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A Real-time Cutting Model Based on Finite Element and Order Reduction

computer Systems science & engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

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Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension 39

Thought-Path Contrastive Learning via Premise-Oriented Data ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Wang, Chenxu Jian, Ping Yang, Zhen School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing China

ISBN: (纸本)157735897X

Logical reading comprehension is a challenging task that involves understanding the underlying semantics of text and applying reasoning to deduce the correct answer. Prior researches have primarily focused on enhancing logical reasoning capabilities through Chain-of-Thought (CoT) or data augmentation. However, previous work constructing chain-of-thought rationales concentrates solely on analyzing correct options, neglecting the incorrect alternatives. Addtionally, earlier efforts on data augmentation by altering contexts rely on rule-based methods, which result in generated contexts that lack diversity and coherence. To address these issues, we propose a Premise-Oriented Data Augmentation (PODA) framework. This framework can generate CoT rationales including analyses for both correct and incorrect options, while constructing diverse and high-quality counterfactual contexts from incorrect candidate options. We integrate summarizing premises and identifying premises for each option into rationales. Subsequently, we employ multi-step prompts with identified premises to construct counterfactual context. To facilitate the model’s capabilities to better differentiate the reasoning process associated with each option, we introduce a novel thought-path contrastive learning method that compares reasoning paths between the original and counterfactual samples. Experimental results on three representative LLMs demonstrate that our method can improve the baselines substantially across two challenging logical reasoning benchmarks (ReClor and LogiQA 2.0). © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

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Revolutionizing Prostate Cancer Diagnosis: Harnessing the Potential of Transfer Learning for MRI-Based Classification 4

Revolutionizing Prostate Cancer Diagnosis: Harnessing the Po...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Degadwala, Sheshang Vyas, Dhairya Trivedi, Sanjay Dave, Harsh Nilaykumar, Patel Khush Dalal, Pankaj Sigma University Department of Computer Engineering Gujarat India The Maharaja Sayajirao University of Baroda Gujarat Vadodara India Gjpiasr Surgeon Department of Surgery Gujrat Anand India Smt.B.K.Shah Medical Institute and Research Center Gujarat Vadodara India Charotar University of Science and Technology Changa India Sigma University Computer Science and Applications Gujrat Vadodara India

ISBN: (纸本)9798350300888

This study introduces a novel framework that harnesses the potential of transfer learning for MRI -based classification in prostate cancer diagnosis. The study explores the challenges of accurately classifying prostate cancer from MRI images and proposes a methodology that integrates pre-trained deep neural networks with a large, annotated dataset. The framework demonstrates superior performance compared to conventional methods, achieving higher Accuracy, Precision, Recall, Fl-Score. The approach exhibits robustness across different MRI scanners and patient populations, highlighting its potential for real-world clinical applications. Additionally, this study emphasizes the interpretability of the model through visualization techniques, aiding clinicians in understanding the underlying pathology and making informed treatment decisions. Overall, this research contributes to the revolutionization of prostate cancer diagnosis, offering improved accuracy and efficiency in clinical settings and paving the way for advanced computer-aided diagnostic systems. © 2023 IEEE.

关键词： Magnetic resonance imaging

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FCGSM: Fast Conjugate Gradient Sign Method for Adversarial Attack on Image Classification 6th

FCGSM: Fast Conjugate Gradient Sign Method for Adversarial ...

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6th International Conference on Innovative Computing, IC 2023

作者： Xia, Xiaoyan Xue, Wei Wan, Pengcheng Zhang, Hui Wang, Xinyu Zhang, Zhiting School of Computer Science and Technology Anhui University of Technology Maanshan243032 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Maanshan243032 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819922864

Deep neural network is sensitive to adversarial samples that crafted by adding imperceptible perturbations to original images, and many methods of generating adversarial samples have emerged. Although existing methods based on gradient direction have good attack performance, some ill-conditioned issues may reduce their performance on occasion. In this paper, we propose a novel attack method based on three-terms conjugate gradient direction, which is effectively for improving this limitation, and its is named as fast conjugate gradient sign method (FCGSM). The proposed method FCGSM can jump from the local maximum during the process of finding the maximum value of loss function, thus generating more adversarial samples than the SOTA methods APGD and ACG. Experiments conducted on two benchmark datasets show that the FCGSM works well in attacking deep neural network-based classification models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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Differential Privacy Generative Adversarial Networks Based on Dynamic Learning Rate Constrained Adaptive Gradient Algorithm

Differential Privacy Generative Adversarial Networks Based o...

