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Mediterranean Journal of Measurement and Control 2007年第2期3卷 59-67页

作者： Tahoun, Ali Husin Abouelsoud, Ahmed Ali Mahmoud, Magdi Sadek Hassan, Mohamed F. Fahmy, M.M. Computer and Control Department Faculty of Engineering Tanta University Tanta Egypt Electronic and Communication Department Faculty of Engineering Cairo University Giza Egypt Graduate Studies Program Cairo University Giza Egypt Hust University Huazhong China

In this paper, we develop an approach for robust model reference adaptive control of continuous-time MIMO linear dynamical systems in the presence of output disturbance. In comparison with earlier approaches in the literature, the proposed approach has the advantage that the assumption of knowing an upper bound of the disturbance is removed. The development of the approach relies heavily on Lyapunov's stability criterion and the dead-zone technique. The approach is applied to a numerical example of an articulated suspension system subject to output disturbance. Copyright © 2007 SoftMotor Ltd.

关键词： Multivariable systems

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Corrigendum to "Novel model of multiple sclerosis induced by EBV-like virus generate a unique B cell population" [Journal of Neuroimmunology volume 394 (2024) 578408]

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Journal of neuroimmunology 2025年 404卷 578625页

作者： J L Deffenbaugh K-J Jung S P Murphy Y Liu C N Rau C Petersen-Cherubini P L Collins D Chung A E Lovett-Racke Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA. Department of Computer Science and Engineering The Ohio State University USA. Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA Neuroscience Graduate Program The Ohio State University USA. Department of Biomedical Informatics The Ohio State University Wexner Medical Center USA Pelotonia Institute for Immuno-Oncology The Ohio State University Wexner Medical Center USA. Department of Neuroscience The Ohio State University Wexner Medical Center USA. Electronic address: amylovettracke@***.

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Lightweight Authenticated Key Agreement Protocol for Smart Power Grid Systems Using PUF

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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A Preliminary Study on the Collaborative Playing Piano Automatic with Deep Learning

A Preliminary Study on the Collaborative Playing Piano Autom...

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IEEE International Conference on Consumer electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Karuna Yampray Department of Electronic Engineering International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan College of Creative Design and Entertainment Technology Dhurakij Pundit University Bangkok Thailand

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A great number of deep learning-based models have been recently proposed for automatic piano classification. In this paper, we describe our contribution to the challenge of automatic piano classification when the performer performs at the concert or stage. Among these models in deep learning, we use init-1D-WaveNet and init-2D-MLNet for comparison the accuracy in the piano beginning level of the Christmas song (Jingle bells). Our experimental results show that the assessment using the init-2D-MLNet still achieve high accuracy of 87.5%.

关键词： Deep learning Accuracy Instruments Collaboration Consumer electronics

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Act as you wish: fine-grained control of motion diffusion model with hierarchical semantic graphs 23

Act as you wish: fine-grained control of motion diffusion mo...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Peng Jin Yang Wu Yanbo Fan Zhongqian Sun Yang Wei Li Yuan School of Electronic and Computer Engineering Peking University Shenzhen China and AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China Tencent AI Lab China School of Electronic and Computer Engineering Peking University Shenzhen China and Peng Cheng Laboratory Shenzhen China and AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China

Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicitly for human motion synthesis. However, these compact text representations may overemphasize the action names at the expense of other important properties and lack fine-grained details to guide the synthesis of subtly distinct motion. In this paper, we propose hierarchical semantic graphs for fine-grained control over motion generation. Specifically, we disentangle motion descriptions into hierarchical semantic graphs including three levels of motions, actions, and specifics. Such global-to-local structures facilitate a comprehensive understanding of motion description and fine-grained control of motion generation. Correspondingly, to leverage the coarse-to-fine topology of hierarchical semantic graphs, we decompose the text-to-motion diffusion process into three semantic levels, which correspond to capturing the overall motion, local actions, and action specifics. Extensive experiments on two benchmark human motion datasets, including HumanML3D and KIT, with superior performances, justify the efficacy of our method. More encouragingly, by modifying the edge weights of hierarchical semantic graphs, our method can continuously refine the generated motion, which may have a far-reaching impact on the community. Code and pre-trained weights are available at https://***/jpthu17/GraphMotion.

