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43rd Chinese control Conference, CCC 2024

作者： Yang, Xinxin Ni, Yuqing Chen, Xiaomeng Chen, Shan Liu, Fei Jiangnan University The Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Wuxi214122 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9789887581581

This study investigates the optimal allocation problem of attack energy in multi-system remote state estimation for Cyber-Physical Systems (CPSs). We consider a scenario where there are M independent systems, each equipped with a remote sensor monitoring system. The local estimates from these systems are sent to a remote estimator through a packet loss channel. The objective of the attacker is to degrade the communication channel between the sensors and the remote estimator. Due to capacity limitations, the attacker is restricted to attacking at most one out of M channels. We incorporate interference from other sensors or interference sources into the communication model based on the SINR (Signal-to-Interference-plus-Noise Ratio) model. It should be noted that the same attack power can lead to different packet loss rates in different network environments. From the attacker's perspective, the goal is to find the optimal attack strategy that maximizes the average estimation error of the remote estimator. Given the uncertainties of wireless network environments, we employ the sequentially-observed Markov decision process (SOMDP) framework to solve the problem. By observing the wireless channels, we gather additional information and incorporate it into the decision-making policy, resulting in better performance than using a standard Markov decision process (MDP). The simulation results support our theoretical findings. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Markov processes

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Design Considerations for Implementing a Home Energy Management System 4

Design Considerations for Implementing a Home Energy Managem...

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4th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2021

作者： Muusha, Trust-More Mathaba, Tebello N.D. Vaal University of Technology Department of Process Control and Computer Systems Vanderbijlpark South Africa

ISBN: (纸本)9781728185927

Home Energy Management Systems (HEMS) equip users with additional control over their energy consumption, allowing them to schedule economically how their appliances may be used. The essence of HEMS is to provide energy and cost saving while avoiding user inconvenience. A significantly high number of the proposed HEMS solutions in literature are focused mainly on developing algorithms for appliance scheduling while putting less emphasis on the selection of the appropriate technologies and modelling techniques. Moreover, the current rise of the internet-of-Things (IoT) and low-cost microcontroller hardware present further opportunities for development of better HEMS. This work contributes to the study of HEMS in three ways. Firstly, it proposes an IoT-based HEMS framework. Secondly, it provides a brief comparison suitable for low-cost computing hardware. Lastly, it presents design considerations necessary for implementing HEMS. The analysis shows that the considerations must review available Demand-side management programmes, communication technologies and energy driving variables. © 2021 IEEE.

关键词： Energy efficiency

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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Improving the activity of electrochemical reduction of CO_(2) to C_(1) products by oxidation derived copper catalyst

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Materials Reports(Energy) 2023年第1期3卷 107-114,I0004页

作者： Lingxue Diao Yingda Liu Feifei Chen Hong Pan David Perez de Lara Hui Liu Yahui Cheng Feng Luo Department of Electronic Science and Engineering and Tianjin Key Laboratory of Process Control and Green Technology for Pharmaceutical Industry Nankai UniversityTianjin300350China Department of Basic Science Tianjin Agricultural UniversityTianjin300392China IMDEA Nanosci Faraday 9Ciudad Univ CantoblancoMadrid28049Spain Tianjin Key Lab for Rare Earth Materials and Applications Center for Rare Earth and Inorganic Functional MaterialsSchool of Materials Science and EngineeringNankai UniversityTianjin300350China

Cu-based electrocatalysts have become the focus in the field of electrochemical CO_(2) reduction reaction(ECO_(2) RR)due to their ability to produce multicarbon ***,the research on generating single carbon products with higher economic feasibility via ECO_(2) RR based on Cu-based electrocatalysts is rather rare,and the roles of the surface architecture and oxides of the electrocatalysts have not been explained *** this work,a two-step method including thermal oxidation and electroreduction is proposed to introduce Cuþinto pure Cu foil to form Cu_(2)O/Cu *** regulating the surface composition and morphology of the electrocatalyst in this way,the activity of ECO 2 RR to C_(1) products has been greatly *** Faradaic efficiency of carbon products of the Cu_(2)O/Cu electrode reaches 84%at?0.7 V *** with good selectivity for HCOOH and *** current density of Cu_(2)O/Cu electrode reaches-12.21 mA cm^(2) at-0.8 V ***,which is much higher than that of the Cu foil electrode(?0.09 mA cm?2).In-situ Raman characterization shows that Cuþin Cu_(2)O/Cu electrode could inhibit hydrogen generation and promote ECO_(2) RR by stabilizing the adsorption of CO_(2).

关键词： Cu-based electrocatalyst Electroreduction of CO_(2) In-situ Raman spectra C_(1)product

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Enhancing 6G-Satellite Network Integration with Artificial Intelligence: A Future Communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

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22nd International Learning and Technology Conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial Intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 IEEE.

