Hyun-Kyung Lee, Sue-Yeon Chae, Seung-Yeon Choi, Dong-Hwan Hong, Sang-Gu Kang, Gyomin Koo, Seo-Hyeon Lee, Sun-Woo Lee, Young-Seo Lee, M. Oh, Geena Park, Ji-Hyun Park, S. Park
Current appropriate technology promoting social sustainability for rural, underprivileged populations is often plagued by lack of affordability, maintenance, and personal training, and is also empathetically disconnected from local people and culture. This study proposes criteria for balancing design thinking processes and appropriate technology for social sustainability. In this study, we concretized five assumptions for design thinking processes: user-oriented design with mass productivity; reiterative nature through user satisfaction surveys; affordability for purchase, maintenance, and repair services; local appropriateness; and eco-friendliness with environmental sustainability. Next, we applied the criteria to 28 representative cases from the water, energy, health, shelter, and transportation fields. The cases were evaluated using qualitative content analysis. Findings show that the criteria are necessary for setting economic, social, and environmental development goals for underprivileged regions after considering local contexts. Cultural empathy and collaboration with locals are key for finding practical solutions and co-creating options iteratively. Further, the cases were compared quantitatively using radar diagrams, histograms, and graphs showing average values and standard deviations, providing an objective measure for appropriate technology. Notably, both qualitative and quantitative approaches can serve as useful guidelines for designers, developers, and local users when developing appropriate technology for social sustainability in underprivileged regions.
{"title":"Design Thinking with Appropriate Technology for Improving Social Sustainability: Critical and Comprehensive Criteria","authors":"Hyun-Kyung Lee, Sue-Yeon Chae, Seung-Yeon Choi, Dong-Hwan Hong, Sang-Gu Kang, Gyomin Koo, Seo-Hyeon Lee, Sun-Woo Lee, Young-Seo Lee, M. Oh, Geena Park, Ji-Hyun Park, S. Park","doi":"10.3233/JID200012","DOIUrl":"https://doi.org/10.3233/JID200012","url":null,"abstract":"Current appropriate technology promoting social sustainability for rural, underprivileged populations is often plagued by lack of affordability, maintenance, and personal training, and is also empathetically disconnected from local people and culture. This study proposes criteria for balancing design thinking processes and appropriate technology for social sustainability. In this study, we concretized five assumptions for design thinking processes: user-oriented design with mass productivity; reiterative nature through user satisfaction surveys; affordability for purchase, maintenance, and repair services; local appropriateness; and eco-friendliness with environmental sustainability. Next, we applied the criteria to 28 representative cases from the water, energy, health, shelter, and transportation fields. The cases were evaluated using qualitative content analysis. Findings show that the criteria are necessary for setting economic, social, and environmental development goals for underprivileged regions after considering local contexts. Cultural empathy and collaboration with locals are key for finding practical solutions and co-creating options iteratively. Further, the cases were compared quantitatively using radar diagrams, histograms, and graphs showing average values and standard deviations, providing an objective measure for appropriate technology. Notably, both qualitative and quantitative approaches can serve as useful guidelines for designers, developers, and local users when developing appropriate technology for social sustainability in underprivileged regions.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122695981","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}
Healthcare delivery systems are evolving with the advances in health information technology (HIT) development and its applications to coordinated or guided care for polychronic conditions. The design features of artificial intelligence in healthcare reflect the public interest in optimizing care coordination and communication between providers and patients. This article offers a practical evaluation and assessment of the relevance of theoretical frameworks and appropriate methodologies to formalize a multi-criteria optimization of a logic model applicable for achieving the system’s efficiency and effectiveness. In specifying theoretical constructs and evaluation methods for HIT evaluation, a three-fold purpose is to show the relevance of personal and behavioral determinants of HIT use, articulate the need for developing a transdisciplinary framework, and formulate appropriate multilevel modeling and causal analysis of the determinants of HIT use and its impacts on chronic care.
