A Review of the Principles of Designing Smart Cyber-Physical Systems for Run-Time Adaptation: Learned Lessons and Open Issues

Tavčar, Jože; Horváth, Imre

doi:10.1109/tsmc.2018.2814539

Cited by 59 publications

(31 citation statements)

References 116 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the age of artificial intelligence, big data (Wang, Yang, Liu & Deen, 2018), edge computing (Wang, Yao, Zheng, Sun & Song, 2019), cyber-physical system (Tavcar & Horvath, 2019) and other modern information technologies have developed rapidly, providing a brand new way of learning and an unprecedented new approach for foreign language teaching (Fang, 2019;Xin, 2019). Hu Peiran et al (2018), starting from the definition of education technology, positioned the function of higher education technology center in servicing the whole process of college teaching and learning, and in view of three objects of implementation behavior including technology providers, technology users and technical evaluators, respectively put forward the concrete function orientation, making clear of the role of modern information technology like big data in education in colleges and universities and their status in the development of education reform in the era of artificial intelligence.…”

Section: Related Workmentioning

confidence: 99%

A Study of College English Culture Intelligence-Aided Teaching System and Teaching Pattern

Cao¹,

Li²,

Jun³

2020

ELT

View full text Add to dashboard Cite

College English teaching is supposed to cover both language acquisition and culture learning due to the close relationship between language and culture, taking cultural teaching as an indispensible part of college English courses. With the rapid integration of information technology and English curriculum, artificial intelligence has brought new opportunities to college English teaching, and college English cultural teaching methods are now faced with new innovations. In the age of intelligence, to promote teaching quality and learning effect, artificial intelligence technology can be embedded in English teaching practice, exerting its technical advantages and frontier characteristics. In consideration of integrated developing tendency of college English cultural teaching model and modern information technology, the paper is aimed to design and build up an intelligence-aided system so as to extend the depth and width of the application of modern information technology in college English cultural teaching as well as to exploit the great application potential of modern information technology in college English cultural teaching, thus opening a new way and presenting a direction for college English cultural teaching.

show abstract

Section: Related Workmentioning

confidence: 99%

A Study of College English Culture Intelligence-Aided Teaching System and Teaching Pattern

Cao¹,

Li²,

Jun³

2020

ELT

View full text Add to dashboard Cite

show abstract

“…This entails that multi-actor S-CPSs are not fully deterministic systems. They have some level of freedom in setting the objectives of system operations, as well as the capability of adapting themselves to varying tasks, situations, and contexts (Tavčar, and Horváth, 2018).…”

Section: Characteristics Of Smart Cyber-physical Systemsmentioning

confidence: 99%

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Tavčar

Duhovnik

Horváth

2020

JID

View full text Add to dashboard Cite

Conventionally, designing of a technical system is completed in the product development phase in terms of all details and aspects. This can be done if the expected behavior and the conditions of operation are known in advance and can be validated before the product is launched on the market. Validation is typically based on a predictive analysis or simulation of the designed operation. However, this contradicts with the case of smart systems, such as smart cyber-physical systems (CPSs), which self-manage their operation or at least a part of it. Being able to adapt at run-time and evolve over time, smart CPSs cannot be validated using conventional deterministic approaches. This is especially true for smart CPSs used as instrumentation in the medical field. This gave the stimulation of our background research, the results of which are concisely summarized and critically concluded in this paper. The literature has been found fairly narrow in terms of novel validation approaches for self-managing smart systems. The main finding is that the tasks of operational and behavioral validation should be shared among the system designers and the designed systems. Designers need prognostic approaches, while systems need to construct validation plans and execute them at run-time. This needs validation-specific functionalities and context dependent mechanisms such as run-time validation frameworks or meta-models, objective-sensitive self-monitoring mechanisms, self-constraining and self-supporting mechanisms, and other enablers. Extensive foundational research and system prototype testing are deemed to be indispensable. To make the first small step in this direction, this paper proposes a concept for validation of smart medical CPSs. This relies on the following hypothesis: If a system has freedom for self-adaptation, then it should also be equipped with selfcontrol mechanism, meta-knowledge and a supervisory controller. It all together enables a purpose-and context dependent semantic reasoning about the operational and behavioral objectives. The paper suggests a number of topics for future research towards a run-time validation engine.

show abstract

“…Smart CPS technology is result of long-term development in automatic equipment and device control and in active knowledge representation for engineering model and product operation control. Authors of [14] analyze changes caused by increasingly complex engineered systems. They define smart cyber-physical system, which is empowered by cyber-physical computing features and has capabilities for reasoning, learning, adapting, and evolving.…”

Section: General Model Of Integrated Smart Engineering Systemmentioning

confidence: 99%

Smart Engineering Modeling for Smart Industrial Products

Horváth

2019

ACTA POLYTECH HUNG

View full text Add to dashboard Cite

Automation of industrial and consumer products has reached the level on which systems provide for the capability to supervise decisions on physical actions and execution of these actions. Development of these industrial products proceed during their full lifecycle requiring lifecycle integration of innovation, manufacturing, and application as well as utilization the recently emerged methodology of continuous engineering. Engineering in the above level of industrial technology requires contextually integrated model system which serves all research, development, production, and operational activities during the integrated life cycle of product. Smart product requires smart model system which has the capability to recognize situation and apply it at decision on values of relevant product object parameters in virtual to control physical operation of product. This paper introduces recent contributions in modeling for smart engineering. It starts with a novel general model of integrated smart engineering system. Considering this model, smart engineering specific upgrade of formerly published concept of virtual engineering space (VES) is introduced. VES upgrade concentrates on research as key issue in giving smart characteristics for contexts in VES model system. Following this, contextual driving of object parameters is outlined for integrated smart engineering system. The remaining part of paper introduces concept and plan of virtual research laboratory (VRL) in close connection with modeling for integrated smart engineering system. Plans are outlined for next future implementation of the VRL concept and methodology at the Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University. The laboratory system consists of research eligible configuration of the 3DEXPERIENCE engineering modeling platform. It is accessed in the professional cloud of Dassault Systémes.Keywords: system level model of engineering structure; virtual engineering space (VES); contextual driving structure in engineering model; virtual research laboratory (VRL)

show abstract

A Review of the Principles of Designing Smart Cyber-Physical Systems for Run-Time Adaptation: Learned Lessons and Open Issues

Cited by 59 publications

References 116 publications

A Study of College English Culture Intelligence-Aided Teaching System and Teaching Pattern

A Study of College English Culture Intelligence-Aided Teaching System and Teaching Pattern

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Smart Engineering Modeling for Smart Industrial Products

Contact Info

Product

Resources

About