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communication, Computing and Industry 4.0 (C2I4), International Conference on

作者： Kumaresan K Mohanraj K Ruban Thomas Deepa R Madhumita S Nithishkumar K Electronics and Instrumentation Engineering Bannari Amman Institute of Technology Sathyamangalam India Instrumentation and Control Engineering Sri Sairam Engineering college Chennai India Electronics and communication Engineering Vel Tech Multi Tech Engineering College Chennai India Electronics and Communication Engineering CMR Institute of Technology Bangalore India

ISBN: (数字)9781665474979

ISBN: (纸本)9781665474986

In modern industrial automation, one of the most frequent control systems in process industries is cascade control. If, in addition to the main process variable, additional system variables are measured and given back as secondary process variables, generating subordinate control loops, a cascade control system can be constructed. The integrated cascade control system based on Logix 5571 was developed to resolve the problem of nonlinear and more time delays in chemical process. Steam pressure, steam temperature, air/fuel ratio, drum level, and drum flow are all sensitive to variations in working conditions when considering the primary variables of the continuous chemical process. A temperature process is master control and a steam flow process is slave control have become so integrated. This paper used the velocity form algorithm in PID to optimize the values and design a cascade enhanced proportional integral derivative controller (PIDE) to solve the large time delay in chemical processes. The real-time monitoring, a process parameter actual values and configure I\O tag to Human Machine Interface (HMI) using a factory talk automation software. The logix structure of cascade control loops is especially important for obtaining quick dynamics and proper behavior in all real-world operating modes. In the field of industrial control, which uses PLC Modbus TCP/IP to communicate between one master station and more slave stations.

关键词： Temperature sensors Temperature measurement Delay effects Process control TCPIP control systems Chemical processes

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Enhanced Security Through Honeywords and Video CAPTCHA: An Innovative Authentication and Tracking Mechanism

Enhanced Security Through Honeywords and Video CAPTCHA: An I...

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Advances in Electrical, Computing, communication and Sustainable Technologies (ICAECT), International Conference on

作者： Madhuri Gurale Komal Borate Rachana R. Sangitrao Garima Tiwari Information Technology Department D. Y. Patil College of Engineering Akurdi Pune India Artifical Intelligency and Data Science Department D. Y. Patil College of Engineering Akurdi Pune India Department of Instrumentation and Control D. Y. Patil College of Engineering Akurdi Pune India Department of Electronics & Communication D. Y. Patil College of Engineering Akurdi Pune India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

In recent years, activities across countries have increasingly been carried out digitally, with information being shared over networks to boost speed and efficiency. However, this digital transformation poses security threats. Cybercrime has consistently evolved, necessitating improved network security measures to combat digital scams. To maintain security, users are assigned unique identification passwords, which they are instructed to keep secret. Despite this, attackers often manage to steal passwords. To counter these threats, we propose using honeywords, which are decoy passwords created from the existing user password. If an attacker inputs a honeyword, an alert is activated for the administrator. Moreover, we implement IP and location monitoring for users and introduce a approach known as the video click-based CAPTCHA system. This scheme authenticates users by distinguishing between humans and bots, addressing issues in traditional graphic password CAPTCHA schemes. This architecture significantly enhances protection and security of data and applications over online networks.

关键词： Resistance Authentication Passwords Network security Reliability Protection Computer crime Usability Monitoring CAPTCHAs

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3D printed fiber-optic nanomechanical bioprobe

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International Journal of Extreme Manufacturing 2023年第1期5卷 222-234页

作者： Mengqiang Zou Changrui Liao Yanping Chen Lei Xu Shuo Tang Gaixia Xu Ke Ma Jiangtao Zhou Zhihao Cai Bozhe Li Cong Zhao Zhourui Xu Yuanyuan Shen Shen Liu Ying Wang Zongsong Gan Hao Wang Xuming Zhang Sandor Kasas Yiping Wang Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China School of Electronic and Communication Engineering Shenzhen PolytechnicShenzhen 518000People’s Republic of China Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical EngineeringHealth Science CenterShenzhen UniversityShenzhen 518055People’s Republic of China Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China Laboratory of Food and Soft Materials Department of Health Sciences and TechnologyETH Zurich8092 ZurichSwitzerland Wuhan National Laboratory for Optoelectronics(WNLO) Huazhong University of Science and Technology(HUST)Wuhan 430074People’s Republic of China Department of Applied Physics The HongKong Polytechnic UniversityHong KongPeople’s Republic of China Laboratory of Biological Electron Microscopy Ecole Polytechnique Fédérale de Lausanne1015 LausanneSwitzerland UnitéFacultaire d’Anatomie et de Morphologie(UFAM) CUMRLUniversity of Lausanne1005 LausanneSwitzerland

