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Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks

Physical Review Applied 2024年第2期22卷 024063页

作者： Henri Tertilt Jonas Mensing Marlon Becker Wilfred G. van der Wiel Peter A. Bobbert Andreas Heuer Institute for Physical Chemistry Department of Physics NanoElectronics Group Faculty of Electrical Engineering Mathematics and Computer Science MESA+ Institute for Nanotechnology and Center for Brain-Inspired Nano Systems (BRAINS) Department of Applied Physics Center for Computational Energy Research (CCER)

Nonlinear behavior in the hopping transport of interacting charges enables reconfigurable logic in disordered dopant network devices, where voltages applied at control electrodes tune the relation between voltages applied at input electrodes and the current measured at an output electrode. From kinetic Monte Carlo simulations we analyze the critical nonlinear aspects of variable-range hopping transport for realizing Boolean logic gates in these devices on three levels. First, we quantify the occurrence of individual gates for random choices of control voltages. We find that linearly inseparable gates such as the xor gate are less likely to occur than linearly separable gates such as the and gate, despite the fact that the number of different regions in the multidimensional control voltage space for which and or xor gates occur is comparable. Second, we use principal-component analysis to characterize the distribution of the output current vectors for the (00,10,01,11) logic input combinations in terms of eigenvectors and eigenvalues of the output covariance matrix. This allows a simple and direct comparison of the behavior of different simulated devices and a comparison to experimental devices. Third, we quantify the nonlinearity in the distribution of the output current vectors necessary for realizing Boolean functionality by introducing three nonlinearity indicators. The analysis provides a physical interpretation of the effects of changing the hopping distance and temperature and is used in a comparison with data generated by a deep neural network trained on a physical device.

关键词： Carrier dynamics Dynamics of networks electrical conductivity Fitness Hopping transport Network optimization Optimization problems Temperature

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Robust Optimal Higher-order-observer-based Dynamic Sliding Mode Control for VTOL Unmanned Aerial Vehicles

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International Journal of Automation and computing 2021年第5期18卷 802-813页

作者： Yashar Mousavi Amin Zarei Arash Mousavi Mohsen Biari Department of Applied Science School of ComputingEngineering and Built EnvironmentGlasgow Caledonian UniversityGlasgow G4 OBAUK Department of Electrical and Computer Engineering University of Sistan and BaluchestanZahedan ***Iran Department Electrical Engineering and Applied Sciences Paradise Research CenterJahrom ***Iran Faculty of Electrical and Robotic Engineering Shahrood University of TechnologyShahrood ***Iran

This paper investigates the precise trajectory tracking of unmanned aerial vehicles(UAV) capable of vertical take-off and landing(VTOL) subjected to external disturbances. For this reason, a robust higher-order-observer-based dynamic sliding mode controller(HOB-DSMC) is developed and optimized using the fractional-order firefly algorithm(FOFA). In the proposed scheme, the sliding surface is defined as a function of output variables, and the higher-order observer is utilized to estimate the unmeasured variables,which effectively alleviate the undesirable effects of the chattering phenomenon. A neighboring point close to the sliding surface is considered, and as the tracking error approaches this point, the second control is activated to reduce the control input. The stability analysis of the closed-loop system is studied based on Lyapunov stability theorem. For a better study of the proposed scheme, various trajectory tracking tests are provided, where accurate tracking and strong robustness can be simultaneously ensured. Comparative simulation results validate the proposed control strategy′s effectiveness and its superiorities over conventional sliding mode controller(SMC) and integral SMC approaches.

关键词： Unmanned aerial vehicle dynamic sliding mode trajectory tracking fractional firefly algorithm vertical take-off and landing system

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Lightning flash started near the electron acceleration region in the thundercloud 38

Lightning flash started near the electron acceleration regio...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Tsurumi, Miwa Enoto, Teruaki Ikkatai, Yuko Wu, Ting Wang, Daohong Shinoda, Taro Nakazawa, Kazuhiro Tsuji, Noki Gabriel, Diniz Kaoataoka, Jun Iwashita, Ryoji Koshikawa, Nanase Kamogawa, Masashi Takagaki, Toru Miyake, Shoko Tomioka, Dai Morimoto, Takeshi Nakamura, Yoshitaka Tsuchiya, Harufumi Department of Physics Graduate School of Science Kyoto University Kyoto Japan Graduate School of Science and Engineering Aoyama Gakuin University Kanagawa Japan Extreme Natural Phenomena RIKEN Hakubi Research Team Cluster of Pioneering Research RIKEN Saitama Japan Institute of Human and Social Sciences Kanazawa University Ishikawa Japan Department of Electrical Electronic and Computer Engineering Gifu University Gifu Japan Institute for Space-Earth Environmental Research Nagoya University Aichi Japan Kobayashi-Maskawa Institute for the Origin of Particles and the Universe Nagoya University Aichi Japan Faculty of Science and Engineering Waseda University Tokyo Japan Global Center for Asian and Regional Research University of Shizuoka Shizuoka Japan TAC Inc. Kyoto Japan Ibaraki College Ibaraki Japan Faculty of Science and Engineering Kindai University Osaka Japan Department of Electrical Engineering Kobe City College of Technology Hyogo Japan Nuclear Science and Engineering Center Japan Atomic Energy Agency Ibaraki Japan

