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International Conference on Power Electronics and Motion control (IPEMC)

作者： Liang Wang Yu-heng Yan Xiao-yang He Wei-chun Ge Chuang Liu Yu-tong Liu Power dispatching control center State Grid Liaoning Electric Power Co. Ltd. Shenyang China School of Electrical Engineering Northeast Electric Power University Jilin China Ministry of science and technology communication State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (数字)9781728153018

ISBN: (纸本)9781728153025

In order to provide the system with the inertia support through wind turbine rotor kinetic energy when the power of the power system fluctuates, the virtual synchronous generator (VSG) control strategy is adopted to the grid-connected inverter of the permanent magnet synchronous generator (PMSG), which can actively adjust the imbalance power caused by the system fluctuations, and provide the system with inertia support at the initial stage of system disturbance. And meanwhile a new parallel control method is proposed for wind turbines in this paper. The master-slave control strategy is adopted by the wind turbine machine-side converter, which can realize the collection and transmission of DC power, and reduce the number of inverters, save economic costs and avoid many problems caused by the connection of AC power. Finally, the performance and effectiveness of the proposed method are validated by the simulation results.

关键词： Simulation Rotors Master-slave Synchronous generators Inverters Wind turbines Voltage control

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Enhanced maturation and heavy metal stabilization by humic substance addition during dredged sediments composting

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Journal of Environmental Chemical engineering 2025年第4期13卷

作者： Chuxuan Song Shiquan Sun Bo Xia Qingwei Zhang Lijuan Liu Yoshiyuki Hidawa Tianxiang Li Lean Zhou Yang Gao Suiqin Yang Wei Zhang School of Hydraulic and Ocean Engineering Changsha University of Science & Technology Changsha 410114 China Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province Changsha 410114 China Wuhan Municipal Construction Group Co. Ltd. Wuhan 430023 China Environmental Business Communication Association 953-1-416 Wanagaya Matsudo City Chiba Prefecture 2702232 Japan Nihon Sofuken Co Ltd. 1-10-15-204 Takadanobaba Shinjuku-ku Tokyo 169-0075 Japan

Composting is a promising approach for the resource utilization of dredged sediments, but maturity and heavy metals (HMs) remain key challenges. This study investigates the effects of humic acid (HA) and fulvic acid (FA) as additives on the humification process and HMs stabilization during composting. Results showed that HA and FA extended the thermophilic phase by 1–3 days. Compared to the control group, HA and FA increased the total nitrogen content in the final product by 12.7 %-21.4 %. Both HA and FA promoted the transformation of HMs into more stable forms, with the residual cobalt fraction increasing by 9.2 % (HA) and 10.3 % (FA), thus stabilizing the HMs. The addition of HA and FA accelerated the humification process, as evidenced by the increased formation of aromatic carbon in dissolved organic matter, resulting in an increase in the humic acid-like material content by 6.5 % and 15.3 %, respectively. The optimization of microbial diversity and community structure was one of the key factors driving the accelerated humification and HMs passivation. The Ace index in the experimental groups increased by 9.8 % (HA) and 22.0 % (FA). During the thermophilic phase, HA and FA inhibited harmful microorganisms and promoted the growth of beneficial bacteria such as Bacillus and Pseudomonas . Canonical correspondence analysis revealed that the addition of HA and FA increased pH and electrical conductivity (EC), which in turn enhanced the abundance of HMs-passivating bacteria. These results underscore the potential of FA as an effective additive for dredged sediment composting, enhancing compost quality and mitigating environmental risks linked to HMs contamination.

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Preface

EAI/Springer Innovations in Communication and Computing

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EAI/Springer Innovations in communication and Computing 2021年 vii-viii页

作者： Srivastava, Smriti Khari, Manju Crespo, Ruben Gonzalez Chaudhary, Gopal Arora, Parul Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi Delhi India Department of Computer Science and Technology Universidad Internacional de La Rioja Logroño La Rioja Spain Department of Electronics and Communication Engineering Jaypee Institute of Information Technology Noida India School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi Delhi India Department of Electronics and Communication Engineering Bharati Vidyapeeth’s College of Engineering New Delhi Delhi India

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Unconstrained Face Verification Based on Monogenic Binary Pattern and Convolutional Neural Network

