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Engineering 2024年第6期 208-214页

作者：刘雪明闫贤 H.Eugene Stanley School of Artificial Intelligence and Automation & The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems & the Key Laboratory of Image Processing Huazhong University of Science and Technology Center for Polymer Studies Department of Physics Boston University

Complex networked systems, which range from biological systems in the natural world to infrastructure systems in the human-made world, can exhibit spontaneous recovery after a failure; for example, a brain may spontaneously return to normal after a seizure, and traffic flow can become smooth again after a jam. Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks. However, most real-world networks are directed. To fill this gap, we build a model in which nodes may alternately fail and recover, and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks. We find that the tool can accurately predict the final fraction of active nodes, and the prediction accuracy decreases as the fraction of bidirectional links in the network increases, which emphasizes the importance of directionality in network dynamics. Due to different initial states, directed dynamical networks may show alternative stable states under the same control parameter, exhibiting hysteresis behavior. In addition, for networks with finite sizes, the fraction of active nodes may jump back and forth between high and low states, mimicking repetitive failure-recovery processes. These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

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The Digestive Residues of Maize Starch-Caffeic Acid Complexes Significantly Change the Metabolites and Microbiota Composition During in Vitro Colon Fermentation

SSRN

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SSRN 2024年

作者： Zheng, Yuxue Ye, Xingqian Hu, Yanyu Wang, Shaoyun Tian, Jinhu College of Biological Science and Engineering Institute of Food and Marine Bio-Resources Fuzhou University Fuzhou350108 China College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang Key Laboratory for Agro-Food Processing Integrated Research Base of Southern Fruit and Vegetable Preservation Technology Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control Fuli Institute of Food Science Zhejiang University Hangzhou310058 China Zhejiang University Zhongyuan Institute Zhengzhou450000 China

To investigate the effect of digestive residues of maize starch–caffeic complexes on the composition of human metabolites and gut microbiota, maize starch was extruded with caffeic acid, and subjected to in vitro gastrointestinal digestion. Then, the undigested parts were fermented with human faecal microbiota in vitro, and the morphology, short-chain fatty acids composition, microbiota communities and structural characteristics of the fermented residues were investigated. The results indicated that the amorphous area of the residues is preferentially utilized by gut microbiota and then the crystalline area. The acetate concentration in extruded maize residues with or without caffeic acid residues increased to 19.19 ± 0.40 and 23.10 ± 0.92 mmoL/L, respectively, after 24 h of fermentation. Microbiota analysis indicated that the digestive residue of maize starch-caffeic acid complexes promoted the growth of potentially beneficial microbiota, especially Bifidobacterium and Lactococcus genus. In general, extruded maize starch with caffeic acid might be a potential functional food substance for gut health. © 2024, The Authors. All rights reserved.

关键词： Fatty acids

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Preface

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2023年 492卷 v-vi页

作者： Luan, Xiaoli He, Shuping Liu, Fei Key Laboratory of Advanced Process Control for Light Industry [Ministry of Education Institute of Automation Jiangnan University Jiangsu Wuxi China Key Laboratory of Intelligent Computing and Signal Processing [Ministry of Education School of Electrical Engineering and Automation Anhui University Anhui Hefei China

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V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results

arXiv

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arXiv 2024年

作者： Wang, Jiaqi Zang, Yuhang Zhang, Pan Chu, Tao Cao, Yuhang Sun, Zeyi Liu, Ziyu Dong, Xiaoyi Wu, Tong Lin, Dahua Chen, Zeming Wang, Zhi Meng, Lingchen Yao, Wenhao Yang, Jianwei Wu, Sihong Chen, Zhineng Wu, Zuxuan Jiang, Yu-Gang Wu, Peixi Chai, Bosong Nie, Xuan Yan, Longquan Wang, Zeyu Zhou, Qifan Wang, Boning Huang, Jiaqi Xu, Zunnan Li, Xiu Yuan, Kehong Zu, Yanyan Hao, Jiayao Gao, Qiong Jiao, Licheng Shanghai AI Laboratory China Chinese University of Hong Kong Hong Kong Shanghai Jiao Tong University China Wuhan University China Shenzhen International Graduate School Tsinghua University China Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University China Shanghai Collaborative Innovation Center of Intelligent Visual Computing China Microsoft Research Redmond United States University of Science and Technology of China China Zhejiang University China Northwestern Polytechnical University China Northwest University China Tsinghua Shenzhen International Graduate School Tsinghua University China Intelligent Perception and Image Understanding Lab Xidian University China

Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown or unseen objects. The challenges necessitate the development of public benchmarks and challenges to advance the field of object detection. Inspired by the success of previous COCO [15] and LVIS [11] Challenges, we organize the V3Det Challenge 2024 in conjunction with the 4th Open World Vision Workshop: Visual Perception via Learning in an Open World (VPLOW) at CVPR 2024, Seattle, US. This challenge aims to push the boundaries of object detection research and encourage innovation in this field. The V3Det Challenge 2024 consists of two tracks: 1) Vast Vocabulary Object Detection: This track focuses on detecting objects from a large set of 13204 categories, testing the detection algorithm's ability to recognize and locate diverse objects. 2) Open Vocabulary Object Detection: This track goes a step further, requiring algorithms to detect objects from an open set of categories, including unknown objects. In the following sections, we will provide a comprehensive summary and analysis of the solutions submitted by participants. By analyzing the methods and solutions presented, we aim to inspire future research directions in vast vocabulary and open-vocabulary object detection, driving progress in this field. Challenge homepage: https://***/challenge. © 2024, CC BY-NC-SA.

关键词： Object detection

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Consensus algorithms for biased labeling in crowdsourcing

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Information Sciences 2017年 382-383卷 254-273页

作者： Jing Zhang Victor S. Sheng Qianmu Li Jian Wu Xindong Wu School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 P. R. China Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing 210094 P. R. China Department of Computer Science University of Central Arkansas Conway AR 72035 USA Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 P. R. China Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 P. R. China School of Computing and Informatics University of Louisiana at Lafayette LA 70504 USA

Although it has become an accepted lay view that when labeling objects through crowdsourcing systems, non-expert annotators often exhibit biases, this argument lacks sufficient evidential observation and systematic empirical study. This paper initially analyzes eight real-world datasets from different domains whose class labels were collected from crowdsourcing systems. Our analyses show that biased labeling is a systematic tendency for binary categorization; in other words, for a large number of annotators, their labeling qualities on the negative class (supposed to be the majority) are significantly greater than are those on the positive class (minority). Therefore, the paper empirically studies the performance of four existing EM-based consensus algorithms , DS, GLAD, RY, and ZenCrowd, on these datasets. Our investigation shows that all of these state-of-the-art algorithms ignore the potential bias characteristics of datasets and perform badly although they model the complexity of the systems. To address the issue of handling biased labeling, the paper further proposes a novel consensus algorithm, namely adaptive weighted majority voting (AWMV), based on the statistical difference between the labeling qualities of the two classes. AWMV utilizes the frequency of positive labels in the multiple noisy label set of each example to obtain a bias rate and then assigns weights derived from the bias rate to negative and positive labels. Comparison results among the five consensus algorithms (AWMV and the four existing) show that the proposed AWMV algorithm has the best overall performance. Finally, this paper notes some potential related topics for future study.

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The influence mechanism of rare earth element doping on the electron/phonon transport performances of In₂O₃ based thermoelectric materials

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Results in Physics 2024年 60卷

作者： She, Xinqi Xiong, Tongqiang Wang, Zhibin Cai, Guoji Chen, Yonghong Sun, Yong Zheng, ZhiPeng Zhou, Guopeng Feng, Bo Institute of Engineering and Technology Hubei University of Science and Technology Xianning 437100 China The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and Technology Wuhan 430081 China School of Mechanical and Electrical Engineering Wuhan Donghu University Wuhan 430070 China Natural Gas Processing Plant of Zhong Yuan Oil Field Company of SINOPEC Puyang 457162 China The Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and Technology Xianning 437100 China School of Electronic and Electrical Engineering Wuhan Textile University Wuhan 430200 China

In2O3 based materials are one of the most promising high-temperature thermoelectric materials for application. Herein, Sm doped In2O3 samples were prepared by mechanical alloying, high-temperature calcination, and dis... 详细信息