{"title":"An Integrated Social and Behavioral System Approach to Evaluation of Healthcare Information Technology for Polychronic Conditions","authors":"T. Wan, Bing-Long Wang","doi":"10.3233/JID200011","DOIUrl":"https://doi.org/10.3233/JID200011","url":null,"abstract":"Healthcare delivery systems are evolving with the advances in health information technology (HIT) development and its applications to coordinated or guided care for polychronic conditions. The design features of artificial intelligence in healthcare reflect the public interest in optimizing care coordination and communication between providers and patients. This article offers a practical evaluation and assessment of the relevance of theoretical frameworks and appropriate methodologies to formalize a multi-criteria optimization of a logic model applicable for achieving the system’s efficiency and effectiveness. In specifying theoretical constructs and evaluation methods for HIT evaluation, a three-fold purpose is to show the relevance of personal and behavioral determinants of HIT use, articulate the need for developing a transdisciplinary framework, and formulate appropriate multilevel modeling and causal analysis of the determinants of HIT use and its impacts on chronic care.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122138736","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}
Knowledge is a central constituent of the societal infrastructure. Knowledge is produced, interchanged, represented, and used for different purposes. In societies, where tangible or intangible artifacts are essential elements of the interaction of humans with the environment, knowledge is a central piece of the reasoning and realization mechanisms of artifacts. In turn, those artifacts can become a source of knowledge production. It is not a human specificity to produce, share, use, or transmit knowledge. Several studies have demonstrated that species such as whales enjoy this capability too (Whitehead et al., 2021). This means that producing and sharing knowledge is associated with social interactions both for humans and whales’ groups. On the contrary, social interactions of extremely large groups and the capacity to interact and collaborate with distant, unknown fellows is probably a human specificity. This collaboration implies the sharing of knowledge in a format ensuring diffusion and interchange. But what is happening when a new phenomenon such as knowledge produced by machines can become a reality? Is this extended collaboration remaining human specificity? Professor Horvath with his paper titled “On Reasonable Inquiry and Analysis Domains of Sympérasmology", clears the way by providing an interesting contribution to the theory of synthetic system knowledge (SSK). His contribution opens a new area of investigation permitted by complex systems and their capacity to produce knowledge and use it intelligently. For us humans, all those elements can be the source of apparent intractable complexity. When faced with the emergence of complex phenomena, a seductive vision of complexity as an emergent, autoorganizing phenomenon is prevalent in multiple communities and crosses multiple domains of sciences such as computing science or economy. Self-organization as such is an interesting line of research but considering that complexity and self-organization can take care of themselves, and without a deep understanding of the multiple interactions, complex control and adaptation is a detrimental approach and can be the source of negative impacts. It is dangerous to see self-organization as an assumed self-organizing property of complex systems. This is, for example, a commonly adopted perspective in the mainstream economic school of thought. Another example is the behaviour of the Internet that gives the illusion of robust self-organizing structures despite high uncertainty in the environment itself. The reality is that for those systems complexity is hidden and that sophisticated control and adaptation procedures of designed systems exist. Complexity can and should be designed. This can be supported by providing a leading role in the design process to the description of the environment of the system. This is an approach favoured by multiple
知识是社会基础设施的核心组成部分。知识是为了不同的目的而产生、交换、表现和使用的。在社会中，有形或无形的人工制品是人类与环境相互作用的基本要素，知识是人工制品推理和实现机制的核心部分。反过来，这些工件可以成为知识生产的来源。创造、分享、使用或传播知识并不是人类的特性。几项研究表明，鲸鱼等物种也具有这种能力(Whitehead et al.， 2021)。这意味着生产和分享知识与人类和鲸鱼群体的社会互动有关。相反，超大群体的社会互动以及与遥远的、未知的同伴互动和合作的能力可能是人类的特征。这种合作意味着以一种确保传播和交流的形式分享知识。但是，当机器产生的知识等新现象成为现实时，会发生什么呢?这种扩展的合作是否保留了人类的特异性?Horvath教授的论文题为《论症候学的合理探究和分析领域》，通过对合成系统知识(SSK)理论的有趣贡献扫清了道路。他的贡献打开了一个新的研究领域，允许复杂的系统和他们的能力产生知识，并明智地使用它。对于我们人类来说，所有这些因素都可能是表面上难以处理的复杂性的来源。当面对复杂现象的出现时，一种诱人的观点认为复杂性是一种新兴的、自组织的现象，这种观点在多个社区和多个科学领域(如计算科学或经济学)中普遍存在。自组织本身是一个有趣的研究方向，但考虑到复杂性和自组织可以照顾自己，如果没有对多种相互作用的深刻理解，复杂的控制和适应是一种有害的方法，可能成为负面影响的来源。把自组织看作是复杂系统的一种假定的自组织性质是危险的。例如，这是主流经济学派普遍采用的观点。另一个例子是互联网的行为，尽管环境本身存在很大的不确定性，但它却给人一种强大的自组织结构的错觉。现实情况是，对于这些系统来说，复杂性是隐藏的，并且存在设计系统的复杂控制和自适应程序。复杂性可以而且应该被设计出来。这可以通过在系统环境描述的设计过程中提供一个主导角色来支持。这是一种多方青睐的方法