The interaction between cosmic rays and thunderclouds has attracted much attention in recent years. Cosmic rays have been considered as one possible cause of the trigger of lightning flashes: e.g., a possible correlation between the number of observed lightning and cosmic ray flux (e.g.,Themis G. Chronis, journal of Climate,2009). In thunderclouds, electric fields are thought to cause relativistic acceleration of electrons as an interaction with cosmic ray air shower and emit bremsstrahlung photons, known as gamma-ray glows. One unresolved is that such electron acceleration, and thus gamma-ray glows, may be related to initiating lightning flashes. To verify this hypothesis, we conducted winter thundercloud observations using mapping radiation measurements in Japan. At 04:06–04:08 JST on December 30, 2021, five radiation detectors recorded a gamma-ray glow, terminated with the lightning flash recorded by two lightning mapping systems (FALMA and DALMA). Our multi-location observation revealed that the gamma-ray glow region had a horizontal size of about 2 km×2.5 km. The XRAIN radar observation showed that the high reflectivity area, presumably corresponding to the electron acceleration region, reaches more than 2 km above the gamma-ray detected radiation detectors. The initiation of this lightning discharge started from 1.6 km altitude from the ground around the gamma-ray glow region [1]. This result indicates that the lightning flash began in the vicinity of the electric field region and a possible connection between the cosmic ray interaction with the electric fields in thundercloud and the triggering of the lightning flash. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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Ferromagnetism triggered by band tripling in ruthenate Sr4Ru3O10

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Physical Review B 2024年第15期110卷 155134页

作者： N. Watanabe S. Souma K. Nakayama K. Yamauchi J. F. Ribeiro Y. Wang Miho Kitamura Koji Horiba Hiroshi Kumigashira T. Oguchi Z. Q. Mao Y. P. Chen T. Sato Department of Physics Graduate School of Science Advanced Institute for Materials Research (WPI-AIMR) Center for Science and Innovation in Spintronics (CSIS) Precursory Research for Embryonic Science and Technology (PRESTO) Center for Spintronics Research Network (CSRN) School of Electrical and Computer Engineering and Birck Nanotechnology Center Department of Physics Institute of Materials Structure Science (QST) Sendai 980-8579 Japan Institute of Multidisciplinary Research for Advanced Materials (IMRAM) Department of Physics and Astronomy and Purdue Quantum Science and Engineering Institute International Center for Synchrotron Radiation Innovation Smart (SRIS) Mathematical Science Center for Co-creative Society (MathCCS)

Itinerant ferromagnetism is understood in terms of a quasiparticle picture with renormalized many-body effects. While the ferromagnetic ground state is destabilized by thermal and quantum fluctuations leading to exotic states such as unconventional superconductivity, how the quasiparticles evolve across the ferromagnetic transition is a target of intensive debate. Here, we present a type of ferromagnetic transition that is accompanied by a drastic reconstruction of quasiparticle spectrum in a layered ferromagnetic ruthenate, Sr4Ru3O10. Angle-resolved photoemission spectroscopy uncovered that the three-dimensional coherent states below the ferromagnetic transition temperature (TC) turn into two-dimensional incoherent electronic states slightly above TC characterized by the disappearance of trilayer band splitting, ferromagnetic exchange splitting, and long-lived quasiparticles. Our findings suggest that the electronic coherence strongly modifies the fermiology and magnetic order, pointing to an intriguing coupling between quasiparticles and magnetic properties.

关键词： Electronic structure Fermi surface Ferromagnetism Quasiparticles & collective excitations van Hove singularity Ruddlesden-Popper compounds Angle-resolved photoemission spectroscopy Density functional theory First-principles calculations

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Dynamic and Distributed Optimization for the Allocation of Aerial Swarm Vehicles

Dynamic and Distributed Optimization for the Allocation of A...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Jason Hughes Dominic Larkin Charles O’ Donnell Christopher Korpela Department of Electrical Engineering and Computer Science Robotics Research Center United States Military Academy West Point NY USA

ISBN: (数字)9781665405935

ISBN: (纸本)9781665405942

Optimal transport (OT) is a framework that can guide the design of efficient resource allocation strategies in a network of multiple sources and targets. This paper applies discrete OT to a swarm of UAVs in a novel way to achieve appropriate task allocation and execution. Drone swarm deployments already operate in multiple domains where sensors are used to gain knowledge of an environment [1]. Use cases such as, chemical and radiation detection, and thermal and RGB imaging create a specific need for an algorithm that considers parameters on both the UAV and waypoint side and allows for updating the matching scheme as the swarm gains information from the environment. Additionally, the need for a centralized planner can be removed by using a distributed algorithm that can dynamically update based on changes in the swarm network or parameters. To this end, we develop a dynamic and distributed OT algorithm that matches a UAV to the optimal waypoint based on one parameter at the UAV and another parameter at the waypoint. We show the convergence and allocation of the algorithm through a case study and test the algorithm’s effectiveness against a greedy assignment algorithm in simulation.