Unconstrained Face Verification Based on Monogenic Binary Pa...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Bilel Ameur Mebarka Belahcene Sabeur Masmoudi Ahmed Ben Hamida ATMS Advanced Technologies for Medecine and Signals National Engineering School of Sfax (ENIS) Sfax University Soukra street Km 3.5 B.P. 1173 Sfax Tunisia LI3C Laboratory of Identification Command Control and Communication Faculty of Science and Technology Mohamed Khider University Biskra BP 145 RP Biskra Algeria

ISBN: (数字)9781728175133

ISBN: (纸本)9781728175140

Unconstrained Face Verification is still an important problem worth researching. The major challenges such as illumination, pose, occlusion and expression can produce more complex variations in both shape and texture of the face. In this paper, we propose a method based on Monogenic Binary Pattern and Convolutional Neural Network (MBP-CNN) to improve the performance of face recognition system. For each facial image, the proposed method firstly extracts local features using Monogenic Binary Pattern (MBP) which is an excellent and powerful local descriptor compared to the well-recognized Gabor filtering-based LBP models. Then, we use Convolutional Neural Networks which is one of the best representative network architectures of deep learning in the literature, in order to extract more deep features. Thus, the developed MBP-CNN has robustness to variations of illumination, occlusion, pose, expression, texture and shape by combining Monogenic Binary Pattern and convolutional neural network. Moreover, MBP-CNN was more accurately represented by combining global and local information of facial images. Experiments demonstrate that our method provided competitive performance on the LFW database, compared to the others described in the state-of-the-art.

关键词： Face recognition Feature extraction Convolution Convolutional neural networks Lighting Deep learning Databases

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Sensing Matrix Design for MMV Compressive Sensing: An MVDR Approach

Sensing Matrix Design for MMV Compressive Sensing: An MVDR A...

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作者： Zhang, Liang Huang, Lei Li, Bo Yin, Jingwei Bao, Weimin School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Nuance Communication Inc. MontrealQCH3A 3S7 Canada Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology Harbin150001 China Science and Technology Council China Aerospace Science and Technology Cooperation Beijing100048 China College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China

Compressive sensing (CS) has been widely used in vehicular technology including compressive spectrum sensing, sparse channel estimation, and vehicular communications. The complete procedure of CS consists of sparse representation, sparse measurement, and sparse recovery. In the CS, measurement matrix Φ is utilized to sample a sparse signal, while sensing matrix Ψ is exploited for sparse recovery. It is important to properly design the sensing matrix that significantly affects the signal recovery performance. This paper addresses the issue of the sensing matrix design for the CS with multiple measurement vectors (MMV). We first study sufficient conditions for the MMV-CS and then develop three sensing matrix design approaches in different situations. The proposed methods have their roots in the principle of minimum variance distortionless response (MVDR) beamformer. This allows us to optimally determine the sensing matrix in the framework of the MVDR, which amounts to minimizing local cumulative cross-coherence between Φ and Ψ while keeping the columns of Ψ highly correlated to their counterparts of Φ. Simulation results are presented to verify the effectiveness of the proposed methods. © 1967-2012 IEEE.

关键词： Compressed sensing

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Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

arXiv

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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well. © 2021, CC BY-NC-ND.

关键词： Machine learning

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Research on Deep Reinforcement Learning Exploration Strategy in Wargame Deduction

Research on Deep Reinforcement Learning Exploration Strategy...

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International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Tongfei Shang Haoyang Dong Jing Liu Yuan Yu College of information and communication national university of defense technology Xi’an China School of electronic and information engineering Xi’an Jiaotong University Xi’an China College of command and control engineering Army engineering university of PLA Nanjing China Xi’an satellite control center Xi’an China

ISBN: (数字)9781728130668

ISBN: (纸本)9781728130675

The wargame deduction is the application of wargame. It refers to the use of boards and wargame pieces representing the battlefield and its military power, or based on the virtual battlefield environment and force of the computer, based on military rules and probability theory, simulating war confrontation. The process deduction and evaluation optimization of the combat plan is an activity that uses wargame to simulate war and is a tool for combat simulation. In this paper, the actual or assumed situation is used to simulate the military actions of two or more opposing parties. The deep reinforcement learning and exploration strategy is used to improve the realistic function of the wargame simulation and the deductive pushability function, and systematically study the wargame technology. Advancing operational decision-making and military training has certain practical and strategic significance.

