Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineeri...Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.展开更多
In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty ...In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.展开更多
After field survey and literature review, we found that software requirement development (SRD) is a knowledge creation process, and knowledge creation theory of Nonaka is appropriate for analyzing knowledge creating o...After field survey and literature review, we found that software requirement development (SRD) is a knowledge creation process, and knowledge creation theory of Nonaka is appropriate for analyzing knowledge creating of SRD. The characteristics of knowledge in requirement elicitation process are analyzed, and dissymmetric knowledge of SRD is discussed. Experts on requirement are introduced into SRD process as a third knowledge entity. In addition, a knowledge creation model of SRD is put forward and the knowledge flow and the relationship of entities of this model are illustrated. Case study findings are illustrated in the following: 1) The necessary diversity of the project team can facilitate the implementation of the SRD. 2) The introduction of experts on requirement can achieve the transformation of knowledge effectively, thus helping to carry out the SRD. 3) Methodology and related technologies are important for carrying out the SRD.展开更多
Purpose-This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment.For this purpose,different classification methods based on data,experts’knowledge...Purpose-This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment.For this purpose,different classification methods based on data,experts’knowledge and both are considered in some cases.Besides,feature reduction and some clustering methods are used to improve their performance.Design/methodology/approach-First,the performances of classification methods are evaluated for differential diagnosis of different diseases.Then,experts’knowledge is utilized to modify the Bayesian networks’structures.Analyses of the results show that using experts’knowledge is more effective than other algorithms for increasing the accuracy of Bayesian network classification.A total of ten different diseases are used for testing,taken from the Machine Learning Repository datasets of the University of California at Irvine(UCI).Findings-The proposed method improves both the computation time and accuracy of the classification methods used in this paper.Bayesian networks based on experts’knowledge achieve a maximum average accuracy of 87 percent,with a minimum standard deviation average of 0.04 over the sample datasets among all classification methods.Practical implications-The proposed methodology can be applied to perform disease differential diagnosis analysis.Originality/value-This study presents the usefulness of experts’knowledge in the diagnosis while proposing an adopted improvement method for classifications.Besides,the Bayesian network based on experts’knowledge is useful for different diseases neglected by previous papers.展开更多
In this paper, well-known and structured Monte Carlo simulation technique has been employed in predicting the amounts of the corrosion wastage over some bulk carriers＇ structural elements in different points of time ...In this paper, well-known and structured Monte Carlo simulation technique has been employed in predicting the amounts of the corrosion wastage over some bulk carriers＇ structural elements in different points of time during their exploitation life. As a base for the realization of the simulations, the appropriate statistical data collected over the group of ten bulk carriers have been used. Both longitudinal and transversal ships＇ hull structural elements have been taken into the consideration. Due to some experts＇ knowledge in this domain, the critical hull zones are identified and certain interventions are done in the pre-processing of the input data to the Monte Carlo simulations, all with the aim of achieving better convergence between simulation results and the experts＇ expectations in this field.展开更多
At present,experts have become a mainstay of modern litigation,although criticisms suggest that the problems of how to fit expert knowledge comfortably into the method of adversarial fact-finding are numerous,signific...At present,experts have become a mainstay of modern litigation,although criticisms suggest that the problems of how to fit expert knowledge comfortably into the method of adversarial fact-finding are numerous,significant,and without simple solutions.Concerns about partisanship and lack of scientific competence by adjudicators to evaluate contradictory expert testimony have been widely recognized in the traditional use of party-called expert witnesses.While such concerns cannot be wholly ameliorated,there may be alternative mechanisms that can help.One solution would be to call for the use of neutral court-appointed experts,to create a nonpartisan source of expert knowledge.A system of neutral court-appointed experts is an advisory tribunal to the court that could deliver“those general truths,applicable to the issue,which they may treat as final and decisive.”However,no matter in which country,the choice of appointing neutral experts still seems to be a rare option for trial judges to consider and exercise.An obvious question would be:Why are neutral experts not used more frequently at trial?This paper did a study on court-appointed experts,with a focus on challenges that such mechanism faces.Part Ⅰ examines problems in the traditional use of expert witnesses in an adversarial system.Part Ⅱ discusses the incentives to make greater use of court-appointed experts in a typical adversarial system and to what extent such mechanism would solve difficulties within the traditional use of party-called expert witnesses.Part Ⅲ further explores and analyzes obstacles that a typical neutral expert system nowadays encounters when it operates in practice.Taking all analysis together,Part IV makes an overall evaluation of the mechanism of court-appointed experts.展开更多
文摘Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.
