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Research on conducted emi characteristics of sic mosfet considering temperature effect

Progress In Electromagnetics Research C 2021年 112卷 69-82页

作者： Du, Mingxing Bian, Weiguo Wang, Hongbin Dai, Qiqi Ouyang, Ziwei Tianjin Key Laboratory of Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin300384 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China

—The junction temperature change of SiC MOSFET will change its switching process, and then affect the electromagnetic interference (EMI) characteristics of the system where the device is located and the safe operation of the surrounding equipment. Therefore, it is of great significance to research the temperature dependence of its EMI characteristics. In this paper, a buck converter composed of SiC MOSFET is taken as the research object to study the temperature variation characteristics of the conducted EMI spectrum during the switching process. Combined with the specific circuit connection form of the buck converter, the coupling paths of the conducted EMI are determined, and then the influence mechanisms of temperature change on the differential mode (DM) interference and common mode (CM) interference are analyzed. The theoretical analysis and experimental results show that the DM interference of the buck converter composed of SiC MOSFET increases with the increase of temperature, and the CM interference is almost unaffected by temperature. When the working temperature increases from 25◦C to 145◦C, the peak value of DM voltage increases by 6.7 dBµV, and the peak value of CM voltage changes less than 1.4 dBµV. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Temperature distribution

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Emerging material platforms for integrated microcavity photonics

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Science China(Physics,Mechanics & Astronomy) 2022年第10期65卷 10-28页

作者： Jin Liu Fang Bo Lin Chang Chun-Hua Dong Xin Ou Blake Regan Xiaoqin Shen Qinghai Song Baicheng Yao Wenfu Zhang Chang-Ling Zou Yun-Feng Xiao State Key Laboratory of Optoelectronic Materials and Technologies School of PhysicsSun Yat-sen UniversityGuangzhou 510000China MOE Key Laboratory of Weak-Light Nonlinear Photonics TEDA Institute of Applied Physics and School of PhysicsNankai UniversityTianjin 300071China State Key Laboratory of Advanced Optical Communications System and Networks School of ElectronicsPeking UniversityBeijing 100871China CAS Key Lab of Quantum Information University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Functional Material for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Mathematical and Physical Sciences University of Technology SydneyUltimo 2007Australia School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of TechnologyShenzhen 518055China Key Laboratory of Optical Fiber Sensing and Communications(Ministry of Education) University of Electronic Science and Technology of ChinaChengdu 611731China State Key Laboratory of Transient Optics and Photonics Xi’an Institute of Optics and Precision MechanicsChinese Academy of SciencesXi’an 710119China State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics School of PhysicsPeking UniversityBeijing 100871China

Many breakthroughs in technologies are closely associated with the deep understanding and development of new material *** the main material used in microelectronics,Si also plays a leading role in the development of integrated *** indirect bandgap,absence ofχ(2)nonlinearity and the parasitic nonlinear absorptions at the telecom band of Si imposed technological bottlenecks for further improving the performances and expanding the functionalities of Si microcavities in which the circulating light intensity is dramatically *** past two decades have witnessed the burgeoning of the novel material platforms that are compatible with the complementary metal-oxide-semiconductor(COMS)*** particular,the unprecedented optical properties of the emerging materials in the thin film form have resulted in revolutionary progress in microcavity *** this review article,we summarize the recently developed material platforms for integrated photonics with the focus on chip-scale microcavity *** material characteristics,fabrication processes and device applications have been thoroughly discussed for the most widely used new material *** also discuss open challenges and opportunities in microcavity photonics,such as heterogeneous integrated devices,and provide an outlook for the future development of integrated microcavities.

关键词： microcavity integrated optics nonlinear optics

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Snap-through path in a bistable dielectric elastomer actuator

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Applied Mathematics and Mechanics(English Edition) 2022年第8期43卷 1159-1170页

作者： Wenjie SUN Wentao MA Fei ZHANG Wei HONG Bo LI School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an710048China State Key Laboratory for Strength and Vibration of Mechanical Structures and School of Aerospace Xi’an Jiaotong UniversityXi’an710049China State Key Laboratory for Manufacturing System Engineering Shaanxi Key Lab for Intelligent RobotsSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an710049China Department of Mechanics and Aerospace Engineering Southern University of Science and TechnologyShenzhenGuangdong Province518055China

The dielectric elastomer(DE)has attracted significant attention due to its desired features,including large deformation,fast response,and high energy ***,for a DE actuator(DEA)utilizing a snap-through deformation mode,most existing theoretical models fail to predict its deformation *** paper develops a new finite element method(FEM)based on the three-parameter Gent-Gent model suitable for capturing strain-stiffening *** simulation results are verified by experiments,indicating that the FEM can accurately characterize the snap-through path of a *** method proposed in this paper provides theoretical guidance and inspiration for designing and applying DEs and bistable electroactive actuators.

