Faith-Michael E. Uzoka

An experimental comparison of fuzzy logic and analytic hierarchy process for medical decision support systems

The task of medical diagnosis is a complex one, considering the level vagueness and uncertainty management, especially when the disease has multiple symptoms. A number of researchers have utilized the fuzzy-analytic hierarchy process (fuzzy-AHP) methodology in handling imprecise data in medical diagnosis and therapy. The fuzzy logic is able to handle vagueness and unstructuredness in decision making, while the AHP has the ability to carry out pairwise comparison of decision elements in order to determine their importance in the decision process. This study attempts to do a case comparison of the fuzzy and AHP methods in the development of medical diagnosis system, which involves basic symptoms elicitation and analysis. The results of the study indicate a non-statistically significant relative superiority of the fuzzy technology over the AHP technology. Data collected from 30 malaria patients were used to diagnose using AHP and fuzzy logic independent of one another. The results were compared and found to covary strongly. It was also discovered from the results of fuzzy logic diagnosis covary a little bit more strongly to the conventional diagnosis results than that of AHP.

Conceptualizing a model for adoption of cloud computing in education

We developed a model for cloud computing adopting in education.Triangulation of two popular adoption theories used as theoretical basis.We contextualized the adoption process for developing countries.Socio-cultural factors were found to be crucial for sub-Saharan Africa.Results demonstrability not supported as critical factor for adoption model. Cloud computing is a pervasive computing paradigm that has revolutionized how computer infrastructure and services are delivered. Current research trends on cloud computing have been focused on the technology, applications, costs, benefits, and security of cloud computing at the organizational level within small and medium sized enterprises. Little research attention has been paid on adoption and usage of cloud computing at educational establishments and how contextual factors can influence diffusion and adoption of cloud computing. Universities in developing countries are faced with challenging socio-economic and political constraints that limit their ability to invest in expensive information systems to compete on the global stage. Using constructs from the diffusion of innovation theory and the technology acceptance model, this paper proposes a model that takes account of contextual, economic, and technological influences in the perception and adoption of cloud computing at universities in sub-Saharan Africa. Results from a pilot study, based on the model, through a survey of university lecturers and IS experts shows reliability and validity of the instrument and supports its usage for a more extensive study. Implications, potential contributions to research, and suggestions for future study are discussed.

Clinical decision support system (DSS) in the diagnosis of malaria: A case comparison of two soft computing methodologies

The purpose of this study is to make the case for the utility of decision support systems (DSS) in the diagnosis of malaria and to conduct a case comparison of the effectiveness of the fuzzy and the AHP methodologies in the medical diagnosis of malaria, in order to provide a framework for determining the appropriate kernel in a fuzzy-AHP hybrid system. The combination of inadequate expertise and sometimes the vague symptomatology that characterizes malaria, exponentially increase the morbidity and mortality rates of malaria. The task of arriving at an accurate medical diagnosis may sometimes become very complex and unwieldy. The challenge therefore for physicians who have limited experience investigating, diagnosing, and managing such conditions is how to make sense of these confusing symptoms in order to facilitate accurate diagnosis in a timely manner. The study was designed on a working hypothesis that assumed a significant difference between these two systems in terms of effectiveness and accuracy in diagnosing malaria. Diagnostic data from 30 patients with confirmed diagnosis of malaria were evaluated independently using the AHP and the fuzzy methodologies. Results were later compared with the diagnostic conclusions of medical experts. The results of the study show that the fuzzy logic and the AHP system can successfully be employed in designing expert computer based diagnostic system to be used to assist non-expert physicians in the diagnosis of malaria. However, fuzzy logic proved to be slightly better than the AHP, but with non-significant statistical difference in performance.

Decision support system for library acquisitions : a framework

Purpose – Acquisition of books, serials and other educational materials by libraries involves a complex decision process; especially when there are many books to choose from and the resources are meager. Attempts have been made in the past to take decisions concerning library acquisitions using structured information such as cost, availability of funds, and number of copies needed by the library, author and year of publication. The purpose of this research is to provide a framework for the combination of both structured and unstructured information in the library acquisitions decision process.Design/methodology/approach – The research methodology involves the design of a knowledge‐based system, which is powered by the classical method of the analytical hierarchy process (AHP), which carries out a pairwise comparison (PWC) of acquisition decision variables.Findings – The results of the study show that decision variables involved in library acquisitions can be grouped and hierarchically structured. The appl...

