检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

High Accurate Detection Method for Aortic Valve Opening of Seismocardiography Signals

SSRN

引用

SSRN 2022年

作者： Zheng, Chundi Peng, Weiming Huang, Tianyao Eldar, Yonina C. Yu, Meiyi School of Electronic Information Engineering Foshan University Guangdong Foshan528225 China School of Mechatronic Engineering and Automation Foshan University Guangdong Foshan528225 China Department of Electronic Engineering Tsinghua University Beijing100084 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

Accurately detecting the aortic valve opening (AO) peaks of seismocardiography (SCG) is a challenging problem due to interference of other morphological inflection points. In this paper, a high accurate method is proposed to extract AO peaks based solely upon the SCG data. The raw SCG signal is purified by a first order interference cancellation method, resulting in a reduced number of modes to be decomposed. The purified SCG signal is then decomposed into a series of quasi-orthogonal modes by successive variational mode decomposition without any prior about the number of modes. Considering the pulsatile nature of the AO signal, a waveform factor criterion is proposed to reconstruct the AO signal based on the pulsatile level of each mode. A seventh power law detector is designed to amplify the AO peak and suppress spurious peaks. The publicly available CEBS database is exploited to verify the performance of the proposed method. We show that the average sensitivity of our technique is 99.02%, the prediction rate is 99.06%, and the detection accuracy is 98.10%, which is superior to several state-of-the-art methods. In addition, compared with the ECG reference value, the instantaneous heart rate extracted by the proposed method is in good agreement with that of the ECG, e.g., the maximum average absolute error percentage is as low as 2.11 and the maximum average value relative error is about 0.03, further demonstrating that the proposed method can achieve accurate estimates of heart rate with an accelerometer alone. © 2022, The Authors. All rights reserved.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Galaxy Morphological Visual Representation with Deep Contrastive Learning

arXiv

引用

arXiv 2022年

作者： Wei, Shoulin Li, Yadi Lu, Wei Li, Nan Liang, Bo Dai, Wei Zhang, Zhijian Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming650500 China National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China Faculty of Science Kunming University of Science and Technology Kunming650500 China

Galaxy morphology reflects structural properties which contribute to understand the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented performance on galaxy morphological classification. Such networks mostly follow the supervised learning paradigm which requires sufficient labelled data for training. However, it is an expensive and complicated process of labeling for million galaxies, particularly for the forthcoming survey projects. In this paper, we present an approach based on contrastive learning with aim for learning galaxy morphological visual representation using only unlabeled data. Considering the properties of low semantic information and contour dominated of galaxy image, the feature extraction layer of the proposed method incorporates vision transformers and convolutional network to provide rich semantic representation via the fusion of the multi-hierarchy features. We train and test our method on 3 classifications of datasets from Galaxy Zoo 2 and SDSS-DR17, and 4 classifications from Galaxy Zoo DECaLS. The testing accuracy achieves 94.7%, 96.5% and 89.9% respectively. The experiment of cross validation demonstrates our model possesses transfer and generalization ability when applied to the new datasets. The code that reveals our proposed method and pretrained models are publicly available and can be easily adapted to new surveysa) © 2022, CC BY.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Practical Aspects of Creating a Teacher's Information Space 5

Practical Aspects of Creating a Teacher's Information Space

引用

5th International Conference on Information Technologies in engineering Education, Inforino 2020

作者： Muzyleva, Inna Yazykova, Liubov Martynova, Anzhelika Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia Lipetsk State Technical University Institute of Mechanical Engineering Lipetsk Russia

ISBN: (纸本)9781728148106

The article discusses one of the aspects of digitalization of education, in terms of digitalization of the educational process itself. The methodology of creating a personal information space of a teacher is presented. The form of this space is a teaching site with teaching materials. A method for structuring methodological content is proposed. The methodology of posting structured content on a WordPress blog is described. A method for creating media content for special disciplines of technical areas of training is considered. The analysis of educational video content presented on the Internet is carried out. A step-by-step methodology for creating a video lesson in the Camtasia Studio program based on the Power Point presentation is described. There is an example of its application, successfully implemented in the educational process. © 2020 IEEE.

