检索结果-内蒙古大学图书馆

A Memristive Spiking Neural Network Circuit for Bio-Inspired Navigation Based on Spatial Cognitive Mechanisms

IEEE Transactions on Biomedical Circuits and Systems 2025年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Hubei Key Laboratory of Brain-Inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation, a high-level and crucial function for organisms' survival in nature, enables autonomous exploration and navigation within the environment. However, most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation, capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application, the entire SNN is quantized and deployed on a real memristive hardware platform, achieving about a 21 × reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Event-triggered adaptive neural network control design for stochastic nonlinear systems with output constraint

引用

International Journal of Adaptive Control and Signal Processing 2024年第1期38卷 342-358页

作者： Shen, Fei Wang, Xinjun Pan, Xinxin School of Electrical and Automation Changshu Institute of Technology Suzhou China College of Information Science and Engineering Shandong Normal University Jinan China College of Computer and Information Hohai University Nanjing China

This paper is concerned with the adaptive neural network event-triggered control (ETC) problem for stochastic nonlinear systems with output constraint. The influence of stochastic disturbance inevitably exists in many practical systems, which leads to system instability. Meanwhile, a novel tan type barrier Lyapunov function (Tan-BLF) structure is proposed to deal with the constraint requirements of stochastic systems. In the sense of probability, the output constraints will not be violated during the operation of the system. In addition, the ETC strategy is adopted to reduce the burden of communication. The asymptotic stability of the closed-loop system is guaranteed without violating output constraints. Meanwhile, the tracking error converges to a small region of the origin. Two simulations results demonstrate the effectiveness of theoretical analysis. © 2023 John Wiley & Sons Ltd.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

SR-Mamba: Data-Driven EV Charging Load-Altering Attack Detection and Localization Using Selective State based Model 6

SR-Mamba: Data-Driven EV Charging Load-Altering Attack Detec...

引用

6th International Conference on Electronic engineering and Informatics, EEI 2024

作者： Li, Yi Hanif, Umara College of Design and Engineering National University of Singapore Department of Electrical and Computer Engineering Singapore Central South University Department of Automation Changsha410083 China

ISBN: (纸本)9798350353594

Driven by the imperative to reduce emissions from transportation, Electric Vehicles (EVs) are proliferating rapidly. However, the widespread adoption of EV charging facilities poses a potential threat to the stability of the grid. Manipulating the demand for charging facilities can disrupt the supply/demand balance of the grid, potentially leading to blackouts. Moreover, current load alternation attack detection relies on static linearized grid modeling, which struggles to accurately represent the dynamic nature of the grid, thus making it difficult to detect such attacks effectively. In this paper, we propose a data-driven model using a State Space Model (Mamba-based structure) to capture temporal correlation among buses. We introduce spectral domain representation to enhance detection and utilize hidden grid representations for identifying load alternative attacks and their location. © 2024 IEEE.

关键词： State of charge

来源：评论

学校读者我要写书评

暂无评论

Automating CPPSs Analyses with SysML v2 and Lingua Franca in the Context of Industry 4.0 50

Automating CPPSs Analyses with SysML v2 and Lingua Franca in...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Gaiardelli, Sebastiano Wilch, Jan Fummi, Franco Vogel-Heuser, Birgit Industrial Computer Engineering Laboratory Department of Engineering for Innovation Medicine University of Verona Italy Institute of Automation and Information Systems Technical University of Munich Germany

ISBN: (纸本)9781665464543

The design of manufacturing systems requires exploring diverse component configurations for one that best satisfies the requirements of the target system. At the same time, manufacturing systems evolve continuously, increasing their complexity and that of the production line in which they are installed. Model-based System engineering (MBSE) methodologies and modeling languages like System Modeling Language (SysML) are used to assist system engineers during the entire design process. Yet, MBSE methodologies mainly rely on manually composed models for requirements verification, incurring enormous cost and effort especially in larger, more complex systems. This paper proposes a methodology exploiting the knowledge enclosed in a SysML model to automate the execution of a set of analyses defined over the represented manufacturing system. The proposed approach relies on Lingua Franca (LF) to simulate the specified analysis and analyze the results. Moreover, the methodology supports chains of analyses to represent dependent requirements and tradeoffs imposed upon a manufacturing system. The proposed methodology has been evaluated on a manufacturing system demonstrator. Results show the proposed methodology’s applicability and scalability on diverse configurations of the manufacturing system. © 2024 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Addressing Privacy and Security Challenges at the Industry 5.0 Human-Intensive and Highly Automated Factory Floor 50

