检索结果-内蒙古大学图书馆

19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

Attention-based Vision Knowledge Adaptation for Constrained Continual Learning

Attention-based Vision Knowledge Adaptation for Constrained ...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Bicheng Guo Conghao Zhou Haoyu Liu Shibo He Jiming Chen Xuemin Sherman Shen College of Control Science and Engineering Zhejiang University China Department of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The demand for continual machine learning in the context of limited computational resources and data availability is critical in the evolving landscape of the connected digital world. Current network applications predominantly rely on deep learning models that require labor/computation-intensive training processes. These models often struggle to effectively adapt to new data while preserving performance on previously acquired knowledge. In this paper, we introduce a lightweight framework for continual knowledge adaptation and learning designed to address these challenges. To prevent disruption of existing services, we propose an attention-based adapter that integrates seamlessly with the existing vision model to encode new incoming data. The weights of the original model are kept fixed during the adaptation process, ensuring the preservation of previously learned knowledge. Furthermore, to enhance learning efficiency and accelerate convergence with new data, we implement a knowledge fusion mechanism that facilitates interaction between existing knowledge and information from new data. Our framework is modular, enabling flexible deployment across distributed devices. The adapter and knowledge fusion module are implemented at each stage with minimal trainable parameters, optimizing resource usage. Extensive experiments and ablation studies validate the effectiveness of the proposed framework.

关键词： Continuing education Training Deep learning Adaptation models Multi-access edge computing Computational modeling Data models Global communication Convergence

来源：评论

学校读者我要写书评

暂无评论

A Case of Cups and a Ball: Utilizing Generative Artificial Intelligence for Human-robotic Collaboration in Task Execution

A Case of Cups and a Ball: Utilizing Generative Artificial I...

引用

2024 International Automatic control Conference, CACS 2024

作者： Khoirurizka, Nurdin Prajogo, Joy Chrissetyo Perkins, Spencer Kuo, Chao-Hsiang Lin, Hsien-I National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu Taiwan

ISBN: (纸本)9798350354904

Within the domain of robotics, effective interaction between a human collaborator and robot is a topic of great importance. With the continued advancements in Generative Artificial Intelligence (GAI), we propose a prototype system that utilizes GAI and seeks to bridge the gap between the human and robot. This prototype utilizes a Large Language Model (LLM) combined with a vision system for detection and tracking, to allow the GAI system to control a robotic arm and manipulate objects within the action space. We model the action space within our experiments on the 3-cup Monte game where the user can prompt the system to manipulate the cups within the action space based on the ball's location. Experimentation is done on prompts of varying lengths of sequences, and we evaluate our system based on its ability to understand the prompt and correctly execute the desired task. With this collaboration of techniques and technologies, we hope to open the possibilities and extend human and robotic collaboration into new areas. The results of our experiments show promising results to this end. © 2024 IEEE.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

A Review of Security and Information control in Blockchain-Integrated IoT Applications

A Review of Security and Information Control in Blockchain-I...

引用

Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Abhijeet Cholke V.V.Mandhare P.S.Vikhe Department of Computer Engineering Matoshri College of Engineering & Research Centre Nashik India Department of Computer Engineering Pravara Rural Engineering College Loni Ahmednagar India Department of Instrumentation and Control Engineering Pravara Rural Engineering College Loni Ahmednagar India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

The convergence of the Internet of Things (IoT) and blockchain technologies has gained substantial traction in recent years, owing to the rapid advancement of communication technologies worldwide. This research introduces a prototype model that seamlessly integrates an IoT platform with blockchain technology to ensure the integrity of data. The prototype establishes a decentralized framework for IoT devices, underpinned by a private blockchain infrastructure capable of replicating device data and validating transactions among devices through a consensus mechanism. Nevertheless, the implementation of this concept necessitates a closer examination of various considerations. One crucial aspect to address is transforming data generated by diverse IoT devices into a format compatible with the blockchain. This research takes a proactive approach to effective data management within the blockchain. Initially, we collect data from IoT devices and systematically store it in a blockchain-compatible manner. The custom blockchain and smart contract components define the data access policies for end-users. Within this model, we categorize IoT appliances responsible for different services into distinct sets of chains. These sets of chains collaboratively exchange data while adhering to a comprehensive access control *** research endeavors to harmonize IoT and blockchain technologies through a prototype that safeguards data integrity. It tackles the challenge of data conversion from various IoT devices into a blockchain-compatible format and outlines a sophisticated data management strategy. By delineating access policies and segmenting IoT appliances into specialized sets of chains, this model aims to facilitate secure and efficient data sharing among decentralized IoT devices.