{"title":"Knowledge production, sharing, and design in an age of fundamental transformations","authors":"E. Coatanéa","doi":"10.3233/JID200010","DOIUrl":"https://doi.org/10.3233/JID200010","url":null,"abstract":"Knowledge is a central constituent of the societal infrastructure. Knowledge is produced, interchanged, represented, and used for different purposes. In societies, where tangible or intangible artifacts are essential elements of the interaction of humans with the environment, knowledge is a central piece of the reasoning and realization mechanisms of artifacts. In turn, those artifacts can become a source of knowledge production. It is not a human specificity to produce, share, use, or transmit knowledge. Several studies have demonstrated that species such as whales enjoy this capability too (Whitehead et al., 2021). This means that producing and sharing knowledge is associated with social interactions both for humans and whales’ groups. On the contrary, social interactions of extremely large groups and the capacity to interact and collaborate with distant, unknown fellows is probably a human specificity. This collaboration implies the sharing of knowledge in a format ensuring diffusion and interchange. But what is happening when a new phenomenon such as knowledge produced by machines can become a reality? Is this extended collaboration remaining human specificity? Professor Horvath with his paper titled “On Reasonable Inquiry and Analysis Domains of Sympérasmology\", clears the way by providing an interesting contribution to the theory of synthetic system knowledge (SSK). His contribution opens a new area of investigation permitted by complex systems and their capacity to produce knowledge and use it intelligently. For us humans, all those elements can be the source of apparent intractable complexity. When faced with the emergence of complex phenomena, a seductive vision of complexity as an emergent, autoorganizing phenomenon is prevalent in multiple communities and crosses multiple domains of sciences such as computing science or economy. Self-organization as such is an interesting line of research but considering that complexity and self-organization can take care of themselves, and without a deep understanding of the multiple interactions, complex control and adaptation is a detrimental approach and can be the source of negative impacts. It is dangerous to see self-organization as an assumed self-organizing property of complex systems. This is, for example, a commonly adopted perspective in the mainstream economic school of thought. Another example is the behaviour of the Internet that gives the illusion of robust self-organizing structures despite high uncertainty in the environment itself. The reality is that for those systems complexity is hidden and that sophisticated control and adaptation procedures of designed systems exist. Complexity can and should be designed. This can be supported by providing a leading role in the design process to the description of the environment of the system. This is an approach favoured by multiple","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121186774","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}
Charging network scheduling for battery electric vehicles is a challenging research issue on deciding where and when to activate users’ charging under the constraints imposed by their time availability and energy demands, as well as the limited available capacities provided by the charging stations. Moreover, users’ strategic behaviors and untruthful revelation on their real preferences on charging schedules pose additional challenges to efficiently coordinate their charging in a market setting, where users are reasonably modelled as self-interested agents who strive to maximize their own utilities rather than the system-wide efficiency. To tackle these challenges, we propose an incentive-compatible combinatorial auction for charging network scheduling in a decentralized environment. In such a structured framework, users can bid for their preferred destination and charging time at different stations, and the scheduling specific problem solving structure is also embedded into the winner determination model to coordinate the charging at multiple stations. The objective is to maximize the social welfare across all users which is represented by their total values of scheduled finishing time. The Vickrey–Clarke–Groves payment rule is adopted to incentivize users to truthfully disclose their true preferences as a weakly dominant strategy. Moreover, the proposed auction is proved to be individually rational and weakly budget balanced through an extensive game-theoretical analysis. We also present a case study to demonstrate its applicability to real-world charging reservation scenarios using the charging network data from Manhattan, New York City.