关键词： Studios

来源：评论

学校读者我要写书评

暂无评论

Unified Domain Adaptive Semantic Segmentation

arXiv

引用

arXiv 2023年

作者： Zhang, Zhe Wu, Gaochang Zhang, Jing Zhu, Xiatian Tao, Dacheng Chai, Tianyou The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China The Surrey Institute for People-Centred Artificial Intelligence Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom The School of Computer Science Faculty of Engineering University of Sydney Sydney Australia

Unsupervised Domain Adaptive Semantic Segmentation (UDA-SS) aims to transfer the supervision from a labeled source domain to an unlabeled and shifted target domain. The majority of existing UDA-SS works typically consider images whilst recent attempts have extended further to tackle videos by modeling the temporal dimension. Although two lines of research share the major challenges – overcoming the underlying domain distribution shift, their studies are largely independent. It causes several issues: (1) The insights gained from each line of research remain fragmented, leading to a lack of holistic understanding of the problem and potential solutions. (2) Preventing the unification of methods and best practices across two scenarios (images and videos) will lead to redundant efforts and missed opportunities for cross-pollination of ideas. (3) Without a unified approach, the knowledge and advancements made in one scenario may not be effectively transferred to the other, leading to suboptimal performance and slower progress. Under this observation, we advocate unifying the study of UDA-SS across video and image scenarios, enabling a more comprehensive understanding, synergistic advancements, and efficient knowledge sharing. To that end, we explore the unified UDA-SS from a general domain augmentation perspective, serving as a unifying framework, enabling improved generalization, and potential for cross-pollination, ultimately contributing to the practical impact and overall progress. Specifically, we propose a Quad-directional Mixup (QuadMix) method, characterized by tackling intra-domain discontinuity, fragmented gap bridging, and feature inconsistencies through four-directional paths designed for intra- and inter-domain mixing within an explicit feature space. To deal with temporal shifts within videos, we incorporate optical flow-guided feature aggregation across spatial and temporal dimensions for fine-grained domain alignment, which is extendable to image scenarios

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

来源：评论

学校读者我要写书评

暂无评论

Decentralized Nonconvex Robust Optimization over Unsafe Multiagent Systems: System Modeling, Utility, Resilience, and Privacy Analysis

arXiv

引用

arXiv 2024年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Cheng, Huqiang Guo, Xiaoyu Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Key Laboratory of Dependable Services Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing400044 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multiagent systems (MASs). Considering an unsafe MAS with these two issues, this paper targets the resolution of a class of nonconvex optimization problems under the Polyak-Lojasiewicz (P-L) condition. To address this problem, we first identify and construct the unsafe MAS model. Under this kind of unfavorable MASs, we mask the local gradients with Gaussian noises and adopt a resilient aggregation method self-centered clipping (SCC) to design a differentially private (DP) decentralized Byzantine-resilient algorithm, namely DP-SCC-PL, which simultaneously achieves differential privacy and Byzantine resilience. The convergence analysis of DP-SCC-PL is challenging since the convergence error can be contributed jointly by privacy-preserving and Byzantine-resilient mechanisms, as well as the nonconvex relaxation, which is addressed via seeking the contraction relationships among the disagreement measure of reliable agents before and after SCC aggregation, together with the optimal gap. Theoretical results reveal that DP-SCC-PL achieves consensus among all reliable agents and sublinear (inexact) convergence with well-designed step-sizes. It has also been proved that if there are no privacy issues and Byzantine agents, then the asymptotic exact convergence can be recovered. Numerical experiments verify the utility, resilience, and differential privacy of DP-SCC-PL by tackling a nonconvex optimization problem satisfying the P-L condition under various Byzantine attacks. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

DFGC-VRA: DeepFake Game Competition on Visual Realism Assessment

DFGC-VRA: DeepFake Game Competition on Visual Realism Assess...