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Partial response maximum likelihood sequence detector for a nonlinear magnetic recording channel

Partial response maximum likelihood sequence detector for a ...

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International Conference on System Science and engineering (ICSSE)

作者： Tsai-Sheng Kao Chiu-Hsiung Chen Sheng-Chih Chen Sheng-Yun Hou Yuan-Chang Chang Xsing-Bang Chou Department of Electronic Engineering Hwa-Hsia College of Technology and Commerce Taipei Taiwan Department of Computer Science and Information Engineering China University of Technology Hsinchu Taiwan Graduate Program of Digital Content and Technologies Chengchi University Taiwan

The nonlinear effects of partial erasure and transition shift, however, often limit the performance attained by the partial response maximum likelihood (PRML) detector because of model mismatch. Conventionally, the nonlinear effects are either ignored or approximated by linearization technique. In the article, a PRML detector for the PR4 model including the nonlinear effects has been developed to improve the detector performance. The new representation is more accurate and the corresponding PRML detector has better performance without increasing the realization complexity. computer simulation results show that the new representation outperforms the conventional ones due to the enhanced modeling capability. The method is also expected to be applied in the high order partial response channel.

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Reconfigurable Intelligent Surface-Aided Joint Radar and Covert Communications: Fundamentals, Optimization, and Challenges

arXiv

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arXiv 2022年

作者： Du, Hongyang Kang, Jiawen Niyato, Dusit Zhang, Jiayi Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Future wireless communication systems will evolve toward multi-functional integrated systems to improve spectrum utilization and reduce equipment sizes. A joint radar and communication (JRC) system, which can support simultaneous information transmission and target detection, has been regarded as a promising solution for emerging applications such as autonomous vehicles. In JRC, data security and privacy protection are critical issues. Thus, we first apply covert communication into JRC and propose a joint radar and covert communication (JRCC) system to achieve high spectrum utilization and secure data transmission simultaneously. In the JRCC system, an existence of sensitive data transmission is hidden from a maliciously observant warden. However, the performance of JRCC is restricted by severe signal propagation environment and hardware devices. Fortunately, reconfigurable intelligent surfaces (RISs) can change the signal propagation smartly to improve the networks performance with low cost. We first overview fundamental concepts of JRCC and RIS and then propose the RIS-aided JRCC system design. Furthermore, both covert communication and radar performance metrics are investigated and a game theory-based covert rate optimization scheme is designed to achieve secure communication. Finally, we present several promising applications and future directions of RIS-aided JRCC systems. © 2022, CC BY.

关键词： Data transfer

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WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation

arXiv

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arXiv 2023年

作者： Cheng, Zesen Jin, Peng Li, Hao Li, Kehan Li, Siheng Ji, Xiangyang Liu, Chang Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Peng Cheng Laboratory Shenzhen China Tsinghua University Beijing China

The top-down and bottom-up methods are two mainstreams of referring segmentation, while both methods have their own intrinsic weaknesses. Top-down methods are chiefly disturbed by Polar Negative (PN) errors owing to the lack of fine-grained cross-modal alignment. Bottom-up methods are mainly perturbed by Inferior Positive (IP) errors due to the lack of prior object information. Nevertheless, we discover that two types of methods are highly complementary for restraining respective weaknesses but the direct average combination leads to harmful interference. In this context, we build Win-win Cooperation (WiCo) to exploit complementary nature of two types of methods on both interaction and integration aspects for achieving a win-win improvement. For the interaction aspect, Complementary Feature Interaction (CFI) provides fine-grained information to top-down branch and introduces prior object information to bottom-up branch for complementary feature enhancement. For the integration aspect, Gaussian Scoring Integration (GSI) models the gaussian performance distributions of two branches and weighted integrates results by sampling confident scores from the distributions. With our WiCo, several prominent top-down and bottom-up combinations achieve remarkable improvements on three common datasets with reasonable extra costs, which justifies effectiveness and generality of our method. Copyright © 2023, The Authors. All rights reserved.