关键词： dielectric elastomer actuator(DEA) snap-through bistable finite element method(FEM) strain-stiffening behavior

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TMATH: A Dataset for Evaluating Large Language Models in Generating Educational Hints for Math Word Problems 31

TMATH: A Dataset for Evaluating Large Language Models in Gen...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Qi, Changyong Wei, Yuang Xu, Haoxin Zheng, Longwei Chen, Peiji Gu, Xiaoqing Lab of Artificial Intelligence for Education East China Normal University Shanghai China Shanghai Institute of Artificial Intelligence for Education East China Normal University Shanghai China School of Education City University of Macau China State Key Laboratory of Cognitive Intelligence Hefei China The University of Electro-Communications Tokyo Japan Department of Education Information Technology East China Normal University Shanghai China

ISBN: (纸本)9798891761964

Large Language Models (LLMs) are increasingly being applied in education, showing significant potential in personalized instruction, student feedback, and intelligent tutoring. Generating hints for Math Word Problems (MWPs) has become a critical application, particularly in helping students understand problem-solving steps and logic. However, existing models struggle to provide pedagogically sound guidance that fosters learning without offering direct answers. To address this issue, we introduce TMATH, a dataset specifically designed to evaluate LLMs' ability to generate high-quality hints for MWPs. TMATH contains diverse mathematical problems paired with carefully crafted, human-generated hints. To assess its impact, we fine-tuned a series of 7B-scale language models using TMATH. Our results, based on quantitative evaluations and expert assessments, show that while LLMs still face challenges in complex reasoning, the TMATH dataset significantly enhances their ability to generate more accurate and contextually appropriate educational hints. The dataset is available at https://***/qigithub-ui/TMATH. © 2025 Association for Computational Linguistics.

关键词： Students

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An Iterative Min-Min Optimization Method for Sparse Bayesian Learning 41

An Iterative Min-Min Optimization Method for Sparse Bayesian...

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41st International Conference on Machine Learning, ICML 2024

作者： Wang, Yasen Li, Junlin Yue, Zuogong Yuan, Ye School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China School of Mathematics and Statistics Fuyang Normal University Fuyang China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

As a well-known machine learning algorithm, sparse Bayesian learning (SBL) can find sparse representations in linearly probabilistic models by imposing a sparsity-promoting prior on model coefficients. However, classical SBL algorithms lack the essential theoretical guarantees of global convergence. To address this issue, we propose an iterative Min-Min optimization method to solve the marginal likelihood function (MLF) of SBL based on the concave-convex procedure. The method can optimize the hyperparameters related to both the prior and noise level analytically at each iteration by re-expressing MLF using auxiliary functions. Particularly, we demonstrate that the method globally converges to a local minimum or saddle point of MLF. With rigorous theoretical guarantees, the proposed novel SBL algorithm outperforms classical ones in finding sparse representations on simulation and real-world examples, ranging from sparse signal recovery to system identification and kernel regression. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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RLCkt: An Analog Circuit Automatic Sizing Sage Based on Reinforcement Learning

RLCkt: An Analog Circuit Automatic Sizing Sage Based on Rein...

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2023 China Semiconductor technology International Conference, CSTIC 2023

作者： Zuo, Wangge Liu, Lingge Li, Fei Huang, Yifei Zhang, Liqian Wan, Jing Fudan University School of Information Science and Engineering State Key Lab of Asic and System Shanghai200433 China Suzhou Foohu Technology Co. Ltd. Shanghai200433 China

ISBN: (纸本)9798350311006

Automated solutions for sizing analog circuits have gained significant interest due to the labor-intensive nature of the task in a typical design cycle, especially with technology development and circuit scaling. This study introduces the RLCkt, an Analog Circuit Automatic Sizing Sage, which utilizes reinforcement learning (RL) and the SPICE simulator to automatically adjusts design parameters to meet performance metrics. After several hours of training, RLCkt runs 94 times faster than a traditional generic algorithm with comparable performance. Additionally, its generalization capability surpasses that of state-of-the-art methods. © 2023 IEEE.

关键词： Reinforcement learning

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U-DiTs: downsample tokens in U-shaped diffusion transformers 24

U-DiTs: downsample tokens in U-shaped diffusion transformers

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Yuchuan Tian Zhijun Tu Hanting Chen Jie Hu Chao Xu Yunhe Wang State Key Lab of General AI School of Intelligence Science and Technology Peking University Huawei Noah's Ark Lab.