关键词： Satellite communication systems

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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Oral Cancer Classification Using a Hybrid Attention-Aided Deep Learning Model 5th

Oral Cancer Classification Using a Hybrid Attention-Aided D...

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5th International Conference on Medical Imaging and computer Aided Diagnosis, MICAD 2024

作者： Dutta, Srinjan Roy, Jibesh Mandal, Diptarka Kaplun, Dmitrii Shpakovskaya, Irina Sarkar, Ram Department of Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri India School of Computer Engineering and Mathematical Sciences Defence Institute of Advanced Technology Pune India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Process Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India I.P. Pavlov Saint Petersburg First State Medical University St. Petersburg Russia

ISBN: (纸本)9789819638628

Oral cancer remains a critical global health challenge, characterized by high morbidity and mortality due to late-stage diagnosis. This paper addresses the need for improved diagnostic accuracy by introducing a novel hybrid-attention aided deep learning model for oral cancer classification. Our approach integrates the EfficientNetB0 model for feature extraction with a customized hybrid attention module, combining self, spatial, and soft attention mechanisms to emphasize crucial features. The model has been trained and evaluated on both microscopic and macroscopic oral cancer datasets, demonstrating its generalizability. Our proposed model achieves an accuracy of 96.97% on a macroscopic dataset and 92% on a microscopic dataset, with respective F1-scores of 0.97 and 0.89, outperforming baseline models. This hybrid attention-aided deep learning model shows significant potential in improving early detection and treatment planning of oral cancer. Source code and additional results of this work can be found at the GitHub repository. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Multi-Agent control:A Graph-Theoretic Perspective

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Journal of Systems Science & Complexity 2021年第5期34卷 1973-2002页

作者： CHEN Fei REN Wei State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110004China School of Control Engineering Northeastern University at QinhuangdaoQinhuangdao 066004China. Department of Electrical and Computer Engineering University of CaliforniaRiversideCA 92521USA

Progress in development of multi-agent control is *** approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic *** is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph *** emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development *** are over 200 references listed,mostly to recent contributions.

关键词： Consensus cooperative control distributed average tracking distributed optimization multi-agent system

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GLEm-Net: Unified Framework for Data Reduction with Categorical and Numerical Features

GLEm-Net: Unified Framework for Data Reduction with Categori...

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IEEE International Conference on Big Data

作者： Francesco De Santis Danilo Giordano Marco Mellia Alessia Damilano Department of Control and Computer Engineering Politenico di Torino Torino Italy Quality & Process Digitalization Deparment Electronic Division Bitron Grugliasco Italy

In the era of Big Data, effective data reduction through feature selection is of paramount importance for machine learning. This paper presents GLEm-Net (Grouped Lasso with Embeddings Network), a novel neural framework that seamlessly processes both categorical and numerical features to reduce the dimensionality of data while retaining as much information as possible. By integrating embedding layers, GLEm-Net effectively manages categorical features with high cardinality and compresses their information in a less dimensional space. By using a grouped Lasso penalty function in its architecture, GLEm-Net simultaneously processes categorical and numerical data, efficiently reducing high-dimensional data while preserving the essential information. We test GLEm-Net with a real-world application in an industrial environment where 6 million records exist and each is described by a mixture of 19 numerical and 7 categorical features with a strong class imbalance. A comparative analysis using state-of-the-art methods shows that despite the difficulty of building a high-performance model, GLEm-Net outperforms the other methods in both feature selection and classification, with a better balance in the selection of both numerical and categorical features.

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Use of Elements and Algorithms of Intelligent Support in the Automation of Technologies for control and Quality Management of Bulk Materials

Use of Elements and Algorithms of Intelligent Support in the...

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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Kalandarov, Palvan I. Ubaydulayeva, Shakhnoza R. Gaziyeva, Rano T. Nikolov, Nikola N. Alexsandrova, Mariela I. National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Department Automation and Control of Technology Process in Production Tashkent Uzbekistan Technical University of Varna Faculty of Computer Science and Automation Department of Automation Varna9010 Bulgaria

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

The article deals with the choice of criteria for efficiency, applicability in measuring technology, analytical and construction, on the basis of which a methodology for assessing the quality of structures of measuring devices of moisture of materials of the agro-industrial complex is proposed. The standard deviation of the random error characterizing the accuracy of measurements is shown. A complex efficiency criterion is discussed, including the dominant particular parameters: accuracy, reliability, cost, allowing to solve the problem of optimal design of humidity control devices for the materials under consideration. As an optimal option, a differential measuring device is analyzed, which practically eliminates random and systematic errors and makes it possible to design a multiparameter measurement method that considers the features of a heterogeneous environment, such as bulk grain materials of the agro-industrial complex © 2022 IEEE.

关键词： Random errors

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