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arXiv 2024年

作者： Wang, Zhiyuan Duan, Jinhao Yuan, Chenxi Chen, Qingyu Chen, Tianlong Zhang, Yue Wang, Ren Shi, Xiaoshuang Xu, Kaidi Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China Department of Computer Science Drexel University PhiladelphiaPA19104 United States Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States Section of Biomedical Informatics & Data Science Yale School of Medicine Yale University New HavenCT06510 United States Computer Science & Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

Uncertainty estimation is crucial for the reliability of safety-critical human and artificial intelligence (AI) interaction systems, particularly in the domain of healthcare engineering. However, a robust and general uncertainty measure for free-form answers has not been well-established in open-ended medical question-answering (QA) tasks, where generative inequality introduces a large number of irrelevant words and sequences within the generated set for uncertainty quantification (UQ), which can lead to biases. This paper introduces Word-Sequence Entropy (WSE), a method that calibrates uncertainty at both the word and sequence levels, considering semantic relevance. WSE quantifies uncertainty in a way that is more closely aligned with the reliability of LLMs during uncertainty quantification (UQ). We compare WSE with six baseline methods on five free-form medical QA datasets, utilizing seven popular large language models (LLMs). Experimental results demonstrate that WSE exhibits superior performance in UQ under two standard criteria for correctness evaluation. Additionally, in terms of real-world medical QA applications, the performance of LLMs is significantly enhanced (e.g., a 6.36% improvement in model accuracy on the COVID-QA dataset) by employing responses with lower uncertainty that are identified by WSE as final answers, without any additional task-specific fine-tuning or architectural modifications. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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Research on Biomimetic Design Methods for Humanoid Robot Thigh*

Research on Biomimetic Design Methods for Humanoid Robot Thi...

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IEEE International Conference on Robotics and Biomimetics

作者： Daming Nie Anhuan Xie Lingyu Kong Yu Zhang Gang Zheng Yili Fu Jason Gu Intelligent Robot Research Center Zhejiang Laboratory Hangzhou China School of Mechanical and Energy Engineering Zhejiang University of Science and Technology Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human’s longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of "variable thickness shell + variable density lattice". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of "stress - shell thickness" and "stress - lattice rod diameter", while the structural stiffness meets the application requirements. Finally, the limiting factors of the "variable thickness shell + variable density lattice" structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described.

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An optimal power supervising strategy for a smart home assessed based on BPMN Framework

An optimal power supervising strategy for a smart home asses...

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International Conference on sciences and Techniques of Automatic Control and computer engineering (STA)

作者： Leila Lanouar Mouna Rekik Olfa Bouchaala Lotfi Krichen Multimédia & Web Department University of Gabes Higher Institute of Computer Science and Multimedia of Gabes (ISIMG) Gabes Tunis Electrical Engineering Department Electrical systems and renewable energies Laboratory (LSEER) University of Sfax University of Gabes National Engineering School of Sfax (ENIS) Higher Institute of Computer Science and Multimedia of Gabes (ISIMG) Sfax Gabes Tunis Department of Computer Engineering and Applied Mathematics Research Laboratory on Development and Control and Distributed Applications (ReDCAD) University of Sfax National Engineering School of Sfax (ENIS) Sfax Tunis Electrical Engineering Department Electrical systems and renewable energies Laboratory (LSEER) University of Sfax National Engineering School of Sfax (ENIS) Sfax Tunis

ISBN: (纸本)9781665482622

For each smart home, the need of energy consumption supervision is necessary, which plays an important role to ensure the highest power quality and to enhance the stability of the whole grid. The current document implements a smart home supply strategy based on endless resources to reduce the electricity bill and confirm the energy balance. In this context, a proposed supervision algorithm operates in eight cases to reach optimal energy flow between renewable generators, home battery and grid in a smart home concept is presented. The system is evaluated using the framework “Business Process Model and Notation” (BPMN) Camunda basing on information stored in Firebase Cloud and results are presented in order to manifest the efficiency of this control strategy.

关键词： Renewable energy sources Energy consumption Power quality Process control Smart homes Power system stability Stability analysis

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Movable Antenna-Aided Hybrid Beamforming for Multi-User Communications

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IEEE Transactions on Vehicular Technology 2025年

作者： Zhang, Yichi Zhang, Yuchen Zhu, Lipeng Xiao, Sa Tang, Wanbin Eldar, Yonina C. Zhang, Rui University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Electronic Science and Technology of China National Key Laboratory of Science and Technology on Communications Chengdu611731 China Kash Institute of Electronics and Information Industry Kash844000 China Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot7610001 Israel National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore Chinese University of Hon g Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen518172 China

In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of sub-arrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array. © 1967-2012 IEEE.

