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6th IEEE International Conference on Intelligent computing and Signal Processing, ICSP 2021

作者： Zhang, Qi Liu, Yan Cai, Yuheng Zhong Yuan Network Security Research Institute Zhengzhou University Zhengzhou China Pla Strategic Support Force Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9780738143705

The network group detection has a large number of application researches and has achieved certain results in network security, IP entity location and load balancing. However, due to the large scale of the network topology graph and the large number of terminal nodes, most of the existing overlapping group detection algorithms are relatively complex, and the data size that can be processed is limited, and cannot be directly applied to the network topology. This paper proposes a network topology overlapping group detection algorithm based on h-core pruning. This algorithm decomposes the network into smaller strong connected components, reduces the interference of noisy nodes to overlapping group discovery, and more efficiently detect the largest k-plex group on the target network. A large number of experiments show that the method in this paper is effective. Compared with the full-enum algorithm, our method increases the network size that can be handled by the largest k-plex group by two orders of magnitude, and can detect overlapping groups in the network topology more efficiently. © 2021 IEEE.

关键词： Network topology

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Non-Gaussian States Generation Using a High-Speed Single-Pixel Superconducting Nano-Strip Photon-Number-Resolving Detector

Non-Gaussian States Generation Using a High-Speed Single-Pix...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Takahashi, Kazuma Endo, Mamoru Nomura, Takefumi Sonoyama, Tatsuki Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Yabuno, Masahiro China, Fumihiro Terai, Hirotaka Miki, Shigehito Nehra, Rajveer Takase, Kan Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan NTT Device Technology Labs. NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan Graduate School of Engineering Kobe University 1-1 Rokkodai-cho Nada-ku Hyogo Kobe657-0013 Japan Department of Electrical and Computer Engineering University of Massachusetts-Amherst AmherstMA01003 United States Department of Physics University of Massachusetts-Amherst AmherstMA01003 United States

ISBN: (纸本)9781957171395

We performed the first non-Gaussian state generation through two photon subtraction with a recently developed single-pixel superconducting nano-strip photon-number-resolving detector. We observed negative values of Wigner function of W(0,1.0) = -0.0072 ± 0.006 without loss correction. © 2024 The Author(s) © Optica Publishing Group 2024.

关键词： Photons

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Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

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Applying machine learning classifiers in argumentation context 17th

Applying machine learning classifiers in argumentation conte...

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17th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2020

作者： Conceição, Luís Carneiro, João Marreiros, Goreti Novais, Paulo ALGORITMI Centre University of Minho Guimarães4800-058 Portugal GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto4200-072 Portugal

ISBN: (纸本)9783030530358

Group decision making is an area that has been studied over the years. Group Decision Support Systems emerged with the aim of supporting decision makers in group decision-making processes. In order to properly support decision-makers these days, it is essential that GDSS provide mechanisms to properly support decision-makers. The application of Machine Learning techniques in the context of argumentation has grown over the past few years. Arguing includes negotiating arguments for and against a certain point of view. From political debates to social media posts, ideas are discussed in the form of an exchange of arguments. During the last years, the automatic detection of this arguments has been studied and it’s called Argument Mining. Recent advances in this field of research have shown that it is possible to extract arguments from unstructured texts and classifying the relations between them. In this work, we used machine learning classifiers to automatically classify the direction (relation) between two arguments. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Machine learning

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High-rate generation and ultrafast real-time observation of optical non-Gaussian states encoded in sub-nanosecond wavepackets

High-rate generation and ultrafast real-time observation of ...

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Quantum 2.0, QUANTUM 2024 in Quantum 2.0 Conference and Exhibition

作者： Kawasaki, Akito Ide, Ryuhoh Brunel, Hector Suzuki, Takumi Nehra, Rajveer Nakashima, Katsuki Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi China, Fumihiro Yabuno, Masahiro Miki, Shigehito Terai, Hirotaka Yamashima, Taichi Sakaguchi, Atsushi Takase, Kan Endo, Mamoru Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Physics Ecole Normale Supérieure 24 rue Lhomond Paris75005 France Department of Electrical and Computer Engineering University of Massachusetts-Amherst AmherstMA01003 United States Department of Physics University of Massachusetts-Amherst AmherstMA01003 United States NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan Advanced ICR Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi Kobe651-2492 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan

We generate and observe optical non-Gaussian states defined in wavepackets of sub-nanosecond time width—O(103) faster than previous research—using waveguide optical parametric amplifier made of PPLN crystal, enablin... 详细信息

