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Advances in Intelligent Systems and Computing

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Preface

Advances in Intelligent Systems and Computing 2018年 620卷 v-vi页

作者： Omatu, Sigeru Rodríguez, Sara Villarrubia, Gabriel Faria, Pedro Sitek, Pawel Prieto, Javier Faculty of Engineering Department of Electronics Information and Communication Engineering Osaka Institute of Technology OsakaOsaka Japan Faculty of Science Department of Computer Science and Automation Control University of Salamanca Salamanca Spain GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Instituto Superior de Engenharia do Porto Porto Portugal Faculty of Electrical Engineering and Computer Science Department of Control and Management Systems Department of Information Systems Kielce University of Technology Kielce Poland

An Opponent Colour LGMD Neural Network for Collision Detection at Night with Thermal Camera

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SSRN

SSRN 2023年

作者： Zhang, Yicheng Han, Huizi Luan, Hao Hua, Mu Liu, Mei Cuayahuitl, Heriberto Yue, Shigang School of Automation Guangdong University of Petrochemical Technology 139 Guanduer Road Guangdong Maoming525000 China School of Computer Science University of Lincoln Brayford Pool LincolnLN6 7TS United Kingdom Faculty of Engineering The Hong Kong Polytechnic University 11 Yuk Choi Road 999077 Hong Kong School of Computer Science Tianjin University of Technology and Education No.1310 Dagu South Road Hexi District Tianjin300222 China School of Computing and Mathematical Sciences University of Leicester University Road LeicesterLE1 7RH United Kingdom

It is an enormous challenge for intelligent robots or vehicles to detect and avoid collisions at night because of poor light conditions. Thermal cameras capture the night scenes with temperature maps, often showing in different pseudo-colour modes to enhance the visual effects for the human eyes. Since the features of approaching objects could have been well enhanced in the pseudo colour outputs of a thermal camera, colour cues could likely help the collision detector - lobula giant movement detector (LGMD) to pick up the collision cues nicely. However, no investigation has been published on this aspect, and it is unclear whether the LGMD-like visual neural networks can take pseudo-colour information as inputs for collision detection in extremely dim conditions. In this study, we proposed a model consisting of three sub-networks, each dealing with one specific opponent colour channel, i.e., black-white, red-green, and yellow-blue. A collision alarm will be triggered if any channel’s output has exceeded its threshold for a few successive frames. Systematical experiments have been carried out to verify the proposed neural network with different thermal pseudo-colour modes in various nighttime scenarios. Our experiments demonstrated that the proposed bioinspired collision detection system works well in detecting colliding objects in direct collision courses at low light conditions quickly. The proposed method showed its potential to be part of the sensor systems for future robots or vehicles at night or in other extreme light conditions to avoid fatal collisions. © 2023, The Authors. All rights reserved.

关键词： Intelligent robots

Unsupervised Social Bot Detection via Structural Information Theory

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arXiv 2024年

作者： Peng, Hao Zhang, Jingyun Huang, Xiang Hao, Zhifeng Li, Angsheng Yu, Zhengtao Yu, Philip S. School of Cyber Science and Technology Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China State Key Laboratory of Public Big Data Guizhou University No. 2708 South Section of Huaxi Avenue Huaxi District Guizhou Province Guiyang City550025 China Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin541004 China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China College of Science University of Shantou No. 243 University Road Shantou515063 China School of Computer Science and Engineering Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China Faculty of Information Engineering and Automation Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States

Research on social bot detection plays a crucial role in maintaining the order and reliability of information dissemination while increasing trust in social interactions. The current mainstream social bot detection models rely on black-box neural network technology, e.g., Graph Neural Network, Transformer, etc., which lacks interpretability. In this work, we present UnDBot, a novel unsupervised, interpretable, yet effective and practical framework for detecting social bots. This framework is built upon structural information theory. We begin by designing three social relationship metrics that capture various aspects of social bot behaviors: Posting Type Distribution, Posting Influence, and Follow-to-follower Ratio. Three new relationships are utilized to construct a new, unified, and weighted social multi-relational graph, aiming to model the relevance of social user behaviors and discover long-distance correlations between users. Second, we introduce a novel method for optimizing heterogeneous structural entropy. This method involves the personalized aggregation of edge information from the social multi-relational graph to generate a two-dimensional encoding tree. The heterogeneous structural entropy facilitates decoding of the substantial structure of the social bots network and enables hierarchical clustering of social bots. Thirdly, a new community labeling method is presented to distinguish social bot communities by computing the user's stationary distribution, measuring user contributions to network structure, and counting the intensity of user aggregation within the community. Compared with ten representative social bot detection approaches, comprehensive experiments demonstrate the advantages of effectiveness and interpretability of UnDBot on four real social network datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Information theory