Ultrasensitive nanomechanical instruments,*** force microscopy(AFM),can be used to perform delicate biomechanical measurements and reveal the complex mechanical environment of biological ***,these instruments are limited because of their size and complex feedback *** this study,we demonstrate a miniature fiber optical nanomechanical probe(FONP)that can be used to detect the mechanical properties of single cells and in vivo tissue measurements.A FONP that can operate in air and in liquids was developed by programming a microcantilever probe on the end face of a single-mode fiber using femtosecond laser two-photon polymerization *** realize stiffness matching of the FONP and sample,a strategy of customizing the microcantilever’s spring constant according to the sample was proposed based on structure-correlated *** a proof-of concept,three FONPs with spring constants varying from 0.421 N m^(−1)to 52.6 N m^(−1)by more than two orders of magnitude were *** highest microforce sensitivity was 54.5 nmμN^(−1)and the detection limit was 2.1 *** Young’s modulus of heterogeneous soft materials,such as polydimethylsiloxane,muscle tissue of living mice,onion cells,and MCF-7 cells,were successfully measured,which validating the broad applicability of this *** strategy provides a universal protocol for directly programming fiber-optic ***,this method has no special requirements for the size and shape of living biological samples,which is infeasible when using commercial *** has made substantial progress in realizing basic biological discoveries,which may create new biomedical applications that cannot be realized by current AFMs.

关键词： two-photon polymerization nanolithography optical fiber sensor nanomechanical probe stiffness tunable microcantilever biosensor

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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Design of Planar Ultra-wideband Notch Antenna 19

Design of Planar Ultra-wideband Notch Antenna

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19th International Conference on Optical communications and Networks, ICOCN 2021

作者： Zheng, Xuemei Xu, Xiuming Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China College of Information & Communication Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9781665424462

Ultra-wideband technology determines the development trend of the future society. As the core technology of ultra-wideband technology, ultra-wideband antennas are the most important structure in the radio system. When it is working, it will generate electromagnetic waves in free space and be converted into radio waves. There are many narrow-band frequency bands in the ultra-wideband frequency range (3.1GHz-10.6GHz). Use possible ways to make the antenna filter out other narrow-band interference in the working frequency band to realize the notch function. © 2021 IEEE.

关键词： Ultra-wideband (UWB)

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Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions

arXiv

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arXiv 2024年

作者： Javaid, Shumaila Khalil, Ruhul Amin Saeed, Nasir He, Bin Alouini, Mohamed-Slim The Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China The Department of Electrical and Communication Engineering College of Engineering UAE University Al-Ain15551 United Arab Emirates Division King Abdullah University Of Science And Technology 23955 Saudi Arabia

Integrated satellite, aerial, and terrestrial networks (ISATNs) represent a sophisticated convergence of diverse communication technologies to ensure seamless connectivity across different altitudes and platforms. This paper explores the transformative potential of integrating Large Language Models (LLMs) into ISATNs, leveraging advanced Artificial Intelligence (AI) and Machine Learning (ML) capabilities to enhance these networks. We outline the current architecture of ISATNs and highlight the significant role LLMs can play in optimizing data flow, signal processing, and network management to advance 5G/6G communication technologies through advanced predictive algorithms and real-time decision-making. A comprehensive analysis of ISATN components is conducted, assessing how LLMs can effectively address traditional data transmission and processing bottlenecks. The paper delves into the network management challenges within ISATNs, emphasizing the necessity for sophisticated resource allocation strategies, traffic routing, and security management to ensure seamless connectivity and optimal performance under varying conditions. Furthermore, we examine the technical challenges and limitations associated with integrating LLMs into ISATNs, such as data integration for LLM processing, scalability issues, latency in decision-making processes, and the design of robust, fault-tolerant systems. The study also identifies key future research directions for fully harnessing LLM capabilities in ISATNs, which is crucial for enhancing network reliability, optimizing performance, and achieving a truly interconnected and intelligent global network system. © 2024, CC BY-NC-SA.

关键词： Decision making

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communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity

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IEEE Transactions on Cognitive communications and Networking 2025年

作者： Tian, Zhuojun Zhang, Zhaoyang Li, Yiwei Bennis, Mehdi Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Oulu Center for Wireless Communications Oulu90014 Finland State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multimodal Communication Networks and Intelligent Information Processing Hangzhou310027 China Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China

To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a communication-efficient personalized learning algorithm is developed. In the proposed method, each local model is represented as the ‌Hadamard product of global real-valued parameters and a personalized binary mask for pruning. The local model is learned by updating and fusing the personalized binary masks while the real-valued parameters are fixed among different agents. To further reduce the complexity of hardware implementation, we incorporate a group sparse regularization term in the loss function, enabling the learned local model to achieve structured sparsity. Then, a binary mask aggregation algorithm is designed by introducing an intermediate aggregation tensor and adding a personalized fine-tuning step in each iteration, which constrains model updates towards the local data distribution. The proposed method effectively leverages the relativity among agents while meeting personalized requirements in heterogeneous node conditions. We also provide a theoretical proof for the DSLTH, establishing it as the foundation of the proposed method. Numerical simulations confirm the validity of the DSLTH and demonstrate the effectiveness of the proposed algorithm. © 2015 IEEE.