关键词： Access control Reviews Scalability Smart contracts Prototypes Data models Blockchains Internet of Things Secure storage Resilience

来源：评论

学校读者我要写书评

暂无评论

Prioritization Method of Test Data for Intelligent Software based on Multi-objective Optimization 9

Prioritization Method of Test Data for Intelligent Software ...

引用

9th International Conference on Dependable Systems and Their Applications, DSA 2022

作者： Xia, Chunyan Huang, Yifan Huang, Song Zheng, Changyou Wang, Yutong Wang, Yu College of Command and Control Engineering Army Engineering University of Pla China College of Computer and Information Technology Mudanjiang Normal University China Illinois Institute of Technology United States

ISBN: (数字)9781665488778

ISBN: (纸本)9781665488778

With the rapid development of the information industry, intelligent software testing has become one of the hot research. This paper studies how to extract useful data from the original test set to test the modified model for the intelligent software. First, the initial test data are obtained according to the label classification of the original structured documents. Second, the non-dominated sorting genetic algorithm is used to prioritize the test data. Finally, the experimental results of intelligent software show that compared with the random method, the accuracy of the penalty_money prediction model is reduced by 0.04% 34.91 %, and the accuracy of the penalty_imprisonment prediction model is reduced by 0.08% 32.63 %, indicating that the proposed method can find more defects of the penalty prediction model earlier, to reduce the cost of intelligent software testing. © 2022 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Clustering-Based State Grouping Reinforcement Learning for Switching Decision of Autonomous Vehicles

Hierarchical Clustering-Based State Grouping Reinforcement L...

引用

2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Ouyang, Wenjie Jiao, Yiwen Liu, Yang Li, Yang Hu, Manjiang Qin, Hongmao College of Mechanical and Vehicle Engineering Hunan University Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China College of Electrical Mechanical and Computer Science Delft University of Technology Delft Netherlands College of Mechanical and Vehicle Engineering Hunan University State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Changsha China Institute of Hunan University Wuxi Intelligent Control Research Wuxi China

ISBN: (纸本)9798350316308

Reinforcement learning (RL) has gained wide attention, but its implementation in autonomous vehicles is still limited by insufficient sample efficiency and heavy training costs. The training efficiency of RL agents is influenced by the dimension of the state space, which can be partitioned to reduce the complexity of sampling and computation. This study proposes a hierarchical clustering-based state grouping reinforcement learning (HCSG-RL) method for the switching decision of autonomous vehicles. First, we partition the base state space into groups and generate a hierarchical tree of state space groups. Then, we train multiple sub-agents for each node in the hierarchical tree. Finally, we add these trained-well sub-model into master policy. This method allows us to fully explore all state spaces and improve the training efficiency of individual agents, which handles the 'long-tail' issue and the curse of dimensionality issue. We conduct experiments in a simulation environment and results show that the proposed method has 16-72% reward improvement compared to the tree model in different road length. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

On the chronological understanding of the homogeneous dielectric barrier discharge

引用

High Voltage 2023年第6期8卷 1132-1150页

作者： Xinpei Lu Zhi Fang Dong Dai Tao Shao Feng Liu Cheng Zhang Dawei Liu Lanlan Nie Chunqi Jiang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhanChina College of Electrical Engineering and Control Science Nanjing Tech TechnologyNanjingChina School of Electric Power South China University of TechnologyGuangzhouChina Institute of Electrical Engineering Chinese Academy of SciencesBeijingChina Frank Reidy Research Center for Bioelectrics Old Dominion UniversityNorfolkVirginiaUSA Department of Electrical and Computer Engineering Old Dominion UniversityNorfolkVirginiaUSA

Dielectric barrier discharges(DBD)are widely utilised non‐equilibrium atmospheric pressure plasmas with a diverse range of applications,such as material processing,surface treatment,light sources,pollution control,and *** the course of several decades,extensive research has been dedicated to the generation of homogeneous DBD(H‐DBD),focussing on understanding the transition from H‐DBD to filamentary DBD and exploring strategies to create and sustain H‐*** paper first discusses the in-fluence of various parameters on DBD,including gas flow,dielectric material,surface conductivity,and mesh ***,a chronological literature review is presented,highlighting the development of H‐DBD and the associated understanding of its un-derlying *** encompasses the generation of H‐DBD in helium,nitrogen,and ***,the paper provides a brief overview of multiple‐current‐pulse(MCP)behaviours in H‐*** objective of this article is to provide a chronological un-derstanding of homogeneous dielectric barrier discharge(DBD).This understanding will aid in the design of new experiments aimed at better comprehending the mechanisms behind H‐DBD generation and ultimately assist in achieving large‐volume H‐DBD in an air environment.