ISBN: (纸本)9781557525185

关键词： Parametric amplifiers

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FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis

FinXABSA: Explainable Finance through Aspect-Based Sentiment...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Keane Ong Wihan van der Heever Ranjan Satapathy Erik Cambria Gianmarco Mengaldo Asian Institute of Digital Finance National University of Singapore Singapore School of Computer Science and Engineering Nanyang Technological University Singapore Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) Singapore College of Design & Engineering National University of Singapore Singapore

This paper presents a novel approach for explain-ability in financial analysis by deriving financially-explainable statistical relationships through aspect-based sentiment analysis, Pearson correlation, Granger causality & uncertainty coefficient. The proposed methodology involves constructing an aspect list from financial literature and applying aspect-based sentiment analysis on social media text to compute sentiment scores for each aspect. Pearson correlation is then applied to uncover financially explainable relationships between aspect sentiment scores and stock prices. Findings for derived relationships are made robust by applying Granger causality to determine the forecasting ability of each aspect sentiment score for stock prices. Finally, an added layer of interpretability is added by evaluating uncertainty coefficient scores between aspect sentiment scores and stock prices. This allows us to determine the aspects whose sentiment scores are most statistically significant for stock prices. Relative to other methods, our approach provides a more informative and accurate understanding of the relationship between sentiment analysis and stock prices. Specifically, this methodology enables an interpretation of the statistical relationship between aspect-based sentiment scores and stock prices, which offers explainability to AI-driven financial decision-making.

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A Group Theory Based Topology Optimization Scheme for the Design of Inhomogeneous Waveguides with Dihedral Group Symmetries

SSRN

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SSRN 2024年

作者： Chu, Peiwen Li, Yifan He, Zhicheng Li, Eric Ozgun, Ozlem Vandenbosch, Guy A.E. Zheng, Xuezhi State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle the college of Mechanical and Transportation Engineering Hunan university Changsha410082 China ESAT-WaveCoRE Research Division Department of Electrical Engineering KU Leuven Leuven3001 Belgium School of Computing Engineering & Digital Technologies Teesside University United Kingdom Electrical and Electronics Engineering Hacettepe University Beytepe AnkaraTR 06800 Turkey

In this paper, we introduce a novel topology optimization scheme dedicated to designing waveguides with inhomogeneities holding rotation and reflection symmetries. At begining, we build the scheme by first developing a new computational algorithm that combines the Finite Element Method with the group representation theory. This combination allows the decomposition of the eigenvalue problem in a classic FEM to orthogonal (decoupled) subproblems, which therefore leads to an improved solver efficiency by order of magnitude. For a targeted mode profile, the involvement of the GRT does not only enable a pre-selection of the subproblems that are to be optimized, which further improves the computational speed, but also completely avoids potential mode degeneracies, which adversely affects the convergence of the optimization. To validate, the GRT – FEM algorithm is first tested against the results from a full FEM simulation for a guide with inhomogeneities with six-fold rotation and reflection symmetries. Then, the entire scheme is applied to achieve a desired eigenmode with a targeted propagation constant. The proposed scheme does not only provide an efficient design tool for exploiting interesting wave phenomena in waveguiding structures, but also lays down a theoretical foundation for systematically integrating symmetries with classic Computational Electromagnetics algorithms. © 2024, The Authors. All rights reserved.

关键词： Finite element method

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NOMA: A Novel Reliability Improvement Methodology for 3-D IC-based Neuromorphic Systems

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2024年

作者： Nguyen, Ngo-Doanh Dang, Khanh N. Ahmed, Akram Ben Abdallah, Abderazek Ben Tran, Xuan-Tu The University of Aizu The Graduate School of Computer Science and Engineering Fukushima Aizu-Wakamatsu965-8580 Japan Vietnam National University The Information Technology Institute Hanoi10000 Viet Nam National Institute of Advanced Industrial Sciences and Technology The Digital Architecture Research Center 2-3-26 Aomi Koto-ku Tokyo Japan

