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

Cybercrime Pervasiveness, Consequences, and Sustainable Counter Strategies

As our connectivity and dependency on technology increases, so does our vulnerability. Technology has provided not only new tools, but also new opportunities for criminals in the digital world. The abuse of new technologies has been threatening economic and Jinancial security and actually devastating the lives of affected indivicluals. In Nigeria, cybercrime has recorded mostly foregin-based individuals and organizations as victims thereby getting Nigeria ranked among the nations with notorious pemasiveness of high-tech crimes. Indeed, adequately formulating a strategy to contain the menace of cybercrime presents aformidable challenge to law enforcement. This paper x-rays noted instances of cybercrime pervasiveness, its devastating consequences, and up-to-date countermeasures in Nigeria It develops an enforceable/sustainable framework to determine how critical infrastructures are put at risk snd how law enforcement should react in responding to the threats

On Sharp Boundary Problem in Rule Based Expert Systems in the Medical Domain

Recently the application of the conventional rule based expert system of disease risk determination in medical domains has increased. However a major limitation to the effectiveness of the rule based expert SyStem approach is the sharp boundary problem that leads to underestimation or overestimation of boundary cases, which ultimately affects the accuracy of their recommendation.In this paper an expert driven approach is used to investigate the viability a fuzzy expert system in the determination of risk associated with coronary heart disease with regards to the sharp boundary problem in rule based expert system

REALISING POLITICAL STABILITY IN NIGERIA THROUGH ICT-TRANSFORMED GOVERNMENT AT GRASSROOTS

Political processes are undergoing profound changes due to the challenges imposed by globalization processes to the legitimacy of policy actors and to the effectiveness of policymaking. Political stability emerges from the perceptions of the likelihood that the government will not be destabilized or overthrown by unconstitutional or violent means, including domestic violence and terrorism. Civil conflicts can lead to the destruction of limited resources, economic infrastructure, institutions of political stability and governance, and ethnic and social fabric. Public services are failing the poor in most countries making building public confidence in e-Government remain an agenda item for the countries. Nigerian Governments have been consistently facing challenges to reposition, reinvent, and realign themselves in light of increasing expectations for demonstrable results and enhanced responsiveness for a more cost effective, citizen-centric, and networked government evidenced by several incessant conflicts arising from marginalization of grassroots communities. Access to primary and authentic source of information at the grassroots is key to transparent and responsive government. The ICTs support for traditional governance is thus an effort aimed at building the capacity of indigenous political institutions, to participate in modern governance, have access to information and knowledge as well as to share experiences among themselves and with other stakeholders. This paper examines challenges and opportunities for transforming government and building an information-rich society. It provides strategies to digitize local government administration as a panacea to gaining access to authentic and reliable demographic data/information for meaningful decision-making processes towards attaining political stability from the grassroots level of governance using Nigeria’s Ondo State Local Government Areas as case study. It concludes by advocating the adoption and implementation of an “EATING” model, a bottom-up to participatory community engagement and development towards achieving political stability. Keywords: ICT-transformed, local government, political stability, responsiveness, transparenc

Clinical Decision Diagnosis Support System for Complementary and Alternative Medicine Practitioners in Lifestyle-related Diseases Management

Chronic diseases accounted for 60% of all deaths – corresponding to a projected 36.65 million deaths worldwide in 2007. 2.8% of the world population suffers from diabetes mellitus and it may cross 5.4% by the year 2025. Hypertension is a major burden on health care. Prevalence of lifestyle-related diseases increases. Low accessibility to and non-affordability of orthodox medicine by rural dwellers and their need to keep healthy to be economically productive have led to their dependence on medicinal plants to remedy afflictions. Complementary and Alternative Medicine (CAM) attracts patronage due to patients’ dissatisfaction with conventional health care, a desire for treatment and care that work, good relationship with practitioner, provision of information, a desire for greater control over one’s health, and a desire for cultural and philosophical congruence with personal beliefs about health and illness. Medicinal plants’ threatened sustainability makes adulteration and species’ substitutions reduce their efficacy, quality and safety. It was found that CAM practitioners who participated in this study relied heavily upon knowledge that had 'stood the test of time' (traditional theory and practice) and 'that which worked' (experientially based knowledge) as the basis for clinical decision-making. The safe, effective and efficient delivery of client care is informed primarily by sound clinical decision making. Body mass index (BMI) plays a significant role in the process. Strategies that guide practitioners through the process of decision making may not only foster professional excellence in CAM practice, but also help to improve the quality of client care. Clinical decision-making is a complex process that is reliant on accurate and timely information. Clinicians are dependent (or should be dependent) on massive amounts of information and knowledge to make decisions that are in the best interest of the patient. CAM practitioners of modern time need currency and timeliness on computations of patients’ body mass index, waist circumference and body shape combination; product/therapy data on therapeutic efficacy; product quality and safety; adverse reactions and herb-drug interactions. This paper presents a clinical decision diagnosis system supporting CAM practitioners to effectively treat emerging lifestyle-related diseases with medicinal plants. Keywords: body mass index, complementary and alternative medicine, lifestyle-related diseases, medicinal plants, clinical decision support syste

