Formal interpretation of cyber-physical system performance with temporal logic

Chen, Gang; Sabato, Zachary; Kong, Zhaodan

doi:10.1080/23335777.2018.1510857

Cited by 6 publications

(1 citation statement)

References 26 publications

(50 reference statements)

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“…CPS's cooperation with IoT can produce remarkable progress in various industries. Fully grasping the distinctions and the relationship between IoT and CPS is of the utmost importance [33,[45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

A Mixed Reality-Based Platform towards Human-Cyber-Physical Systems with IoT Wearable Device for Occupational Safety and Health Training

Li¹,

Liang

Chow

et al. 2022

Applied Sciences

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Occupational safety and health (OSH) should be regarded as a crucial challenge that affects the public world widely. Work-related accidents and occupational illness contribute to considerable mortality and morbidity. As technology advances, mixed reality (MR) has gained popularity. To minimize occupational accidents occurring in the workplace and reduce human training time, an MR-based platform for OSH training combined with CPS and IoT technology is proposed in this paper. Multi-criteria decision-making (MCDM) and fuzzy-analytic hierarchy process (FAHP) were applied to evaluate and select suitable gloves. Only when the MR wearable devices are improved can a more powerful MR-based OSH training program be established. A higher immersive level of OSH training offers people a more realistic experience. They will better understand possible risks in workers’ future work, resulting in a lower occupational accident rate in the workplace.

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Section: Introductionmentioning

confidence: 99%

A Mixed Reality-Based Platform towards Human-Cyber-Physical Systems with IoT Wearable Device for Occupational Safety and Health Training

Li¹,

Liang

Chow

et al. 2022

Applied Sciences

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Control/physical systems co-design with spectral temporal logic specifications and its applications to MEMS

Chen,

Kong,

Xie

2024

International Journal of Control

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Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society

Ogbuke

Yusuf

Kovvuri

et al. 2020

Production Planning & Control

114

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This study conducted a comprehensive review of big data supply chain analytics (BDSCA). The paper explored the application of big data in supply chain management and its benefits for organisations and society. The paper also examined the ethical, security, privacy and operational challenges of big data techniques, as well as the potential reputational damages to businesses. The review outlined four principal facets, namely: Big data analytics, applications, ethics and privacy issues, and how organizations employed this emerging tool to anticipate and even predict the future and direct their operations. These principle facets are built across the multiple levels and unique conceptual standpoints indicated by 7 themes and 14 sub-themes. These themes were generated based on 120 articles (2005À2020) drawn mainly from leading academic journals. Overall, there is a considerable consensus across current literature that big data analytics extend far beyond just reinventing the supply chain. It has the potential to support more responsive next-generation of global companies who are operating in an increasingly challenging and uncertain environment.

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Formal interpretation of cyber-physical system performance with temporal logic

Cited by 6 publications

References 26 publications

A Mixed Reality-Based Platform towards Human-Cyber-Physical Systems with IoT Wearable Device for Occupational Safety and Health Training

A Mixed Reality-Based Platform towards Human-Cyber-Physical Systems with IoT Wearable Device for Occupational Safety and Health Training

Control/physical systems co-design with spectral temporal logic specifications and its applications to MEMS

Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society

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