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检索条件"任意字段=International Conference on Process Automation, Control and Computing"

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Intra-Day Rolling Optimal Strategy Considering Whole Dispatch process and Multi-Type Adjustable Measures

Intra-Day Rolling Optimal Strategy Considering Whole Dispatc...

引用

IEEE international conference on Power and Energy Applications (ICPEA)

作者： Wenzhong Li Duanhong Zhang Xichen Tian Yan Lv Zhengqi Xu Jingfeng Liang State Grid Fujian Electric Power Dispatching and Control Center State Grid Fujian Electric Power Company Fuzhou China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

The current electric power system practices hierarchical and zonal administration to facilitate more effective monitoring of grid safety and event management. With an escalating integration of new energy sources on the generation side, the intrinsically variable nature of these resources introduces substantial uncertainties into grid operations. Meanwhile, on the demand side, load profiles are diversifying further, significantly influenced by weather conditions, market price signals, or incentive schemes, thereby adding another layer of unpredictability. Against this context, this paper proposes an intra-day rolling optimal strategy considering whole dispatch process and multi-type adjustable measures. By synthesizing regulating resources from both the source and load sides, it undertakes a series of intra-day rolling optimization decisions across the entire dispatch workflow. This strategy aims to harmonize and optimize the allocation of various resources, thereby ensuring the secure and stable functioning of the electrical grid amidst the complexities introduced by the integration of intermittent renewables and the dynamics of diversified loads.

关键词： Renewable energy sources Power measurement Uncertainty Power supplies process control Robustness Safety Power system reliability Resource management Optimization

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Search Based Testing for Code Coverage and Falsification in Cyber-Physical Systems

Search Based Testing for Code Coverage and Falsification in ...

引用

IEEE international conference on automation Science and Engineering (CASE)

作者： Quinn Thibeault Tanmay Khandait Giulia Pedrielli Georgios Fainekos School of Computing and Augmented Intelligence Arizona State University Tempe United States of America Toyota Research Institute of North America Ann Arbor United States of America

State of the art test case generation tools vary in the way they exploit knowledge of the system under test. While experimental results demonstrate that such knowledge can improve the efficiency of the test case generation process, how to (automatically) retrieve and integrate such information in test generation is non-trivial. Especially, in the case of Cyber-Physical Systems (CPS), the problem is more challenging since CPS have not only software requirements but also physical functional requirements. In this work, we instrument a system's source code to extract run-time information related to the behavior of the system to determine the path taken through the source code itself. Given our focus on CPS, this information enables us to compute a metric representing the total coverage of the system behaviors for a series of inputs. We present the framework to instrument the code, and our method for using the instrumented code to calculate coverage-related robustness. We also demonstrate how to integrate this approach into a search to generate tests that can manage the trade-off between code coverage and identification of functionally unsafe behaviors (falsification). Our results show that our approach is more efficient than Uniform Random sampling in covering CPS operating modes (code). In addition, we show that our approach promotes better falsifications when violating inputs are present in a, possibly small, subset of the CPS states.

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Classification of Information Objects with Fuzzy Parameters in E-Learning Systems

Classification of Information Objects with Fuzzy Parameters ...

引用

IEEE international Workshop on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications

作者： Vadym Mukhin Valerii Zavgorodnii Viacheslav Liskin Sergiy Syrota Vasyl Koval Liudmyla Honchar Department of System Design National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Information Systems and Technologies National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Applied Mathematics National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kiev Ukraine Department of Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine Department of Computer Science West Ukrainian National University Ternopil Ukraine

The paper describes the process of the information objects classification in e-learning systems using the mathematical background of fuzzy logic. This approach can be used to improve the process of searching and organizing information in e-learning systems. As the volume of educational materials grows, it becomes more and more difficult to find and structure information. Fuzzy logic helps to optimize the search, and the use of a neural network can correctly classify materials in e-learning systems, which increases the efficiency and accuracy of search queries.

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Meticulous Approach to Internet of Things in Precision Agriculture: A Review 3

Meticulous Approach to Internet of Things in Precision Agric...

引用

3rd international conference on Advances in computing, Communication control and Networking, ICAC3N 2021

作者： Akilan, T. Baalamurugan, K.M. Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9781665438117

It is critical to raise the yield of agriculture and farming activities in order to improve the productivity and low cost. The emerging technology like Internet of Things, can improve the efficiency of agriculture and farming processes by eliminating human intervention through automation. The IoT has transformed into agriculture industry in the view of both quality and quantity. The combination of species hybridization and real-time farm monitoring cleared the path for resource optimization. Researchers, research institutions, academics, and most countries throughout the world are advancing toward the development and accomplishment of collaboration in team project in order to expand the field's horizons for the benefit of humanity. The goal of this research is to examine newly emerging applications using IoT in the field of agricultural sector and farming sector in view of the findings of sensor data and technology. Various IoT devices and communication mechanisms was examined in order to demonstrate which sensors are accessible for certain agriculture productivity such as soil condition, crop condition, irrigation finally wind speed. © 2021 IEEE.

