A Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to Knowledge Acquisition

Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to knowledge acquisition is proposed in this paper as a viable solution to the challenges of rule-based unwieldiness and sharp boundary problem in building a fuzzy rule-based expert system. The fuzzy models were based on domain experts’ opinion about the data description. The proposed approach is committed to modelling of a compact Fuzzy Rule-Based Expert Systems. It is also aimed at providing a platform for instant update of the knowledge-base in case new knowledge is discovered. The insight to the new approach strategies and underlining assumptions, the structure of FARME-D and its practical application in medical domain was discussed. Also, the modalities for the validation of the FARME-D approach were discussed

Design and Implementation of a Secured Census Information Management System

Census in most countries has been faced with various natural and human made barriers. Thus, the aim of this research is to develop a systematic, coordinated, and responsive database which will adequately interact with a web application by harnessing the strengths of computational science and biometrics. The programming language employed in the development of this web-based application was the C#.NET programming language. Microsoft Visual Studio was used as an integrated environment for the development of this tool. Microsoft SQL Server (2005) served as a relational database management application for handling the data used in this research. From the results obtained from this research work, it had shown that with design and implementation of a secured system information countries can make informed decisions for effective policy, planning and management of their ever-increasing populace and economy

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

An Improved Stock Price Prediction using Hybrid Market Indicators

In this paper the effect of hybrid market indicators is examined for an improved stock price prediction. The hybrid market indicators consist of technical, fundamental and expert opinion variables as input to artificial neural networks model. The empirical results obtained with published stock data of Dell and Nokia obtained from New York Stock Exchange shows that the proposed model can be effective to improve accuracy of stock price prediction

Business-to-consumer e-commerce in Nigeria: Prospects and challenges

The growth of Internet usage in Nigeria continues to increase, recording over 90% growth rate between 2000 and 2008. While businesses in Nigeria are reported to have online access with opportunity for ecommercial activities, customers in the country however access business websites only to source for information but make purchases the traditional way. This paper aims at assessing the prospects and challenges of Business-to-consumer (B2C) e-commerce implementation in Nigeria from the consumers’ perspective. Survey research was adopted for this study. Research hypotheses were formulated and questionnaire designed and administered randomly to 900 respondents. Collected data was used to evaluate the acceptance of B2C e-commerce using the extended technology acceptance model (TAM). The extended TAM combines task-technology fit, relationship related construct: trust and risk, and the two TAM constructs to determine factors influencing consumer acceptance of B2C e-commerce in Nigeria. Findings revealed that there are significant relationships between the model variables. Tasktechnology fit and perceived usefulness have significant relationships with intentions to use, having a correlation coefficient of 0.2623 and 0.2002 respectively. Similarly, the interrelationship among trust, perceived risk, and behavioral intention are significant. The effect of risk on trust was statistically showing that risk is a predictor of trust. Risk has a high significant on trust and trust in turn has low significant effect on behavioral intention. Adding TTF and its relationships to the TAM also fit the data. The relationship between task-technology fit, perceived ease of use, perceived usefulness and intention are significant

Improved Shellsort for the Worst-Case, the Best-Case and a Subset of the Average-Case Scenarios

Sorting involves rearrangement of items into ascending or descending order. There are several sorting algorithms but some are more efficient than others in terms of speed and memory utilization. Shellsort improves on Insertion sort by decreasing the number of comparisons made on the items to be sorted. This paper presents an Improved Shellsort algorithm that further decreases the number of comparisons made on the items to be sorted through a modified diminishing increment sort. The results obtained from the implementation of both Shellsort and the proposed algorithm shows that the proposed algorithm has a fewer number of comparisons made for all input sizes of the best and worst cases and for input size of twenty or less for the average case. By implication, this means that the proposed algorithm is faster in these situations. The strength of the algorithm however diminishes for only the average case of input size greater than twenty

The State of e-Banking Implementation in Nigeria: A Post-Consolidation Review

The most widely used e-Banking instrument in �igeria is e-Payment, particularly the automatic teller machine (ATM) card. However, with the adoption of e-Banking by all the banks in �igeria, the volume of cash in circulation has continued to increase pre-and-post bank recapitalization/consolidation exercise. Furthermore, some of the 25 banks that survived the exercise were found lately to have depleted their capital base and have lost credibility before the consumers, e-Banking implementation notwithstanding. Therefore, in this paper, we review the state of e-Banking implementation in �igeria and evaluate the influence of trust on the adoption of e-Payment using an extended technology acceptance model (TAM). Similarly, we investigate organizational reputation, perceived risk and perceived trust in the management of banks as a factor for enhancing customer loyalty. The findings in this work reveal that perceived ease of use and perceived usefulness are not only antecedent to ebanking acceptance, they are also factors to retain customers to the use of e-banking system such as organizational reputation, perceived risk and trust