In the developmental dilemma of artificial intelligence(AI)-assisted judicial decision-making,the technical architecture of AI determines its inherent lack of transparency and interpretability,which is challenging to ...In the developmental dilemma of artificial intelligence(AI)-assisted judicial decision-making,the technical architecture of AI determines its inherent lack of transparency and interpretability,which is challenging to fundamentally improve.This can be considered a true challenge in the realm of AI-assisted judicial decision-making.By examining the court’s acceptance,integration,and trade-offs of AI technology embedded in the judicial field,the exploration of potential conflicts,interactions,and even mutual shaping between the two will not only reshape their conceptual connotations and intellectual boundaries but also strengthen the cognition and re-interpretation of the basic principles and core values of the judicial trial system.展开更多
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
The Basel II committee sets their customers. This new up directives encouraging banks to use internal scores in order to assess the risk of form of information competes with the existing ones. Small and medium-sized e...The Basel II committee sets their customers. This new up directives encouraging banks to use internal scores in order to assess the risk of form of information competes with the existing ones. Small and medium-sized enterprises （SMEs） are most concerned by these new stakes, due to the lack of transparency. The aim of this paper is to understand the determinants of the choice between substitution and complementarity between the two types of information： ＂soft＂ and ＂hard＂, to test a potential effect of this choice on the banking performance and to describe which variables are involved in the decision-making process. The originality of this work is to try to quantify the information costs and to use it as a variable which is affecting the adopted choice.展开更多
Collaboration with universities as ＇knowledge factories＇ is increasingly perceived to be an effective and viable solution for firms to gain competitive advantage. One of the main challenges firms face in this area i...Collaboration with universities as ＇knowledge factories＇ is increasingly perceived to be an effective and viable solution for firms to gain competitive advantage. One of the main challenges firms face in this area is how to select the best university for collaboration. This selection undoubtedly affects some other strategic activities of firms, such as managing and governing the relationship with the selected university and, most importantly, firm performance. As such, the selection becomes an important strategic decision that deserves a great deal of attention. Thus far, no systematic attempt has been made to investigate this significant area of research. The main purpose of this study is to formulate a decision-making model for university selection. Reviewing existing literature of university-industry relationship yields a list of relevant criteria for this problem. The problem is then formulated as a multi-criteria decision-making （MCDM） model, and a fuzzy AHP is used to provide the solution. To illustrate the model, three Dutch universities are ranked based on the importance of the selected criteria.展开更多
文摘In the developmental dilemma of artificial intelligence(AI)-assisted judicial decision-making,the technical architecture of AI determines its inherent lack of transparency and interpretability,which is challenging to fundamentally improve.This can be considered a true challenge in the realm of AI-assisted judicial decision-making.By examining the court’s acceptance,integration,and trade-offs of AI technology embedded in the judicial field,the exploration of potential conflicts,interactions,and even mutual shaping between the two will not only reshape their conceptual connotations and intellectual boundaries but also strengthen the cognition and re-interpretation of the basic principles and core values of the judicial trial system.
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The Basel II committee sets their customers. This new up directives encouraging banks to use internal scores in order to assess the risk of form of information competes with the existing ones. Small and medium-sized enterprises （SMEs） are most concerned by these new stakes, due to the lack of transparency. The aim of this paper is to understand the determinants of the choice between substitution and complementarity between the two types of information： ＂soft＂ and ＂hard＂, to test a potential effect of this choice on the banking performance and to describe which variables are involved in the decision-making process. The originality of this work is to try to quantify the information costs and to use it as a variable which is affecting the adopted choice.
文摘Collaboration with universities as ＇knowledge factories＇ is increasingly perceived to be an effective and viable solution for firms to gain competitive advantage. One of the main challenges firms face in this area is how to select the best university for collaboration. This selection undoubtedly affects some other strategic activities of firms, such as managing and governing the relationship with the selected university and, most importantly, firm performance. As such, the selection becomes an important strategic decision that deserves a great deal of attention. Thus far, no systematic attempt has been made to investigate this significant area of research. The main purpose of this study is to formulate a decision-making model for university selection. Reviewing existing literature of university-industry relationship yields a list of relevant criteria for this problem. The problem is then formulated as a multi-criteria decision-making （MCDM） model, and a fuzzy AHP is used to provide the solution. To illustrate the model, three Dutch universities are ranked based on the importance of the selected criteria.