关键词： Soil moisture

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Deep Reinforcement Learning-Based Task Unloading Algorithm in MEC 11

Deep Reinforcement Learning-Based Task Unloading Algorithm i...

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11th international conference of Information and Communication Technology, ICTech 2022

作者： Yin, Zhenyu Bi, Zhiying Chai, Anying He, Zhiyun Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

MEC is a new form that provides rich computing capability closing to the network edge to get closer to the users. In mobile edge computing, the mobile device can offload some tasks to the edge server for data storage and calculation. This paper assumes that there are a mobile device, multiple edge servers, and each edge server has limited resources. In order to improve the task offloading and assignment efficiency of MEC and decrease the equipment energy consumption and task execution delay, this paper proposes a task offloading algorithm based on modified deep reinforcement learning to select a best edge server for each offloading task. Firstly, the problem is described as a Markov decision process, a system model is established, and then deep reinforcement learning algorithms are used to solve the optimal task offloading strategy. The task offloading method based on deep reinforcement learning improves the algorithm convergence speed by setting the experience relay memory to quickly update the parameters in the network. Experimental results show that the algorithm improves the efficiency of task offloading compared with the commonly used basic algorithms, reduces the energy consumption of equipment and the time delay about task execution, and proves the reliability of the algorithm. © 2022 IEEE.

关键词： Reinforcement learning

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Fog-Cloud-IoT Enabled WSN Architecture 3

Fog-Cloud-IoT Enabled WSN Architecture

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Anitha Christy Angelin, P. Samuel Devakumar, P.V. Al-Farhani, Liwa H. Kumar, Gandam Vijay Deep, Shaurya Mohammad, Shoaib PSNA College of Engineering and Technology Tamilnadu Dindigul India Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India RUDN University System Analysis Control and Information Processing Academy of Engineering Moscow Russia Career Point University Computer Science and Engineering Rajasthan India IIMT College of Management Greater Noida India IMS Unison University Department of Law Uttarakhand Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Remote Because of the exciting innovation it introduces, the WSN likely to be a subject of research in recent time. Because of the impromptu distant connections, adaptability, and simplicity of execution, this has all the makings of becoming the most maintainable innovation for ecological detecting, whether it's about limited or huge scope watching. In any case, the main drawbacks stem from the limited capacity, processing, and accessibility of organization centers for information. Virtual machines resources have been adopted to overcome such constraints, devices to expanded capacity, computation, and easy-to-understand availability. This was a natural progression from traditional WSN designs among pattern in recent theories evolved along advent of Internet-of-Things advancements. Against the growing popularity of WSN associated cloud checking frameworks, still the issues are detected because of the distributed comp ting's disadvantages, like dormancy with the capacity charges. In this paper, the advancements achieved to a fog-cloud-IoT associated with WSN architecture of putting a bit of computing at the network part are elaborated, a process, which follows the smart Fog associated with Cloud-computing concept of dissecting also following up on IoT data. A similar investigation was carried out to illustrate the improvements made possible by processing at the organization's edge. © 2022 IEEE.

关键词： Fog computing

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Quality control for Small Multi Domain Industries Using Image processing

Quality Control for Small Multi Domain Industries Using Imag...

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MIT Art, Design and Technology School of computing international conference (MITADTSoCiCon)

作者： Puja Chavan Cholke Jayant Kulkarni Ananya Sharma Atharva Ansingkar Sarvesh Bajare Sarthak Biyani Shreya Bhosale Information Technology Vishwakarma Institute of Technology Pune India Instrumentation and Control Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798350362879

ISBN: (纸本)9798350362886

Strategic acquisition and effective management of resources empower small industries to overcome challenges, thrive in their respective sectors, and contribute to economic growth. Scarcity of resources and the intricacy of overseeing numerous production lines present particular difficulties for small, multi-domain firms in preserving a consistent level of product quality. Conventional quality control techniques frequently struggle to adequately address existing problems. These include the initial outlay needed to establish the image processing infrastructure, the possible limits in managing intricate product variants, and the requirement for large training datasets for machine learning models. Automating and enhancing the accuracy of quality control processes can be achieved through the integration of image processing technologies. Creating and implementing a strong quality control system suited for small multi-domain enterprises is the main goal of this study. The emphasis is on using image processing techniques to improve the precision and effectiveness of quality evaluation, fault identification, and classification across various product *** proposed approach analyses object photos taken in a controlled environment with suitable constraints. Techniques for feature extraction and image segmentation are used to find abnormalities and flaws. Real-time quality assessment is made possible by the integration of machine learning models, which enable automated decision-making. The solution enables accurate identification of circular objects inside the images through the successful detection and classification of *** study is a viable solution for improving production processes because of its scalability, and accuracy in circle detection.

