FACULTY OF PHYSICAL SCIENCES

I have used the newly formulated Analytical Equivalent Crystal Theory method which is a modification of the AECT method is use to calculate the surface energies and surface relaxation for three low-index surface of Bcc transition metals. Fe,W and Mo. Our calculations predicted top layer contractions for the Bcc metals in reasonable agreement with experiment and theory. The data may be used as a starting point for models of surface science phenomena. The accuracy of the surface energies and relaxation is established from a comparison with other theoretical results and experiments

Access points, also known as wireless networks, provide networking professionals with an enterprise-level feature set along with a mobile, flexible, and affordable wireless local area network (LAN) solution. A wireless device that is set up as a wireless access point serves as the hub of a stand-alone wireless network or as a connecting point between wireless and wired networks. Wireless users in large facilities can move around the building and still have seamless, continuous network access as long as they are within radio range of a wireless access point. The primary objectives of this study are to comprehend the nature of wireless
networks, their various varieties, their organizational structure, and the benefits they provide. Wireless networks have witnessed a sharp rise in both their capacity and user base in recent times. Furthermore, the volume of data handled by these networks has increased. The foundation of cloud computing is the concept of "Software as a Service" (SaaS), in which all data processing happens on the cloud. Although the use of wireless networks has increased, not much has been done to strengthen their security, leaving them open to attacks by unauthorized users. The Wi-Fi network is one of the most popular wireless networks that is still open to assaults. Over the years, numerous updates have been made to the IEEE 802.11 protocol (Wi-Fi), with the majority of these updates concentrating on boosting the rate of communication overall.

The global threat of cancer to human health is significant. It is one of the main factors contributing to rising mortality and morbidity, particularly in developing African countries. The lack of medical professionals in Nigeria's development of medical health centers is one of a number of issues related to cancer. Additionally, the fatality rate from most cancers, including skin cancer, has increased due to a lack of awareness, making treatment more challenging. The research suggests using machine learning approaches for erythemato squamous disease diagnosis. The objective of the work is to develop and implement a hybrid ensemble approach using filter-embedded feature selection and ensemble of classifiers through bagging, boosting, and stacking. The classification algorithms adopted in this study includes decision trees, naive bayes, multilayer perceptrons, support vector machines, KNN, and logical regression. While some of the feature selection methods are chi-square, information gain, reliefF, gain ratio, and recursive feature selection - SVM. The performance of our models showed improved accuracy especially when using the ensemblemethods. This project proves that using ensemble methods to predict erythemato squamous disease can address some of our challenges and the project also shows future prospects.

This study focuses on the development of a web application-based Census Management System, designed to streamline the process of collecting, managing, and analyzing census data. The system aims to enhance the efficiency and accuracy of census operations by automating data collection, reducing human error, and improving the overall management of census records. Key features of the system include real-time data entry, secure user authentication, data validation, and an intuitive interface for both administrators and users. Additionally, the system provides tools for generating reports and visualizing census data, facilitating decision-making and policy formulation. This webbased approach ensures easy access, scalability, and seamless integration with existing infrastructure. The development of this system contributes to improving the management and utilization of census data, offering a more effective solution for national or regional demographic surveys.

Breast cancer remains a significant health concern worldwide, necessitating the development of accurate and reliable diagnostic models. This project aims to construct an ensemble model utilizing the Wisconsin Breast Cancer dataset, which has been preprocessed using correlation coefficient and ReliefF feature selection techniques. The dataset is subsequently trained using three popular classifiers: Support Vector Machine (SVM), Naive Bayes, and Logistic Regression. The results demonstrate that the proposed ensemble model leveraging SVM, Naive Bayes, and Logistic Regression classifiers, along with voting, bagging, and stacking techniques, yields superior performance with 96% accuracy compared to individual classifiers and existing benchmark models. This project contributes to the field of breast cancer diagnosis by providing an effective and reliable ensemble model that can assist
medical professionals in making accurate and timely predictions for breast cancer classification.

The research project aim to take advantage of all available information for analyzing data as a
critical component for its success it will be looking at other business intelligence system, their
strengths and weaknesses, errors, strategies etc and build on it.

Throughout the world, plants are used traditionally to treat many ailments, particularly infectious diseases, such as diarrhea, fever, cold as well as for birth control and dental hygiene. This is as a result of the presence of various secondary metabolites in them. In this study, the leaves of D. metel were collected, dried and pulverized. Then, the powdered sample was extracted using ethyacetate solvent and screened for the presence of phytochemicals. After this, the extract was characterized by High Performance Liquid Chromatography (HPLC) to determine its specific constituents. The result of the phytochemical study showed the presence of five (5) out of nine (9) secondary metabolites that were investigated. These include glycosides, phenolics, alkaloids, steroids, and eugenols. However, the following metabolites such as saponins, terpenoids, flavonoids, and tannins were absent. The HPLC study showed an abundance of useful constituents with pharmacological activities such as atropine, scopolamine and quercetin. These compounds have been seen to perform health remediating functions such as antidepressant, anti-inflammation, anxiolytic, and many more. The findings of this study proves the D. metel plant is composed of useful bioactive substances. Therefore, the D. metel plant has a huge potential in performing medicinal functions to humans, so it is advisable to either consume it or utilize it in the discovery of novel drugs.

