FACULTY OF SCIENCE

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4DS OF CURRICULUM MODEL, SUSTAINABLE DEVELOPMENT GOALS, AND CURRICULUM ON EDUCATION FOR SUSTAINABLE DEVELOPMENT.
(2016) OGUNFOLAKAN, B.A
Most archaeological works in southwestern Nigeria are concentrated in Ile-Ife, Esie, Old Oyo and Owo. In these areas, the focus of archaeological studies had been on different works of art in bronze, terracotta, wood and stone. Studies on cultural themes related to the issues of conflict, war and displacement which have implications for landscape archaeology of the area are often relegated to the background. The main goal of this research was to highlight how conflict, war and displacement impacted on the settlement history of parts of Osun State, southwestern Nigeria. The study also appraised human interactions with the environment and the concomitant effects on emergent settlement configurations. Oral and written data were collected from Ile-Ife, Ikire, Ipetumodu, Ila-Orangun, and Ajaba to generate anthropological data. Investigations aimed at identifying and collecting surface artifacts involved reconnaissance and detailed surveys of the studied sites. Excavations were carried out on potsherd pavements at Ajaba and Asi and on a refuse mound at Ajaba. Artifacts from surface collections and excavations were classified according to types, decoration and functional attributes. Analysis of Mo, Cu, Pb, and Ni of sherd samples was done using inductively coupled plasma mass spectrometry. Ten thin sections were made from selected sherd samples for determination of pottery fabric and inclusions. Palynological analysis of soil samples collected from different depths of the excavated mound was carried out using a microscope with an attached camera. Decorative motifs such as single twisted cord impression were common to all sites. With exception of sherds from Ila-Orangun, those from other areas were related in terms of types, fabric and functional attributes. Some of the sherds bore striking resemblance to those documented for Old Oyo and Ile-Ife with regard to type, decoration and function. Stylistically, the potsherd pavements at Asi and Ajaba were similar to those documented for Ile-Ife. A C-14 date of AD 1263 was obtained from charcoal at a depth of 80cm from the Ajaba mound excavation. Maize cob decoration was absent which indicated that Ajaba site was occupied prior to 16th century when maize was introduced into West Africa. Pollen of forest species and ornamental plants of Asian origin, such as Lagerstroemia indica, Casuarina equisetifolia and Delonix regia was identified from the excavated mound. These were abundant at the lower levels of the excavated mound. However, pollen of ornamental plants disappeared completely at the upper levels while secondary forest species and artifacts increased in abundance which was indicative of increase in human population and subsequent impact on vegetation. There was evidence of increased peopling of the area from around AD 1263. Oral and written records suggested that conflicts and war caused displacement and re-occupation of most of the settlements. Conflict and war resulted in the abandonment and reoccupation of all the sites, resulting in the delineation of several historical phases of occupation. Human impact on the environment was noted from the 13th century.
A comparison of the predictive capabilities of artificial neural networks and regression models for knowledge discovery
(2013) Ojo, A. K.; Adeyemo, A. B.
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to determine which of them performs better. Prediction was done using one hidden layer and three processing elements in the ANN model. Furthermore, prediction was done using regression analysis. The parameters of regression model were estimated using Least Square method. To determine the better prediction, mean square errors (MSE) attached to ANN and regression models were used. Seven real series were fitted and predicted with in both models. It was found out that the mean square error attached to ANN model was smaller than regression model which made ANN a better model in prediction.
A mobile students’ industrial work experience scheme logbook application
(Science and Education Publishing, 2020) Olojakpoke, D. M.; Ojo, A. K.
Monitoring of students who are undergoing the Students’ Industrial Work Experience Scheme (SIWES) program by school-based supervisors is a difficult task because the current paper based logbook system currently employed is not adequate enough to determine how well students are undergoing the program. It is difficult for school-based supervisors to know whether students actually filled their logbooks daily, showing what they have done or whether they filled it all at the end of a long period of time which means that such entries are very likely to be fraudulent. Which is why school-supervisors try to visit students on the program to physically monitor such students, however due to distance and other logistical issues school-based supervisors are only able to visit such students once or at most twice or sometimes never. The application was developed following the incremental model. Node.Js was used for the backend, MongoDB was used as the database while React Native was used to create the front-end. This application helps school-based supervisors monitor students on the SIWES program more effectively and also makes grading and commenting on logbook entries a lot easier. It can therefore be deployed to tertiary institutions in Nigeria to assist them in the running of their respective SIWES programmes.
