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High throughput event filtering: The interpolation-based DIF algorithm hardware architecture

Microprocessors and Microsystems 2025年

作者： Marcin Kowalczyk Tomasz Kryjak Embedded Vision Systems Group Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Krakow Poland

In recent years, there has been rapid development in the field of event vision. It manifests itself both on the technical side, as better and better event sensors are available, and on the algorithmic side, as more and more applications of this technology are proposed and scientific papers are published. However, the data stream from these sensors typically contains a significant amount of noise, which varies depending on factors such as the degree of illumination in the observed scene or the temperature of the sensor. We propose a hardware architecture of the Distance-based Interpolation with Frequency Weights(DIF) filter and implement it on an FPGA chip. To evaluate the algorithm and compare it with other solutions, we have prepared a new high-resolution event dataset, which we are also releasing to the community. Our architecture achieved a throughput of 403.39 million events per second (MEPS) for a sensor resolution of 1280 × 720 and 428.45 MEPS for a resolution of 640 × 480. The averagevalues of the Area Under the Receiver Operating Characteristic (AUROC) index ranged from 0.844 to 0.999, depending on the dataset, which is comparable to the state-of-the-art filtering solutions, but with much higher throughput and better operation over a wide range of noise levels.

关键词： Dataset Denoising DVS FPGA High-throughput

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Distributed No-Regret Learning for Stochastic Aggregative Games over Networks

Distributed No-Regret Learning for Stochastic Aggregative Ga...

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第40届中国控制会议

作者： Jinlong Lei Peng Yi Li Li The Department of Control Science and Engineering Tongji University The Institute for Advanced Study Tongji University Shanghai Research Institute for Intelligent Autonomous Systems

In this work, we propose a distributed no-regret learning for stochastic aggregative games over time-varying *** consider a finite set of players repeatedly playing the network aggregative game in stochastic regimes, where each player has an expectation-valued objective function depending on its own strategy and the aggregate of all player strategies, and the players can estimate gradients of their objective functions up to a zero-mean error with bounded variance. We consider the scenario in which players cannot directly obtain the aggregate value, but they are able to share their estimates of the aggregate with their neighbors without disclosing their own strategies. We design a distributed learning algorithm based on the mirror descent and dynamical averaging tracking. We then provide analysis for both the variational regret and the cost r√egret for aggregative games These analyses indicate the key correlations between the regret bounds, the network connectivity, and game structures, etc. In addition, we validate the almost sure convergence to the Nash equilibrium for the class of strictly monotone games. Finally, we present preliminary numerics by applying the proposed scheme to the Nash-Cournot competition problem.

关键词： Network Aggregative Games Distributed Learning No-regret Learning Mirror Descent

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Correction to: Enhanced critical current density of ex situ MgB2 via control of Mg assisted sintering

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Journal of Materials science: Materials in Electronics 2022年第14期33卷 11269-11270页

作者： Hapipi, Nurhidayah Mohd Chen, Soo Kien Shaari, Abdul Halim Kechik, Mohd Mustafa Awang Lim, Kean Pah Tan, Kar Ban Lee, Oon Jew Arvapalli, Sai Srikanth Miryala, Muralidhar Department of Physics Faculty of Science Universiti Putra Malaysia Serdang Malaysia Institute of Advanced Technology Universiti Putra Malaysia Serdang Malaysia Department of Chemistry Faculty of Science Universiti Putra Malaysia Serdang Malaysia Faculty of Science and Marine Environment Universiti Malaysia Terengganu Kuala Nerus Malaysia Graduate School of Science and Engineering Regional Environment Systems Superconducting Research Laboratory (SRL) Shibaura Institute of Technology Tokyo Japan

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POLYNOMIAL DECELERATION FOR A SYSTEM OF CUBIC NONLINEAR SCHRÖDINGER EQUATIONS IN ONE SPACE DIMENSION

arXiv

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arXiv 2022年

作者： Kita, Naoyasu Masaki, Satoshi Segata, Jun-Ichi Uriya, Kota Faculty of Advanced Science and Technology Kumamoto University Kumamoto860-8555 Japan Department of Systems Innovation Graduate School of Engineering Science Osaka University Osaka Toyonaka560-8531 Japan Faculty of Mathematics Kyushu University Fukuoka819-0395 Japan Department of Applied Mathematics Faculty of Science Okayama University of Science Okayama700-0005 Japan

In this paper, we consider the initial value problem of a specific system of cubic nonlinear Schrödinger equations. Our aim of this research is to specify the asymptotic profile of the solution in L∞ as t → ∞. It is then revealed that the solution decays slower than a linear solution does. Further, the difference of the decay rate is a polynomial order. This deceleration of the decay is due to an amplification effect by the nonlinearity. This nonlinear amplification phenomena was previously known for several specific systems, however the deceleration of the decay in these results was by a logarithmic order. As far as we know, the system studied in this paper is the first model in that the deceleration in a polynomial order is *** Codes 35Q55, 35A22, 35B40. Copyright © 2022, The Authors. All rights reserved.