In₂O₃ based materials are one of the most promising high-temperature thermoelectric materials for application. Herein, Sm doped In₂O₃ samples were prepared by mechanical alloying, high-temperature calcination, and discharge plasma sintering, and the influence mechanism of rare earth element doping on the thermoelectric properties of In₂O₃ based semiconductors was studied. The results indicate that the electrical conductivity increased significantly. Due to the introduction of Sm impurity levels, the density of states near the Fermi level significantly increases. The bandgap widens, and the mobility first decreases and then increases. Due to the increase in carrier concentration, the absolute value of the Seebeck coefficient decreases, but the gain effect caused by the increase in conductivity is greater than the debuff caused by the decrease in the absolute value of the Seebeck coefficient. The power factor increases after Sm *** thermal conductivity decreases due to the decrease in Young's modulus, enhanced heterogeneous scattering, and enhanced heavy element scattering. The ZT value was raised to ∼0.327 at 973 K, obtained by Sm doped In₂O₃ sample with x = 0.060, which is ∼6 times as that of the pristine In₂O₃ sample. © 2024 The Authors

关键词： Electron transport Impurity level Rare-earth element Thermoelectric materials

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Research on Improved Multiple Users Detection Algorithm in Pattern Division Multiple Access System

SSRN

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SSRN 2022年

作者： Tang, Wanwei Wang, Lixia Wang, Zedai Han, Guofeng Zhao, Jinlong Yue, Xinwei The Key Laboratory of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan063000 China The School of Engineering Hong Kong University of Science and Technology Hong Kong999077 Hong Kong The Guofeng Han is with the Tangshan employment service center Tangshan human resources and Social Security Bureau Tangshan063000 China The School of Electronic and Information Engineering Beihang University Beijing100191 China The School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China

Receiver detection algorithm has always been a research hotspot in communication system and the key point to determine the performance of 5G system. Both industry and academia have been committed to finding detection algorithms with lower complexity and higher detection performance. This paper will study how to solve the problems of low detection performance and high complexity of classical algorithms. Taking Pattern Division Multiple Access (PDMA) as an example, this paper improves the existing receiver detection algorithms such as Minimum Mean Square Error-Serial Interference Cancellation(MMSE-SIC), Message Passing Algorithm (MPA) and Expectation Propagation Algorithm (EPA), and puts forward corresponding improved algorithms with specific formulas, i.e. Enhanced-MMSE-SIC, Turbo-like MPA (MPA-Turbo) and Turbo-like EPA with hybrid parallel interference cancellation (EPA-Turbo-PIC). Link-level simulation results and analysis show that the proposed improved algorithms have performance advantages over the corresponding traditional algorithms. © 2022, The Authors. All rights reserved.

关键词： Mean square error

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Design and implementation of a clock recovery circuit for fast Ethernet applications

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Chinese Journal of Systems Engineering and Electronics 2004年第4期000卷

A circuit architechure to realize clock recovery for fast Ethernet applications is presented, whick includies system architecture, modified Mueller Muller algorithm for 100BASE-TX, phase detector for 100BASE-TX and multiple output charge pump PLL. The clock recovery circuit is verified by TSMC 0.35um 1P5M CMOS process. The results show that this clock recovery circuit exactly extracts the timing information. It has advantages over others for simple and easy implementation.

关键词： clock recovery phase locked loop adaptive equalizer

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Strategy evolution on dynamic networks

arXiv

引用

arXiv 2023年

作者： Su, Qi McAvoy, Alex Plotkin, Joshua B. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Data Science and Society University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Mathematics University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Biology University of Pennsylvania PhiladelphiaPA19104 United States Center for Mathematical Biology University of Pennsylvania PhiladelphiaPA19104 United States

Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One key mechanism is the formation of altruistic spatial clusters, where neighbors of a cooperative individual are likely to reciprocate, which protects prosocial traits from exploitation. But most real-world interactions are ephemeral and subject to exogenous restructuring, so that social networks change over time. Strategic behavior on dynamic networks is difficult to study, and much less is known about the resulting evolutionary dynamics. Here, we provide an analytical treatment of cooperation on dynamic networks, allowing for arbitrary spatial and temporal heterogeneity. We show that transitions among a large class of network structures can favor the spread of cooperation, even if each individual social network would inhibit cooperation when static. Furthermore, we show that spatial heterogeneity tends to inhibit cooperation, whereas temporal heterogeneity tends to promote it. Dynamic networks can have profound effects on the evolution of prosocial traits, even when individuals have no agency over network structures. © 2023, CC BY.

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