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PCA: Semi-Supervised Segmentation with Patch Confidence Adversarial Training

IEEE Transactions on Network Science and engineering 2025年

作者： Xu, Zhenghua Yang, Runhe Xu, Zihang Zhang, Shuo Yang, Yuchen Liu, Weipeng Xu, Weichao Chen, Junyang Lukasiewicz, Thomas Leung, Victor C. M. Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Tianjin China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong The Johns Hopkins University Department of Applied Mathematics and Statistic Baltimore United States Hebei University of Technology School of Artificial Intelligence Tianjin China Hebei Provincial Hospital of Traditional Chinese Medicine Digestive Disease Center Shijiazhuang China Shenzhen University College of Computer Science and Software Engineering Shenzhen China University of Oxford Department of Computer Science University of Oxford United Kingdom Department of Computer Science United Kingdom Vienna University of Technology institute of Logic and Computation nstitute of Logic and Computation Vienna Austria

Deep-learning-based semi-supervised learning (SSL) methods have achieved a strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by utilizing a large amount of unlabeled data. Unlike most existing semi-supervised learning methods, adversarial training methods distinguish samples from different sources by learning the data distribution of the segmentation map, leading the segmenter to generate more accurate predictions. We argue that the current performance restrictions for such approaches are the problems of feature extraction and learning preferences. In this paper, we propose a new semi-supervised adversarial method called Patch Confidence Adversarial Training (PCA) for medical image segmentation. The PCA method's discriminator penalizes patch-level structures, guiding the generator to optimize different patch areas, by leveraging pixel context, the generator is driven to focus on high-frequency features, making it harder to deceive the discriminator and easy to converge to an ideal state, which more effectively guides the segmenter to generate high-quality pseudo-labels. Furthermore, at the discriminator's input, we supplement image information constraints, making it simpler to fit the expected data distribution. Extensive experiments on the Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset and the Brain Tumor Segmentation (BraTS) 2019 challenge dataset show that our method outperforms the state-of-the-art semi-supervised methods, which demonstrates its effectiveness for medical image segmentation. © 2025 IEEE. All rights reserved.

关键词： Adversarial machine learning

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Structural reliability analysis using Conjugate FORM-based Support Vector Regression

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Procedia Structural Integrity 2023年 48卷 356-362页

作者： Mohamed El Amine Ben Seghier Behrooz Keshtegar José A.F.O. Correia Laboratory for Computational Mechanics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Vietnam Faculty of Mechanical - Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City Vietnam Department of Civil Engineering Faculty of Engineering University of Zabol P.B. *** Zabol Iran INEGI Faculty of Engineering University of Porto Rua Dr. Roberto Frias 4200-465 Porto Portugal

Appropriate reliability methods for estimating the failure probability using most efficient and robust properties are crucial in structural reliability analyses of engineering structures. In this paper, an enhanced first-order reliability method (FORM) using conjugate search direction was coupled with artificial intelligence technique called support vector regression (SVR) named as SVR-CFORM for structural reliability analyses of complex limit state functions. The conjugate FORM (CFORM) is formulated using adaptive formulas to search the most probable point to improve the robustness of iterative FORM formula, whereas the SVR is used to predict the performance functions to improve the efficiency of the proposed reliability method. Several FORM formulas such as HL-RF, directional stability transformation method, and finite step length are used to compare the performance of the proposed SVR-CFORM in terms of both efficiency and robustness using different numerical/structural reliability examples. In comparison to other studied FORM formulas, the proposed SVR-CFORM method improves the iterative FORM formulation more efficiently and with more stable results.

关键词： Structural reliability First-order reliability method Support vector regression Conjugate FORM Failure probability

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Butterfly-Accelerated Solution of Coupled Volume Integral and Hydrodynamic Equations

Butterfly-Accelerated Solution of Coupled Volume Integral an...