ISBN: (纸本)9798331314385

Diffusion Transformers (DiTs) introduce the transformer architecture to diffusion tasks for latent-space image generation. With an isotropic architecture that chains a series of transformer blocks, DiTs demonstrate competitive performance and good scalability; but meanwhile, the abandonment of U-Net by DiTs and their following improvements is worth rethinking. To this end, we conduct a simple toy experiment by comparing a U-Net architectured DiT with an isotropic one. It turns out that the U-Net architecture only gain a slight advantage amid the U-Net inductive bias, indicating potential redundancies within the U-Net-style DiT. Inspired by the discovery that U-Net backbone features are low-frequency-dominated, we perform token downsampling on the query-key-value tuple for self-attention that bring further improvements despite a considerable amount of reduction in computation. Based on self-attention with downsampled tokens, we propose a series of U-shaped DiTs (U-DiTs) in the paper and conduct extensive experiments to demonstrate the extraordinary performance of U-DiT models. The proposed U-DiT could outperform DiT-XL/2 with only 1/6 of its computation cost. Codes are available at https://***/YuchuanTian/U-DiT.

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Fault-Tolerant Walking and Turning Gait Planning for Quadruped Robots with One Locked Leg on Rough Terrains 23rd

Fault-Tolerant Walking and Turning Gait Planning for Quadrup...

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23rd IFToMM China International Conference on Mechanism and Machine Science and Engineering, IFToMM CCMMS 2022

作者： Chen, Zhijun Gao, Feng Xi, Qingxing Zhao, Yue State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China MoE Key Lab of Artificial Intelligence Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789811993978

Fault-tolerant gaits can effectively improve the reliability and prolong the service life of legged robots in unmanned environments. However, few stability-guaranteed fault-tolerant gaits are available for quadruped robots to traverse rough terrains. This paper proposes a fault-tolerant walking and turning gait planning method for quadruped robots with one locked leg on rough terrains. First, a quadruped robot with serial-parallel leg mechanism is introduced and the inverse kinematics is built. Then, the fault-tolerant gait is designed for both walking and turning. The gait trajectory planning method is proposed for both gaits on rough terrains with slopes and steps. Finally, simulations are carried out to visually illustrate and validate the fault-tolerant gaits. The results prove the correctness of the gaits planning. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Inverse kinematics

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FIRE: a dataset for feedback integration and refinement evaluation of multimodal models 24

FIRE: a dataset for feedback integration and refinement eval...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Pengxiang Li Zhi Gao Bofei Zhang Tao Yuan Yuwei Wu Mehrtash Harandi Yunde Jia Song-Chun Zhu Qing Li Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and State Key Laboratory of General Artificial Intelligence BIGAI State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University State Key Laboratory of General Artificial Intelligence BIGAI Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University Department of Electrical and Computer System Engineering Monash University Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University and Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University and Department of Automation Tsinghua University

ISBN: (纸本)9798331314385

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset.

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HRVDA: High-Resolution Visual Document Assistant

HRVDA: High-Resolution Visual Document Assistant

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Chaohu Liu Kun Yin Haoyu Cao Xinghua Jiang Xin Li Yinsong Liu Deqiang Jiang Xing Sun Linli Xu School of Computer Science and Technology University of Science and Technology of China State Key Laboratory of Cognitive Intelligence Tencent YouTu Lab

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Leveraging vast training data, multimodal large language models (MLLMs) have demonstrated formidable general visual comprehension capabilities and achieved remarkable performance across various tasks. However, their performance in visual document understanding still leaves much room for improvement. This discrepancy is primarily attributed to the fact that visual document understanding is a fine-grained prediction task. In natural scenes, MLLMs typically use low-resolution images, leading to a substantial loss of visual information. Furthermore, general-purpose MLLMs do not excel in handling document-oriented instructions. In this paper, we propose a High-Resolution Visual Document Assistant (HRVDA), which bridges the gap between MLLMs and visual document understanding. This model employs a content filtering mechanism and an instruction filtering module to separately filter out the content-agnostic visual tokens and instruction-agnostic visual tokens, thereby achieving efficient model training and inference for high-resolution images. In addition, we construct a document-oriented visual instruction tuning dataset and apply a multi-stage training strategy to enhance the model's document modeling capabilities. Extensive experiments demonstrate that our model achieves state-of-the-art performance across multiple document understanding datasets, while maintaining training efficiency and inference speed comparable to low-resolution models.

关键词： Training Visualization Computer vision Large language models Computational modeling Training data Transformers

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