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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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DoS-Aware Quantized Control of Nonlinear systems via Linearization ⁎

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IFAC-PapersOnLine 2020年第2期53卷 3054-3059页

作者： Rui Kato Ahmet Cetinkaya Hideaki Ishii Department of Computer Science Tokyo Institute of Technology Yokohama 226-8502 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo 101-8430 Japan

This paper deals with a quantized feedback stabilization problem of nonlinear networked control systems via linearization. In particular, we study circumstances where the communication channel is interrupted by Denial-of-Service (DoS) attacks and its data rate is limited. We employ a deterministic DoS attack model which constraints the amount of attacks only by their frequency and duration, allowing us to capture a large class of potential attacks. To achieve asymptotic stabilization, we propose a resilient dynamic quantizer in the sense that it does not saturate in the presence of packet losses caused by DoS attacks. A sufficient condition for stability is derived by restricting the average frequency and duration of attacks. Since our result only guarantees local stability, we explicitly investigate an estimate of the region of attraction, which may be reduced by attacks. A simulation example is presented for demonstration of our results.

关键词： DoS attacks quantized control nonlinear systems stability analysis linearization

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Pressure induced transition from chiral charge order to time-reversal symmetry-breaking superconducting state in Nb-doped CsV3Sb5

arXiv

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arXiv 2024年

作者： Graham, J.N. Islam, S.S. Sazgari, V. Li, Y. Deng, H. Janka, G. Zhong, Y. Gerguri, O. Král, P. Doll, A. Bialo, I. Chang, J. Salman, Z. Suter, A. Prokscha, T. Yao, Y. Okazaki, K. Luetkens, H. Khasanov, R. Wang, Z. Yin, J.-X. Guguchia, Z. PSI Center for Neutron and Muon Sciences CNM Villigen5232 Switzerland Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement Ministry of Education School of Physics Beijing Institute of Technology Beijing100081 China Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems Beijing Institute of Technology Beijing100081 China Department of Physics Southern University of Science and Technology Guangdong Shenzhen518055 China Institute for Solid States Physics The University of Tokyo Kashiwa Japan Physik-Institut Universität Zürich Winterthurerstrasse 190 ZürichCH-8057 Switzerland AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków30-059 Poland International Center for Quantum Materials Beijing Institute of Technology Zhuhai319000 China Trans-scale Quantum Science Institute The University of Tokyo Tokyo Japan Material Innovation Research Center The University of Tokyo Kashiwa Japan

The experimental realisation of unconventional superconductivity and charge order in kagome systems AV3Sb5 is of critical importance. We conducted a highly systematic study of Cs(V1−xNbx)3Sb5 with x=0.07 (Nb0.07-CVS) by employing a unique combination of tuning parameters such as doping, hydrostatic pressure, magnetic fields, and depth, using muon spin rotation, AC susceptibility, and STM. We uncovered tunable magnetism in the normal state of Nb0.07-CVS, which transitions to a time-reversal symmetry (TRS) breaking superconducting state under pressure. Specifically, our findings reveal that the bulk of Nb0.07-CVS (at depths >20 nm from the surface) experiences TRS breaking below T∗ = 40 K, lower than the charge order onset temperature, TCO = 58 K. However, near the surface ( © 2024, CC BY.

关键词： Magnetic susceptibility

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Multi-Objective Squirrel Search Algorithm for EEG Feature Selection

SSRN

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SSRN 2022年

作者： Wang, Chao Li, Songjie Shi, Miao Zhao, Jie Acharya, U. Rajendra Xie, Neng-Gang Cheong, Kang Hao College of Civil Engineering and Architecture Anhui Polytechnic University Anhui Wuhu241000 China Anhui Province Key Laboratory of Multidisciplinary Management and Control of Complex Systems Anhui Ma’anshan 243002 China Department of Management science and Engineering Anhui University of Technology Anhui Maanshan243002 China 8 Somapah Road Singapore487372 Singapore Department of Mechanical Engineering Anhui University of Technology Maanshan243002 China Department of Electronics and Computer Engineering Ngee Ann Polytechnic S599489 Singapore Department of Biomedical Engineering School of Science and Technology SUSS University Singapore Department of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