关键词： Initial value problems

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Solving the multiplication problem of a large language model system using a graph-based method

arXiv

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arXiv 2023年

作者： Tuncer, Turker Dogan, Sengul Baygin, Mehmet Barua, Prabal Datta Hafeez-Baig, Abdul Tan, Ru-San Chakraborty, Subrata Acharya, U. Rajendra Department of Digital Forensics Engineering Technology Faculty Firat University Elazig Turkey Department of Computer Engineering Faculty of Engineering and Architecture Erzurum Technical University Erzurum Turkey University of Southern Queensland Australia School of Management and Enterprise University of Southern Queensland ToowoombaQLD Australia Department of Cardiology National Heart Centre Singapore Singapore169609 Singapore Duke-NUS Medical School Singapore169857 Singapore School of Science and Technology Faculty of Science Agriculture Business and Law University of New England ArmidaleNSW2351 Australia Center for Advanced Modelling and Geospatial Information Systems Faculty of Engineering and IT University of Technology Sydney SydneyNSW2007 Australia School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia

The generative pre-trained transformer (GPT)-based chatbot software ChatGPT possesses excellent natural language processing capabilities but is inadequate for solving arithmetic problems, especially multiplication. Its GPT structure uses a computational graph for multiplication, which has limited accuracy beyond simple multiplication operations. We developed a graph-based multiplication algorithm that emulated human-like numerical operations by incorporating a ×10k operator, where k represents the maximum power to base 10 of the larger of two input numbers. Our proposed algorithm attained 100% accuracy for 1,000,000 large number multiplication tasks, effectively solving the multiplication challenge of GPT-based and other large language models. Our work highlights the importance of blending simple human insights into the design of artificial intelligence algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Blending

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Three-dimensional tracking and height verification of polystyrene particles with piezo actuator positioning by means of multi-wavelength evanescent fields 20

Three-dimensional tracking and height verification of polyst...

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20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Permpatdechakul, Thitipat Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9780995775176

To understand the nanoparticle motion behaviours on a surface, we have studied to investigate the three-dimension tracking of an individual nanoparticle with nanometre localisation accuracy. In three-dimensional nanoparticle moving position, the X and Y coordinates are on the parallel plane to the surface, which their coordinates can be tracked in general microscopy. However, the Z coordinate is the nanoparticle height position perpendicularly to the surface plane, which could not be generally tracked without longitudinal scanning method. In this paper, the polystyrene 100 nm standard particles were used to investigate the three-dimensional tracking. The individual standard nanoparticles were fixed on the tip, which was vertically travelled with the piezo actuator for movement control on the third dimension to verify the actual height Z. Our developed optical microscopy apparatus has been applying multi-wavelength evanescent fields, and obtaining multi scattering light intensities from the observed nanoparticles near to surface. Commonly, the X and Y coordinates of nanoparticle were determined by the centre of mass of each scattering light intensity. The height Z was investigated from the integration of the detected scattering intensities of each wavelength. By using our method, the height Z uncertainty could be measured approximately less than ±20 nm, and the penetration height measurability was approximately 250 nm far from the reference surface. Consequently, we could three-dimensionally track the individual standard nanoparticle in recording speed higher than 50 frames per second. Copyright © Proceedings of the 20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020. All rights reserved.

关键词： Nanoparticles

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Active Wildfires Detection and Dynamic Escape Routes Planning for Humans Through Information Fusion between Drones and Satellites

Active Wildfires Detection and Dynamic Escape Routes Plannin...