A model for conflicts’ prediction using deep neural network
(2021-10) Olaide, O. B.; Ojo, A. K.
Conflict is part of human social interaction, which may occur from a mere misunderstanding among groups of settlers. In recent times, advanced Machine Learning (ML) techniques have been applied to conflict prediction. Strategic frameworks for improving ML settings in conflict research are emerging and are being tested with new algorithm-based approaches. These developments have given rise to the need to develop a Deep Neural Network model that predicts conflicts. Hence, in this study, two Artificial Neural Network models were developed, the dataset which was extracted from https://www.data.worlduploaded by the Armed Conflict Location and Event Data Project (ACLED), in four separate CSV files (January 2015 to December 2018). The dataset for the year 2015 has 2697 instances and 28 features, for 2016 was 2233 with the same feature, for 2017 has 2669 instances with the same features, and 2018 has 1651 instances. After the development of the models: the baseline Artificial Neural Network achieved an accuracy of 95% and a loss of 5% on the training data and an accuracy of 90% and 10% loss on the test set. The Deep Neural Network Model achieved 98% accuracy and 2% loss on the training set, with 89% accuracy and 11% loss on the test set. It was concluded that to further improve the prediction of conflict, there is a need to address the issue of the dataset, in developing a better and more robust model.
A predicting phishing websites using support vector machine and multi-class classification based on association rule techniques
(2018-06) Woods, N. C.; Agada, V. E.; Ojo, A. K.
Phishing is a semantic attack which targets the user rather than the computer. It is a new Internet crime in comparison with other forms such as virus and hacking. Considering the damage phishing websites has caused to various economies by collapsing organizations, stealing information and financial diversion, various researchers have embarked on different ways of detecting phishing websites but there has been no agreement about the best algorithm to be used for prediction. This study is interested in integrating the strengths of two algorithms, Support Vector Machines (SVM) and Multi-Class Classification Rules based on Association Rules (MCAR) to establish a strong and better means of predicting phishing websites. A total of 11,056 websites were used from both PhishTank and yahoo directory to verify the effectiveness of this approach. Feature extraction and rules generation were done by the MCAR technique; classification and prediction were done by SVM technique. The result showed that the technique achieved 98.30% classification accuracy with a computation time of 2205.33s with minimum error rate. It showed a total of 98% Area under the Curve (AUC) which showed the proportion of accuracy in classifying phishing websites. The model showed 82.84% variance in the prediction of phishing websites based on the coefficient of determination. The use of two techniques together in detecting phishing websites produced a more accurate result as it combined the strength of both techniques respectively. This research work centralized on this advantage by building a hybrid of two techniques to help produce a more accurate result.
A predicting phishing websites using support vector machine and multi-class classification based on association rule techniques
(2018-06) Woods, N. C.; Agada, V. E.; Ojo, A. K.
Phishing is a semantic attack which targets the user rather than the computer. It is a new Internet crime in comparison with other forms such as virus and hacking. Considering the damage phishing websites has caused to various economies by collapsing organizations, stealing information and financial diversion, various researchers have embarked on different ways of detecting phishing websites but there has been no agreement about the best algorithm to be used for prediction. This study is interested in integrating the strengths of two algorithms, Support Vector Machines (SVM) and Multi-Class Classification Rules based on Association Rules (MCAR) to establish a strong and better means of predicting phishing websites. A total of 11,056 websites were used from both PhishTank and yahoo directory to verify the effectiveness of this approach. Feature extraction and rules generation were done by the MCAR technique; classification and prediction were done by SVM technique. The result showed that the technique achieved 98.30% classification accuracy with a computation time of 2205.33s with minimum error rate. It showed a total of 98% Area under the Curve (AUC) which showed the proportion of accuracy in classifying phishing websites. The model showed 82.84% variance in the prediction of phishing websites based on the coefficient of determination. The use of two techniques together in detecting phishing websites produced a more accurate result as it combined the strength of both techniques respectively. This research work centralized on this advantage by building a hybrid of two techniques to help produce a more accurate result.
A review of the bulk layer pollutant transfer over Nigeria during the harmattan season
(2007) Oladiran, E. O.,; Nymphas, F. F.