Hardware is the foundation of trust for all real-time applications and is especially crucial in Artificial Intelligence (AI). The growing reliance on AI for various tasks has raised concerns about the reliability of the hardware. Extensive research has shown that hardware faults arising from the manufacturing process or device variation can significantly impact the precision and accuracy of AI applications. This also applies to 3-D IC (Three-Dimensional Integrated Circuit)-based Spiking Neural Networks (SNNs), despite their noise resilience, low-power, and low memory footprint advantages. This is because, in addition to the mentioned hardware faults, thermal dissipation on 3-D ICs can negatively affect the memory stacked on upper dies. Hence, this article proposes a methodology called NOMA (Network-of-Memory Architecture) to enhance the reliability of 3-D IC-based SNNs by replacing the defective critical synaptic weights in high-priority layers with lower-priority ones. The method is assessed on multiple memory-on-logic architectures with various memory technologies such as SRAM, eDRAM, STT-RAM, and RRAM. As a result, for the 45nm SRAM library, the accuracy degradation improves by roughly 56% at a BER of 0.05 with a timing overhead of 3.538μs and a power overhead of 390.796nJ. © 2011-2012 IEEE.

关键词： Memory architecture

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Vacancy-Type Defects in Thin HfO2 Layers Probed by Monoenergetic Positron Beams 30

Vacancy-Type Defects in Thin HfO2 Layers Probed by Monoenerg...

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30th International Symposium on Semiconductor Manufacturing, ISSM 2024

作者： Uedono, Akira Kawakami, Kazuya Kuribara, Tatsunori Hasunuma, Ryu Harashima, Yosuke Shigeta, Yasuteru Ni, Zeyuan Yan, Ruolin Nakamura, Hideo Notake, Akira Moriya, Tsuyoshi Michishio, Koji Ishibashi, Shoji University of Tsukuba Faculty of Pure and Applied Science Ibaraki Tsukuba305-8573 Japan Nara Institute of Science and Technology Graduate School of Science and Technology Nara Ikoma630-0192 Japan Tokyo Electron Technology Solutions Ltd. S-Technology Development Center Yamanashi Nirasaki407-0192 Japan Tokyo Electron Technology Solutions Ltd. Development Department 1 Yamanashi Nirasaki407-0192 Japan Tokyo Electron Ltd. Digital Design Center Hokkaido Sapporo060-0003 Japan Tokyo Electron Technology Solutions Ltd. Software and Data Engineering Division Yamanashi Nirasaki407-0192 Japan National Institute of Advanced Industrial Science and Technology Research Institute for Measurement and Analytical Instrumentation Ibaraki Tsukuba305-8568 Japan National Institute of Advanced Industrial Science and Technology Research Center for Computational Design of Advanced Functional Materials Ibaraki Tsukuba305-8568 Japan

ISBN: (纸本)9798331510589

Behaviors of vacancies during the amorphous-to-crystalline transition of thin HfO2 layers were studied by monoenergetic positron beams. The HfO2 layers with 430 nm thickness were fabricated on TiN/Si templates by atomic layer deposition technique. The major vacancy-type defects in the layers were identified as (i) Hf vacancies (VHf) coupled with oxygen vacancies (VOs) and (ii) vacancy clusters. After annealing at 500°C, the concentration of vacancy clusters increased, which was attributed to the agglomeration of intrinsic open spaces in the amorphous phase upon the phase transition from amorphous to crystalline phases. The phase transition started near the interface between the HfO2 layer and bottom electrodes (TiN). After the crystallization, the concentration of vacancy clusters decreased as the annealing temperature increased. © 2024 IEEE.

关键词： Positron annihilation

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Next Generation Optical Quantum State Synthesis: Observation of Fourfold Negativity in the Wigner Function

Next Generation Optical Quantum State Synthesis: Observation...

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2024 Laser Science, LS 2024

作者： Endo, Mamoru Takase, Kan Nomura, Takefumi Sonoyama, Tatsuki Takahashi, Kazuma Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Takasu, Sachiko Fukuda, Daiji Marek, Petr Filip, Radim Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Tokyo Bunkyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan NTT Device Technology Labs. NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan National Institute of Advanced Industrial Science and Technology Ibaraki Tsukuba305-8563 Japan AIST-UTokyo Advanced Operando-Measurement Technology Open Innovation Laboratory Ibaraki Tsukuba305-8563 Japan Department of Optics Palacky University 17. listopadu 1192/12 Olomouc77146 Czech Republic

An optical quantum state with fourfold Wigner negativity was generated without any loss correction. Generalized photon subtraction scheme, broadband squeezed light source, and high-temporal-resolution transition-edge sensor enabled generation rates of tens of counts per second. © 2024 The Author(s). © Optica Publishing Group 2024.

关键词： Squeezed light

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