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Cross Strait Quad-Regional Radio science and Wireless Technology Conference (CSRWTC)

作者： Hui Wang Zhen-Yu Wan Yi-Bing Hou Ze-Gang Chen Tao Tao School of Computer Science and Technology Anhui University of Technology Maanshan China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Maanshan China Engineering Research Institute Anhui University of Technology Maanshan China

ISBN: (数字)9798331507794

ISBN: (纸本)9798331507800

The Generative Adversarial Network (GAN) based on differential privacy(DP) aims to protect data privacy through generative models. However, it faces challenges in balancing the trade-off between generation quality and privacy protection, as well as ensuring stable training. This paper proposes a novel algorithm called Adaptive Bound Differential Privacy GAN (ABDP-GAN), which applies the AdaBound optimizer to the training of differentially private GANs. By dynamically adjusting the learning rate, the algorithm accelerates model convergence, smooths out the impact of differential privacy noise, and ensures stable training. Experimental comparisons with other algorithms show that ABDP-GAN not only maintains the utility and privacy of image data but also achieves more stable training and higher convergence efficiency.

关键词： Training Wireless communication Differential privacy Adaptation models Adaptive systems Heuristic algorithms Generative adversarial networks Data models Stability analysis Convergence

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Capturing Global Structural Information in Long Document Question Answering with Compressive Graph Selector Network

Capturing Global Structural Information in Long Document Que...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Nie, Yuxiang Huang, Heyan Wei, Wei Mao, Xian-Ling School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Beijing Institute of Technology Southeast Academy of Information Technology China Huazhong University of Science and Technology China

Long document question answering is a challenging task due to its demands for complex reasoning over long text. Previous works usually take long documents as non-structured flat texts or only consider the local structure in long documents. However, these methods usually ignore the global structure of the long document, which is essential for long-range understanding. To tackle this problem, we propose Compressive Graph Selector Network (CGSN) to capture the global structure in a compressive and iterative manner. The proposed model mainly focuses on the evidence selection phase of long document question answering. Specifically, it consists of three modules: local graph network, global graph network and evidence memory network. Firstly, the local graph network builds the graph structure of the chunked segment in token, sentence, paragraph and segment levels to capture the short-term dependency of the text. Secondly, the global graph network selectively receives the information of each level from the local graph, compresses them into the global graph nodes and applies graph attention to the global graph nodes to build the long-range reasoning over the entire text in an iterative way. Thirdly, the evidence memory network is designed to alleviate the redundancy problem in the evidence selection by saving the selected result in the previous steps. Extensive experiments show that the proposed model outperforms previous methods on two datasets. © 2022 Association for Computational Linguistics.

关键词： Iterative methods

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Three-dimensional reconstruction of mobile binocular stereo vision based on push-broom line structured light for a workpiece surface

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Journal of the Optical Society of America A: Optics and Image science, and Vision 2023年第11期40卷 2096-2107页

作者： Wang, Yue Han, Xueyou Rui, Jing Zhang, Hailan Yin, Lei Zhang, Xuefeng Wang, Xiangjun School of Computer Science and Technology Anhui University of Technology Maanshan China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Maanshan243032 China School of Electrical and Information Engineering Anhui University of Technology Maanshan China The 53th Research Institute of China Electronics Technology Group Corporation Tianjin China State Key Laboratory of Precision Measuring Technology and Instruments Tianjin University Tianjin China Key Laboratory ofMOEMS of the Ministry of Education Tianjin University Tianjin China

Stereo vision technology based on line structured light can effectively solve the problem of a three-dimensional (3D) reconstruction of a smooth surface. A method for 3D reconstruction of mobile binocular stereo vision based on push-broom line structured light for a workpiece surface is presented in this paper. The subpixel coordinates of the light strip centers of the line structured light are obtained by the Steger algorithm while the binocular module moves along the guide rail, and the polar constraint is used to achieve the matching of the extracted light strip centers. As a result, the3Dcoordinates of the light strip centers in each location can be calculated because of the known interior and external parameters of the binocular module. To obtain the 3D point cloud data of the entire surface, a relative pose optimization method with respect to the initial frame is proposed, which accurately estimates the pose of the cameras in each location with respect to that in the initial location and unifies the 3D coordinates of the light strip centers in each location to the datum coordinates. The relative pose optimization method first estimates the rough values by using the direct linear transform method, and then iteratively calculates the refined solutions based on the principle of minimizing the re-projection errors. Simulation data and substantial experimental results validate the effectiveness of our method. Our method is compared to the direct linear transform method and the frame-by-frame transfer method, and the root mean square error (RMSE) of the distance from 3D point cloud to fitted plane is used to evaluate the 3D reconstruction accuracy. The repeatability experiment shows that the RMSE fromour method is as lowas 0.83mm. © 2023 Optica Publishing Group.

