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S. Tepjit
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4 records found
1
Doctoral thesis
(2022)
-
S. Tepjit
Our research concentrated on a newly emerged problem related to smart cyber-physical systems (S-CPSs). The essence of the problem is that S-CPSs are based on reasoning mechanisms that enable them to generate context-dependent solutions for various application problems. Typically, development of application-specific reasoning mechanisms (ASRMs) is a challenge for all stakeholders including software developers, knowledge engineers, and application developers. The research was conducted based on the global research hypothesis stated that an active recommendation framework (ARF) is a computer-aided design support tool with new features, including the coupling of process monitoring and decision support functionalities for compositional design of ASRMs of S-CPSs is not yet proposed. The whole research project was methodologically framed by a logical flow of four research cycles. Each research cycle addressed different aspects of the ARF development. The selected application context was a specific part of the design process of an automated parking assist system (APAS), as the target ASRMs. The research activities included: (i) knowledge aggregation, demarcation of the domain of interest, and specification of requirements; (ii) functional and architectural conceptualization of the ARF; (iii) computational implementation and operationalization of the demonstrative modules; and (iv) validation of the usefulness of the recommendations generated by the implemented demonstrative modules of the ARF. Initially proposed by researchers of the hosting Section of Cyber-Physical Systems Design, the concept of an ARF as significant novelty and supposed to play an influential role in the future. The term “framework” was used to refer to a purposeful enabler that arranges and rationalizes design activities, information processing, and designer-system interaction. The term “recommender” expresses that, as a complex system, the ARF derives context-dependent advice for the designer based on a comprehensive system model of the concerned (specific) design process. The term “active” refers to the fact that the ARF continuously monitors the design process and spontaneously interacts with the designer wherever it is needed in the design process. Our conclusions have been that the ARF goes well beyond the concepts of traditional SEFs and static recommender systems.
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Our research concentrated on a newly emerged problem related to smart cyber-physical systems (S-CPSs). The essence of the problem is that S-CPSs are based on reasoning mechanisms that enable them to generate context-dependent solutions for various application problems. Typically, development of application-specific reasoning mechanisms (ASRMs) is a challenge for all stakeholders including software developers, knowledge engineers, and application developers. The research was conducted based on the global research hypothesis stated that an active recommendation framework (ARF) is a computer-aided design support tool with new features, including the coupling of process monitoring and decision support functionalities for compositional design of ASRMs of S-CPSs is not yet proposed. The whole research project was methodologically framed by a logical flow of four research cycles. Each research cycle addressed different aspects of the ARF development. The selected application context was a specific part of the design process of an automated parking assist system (APAS), as the target ASRMs. The research activities included: (i) knowledge aggregation, demarcation of the domain of interest, and specification of requirements; (ii) functional and architectural conceptualization of the ARF; (iii) computational implementation and operationalization of the demonstrative modules; and (iv) validation of the usefulness of the recommendations generated by the implemented demonstrative modules of the ARF. Initially proposed by researchers of the hosting Section of Cyber-Physical Systems Design, the concept of an ARF as significant novelty and supposed to play an influential role in the future. The term “framework” was used to refer to a purposeful enabler that arranges and rationalizes design activities, information processing, and designer-system interaction. The term “recommender” expresses that, as a complex system, the ARF derives context-dependent advice for the designer based on a comprehensive system model of the concerned (specific) design process. The term “active” refers to the fact that the ARF continuously monitors the design process and spontaneously interacts with the designer wherever it is needed in the design process. Our conclusions have been that the ARF goes well beyond the concepts of traditional SEFs and static recommender systems.
Smart CPSs (S-CPSs) have been evolving beyond what was identified by the traditional definitions of CPSs. The objective of our research is to investigate the concepts and implementations of reasoning processes for S-CPSs, and more specifically, the frameworks proposed for the fuzzy front end of their reasoning mechanisms. The objectives of the paper are: (i) to analyze the framework concepts and implementations of CPS, (ii) to review the literature concerning system-level reasoning and its enablers from the points of view of the processed knowledge, building awareness, reasoning mechanisms, decision making, and adaptation. Our findings are: (i) awareness and adaptation behaviors are considered as system-level smartness of S-CPSs that are not achieved by traditional design approaches; (ii) model-based and composability approaches insufficiently support the development of reasoning mechanisms for S-CPSs; (iii) frameworks for development of reasoning in S-CPS should support compositional design. Based on the conclusions above, we argue that coping with the challenges of compositionality requires both software-level integration and holistic fusion of knowledge by means of semantic transformations. This entails the need for a multi aspect framework that is able to capture at least conceptual, functional, architectural, informational, interoperation, and behavioral aspects. It needs further investigation if a compositionality enabling framework should appear in the form of a meta-framework (abstract) or in the form of a semantically integrated (concrete) framework.
...
