In order to deeply implement the sustainable development strategy, effectively implement the 'dual carbon' goal, improve the efficiency and lifespan of electronic equipment, in-depth research on new power syst...
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With the development of human-computer interaction, tactile gesture recognition has been widely used in our life. To solve the problem of overfitting on the sample-limited tactile datasets, we apply the Supervised Aut...
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The goal of a recommender system is to recommend the most suitable items to a user from a large number of candidate items. The computational cost increases with the number of user requests and the complexity of the se...
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Actuator backlash nonlinearity typically leads to delays, oscillations, and errors, thereby affecting the effective control of actuators in closed-loop systems. To suppress the effects of backlash, numerous adaptive b...
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The six-degree-of-freedom Stewart-Gough platform finds use in a variety of fields, such as radio telescopes, micromanipulators, motion simulators, parallel machine tools, stabilizing elements, and etc. Two categories ...
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Humans have often been perceived as a leading cause of error in Zero-defect manufacturing (ZDM) processes. There is thus a reduction of human interventions in the deployment of industry 4.0 (I4.0) technologies used fo...
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ISBN:
(纸本)9783031381645;9783031381652
Humans have often been perceived as a leading cause of error in Zero-defect manufacturing (ZDM) processes. There is thus a reduction of human interventions in the deployment of industry 4.0 (I4.0) technologies used for ZDM such as Machine Learning (ML). However, as manufacturing (e.g., I4.0 context) is often placed within a socio-technological context involving the co-integration of humans and technology, the manufacturing processes are now more vulnerable to cyber risk and threats. System vulnerabilities also derive from limitations associated with ML. This paper highlights three challenges associated with ML: explainability, data privacy, and security for ZDM. We argue that due to the high level of data complexity and lack of flexibility in ML models, humans play a critical role in ZDM decision-making. The paper explores the concept of security culture as an enabler for transformative resilience and zero-defect manufacturing and contributes to rethinking the human-centered approach in ZDM. The paper stresses a need to enhance contextual and empirical understanding of transformative resilience and security culture in ML/ZDM environments to better address adverse events such as cyber threat situations.
As the integration of digital technologies with Industrial controlsystems (ICS) and Operational technology (OT) continues to deepen, these systems increasingly become targets for sophisticated cyber attacks. These at...
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ISBN:
(纸本)9798350367102;9798350367096
As the integration of digital technologies with Industrial controlsystems (ICS) and Operational technology (OT) continues to deepen, these systems increasingly become targets for sophisticated cyber attacks. These attacks not only threaten the operational integrity but also pose significant risks to national security and public safety. In this paper, we provide insights into the value of ICS/OT security solutions that are based on Identity and Access Management (IAM). Beginning with presenting an abstraction model for typical ICS/OT attacks, the paper systematically outlines the main stages of an attack and the corresponding vectors employed by adversaries. Drawing from the MITRE ATT&CK framework tailored for ICS, the paper quantifies the extent to which IAM-based mitigation approaches can strengthen defense-in-depth mechanisms against cyber threats targeting ICS/OT environments. Our findings show that there are modern attack vectors that can only be mitigated through robust IAM solutions. Moreover, we found that while advanced techniques such as firewall and gateway-based intelligent threat detection play a significant role in safeguarding ICS/OT, they are insufficient on their own to address several attack vectors in ICS/OT environments.
This paper presents an advanced control error processing to enable the feedback position control of an industrial robot based on external sensor signals for dual-stage actuation. A measurement module comprising a magn...
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ISBN:
(纸本)9798350355376;9798350355369
This paper presents an advanced control error processing to enable the feedback position control of an industrial robot based on external sensor signals for dual-stage actuation. A measurement module comprising a magnetically levitated platform with an integrated 3D measurement tool is mounted as end effector on the industrial robot. The industrial robot is used to maintain the measurement platform within its limited actuation range, while actively tracking a sample in motion. The measurement module provides the short stroke but precision positioning of the measurement tool relative to a sample surface in 6-DoF. For a feedback controlled repositioning of the industrial robot's tool center point based on the internal measurement platform's position signals, a real-time interface is used. The implementation of the advanced control error processing successfully demonstrates the active tracking of a sample in motion, with residual tracking errors of 473 nm rms in sample-motion direction.
Customary low-voltage circuit breakers lack integrated chips, making them challenging to enhance with smart capabilities. However, with advancements in chip and data technology, it's now possible to incorporate el...
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The dynamic-memory event-triggered control problem for networked controlsystems is investigated in this paper. Firstly, a dynamic-memory event-triggered scheme (DMETS) is proposed to reduce the unnecessary data trans...
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