Expert Systems for Human Materials and Automation Part 1 pdf

EXPERT SYSTEMS FOR HUMAN, MATERIALS AND AUTOMATION Edited by Petrică Vizureanu Expert Systems for Human, Materials and Automation Edited by Petrică Vizureanu Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Sandra Bakic Technical Editor Teodora Smiljanic Cover Designer Jan Hyrat Image Copyright Statsenko, 2010. Used under license from Shutterstock.com First published September, 2011 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Expert Systems for Human, Materials and Automation, Edited by Petrică Vizureanu p. cm. ISBN 978-953-307-334-7 free online editions of InTech Books and Journals can be found at www.intechopen.com Contents Preface IX Part 1 Human 1 Chapter 1 Expert System for Identification of Sport Talents: Idea, Implementation and Results 3 Vladan Papić, Nenad Rogulj and Vladimir Pleština Chapter 2 SeDeM Diagram: A New Expert System for the Formulation of Drugs in Solid Form 17 Josep M. Suñé Negre, Encarna García Montoya, Pilar Pérez Lozano, Johnny E. Aguilar Díaz, Manel Roig Carreras, Roser Fuster García, Montserrat Miñarro Carmona and Josep R. Ticó Grau Chapter 3 Parametric Modeling and Prognosis of Result Based Career Selection Based on Fuzzy Expert System and Decision Trees 35 Avneet Dhawan Chapter 4 Question-Answer Shell for Personal Expert Systems 51 Petr Sosnin Chapter 5 AI Applications in Psychology 75 Zaharia Mihai Horia Chapter 6 An Expert System to Support the Design of Human-Computer Interfaces 93 Cecilia Sosa Arias Peixoto and Tiago Cinto Chapter 7 Advances in Health Monitoring and Management 109 Nezih Mrad and Rim Lejmi-Mrad VI Contents Part 2 Materials Processing 137 Chapter 8 Expert System for Simulation of Metal Sheet Stamping: How Automation Can Help Improving Models and Manufacturing Techniques 139 Alejandro Quesada, Antonio Gauchía, Carolina Álvarez-Caldas and José-Luis San- Román Chapter 9 Expert System Used on Materials Processing 161 Vizureanu Petrică Chapter 10 Interface Layers Detection in Oil Field Tanks: A Critical Review 181 Mahmoud Meribout, Ahmed Al Naamany and Khamis Al Busaidi Chapter 11 Integrated Scheduled Waste Management System in Kuala Lumpur Using Expert System 209 Nassereldeen A. K, Mohammed Saedi and Nur Adibah Md Azman Chapter 12 Expert System Development for Acoustic Analysis in Concrete Harbor NDT 221 Mohammad Reza Hedayati, Ali Asghar Amidian and S. Ataolah Sadr Part 3 Automation & Control 237 Chapter 13 Conceptual Model Development for a Knowledge Base of PID Controllers Tuning in Open Loop 239 José Luis Calvo-Rolle, Ramón Ferreiro García, Antonio Couce Casanova, Héctor Quintián-Pardo and Héctor Alaiz-Moreton Chapter 14 Hybrid System for Ship-Aided Design Automation 259 Maria Meler-Kapcia Chapter 15 An Expert System Structured in Paraconsistent Annotated Logic for Analysis and Monitoring of the Level of Sea Water Pollutants 277 João Inácio Da Silva Filho, Maurício C. Mário, Camilo D. Seabra Pereira, Ana Carolina Angari, Luis Fernando P. Ferrara, Odair Pitoli Jr. and Dorotéa Vilanova Garcia Chapter 16 Expert System Based Network Testing 301 Vlatko Lipovac Chapter 17 An Expert System Based Approach for Diagnosis of Occurrences in Power Generating Units 327 Jacqueline G. Rolim and Miguel Moreto Contents VII Chapter 18 Fuzzy Based Flow Management of Real-Time Traffic for Quality of Service in WLANs 351 Tapio Frantti and Mikko Majanen Chapter 19 Expert System for Automatic Analysis of Results of Network Simulation 377 Joze Mohorko, Sasa Klampfer, Matjaz Fras and Zarko Cucej Preface The ability to create intelligent machines has intrigued humans since ancient times, and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems, which can mimic human beings. Accurate mathematical models neither always exist nor can they be derived for all complex environments because the domain may not be thoroughly understood. The solution consists of constructing rules that apply when input values lie within certain designer-defined categories. The concept of human-computer interfaces (HCI) has been undergoing changes over the years. Currently the demand is for user interfaces for ubiquitous computing. In this context, one of the basic requirements is the development of interfaces with high usability that meet different modes of interaction depending on users, environments and tasks to be performed. In carrying out the most important tasks is the lack of formalized application methods, mathematical models and advanced computer support. Decisions and adopted solutions are often based on knowledge resulting from experience and intuition of designers. Use of information on previously executed projects of similar ships allow expert systems using the Case Based Reasoning method (CBR), which is a relatively new way of solving problems related to databases and knowledge bases. The evolution of biological systems to adapt to their environment has fascinated and challenged scientists to increase their level of understanding of the functional characteristics of such systems. Such understanding has already benefited our society though increased life expectancy and quality, improved and cost effective health care and prevention. Engineers have looked for inspiration from such biological systems functionalities to enhance our society’s communication, economic and transportation infrastructure. This book has 19 chapters and explain that the expert systems are products of the artificial intelligence, branch of computer science that seeks to develop intelligent programs for human, materials and automation. Petrică Vizureanu „Gh. Asachi” Technical University of Iasi, Romania [...]