Addressing Privacy and Security Challenges at the Industry 5...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Kolesnikov, Mikhail Lossi, Leonardo Alberti, Enrico Atmojo, Udayanto Dwi Vyatkin, Valeriy Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Computer and Space Engineering Luleå Tekniska Universitet Sweden Nextworks s.r.l Pisa Italy

ISBN: (纸本)9781665464543

With Industry 5.0, prioritizing worker well-being, the integration of human-related data into production processes poses challenges related to data privacy and compliance with regulations such as GDPR. This paper presents a comprehensive approach to anonymizing sensitive data collected from wearable devices. We propose a methodology that combines real-time processing and complex anonymization algorithms, ensuring end-to-end protection. We employ techniques such as normalization, hashing, and feature dropping. Our findings contribute to advancing privacy-preserving techniques in Industry 5.0 and underscore the importance of safeguarding user privacy in the era of advanced manufacturing. © 2024 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

引用

computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： Muhammad Dawood Shanshan Tu Chuangbai Xiao Muhammad Haris Hisham Alasmary Muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

来源：评论

学校读者我要写书评

暂无评论

Access Control Method for EV Charging Stations Based on State Aggregation and Q-Learning

引用

Journal of Systems Science & Complexity 2022年第6期35卷 2145-2165页

作者： TANG Ziyu LUO Yonglong FANG Daohong ZHAO Chuanxin School of Computer and Information Anhui Normal UniversityWuhu 241002China Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China

This paper presents intelligent access control for a charging station and a framework for dynamically and adaptively managing charging requests from randomly arriving electric vehicles(EVs),to increase the revenue of the ***,charging service requests from random EV arrivals are described as an event-driven sequential decision process,and the decision-making relies on an eventextended state that is composed of the real-time electricity price,real-time charging station state,and EV arrival ***,a state aggregation method is introduced to reduce the state space by first aggregating the charging station state in the form of the remaining charging time and then further aggregating it via sort ***,mathematical calculations of the code value are provided,and their uniqueness and continuous integer characteristics are ***,a corresponding Q-learning method is proposed to derive an optimal or suboptimal access control *** results of a case study demonstrate that the proposed learning optimisation method based on the event-extended state aggregation performs better than flat *** space complexity and time complexity are significantly reduced,which substantially improves the learning efficiency and optimisation performance.

关键词： Access control aggregation EV charging station event-extended state Q-learning

来源：评论

学校读者我要写书评

暂无评论

GRU combined model based on multi-objective optimization for short-term residential load forecasting

引用

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

来源：评论

学校读者我要写书评

暂无评论

HKB-YOLO: transmission line fire detection method based on hierarchical feature fusion

引用

International Journal of Security and Networks 2024年第4期19卷 188-198页

作者： Ying, Zhilei Meng, Yanan Chen, Ruoxi Lou, Jianlou School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin 132022 China Department of Automation Jilin Institute of Chemical Technology Jilin 132022 China School of Computer Engineering Northeast Electric Power University Jilin 132012 China

Timely transmission line fire inspections are vital for power system safety. Although deep learning models are widely used for flame detection, struggle with small target recognition due to background interference and are vulnerable to input data perturbations, posing security risks. This study introduces a hierarchical feature fusion method based on the you only look once Version 8 (YOLOV8) framework. It employs high-performance GPU network version 2 (HGNetV2) to enhance small-target feature extraction while reducing computational complexity. A spatial pyramid pooling-fast module with large separable kernel attention is designed to highlight key features and suppress background noise. The proposed bidirectional slim neck structure (BiSlimneck) reduces feature loss. Adversarial training enhances the model’s robustness. Experimental results show a 1.4% accuracy improvement, with a reduction in parameters and complexity by 18.3% and 21.6%, respectively. After adversarial training, the accuracy of the network in the face of attacks increased by 10% compared to the pre-training. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Premixed flames

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：