关键词： Budget control

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Bonding and Failure Mechanisms of Sintered-silver Die-attach on Electroless Nickel (Phosphorus) Surface Finish for Packaging Power Electronics Modules

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IEEE Transactions on Power Electronics 2024年

作者： Wang, Meiyu Zhang, Haobo Hu, Weibo Mei, Yunhui Lu, Guo-Quan Nankai University College of Electronic Information and Optical Engineering Tianjin300350 China Shenzhen research institute of Nankai University Shenzhen518083 China Nankai University Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin300350 China Tiangong University School of Electrical Engineering Tianjin300387 China The Bradley Department of Electrical and Computer Engineering The Department of Materials Science and Engineering BlacksburgVA24061 United States

The low-temperature silver sintering technology has been increasingly applied for die-attach in power electronics modules. Most reported studies of the technology involved bonding on silver (Ag) or gold (Au) surface finish. Compared to Ag or Au, electroless nickel (phosphorus) or Ni(P) is a cost-effective and widely-used process for surface-finishing module substrates. However, there is a lack of studies on sintered-Ag bonding on the Ni(P) surface. In this study, IGBT devices were bonded using pressureless Ag-sintering on electroless Ni(P)-plated substrates. Micro-morphologies and macro-properties were then characterized before and after three reliability tests including high temperature storage life (HTSL), steady-state temperature-humidity bias life (STHBL), and temperature cycling (TC) tests. The as-sintered joints measured strong adhesion of 39 MPa, resulting from Ag-NiO-Ni chemical bonds across the (111) crystal planes with reduced lattice misfit. The Ag-Ni(P) joints exhibited high reliability under high-temperature and thermo-mechanical stress in the HTSL and TC tests, but performed poorly when exposed to high humidity in the STHBL test. The founding in this study helps understand the physical nature of bonding between sintered-Ag and Ni(P), and its failure mechanisms under the influence of different physical stresses. © 1986-2012 IEEE.

关键词： Bond strength (chemical)

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Peachy Parallel Assignments (EduHPC 2022)

Peachy Parallel Assignments (EduHPC 2022)

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Workshop on Education for High Performance Computing (EduHPC)

作者： Rocío Carratalá-Sáez Arturo Gonzalez-Escribano Alexandros-Stavros Iliopoulos Charles E. Leiserson Charlotte Park Isabel Rosa Tao B. Schardl Yuri Torres David P. Bunde Departamento de Informática Universidad de Valladolid Valladolid Spain Department of Electrical Engineering and Computer Science Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Knox College Galesburg IL USA

ISBN: (纸本)9781665473675

Peachy Parallel Assignments are model assignments for teaching parallel computing concepts. They are competitively selected for being adoptable by other instructors and “cool and inspirational” for students. Thus, they allow instructors to easily add high-quality assignments that will engage students to their classes. This group of Peachy assignments features two new assign-ments. The first has students speed up a graphical n-body simulation by identifying performance bottlenecks, making algorithmic improvements, and parallelizing the program using OpenCilk. The second has them parallelize a Monte Carlo hill climbing algorithm using one or more of OpenMP, MPI, and CUDA or OpenCL.

关键词： Monte Carlo methods Computational modeling High performance computing Conferences Education Graphics processing units Parallel processing

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Role of Mixup in Topological Persistence Based Knowledge Distillation for Wearable Sensor Data

arXiv

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arXiv 2025年

作者： Jeon, Eun Som Choi, Hongjun Buman, Matthew P. Turaga, Pavan Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of Lawrence Livermore National Laboratory LivermoreCA94550 United States College of Health Solutions Arizona State University PhoenixAZ85004 United States Geometric Media Lab School of Arts Media and Engineering School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States

The analysis of wearable sensor data has enabled many successes in several applications. To represent the high-sampling rate time-series with sufficient detail, the use of topological data analysis (TDA) has been considered, and it is found that TDA can complement other time-series features. Nonetheless, due to the large time consumption and high computational resource requirements of extracting topological features through TDA, it is difficult to deploy topological knowledge in machine learning and various applications. In order to tackle this problem, knowledge distillation (KD) can be adopted, which is a technique facilitating model compression and transfer learning to generate a smaller model by transferring knowledge from a larger network. By leveraging multiple teachers in KD, both time-series and topological features can be transferred, and finally, a superior student using only time-series data is distilled. On the other hand, mixup has been popularly used as a robust data augmentation technique to enhance model performance during training. Mixup and KD employ similar learning strategies. In KD, the student model learns from the smoothed distribution generated by the teacher model, while mixup creates smoothed labels by blending two labels. Hence, this common smoothness serves as the connecting link that establishes a connection between these two methods. Even though it has been widely studied to understand the interplay between mixup and KD, most of them are focused on image based analysis only, and it still remains to be understood how mixup behaves in the context of KD for incorporating multimodal data, such as both time-series and topological knowledge using wearable sensor data. In this paper, we analyze the role of mixup in KD with time-series as well as topological persistence, employing multiple teachers. We present a comprehensive analysis of various methods in KD and mixup, supported by empirical results on wearable sensor data. We observe that app