... Fundamental Human Movements Human Kinetics, Champaign 16 Expert Systems for Human, Materials and Automation Dežman, B.; Trninić, S & Dizdar, D (2001a) Models of expert system and decision-making systems for efficient assessment of potential and actual quality of basketball players, Kinesiology, 33(2), 207- 215 Dežman, B, Trninić, S, Dizdar, D (2001b) Expert model of decision-making system for efficient orientation... 6 Expert Systems for Human, Materials and Automation sports can easily be added to the knowledge base Determination of the tests importance was based on the expert knowledge obtained from 97 kinesiology experts A questionnaire presented by Table 1 was prepared and handed out to two groups of experts: general knowledge experts (kinesiology teachers in high and elementary schools) and experts in a particular... rule and another with the nearest upper age in the antecedent part of the rule Final membership grade value can be calculated using the following equations: cl* = c k ,l + (κ − k ) ⋅ ( c k + 1, l − c k ,l ) cl*+ 1 = c k ,l + 1 + (κ − k ) ⋅ ( c k + 1, l + 1 − c k ,l + 1 ) (12 ) Membership grade indexes for particular age value can be simplified: μ k ,l = μ k + 1, l = μl ; μ k ,l + 1 = μ k + 1, l + 1 = μl + 1. .. + 1 − μl cl*+ 1 − cl* ( ) ⋅ Rij − cl* + μl (13 ) 4 Implementation and development Although entity names presented in Fig 5 are descriptive and may differ to the table names in the database, structure that is presented gives the main relations between them Fig 5 Expert system structure Expert knowledge is stored as rules, norms and test weights for each sport 12 Expert Systems for Human, Materials and. . .Part 1 Human 1 Expert System for Identification of Sport Talents: Idea, Implementation and Results Vladan Papić, Nenad Rogulj and Vladimir Pleština University of Split, Croatia 1 Introduction Selecting children for appropriate sport is the most demanding and the most responsible task for sport experts and kinesiology in general Sport activities have significant differences regarding structural and. .. 52,02 51, 78 47,42 44,53 42,75 42, 31 42 ,14 41, 95 41, 68 39,75 39,32 38,42 37,07 44,05 Table 4 Average output results for all examinees 6 Conclusion and discussion In this chapter we have presented an expert system for the selection and identification of an optimal sport for a child This is the first expert system developed for this purpose that uses fuzzy logic and has wide Internet accessibility Expert. .. M (2 010 ) Application of expert- system for talent scouting in dancing Acta Kinesiologica 4( 1) , 10 9 -11 3 Stergiou, N (2004) Innovative Analysis of Human Movement Champaign, IL: Human Kinetics Šimić, G & Devedžić, V (2003) Building an intelligent system using modern Internet technologies Expert Systems with Applications, Issue 25, 2 31- 246 Rajković, V.; Bohanec, M.; Šturm, J.; Leskošek, B (19 91) An expert. .. FBi, μBMIi ∈ ⎡0 ,1 , 1 ≤ i ≤ 6 ⎣ ⎦ 8 Expert Systems for Human, Materials and Automation An example of a fuzzy rule matrix to infer the body model adequacy is presented in Table 1 Each sport has different rule matrix Based on the fuzzy grade vectors FH, FB and fuzzy rules which are partially shown in Table 2, fuzzy reasoning is performed in order to evaluate the athletic body adequacy for each sport... additional demands on new tests and equipment, these tests were chosen as the measurement instrument for input data to our expert system Also, normative values for chosen tests are available from the literature (Findak et al., 19 96) and updated according to Norton and Olds (20 01) Fig 1 Idea and development of the expert system As a first step, importance of each test for every sport has to be determined and. .. Issue 3, Volume 9, 17 52 -17 55 Rogulj, N.; Papić, V & Čavala, M (2009) Evaluation Models of Some Morphological Characteristics for Talent Scouting in Sport, Collegium Antropologicum, 33 (1) , 10 511 0 Shim, J P.; Warkentin, M.; Courtney, J.F.; Power, D J., Sharda, R & Carlsson, C (2002) Past, present, and future of decision support technology Decision Support Systems, Volume 33 (2), 11 1 -12 6 (16 ) Srhoj, Lj.; . EXPERT SYSTEMS FOR HUMAN, MATERIALS AND AUTOMATION Edited by Petrică Vizureanu Expert Systems for Human, Materials and Automation Edited by. (MFI) that Expert Systems for Human, Materials and Automation 10 can be obtained for each sport is equal which means that the following condition must be satisfied () () 1 1, K n KSi. FB i , 0 ,1 , 1 6 BMIi i μ ∈≤≤ ⎡⎤ ⎣⎦ . Expert Systems for Human, Materials and Automation 8 An example of a fuzzy rule matrix to infer the body model adequacy is presented in Table 1. Each