Feature selection plays a critical role in the application of Brain computer Interface (BCI) systems. Many methods have been used to solve the feature selection problem, but they model it as a single-objective problem, considering only classification accuracy or number of features. To close this critical gap, we improve the squirrel search algorithm by combining it with the grid method, and propose a Multi-Objective Squirrel Search Algorithm (MOSSA) to solve the feature selection problem in BCI. We conduct experiments on three publicly available motion imagery datasets, and the experimental results reveal the best classification results of the method on dataset 1. The average classification accuracy of dataset 2 is 96.71%, with the number of selected features reduced to 18 on average. The highest classification accuracy of dataset 3 is 83.57% on the training set and 82.86% on the test set. In addition, we compare MOSSA with other algorithms and the results show the superiority of our proposed method in solving the feature selection problem. Finally, we combine MOSSA with an online application of BCI, where subjects visualise controlling the robot to perform the corresponding actions by the left and right hand movements. The average recognition rate of the three subjects is approximately 70%. In summary, the MOSSA is an effective method for solving the feature selection problem and is useful for the development of online © 2022, The Authors. All rights reserved.

关键词： Brain computer interface

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Using the Model of a Functional Rationalizer of Consumer Behavior in Recommendation systems for Managing the Transport Activity of the Urban Population 23

Using the Model of a Functional Rationalizer of Consumer Beh...

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23rd International Conference on Soft Computing and Measurements, SCM 2020

作者： Seliverstov, Yaroslav A. Seliverstov, Svytoslav A. Podoprigora, Nikolay V. Starichenkov, Alexey L. Naryshkin, Roman S. Solomenko Institute of Transport Problems Russian Academy of Sciences Institute of Computer Science and Technology Peter the Great St.Petersburg Polytechnic University Laboratory of Intelligent Transport Systems St. Petersburg Russia Saint Petersburg State University of Architecture and Civil Engineering Department of Ground Transportation Technological Machines St. Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Department of Ship Control Systems St. Petersburg Russia Saint Petersburg State University Department of Programming Technology St. Petersburg Russia

ISBN: (纸本)9781728196923

An overview of existing urban software mobile applications of the transport and economic direction is given. A model of a functional rationalizer of consumer behavior is being built. The software model of the functional rationalizer of consumer behavior (SM FRCB) was developed for the first time. PMFRCB allows the user to expand the number of his preferred needs (occupations, activities) during the daily cycle through intelligent recommendations. Also, SM FRCB allows you to optimize needs (activities, activities) at the cost and rate of their use. The SM FRCB is made in Python_3 using the libraries matplotlib, collections, numpy, pyplot, mplot3d. The analysis of consumer behavior before and after using the functional rationalizer model is carried out. The graphical results of a structural analysis of the costs of old and new consumer behavior, analysis of consumer behavior within the boundaries of the theory of possibilities and the model of transport behavior of a resident before and after applying the functional rationalizer model are presented. The prospects of further improving the SM FRCB are considered. © 2020 IEEE.

关键词： Smart city

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SSMTL++: Revisiting self-supervised multi-task learning for video anomaly detection

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computer Vision and Image Understanding 2023年第1期229卷

作者： Barbalau, Antonio Ionescu, Radu Tudor Georgescu, Mariana-Iuliana Dueholm, Jacob Ramachandra, Bharathkumar Nasrollahi, Kamal Khan, Fahad Shahbaz Moeslund, Thomas B. Shah, Mubarak Department of Computer Science University of Bucharest 14 Academiei Street Bucharest010014 Romania SecurifAI 21D Mircea Voda Bucharest030662 Romania MBZ University of Artificial Intelligence Masdar City Abu Dhabi United Arab Emirates Department of Architecture Design and Media Technology Aalborg University Rendsburggade 14 Aalborg9000 Denmark Milestone Systems Banemarksvej 50C Brøndby2605 Denmark Geopipe Inc 460W 51st New York CityNY10019 United States Linköping University 581 83 Linköping Sweden University of Central Florida OrlandoFL32816 United States