Cross-ethnicity face anti-spoofing recognition challenge: A review

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arXiv 2020年

作者： Liu, Ajian Li, Xuan Wan, Jun Liang, Yanyan Escalera, Sergio Escalante, Hugo Jair Madadi, Meysam Jin, Yi Wu, Zhuoyuan Yu, Xiaogang Tan, Zichang Yuan, Qi Yang, Ruikun Zhou, Benjia Guo, Guodong Li, Stan Z. Faculty of Information Technology Avenida WaiLong Taipa Macau China School of Computer and Information Technology Beijing Jiaotong University Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Science Beijing China Universitat de Barcelona and Computer Vision Center Barcelona Instituto Nacional de Astrofísica Óptica y Electrónica Puebla Mexico School of Software Beihang University Beijing China Institute of Deep Learning Baidu Research and National Engineering Laboratory for Deep Learning Technology and Application Beijing Westlake University Hangzhou China

Face anti-spoofing is critical to prevent face recognition systems from a security breach. The biometrics community has achieved impressive progress recently due the excellent performance of deep neural networks and the availability of large datasets. Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing. Recently, a multi-ethnic face anti-spoofing dataset, CASIA-SURF CeFA, has been released with the goal of measuring the ethnic bias. It is the largest up to date cross-ethnicity face anti-spoofing dataset covering 3 ethnicities, 3 modalities, 1;607 subjects, 2D plus 3D attack types, and the first dataset including explicit ethnic labels among the recently released datasets for face *** organized the Chalearn Face Anti-spoofing Attack Detection Challenge which consists of single-modal (e.g., RGB) and multi-modal (e.g., RGB, Depth, Infrared (IR)) tracks around this novel resource to boost research aiming to alleviate the ethnic bias. Both tracks have attracted 340 teams in the development stage, and finally 11 and 8 teams have submitted their codes in the single-modal and multi-modal face anti-spoofing recognition challenges, respectively. All the results were verified and re-ran by the organizing team, and the results were used for the final ranking. This paper presents an overview of the challenge, including its design, evaluation protocol and a summary of results. We analyze the top ranked solutions and draw conclusions derived from the competition. In addition we outline future work directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Large dataset

Joint Registration of Multiple Point Sets by Preserving Global and Local Structure

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Joint Registration of Multiple Point Sets by Preserving Glob...

International Conference on Information Fusion

作者： Hao Zhu Bin Guo Ka-Veng Yuen Henry Leung Yongfu Li Zhen Tian Department of Automation Chongqing University of Posts and Telecommunications Chongqing P. R. China Faculty of Science and Technology University of Macau Macao P. R. China Department of Electrical and Computer Engineering University of Calgary Calgary Alberta Canada

In previous work on joint multiple point sets registration, the multiple point sets are often formulated by a Gaussian mixture model (GMM) and the registration is then cast to a clustering problem, which aims to exploit global relationships on the multiple point sets. However, local relationships on the multiple point sets are ignored in the state-of-the-art joint multiple point sets registration techniques. In this paper, the multiple point sets are assumed to be generated from a GMM. Local features of the multiple point sets, such as shape context, are proposed to infer the membership probabilities of the GMM. The problem of joint multiple point sets registration can be performed by maximum likelihood of the GMM. The parameters of GMM and registration are estimated by an expectation maximization algorithm. Comprehensive experiments demonstrate that our proposed method has better performance than the state-of-the-art methods.

