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2018 2nd International Conference on Data Mining,Communications and Information technology (DMCIT 2018)

作者： X J Zhao L J Kong J Y Zhao Science and Technology on Complex Land Systems Simulation Laboratory

The meta-synthetic methodology is the scientific and effective way to solve the problems of the complicated large *** the meta-synthetic Hall,we combined the expert,repository,and simulation test together,building an environment to realize the Meta-Synthesis *** this article,we put forward simulation architecture for the Meta-Synthesis *** the architecture,we can build the simulation system and do experiment for the Hall,supporting expert discussion and repository *** can solve the system experiment and data collection problems for complicated large system analysis,enforces system improve and perfect.

关键词： simulation The Study of simulation Architecture in Meta-Synthetic Hall

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Deep Modular Co-Attention Networks for Visual Question Answering

Deep Modular Co-Attention Networks for Visual Question Answe...

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Zhou Yu Jun Yu Yuhao Cui Dacheng Tao Qi Tian Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney Noah's Ark Lab

ISBN: (纸本)9781728132945

Visual Question Answering (VQA) requires a finegrained and simultaneous understanding of both the visual content of images and the textual content of questions. Therefore, designing an effective 'co-attention' model to associate key words in questions with key objects in images is central to VQA performance. So far, most successful attempts at co-attention learning have been achieved by using shallow models, and deep co-attention models show little improvement over their shallow counterparts. In this paper, we propose a deep Modular Co-Attention Network (MCAN) that consists of Modular Co-Attention (MCA) layers cascaded in depth. Each MCA layer models the self-attention of questions and images, as well as the question-guided-attention of images jointly using a modular composition of two basic attention units. We quantitatively and qualitatively evaluate MCAN on the benchmark VQA-v2 dataset and conduct extensive ablation studies to explore the reasons behind MCAN's effectiveness. Experimental results demonstrate that MCAN significantly outperforms the previous state-of-the-art. Our best single model delivers 70.63% overall accuracy on the test-dev set.

关键词： Modularity images Visualization system buses compensatory amounts Maximum credible accidents Layer models

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Interfacial strength vs toughness: Enhancing mechanical and impact performance of CF/PEEK thermoplastic composites

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Chemical Engineering Journal 2025年

作者： Yu Gao Song Yan Kaiyan Min Xiahui Liu Yue Li Ju Wu Jianfeng Zhou Shu Zhu Peng Wang State Key Laboratory for Modification of Chemical Fibers and Polymer Materials Shanghai Collaborative Innovation Center of High-Performance Fibers and Composites (Province-Ministry Joint) Key Laboratory of High-Performance Fibers & Products Ministry of Education Center for Civil Aviation Composites Donghua University Shanghai 201620 China Key Laboratory of Shanghai City for Lightweight Composites College of Materials Science and Engineering Donghua University Shanghai 201620 China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science BIC-ESAT College of Engineering Peking University Beijing 100871 China School of Chemistry and Chemical Engineering Frontiers Science Center for Transformative Molecules Shanghai Jiao Tong University Shanghai 201306 China Key Laboratory of Textile Science & Technology of Ministry of Education College of Textiles Donghua University Shanghai 201620 China

Carbon fiber reinforced thermoplastic composites (CFRTP) are highly recyclable, reducing waste and promoting sustainability in industrial applications. Good interfacial adhesion is key to the mechanical performance of CFRTPs. Despite its critical role in impact resistance and durability, interfacial toughness has received less attention than interfacial strength, which has been more widely studied and discussed. In this study, Carbon fiber fabrics were treated with two modifiers of different stiffness: polyimide (M1) and poly(arylsulfone) (M2). Composites containing varying concentrations of these modifiers were then fabricated via compression molding. The influence of modifier stiffness on the mechanical properties and fracture toughness of the composites was systematically analyzed. Compared to untreated fibers, the composites modified with an optimal concentration of M1 achieved tensile strength, flexural strength, and interlaminar shear strength (ILSS) improvements of 24.9 %, 20.5 %, and 27.8 %, respectively, while the M2 modified composites exhibited respective increases of 43.8 %, 19.3 %, and 28.3 %. Analysis of impact damage morphology and C-scan imaging revealed that composites modified with 2 wt% M1 and 1 wt% M2 exhibited reduced internal damage areas. The rigid -C=O-N structure of M1 led to brittle fracture, while the flexible long chains of M2 facilitated stress transfer and energy absorption, resulting in ductile fracture. Their compression-after-impact (CAI) failure modes were characterized by transverse cracking along the central defect. These findings provide valuable theoretical guidance for enhancing the toughness of thermoplastic composites through interfacial treatment.