{"title":"An Incentive-Compatible Combinatorial Auction Design for Charging Network Scheduling of Battery Electric Vehicles","authors":"Luyang Hou, Chun Wang, Jun Yan","doi":"10.3233/JID200007","DOIUrl":"https://doi.org/10.3233/JID200007","url":null,"abstract":"Charging network scheduling for battery electric vehicles is a challenging research issue on deciding where and when to activate users’ charging under the constraints imposed by their time availability and energy demands, as well as the limited available capacities provided by the charging stations. Moreover, users’ strategic behaviors and untruthful revelation on their real preferences on charging schedules pose additional challenges to efficiently coordinate their charging in a market setting, where users are reasonably modelled as self-interested agents who strive to maximize their own utilities rather than the system-wide efficiency. To tackle these challenges, we propose an incentive-compatible combinatorial auction for charging network scheduling in a decentralized environment. In such a structured framework, users can bid for their preferred destination and charging time at different stations, and the scheduling specific problem solving structure is also embedded into the winner determination model to coordinate the charging at multiple stations. The objective is to maximize the social welfare across all users which is represented by their total values of scheduled finishing time. The Vickrey–Clarke–Groves payment rule is adopted to incentivize users to truthfully disclose their true preferences as a weakly dominant strategy. Moreover, the proposed auction is proved to be individually rational and weakly budget balanced through an extensive game-theoretical analysis. We also present a case study to demonstrate its applicability to real-world charging reservation scenarios using the charging network data from Manhattan, New York City.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129054662","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}
Sympérasmology was proposed as the theory of synthetic system knowledge (SSK), which is seen as the fuel for the engine of systelligence. There are two main reasons why the proposal is made: (i) rapidly growing, SSK represents a third category of knowledge beside common personal knowledge and testified scientific knowledge, and (ii) though important, neither modern gnoseology nor contemporary epistemology studies its nature, principles, progression, and impacts. The need for rational and empirical studies of SSK is also underpinned by the on-going intelligence revolution, in which knowledge is deemed to be a productive power, a cognitive enabler of smart systems, and a strong transformer of social life. Sympérasmology is still in an embryonic state. Notwithstanding, a map of possible inquiry and analysis domains is released for a public debate in this paper. These domains can be sorted into four categories: (i) rudiments, (ii) principles, (iii) faculties, and (iv) implications. This paper explains these categories and the related domains of interest, and discusses some relevant aspects of study. Without striving for exhaustiveness, it elaborates on many relevant discussion topics and issues. The paper emphasizes that a precise specification of the scope and objectives of sympérasmology needs a stream of exploratory research studies as well as further insightful philosophical discussions.