A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature. Due to its highly accurate results, the method attracted the attention of many researchers. In this work, we revisit the self-supervised multi-task learning framework, proposing several updates to the original method. First, we study various detection methods, e.g. based on detecting high-motion regions using optical flow or background subtraction, since we believe the currently used pre-trained YOLOv3 is suboptimal, e.g. objects in motion or objects from unknown classes are never detected. Second, we modernize the 3D convolutional backbone by introducing multi-head self-attention modules, inspired by the recent success of vision transformers. As such, we alternatively introduce both 2D and 3D convolutional vision transformer (CvT) blocks. Third, in our attempt to further improve the model, we study additional self-supervised learning tasks, such as predicting segmentation maps through knowledge distillation, solving jigsaw puzzles, estimating body pose through knowledge distillation, predicting masked regions (inpainting), and adversarial learning with pseudo-anomalies. We conduct experiments to assess the performance impact of the introduced changes. Upon finding more promising configurations of the framework, dubbed SSMTL++v1 and SSMTL++v2, we extend our preliminary experiments to more data sets, demonstrating that our performance gains are consistent across all data sets. In most cases, our results on Avenue, ShanghaiTech and UBnormal raise the state-of-the-art performance bar to a new level. © 2023 Elsevier Inc.

关键词： Anomaly detection

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Collaborating with a Robot Biases Human Spatial Attention

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iScience 2025年

作者： Giulia Scorza Azzarà Joshua Zonca Francesco Rea Joo-Hyun Song Alessandra Sciutti Robotics Brain and Cognitive Sciences Unit Italian Institute of Technology 16152 Genoa GE Italy Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genoa 16145 Genoa GE Italy Cognitive Architecture for Collaborative Technologies (CONTACT) Unit Italian Institute of Technology 16152 Genoa GE Italy Department of Cognitive & Psychological Sciences Brown University 02912 Providence RI USA

Advancements in collaborative technologies have increased the accessibility of Human-Robot Interaction (HRI), yet a gap remains in understanding how HRI affects human systems. This work investigates how HRI influences human visual processing, specifically through the near-hand effect, a phenomenon where the proximity of one’s hand enhances spatial attention. Research has shown that this attentional priority can extend to another person’s hand during collaborative tasks, integrating it into an individual’s body schema. A critical question arises: Can a robot’s anthropomorphic hand similarly bias human attentional priority? Our findings revealed that collaborative HRI facilitates target detection near the robot’s hand, an effect absent before the interaction. Additionally, we examined social and kinematic metrics that enhance this attentional shift by fostering joint body schema formation. These results highlight that HRI can shape human visual processing and body schema integration, offering insight into the interplay between our perceptual and cognitive systems and robotic collaborators.

关键词： Collaborative Human-Robot Interaction Visual Processing Human Spatial Attention Near-Hand Effect Joint Body Schema

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Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors

arXiv

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arXiv 2023年

作者： Neun, Moritz Eichenberger, Christian Martin, Henry Spanring, Markus Siripurapu, Rahul Springer, Daniel Deng, Leyan Wu, Chenwang Lian, Defu Zhou, Min Lumiste, Martin Ilie, Andrei Wu, Xinhua Lyu, Cheng Lu, Qing-Long Mahajan, Vishal Lu, Yichao Li, Jiezhang Li, Junjun Gong, Yue-Jiao Grötschla, Florian Mathys, Joël Wei, Ye Haitao, He Fang, Hui Malm, Kevin Tang, Fei Kopp, Michael Kreil, David Hochreiter, Sepp Vienna Austria Institute of Cartography and Geoinformation ETH Zurich Switzerland School of Data Science University of Science and Technology of China China Huawei Noah’s Ark Lab Bolt Technology Tallinn Estonia University of Bucharest Bucharest Romania Department of Civil and Environmental Engineering Northeastern University BostonMA United States Transportation Systems Engineering Technical University of Munich Germany Layer 6 AI Toronto Canada School of Coumpute Science and Engineering South China University of Technology Guangzhou China ETH Zurich Switzerland Department of Computer Science Loughborough University Loughborough United Kingdom School of Architecture Building and Civil Engineering Loughborough University Loughborough United Kingdom HERE Technologies ChicagoIL United States Kaiko Zurich Switzerland Machine Learning Institute Johannes Kepler University Linz Austria

