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.

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.

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.

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

Augmented Reality Prototype for Visualising Large Sensors’ Datasets

This paper addressed the development of an augmented reality (AR) based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil leakages sensors datasets. Sensors generates significant amount of multivariate datasets during normal and leak situations which made data exploration and visualisation daunting tasks. Therefore a model to manage such data and enhance computational support needed for effective explorations are developed in this paper. A challenge of this approach is to reduce the data inefficiency. This paper presented a model for computing information gain for each data attributes and determine a lead attribute.The computed lead attribute is then used for the development of an AR-based scientific visualization interface which automatically identifies, localises and visualizes all necessary data relevant to a particularly selected region of interest (ROI) on the network. Necessary architectural system supports and the interface requirements for such visualizations are also presented

A Systematic Review of Health Care Ontology

Objective: The study sought to extracts information about the steps, methods, techniques, initiatives and strategies that is use in establishing ontology in the medical sector. Methods: The guideline that was employed for conducting the systematic review in this research work is that which was proposed by Kitchenham. The Google Scholar, Scopus and Web of science were searched for proceedings from conferences and journal papers between 2009 and 2018. Articles focusing on health care and ontology, health ontology and diagnosis system were selected. The AND operator was used in the Boolean language construction for the article search to limit articles presented to those that actually apply Ontology in the Health care. Selected articles were considered eligible based on their studies appropriately fitting into providing answers for the research questions that were presented in this research work within the last 10 years. Results: Twenty (20) research articles were included in the review; of the initiatives of the research works considered, Seven (7) were of Methodology, Two (2) were Technique based, Three (3) were Framework based, Two (2) were Process based while Six (6) were extensions of those in existence. Conclusions: The approaches considered were ontology based in terms of the use of Protégé-owl editor tool, SPARQL, Protégé 4, OWL 2, OWL, RDF, SNOMED CT. The main contributions include but not limited to Modelling of knowledge representation using Protégé for relating data and concepts with references to diabetes diseases, mobile based health care ontology, classification of diseases based on phenotypes, improvement in service delivery and availability of reliable health data. This Ontology heath care review which was carried out shows the need for Ontology based models to improve health service delivery for both the users (patients) and the care providers

Rapid screening of Musa species for resistance to black leaf streak using in vitro plantlets in tubes and detached leaves

This study investigated the utility of inoculation of in vitro plantlets in tubes and detached leaves as reliable and rapid assays for screening Musa genotypes against Mycosphaerella fijiensis, the causal agent of black leaf streak. In the first part of the study, three types of inocula were evaluated to determine suitability for in vitro inoculation. Inoculation of in vitro plantlets with mycelial fragments resulted in significantly (P< 0.05) higher levels of disease severity and faster rates of disease progress compared with inoculations using conidial suspensions. In the detached leaf assay, amending agar medium with plant hormones significantly (P< 0.0001) aided retention of green leaf color. Leaf pieces on medium containing gibberellic acid at 5mgliter had about 5% chlorosis at 52 days after plating. When in vitro plantlets in tubes and detached leaves of 10 Musa genotypes with different levels of disease resistance were inoculated with M. fijiensis, there were significant (P< 0.05) differences among genotypes in leaf area infected, incubation time, and symptom evolution time. For incubation time and leaf area infected, cultivars responded depending on their level of disease resistance, with resistant genotypes Calcutta-4 and PITA-17 having significantly (P= 0.001) longer incubation times and lower infected leaf areas compared with the susceptible cultivar Agbagba and moderately resistant cultivar FHIA-23. A similar pattern in cultivar response was observed for symptom evolution time. Leaf area infected was not significantly (P= 0.2817 for two-tailed t test) different when assessed using the two assays, and infected leaf areas in both assays were strongly correlated (r= 0.88, n= 48, P<0.0001). Although incubation times were significantly (P= 0.0062 for two-tailed ttest) different between the two assays, values from the two assays were strongly correlated (r= 0.69, n= 48, P< 0.0001). These results show that these two assays are rapid and space-effective, and can reliably be used for screening Musa genotypes for resistance to black leaf streak