关键词： dielectric barrier pollution

来源：评论

学校读者我要写书评

暂无评论

PDDM: IP image design via diffusion model 4

PDDM: IP image design via diffusion model

引用

4th IEEE International Conference on Data Science and computer Application, ICDSCA 2024

作者： Yao, Mingbo Wang, Haiyi Yang, Shuxiang School of Mathematics and Statistics Shandong University of Technology Zibo China College of Computer and Control Engineering Northeast Forestry University Harbin China Faculty of Computational Mathematics and Cybernetics Shenzhen MSU- BIT University Shenzhen China

ISBN: (纸本)9798350368239

Traditional methods and models, while capable of generating high-quality images, often require substantial human resources and time, limiting their feasibility for large-scale applications. To address these challenges, this paper proposes the Pose-Directed Diffusion Model. Through optimized training of this module, the model in this paper significantly reduces training time. Additionally, the model in this paper integrates the Pro-controlNet module to enhance fine control during the image generation process. Importantly, this paper constructs a new CCC Image Collection dataset, featuring precise classifications, detailed annotations, and high-resolution images. The experimental results on the CCC Image Collection dataset demonstrate that our model performs excellently in terms of evaluation metrics such as MSE, PSNR, and SSIM. It shows significant improvement in training effectiveness on the original dataset, with outstanding performance both in terms of absolute error measurement and visual perception by the human eye. ©2024 IEEE.

关键词： Image annotation

来源：评论

学校读者我要写书评

暂无评论

FusionGCNN: An IoT-Based Novel Spatiotemporal Graph Convolutional Network for ECG Arrhythmia Detection

引用

IEEE Internet of Things Journal 2025年

作者： Iqbal, Saeed Zhong, Xiaopin Alhussein, Musaed Wu, Zongze Aurangzeb, Khursheed Liu, Weixiang Zhang, Yudong Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11543 Saudi Arabia Henan Polytechnic University School of Computer Science and Technology Henan Jiaozuo China

Electrocardiogram (ECG) arrhythmia identification is critical for early cardiovascular disease diagnosis and monitoring in Internet of Things (IoT) industry. Still, it is difficult due to complicated waveforms, individual variability, and the requirement for real-time analysis on resource-limited equipment. Traditional approaches sometimes fail to detect complicated spatial-temporal correlations in ECG data, limiting their efficiency in identifying arrhythmias. Furthermore, deploying these models in tinyML contexts, such as edge and IoT devices limited by large computational and memory needs, emphasizes the importance of lightweight, accurate models for real-time applications. Our suggested solution consists of three main components: SigNet, DualGCNN, and FusionGCNN. SigNet uses Separable Convolution layers to effectively extract local spatial features, making it ideal for IoT-based healthcare deployment. DualGCNN combines dual Graph Convolutional layers with spatial attention, allowing the model to capture local and global dependencies for better classification of arrhythmia. FusionGCNN combines the capabilities of GCN and SigNet with an effective feature fusion technique to improve feature representation while remaining computationally economical. Ablation tests show that FusionGCNN improves performance considerably, with greater accuracy (0.9641), lower training error (0.0004), and a higher F1 Score (0.9645) across a variety of ECG patterns. FusionGCNN, with its low training error, high stability, and computational economy, is well-suited to tinyML requirements, allowing implementation on edge and IoT devices for scalable, real-time ECG monitoring in healthcare. © 2014 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

A Class of Perimeter Defense Strategy via Relative Time and Maximum Matching

A Class of Perimeter Defense Strategy via Relative Time and ...

引用

2024 China Automation Congress, CAC 2024

作者： Yang, Chengqian Du, Ziyi Lin, Lixiong Xu, Guangtong Huang, Bomin School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China Department of Precision Instrument Tsinghua University Beijing China School of Ocean Information Engineering Jimei University Xiamen China Huzhou Institute Zhejiang University Huzhou China College of Computer Engineering Jimei University Xiamen China

ISBN: (纸本)9798350368604

This paper studies a class of perimeter defense problems for large-scale multi-robot systems. A perimeter defense strategy is designed via relative time calculations and maximum matching methods. The strategy is simple, effective, and easy to implement for large-scale perimeter defense problems. Some simulations are made to verify the effectiveness of the strategy. © 2024 IEEE.

关键词： Nanorobots

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：