关键词： Integration

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Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

arXiv

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arXiv 2023年

作者： Jin, Peng Wu, Yang Fan, Yanbo Sun, Zhongqian Wei, Yang Yuan, Li School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China Tencent AI Lab China -Preferred Program Peking University Shenzhen Graduate School China

Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicitly for human motion synthesis. However, these compact text representations may overemphasize the action names at the expense of other important properties and lack fine-grained details to guide the synthesis of subtly distinct motion. In this paper, we propose hierarchical semantic graphs for fine-grained control over motion generation. Specifically, we disentangle motion descriptions into hierarchical semantic graphs including three levels of motions, actions, and specifics. Such global-to-local structures facilitate a comprehensive understanding of motion description and fine-grained control of motion generation. Correspondingly, to leverage the coarse-to-fine topology of hierarchical semantic graphs, we decompose the text-to-motion diffusion process into three semantic levels, which correspond to capturing the overall motion, local actions, and action specifics. Extensive experiments on two benchmark human motion datasets, including HumanML3D and KIT, with superior performances, justify the efficacy of our method. More encouragingly, by modifying the edge weights of hierarchical semantic graphs, our method can continuously refine the generated motion, which may have a far-reaching impact on the community. Code and pre-training weights are available at https://***/jpthu17/GraphMotion. Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

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Discover and align taxonomic context priors for open-world semi-supervised learning 23

Discover and align taxonomic context priors for open-world s...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Yu Wang Zhun Zhong Pengchong Qiao Xuxin Cheng Xiawu Zheng Chang Liu Nicu Sebe Rongrong Ji Jie Chen School of Electronic and Computer Engineering Peking University Shenzhen China and AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China School of Computer Sceince University of Nottingham United Kingdom School of Electronic and Computer Engineering Peking University Shenzhen China and Department of Information Engineering and Computer Science University of Trento Italy School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China and Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Department of Automation Tsinghua University Beijing China Department of Information Engineering and Computer Science University of Trento Italy School of Electronic and Computer Engineering Peking University Shenzhen China and Peng Cheng Laboratory Shenzhen China and AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China

Open-world Semi-Supervised Learning (OSSL) is a realistic and challenging task, aiming to classify unlabeled samples from both seen and novel classes using partially labeled samples from the seen classes. Previous works typically explore the relationship of samples as priors on the pre-defined single-granularity labels to help novel class recognition. In fact, classes follow a taxonomy and samples can be classified at multiple levels of granularity, which contains more underlying relationships for supervision. We thus argue that learning with single-granularity labels results in sub-optimal representation learning and inaccurate pseudo labels, especially with unknown classes. In this paper, we take the initiative to explore and propose a uniformed framework, called Taxonomic context prIors Discovering and Aligning (TIDA), which exploits the relationship of samples under various granularity. It allows us to discover multi-granularity semantic concepts as taxonomic context priors (i.e., sub-class, target-class, and super-class), and then collaboratively leverage them to enhance representation learning and improve the quality of pseudo labels. Specifically, TIDA comprises two components: i) A taxonomic context discovery module that constructs a set of hierarchical prototypes in the latent space to discover the underlying taxonomic context priors; ii) A taxonomic context-based prediction alignment module that enforces consistency across hierarchical predictions to build the reliable relationship between classes among various granularity and provide additions supervision. We demonstrate that these two components are mutually beneficial for an effective OSSL framework, which is theoretically explained from the perspective of the EM algorithm. Extensive experiments on seven commonly used datasets show that TIDA can significantly improve the performance and achieve a new state of the art. The source codes are publicly available at https://***/rain305f/TIDA.

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