关键词： Location

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Robustness Study of Website Fingerprinting Based on Feature Fusion

Robustness Study of Website Fingerprinting Based on Feature ...

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Cross Strait Quad-Regional Radio science and Wireless Technology Conference (CSRWTC)

作者： Da-Fu Su Bo Chen Xiao-Feng Jia Zhen-Yu Wan Yi-Bing Hou Hong-Chi Zhou Tao Tao School of Computer Science and Technology Anhui University of Technology Maanshan Anhui China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Maanshan China Engineering Research Institute Anhui University of Technology Maanshan China

ISBN: (数字)9798331507794

ISBN: (纸本)9798331507800

With the ongoing advancement of website traffic analysis technologies, techniques such as website fingerprinting and traffic pattern analysis have become increasingly sophisticated. However, the widespread adoption of encryption and anonymity technologies like Tor has also presented new challenges for network regulation. Current defense mechanisms such as WTF-PAD and Walkie-Talkie have relied on adaptive traffic padding by inserting fake packets intelligently and controlling the timing of bidirectional traffic transmission and reception, effectively reducing the accuracy of website fingerprinting. To address the limitations of these defense mechanisms, a robustness-enhanced website fingerprinting method based on time feature enhancement was proposed. This method incorporated the time dimension into feature learning and combined traffic direction and size features, significantly improving recognition robustness. Experimental results showed that under the WTF-PAD defense, the proposed method achieved a recognition accuracy of 94.34%.

关键词： Wireless communication Representation learning Accuracy Fingerprint recognition Traffic control Robustness Regulation Timing Encryption

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Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension

arXiv

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arXiv 2024年

关键词： Contrastive Learning

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Chlorine-substituted chiral 2D perovskite microwires with enhanced lattice rigidity for sensitive circularly polarized light detection

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science China Chemistry 2023年第12期66卷 3602-3610页

作者： Meng Yuan Yuchen Qiu Yingjie Zhao Yuyan Zhao Hui Li Xiao Wei Gaosong Chen Jiangang Feng Hanfei Gao Jinjin Zhao Jiahui Zhao Lei Jiang Yuchen Wu Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China College of Chemistry Zhengzhou UniversityZhengzhou 450001China College of Chemistry Jilin UniversityChangchun 130012China Key Laboratory for Special Functional Materials of Ministry of Education National and Local Joint Engineering Research Center for High-Efficiency Display and Lighting TechnologyCollaborative Innovation Center of Nano Functional Materials and ApplicationsHenan UniversityKaifeng 475004China University of Chinese Academy of Sciences(UCAS) Beijing 100049China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117585Singapore Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China Ji Hua Laboratory Foshan 528000China Department of Physics Shanxi Datong UniversityDatong 037009China

Chiral two-dimensional(2D) perovskites offer numerous attractive features for optoelectronics owing to their soft, deformable lattices and a high degree of chemical tunability. While tremendous advances have been made in perovskite-based direct circularly polarized light(CPL) detection, the low circular polarization anisotropy factor and sensitivity of those photodetectors arising from large lattice distortion still limit practical applications. Herein, chiral 2D perovskite-based single-crystalline microwire arrays with enhanced circular dichroism(CD) absorption are fabricated with the synergy of the capillary-bridgeconfined assembly method and chlorine-substituted phenethylamine(Cl-MBA). Compared with phenethylamine(MBA)-inserted perovskites, the smaller lattice distortion and increased halogen–halogen interaction within Cl–MBA-inserted perovskites strengthen lattice rigidity and weaken electron–phonon coupling to improve carrier transport and thermal stability, resulting in high-performance CPL photodetectors with an anisotropy factor of 0.25, responsivity exceeding 95.7±9.3 A W^(-1)and detectivity exceeding(3.05±0.30)×10^(13)Jones. This work opens a new perspective to modulate circular polarization sensitivity and will be helpful to realize promising implementations in quantum computation and communication.

关键词： chiral perovskites microwire arrays lattice rigidity circular polarization photodetectors

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