检索结果-内蒙古大学图书馆

IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Hungary

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

The ever increasing need for performance results in increasingly rigorous demands on throughput and positioning accuracy of high-precision motion systems, which often suffer from position dependent effects that originate from relative actuation and sensing of the moving-body. Due to the highly stiff mechanical design, such systems are typically controlled using rigid body control design approaches. Nonetheless, the presence of position dependent flexible dynamics severely limits attainable position tracking performance. This paper presents two extensions of the conventional rigid body control framework towards active control of position dependent flexible dynamics. Additionally, a novel control design approach is presented, which allows for shaping of the full closed-loop system by means of structured H ∞ co-design. The effectiveness of the approach is validated through simulation using a high-fidelity model of a state-of-the-art moving-magnet planar actuator.

关键词： Linear systems Mechatronics Costs control design Tracking Dynamics Observers

来源：评论

学校读者我要写书评

暂无评论

Quality of Service-aware 6G-Enabled NB-IoT for Health Monitoring in Long Distance High-Speed Trains

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Roy, Bipasha Guha Roy, Deepsubhra Guha Dutta, Piyali Khan, Surbhi Bhatia Asiri, Fatima Ayadi, Manel Institute of Engineering and Management Kolkata India Institute of Engineering and Management Kolkata India University of Salford Chitkara University Institute of Engineering and Technology Chitkara University Department of Data Science United Kingdom University Centre for Research and Development Chandigarh University India Centre for Research Impact and Outcome Punjab Rajpura140401 India King Khalid University College of computer science Informatics and computer systems department Saudi Arabia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems Riyadh11671 Saudi Arabia

Internet of Things connectivity in home health monitoring is a high-in-demand application area. The electronics industry and procedural researchers seek high-end, secured, on-time, cost-effective ways to build reliable quality of service (QoS) proved autonomous systems using existing wireless techniques. Also, the continuous availability of a traffic-free gateway, particularly in isolated places, is necessary for large-scale data gathering and real-time data update processes to function the sensor nodes in an Internet of Things (IoT) network. Improved Narrowband IoT (NB-IoT) is one of the most desirable networks offered by 6th generation (6G) connectivity in IoT-associated remote-monitoring proceedings. In this article, we propose a QoS-aware narrow bandwidth allocation-based prototype model for healthcare monitoring in long-distance high-speed trains during the patient transfer from home to the healthcare center or vice versa. This article demonstrates a possible enhancement in social aspects of cognitive IoT applications with large data systems in industrial informatics. © 1975-2011 IEEE.

关键词： Frequency allocation

来源：评论

学校读者我要写书评

暂无评论

Machine Learning in Higher Education using RF and SVM for Pedagogical Enhancement 3

Machine Learning in Higher Education using RF and SVM for Pe...

引用

3rd International Conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Kunwar, Fateh Bahadur Srivastava, Satyajee Dhivya, R. Gulati, Monika Anand, Taruna Raj, D. Antony Arul Geetanjali Institute of Technical Studies Department of Computer Science and Engineering Udaipur India School of Engineering and Technology Manav Rachna International Institute of Research and Studies Department of Computer Science and Engineering Faridabad India M.Kumarasamy College of Engineering Department of Information Technology Karur India Ambala India University Department of Humanities and Social Sciences Dehradun India Psg College of Arts & Science Department of Software Systems Coimbatore India

ISBN: (纸本)9798331508456

AI's revolutionary potential in higher education is examined in this proposal, including how it could revolutionize teaching, learning, administration, and research. Adaptive learning platforms, intelligent tutoring systems, and virtual learning assistants may change how students learn by improving engagement, providing quick feedback, and enabling tailored learning. The suggested process includes preprocessing, feature extraction, and model training. Preprocessing involves de-anonymizing, tokenizing, and removing punctuation, spaces, and numbers before analysis. The linear transformation method PCA extracts features. Training the systems uses the RF -SVM approach, which combines the advantages of RF and SVM. The suggested RF -SVM model beats two RF and SVM models with an average accuracy of 90.39 *** improves resource use, strategic decision-making, and research capacity in university management. The RF-SVM model's success in academia highlights the practicality of AI-driven solutions. © 2025 IEEE.