文摘In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.
文摘After field survey and literature review, we found that software requirement development (SRD) is a knowledge creation process, and knowledge creation theory of Nonaka is appropriate for analyzing knowledge creating of SRD. The characteristics of knowledge in requirement elicitation process are analyzed, and dissymmetric knowledge of SRD is discussed. Experts on requirement are introduced into SRD process as a third knowledge entity. In addition, a knowledge creation model of SRD is put forward and the knowledge flow and the relationship of entities of this model are illustrated. Case study findings are illustrated in the following: 1) The necessary diversity of the project team can facilitate the implementation of the SRD. 2) The introduction of experts on requirement can achieve the transformation of knowledge effectively, thus helping to carry out the SRD. 3) Methodology and related technologies are important for carrying out the SRD.
文摘Purpose-This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment.For this purpose,different classification methods based on data,experts’knowledge and both are considered in some cases.Besides,feature reduction and some clustering methods are used to improve their performance.Design/methodology/approach-First,the performances of classification methods are evaluated for differential diagnosis of different diseases.Then,experts’knowledge is utilized to modify the Bayesian networks’structures.Analyses of the results show that using experts’knowledge is more effective than other algorithms for increasing the accuracy of Bayesian network classification.A total of ten different diseases are used for testing,taken from the Machine Learning Repository datasets of the University of California at Irvine(UCI).Findings-The proposed method improves both the computation time and accuracy of the classification methods used in this paper.Bayesian networks based on experts’knowledge achieve a maximum average accuracy of 87 percent,with a minimum standard deviation average of 0.04 over the sample datasets among all classification methods.Practical implications-The proposed methodology can be applied to perform disease differential diagnosis analysis.Originality/value-This study presents the usefulness of experts’knowledge in the diagnosis while proposing an adopted improvement method for classifications.Besides,the Bayesian network based on experts’knowledge is useful for different diseases neglected by previous papers.
文摘In this paper, well-known and structured Monte Carlo simulation technique has been employed in predicting the amounts of the corrosion wastage over some bulk carriers＇ structural elements in different points of time during their exploitation life. As a base for the realization of the simulations, the appropriate statistical data collected over the group of ten bulk carriers have been used. Both longitudinal and transversal ships＇ hull structural elements have been taken into the consideration. Due to some experts＇ knowledge in this domain, the critical hull zones are identified and certain interventions are done in the pre-processing of the input data to the Monte Carlo simulations, all with the aim of achieving better convergence between simulation results and the experts＇ expectations in this field.
基金This article is interim research product for China Ministry of Education–Project of Humanities and Social Sciences(Project No.13YJC820073).
文摘At present,experts have become a mainstay of modern litigation,although criticisms suggest that the problems of how to fit expert knowledge comfortably into the method of adversarial fact-finding are numerous,significant,and without simple solutions.Concerns about partisanship and lack of scientific competence by adjudicators to evaluate contradictory expert testimony have been widely recognized in the traditional use of party-called expert witnesses.While such concerns cannot be wholly ameliorated,there may be alternative mechanisms that can help.One solution would be to call for the use of neutral court-appointed experts,to create a nonpartisan source of expert knowledge.A system of neutral court-appointed experts is an advisory tribunal to the court that could deliver“those general truths,applicable to the issue,which they may treat as final and decisive.”However,no matter in which country,the choice of appointing neutral experts still seems to be a rare option for trial judges to consider and exercise.An obvious question would be:Why are neutral experts not used more frequently at trial?This paper did a study on court-appointed experts,with a focus on challenges that such mechanism faces.Part Ⅰ examines problems in the traditional use of expert witnesses in an adversarial system.Part Ⅱ discusses the incentives to make greater use of court-appointed experts in a typical adversarial system and to what extent such mechanism would solve difficulties within the traditional use of party-called expert witnesses.Part Ⅲ further explores and analyzes obstacles that a typical neutral expert system nowadays encounters when it operates in practice.Taking all analysis together,Part IV makes an overall evaluation of the mechanism of court-appointed experts.