A review of the results of the bulk characteristics of the harmattan dust is presented to facilitate ease of reference and regional comparison where similar local effects exist. The meteorological interconnections are dealt with. The transport properties are presented, and are found to agree with the plume model for cascaded continuous sources on a 1km x 1km gnd point system. The wind profile is found to be consistent with turbulent electrode model of Willet.
A statistical approach to estimate wind speed distribution in ibadan, nigeria
(2016) Rauff, K.O; Nymphas, E.F.
In this paper, the wind energy potential in Ibadan is statistically analyzed using daily wind speed data for 10 years (1995-2004) obtained from the International Institute of Tropical Agriculture (IITA) and 1 year (2006) obtained from Nigeria Micro-scale Experimental (NIMEX) Ibadan,Nigeria. The statistical wind data set was analyzed using Weibull distributions in order to investigate the Weibull shape and scale parameters. The daily, monthly, seasonal, and yearly wind speed probability density distributions were modeled using Weibull Distribution Function. The measured annual mean wind speed was found to be 0.76 m/s and the total extractable wind power has been estimated as 0.33 kW at IITA while the annual mean wind speed ranged between 0.74 m/s, 1.02 m/s, 1.16 m/s and 1.34 m/s at (3 m, 6 m, 12 m and 15 m) respectively at NIMEX. The maximum extractable annual wind power density value of 0.90W /m2 for the whole year at IITA and 5.61W / m2 at the highest height of 15 m at NIMEX indicated that, Ibadan can be classified as a low wind energy region and it belongs to the wind power class 1, since the density is less than 100W /m2 . It is concluded that at both sites, the highest wind speed that prevailed in Ibadan is March and the location can be explored for wind power.
A VECTOR MATRIX APPROACH OF COUNTING CYCLIC QUOTIENTS OF SOME ABELIAN P-GROUPS
(2009) Enioluwafe, M.
We determine in this paper, the precise number of cyclic quotients of Abelian p-groups of exponent p i and rank r > 1, i = 1, 2, . . . , n for all natural numbers n
Additive effects of ciprofloxacin on the in-vitro activity of chloroquine against a clinical isolate of Plasmodium falciparum
(Taylor & Francis, 2006) Kazzim, O. J.; Adegbolagun, O. M,; Osho, O.; Anumudu, C. I.
As chloroquine and ciprofloxacin each possess substantial inhibitory activity against the schizonts of Plasmodium falciparum, it seems possible that a combination of the two drugs may be clinically useful. The effects on the erythrocytic stages of P. falciparum of combined treatment with chloroquine and ciprofloxacin were therefore evaluated in vitro, using the World Health Organization’s standardized micro test. When used alone, the median inhibitory concentration (IC50) of chloroquine against the schizonts in the assay mixtures was found to be 7.75 mg/ml, whereas the corresponding value for ciprofloxacin was markedly lower, at 3.35 mg/ml. When they were used together, however, there was marked and statistically significant mutual enhancement of schizont inhibition by the two drugs, indicating that a chloroquine–ciprofloxacin combination may be useful clinically, in the treatment and management of P. falciparum malaria.
An adjusted network information criterion for model selection in statistical neural network models
(JMASM, Inc., 2016) Udomboso, C. G.; Amahia, G. N.; Dontwi, I. K.
In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model selection in more sample sizes than does the NIC.
Ako, A.
(2019-09) Ojo, A. K.
This study presents an approach to extracting data from amazon dataset and performing some preprocessing on it by combining the techniques of Bi-Directional Long Short-Term Memory and 1-Dimensional Convolution Neural Network to classify the opinions into targets. After parsing the dataset and identifying desired information, we did some data gathering and preprocessing tasks. The feature selection technique was developed to extract structural features which refer to the content of the review (Parts of Speech Tagging) along with extraction of behavioral features which refer to the meta-data of the review. Both behavioral and structural features of reviews and their targets were extracted. Based on extracted features, a vector was created for each entity which consists of those features. In evaluation phase, these feature vectors were used as inputs of classifier to identify whether they were fake or non-fake entities. It could be seen that the proposed solution has over 90% of the predictions when compared with other work which had 77%. This increase was as a result of the combination of the bidirectional long short-term memory and the convolutional neural network algorithms.