A framework for an Integrated Mining of Heterogeneous data in decision support systems

The volume of information available on the Internet and corporate intranets continues to increase along with the corresponding increase in the data (structured and unstructured) stored by many organizations. Over the past years, data mining techniques have been used to explore large volume of data (structured) in order to discover knowledge, often in form of a decision support system. For effective decision making, there is need to discover knowledge from both structured and unstructured data for completeness and comprehensiveness. The aim of this paper is to present a framework to discover this kind of knowledge and to present a report on the work-in-progress on an on going research work. The proposed framework is composed of three basic phases: extraction and integration, data mining and finally the relevance of such a system to the business decision support system. In the first phase, both the structured and unstructured data are combined to form an XML database (combined data warehouse (CDW)). Efficiency is enhanced by clustering of unstructured data (documents) using SOM (Self Organized Maps) clustering algorithm, extracting keyphrases based on training and TF/IDF (Term Frequency/Inverse Document Frequency) by using the KEA (Keyphrases Extraction Algorithm) toolkit. In the second phase, association rule mining technique is applied to discover knowledge from the combined data warehouse. The final phase reflects the changes that such a system will bring about to the marketing decision support system. The paper also describes a developed system which evaluates the association rules mined from structured data that forms the first phase of the research work. The proposed system is expected to improve the quality of decisions, and this will be evaluated by using standard metrics for evaluating the interestingness of association rule which is based on statistical independence and correlation analysis

Multimedia-based Medicinal Plants Sustainability Management System

Medicinal plants are increasingly recognized worldwide as an alternative source of efficacious and inexpensive medications to synthetic chemo-therapeutic compound. Rapid declining wild stocks of medicinal plants accompanied by adulteration and species substitutions reduce their efficacy, quality and safety. Consequently, the low accessibility to and non-affordability of orthodox medicine costs by rural dwellers to be healthy and economically productive further threaten their life expectancy. Finding comprehensive information on medicinal plants of conservation concern at a global level has been difficult. This has created a gap between computing technologies’ promises and expectations in the healing process under complementary and alternative medicine. This paper presents the design and implementation of a Multimedia-based Medicinal Plants Sustainability Management System addressing these concerns. Medicinal plants’ details for designing the system were collected through semi-structured interviews and databases. Unified Modelling Language, Microsoft-Visual-Studio.Net, C#3.0, Microsoft-Jet-Engine4.0, MySQL, Loquendo Multilingual Text-to-Speech Software, YouTube, and VLC Media Player were used. Keywords: Complementary and Alternative Medicine, conservation, extinction, medicinal plant, multimedia, phytoconstituents, rural dweller

Improving Customer Relationship Management through Integrated Mining of Heterogeneous Data

The volume of information available on the Internet and corporate intranets continues to increase along with the corresponding increase in the data (structured and unstructured) stored by many organizations. In customer relationship management, information is the raw material for decision making. For this to be effective, there is need to discover knowledge from the seamless integration of structured and unstructured data for completeness and comprehensiveness which is the main focus of this paper. In the integration process, the structured component is selected based on the resulting keywords from the unstructured text preprocessing process, and association rules is generated based on the modified GARW (Generating Association Rules Based on Weighting Scheme) Algorithm. The main contribution of this technique is that the unstructured component of the integration is based on Information retrieval technique which is based on content similarity of XML (Extensible Markup Language) document. This similarity is based on the combination of syntactic and semantic relevance. Experiments carried out revealed that the extracted association rules contain important features which form a worthy platform for making effective decisions as regards customer relationship management. The performance of the integration approach is also compared with a similar approach which uses just syntactic relevance in its information extraction process to reveal a significant reduction in the large itemsets and execution time. This leads to reduction in rules generated to more interesting ones due to the semantic clustering of XML documents introduced into the improved integrated mining technique

An Empirical Analysis of Mobile Phone Users for Competitive Business Intelligence

With the current globalization drive, most firms rely on Competitive Intelligence to help position them strategically through effective decision-making based on Customer Relationship Management {CRM}, marketing activities and competitors' vulnerability. It is of interest therefore to make decisions based on accurate inferences. Association rules have been widely used in data mining to find patterns in data that reveal combinations that occur at the same time which are called rules. The rules are sometimes too numerous to be used in decision making, hence, the interestingness of the rules are used to select the subset to act upon. This paper aims at evaluating the interestingness of rules gotten from applying association rule mining algorithm to data received from questionnaires of mobiles phone users in Nigeria. A patterr. is interesting if it is easily understood by humans, potentially useful and novel. The evaluation of the rule is done objectively using statistical independence and correlation analysis. This research has helped to reduce the uncertainty and inaccuracy of rules f~om which decisions are based towards the competitive advantage of an organization. Findings from the research revealed the areas of strength and weakness of mobile phone manufacturers and this understanding is used to provide competitive business decisions. which will in turn contribute to the profit of the organizatio