An Expert System for Foundation Design of Buildings: Case Demonstration of a GCPM-Integrated Prototype System

Author(s):  
J.F. van den Adel ◽  
S.H. Al-Jibouri ◽  
U.F.A. Karim ◽  
M. Mawdesley
2003 ◽  
Vol 1 (1) ◽  
pp. 55-74
Author(s):  
J.F. van den Adel ◽  
S.H. Al‐Jibouri ◽  
U.F.A. Karim ◽  
M. Mawdesley

2014 ◽  
Vol 651-653 ◽  
pp. 2063-2066
Author(s):  
Chung C. Chang ◽  
Shu Hui Tsai

This study combines an expert system with cloud computing, establishing the expert system on a cloud platform to provide users with assistance and recommendations about diabetes and diabetic retinopathy diagnosis. This study mainly adopts an empirical approach. The first step is to define the research topic, and then propose questions and the research purpose based on the research background and motivation. Research results are related to three areas, specifically diabetes and diabetic retinopathy, expert systems, and cloud computing. After analyzing and organizing the literature, the research method and scope of research are established with a system design based on the three areas. This study then develops a prototype system to validate, evaluate, and test the expert system. Finally, study gives the conclusion and recommendations.


2016 ◽  
Vol 25 (1) ◽  
pp. 117
Author(s):  
Indah Puji Astuti ◽  
Irman Hermadi ◽  
Agus Buono ◽  
Kikin H Mutaqin

Early detection and identification of soybean diseases is important to support better productivity of soybean. The demand for the availability of an expert on soybean disease is very high, especially for the beginners in the field of agriculture. However, the number and time allocation of the experts are not adequate to serve farmers located in different geographical areas. Therefore, an expert system is proposed as a solution to use as a diagnostic tool for soybean diseases just like a human expert. It will be even easier when the system is implemented into an Android-based application to be used anywhere and anytime. The objective of this study was to analyze and design an expert system for early identification of soybean diseases. This study was adopting the Expert System Development Life Cycle (ESDLC) approach. The stages were project initialization, knowledge engineering process, and implementation. The study was started with the project initialization phase that conducted in September 2014 and the completion of the implementationphase in August 2015. The results of research were in the form of document analysis and prototype system.


Author(s):  
J. F. van den Adel ◽  
S. H. Al-Jibouri ◽  
U. F. A. Karim ◽  
M. Mawdesley

Ethiopia is among the African countries that are following stereotype of Agricultural Development Led Industrialization (ADLI). In fact, textile and garment sector is the second largest manufacturing industry that plays a significant role in the development of Ethiopian economy. However, the textile and garment sector is still in its embryonic stage and the production quality is rather poor, even when compared with other developing countries. In light of this, the researchers argued that the Ethiopian textile and garment sector is not competitive. Behind the low performance of the Ethiopian textile and garment industry, there is also lack of specialized and experienced man power. Therefore, unless a technological improvement of the industry is undertaken, it may not be able to achieve the set objectives The researchers assess the need and application of expert systems in the textile and garment industries. They had also assessed the training programs of both textile and garment industries. As a result, textile and garment industries have not yet applied an expert system, and they have also limited training programs. Therefore, specific training on defect detection is required. In an effort to address such problem, this study recommends to integrate expert system for defect detection of textile faults by designing and developing a prototype. The findings of this research showed 91% (the highest percentage) of the industry workers agreed that a prototype system which considers employee needs shall be constructed. So, the result of this research becomes an input for the prototype system development. Therefore, researches encourage textile and garment industries to implement expert systems.


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