关键词： Industries Accuracy Biological system modeling process control Quality control Machine learning Production

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Secure Data Sharing Method Based on Federated Learning in IoVs

Secure Data Sharing Method Based on Federated Learning in Io...

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IEEE international conference on Communications (ICC)

作者： Shu-Jia Fan Jia-Wen Xue School of Computing and Information Technology University of Wollongong Australia Department of Automation & Information Engineering Xi'an University of Technology Xi'an China

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In the realm of the Internet of Vehicles (IoVs), a broad spectrum of information encompassing vehicle operation, traffic conditions, and incidents can be exchanged between vehicles and infrastructure. This data plays a pivotal role in enhancing decision-making processes and holds considerable importance for the advancement of autonomous driving and traffic management. Utilizing machine learning (ML) methods, vehicles can assimilate insights from road and environmental data, subsequently sharing trained model parameters. Addressing concerns related to data security and user privacy during the data-sharing process in IoVs, a framework called DBL is introduced. This framework leverages blockchain and federated learning to validate local model updates. It facilitates the updating and exchange of local ML models among multiple participants, with the option to upload these models to Road Side Units (RSUs). Subsequently, RSUs scrutinize the local ML models, identifying and discarding any malicious ones while aggregating the legitimate ones to generate the global ML model. Simulation results demonstrate that the proposed DBL framework not only safeguards user data privacy but also enhances model accuracy.

关键词： Training Data privacy Federated learning Data security Simulation Roads Road side unit

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Enhancing Power Efficiency by Integrating processor Performance Metrics with Power Supply Phase control

Enhancing Power Efficiency by Integrating Processor Performa...

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international conference on Renewable Energy Research and Applications (ICRERA)

作者： Shinichi Kawaguchi Department of Clinical Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

The processor is the most power-consuming device in a computer, yet it often operates under light load conditions for extended periods. During these times, the processor's power supply also experiences a light load, which significantly decreases its efficiency. Therefore, maintaining high efficiency across a wide range of conditions, including light load, is crucial. Previously, an adaptive power efficiency control method was proposed that links real-time power control to the processor's logical data processing workload, optimizing the configuration to achieve the highest possible power efficiency. While this method has shown the potential to improve CPU power efficiency in some programs, processor power fluctuations vary depending on the computing system, and the characteristics of power load differ according to the program being executed. In this study, the processor power supply efficiency improvement under more fluctuating power loads was experimentally verified by applying the proposed method during the execution of various types of programs. The results confirmed that the proposed method can enhance power efficiency and reduce power loss.

关键词： Measurement Renewable energy sources Fluctuations Program processors Power supplies Power control process control Phase control Real-time systems Monitoring

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Consensus algorithms for Opt-in/Opt-out and proximity marketing context

Consensus algorithms for Opt-in/Opt-out and proximity market...

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international conference on computing, Networking and Communications (ICNC)

作者： Fatima Chahal Hacene Fouchal Dominique Gaiti LIST3N University of Technology of Troyes Troyes France CReSTIC Université de Reims Champagne-Ardenne Reims France

Data security is today regarded as one of the most difficult duties that IT professionals must fight for. And today, consumers are more concerned about their data, and they begin to wonder why the rules that attempted to protect their data, particularly in the proximity marketing arena, have failed. Users’ information is shared without their awareness among market participants. Many systems have emerged through regulation to safeguard users and the market, the most well-known of which is Opt-in/Opt-out, which asks users for permission to use and share personal information with a third party. In addition, they have the opportunity to revoke their permission at any moment. In practice, however, this approach is ineffectual because opting out does not prohibit corporations from exploiting the data. In this work, we propose a novel invention that combines Opt-in/Opt-out with consensus algorithms in a decentralized way to provide a more secure environment for the user, giving the user the primary control to grant the company access to his data or a real withdrawal consent at any time.

关键词： Technological innovation Backtracking Data security process control Consensus algorithm Companies Regulation

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