引用

IEEE International Joint Conference on Biometrics (IJCB)

作者： Bo Peng Xianyun Sun Caiyong Wang Wei Wang Jing Dong Zhenan Sun Rongyu Zhang Heng Cong Lingzhi Fu Hao Wang Yusheng Zhang Hanyuan Zhang Xin Zhang Boyuan Liu Hefei Ling Luka Dragar Borut Batagelj Peter Peer Vitomir Štruc Xinghui Zhou Kunlin Liu Weitao Feng Weiming Zhang Haitao Wang Wenxiu Diao Center for Research on Intelligent Perception and Computing (CRIPAC) Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Beijing University of Civil Engineering and Architecture (BUCEA) China Interactive Entertainment Group of Netease Inc Guangzhou China Huazhong University of Science and Technology (HUST) China Faculty of Computer and Information Science University of Ljubljana (UNILJ) Slovenia Faculty of Electrical Engineering University of Ljubljana (UNILJ) Slovenia University of Science and Technology of China (USTC) China Institute of Network Technology (INT) Yantai China Nanjing University of Science and Technology (NUST) China

This paper presents the summary report on the DeepFake Game Competition on Visual Realism Assessment (DFGC-VRA). Deep-learning based face-swap videos, also known as deepfakes, are becoming more and more realistic and deceiving. The malicious usage of these face-swap videos has caused wide concerns. There is a ongoing deepfake game between its creators and detectors, with the human in the loop. The research community has been focusing on the automatic detection of these fake videos, but the assessment of their visual realism, as perceived by human eyes, is still an unexplored dimension. Visual realism assessment, or VRA, is essential for assessing the potential impact that may be brought by a specific face-swap video, and it is also useful as a quality metric to compare different face-swap methods. This is the third edition of DFGC competitions, which focuses on the new visual realism assessment topic, different from previous ones that compete creators versus detectors. With this competition, we conduct a comprehensive study of the SOTA performance on the new task. We also release our MindSpore codes to further facilitate research in this field (https://***/bomb2peng/DFGC-VRA-benckmark).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Electronic Arc Ignition System for the Electric Arc Plasmatron 2

Electronic Arc Ignition System for the Electric Arc Plasmatr...

引用

2nd International Conference on Control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2020

作者： Pikalov, Vladimir Boikov, Andrei Znamensky, Vladislav Ambrosimov, Sergey Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia Lipetsk State Technical University Institute of Mechanical Engineering Lipetsk Russia

ISBN: (纸本)9781728188409

Working with an electric arc plasmatron, the technological process provides for the ignition of an electric arc. To simplify and accelerate the process of an electric arc ignition in a direct current electric arc plasmatron, a circuit solution based on a high-voltage electronic ignition system with an independent power source is proposed. The proposed scheme allows the formation of high-voltage high-frequency pulses in the arc interval. The proposed electrical complex provides reliable ignition and maintenance of stable combustion in all possible modes of operation of the electric arc plasmatron. Various ignition systems, an electric arc in an atmospheric environment are considered, as well as using plasma-forming gases. © 2020 IEEE.

关键词： Electric arcs

来源：评论

学校读者我要写书评

暂无评论

Self-Adaptive Teaching-Learning-Based Optimizer with Improved Rbf and Sparse Autoencoder for High-Dimensional Problems

SSRN

引用

SSRN 2022年

作者： Bi, Jing Wang, Ziqi Yuan, Haitao Zhang, Jia Zhou, MengChu School of Software Engineering Faculty of Information Technology Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Department of Computer Science The Lyle School of Engineering Southern Methodist University DallasTX75205 United States Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Evolutionary algorithms are commonly used to solve many complex optimization problems in different fields. Yet, their performance is limited when dealing with high-dimensional complex problems because they often require enormous computational resources to yield desired solutions, and they may easily trap into local optima. To solve this problem, this work proposes a Selfadaptive Teaching-learning-based Optimizer with an improved Radial basis function model and a sparse Autoencoder (STORA). In STORA, a Self-adaptive Teaching-Learning-Based Optimizer (STLBO) is designed to dynamically adjust parameters for balancing exploration and exploitation abilities. Then, a sparse autoencoder (SAE) is adopted as a dimension reduction method to compress search space into lower-dimensional one for more efficiently guiding population to converge towards global optima. Besides, an Improved Radial Basis Function model (IRBF) is designed as a surrogate model to balance training time and prediction accuracy. It is adopted to save computational resources for improving overall performance. In addition, a dynamic population allocation strategy is adopted to well integrate SAE and IRBF in STORA. We evaluate STORA by comparing it with several state-of-the-art algorithms through eight benchmark functions. We further test its actual performance by applying it to solve a real-world computation offloading problem. © 2022, The Authors. All rights reserved.

关键词： Radial basis function networks

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：