{"title":"On Reasonable Inquiry and Analysis Domains of Sympérasmology","authors":"I. Horváth","doi":"10.3233/JID200009","DOIUrl":"https://doi.org/10.3233/JID200009","url":null,"abstract":"Sympérasmology was proposed as the theory of synthetic system knowledge (SSK), which is seen as the fuel for the engine of systelligence. There are two main reasons why the proposal is made: (i) rapidly growing, SSK represents a third category of knowledge beside common personal knowledge and testified scientific knowledge, and (ii) though important, neither modern gnoseology nor contemporary epistemology studies its nature, principles, progression, and impacts. The need for rational and empirical studies of SSK is also underpinned by the on-going intelligence revolution, in which knowledge is deemed to be a productive power, a cognitive enabler of smart systems, and a strong transformer of social life. Sympérasmology is still in an embryonic state. Notwithstanding, a map of possible inquiry and analysis domains is released for a public debate in this paper. These domains can be sorted into four categories: (i) rudiments, (ii) principles, (iii) faculties, and (iv) implications. This paper explains these categories and the related domains of interest, and discusses some relevant aspects of study. Without striving for exhaustiveness, it elaborates on many relevant discussion topics and issues. The paper emphasizes that a precise specification of the scope and objectives of sympérasmology needs a stream of exploratory research studies as well as further insightful philosophical discussions.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"7 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125979425","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}
Md Tarique Hasan Khan, Frédéric Demoly, Kyoung-Yun Kim
Over the last decades, noticeable efforts have been made to construct design knowledge during the detailed geometric definition phase systematically. However, physical products exhibit functional behaviors, which explain that they evolve over space and time. Hence, there is a need to extend assembly product knowledge towards the spatiotemporal dimension to provide more realistic knowledge models in assembly design. Systematic semantic knowledge representation via ontology enables designers to understand the anticipated product’s behavior in advance. In this article, Interval Algebra (IA) and Region Connection Calculus (RCC) are investigated to formalize and construct ontological spatiotemporal assembly product motion knowledge. IA is commonly used to represent the temporality between two entities, while RCC is more appropriate to represent the ‘part-to-part’ relationships of two topological spaces. This paper discusses the roles of IA and RCC and presents a case study of a nutcracker assembly model’s behavior. The assembly product motion ontology with the aid of IA and RCC is evaluated using a task-based approach. The evaluation shows the added value of the developed ontology compared to others published in the literature.
{"title":"Interval Algebra and Region Connection Calculus for Ontological Spatiotemporal Assembly Product Motion Knowledge Representation","authors":"Md Tarique Hasan Khan, Frédéric Demoly, Kyoung-Yun Kim","doi":"10.3233/JID200008","DOIUrl":"https://doi.org/10.3233/JID200008","url":null,"abstract":"Over the last decades, noticeable efforts have been made to construct design knowledge during the detailed geometric definition phase systematically. However, physical products exhibit functional behaviors, which explain that they evolve over space and time. Hence, there is a need to extend assembly product knowledge towards the spatiotemporal dimension to provide more realistic knowledge models in assembly design. Systematic semantic knowledge representation via ontology enables designers to understand the anticipated product’s behavior in advance. In this article, Interval Algebra (IA) and Region Connection Calculus (RCC) are investigated to formalize and construct ontological spatiotemporal assembly product motion knowledge. IA is commonly used to represent the temporality between two entities, while RCC is more appropriate to represent the ‘part-to-part’ relationships of two topological spaces. This paper discusses the roles of IA and RCC and presents a case study of a nutcracker assembly model’s behavior. The assembly product motion ontology with the aid of IA and RCC is evaluated using a task-based approach. The evaluation shows the added value of the developed ontology compared to others published in the literature.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129237277","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}
management in the costume design process: (i) sustainability, (ii) consistency, (iii) convertibility, (iv) immediacy, and (v) shareability. The last article contributed American pair authors, Kim and under the title ’Galois lattices-based formal design concept analysis for crowdsourcing design ‘. The work rests on the three pillars identified in the title. The Galois-lattice is a graphical method of representing knowledge structures. The abstract structure of G-lattice consists of a partially ordered set in which every two elements have a unique supremum (also called a least upper bound or join) and a unique infimum (also called a greatest lower bound or meet). The nodes of G-lattices represent all the possible concepts in a given body of knowledge in the sense that a notion defines a set of individuals or properties with no exceptions or idiosyncrasies. As a recent development, design has become supported by crowdsourcing. The vast knowledge created and contributed by crowds enhances a wide exploration and utilization of design ideas. However, (i) the limited amount of information called ‘scarcity’, (ii) non-guaranteed quality of