Econometric Analysis of Rice Yield Determinants

The limited capacity of domestic rice production to match demand raises number of pertinent questions. What socio-economic factors determine the variation in the yield level among smallholder rice farmers?  This study attempts to determine the effect of some socio-economic variables namely: farm size, capital, technology, interest rate and government incentives to increase rice yield among farmers. Johansen cointegration, fully modified ordinary least squares error correction model as well as Granger causality test based on Toda-Yamamoto procedure were employed to determine the relationship and effect of the socio-economic variables on rice yield and causality among the variables. The findings reveal that the five variables analyzed were integrated of order one and hence co-integrated. The results show that government incentives, capital, farm size and technology have positive impact on rice yield. The Granger causality test results revealed that rice yield is Granger caused by farm size, capital, technology, interest rate and government incentives. The study concludes with policy recommendations to improve rice productivity yield among smallholder farmers in Nigeria by stakeholders increasing the area of land cultivated and improving farmers’ access to capital at low and single digit interest rate

AN ENHANCED TECHNOLOGY ACCEPTANCE MODEL TO MEASURE CUSTOMERS’ WILLINGNESS TO PAY MORE FOR SECURE SOFTWARE DEVELOPMENT

Securing information system (IS) has become a critical concern within many sectors of business organisations with significant resources being devoted to the control of security threats. Recently, it has been discovered that incorporating security at the time of development is the best option for having a robust system. This study explores factors that motivate IS owner’s willingness to pay extra cost for a secure software development and validates the relationships among the various variables. Enhanced Technology Acceptance Model (TAM) was used to investigate the factors that influences IS owner’s willingness to pay extra cost for secured software development. Out of all the constructs considered, Self-Efficacy (SE) is found to be significant (β= 0.617, P<0.05) which suggests that self-efficacy is useful for investigating willingness to pay for a secure software development. In addition, the strength of the linear association between Self-Efficacy and Behavioural Intention (BI) (R2 =0.354) implies that Self Efficacy has direct moderate impact on Behavioural Intention to pay extra cost for a secure software development.

PARAMETER VARIATION FOR LINEAR EQUATION SOLVER USING GENETIC ALGORITHM

Genetic Algorithm has been successfully applied for solving systems of Linear Equations; however the effects of varying the various Genetic Algorithms parameters on the GA systems of Linear Equations solver have not been investigated. Varying the GA parameters produces new and exciting information on the behaviour of the GA Linear Equation solver. In this paper,  a general introduction on the Genetic Algorithm, its application on finding solutions to the Systems of Linear equation as well as the effects of varying the Population size and Number of Generation is presented. The genetic algorithm simultaneous linear equation solver program was run several times using different sets of simultaneous linear equation while varying the population sizes as well as the number of generations in order to observe their effects on the solution generation. It was observed that small population size does not produce perfect solutions as fast as when large population size is used and small or large number of generations did not really have much impact on the attainment of perfect solution as much as population size.

Chemical and biological significance of naturally occurring additives on African black soap and its performance

The potassium ester (C11H23COO-K+) commonly known as African black soap was prepared by the action of palm kernel oil on cocoa pods. This was divided into four portions. Sample A contained the African Black soap without any modification, sample B was black soap modified with honey, sample C and sample D were modified with shear butter and coconut oil respectively. The pH, FTIR and phytochemical analyses of the samples were carried out. They were also screened for in-vitro antibacterial activities against two Gram-positive bacteria (Staphylococcus aureus and Bacillus subtilis) and two Gram-negative bacteria (Pseudomonas aeruginosa and Escherichia coli). The pH determinations showed that all the samples were alkaline in nature with sample A having the lowest pH of 8.90, while sample B had the highest pH of 9.58. FTIR analyses of sample A revealed strong bands assigned to the υ (C=O) frequency of a keto group at 1668 and 1560 cm-1 and a strong band at 1379 cm-1 assigned to the υ (C-O) frequency of the ester oxygen. The spectra of samples B, C and D showed no complexation through these oxygen donor atoms, but rather some interactions with other present molecules. Phytochemical analyses showed that samples A and D were rich in saponin, all the samples were rich in both flavonoids and terpenoids, while tannins and steroids were absent in all the samples. Antimicrobial studies showed that only sample B was active against Staphylococcus aureus, while samples A, C and D were inactive against all tested microorganisms.Keywords: Additives, African Black Soap, Phytochemical and Antimicrobia

Goldmine Tailings Stabilization using Quarry Dust and Coal Ash for Pavement Applications - A Review