关键词： Multiple point sets registration Local features Gaussian mixture model Expectation maximization

Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

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ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

Advances in Intelligent Systems and Computing

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Preface

Advances in Intelligent Systems and Computing 2020年 1241 AISC卷 v-vi页

作者： Vittorini, Pierpaolo Di Mascio, Tania Tarantino, Laura Temperini, Marco Gennari, Rosella De la Prieta, Fernando Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

Magnetic connectivity between the light bridge and penumbra in a sunspot

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arXiv 2020年

作者： Feng, Song Miao, Yuhu Yuan, Ding Qu, Zhongquan Nakariakov, Valery M. Yunnan Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Astronomical Observatory Chinese Academy of Sciences PO Box 110 Kunming650011 China Institute of Space Science and Applied Technology Harbin Institute of Technology Shenzhen Guangdong518055 China Centre for Fusion Space and Astrophysics Department of Physics University of Warwick CV4 7AL United Kingdom St Petersburg Branch Special Astrophysical Observatory Russian Academy of Sciences St Petersburg196140 Russia

A light bridge is a prominent structure commonly observed within a sunspot. Its presence usually triggers a wealth of dynamics in a sunspot, and has a lasting impact on sunspot evolution. However, the fundamental structure of light bridges is still not well understood. In this study, we used the high-resolution spectropolarimetry data obtained by the Solar Optical Telescope onboard the Hinode satellite to analyze the magnetic and thermal structure of a light bridge at AR 12838. We also combined the high-cadence 1700 Å channel data provided by the Atmospheric Imaging Assembly onboard the Solar Dynamic Observatory to study the dynamics on this bridge. We found that a pair of blue and red Doppler shift patches at two ends of this bridge, this pattern appears to be the convective motion directed by the horizontal component of the magnetic field aligned with the spine of this bridge. Paired upward and downward motions implies that the light bridge could have a two-legged or undulate magnetic field. Significant four minute oscillations in the emission intensity of the 1700 Å bandpass were detected at two ends, which had overlap with the paired blue and red shift patches. The oscillatory signals at the light bridge and the penumbra were highly correlated with each other. Although they are separated in space at the photosphere, the periodicity seems to have a common origin from the underneath. Therefore, we infer that the light bridge and penumbra could share a common magnetic source and become fragmented at the photosphere by magneto-convection. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetohydrodynamics

Preflare very long-periodic pulsations observed in Hα emission before the onset of a solar flare

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arXiv 2020年

作者： Li, Dong Feng, Song Su, Wei Huang, Yu Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory CAS Nanjing210033 China State Key Laboratory of Space Weather Chinese Academy of Sciences Beijing100190 China CAS Key Laboratory of Solar Activity National Astronomical Observatories Beijing100101 China Yunnan Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China MOE Key Laboratory of Fundamental Physical Quantities Measurements School of Physics Huazhong University of Science and Technology Wuhan430074 China

Context. Very long-periodic pulsations during preflare phases (preflare-VLPs) have been detected in the full-disk solar soft X-Ray (SXR) flux (see Tan et al. 2016). They may be regarded as precursors to solar flares and may help us better understand the trigger mechanism of solar flares. Aims. In this letter, we report a preflare-VLP event prior to the onset of an M1.1 circular-ribbon flare on 2015 October 16. It was simultaneously observed in Hα, SXR, and extreme ultraviolet (EUV) wavelengths. Methods. The SXR fluxes in 1−8 Å and 1−70 Å were recorded by the Geostationary Operational Environmental Satellite (GOES) and Extreme Ultraviolet Variability Experiment (EVE), respectively;the light curves in Hα and EUV 211 Å were integrated over a small local region, which were measured by the 1m New Vacuum Solar Telescope (NVST) and the Atmospheric Imaging Assembly (AIA), respectively. The preflare-VLP is identified as the repeat and quasi-periodic pulses in light curves during preflare phase. The quasi-periodicity can be determined from the Fourier power spectrum with Markov chain Monte Carlo (MCMC)-based Bayesian (e.g., Liang et al. 2020). Results. Seven well-developed pulses are found before the onset of an M1.1 circular-ribbon flare. They are firstly seen in the local light curve in Hα emission and then discovered in full-disk SXR fluxes in GOES 1−8 Å and ESP 1−70 Å, as well as the local light curve in AIA 211 Å. These well-developed pulses can be regarded as the preflare-VLP, which might be modulated by LRC-circuit oscillation in the current-carrying plasma loop. The quasi-period is estimated to be ∼9.3 minutes. Conclusions. We present the first report of a preflare-VLP event in the local Hα line and EUV wavelength, which could be considered a precursor of a solar flare. This finding should therefore prove useful for the prediction of solar flares, especially for powerful flares. Copyright © 2020, The Authors. All rights reserved.

关键词： Gamma rays