Algebra 1
(Distance Learning Centre, University of Ibadan, 2008) EniOluwafe M.
We shall expose the meaning of a set and state the different ways of naming a set. We shall also reveal the different types of sets, subsets, equality of sets and the universe of discourse. We shall then interact various sets which belong to the same universe, using the definitions of union, intersection, power set, complements, relative complements and symmetric difference to form new sets. Geometry representation of sets shall be presented in the form of Venn diagrams which will then be used in solving problems on sets. We also study some similarities of algebra of numbers to algebra of set theory and give a theorem on the number of elements in sets
An algoritm for solving electromagnetic field equations by finite element method
(Medwell Journals, 2007) Adetoyinbo, A. A.; Adewole, O. O.
Describing the behaviour of electromagnetic frequency responses from vertically inhomogenous and anisotropic earth of 2-Dimensional structures energized finite sources is computationally laborious. Differential equations were derived and their numerical solutions also sought for the desired components of electric and magnetic fields. Also, expressions for the impedance and apparent conductivity were stated. An algorithm based on the finite element method for computing approximate numerical solutions for these problems were dealinated.
Alternative goodness-of-fit test in logistic regression models
(Medwell Journals, 2011) Nja, M. E.; Enang, E. I.; Chukwu, A. U.; Udomboso, C. G.
The Deviance and the Pearson chi-square are two traditional goodness-of-fit tests in generalized linear models for which the logistic model is a special case. The effort involved in the computation of either the Deviance or Pearson chi-square statistic is enormous and this provides a reason for prospecting an alternative goodness-of-fit test in logistic regression models with discrete predictor variables. The Deviance is based on the log likelihood function while the Pearson chi-square derives from the discrepancies between observed and predicted counts. Replacing observed and predicted counts with observed proportions and predicted probabilities, respectively in a cross-classification data arrangement, the standard error of estimate is proposed as an alternative goodness-of-fit test in logistic regression models. The illustrative example returns favourable comparisons with Deviance and the Pearson chi-square statistics.
An alternative technique to ordinal logistic regression model under failed parallelism assumption
(2009-12) Adeleke, K.A .; Adepoju, A.A
Maternal health status is often measured in medical studies on an ordinal scale but data of this type arc generally reduced for analysis to a single dichotomy. Several statistical models have been developed to make full use of information in ordinal response data, but have not been much used in analyzing pregnancy outcomes. The authors discussed two of these statistical models the ordinal logistic regression model and the multinomial logistic regression model. Logistic regression models are used to analyze the dependent variable with multiple outcomes which can either be ranked or not. In this study, we described two logistic regression models for analyzing the categorical response variable. The first model uses the proportion-! odds model while the second uses the multinomial logistic regression model. The fits of these models using data on delivery from a Nigerian State hospital record/database were illustrated and compared to study the pregnancy outcomes. Analyses based on these models were carried out using STATA statistical package. The Multinomial logistic regression was found to be an important alternative to the ordinal regression technique when proportional odds assumption failed. The weight of the baby and the mother's history of disease (treated or not treated) were found to be important in determining the pregnancy outcome.
An algorithmic framework for hybrid adaptive protocol (HAP) to manage broadcast storm problems in mobile ad-hoc networks (MANETS)
(2008-09) Onifade, O. F. W.; Ojo, A. K.; Okiyi, K. U.
The consequences of pure flooding which is amongst the simplest and the most straight forward approach to performing broadcast include redundant broadcast, contention and collision which are collectively referred to as broadcast storm problem (BSP). This is as a result of the use of plain broadcasting approaches leading to signal overlap in a geographical area with wireless communication. The Counter-based scheme was developed to reduce Broadcast Storm problem. However, to be able to maintain high delivery ratio in either a sparse or dense networks, different thresholds are required. Because of the nature of MANETs determining this threshold require a level of dynamism, without which its operation will be marred. This research work thus proposed an algorithmic framework to address the BSP problem, using the knowledge of it neighbourhood density to dynamically determine the threshold so as to adapt to both dense and sparse network while limiting the above stated constrains.
An appraisal of the contributions of herbalism to primary health care delivery in south west Nigeria
(2010) Kadiri, A. B.; Adekunle, A. A.; Ayodele, A. E.