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USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)

作者： Doolos Aibek Uulu Yang Liu Abdulkadir C. Yucel Hakan Bagci Department of Mathematics and Natural Sciences University of Central Asia (UCA) Naryn Kyrgyzstan Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory Berkeley USA School of Electrical and Electronic Engineering Nanyang Technological University (NTU) Singapore Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9789463968119

ISBN: (纸本)9798350359497

In recent years, advancements in plasmonic devices have enabled the localization of electromagnetic fields at subwavelength scales, contributing to breakthroughs in various scientific and engineering fields (J. C. Ndukaife, et al., ACS Nano, 2014,8,9,9035-9043). These structures are often made of metals and their electric properties are typically represented by the classical Drude model (S. A. Maier, 2007, Springer, New York). As the size of the plasmonic structures approaches the nanoscale, the classical Drude model falls short in explaining the collective movement of free electrons in metals. The interaction between moving charges and the electromagnetic fields can be described by a coupled system of the Maxwell and hydrodynamic equations (X. Zheng, et al., IEEE Trans. Antennas Propag., 2018,66,9, 4759-4771).

关键词： Location awareness Conferences Integral equations Metals Plasmons Hydrodynamics Mathematical models

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USED: Universal Speaker Extraction and Diarization

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2024年 33卷 96-110页

作者： Junyi Ao Mehmet Sinan Yıldırım Ruijie Tao Meng Ge Shuai Wang Yanmin Qian Haizhou Li Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Shenzhen Research Institute of Big Data Shenzhen China Auditory Cognition and Computational Acoustics Lab Department of Computer Science and Engineering and the MoE Key Laboratory of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China

Speaker extraction and diarization are two enabling techniques for real-world speech applications. Speaker extraction aims to extract a target speaker's voice from a speech mixture, while speaker diarization demarcates speech segments by speaker, annotating ‘who spoke when’. Previous studies have typically treated the two tasks independently. In practical applications, it is more meaningful to have knowledge about ‘who spoke what and when’, which is captured by the two tasks. The two tasks share a similar objective of disentangling speakers. Speaker extraction operates in the frequency domain, whereas diarization is in the temporal domain. It is logical to believe that speaker activities obtained from speaker diarization can benefit speaker extraction, while the extracted speech offers more accurate speaker activity detection than the speech mixture. In this paper, we propose a unified model called Universal Speaker Extraction and Diarization (USED) to address output inconsistency and scenario mismatch issues. It is designed to manage speech mixtures with varying overlap ratios and variable number of speakers. We show that the USED model significantly outperforms the competitive baselines for speaker extraction and diarization tasks on LibriMix and SparseLibriMix datasets. We further validate the diarization performance on CALLHOME, a dataset based on real recordings, and experimental results indicate that our model surpasses recently proposed approaches.

关键词： Speech recognition Data mining Training Multitasking Speech enhancement Time-domain analysis Recording Predictive models Particle separators Oral communication

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DPA-2:a large atomic model as a multitask learner

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npj computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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High-speed and low-power molecular dynamics processing unit(MDPU)with ab initio accuracy

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npj computational Materials 2024年第1期10卷 559-568页