关键词： Machine learning Learning (artificial intelligence) Decision making Military computing Optimization Training Conferences

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Research on Evaluation Method of Wargame Strategy Based on Fuzzy Petri Net

Research on Evaluation Method of Wargame Strategy Based on F...

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International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Tongfei Shang Haoyang Dong Kun Han Gang Li College of information and communication national university of defense technology Xi’an China School of electronic and information engineering Xi’an Jiaotong University Xi’an China College of command and control engineering Army engineering university of PLA Nanjing China Xi’an satellite control center Xi’an China

ISBN: (数字)9781728130668

ISBN: (纸本)9781728130675

Wargame can effectively improve the fidelity and efficiency of combat deduction, and has the ability to solve complex military problems. It is theoretical and military significance to carry out the research on the development and application of computer wargame system. In this paper, the method of knowledge representation and reasoning of fuzzy Petri nets is applied to the strategy of wargame deduction. The characteristics of the graphs are used to represent different variables with different symbols, which can form a concise PN map. This PN map can be used for the force representation and reasoning strategy in the wargame system. The results show that the Petri net-based knowledge representation and reasoning algorithm is very effective for the wargame strategy.

关键词： Petri nets Cognition Force Mathematical model Information systems Knowledge representation Correlation

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Android Application and SMS Alert Based Garbage Monitoring and Navigation System

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Journal of Physics: Conference Series 2021年第6期1964卷

作者： K Umapathy T Mangayarkarasi D Subitha A Sivagami Department of Electronics and Communication Engineering Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University (Deemed University) Kanchipuram Tamil Nadu India Department of Instrumentation and Control Engineering Sri Sairam Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Chennai Tamil Nadu India

The treatment of waste is unsafe in city centres where residents are more involved, leading to germs that can lead to disease. How commonly these litter containers are used in different regions is different. Regular timing checks are not helpful. Often, they will overflow much faster than expected. In this article, a smart waste monitoring method is advised to prevent this and increase cleaning, to figure out where the waste is *** architecture of the method collects and transmits information through a wireless network. Under this technique, the dustbin's waste level is measured by sensors and information is transmitted through the GSM and GPS module to the official mobile station. Wi-Fi Module is used to track waste levels online at the control room. Arduino Processor uses network modules to link sensor systems.

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Core-shell [email protected] 2 O-graphene-polydopamine interdigitated microelectrode array sensor for in situ determination of salicylic acid in cucumber leaves

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Sensors and Actuators B: Chemical 2021年 341卷

作者： Dandan Liu Mingji Li Hongji Li Cuiping Li Guilian Wang Penghai Li Baohe Yang Tianjin Key Laboratory of Film Electronic and Communication Devices Engineering Research Center of Optoelectronic Devices & Communication Technology (Ministry of Education) School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin 300384 PR China Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion Tianjin Key Laboratory of Drug Targeting and Bioimaging School of Chemistry and Chemical Engineering Tianjin University of Technology Tianjin 300384 PR China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin 300384 PR China

The in situ detection of active small molecules in plants is one of the key technologies for the development of precision agriculture. An interdigitated microelectrode (IDME) array electrochemical sensor is constructed herein, with three groups of IDME arrays as a three-electrode system. The core-shell [email protected] 2 O-graphene (Gr)-polydopamine (PDA) nanoparticles are densely packed on Al microelectrodes using a three-potential step pulse electrodeposition method. Each of the over 2000 individual microelectrodes is approximately 1 μm wide and 1100 μm in length. The sensor has a high response to salicylic acid (SA) due to the synergistic electrocatalysis of [email protected] 2 O, Gr, and PDA, and the high-density arrangement of the three-electrode unit with microelectrodes. The sensor has a linear concentration range of 0.01–100 μM for SA and the detection limit is as low as 1.16 nM. The SA concentration in cucumber leaves is monitored from the early growth stage to the fruiting stage using the IDME array sensor, and the juice and living stems of the cucumber are detected. The flat structure of the [email protected] 2 O-Gr-PDA IDME array sensor is suitable for attachment onto plant tissues, especially for the in situ detection of SA in leaves.

关键词： Core-shell [email protected] 2 O-graphene-polydopamine Interdigitated microelectrode array Sensor Salicylic acid Plant

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