The adsorption properties of the Dangara middle layer clay were examined to determine the adsorption of the heavy metal, zinc. The effect of variation in parameters such as, adsorbent dosage, initial concentration, contact time, pH and temperature were observed. The result obtained showed that the optimum equilibrium adsorption was 99.578% at pH 8, 99.576% at 1.0g adsorbent dosage, 99.578% at contact time of 60minutes, 99.61% at 10ppm initial concentration, and 99.61% at temperature of 40ºC. The experimental data were analyzed by both the Langmuir and Freundlich isotherm model. The result obtained shows that the Dangara middle layer clay is an effective adsorbent for the adsorption of the heavy metal Zinc from an aqueous solution.

The extent of groundwater and soil pollution arising from an open dumpsite was carried out to examine the physico-chemical and trace metals status in Osubi, Delta State. Twenty two (22) soil samples were collected randomly at depths of 0-15 cm, and 15-30 cm and one control (natural environment). While sixteen (16) groundwater samples were collected through random sampling technique for analysis. The soil samples were digested into solution using aqua regia and analyzed using the Atomic Absorption Spectrometer (AAS), [buck model 210 VGP]. The results of the analysis was then subjected to statistical treatment (One-way Analysis of Variance), Spearman’s Correlation Coefficient and Pollution Load Index to ascertain significant difference among the trace metals, association and status of contamination/pollution respectively. Result from the analysis showed that both groundwater and soil samples in the study area is acidic with pH values ranging from 5.28-5.96, and 2.30-6.20 respectively. The level of average metal contents obtained from soil samples at the different depths is as follows: Arsenic; 10.58-20.4 mg/kg, Manganese; 1.42-3.58 mg/kg, cadmium; 1.05-3.46 mg/kg, Chromium; 1.61-4.55 mg/kg, Lead; 2.11-3.71 mg/kg, Zinc; 5.77-15.5 mg/kg, Copper; 1.69-3.23 mg/kg, Cyanide; 0-0.005 mg/kg, Nickel; 1.31-4.59 mg/kg and Vanadium; 1.24-0.3.95 mg/kg which were much higher than that of the control. The correlation result between the analyzed parameters in hand-dug wells and borehole samples, revealed positive and negative correlation coefficients at r(0.01) and r(0.05) indicating strong association between them, which probably reflects their related source of contamination. However, correlation was also not significant among some parameters in the groundwater samples indicating an uncommon source of contamination. Calculated pollution load index (PLI) indicated that location SS8 had maximum pollution load index of 2.15 and a minimum pollution load index value of 1.80 was obtained at location SS6. The order of pollution load index per location for the sediments is as follows: SS8 > SS5 > SS9 > (SS4=SS7=SS10) > SS2 > SS3 > SS6. While the order of contamination factor (CF) revealed among the heavy metals is as follows: Mn> V > Cr > Ni > Cd > Zn > As >Pb> Cu. The results revealed that both the groundwater and soil were slightly- moderately contaminated. It is hereby reco mended that groundwater monitoring and proactive steps be taken to minimize gradual accumulation of these contaminants from the dumpsite.

One hundred (100) ditch cutting samples from OK-1 well, Greater Ughelli Depobelt, Niger Delta Basin, Southern Nigeria, collected from Research and Development Division of Shell Petroleum Development Company was subjected to lithological analysis with the aim of identifying the lithofacies, lithozones, source rocks and seal or caprocks of the analyzed section of the well. The lithological analysis was carried out between six thousand, one hundred and forty (6140ft) and twelve thousand, seven hundred and forty (12740ft). Various lithofacies, together with their associated mineral units were observed mainly by visual examination, taking note of grain sizes, shapes, color, sorting patterns, presence of plant materials and lignitemstreaks of the samples provided. Results of the lithological analysis yielded two (2) lithofacies, which include shale and sandy shale, with presence of plant materials and streaks of lignite, and as a result six (6) lithozones were established. All the lithofacies within the analyzed section of The well were regarded as potential source rocks, because they satisfied the lithological characteristics of source rocks. Seal or caprocks potential of the analyzed section could not however be totally ascertained, because the shales and sandy shales were not observed to be deposited on a reservoir rock by reason of their stratigraphic position, despite satisfying the lithological characteristics of seal or caprock. The analyzed section 6140ft- 12740ft of the OK-1 well was inferred to be the Agbada Formation (paralic sequence) of the Niger Delta Basin, by reason of depth and lithofacies within the section which are basically shale and lesser percentages of sand particles.