Herbalism contributes significantly to the primary health care delivery system in the southwest Nigeria through sale and administration of different herbal medicinal preparations which are available in a number of ways like tinctures, herbal wine and elixirs, tisanes, decoctions, macerates, topical, poultices, whole herb consumption, syrup, extracts, inhalation, local rings, incision and rubbing, charm belt, and other charm apparels. Medicines may be hawked by the ambulatory vendors (apothecary) or patients consulting practitioners. Charges are relatively cheap, consultation is prompt and the medicines are reportedly efficacious. Non-exclusion of anybody from patronizing and being organized around people’s needs and expectations, which are two of the key elements of WHO to achieve the ultimate goal of primary health care of better health for all are affectively entrenched in the practice. We adopted and employed basic scientific method, anthropological training skills and study approaches in Humanities to elicit our findings. Government support is highly solicited
An artificial neural network estimation of global solar radiation at Ibadan, Nigeria using meteorological data
(2020) Nymphas, E.F.; Udomboso, C.G.
This paper estimates global solar radiation (Rs) from routinely measured meteorological parameters in the city of Ibadan, Nigeria, using artificial neural network method. Six combinations were used to estimate Rs namely (i) daily mean air temperature (T) and day of the year as inputs and global solar radiation as output, ((ii) daily mean relative humidity (RH) and day of the year as inputs and Rs as output (iii) daily mean T, daily mean RH and day of the year as inputs and Rs as output (iv) daily mean minimum relative humidity (RHmin) and day of the year as inputs and Rs as output, (v) daily mean minimum temperature (Tmin), daily RHmin and day of the year as inputs and Rs as output (vi) daily mean maximum temperature (Tmax), daily mean Tmin, daily mean RHmin, daily maximum relative humidity (RHmax) and day of the year as inputs and Rs as output. The neural network was trained with 3653 measured data between 1995 and 2004 and tested with data for 731 days between 2003 and 2004. The data for testing the neural network were not used for the training. The results obtained showed that the combination of RHmin, RHmax and day of the year gave the best estimate of Rs with MSE of 3.4124. This is followed by RHmin and day of the year with MSE of 3.4424. Daily mean air temperature and day of the year could not mimic the measured Rs; it gave MSE of 5.3345. It is concluded that Rs can be estimated for locations where only temperature and relative humidity data are available.
An electronic shopping system with a recommendation agent
(2009) Ojo, A. K.; Emuoyibofarhe, O. J.; Emuoyibofarhe, O. N.; Lala, O. G.; Chukwuemeka, C. U.
There is an inevitable need to improve the operation portfolio of the boutique, and erase problems like time consumption, inconsistency and a host of other problems encountered by most business enterprises. This research study focused on the design of a web based shopping system. The reason for the development of this system is because every shopping software system is precipitated by some business need which are: the need to correct a defect in an existing application, the need to adapt a legacy system to a changing business environment, the need to extend the functions and features of an existing application or the need to create a new product, service or system. A feasibility study was carried out through interviewing an entrepreneur (business proprietor) in order to acquire knowledge about the mode of operation of the boutique; also specialists in the field of fashion designing were interviewed to acquire knowledge that will be used by the proposed software agent to give recommendations online. The existing system was studied and deficiencies such as long queues, customer dissatisfaction and staff impatience, as well as the need for customers to get professional guidance. The Scripting language used for developing the database is MYSQL, and the application used in developing the database for this site is an SQL application called SQLYOG and it is compactable with MYSQL Server which is either wamp, xammp or zends. The system accepts input from the user whether an administrator or a customer, processes the input i.e. (carries out the required action on the input collected as specified by the system design) and produces an output (either a completed transaction report and receipt or an outfit recommendation). Interfaces were designed using PHP on Dreamweaver platform. MySQL Query Language on SQLYOG platform was used as a database tool to develop, organize and store all vital details about customers, suppliers, sales, product, and product categories. The proposed system is designed in a bid to improve speed, accuracy, storage capability, customer satisfaction, job flexibility for the staff as well as shopping flexibility for the customer and consistency in the boutique; it can be used by trained personnel as well as for general public due to its simplicity. This work elaborates on the implementation and use of software agents in global transaction i.e. people can transact from the various locations and their goods are delivered at their doorstep enabling them to save time and the stress involved in physically doing the shopping.