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Mass- and energy-preserving exponential Runge-Kutta methods for the nonlinear Schrödinger equation

arXiv

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arXiv 2020年

作者： Cui, Jin Xu, Zhuangzhi Wang, Yushun Jiang, Chaolong Department of Basic Sciences Nanjing Vocational College of Information Technology Nanjing210023 China Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems School of Mathematical Sciences Nanjing Normal University Nanjing210023 China Department of Mathematics College of Liberal Arts and Science National University of Defense Technology Changsha410073 China School of Statistics and Mathematics Yunnan University of Finance and Economics Kunming650221 China

In this paper, a family of arbitrarily high-order structure-preserving exponential Runge-Kutta methods is developed for the nonlinear Schrödinger equation by combing the scalar auxiliary variable approach and the exponential Runge-Kutta method. By introducing an auxiliary variable, we first transform the original model into an equivalent system which admits both mass and modified energy. Then applying the Lawson method and the symplectic Runge-Kutta method in time, we derive a class of mass- and energy-conserving time-discrete schemes. Numerical experiments are addressed to demonstrate the accuracy and effectiveness of the newly proposed schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Runge Kutta methods

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On exploring undetermined relationships for visual relationship detection

arXiv

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arXiv 2019年

作者： Zhan, Yibing Yu, Jun Yu, Ting Tao, Dacheng Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University China UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney DarlingtonNSW2008 Australia

In visual relationship detection, human-notated relationships can be regarded as determinate relationships. However, there are still large amount of unlabeled data, such as object pairs with less significant relationships or even with no relationships. We refer to these unlabeled but potentially useful data as undetermined relationships. Although a vast body of literature exists, few methods exploit these undetermined relationships for visual relationship detection. In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection. We propose a novel multi-modal feature based undetermined relationship learning network (MF-URLN) and achieve great improvements in relationship detection. In detail, our MF-URLN automatically generates undetermined relationships by comparing object pairs with human-notated data according to a designed criterion. Then, the MF-URLN extracts and fuses features of object pairs from three complementary modals: Visual, spatial, and linguistic modals. Further, the MF-URLN proposes two correlated subnetworks: One subnetwork decides the determinate confidence, and the other predicts the relationships. We evaluate the MF-URLN on two datasets: The Visual Relationship Detection (VRD) and the Visual Genome (VG) datasets. The experimental results compared with state-of-the-art methods verify the significant improvements made by the undetermined relationships, e.g., the top-50 relation detection recall improves from 19.5% to 23.9% on the VRD dataset. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Deep Modular Co-Attention networks for visual question answering

arXiv

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arXiv 2019年

作者： Yu, Zhou Yu, Jun Cui, Yuhao Tao, Dacheng Tian, Qi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney Noah's Ark Lab Huawei

Visual Question Answering (VQA) requires a finegrained and simultaneous understanding of both the visual content of images and the textual content of questions. Therefore, designing an effective 'co-attention' model to associate key words in questions with key objects in images is central to VQA performance. So far, most successful attempts at co-attention learning have been achieved by using shallow models, and deep co-attention models show little improvement over their shallow counterparts. In this paper, we propose a deep Modular Co-Attention Network (MCAN) that consists of Modular Co-Attention (MCA) layers cascaded in depth. Each MCA layer models the self-attention of questions and images, as well as the guided-attention of images jointly using a modular composition of two basic attention units. We quantitatively and qualitatively evaluate MCAN on the benchmark VQA-v2 dataset and conduct extensive ablation studies to explore the reasons behind MCAN's effectiveness. Experimental results demonstrate that MCAN significantly outperforms the previous state-ofthe- A rt. Our best single model delivers 70.63% overall accuracy on the test-dev set. Code is available at http://***/MILVLG/mcan-vqa. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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MobileEdge: Enhancing On-Board Vehicle Computing Units Using Mobile Edges for CAVs

MobileEdge: Enhancing On-Board Vehicle Computing Units Using...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Lin Wang Qingyang Zhang Youhuizi Li Hong Zhong Weisong Shi School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Department of Computer Science Wayne State University Detroit MI USA