The quest to improve the properties of soil and other construction materials by incorporating industrial and agricultural wastes is a growing concern for the construction industry. Many researchers have recently focused on employing waste materials as stabilizers due to their good pozzolanic interactions with soil particles.  Its significance in civil engineering projects such as foundations in buildings and pavement construction cannot be overemphasized. The construction of pavements usually involves using large quantities of natural earth/aggregate materials, often mixed with conventional stabilizers (cement, lime, and bitumen). There is already a shortage of natural aggregate materials in many developing nations. However, a significant quantity of waste, such as mining tailings, is generated by mining industries yearly. In contrast, the disposal of these wastes is not only expensive but has also resulted in various ecological and environmental problems.  The literature has already explored methods of stabilization and solidification of mining tailings employing conventional agents. However, the use of traditional stabilizers indicates an important source of contamination for the environment. Therefore, alternative stabilizing materials are needed. The approach to this literature review included a systematic procedure for locating, choosing, and evaluating sources. The logic for the sources’ selection prioritized contemporary, peer-reviewed studies that particularly address the geotechnical properties of industrial waste products in road construction. This study reviews the geotechnical properties of industrial waste products, such as goldmine tailings, quarry dust, and coal ash and the technical benefits of using them for pavement construction

A FRAMEWORK FOR ONTOLOGY- BASED DIABETES DIAGNOSIS USING BAYELSIAN OPTIMIZATION TECHNIQUE

Diabetes Management System (DMS) is a computer-based system which aid physicians in properly diagnosing diabetes mellitus disease in patients. The DMS is essential in making individuals who have diabetes aware of their state and type. Existing approaches employed have not been efficient in considering all the diabetes type as well as making full prescription to diabetes patients. In this paper, a framework for an improved Ontology-based Diabetes Management System with a Bayesian optimization technique is presented. This helped in managing the diagnosis of diabetes and the prescription of treatment and drug to patients using the ontology knowledge management. The framework was implemented using Java programming language on Netbeans IDE, Protégé 4.2 and mysql. An extract of the ontology graph and acyclic probability graph was shown. The result showed that the nature of Bayesian network which has to do with statistical calculations based on equations, functions and sample frequencies led to more precise and reliable outcome.   &nbsp

Influence of Human Activities on the Water Quality of Ogun River in Nigeria

The quality of Ogun River in south-west, Nigeria was investigated by a field survey; covering the dry season and rainy season. Water samples were collected from seven sites (including an Abattoir, a market, residential community and a brewery); analysis of the physico-chemical parameters using standard methods and their environmental effects on the river were investigated. Generally, the value/degree of dissolved oxygen, phosphate, BOD, COD, pH, temperature, hardness from the sites during the rainy and dry seasons were compared with the World Health Organization (WHO) standards for domestic and commercial water. The traces of some hazardous physical and chemical impurities in the river were above the acceptable limits; and thereby pose a health risk to several rural communities who rely heavily on the river primarily as their source of domestic water. The study revealed a need for continuous pollution monitoring and management program of surface water in Nigeria. Keywords: surface water, water quality, water pollution, field survey, physico-chemical analysi

INVESTIGATION OF FACTORS AFFECTING CLOUD COMPUTING ADOPTION IN NIGERIA

Cloud computing is a viable alternative for meeting the technological needs of many  enterprises with the benefits of instantaneous computing resource fulfillment, technology expenditures at lower costs, common technology platforms that can facilitate standardization and decreased  need for internal technology support personnel. This paper examined the behavioral intention to adopt cloud computing services in large and small organization using an Enhanced Technology Acceptance Model (ETAM). The aim is to investigate the factors affecting cloud computing adoption in Nigeria. The model includes variables that other research has found related to adoption of new computing services and technologies. Regression Analysis was then deployed to test the research hypotheses. The result of regression analysis revealed that attitude and adopters ability to use cloud computing (self-efficacy) were better predictor of intention; perceived usefulness and perceived ease of use of cloud computing were better predictor of attitude; perceived ease of use and the relevant of cloud computing to adopters’ work (job relevance) were the predictor of perceived usefulness.

Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review

In this paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa. The presented bibliometric analysis study consists of 2761 machine learning-related documents, of which 98% were articles with at least 482 citations published in 903 journals during the past 30 years. Furthermore, the collated documents were retrieved from the Science Citation Index EXPANDED, comprising research publications from 54 African countries between 1993 and 2021. The bibliometric study shows the visualization of the current landscape and future trends in machine learning research and its application to facilitate future collaborative research and knowledge exchange among authors from different research institutions scattered across the African continent