contributions, and (iii) similar or contradicting contributions made by unspecified participant groups made it difficult to systematically analyze and reuse design concepts. This article presents a formal analysis method for design concepts generated by crowdsourcing design activities. To enable the formal design concept analysis, first a design feature taxonomy was developed by considering crowdsourcing design environment. In this taxonomy, various design features and participant evaluation features were constructed. The Galois lattice-based formal concept analysis was employed as a design concept analysis method. The pivot power case was used to show that the presented method was applicable to a practical crowdsourcing design environment. Finally, precision and recall tests were conducted through a focus group interview and the results from the design analysis without and with the participant evaluation were compared. As a scientific contribution, a formal design analysis method was introduced in this article to represent and extract concepts from crowdsourcing design activities. Since the proposed method can generate concepts from the sparse pieces of data or information, one of the major constraints of crowdsourcing design – namely, limited amount of information - can be eased. This research also showed that setting up
{"title":"Creating and Managing Knowledge in Design by 'Standing on The Shoulders of Giants'","authors":"I. Horváth","doi":"10.3233/jid190021","DOIUrl":"https://doi.org/10.3233/jid190021","url":null,"abstract":"management in the costume design process: (i) sustainability, (ii) consistency, (iii) convertibility, (iv) immediacy, and (v) shareability. The last article contributed American pair authors, Kim and under the title ’Galois lattices-based formal design concept analysis for crowdsourcing design ‘. The work rests on the three pillars identified in the title. The Galois-lattice is a graphical method of representing knowledge structures. The abstract structure of G-lattice consists of a partially ordered set in which every two elements have a unique supremum (also called a least upper bound or join) and a unique infimum (also called a greatest lower bound or meet). The nodes of G-lattices represent all the possible concepts in a given body of knowledge in the sense that a notion defines a set of individuals or properties with no exceptions or idiosyncrasies. As a recent development, design has become supported by crowdsourcing. The vast knowledge created and contributed by crowds enhances a wide exploration and utilization of design ideas. However, (i) the limited amount of information called ‘scarcity’, (ii) non-guaranteed quality of contributions, and (iii) similar or contradicting contributions made by unspecified participant groups made it difficult to systematically analyze and reuse design concepts. This article presents a formal analysis method for design concepts generated by crowdsourcing design activities. To enable the formal design concept analysis, first a design feature taxonomy was developed by considering crowdsourcing design environment. In this taxonomy, various design features and participant evaluation features were constructed. The Galois lattice-based formal concept analysis was employed as a design concept analysis method. The pivot power case was used to show that the presented method was applicable to a practical crowdsourcing design environment. Finally, precision and recall tests were conducted through a focus group interview and the results from the design analysis without and with the participant evaluation were compared. As a scientific contribution, a formal design analysis method was introduced in this article to represent and extract concepts from crowdsourcing design activities. Since the proposed method can generate concepts from the sparse pieces of data or information, one of the major constraints of crowdsourcing design – namely, limited amount of information - can be eased. This research also showed that setting up","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122225061","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}
Theater is a form of communication, whereas knowledge management (KM) is a type of strategy. Knowledge management application in costume design is still at early stage in Asia. Through case study and content analysis, this paper probed into costume design management from the perspective of knowledge accumulation of costume design. Using costume design of a recent production of Shakespeare’s Measure for Measure as an example, this paper digitalized and organized the documents of text analysis, role analysis, character relationship chart, body measurement chart, and costume. It further analyzed the design knowledge generated in costume design in different phases, planed the business framework of knowledge management, and constructed modules of the costume design process. Through design creation, conceptual integration, design record, modification, and renewal, continuously accumulated knowledge is fed back to the knowledge system. This paper thus constructed a knowledge system of costume design. As the nature of costume design is often perceptual, this paper developed the systematic method and procedure of carrying out costume design through the use of a computer design system database and digital calculation. Through design creation, conceptual integration, design record, modification and renewal, the knowledge is fed back to the knowledge system and continuously accumulates. Communicating the theory of knowledge management to costume design is a groundbreaking attempt in the theater field. Providing a working model from an analytic script to stage costume with a project example, this paper also verifies that KM = (P + K) S can and does improve work efficiency in the field of costume design.