ISBN: (纸本)9781728125848

As the rapid growth of connected and autonomous vehicles (CAVs) and 5G intensifies, more third-party applications are increasingly being deployed on CAVs. They not only improve user experience but also provide more helpful services, for example, enhancing public safety by recognizing criminals in real-time videos. Current CAVs prefer to process collected data on the vehicle to avoid long transmission latency and extra network cost. However, due to the limitations of the on-board vehicle computing unit (VCU) and increasing use of computing-intensive in-vehicle applications, the burden of on-board VCU has sharply increased, which may affect driving safety. In particular, for existing vehicles on the road, adding more computing devices is a challenge if not impossible due to cost concerns. Inspired by edge computing, we propose a novel platform, MobileEdge, to enhance the computing capability of the unchangeable on-board VCU, which leverages mobile devices as edge nodes, e.g., the passengers' smartphones, by offloading computing tasks to them for collaboratively computing. Moreover, MobileEdge provides the dynamic management of mobile devices, monitoring device status and interfaces for customizable task offloading strategies and eventually achieves optimal task scheduling. We build a prototype to demonstrate the designed platform and evaluate three task offloading strategies which were implemented based on the developed interfaces. The results show that MobileEdge significantly reduces the application response latency. Compared with the baseline which does not employ task offloading, the response latency is almost near real-time when more computing resources are available. In addition, the proposed shortest response latency strategy outperforms the best overall task scheduling among the three strategies.

关键词： Edge computing Vehicular data analysis Distributed computing Connected and autonomous vehicles Distributed computing TASK SCHEDULING Response Latency UNLOADING vehicle vinyl chloride-urethane copolymer Mobile devices unchangeable quasi-realtime language Public safety

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Correction to: Batch mode active learning via adaptive criteria weights

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Applied Intelligence 2020年第6期51卷 3490-3490页

作者： Li, Hao Wang, Yongli Li, Yanchao Xiao, Gang Hu, Peng Zhao, Ruxin School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Science and Technology on Complex Systems Simulation Laboratory Beijing China

A correction to this paper has been published: https://***/10.1007/s10489-020-02146-9

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Theoretical analysis and simulation of phase separation in a driven bidirectional two-lane system

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Physical Review E 2019年第3期100卷 032133-032133页

作者： Qing-Yi Hao Rui Jiang Mao-Bin Hu Yunxin Zhang Chao-Yun Wu Ning Guo Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains of Anhui Higher Education Institutes School of Mathematics and Computational Science Anqing Normal University Anqing 246133 China School of Mathematical Sciences Fudan University Shanghai 200433 China MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing 100044 China School of Engineering Science University of Science and Technology of China Hefei 230026 China School of Automotive and Transportation Engineering Hefei University of Technology Hefei 230009 China

The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectional two-lane model. The dynamic characteristics of the model with periodic boundary are investigated by Monte Carlo simulation, simple mean field, and cluster mean field methods, respectively. By simulations, phase separations are observed in the system with some values of model parameters. When the phase separation does not occur, cluster mean field results are in good agreement with simulation results. According to the cluster mean field analysis and simulations, a conjecture about the condition that the phase separation happens is proposed. Based on the conjecture, the phase boundary distinguishing phase separation state and homogeneous state is determined, and a corresponding phase diagram is drawn. The conjecture is validated through observing directly the spatiotemporal diagram and investigating the coarsening process of the system by simulation, and a possible mechanism causing the phase separation is also discussed. These outcomes maybe contribute to understand deeply transport systems including the congestion and efficiency of the transport, and enrich explorations of nonequilibrium state systems.

关键词： Dynamical phase transitions Phase diagrams Phase separation Phase transitions Transport phenomena

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Directed momentum current induced by the PT-symmetric driving

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Physical Review E 2019年第4期99卷 042201-042201页

作者： Wen-Lei Zhao Jiaozi Wang Xiaohui Wang Peiqing Tong School of Science Jiangxi University of Science and Technology Ganzhou 341000 China Department of Modern Physics University of Science and Technology of China Hefei 230026 China School of Information Engineering Jiangxi University of Science and Technology Ganzhou 341000 China Department of Physics and Institute of Theoretical Physics Nanjing Normal University Nanjing 210023 China Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Nanjing Jiangsu 210023 China

We investigate the directed momentum current in the quantum kicked rotor model with PT-symmetric deriving potential. For the quantum nonresonance case, the values of quasienergy become complex when the strength of the imaginary part of the kicking potential exceeds a threshold value, which demonstrates the appearance of the spontaneous PT symmetry breaking. In the vicinity of the transition point, the momentum current exhibits a staircase growth with time. Each platform of the momentum current corresponds to the mean momentum of some eigenstates of the Floquet operator whose imaginary parts of the quasienergy are significantly large. Above the transition point, the momentum current increases linearly with time. Interestingly, its acceleration rate exhibits a kind of “quantized” increment with the kicking strength. We propose a modified classical acceleration mode of the kicked rotor model to explain such an intriguing phenomenon. Our theoretical prediction is in good agreement with numerical results.

关键词： Coherent control Cold atoms & matter waves Light-matter interaction Wave chaos

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