Fuzzy rule-based framework for the management of tropical diseases

The application of the conventional symbolic rules found in knowledge base technology to the management of a disease suffers from its inability to evaluate the degree of severity of a symptom and by extension, the degree of the illness. Fuzzy logic technology provides a simple way to arrive at a definite conclusion from vague, ambiguous, imprecise and noisy data (as found in medical data) using linguistic variables that are not necessarily precise. In order to achieve this, a study of a knowledge base system for the management of diseases was undertaken. The root sum square of drawing inference was employed to infer the data from the rules developed. This resulted in the establishment of some degrees of influence on the diseases. Using malaria as a case study, a system that uses Visual Basic .Net development environment was developed and the results of the computations are presented in this research.

Understanding the factors that determine registered nurses' turnover intentions.

Turnover among registered nurses (RNs) produces a negative impact on the health outcomes of any health care organization. It is also recognized universally as a problem in the nursing profession. Little is known about the turnover intentions and career orientations of RNs working in Calgary, Alberta, Canada. The aim of this study is to contribute to the knowledge of and to advance the discussion on the turnover of nursing professionals. The study population consisted of RNs employed in the five major hospitals in Calgary. There were 193 surveys returned, representing a response rate of 77.2%. The results show that age and education have a negative effect on turnover intention. Education was found to have a significant negative effect on career satisfaction but not on job satisfaction and organizational commitment. Length of service has a significant negative effect on turnover intention. Role ambiguity has significant highly negative effect on career satisfaction. Growth opportunity and supervisor support have a very significant positive effect on job satisfaction, career satisfaction, and organizational commitment. External career opportunities and organizational commitment do not seem to have a significant effect on turnover intention. Career satisfaction, on the other hand, had negative significant effects on turnover intention.

B2C e-commerce development in Africa: case study of Botswana

The global wave of ICT development has become a strong driving force in almost every aspect of human endeavor. Electronic commerce (e-commerce) is fast gaining a prominent place in the global marketing matrix. The volume of transactions that are carried out over the internet globally is extremely huge. It is estimated that in the next decade, e-commerce activities would be a major source of foreign exchange, and a key indicator of national development. Developing countries, especially in Africa, tend to lack the infrastructural, economic, and socio-political framework for the development of electronic-commerce in comparison to developed countries. This study investigates the level of development of e-commerce in Botswana, an African country with a good level of e-readiness. The results of the study show that e-commerce development in Botswana is still at the level of intensity, whereby ICT is utilized in most aspects of human endeavor, while most organizations have a low adoption of e-commerce. A cluster analysis of the surveyed organizations shows that only 44% performed well on the e-commerce indicators.

A framework for user-centric model for evaluating the performance of distributed software system architecture

Highlights? Most software evaluation models are machine centric. ? There is need to match software factors with organizational variables. ? Paper presents a neuro-fuzzy based user centric model. In this work we carried out a review of models for evaluating the performance of distributed software system architecture (DSSA) and Information System (IS) success evaluation models with a view to establishing the utilization of organizational variables in the evaluation of DSSA performance. The findings from the review show that the existing DSSA performance evaluation models are machine-centric and existing IS success measurement models do not map organizational variables with DSSA components. In view of these, we developed a user-centric model for DSSA performance evaluation using organizational variables. Our model utilizes neuro-fuzzy logic in matching organizational/user variables with DSSA evaluation factors.

An investigation of factors affecting biometric technology adoption in a developing country context

This paper examines the prospects of biometrics usage in Botswana. It aims to identify and understand the factors that are significant in explaining the intention to adopt a biometric technology and to explore the potential role of biometric technologies in driving service excellence, productivity and security. The results of the study indicate that although industries may be aware of the benefits and advantages of using a biometric technology for improving security and productivity of an organisation, this has proven to have no significant effect on deciding whether to adopt a biometric technology. The factors that significantly affect the intention to adopt a biometric technology are ease of use, communication, size of organisation and type of organisation.

Expert systems and uncertainty in medical diagnosis: a proposal for fuzzy-ANP hybridisation

Major research efforts in decision support systems for medical diagnosis have focused on the hypothesis testing and management of uncertain and imprecise decision variables aimed at obtaining optimal inferences. In this study, a survey of such systems and methods is carried out. The study identifies medical diagnosis as involving imprecise information in a multi-criteria decision situation. We propose a hybrid fuzzy based analytic network process (ANP) system for managing the hierarchical structuring and imprecision associated with medical diagnosis. The justification being that fuzzy-ANP system is capable of accommodating inherent uncertainty and vagueness in multi-attribute/multi-criteria decision-making with hierarchical structuring and feedback dependence.