{"title":"Application of Knowledge Management in Costume Design: The Case of Measure for Measure","authors":"Yi-Meei Wang, T. Sung","doi":"10.3233/jid200001","DOIUrl":"https://doi.org/10.3233/jid200001","url":null,"abstract":"Theater is a form of communication, whereas knowledge management (KM) is a type of strategy. Knowledge management application in costume design is still at early stage in Asia. Through case study and content analysis, this paper probed into costume design management from the perspective of knowledge accumulation of costume design. Using costume design of a recent production of Shakespeare’s Measure for Measure as an example, this paper digitalized and organized the documents of text analysis, role analysis, character relationship chart, body measurement chart, and costume. It further analyzed the design knowledge generated in costume design in different phases, planed the business framework of knowledge management, and constructed modules of the costume design process. Through design creation, conceptual integration, design record, modification, and renewal, continuously accumulated knowledge is fed back to the knowledge system. This paper thus constructed a knowledge system of costume design. As the nature of costume design is often perceptual, this paper developed the systematic method and procedure of carrying out costume design through the use of a computer design system database and digital calculation. Through design creation, conceptual integration, design record, modification and renewal, the knowledge is fed back to the knowledge system and continuously accumulates. Communicating the theory of knowledge management to costume design is a groundbreaking attempt in the theater field. Providing a working model from an analytic script to stage costume with a project example, this paper also verifies that KM = (P + K) S can and does improve work efficiency in the field of costume design.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123920295","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}
Function-Based (FB) representations of complex systems play an important role in Biologically Inspired Design (BID) by easing the knowledge interchange among biologists, engineers and designers. Many representations have been proposed by scholars over the years, but none of them has ever become a clear favorite. As a matter of fact, each model represents the system from a distinctive perspective. This paper explores the effects of these different representations as creative stimuli for students in order to obtain recommendations for fostering innovation in education and training practices. After introducing a selection of FB models for BID, the paper describes an experiment designed to allow a quantitative comparison of the outcomes of a BID design challenge among undergraduate students attending a course on methods and tools for conceptual design. An analysis of the results of the experiment is followed by the authors’ reflection on directions for educational development.
{"title":"Effects of Function-Based Models in Biologically Inspired Design","authors":"Wei Liu, F. Rosa, G. Cascini, R. Tan","doi":"10.3233/JID200006","DOIUrl":"https://doi.org/10.3233/JID200006","url":null,"abstract":"Function-Based (FB) representations of complex systems play an important role in Biologically Inspired Design (BID) by easing the knowledge interchange among biologists, engineers and designers. Many representations have been proposed by scholars over the years, but none of them has ever become a clear favorite. As a matter of fact, each model represents the system from a distinctive perspective. This paper explores the effects of these different representations as creative stimuli for students in order to obtain recommendations for fostering innovation in education and training practices. After introducing a selection of FB models for BID, the paper describes an experiment designed to allow a quantitative comparison of the outcomes of a BID design challenge among undergraduate students attending a course on methods and tools for conceptual design. An analysis of the results of the experiment is followed by the authors’ reflection on directions for educational development.","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998023","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}