关键词： Teaching

来源：评论

学校读者我要写书评

暂无评论

Model-based Generation of Attack-Fault Trees

arXiv

引用

arXiv 2023年

作者： Groner, Raffaela Witte, Thomas Raschke, Alexander Hirn, Sophie Pekaric, Irdin Frick, Markus Tichy, Matthias Felderer, Michael Institute of Software Engineering and Programming Languages Ulm University Germany Department of Computer Science University of Innsbruck Austria Department of Information Systems and Computer Science University of Liechtenstein Liechtenstein Germany Department of Mathematics and Computer Science University of Cologne Germany

Joint safety and security analysis of cyber-physical systems is a necessary step to correctly capture inter-dependencies between these properties. Attack-Fault Trees represent a combination of dynamic Fault Trees and Attack Trees and can be used to model and model-check a holistic view on both safety and security. Manually creating a complete AFT for the whole system is, however, a daunting task. It needs to span multiple abstraction layers, e.g., abstract application architecture and data flow as well as system and library dependencies that are affected by various vulnerabilities. We present an AFT generation tool-chain that facilitates this task using partial Fault and Attack Trees that are either manually created or mined from vulnerability databases. We semi-automatically create two system models that provide the necessary information to automatically combine these partial Fault and Attack Trees into complete AFTs using graph transformation rules. © 2023, CC BY-NC-ND.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Enhanced Capuchin Search Algorithm Using Cooperative Island Model with Application of Evolutionary Feedforward Neural Networks

Enhanced Capuchin Search Algorithm Using Cooperative Island ...

引用

Intelligent Computing, Communication, Networking and Services (ICCNS), International Conference on

作者： Thaer Thaher Mohammed Awad Alaa Sheta Mohammed Aldasht Department of Computer Systems Engineering Arab American University Jenin Palestine Computer Science Department Southern Connecticut State University CT 06515 USA Department of Computer Engineering Palestine Polytechnic University Hebron Palestine

This paper introduces an enhanced version of the Capuchin Search Algorithm (CapSA) called ECapSA. CapSA draws inspiration from the collective intelligence of Capuchin monkeys and has shown success in solving real-world problems. However, it may encounter challenges handling complex optimization tasks, such as premature convergence or being trapped in local optima. ECapSA employs a local escaping mechanism operating the abandonment limit concept to exploit potential solutions and introduce diversification trends. Additionally, the ECapSA algorithm is improved by integrating the principles of the cooperative island model, resulting in the iECapSA. This modification enables better management of population diversity and a more optimal balance between exploration and exploitation. The efficiency of iECapSA is validated through a series of experiments, including the IEEE-CEC2014 benchmark functions and training the feedforward neural network (FNN) on seven biomedical datasets. The performance of iECapSA is compared to other metaheuristic techniques, namely differential evolution (DE), sine cosine algorithm (SCA), and whale optimization algorithm (WOA). The results of the comparative study demonstrate that iECapSA is a strong contender and surpasses other training algorithms in most datasets, particularly in terms of its ability to avoid local optima and its improved convergence speed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LPV sequential loop closing for high-precision motion systems

arXiv

引用

arXiv 2022年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary

Increasingly stringent throughput requirements in the industry necessitate the need for lightweight design of high-precision motion systems to allow for high accelerations, while still achieving accurate positioning of the moving-body. The presence of position dependent dynamics in such motion systems severely limits achievable position tracking performance using conventional sequential loop closing (SLC) control design strategies. This paper presents a novel extension of the conventional SLC design framework towards linear-parameter-varying systems, which allows to circumvent limitations that are introduced by position dependent effects in high-precision motion systems. Advantages of the proposed control design approach are demonstrated in simulation using a high-fidelity model of a moving-magnet planar actuator system, which exhibits position dependency in both actuation and *** Codes 93-06 © 2022, CC BY.

关键词： Linear systems

来源：评论

学校读者我要写书评

暂无评论

Traditional Chinese Medicine Health Status Identification with Graph Attention Network 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Fu, Amin Ma, Jishun Wang, Chuansheng Zhou, Changen Li, Zuoyong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou350122 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The Traditional Chinese Medicine Health Status Identification plays an important role in TCM diagnosis and prescription recommendation. In this paper, we propose a method of Status Identification via Graph Attention Network, named SIGAT, which captures the complex medical correlation in the symptom-syndrome graph. More specifically, we construct a symptom-syndrome graph in that symptoms are taken as nodes and the edges are connected by syndromes. And we realize automatic induction of symptom to state element classification by using the attention mechanism and perceptron classifier. Finally, we conduct experiments by using hamming loss, coverage, 0/1 error, ranking loss, average precision, macro-F1 score, and micro-F1 score as evaluation metrics. The results demonstrate that the SIGAT model outperforms comparison algorithms on Traditional Chinese Medicine Prescription Dictionary dataset. The case study results suggest that the proposed method is a valuable way to identify the state element. The application of the graph attention network classification algorithm in TCM health status identification is of high precision and methodological feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

EMVGAN: Emotion-Aware Music-Video Common Representation Learning via Generative Adversarial Networks 5

EMVGAN: Emotion-Aware Music-Video Common Representation Lear...