关键词： Iterative methods

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Solar Radiation Forecasting Based on Random Forest and XGBoost

Solar Radiation Forecasting Based on Random Forest and XGBoo...

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International Conference on Green technology and Sustainable Development (GTSD)

作者： Nhat-Truong Nguyen Thai Cat Tuong Dao Le Nhut Tuyen Nguyen Thanh-Dat Nguyen Minh-Vuong Le Isobel Timothea French Van-Tuong Doan Van Hoang Kim Vo Nghi C. Tran Duc-Hung Pham Van-Trung Nguyen Department of Renewable Energy Ho Chi Minh City University of Technology and Education Vietnam Department of Control Engineering and Automation Ho Chi Minh City Industry and Trade College Vietnam LILAMA2 International Technology College Dongnai Viet Nam Institute of Cognitive Neuroscience National Central University Taiwan College of Information and Communication Technology Can Tho University Viet Nam Faculty Electrical and Electronic Engineering Hung Yen University of Technology and Education VietNam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

Renewable energy offers a viable alternative to depleting fossil fuels, contributing to global warming and greenhouse gas emissions. Thus, solar energy is widely favored as a renewable energy source. However, the output power of solar systems is unstable and is highly dependent on environmental circumstances such as radiation, humidity, temperature, and wind. Therefore, accurately estimating solar radiation is crucial for successful integration of the solar system into existing electrical grid systems. In this study, two different machine learning models, XGBoost and Random Forest, were used to predict solar radiation data in Ho Chi Minh City, Vietnam. The results show that RMSE and MAE of the Random Forest model (61.09 and 24.37) is smaller compared to XGBoost (61.31 and 25.08). Regression value of the two models is close to 0.955. In summary, this paper demonstrates that these two machine learning algorithms effectively forecast solar radiation, with the Random Forest model showing better performance.

关键词： Renewable energy sources Temperature distribution Temperature dependence Urban areas Humidity Predictive models Solar system

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Remotely controllable Data Self-Destruction for Privacy-Preserving Sensitive Data Services

Remotely Controllable Data Self-Destruction for Privacy-Pres...

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IEEE International Conference on High Performance Computing and communications (HPCC)

作者： Chengxin Zhou Xianbin Xue Khaled Riad Yan Zhu William Cheng-Chung Chu School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North Navigation Control Technology Co. Ltd. Beijing China College of Computer Science & Information Technology King Faisal University Saudi Arabia School of Computer & Communication Engineering University of Science and Technology Beijing Beijing China Department of Computer Science Tunghai University Taichung Taiwan

This paper address a comprehensive solution to address data privacy and security challenges in data science, providing secure self-destruction of sensitive data, confidentiality through encryption, and flexible control over message destruction. Based on outsourcing cloud data services, we introduce a cloud retrograde storage (CRS) system for privacy-preserving self-destruction of sensitive data. The CRS is based on a frequently colliding hash table and recycle pool, and supports remote time, count, and range control. Hereby, we provide a remotely controllable mechanism for the prompt destruction of inactive messages against digital forensics without reducing the availability of services. The method used in the CRS involves storing messages in a recycle pool, where they are automatically erased at the end of their validity period or after being viewed by all recipients. The system also incorporates encryption and decryption processes to ensure confidentiality. The result of performance evaluation shows that the CRS effectively handles the destruction of messages and provides secure data removal from storage pools. The experiments demonstrate the efficiency and practicality of the CRS for large-scale data services.

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Radio communication Scenarios in 5G-Railways

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China communications 2023年第9期20卷 235-246页

作者： Ruisi He Bo Ai Zhangdui Zhong Mi Yang Chen Huang Ruifeng Chen Jianwen Ding Hang Mi Zhangfeng Ma Guiqi Sun Changzhu Liu State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China Pervasive Communication Research Center Purple Mountain LaboratoriesNanjing 211111China Institute of Computing Technology China Academy of Railway SciencesBeijing 100081China College of Information Engineering Shaoyang UniversityShaoyang 422000China National Research Center of Railway Safety Assessment Beijing Jiaotong UniversityBeijing 100044China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong UniversityBeijing 100044China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong UniversityBeijing 100044China

With the rapid development of railways,especially high-speed railways,there is an increasingly urgent demand for new wireless communication system for *** the mature 5G technology as an opportunity,5G-railways(5G-R)have been widely regarded as a solution to meet the diversified demands of railway wireless *** the design,deployment and improvement of 5GR networks,radio communication scenario classification plays an important role,affecting channel modeling and system performance *** this paper,a standardized radio communication scenario classification,including 18 scenarios,is proposed for *** paper analyzes the differences of 5G-R scenarios compared with the traditional cellular networks and GSM-railways,according to 5G-R requirements and the unique physical environment and propagation *** proposed standardized scenario classification helps deepen the research of 5G-R and promote the development and application of the existing advanced technologies in railways.

关键词： 5G-R scenario classification smart rail-ways

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