关键词： Heuristic algorithms Radiation detectors Imaging Autonomous aerial vehicles Dynamic scheduling Sensors Resource management

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Real-time Architecture for Audio-Visual Active Speaker Detection

Real-time Architecture for Audio-Visual Active Speaker Detec...

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IEEE International Conference on robotics and Biomimetics

作者： Min Huang Wen Wang Zheyuan Lin Fiseha B. Tesema Shanshan Ji Jason Gu Minhong Wan Wei Song Te Li Shiqiang Zhu Intelligent Robotics Research Center Zhejiang Lab and Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical And Computer Engineering Dalhousie University Canada

ISBN: (纸本)9781665481106

Continuously measuring the speaking state of users with robot in a human-robot Interaction(HRI) system improves metrics of interaction quality. Meanwhile, mainstream active speaker detection (ASD) algorithms emphasize achieving high AUCs at frame level in the AVA-Active Speaker dataset and pay less attention to get real-time performance in robotic systems. In this paper, we propose a model named FSDNet to keep a high AUC score in the AVA-Active Speaker dataset while reducing time cost, our model increase AUC score by 0.1% compared with the State-Of-The-Art and need only 75% running time. Furthermore, we put forward an architecture with a time-related prediction function to make our algorithm more effective and generative in interactive robotic systems. The code is released at https://***/huangmin9966/FSDNet_RealTimeArch.

关键词： Measurement Visualization Costs Codes Biological system modeling Transformers Feature extraction

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Knowledge-Infused Learning for Fine-Grained Plant Disease Recognition

Knowledge-Infused Learning for Fine-Grained Plant Disease Re...

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IEEE International Conference on Image Processing

作者： Jamil Ahmad Wail Gueaieb Abdulmotaleb El Saddik Giulia De Masi Fakhri Karray Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi UAE School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada Autonomous Robotics Research Center Technology Innovation Institute Abu Dhabi UAE School of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Domain knowledge exists in various forms, including text, ontologies, graphs, images, audio, and videos. In plant disease detection, most works solely utilize images with disease labels, neglecting textual descriptions of visual disease symptoms used by human experts for diagnosis. These text descriptions and sample images aid expert identification of visual symptoms. We propose a novel method that leverages text descriptions and image data by modeling domain-specific knowledge about visual symptoms in leaf images as separate feature channels. Each channel corresponds to specific features whose absence or presence in the image influences model predictions. We introduce a channel attention-guided fusion module for weighting each channel based on the input and corresponding output. The combined feature channels are transformed into a standardized 3-channel input format, which can then be processed by any pre-trained convolutional neural network (CNN) as input for feature extraction and subsequent classification. Furthermore, intermediate activations of the channel attention layer combined with the weights from the fusion layer make model predictions explainable. Experimental results on three publicly available datasets of apple and cucumber leaf diseases demonstrate improvements of up to 5% utilizing various state-of-the-art CNN architectures, indicating the efficacy of incorporating textual disease descriptions using the proposed approach.

关键词： Training Visualization Plant diseases Predictive models Feature extraction Data models Robustness

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Brain-inspired artificial intelligence research: A review

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science China(Technological sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia Information Processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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TGRMPT: A Head-Shoulder Aided Multi-Person Tracker and a New Large-Scale Dataset for Tour-Guide Robot

TGRMPT: A Head-Shoulder Aided Multi-Person Tracker and a New...

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IEEE International Conference on robotics and Biomimetics

作者： Wen Wang Zheyuan Lin Min Huang Shunda Hu Tianlei Jin Te Li Minhong Wan Jason Gu Shiqiang Zhu Research Center for Intelligent Robotics Zhejiang Lab and Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Canada

ISBN: (纸本)9781665481106

A service robot serving safely and politely needs to track the surrounding people robustly, especially for Tour-Guide Robot (TGR). However, existing multi-object tracking (MOT) or multi-person tracking (MPT) methods are not applicable to TGR for the following reasons: 1. lacking relevant large-scale datasets; 2. lacking applicable metrics to evaluate trackers. In this work, we target the visual perceptual tasks for TGR and present the TGRDB dataset, a novel large-scale multi-person tracking dataset containing roughly 5.6 hours of annotated videos and over 450 long-term trajectories. Besides, we propose a more applicable metric to evaluate trackers using our dataset. As part of our work, we present TGRMPT, a novel MPT system that incorporates information from head shoulder and whole body, and achieves state-of-the-art performance. We have released our codes and dataset in https://***/wenwenzju/TGRMPT.

关键词： Measurement Visualization Target tracking Codes Service robots Biomimetics Trajectory

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