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International Conference on Intelligent Transportation

作者： Chang Liu Tamas Sziranyi Department of Networked Systems and Services Budapest University of Technology and Economics Müegyetem rkp. 3 H-1111 Budapest Hungary and Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest Hungary Faculty of Transportation Engineering and Vehicle Engineering Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest University of Technology and Economics (BME-KJK) Müegyetem rkp. 3 H-1111 Budapest Hungary Budapest Hungary

UAVs are playing an increasingly important role in the field of wilderness rescue by virtue of their flexibility. This paper proposes a fusion of UAV vision technology and satellite image analysis technology for active wildfires detection and road networks extraction of wildfire areas and real-time dynamic escape route planning for people in distress. Firstly, the fire source location and the segmentation of smoke and flames are targeted based on Sentinel 2 satellite imagery. Secondly, the road segmentation and the road condition assessment are performed by D-linkNet and NDVI values in the central area of the fire source by UAV. Finally, the dynamic optimal route planning for humans in real time is performed by the weighted A* algorithm in the road network with the dynamic fire spread model. Taking the Chongqing wildfire on August 24, 2022, as a case study, the results demonstrate that the dynamic escape route planning algorithm can provide an optimal real-time navigation path for humans in the presence of fire through the information fusion of UAVs and satellites.

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Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage

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Plant Phenomics 2023年第2期5卷 226-238页

作者： Yinglun Li Xiaohai Zhan Shouyang Liu Hao Lu Ruibo Jiang Wei Guo Scott Chapman Yufeng Ge Benoit de Solan Yanfeng Ding Frédéric Baret Plant Phenomics Research Centre Academy for Advanced Interdisciplinary StudiesJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjingChina Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan School of Agriculture and Food Sciences The University of QueenslandSt.LuciaQueensland 4072Australia Department of Biological Systems Engineering University of Nebraska-LincolnLincolnNebraska 68583United States INRAE Avignon UniversitéUMR EMMAHUMT CAPTE228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France ARVALIS Institut du Végétal 3 Rue Joseph et Marie Hackin75116 ParisFrance

The number of leaves at a given time is important to characterize plant growth and *** this work,we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB *** digital plant phenotyping platform was used to simulate a large and diverse dataset of RGB images and corresponding leaf tip labels of wheat plants at seedling stages(150,000 images with over 2 million labels).The realism of the images was then improved using domain adaptation methods before training deep learning *** results demonstrate the efficiency of the proposed method evaluated on a diverse test dataset,collecting measurements from 5 countries obtained under different environments,growth stages,and lighting conditions with different cameras(450 images with over 2,162 labels).Among the 6 combinations of deep learning models and domain adaptation techniques,the Faster-RCNN model with cycle-consistent generative adversarial network adaptation technique provided the best performance(R^(2)=0.94,root mean square error=8.7).Complementary studies show that it is essential to simulate images with sufficient realism(background,leaf texture,and lighting conditions)before applying domain adaptation ***,the spatial resolution should be better than 0.6 mm per pixel to identify leaf *** method is claimed to be self-supervised since no manual labeling is required for model *** self-supervised phenotyping approach developed here offers great potential for addressing a wide range of plant phenotyping *** trained networks are available at https://***/YinglunLi/Wheat-leaf-tip-detection.

关键词： Wheat seedling Plant

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Localization of Chiral Edge States by the Non-Hermitian Skin Effect

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Physical Review Letters 2024年第11期132卷 113802-113802页

作者： Gui-Geng Liu (刘癸庚) Subhaskar Mandal Peiheng Zhou Xiang Xi Rimi Banerjee Yuan-Hang Hu Minggui Wei Maoren Wang Qiang Wang Zhen Gao Hongsheng Chen Yihao Yang Yidong Chong Baile Zhang Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore 637371 Singapore National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu 610054 China School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan 523808 China School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing Jiangsu 210093 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen 518055 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang ZJU-UIUC Institute Zhejiang University Hangzhou 310027 China Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore

Quantum Hall systems host chiral edge states extending along the one-dimensional boundary of any two-dimensional sample. In solid state materials, the edge states serve as perfectly robust transport channels that produce a quantized Hall conductance; due to their chirality, and the topological protection by the Chern number of the bulk band structure, they cannot be spatially localized by defects or disorder. Here, we show experimentally that the chiral edge states of a lossy quantum Hall system can be localized. In a gyromagnetic photonic crystal exhibiting the quantum Hall topological phase, an appropriately structured loss configuration imparts the edge states’ complex energy spectrum with a feature known as point-gap winding. This intrinsically non-Hermitian topological invariant is distinct from the Chern number invariant of the bulk (which remains intact) and induces mode localization via the “non-Hermitian skin effect.” The interplay of the two topological phenomena—the Chern number and point-gap winding—gives rise to a non-Hermitian generalization of the paradigmatic Chern-type bulk-boundary correspondence principle. Compared to previous realizations of the non-Hermitian skin effect, the skin modes in this system have superior robustness against local defects and disorders.

关键词： Edge states Photonic crystals Quantum Hall effect Chern insulators Non-Hermitian systems

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