Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection b...
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Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.
This study explores the use of agile approaches to the creation of ontologies for e-learning, evaluating the benefits and drawbacks as well as the impact on information display. Traditional strategies conflict with th...
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To enhance the capability of classifying and localizing defects on the surface of hot-rolled strips, this paper proposed an algorithm based on YOLOv7 to improve defect detection. The BI-SPPFCSPC structure was incorpor...
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Recently,potassium-ion batteries(PIBs) have received significant attention in the energy storage field owing to their high-power output,fast charging capability,natural abundance,and environmental ***,we comprehensive...
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Recently,potassium-ion batteries(PIBs) have received significant attention in the energy storage field owing to their high-power output,fast charging capability,natural abundance,and environmental ***,we comprehensively review recent advancements in the design and development of carbon-based anode materials for PIBs anodes,covering graphite,hard carbon,alloy and conversion materials with carbon,and carbon host for K metal *** strategies such as structural engineering,heteroatom-doping,and surface modifications are highlighted to improve electrochemical performances as well as to resolve technical challenges,such as electrode instability,low initial Coulombic efficiency,and electrolyte ***,we discuss the fundamental understanding of potassium-ion storage mechanisms of carbon-based materials and their correlation with electrochemical ***,we present the current challenges and future research directions for the practical implementation of carbon-based anodes to enhance their potential as next-generation energy storage materials for *** review aims to provide our own insights into innovative design strategies for advanced PIB's anode through the chemical and engineering strategies.
Surveillance cameras have been widely used for monitoring in both private and public sectors as a security *** Circuits Television(CCTV)Cameras are used to surveillance and monitor the normal and anomalous ***-world a...
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Surveillance cameras have been widely used for monitoring in both private and public sectors as a security *** Circuits Television(CCTV)Cameras are used to surveillance and monitor the normal and anomalous ***-world anomaly detection is a significant challenge due to its complex and diverse *** is difficult to manually analyze because vast amounts of video data have been generated through surveillance systems,and the need for automated techniques has been raised to enhance detection *** paper proposes a novel deep-stacked ensemble model integrated with a data augmentation approach called Stack Ensemble Road Anomaly Detection(SERAD).SERAD is used to detect and classify the four most happening road anomalies,such as accidents,car fires,fighting,and snatching,through road surveillance videos with high *** SERAD adapted three pre-trained Convolutional Neural Networks(CNNs)models,namely VGG19,ResNet50 and *** stacking technique is employed to incorporate these three models,resulting in much-improved accuracy for classifying road abnormalities compared to individual ***,it presented a custom real-world Road Anomaly Dataset(RAD)comprising a comprehensive collection of road images and *** experimental results demonstrate the strength and reliability of the proposed SERAD model,achieving an impressive classification accuracy of 98.7%.The results indicate that the proposed SERAD model outperforms than the individual CNN base models.
Graph neural networks have proven their effectiveness for user-item interaction graph collaborative filtering. However, most of the existing recommendation models highly depended on abundant and high-quality datasets ...
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One of the impacts of the COVID pandemic has been to force people to find alternates sources for daily supplies, turning to online to offline (O2O) platforms. The service quality of the O2O platform naturally affects ...
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Point cloud completion is crucial in point cloud processing, as it can repair and refine incomplete 3D data, ensuring more accurate models. However, current point cloud completion methods commonly face a challenge: th...
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With the development of deep learning and computer vision, face detection has achieved rapid progress owing. Face detection has several application domains, including identity authentication, security protection, medi...
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This study investigates robot path planning for multiple agents,focusing on the critical requirement that agents can pursue concurrent pathways without *** agent is assigned a task within the environment to reach a de...
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This study investigates robot path planning for multiple agents,focusing on the critical requirement that agents can pursue concurrent pathways without *** agent is assigned a task within the environment to reach a designated *** the map or goal changes unexpectedly,particularly in dynamic and unknown environments,it can lead to potential failures or performance degradation in various ***,priority inheritance plays a significant role in path planning and can impact *** study proposes a ConflictBased Search(CBS)approach,introducing a unique hierarchical search mechanism for planning paths for multiple *** study aims to enhance flexibility in adapting to different *** scenarios were tested,and the accuracy of the proposed algorithm was *** the first scenario,path planning was applied in unknown environments,both stationary and mobile,yielding excellent results in terms of time to arrival and path length,with a time of 2.3 *** the second scenario,the algorithm was applied to complex environments containing sharp corners and unknown obstacles,resulting in a time of 2.6 s,with the algorithm also performing well in terms of path *** the final scenario,the multi-objective algorithm was tested in a warehouse environment containing fixed,mobile,and multi-targeted obstacles,achieving a result of up to 100.4 *** on the results and comparisons with previous work,the proposed method was found to be highly effective,efficient,and suitable for various environments.
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