The fast diffusion of new technologies such as the Internet of Things (IoT), Cloud Computing, Wireless Communication, Mobile Computing, Big Data, AI (including Machine Learning), Cyber-Physical Systems, Blockchain, and others, has been leading to a pervasive digital transformation (Foster, 2020; Huang, 2017). In this transformation, many traditional artifacts and business processes are digitalized. Examples include digital medical records, digital media, digital currencies, digital twin, digital manufacturing, and digital engineering (US DoD, 2018). Beyond the digital forms of artifacts and processes and the associated big data phenomenon, the digitalization enables fast dissemination of digital information and much-enhanced knowledge sharing, enables virtualization of various services, enables innovations by leveraging digital technologies, and fosters the creation of new “data products” and “digital knowledge products”. Digital transformation is reshaping the landscape of systems design (Huang et al., 2020). Digital transformation and the associated technologies are efficiently and effectively helping the world to cope with the challenging Covid-19 pandemic. On the other hand, they have also been impacting many aspects of the fast-transforming human society and lead to many issues to deal, to think, and to explore. In today’s rapid-changing and highly competitive environment with an unprecedented richness of information, it is an essential capability to turn big data into knowledge, in order to support effective and efficient decision making and operations processes, no matter in a field of scientific research, engineering, business, healthcare, public services, or others. In the transformation of data into knowledge, machine learning and data analytics play a central role, where efficient big data platforms are fundamental for handling the big data. This issue of JIDPS presents four papers, reflecting research topics on the aspects of deep neural
物联网(IoT)、云计算、无线通信、移动计算、大数据、人工智能(包括机器学习)、网络物理系统、区块链等新技术的快速扩散，已经导致了一场无处不在的数字化转型(Foster, 2020;黄,2017)。在此转换中，许多传统工件和业务流程被数字化。例子包括数字医疗记录、数字媒体、数字货币、数字孪生、数字制造和数字工程(美国国防部，2018年)。除了工件和流程的数字化形式以及相关的大数据现象之外，数字化还使数字信息的快速传播和知识共享得到极大加强，使各种服务得以虚拟化，使利用数字技术进行创新成为可能，并促进创造新的“数据产品”和“数字知识产品”。数字化转型正在重塑系统设计的格局(Huang et al.， 2020)。数字化转型和相关技术正在高效地帮助世界应对具有挑战性的Covid-19大流行。另一方面，它们也影响着快速变革的人类社会的许多方面，并导致许多问题需要处理、思考和探索。在当今瞬息万变、竞争激烈、信息空前丰富的环境中，无论是在科研、工程、商业、医疗保健、公共服务还是其他领域，为了支持有效和高效的决策和运营流程，将大数据转化为知识是一项必不可少的能力。在将数据转化为知识的过程中，机器学习和数据分析发挥着核心作用，高效的大数据平台是处理大数据的基础。本期JIDPS收录了四篇论文，反映了深度神经网络方面的研究课题
{"title":"Leveraging Big Data and Machine Learning for Digital Transformation","authors":"Jingwei Huang","doi":"10.3233/jid190020","DOIUrl":"https://doi.org/10.3233/jid190020","url":null,"abstract":"The fast diffusion of new technologies such as the Internet of Things (IoT), Cloud Computing, Wireless Communication, Mobile Computing, Big Data, AI (including Machine Learning), Cyber-Physical Systems, Blockchain, and others, has been leading to a pervasive digital transformation (Foster, 2020; Huang, 2017). In this transformation, many traditional artifacts and business processes are digitalized. Examples include digital medical records, digital media, digital currencies, digital twin, digital manufacturing, and digital engineering (US DoD, 2018). Beyond the digital forms of artifacts and processes and the associated big data phenomenon, the digitalization enables fast dissemination of digital information and much-enhanced knowledge sharing, enables virtualization of various services, enables innovations by leveraging digital technologies, and fosters the creation of new “data products” and “digital knowledge products”. Digital transformation is reshaping the landscape of systems design (Huang et al., 2020). Digital transformation and the associated technologies are efficiently and effectively helping the world to cope with the challenging Covid-19 pandemic. On the other hand, they have also been impacting many aspects of the fast-transforming human society and lead to many issues to deal, to think, and to explore. In today’s rapid-changing and highly competitive environment with an unprecedented richness of information, it is an essential capability to turn big data into knowledge, in order to support effective and efficient decision making and operations processes, no matter in a field of scientific research, engineering, business, healthcare, public services, or others. In the transformation of data into knowledge, machine learning and data analytics play a central role, where efficient big data platforms are fundamental for handling the big data. This issue of JIDPS presents four papers, reflecting research topics on the aspects of deep neural","PeriodicalId":342559,"journal":{"name":"J. Integr. Des. Process. Sci.","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131529158","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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