Smart CPSs (S-CPSs) have been evolving beyond what was identified by the traditional definitions of CPSs. The objective of our research is to investigate the concepts and implementations of reasoning processes for S-CPSs, and more specifically, the frameworks proposed for the fuzzy front end of their reasoning mechanisms. The objectives of the paper are: (i) to analyze the framework concepts and implementations of CPS, (ii) to review the literature concerning system-level reasoning and its enablers from the points of view of the processed knowledge, building awareness, reasoning mechanisms, decision making, and adaptation. Our findings are: (i) awareness and adaptation behaviors are considered as system-level smartness of S-CPSs that are not achieved by traditional design approaches; (ii) model-based and composability approaches insufficiently support the development of reasoning mechanisms for S-CPSs; (iii) frameworks for development of reasoning in S-CPS should support compositional design. Based on the conclusions above, we argue that coping with the challenges of compositionality requires both software-level integration and holistic fusion of knowledge by means of semantic transformations. This entails the need for a multi aspect framework that is able to capture at least conceptual, functional, architectural, informational, interoperation, and behavioral aspects. It needs further investigation if a compositionality enabling framework should appear in the form of a meta-framework (abstract) or in the form of a semantically integrated (concrete) framework.
Smart CPSs (S-CPSs) have been evolving beyond what was identified by the traditional definitions of CPSs. The objective of our research is to investigate the concepts and implementations of S-CPSs, and more specifically, the frameworks proposed for the fuzzy front end of their reasoning processes. The objectives of the paper are: (i) overview of the various framework concepts and implementations in the context of S-CPS, and (ii) analyze the presented frameworks from the points of view of reasoning processes of S-CPSs that included the concepts of structuring knowledge, building awareness, situated reasoning, decision making, and system adaptation. Our major findings are: (i) model-based and composability approaches do not support a development of S-CPSs; (ii) awareness and adaptation behaviors are considered as system level characteristics of S-CPSs that are not achieved by traditional design approaches; (iii) a new framework development should support a compositional design for reasoning in S-CPS. Based on the findings above, we argue that a development of S-CPSs should be supported by a proper framework development for compositional design of smart reasoning and coping with the challenges of compositionality requires both software-level integration and holistic fusion of knowledge by means of semantic transformations. It needs further investigation if a compositionality enabling framework should appear in the form of a meta-framework (abstract) or in the form of a semantically integrated (concrete) framework.
...
Smart CPSs (S-CPSs) have been evolving beyond what was identified by the traditional definitions of CPSs. The objective of our research is to investigate the concepts and implementations of S-CPSs, and more specifically, the frameworks proposed for the fuzzy front end of their reasoning processes. The objectives of the paper are: (i) overview of the various framework concepts and implementations in the context of S-CPS, and (ii) analyze the presented frameworks from the points of view of reasoning processes of S-CPSs that included the concepts of structuring knowledge, building awareness, situated reasoning, decision making, and system adaptation. Our major findings are: (i) model-based and composability approaches do not support a development of S-CPSs; (ii) awareness and adaptation behaviors are considered as system level characteristics of S-CPSs that are not achieved by traditional design approaches; (iii) a new framework development should support a compositional design for reasoning in S-CPS. Based on the findings above, we argue that a development of S-CPSs should be supported by a proper framework development for compositional design of smart reasoning and coping with the challenges of compositionality requires both software-level integration and holistic fusion of knowledge by means of semantic transformations. It needs further investigation if a compositionality enabling framework should appear in the form of a meta-framework (abstract) or in the form of a semantically integrated (concrete) framework.
Compositional engineering frameworks for development of smart cyber-physical systems
A critical survey of the current state of progression
Various system-engineering frameworks (SEFs) have been developed for composable systems, whose overall operation is the sum of the operations of their components. However, smart cyber-physical systems (S-CPSs) are compositional in nature. Their reasoning capability and system knowledge assume an ‘ampliative’ (inter)operation of all hardware, software, or cyberware components. The need for SEFs that support synthesis, modeling, analysis, simulation, verification, and validation of S-CPSs is recognized in the literature. The objective of this paper is a critically review the state of development of compositionality enabling frameworks. Both quantitative and qualitative literature studies were conducted in combination with critical system thinking. The reasoning model used in the qualitative analysis was derived based on the findings of the quantitative analysis. The major observations are: (i) the notion of compositionality is not studied extensively in the context of S-CPSs that do not obey the principle of reductionism, (ii) methodological support of implementation of compositional CPSs seems to be in its infancy, (iii) SEFs may play a crucial role in synthesis, modeling and implementation of S-CPSs, and (iv) SEFs for compositional system design may be realized using the principles of semantic knowledge fusion or meta-synthesis. Our follow up research targets a formal definition and computational implementation of a testable prototype of a specific SEF tool supporting compositional design of reasoning mechanisms.
...
Various system-engineering frameworks (SEFs) have been developed for composable systems, whose overall operation is the sum of the operations of their components. However, smart cyber-physical systems (S-CPSs) are compositional in nature. Their reasoning capability and system knowledge assume an ‘ampliative’ (inter)operation of all hardware, software, or cyberware components. The need for SEFs that support synthesis, modeling, analysis, simulation, verification, and validation of S-CPSs is recognized in the literature. The objective of this paper is a critically review the state of development of compositionality enabling frameworks. Both quantitative and qualitative literature studies were conducted in combination with critical system thinking. The reasoning model used in the qualitative analysis was derived based on the findings of the quantitative analysis. The major observations are: (i) the notion of compositionality is not studied extensively in the context of S-CPSs that do not obey the principle of reductionism, (ii) methodological support of implementation of compositional CPSs seems to be in its infancy, (iii) SEFs may play a crucial role in synthesis, modeling and implementation of S-CPSs, and (iv) SEFs for compositional system design may be realized using the principles of semantic knowledge fusion or meta-synthesis. Our follow up research targets a formal definition and computational implementation of a testable prototype of a specific SEF tool supporting compositional design of reasoning mechanisms.