terms of pose, illumination and expression as well as artefact such as occlusion. With the usage of Local Binary Pattern (LBP), local feature representation which preserves local primitives and texture information, robust against illumination, expression and occlusion was realized in the feature extraction process. Mahalanobis distance and k-NN classifier were employed for recognition as basis for comparison. An assessment of both algorithms was considered. It was observed that Mahalanobis distance measure outperformed the k-NN classifier for access control and recognition system due to its high recognition rate (98.4%), genuine acceptance rate (98.37) and its stern adherence to both FAR and FRR (0.0144, 1.568) than k- NN with 94.9% and (0.392 and 2.895) respectively. This result demonstrates the robustness of Mahalanobis distance classifier for use access control system.
Implication of variation in Ant Colony Optimization Algorithm (ACO) parameters on Feature Subset Size.
(Computing and Information System Journal, University of West Scotland, 2017-05-20) Babatunde, R. S., Isiaka, R.M., Adigun, O.J. and Babatunde, A.N. (2017)
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 task. Design/Methodology/Approach: The ACO feature subset selection process was filter-based, accomplished by using correlation coefficient as the heuristic information 􀟟 which guides the search to determine the pixel (feature) attractiveness. The intensity of the pixel represents the pheromone level 􀟬. Also, ρ, φ, 􀟙 and 􀟚are key parameters which were tuned to various arbitrary values at each iteration to determine the best combination of parameters which can result in a reduced feature subset (window size). The procedure was simulated in MATLAB 2012. Findings: The study has been able to demonstrate that experimental results obtained by tuning the parameters of ACO at each run gave a reduced feature subset (window size), at parameter settings of α (0.10), β (0.45), ρ (0.50), φ (1.0) which was salient for efficient face recognition thereby demonstrating the effectiveness and superiority of filter-based over wrapper–based feature selection. Research Limitation: The major limiting factor in this research was time and materials which hindered the further testing and implementation of innovative computational intelligence. Originality/Value: This research work is valuable because it gives the implication of the variation of the ACO parameters which determines the extent to which the optimal solution construction that results in a reduced feature subset can be realized.
A Systematic Review of Feature Dimensionality Reduction Techniques for Face Recognition Systems.
(Journal of Digital Innovations & Contemp Res. In Sc., Eng & Tech., 2017-09-07) Babatunde, R.S. (2017)
In this research, a comparison of the various techniques used for face recognition is shown in tabular format to give a precise overview of what different authors have already projected in this particular field. A systematic review of 40 journal articles pertaining to feature dimensionality reduction was carried out. The articles were reviewed to appraise the methodology and to identify the key parameters that were used for testing and evaluation. The dates of publication of the articles were between 2007 and 2015. Ten percent (10%) of the articles reported the training time for their system while twenty four percent (24%) reported their testing time. Sixty seven percent (67%) of the reviewed articles reported the image dimension used in the research. Also, only forty eight percent (48%) of the reviewed articles compared their result with other existing methods. The main emphasis of this survey is to identify the major trade-offs of parameters and (or) metrics for evaluating the performance of the techniques employed in dimensionality reduction by existing face recognition systems. Findings from the review carried out showed that major performance metrics reported by vast amount of researchers in this review is recognition accuracy in which eighty six percent (86%) of the authors reported in their experiment.
Awareness, Availability and Accessibility of Library Resources by Students of Kwara State University, Malete, Nigeria
(University Libraries of the University of Nebraska--Lincoln, Lincoln, Nebraska, USA., 2017-09-26) Kennedy Arebamen Eiriemiokhale CLN; Moses Oladele Ibeun PhD
This study investigated the awareness, availability and accessibility of library resources by students of Kwara State University, Malete. The descriptive survey research design was adopted for the study and 210 undergraduate students provided the data. The findings of the study revealed that information resources were available and accessible in Kwara State University Library. The study showed that students do not know the usefulness of some of the resources and this has hampered their desire for them. Also there is a dire need of varieties of information repackaging to enhance awareness, availability and accessibility of resources in the library. Also revealed is the unfriendliness of some library staff, unclassified nature of some of the information resources. Lack of in-depth orientation on library usage with respect to the use of catalogue and the library online services were the main problems militating against accessing information resources. Therefore, library orientation should be more than mere library tour rather it should be practical in nature where students are exposed to library usage with regard to the use of the catalogue/OPAC and online resources. Current and up-to-date information resources should be made available and accessible to all students through services provided by the library staff.
A Generalized Neuron Model (GNM) Based Human Age Estimation.
(Advances in Multidisciplinary & Scientific Research Journal., 2017-10-20) Babatunde, R.S. and Yakubu, I.A. (2017)
In real-world application, the identification characteristic of face images has been widely explored, ranging from National ID card, International passport, driving license amongst others. In spite of the numerous investigation of person identification from face images, there exists only a limited amount of research on detecting and estimating the demographic information contained in face images such as age, gender, and ethnicity. This research aim at detecting the age/age range of individual based on the facial image. In this research, a generalized neuron (GN), which is a modification of the simple neuron, is used, to overcome some of the problems of artificial neural network (ANN) and improve its training and testing performance. The GN is trained with discrete wavelet transform (DWT) features obtained after the application of Canny edge detection algorithm on the face Image. Validating the technique on FGNET face images reveals that the frequency domain features obtained using the DWT captures the wrinkles on the face region, which represents a distinguishing factor on the face as humans grow older. The empirical results demonstrates that the GN outperforms the simple neuron, with detection rate of 93.5%, training time of 96.30secs, matching time of 14secs and root mean square error of 0.0523. The experimental results suggest that the GN model performs comparably and could be adopted for detecting human ages.
Psychosocial Consequences of Intensive Internet Use among Undergraduates of Universities in Ilorin Metropolis
(The University Libraries of the University of Nebraska--Lincoln, Lincoln, Nebraska, USA, 2018) Akanbi, Lawal M.; Sulaiman, Kabir Alabi; Adeyemi, Ismail Olatunji
This study was carried out to investigate the psychosocial consequences of intensive internet use among undergraduate of universities in Ilorin metropolis, Kwara State. This study sought to determine the psychosocial consequences of intensive internet use on the basis on gender, age, level of study and marital status (University of Ilorin and AL-HIKMAH University) universities within Ilorin metropolis. A self-developed questionnaire tagged questionnaire on psychosocial consequences of intensive internet use (PCIIU) was used to collect data from the respondents for the study. Five research hypotheses were formulated and tested at 0.05 alpha level of significance, data collected were analyzed through analysis of variance (ANOVA). The study revealed that psychosocial consequences of intensive internet use are establishing using new relationship with fellow online users; incur more financial cost on internet; spending more time online than going out with others and there was significant gender difference in the psychosocial consequences of intensive internet use among undergraduate students of universities in Ilorin metropolis base on age, level, gender and marital status. Therefore, the following recommendations were made that counsellors should develop strategies to handle internet addiction among the youth and counsellor should encourage the formation of club that will promote safe and responsible internet use among students (peer counselling) and school administrators, teachers and school counsellors should work collaboratively to identify and assist students with or prone to internet addiction before it will have devastating consequences on the addicts and the society at large.

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