Results 41 to 50 of about 22,005,364 (301)

Cyber-Physical Risk Evolution Analysis of Active Distribution Network under Feeder Control Error

Zhongguo dianli, 2021
In the active distribution network cyber-physical system exists a strong coupling relationship between the cyber system and the physical grid. Under the complex cyber-physical interaction, the cyber system anomalies or failures will directly affect and ...
Jiaming WENG, Dong LIU, Yu AN, Haoyang YIN, Zhi HUANG, Han QIN   +5 more
doaj   +1 more source

Effectiveness assessment of Cyber-Physical Systems [PDF]

International Journal of Approximate Reasoning, 2020
By achieving their purposes through interactions with the physical world, Cyber-Physical Systems (CPS) pose new challenges in terms of dependability. Indeed, the evolution of the physical systems they control with transducers can be affected by surrounding physical processes over which they have no control and which may potentially hamper the ...
Rocher, Gérald, Tigli, Jean-Yves, Lavirotte, Stéphane, Le Thanh, Nhan   +3 more
openaire   +5 more sources

Robust Infrared–Visible Fusion Imaging with Decoupled Semantic Segmentation Network

Sensors
The fusion of infrared and visible images provides complementary information from both modalities and has been widely used in surveillance, military, and other fields. However, most of the available fusion methods have only been evaluated with subjective
Xuhui Zhang, Yunpeng Yin, Zhuowei Wang, Heng Wu, Lianglun Cheng, Aimin Yang, Genping Zhao   +6 more
doaj   +1 more source

Automatic Control of Hot Metal Temperature

Metals, 2022
To achieve the automation of blast furnace operation, an automatic control system for hot metal temperature (HMT) was developed. Nonlinear model predictive control (NMPC) which predicts up to ten-hour-ahead HMT and calculates appropriate control actions ...
Yoshinari Hashimoto, Ryosuke Masuda, Max Mulder, Marinus M. (René) van Paassen   +3 more
doaj   +1 more source

Human–Industrial Cyber-Physical System Integration: Design and Evaluation Methods

, 2023
171188In this chapter, the authors focus on the design and evaluation of industrial cyber-physical systems that will be interacting or even cooperating with a human operator.
Pacaux-Lemoine, Marie-Pierre, Flemisch, Frank Ole   +1 more
core   +1 more source

Semi-Supervised Informer for the Compound Fault Diagnosis of Industrial Robots

Sensors
The increasing deployment of industrial robots in manufacturing requires accurate fault diagnosis. Online monitoring data typically consist of a large volume of unlabeled data and a small quantity of labeled data.
Chuanhua Deng, Junjie Song, Chong Chen, Tao Wang, Lianglun Cheng   +4 more
doaj   +1 more source

Intrusion Detection, Prevention, and Response System (IDPRS) for Cyber-Physical Systems (CPSs)

, 2015
Cyber-physical systems (CPSs) are integrated physical, engineered, andsocial systems whose operations are monitored, coordinated, controlled, and integratedby a computing and communication core.
Ding, Jianguo,
core   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Control strategy of robotic manipulator based on multi-task reinforcement learning

Complex & Intelligent Systems
Multi-task learning is important in reinforcement learning where simultaneously training across different tasks allows for leveraging shared information among them, typically leading to better performance than single-task learning.
Tao Wang, Ziming Ruan, Yuyan Wang, Chong Chen   +3 more
doaj   +1 more source