引用

5th International Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia, MMArt-ACM 2022

作者： Tsai, Yu-Chih Pan, Tse-Yu Kao, Ting-Yang Yang, Yi-Hsuan Hu, Min-Chun Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science National Tsing Hua University Taiwan Institue of Information Systems and Applications National Tsing Hua University Taipei Taiwan Research Center for IT Innovation Academia Sinica Taiwan

ISBN: (纸本)9781450392402

Music can enhance our emotional reactions to videos and images, while videos and images can enrich our emotional response to music. Cross-modality retrieval technology can be used to recommend appropriate music for a given video and vice versa. However, the heterogeneity gap caused by the inconsistent distribution between different data modalities complicates learning the common representation space from different modalities. Accordingly, we propose an emotion-Aware music-video cross-modal generative adversarial network (EMVGAN) model to build an affective common embedding space to bridge the heterogeneity gap among different data modalities. The evaluation results revealed that the proposed EMVGAN model can learn affective common representations with convincing performance while outperforming other existing models. Furthermore, the satisfactory performance of the proposed network encouraged us to undertake the music-video bidirectional retrieval task. © 2022 ACM.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Deformation Pattern Shape Sensing for Visuotactile Endoscope

Deformation Pattern Shape Sensing for Visuotactile Endoscope

引用

2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Yanzhe Tian, Yuan Cui, Shaowei Wang, Yupeng Wang, Rui Wang, Shuo Beijing University of Science and Technology Beijing100083 China The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9798350372601

The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework for contact deformation pattern shape, providing a foundation for precise perception in miniaturized visuotactile sensors. Specifically, we first construct a Deformation Pattern shape Descriptor (DPSD) and then track the key points in the descriptor using optical flow to obtain contact deformation shape information. Through extensive qualitative and quantitative experiments, our proposed algorithm achieves an average perception accuracy of around 83.81% for contact pattern shapes. It demonstrates consistent perception accuracy across various contact force magnitudes, directions, and scenarios, highlighting its robustness. Additionally, compared to traditional marker-level methods, it achieves a notable 46.5% improvement in displacement field perception accuracy. This research elevates tactile perception to the dimension of contact pattern shape sensing and has the potential for application in miniaturized visual tactile sensors. © 2024 IEEE.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

RL-Based Cargo-UAV Trajectory Planning and Cell Association for Minimum Handoffs, Disconnectivity, and Energy Consumption

arXiv

引用

arXiv 2023年

作者： Cherif, Nesrine Jaafar, Wael Yanikomeroglu, Halim Yongacoglu, Abbas School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada MontrealQC Canada Department of Systems and Computer Engineering Carleton University OttawaON Canada

Unmanned aerial vehicle (UAV) is a promising technology for last-mile cargo delivery. However, the limited on-board battery capacity, cellular unreliability, and frequent handoffs in the airspace are the main obstacles to unleash its full potential. Given that existing cellular networks were primarily designed to service ground users, re-utilizing the same architecture for highly mobile aerial users, e.g., cargo-UAVs, is deemed challenging. Indeed, to ensure a safe delivery using cargo-UAVs, it is crucial to utilize the available energy efficiently, while guaranteeing reliable connectivity for command-and-control and avoiding frequent handoff. To achieve this goal, we propose a novel approach for joint cargo-UAV trajectory planning and cell association. Specifically, we formulate the cargo-UAV mission as a multiobjective problem aiming to 1) minimize energy consumption, 2) reduce handoff events, and 3) guarantee cellular reliability along the trajectory. We leverage reinforcement learning (RL) to jointly optimize the cargo-UAV’s trajectory and cell association. Simulation results demonstrate a performance improvement of our proposed method, in terms of handoffs, disconnectivity, and energy consumption, compared to benchmarks. © 2023, CC BY.

关键词： Energy utilization

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：