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Effect of temperature oscillations on kinetic inductance and depairing in thin and narrow superconducting nanowire resonators

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Physical Review B 2023年第10期107卷 104520-104520页

作者： Jason P. Allmaras Alexander G. Kozorezov Marco Colangelo Boris A. Korzh Matthew D. Shaw Karl K. Berggren Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA Department of Physics Lancaster University Lancaster LA1 4YB United Kingdom Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02138 USA

Recent experiments have demonstrated a method for extracting the depairing current of nanowires fabricated from thin-film dirty superconductors using the AC response of DC-current biased resonators. While the existing theoretical model for understanding this response, developed by Clem and Kogan, provides agreement with Eilenberger-Usadel theory at low temperatures, there is a systematic and substantial deviation from theory at elevated temperatures. We propose that the DC bias in the presence of electromagnetic oscillations leads to Joule heating in the superconductor. This heating, combined with the strong electron-electron scattering in these heavily disordered materials, leads to oscillations in the effective temperature of the superconductor which alter the kinetic inductance. In this work, we derive the expression for the shift in kinetic inductance in the presence of a bias current and demonstrate that this model provides a significantly improved agreement between experiment and theory.

关键词： Nanowires Superconducting devices Type-II superconductors

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Deterministic Self-Adjusting Tree Networks Using Rotor Walks

arXiv

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arXiv 2022年

作者： Avin, Chen Bienkowski, Marcin Salem, Iosif Sama, Robert Schmid, Stefan Schmidt, Pawel School of Electrical and Computer Engineering Ben Gurion University of the Negev Israel Institute of Computer Science University of Wroclaw Poland Department of Telecommunication Systems TU Berlin Germany Faculty of Computer Science University of Vienna Austria University of Vienna Austria

We revisit the design of self-adjusting single-source tree networks. The problem can be seen as a generalization of the classic list update problem to trees, and finds applications in reconfigurable datacenter networks. We are given a balanced binary tree T connecting n nodes V = {v1,..., vn}. A source node v0, attached to the root of the tree, issues communication requests to nodes in V, in an online and adversarial manner;the access cost of a request to a node v, is given by the current depth of v in T. The online algorithm can try to reduce the access cost by performing swap operations, with which the position of a node is exchanged with the position of its parent in the tree;a swap operation costs one unit. The objective is to design an online algorithm which minimizes the total access cost plus adjustment cost (swapping). Avin et al. [11] (LATIN 2020) recently presented Random-Push, a constant competitive online algorithm for this problem, based on random walks, together with a sophisticated analysis exploiting the working set property. This paper studies analytically and empirically, online algorithms for this problem. In particular, we explore how to derandomize Random-Push. In the analytical part, we consider a simple derandomized algorithm which we call Rotor-Push, as its behavior is reminiscent of rotor walks. Our first contribution is a proof that Rotor-Push is constant competitive: its competitive ratio is 12 and hence by a factor of five lower than the best existing competitive ratio. Interestingly, in contrast to Random-Push, the algorithm does not feature the working set property, which requires a new analysis. We further present a significantly improved and simpler analysis for the randomized algorithm, showing that it is 16-competitive. In the empirical part, we compare all self-adjusting single-source tree networks, using both synthetic and real data. In particular, we shed light on the extent to which these self-adjusting trees can exploit tempora

关键词： Binary trees

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DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network

DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatia...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Shaokun Zhang Xinde Li Chuanfei Hu Jianping Xu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Science and Technology on Information Systems Engineering Laboratory Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Recent transformer-based methods for estimating 3D human pose have gained widespread attention, achieving state-of-the-art results. Previous methods have primarily focused on capturing motion patterns of the human body at a single scale or cascading multiple scales, such as joints, bones, and body-parts. However, they are difficult to simultaneously capture spatial-temporal motion patterns of the human body at different scales due to the complex motion patterns. To address this issue, we propose Dual-scale Spatial and Temporal transFormer (DSTFormer), which can concurrently explore the spatial dependencies and temporal motion patterns of human joints and bones. Additionally, we introduce a Gcn-Spatial Transformer Block (GSTB), which introduces Graph Convolutional Networks (GCN) into transformer to enhance the exploitation of local relationships and global information between adjacent joints or bones. Extensive experiments are conducted on the Human3.6M benchmark dataset, and superior results are reported when comparing to other state-of-the-art methods. More remarkably, our model achieves to-date the best published performance, with P1 errors of 37.9 mm and 15.6 mm, respectively.

关键词： Solid modeling Three-dimensional displays Mechatronics Graph convolutional networks Computational modeling Pose estimation Transformers Bones Joints Robots

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