作者： Pinghui Mo Yujia Zhang Zhuoying Zhao Hanhan Sun Junhua Li Dawei Guan Xi Ding Xin Zhang Bo Chen Mengchao Shi Duo Zhang Denghui Lu Yinan Wang Jianxing Huang Fei Liu Xinyu Li Mohan Chen Jun Cheng Bin Liang Weinan E Jiayu Dai Linfeng Zhang Han Wang Jie Liu College of Integrated Circuits Hunan UniversityChangsha410082P.R.China College of Electrical and Information Engineering Hunan UniversityChangsha410082P.R.China College of Computer National University of Defense TechnologyChangsha410073P.R.China Department of Physics National University of Defense TechnologyChangsha410073P.R.China DP Technology 100080 BeijingP.R.China AI for Science Institute 100080 BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking University100871 BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking University100871 BeijingP.R.China School of Mathematical Science Peking University100871 BeijingP.R.China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEMCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen361005P.R.China School of Integrated Circuits Peking University100871 BeijingP.R.China Center for Machine Learning Research Peking University100871 BeijingP.R.China Institute of Applied Physics and Computational Mathematics 100088 BeijingP.R.China Greater Bay Area Institute for Innovation Hunan UniversityGuangzhou511300P.R.China Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Molecular dynamics(MD)is an indispensable atomistic-scale computational tool widely-used in various *** the past decades,nearly all ab initio MD and machine-learning MD have been based on the general-purpose central/graphics processing units(CPU/GPU),which are well-known to suffer from their intrinsic“memory wall”and“power wall”***,nowadays MD calculations with ab initio accuracy are extremely time-consuming and power-consuming,imposing serious restrictions on the MD simulation size and *** solve this problem,here we propose a special-purpose MD processing unit(MDPU),which could reduce MD time and power consumption by about 103 times(109 times)compared to state-of-the-art machine-learningMD(ab initio MD)based on CPU/GPU,while keeping ab initio *** significantly-enhanced performance,the proposed MDPU may pave a way for the accurate atomistic-scale analysis of large-size and/or longduration problems which were impossible/impractical to compute before.

关键词： consuming power MDP

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SCORE: A Second-Order Conic Initialization for Range-Aided SLAM

SCORE: A Second-Order Conic Initialization for Range-Aided S...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Alan Papalia Joseph Morales Kevin J. Doherty David M. Rosen John J. Leonard Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology (MIT) Cambridge MA USA Department of Applied Ocean Physics & Engineering Woods Hole Oceanographic Institution Woods Hole MA USA Department of Electrical & Computer Engineering Northeastern University Boston MA USA Department of Math Northeastern University Boston MA USA

We present a novel initialization technique for the range-aided simultaneous localization and mapping (RA-SLAM) problem. In RA-SLAM we consider measurements of point-to-point distances in addition to measurements of rigid transformations to landmark or pose variables. Standard formulations of RA-SLAM approach the problem as non-convex optimization, which requires a good initialization to obtain quality results. The initialization technique proposed here relaxes the RA-SLAM problem to a convex problem which is then solved to determine an initialization for the original, non-convex problem. The relaxation is a second-order cone program (SOCP), which is derived from a quadratically constrained quadratic program (QCQP) formulation of the RA-SLAM problem. As a SOCP, the method is highly scalable. We name this relaxation Second-order COnic RElaxation for RA-SLAM (SCORE). To our knowledge, this work represents the first convex relaxation for RA-SLAM. We present real-world and simulated experiments which show SCORE initialization permits the efficient recovery of quality solutions for a variety of challenging single- and multi-robot RA-SLAM problems with thousands of poses and range measurements.

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2D Ge₂Se₂P₄ Monolayer: A Versatile Photocatalyst for Sustainable Water Splitting

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Journal of Physical Chemistry C 2024年第10期128卷 4245-4257页

作者： Vu, Tuan V. Hieu, Nguyen N. Vo, Dat D. Kartamyshev, A.I. Tong, Hien D. Trinh, Thuat T. Khuong Dien, Vo Haman, Zakaryae Dey, Poulumi Khossossi, Nabil Laboratory for Computational Physics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City 70000 Viet Nam Faculty of Mechanical─Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City 70000 Viet Nam Institute of Research and Development Duy Tan University Da Nang 550000 Viet Nam Faculty of Natural Sciences Duy Tan University Da Nang 550000 Viet Nam Faculty of Engineering Vietnamese-German University Binh Duong 820000 Viet Nam Porelab Department of Chemistry Norwegian University of Science and Technology Høgskoleringen 5 Trondheim 7491 Norway Department of Physics National Cheng Kung University 1 University Road Tainan 70101 Taiwan Laboratoire de Physique des Matèriaux et Modélisations des Systèmes LP2MS Faculty of Sciences Department of Physics Moulay Ismail University Meknes 50050 Morocco Department of Materials Science and Engineering Faculty of Mechanical Engineering Delft University of Technology Mekelweg 2 Delft 2628 CD Netherlands

