Imre Horváth, Thomas Wan, Jingwei Huang, Eric Coatanéa, Julia M. Rayz, Yong Zeng, Kyoung-Yun Kim
This Extended Editorial has been compiled by the members of the Editorial Board to celebrate the 25th anniversary of the establishment of the Journal of Integrated Design and Process Science, which operates as the Transactions of the Society for Process and Design Science. The paper divides in three parts. The first part provides a detailed overview of the preliminaries, the objectives, and the periods of operation. It also includes a summary of the current application-orientated professional fields of interests, which are: (i) convergence mechanisms of creative scientific disciplines, (ii) convergence of artificial intelligence, team and health science, (iii) convergence concerning next-generation cyber-physical systems, and (iv) convergence in design and engineering education. The second part includes invited papers, which exemplify domains within the four fields of interest, and also represent good examples of science communication. Short synopses of the contents of these representative papers are included. The third part takes the major changes in scientific research and the academic publication arena into consideration, circumscribes the mission and vision as formulated by the current Editorial Board, and elaborates on the planned strategic exploration and utilization domains of interest.
{"title":"On the Convergence of Process Sciences and Design Science Facilitated by Artificial Intelligence: Proudly Celebrating the 25th Anniversary of the Journal of Integrated Design and Process Science","authors":"Imre Horváth, Thomas Wan, Jingwei Huang, Eric Coatanéa, Julia M. Rayz, Yong Zeng, Kyoung-Yun Kim","doi":"10.3233/jid-230046","DOIUrl":"https://doi.org/10.3233/jid-230046","url":null,"abstract":"This Extended Editorial has been compiled by the members of the Editorial Board to celebrate the 25th anniversary of the establishment of the Journal of Integrated Design and Process Science, which operates as the Transactions of the Society for Process and Design Science. The paper divides in three parts. The first part provides a detailed overview of the preliminaries, the objectives, and the periods of operation. It also includes a summary of the current application-orientated professional fields of interests, which are: (i) convergence mechanisms of creative scientific disciplines, (ii) convergence of artificial intelligence, team and health science, (iii) convergence concerning next-generation cyber-physical systems, and (iv) convergence in design and engineering education. The second part includes invited papers, which exemplify domains within the four fields of interest, and also represent good examples of science communication. Short synopses of the contents of these representative papers are included. The third part takes the major changes in scientific research and the academic publication arena into consideration, circumscribes the mission and vision as formulated by the current Editorial Board, and elaborates on the planned strategic exploration and utilization domains of interest.","PeriodicalId":43457,"journal":{"name":"Journal of Integrated Design & Process Science","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danny Weyns, Thomas Bäck, Renè Vidal, Xin Yao, Ahmed Nabil Belbachir
Computing systems are omnipresent; their sustainability has become crucial for our society. A key aspect of this sustainability is the ability of computing systems to cope with the continuous change they face, ranging from dynamic operating conditions, to changing goals, and technological progress. While we are able to engineer smart computing systems that autonomously deal with various types of changes, handling unanticipated changes requires system evolution, which remains in essence a human-centered process. This will eventually become unmanageable. To break through the status quo, we put forward an arguable opinion for the vision of self-evolving computing systems that are equipped with an evolutionary engine enabling them to evolve autonomously. Specifically, when a self-evolving computing systems detects conditions outside its operational domain, such as an anomaly or a new goal, it activates an evolutionary engine that runs online experiments to determine how the system needs to evolve to deal with the changes, thereby evolving its architecture. During this process the engine can integrate new computing elements that are provided by computing warehouses. These computing elements provide specifications and procedures enabling their automatic integration. We motivate the need for self-evolving computing systems in light of the state of the art, outline a conceptual architecture of self-evolving computing systems, and illustrate the architecture for a future smart city mobility system that needs to evolve continuously with changing conditions. To conclude, we highlight key research challenges to realize the vision of self-evolving computing systems.
{"title":"The vision of self-evolving computing systems","authors":"Danny Weyns, Thomas Bäck, Renè Vidal, Xin Yao, Ahmed Nabil Belbachir","doi":"10.3233/jid-220003","DOIUrl":"https://doi.org/10.3233/jid-220003","url":null,"abstract":"Computing systems are omnipresent; their sustainability has become crucial for our society. A key aspect of this sustainability is the ability of computing systems to cope with the continuous change they face, ranging from dynamic operating conditions, to changing goals, and technological progress. While we are able to engineer smart computing systems that autonomously deal with various types of changes, handling unanticipated changes requires system evolution, which remains in essence a human-centered process. This will eventually become unmanageable. To break through the status quo, we put forward an arguable opinion for the vision of self-evolving computing systems that are equipped with an evolutionary engine enabling them to evolve autonomously. Specifically, when a self-evolving computing systems detects conditions outside its operational domain, such as an anomaly or a new goal, it activates an evolutionary engine that runs online experiments to determine how the system needs to evolve to deal with the changes, thereby evolving its architecture. During this process the engine can integrate new computing elements that are provided by computing warehouses. These computing elements provide specifications and procedures enabling their automatic integration. We motivate the need for self-evolving computing systems in light of the state of the art, outline a conceptual architecture of self-evolving computing systems, and illustrate the architecture for a future smart city mobility system that needs to evolve continuously with changing conditions. To conclude, we highlight key research challenges to realize the vision of self-evolving computing systems.","PeriodicalId":43457,"journal":{"name":"Journal of Integrated Design & Process Science","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A value-based strategy relies on the implementation of a patient-centered care system that will directly benefit patient care outcomes and reduce costs of care. This paper identifies the trends and approaches to artificial intelligence (AI) research in healthcare. The convergence of multiple disciplines in the conduct of healthcare research requires partnerships to be established among academic scholars, healthcare practitioners, and industrial experts in software design and data science. This collaborative work will greatly enhance the formulation of theoretically relevant frameworks to guide empirical research and application, particularly relevant in the search for causal mechanisms to reduce costly and avoidable hospital readmissions for chronic conditions. An example of implementing patient-centered care at the community level is presented and entails the influence of the context, design, process, performance and outcomes on personal and population health, employing AI research and informational technology.
{"title":"Convergence of artificial intelligence research in healthcare: Trends and approaches","authors":"Thomas T.H. Wan","doi":"10.3233/jid-200002","DOIUrl":"https://doi.org/10.3233/jid-200002","url":null,"abstract":"A value-based strategy relies on the implementation of a patient-centered care system that will directly benefit patient care outcomes and reduce costs of care. This paper identifies the trends and approaches to artificial intelligence (AI) research in healthcare. The convergence of multiple disciplines in the conduct of healthcare research requires partnerships to be established among academic scholars, healthcare practitioners, and industrial experts in software design and data science. This collaborative work will greatly enhance the formulation of theoretically relevant frameworks to guide empirical research and application, particularly relevant in the search for causal mechanisms to reduce costly and avoidable hospital readmissions for chronic conditions. An example of implementing patient-centered care at the community level is presented and entails the influence of the context, design, process, performance and outcomes on personal and population health, employing AI research and informational technology.","PeriodicalId":43457,"journal":{"name":"Journal of Integrated Design & Process Science","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135805962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.
{"title":"A prioritized decision making method for reliability allocation: In optimistic and pessimistic view","authors":"Aniruddha Samanta, Kajla Basu","doi":"10.3233/jid-200013","DOIUrl":"https://doi.org/10.3233/jid-200013","url":null,"abstract":"Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.","PeriodicalId":43457,"journal":{"name":"Journal of Integrated Design & Process Science","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136196347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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