The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem in a data-driven way, advancing the latest methods in machine learning for modeling complex spatial systems over time. In this edition, our dynamic road graph data combine information from road maps, 1012 probe data points, and stationary vehicle detectors in three cities over the span of two years. While stationary vehicle detectors are the most accurate way to capture traffic volume, they are only available in few locations. Traffic4cast 2022 explores models that have the ability to generalize loosely related temporal vertex data on just a few nodes to predict dynamic future traffic states on the edges of the entire road graph. In the core challenge, participants are invited to predict the likelihoods of three congestion classes derived from the speed levels in the GPS data for the entire road graph in three cities 15 min into the future. We only provide vehicle count data from spatially sparse stationary vehicle detectors in these three cities as model input for this task. The data are aggregated in 15 min time bins for one hour prior to the prediction time. For the extended challenge, participants are tasked to predict the average travel times on super-segments 15 min into the future – super-segments are longer sequences of road segments in the graph. The competition results provide an important advance in the prediction of complex city-wide traffic states just from publicly available sparse vehicle data and without the need for large amounts of real-time floating vehicle data. © 2023, CC BY-NC-SA.

关键词： Travel time

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Crack identification using extended IsoGeometric analysis and particle swarm optimization 7th

Crack identification using extended IsoGeometric analysis an...

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7th International Conference on Fracture Fatigue and Wear, FFW 2018

作者： Khatir, Samir Wahab, Magd Abdel Benaissa, Brahim Köppen, Mario Department of Electrical Energy Metals Mechanical Constructions and Systems Faculty of Engineering and Architecture Ghent University Ghent Belgium Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan

ISBN: (纸本)9789811304101

The eXtended isogeometric analysis (X-IGA) combined with Particle swarm optimization (PSO) is used for crack identification in twodimensional linear elastic problems based on inverse problem. The application of fracture mechanics test under mode II loading is performed. The X-IGA possesses the advantages of the combination between eXtended Finite Element Method (X-FEM) and the Isogeometric Analysis (IGA). The objective function minimizes the gap between the calculated and measured displacements. Convergence studies at various positions of crack on the plate are calculated and the results shows that the proposed technique can detect damage with minimum accuracy 95% for the position and maximum accuracy 98%. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Inverse problem PSO and crack identification and plate 2D XIGA

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Linearization-based quantized stabilization of nonlinear systems under DoS attacks

arXiv

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arXiv 2020年

作者： Kato, Rui Cetinkaya, Ahmet Ishii, Hideaki Department of Computer Science Tokyo Instutite of Technology Yokohama226-8502 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan

Motivated by recent security issues in cyber-physical systems, this technical note studies the stabilization problem of networked control systems under Denial-of-Service (DoS) attacks. In particular, we consider to stabilize a nonlinear system with limited data rate via linearization. We employ a deterministic DoS attack model constrained in terms of attacks’ frequency and duration, allowing us to cover a large class of potential attacks. To achieve asymptotic stabilization, we propose a resilient dynamic quantizer in the sense that it does not saturate in the presence of packet losses caused by DoS attacks. A sufficient condition for stability is derived by restricting the average DoS frequency and duration. In addition, because of the locality of linearization, we explicitly investigate an estimate of the region of attraction, which can be expected to be reduced depending on the strength of DoS attacks. A simulation example is presented for demonstration of our results. Copyright © 2020, The Authors. All rights reserved.

关键词： Denial-of-service attack

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