This study aims to identify photo-/electrocatalysts that can enhance the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR), which are of utmost importance in electro-/photochemical energy systems, such as solar energy, fuel cells, water electrolyzers, or metal-air batteries. Our study focused on investigating the 2D Ge₂Se₂P₄ monolayer and found that it exhibits a bifunctional photocatalyst with a very high solar-to-hydrogen efficiency. The two-dimensional (2D) Ge₂Se₂P₄ monolayer has superior HER activity compared to that of most 2D materials, and it also outperforms the reference catalysts IrO₂(110) and Pt(111) in terms of low overpotential values for ORR and OER mechanisms. Such superior catalytic performance in the 2D Ge₂Se₂P₄ monolayer can be attributed to its electron states, charge transfer process, and suitable band alignments referring to normal hydrogen electrodes. Overall, the study suggests that the Ge₂Se₂P₄ monolayer could be an excellent bifunctional catalyst for advancing photo-/electrochemical energy systems. © 2024 American Chemical Society.

关键词： Energy Evolution reactions Free energy Hydrogen Monolayers

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RETRACTED ARTICLE: A comparative recognition research on excretory organism in medical applications using neural networks

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Multimedia Tools and Applications 2023年 1-2页

作者： K, Vidhya R, Krishna Priya Vidhyalakshmi, M. Ramesh, S. M. L, Bharathi Kshirsagar, Pravin R. Rajaram, A. Tirth, Vineet Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Engineering - Electrical Section University of Technology and Applied Sciences Shinas Campus Sultanate of Oman Department of Electronics and Communication Engineering SRM Institute of Science and Technology Chennai India Department of Signal and Image Processing With Computational Intelligence Saveetha School of Engineering Chennai India Department of Electricals and Electronics Engineering Sathyabama Institute of Science and Technology Chennai India Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur India Department of Electronics and Communication Engineering EGS Pillay Engineering College Nagapattinam India Department of Mechanical Engineering College of Engineering King Khalid University Abha Kingdom of Saudi Arabia

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Two-dimensional Closed-Form Analytical Model of Laterally-Excited Film Bulk Acoustic Wave Resonator Multiferroic Antennas

arXiv

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arXiv 2024年

作者： Ippet-Letembet, Louis-Charles Xu, Rui-Fu Jeanty, Robin Yao, Zhi Candler, Robert N. Chen, Shih-Yuan Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States California NanoSystems Institute Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan

To overcome the physical limitations of electrically small antennas, strain-mediated magnetoelectric antennas have been studied experimentally and theoretically. However, current closed-form analytical models include solely one-dimensional approaches. This paper proposes a two-dimensional closed-form analytical model of a laterally-excited multiferroic antenna. To model thickness-shear vibrations, we propose an extended Mason model to two dimensions. This theory solves unidirectionally-coupled elastodynamics-magnetization dynamics-electrodynamics. Without using the infinitesimal dipole approximation, this model provides a closed-form solution of the radiated electromagnetic field with an explicit dependency of the antenna response on the physical parameters, enabling their optimization. Furthermore, we compare the efficiency-bandwidth product of different multiferroic antennas with Chu’s limit in the Akhiezer regime, which delimits the highest achievable mechanical quality factor for acoustic resonators at GHz frequencies. We show that phonon-phonon coupling of Akhiezer damping is most likely to limit multiferroic antenna radiation, not Chu’s limit. Moreover, judicious choice of materials can enhance the maximum efficiency by more than an order of magnitude. Copyright © 2024, The Authors. All rights reserved.

关键词： Analytical models

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