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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Sundaramoorthy Sridhar Qiang Li The Bradley Department of Electrical and Computer Engineering Center for Power Electronic Systems Virginia Tech Blacksburg VA USA

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

High-current processor core voltage regulators (VRs) use current-mode constant on-time (COT) control to simplify phase interleaving and achieve high control bandwidth. Reducing VR bus voltage and increasing phase count results in steady-state phase overlapping within their operating duty range. With phase overlap, a smaller external ramp reduces the inner current loop stability margin and introduces large magnitude peaks in control-to-output response. These peaks could lead to double crossover, reduce gain margin, and make high-bandwidth outer voltage loop unstable in phase overlapping regions. Increasing the ramp damps these peaks and improves the gain margin but reduces the phase margin at the target bandwidth. Hence, this paper simplifies infinite-order describing function model and provides external ramp design guidelines to attain desired stability margin at the target bandwidth. The simplified model and small-signal analysis are validated using SIMPLIS simulation and experiments from a six-phase current-mode COT buck converter.

关键词： Regulators Design methodology Transfer functions Process control Bandwidth Stability analysis Resonance Power electronics Steady-state Voltage control

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Soft Sensory Socks Measure Contact Forces During Locomotion

Soft Sensory Socks Measure Contact Forces During Locomotion

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IEEE/SICE International Symposium on System Integration

作者： John Nassour Jan-Erik Hühne Jin-Ho Lee Gordon Cheng Department of Electrical and Computer Engineering Chair for Cognitive Systems Technische Universität München Munich Germany

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Gait monitoring systems play a crucial role in guiding rehabilitation, improving athletic performance, preventing injuries, and ensuring overall mobility and quality of life. Most of these systems are restricted to specialized setups and require calibrations. We propose a soft sensor design using silicone tubes mounted on the bottom side of socks to measure ground reaction force (GRF) during locomotion. Three sensors were mounted on the socks’ anterior, lateral, and posterior areas on the left and right feet. The sensory socks enable the analysis of gait while walking and running at different speeds while wearing shoes and also barefoot. The proposed soft sensory socks open the door to analyzing locomotion in different environments and also barefoot. Preliminary gait analyses confirm the different gait parameters observed in the biomechanics of barefoot locomotion.

关键词： Legged locomotion Force measurement Soft sensors Force Footwear System integration Gait recognition Monitoring Injuries Foot

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Material-Driven Mechanical Programming of Soft Robotic Tentacles

Material-Driven Mechanical Programming of Soft Robotic Tenta...

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IEEE/SICE International Symposium on System Integration

作者： Yao Lu Asmaa Amraouza Yifei Peng Dan Li John Nassour Gordon Cheng Department of Electrical and Computer Engineering Chair for Cognitive Systems Technische Universität München Munich Germany

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Soft robotic grippers with stochastic and topological grasping capabilities can be highly desirable for gentle contact and interaction with fragile objects of various shapes. In this study, we developed soft tentacles using silicon elastomeric material with an embedded pneumatic channel, which generates desirable three-dimensional (3D) curling deformation under pneumatic pressure. Additionally, various ratios and geometrical distributions of two silicon materials, which differ primarily in stiffness, were investigated to determine their effect on grasping efficiency. The tentacle's grasping performance was systematically tested across multiple tentacle designs and grasping strategies. Results showed that optimizing the combination of softer elastomers with stiffer materials significantly improved the tentacle's ability to securely grip and carry loads while maintaining gentle contact with objects (up to 5 kg). The pneumatic tentacle's simple control mechanism and versatility in handling objects of various shapes and sizes offer a low-cost, adaptable solution for future applications in soft robotics.

关键词： Three-dimensional displays Shape Deformation Grasping Elastomers System integration Soft robotics Skin Silicon Filling

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MIRAM: Masked Image Reconstruction Across Multiple Scales for Breast Lesion Risk Prediction

arXiv

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arXiv 2025年

作者： Vo, Hung Q. Yuan, Pengyu Yin, Zheng Wong, Kelvin K. Ezeana, Chika F. Ly, Son T. Wong, Stephen T.C. Nguyen, Hien V. Department of Electrical and Computer Engineering University of Houston United States Systems Medicine and Biomedical Engineering Houston Methodist United States

Self-supervised learning (SSL) has garnered substantial interest within the machine learning and computer vision communities. Two prominent approaches in SSL include contrastive-based learning and self-distillation utilizing cropping augmentation. Lately, masked image modeling (MIM) has emerged as a more potent SSL technique, employing image inpainting as a pretext task. MIM creates a strong inductive bias toward meaningful spatial and semantic understanding. This has opened up new opportunities for SSL to contribute not only to classification tasks but also to more complex applications like object detection and image segmentation. Building upon this progress, our research paper introduces a scalable and practical SSL approach centered around more challenging pretext tasks that facilitate the acquisition of robust features. Specifically, we leverage multi-scale image reconstruction from randomly masked input images as the foundation for feature learning. Our hypothesis posits that reconstructing high-resolution images enables the model to attend to finer spatial details, particularly beneficial for discerning subtle intricacies within medical images. The proposed SSL features help improve classification performance on the Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) dataset. In pathology classification, our method demonstrates a 3% increase in average precision (AP) and a 1% increase in the area under the receiver operating characteristic curve (AUC) when compared to state-of-the-art (SOTA) algorithms. Moreover, in mass margins classification, our approach achieves a 4% increase in AP and a 2% increase in AUC. © 2025, CC BY-NC-SA.

关键词： Self-supervised learning

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Accelerating OTA Circuit Design: Transistor Sizing Based on a Transformer Model and Precomputed Lookup Tables

Accelerating OTA Circuit Design: Transistor Sizing Based on ...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Subhadip Ghosh Endalk Y. Gebru Chandramouli V. Kashyap Ramesh Harjani Sachin S. Sapatnekar Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN USA Cadence Design Systems Portland OR USA

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Device sizing is crucial for meeting performance specifications in operational transconductance amplifiers (OTAs), and this work proposes an automated sizing framework based on a transformer model. The approach first leverages the driving-point signal flow graph (DP-SFG) to map an OTA circuit and its specifications into transformer-friendly sequential data. A specialized tokenization approach is applied to the sequential data to expedite the training of the transformer on a diverse range of OTA topologies, under multiple specifications. Under specific performance constraints, the trained transformer model is used to accurately predict DP-SFG parameters in the inference phase. The predicted DP-SFG parameters are then translated to transistor sizes using a precomputed look-up table-based approach inspired by the 9m / I d methodology. In contrast to previous conventional or machine-learning-based methods, the proposed framework achieves significant improvements in both speed and computational efficiency by reducing the need for expensive SPICE simulations within the optimization loop; instead, almost all SPICE simulations are confined to the one-time training phase. The method is validated on a variety of unseen specifications, and the sizing solution demonstrates over 90% success in meeting specifications with just one SPICE simulation for validation, and 100% success with 3–5 additional SPICE simulations.

关键词： Training Computational modeling Transformers SPICE Tokenization Topology Computational efficiency Transistors Integrated circuit modeling Transconductance

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HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach

arXiv

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arXiv 2025年

作者： Hossain, Abrar Badawy, Abdel-Hameed A. Islam, Mohammad A. Patki, Tapasya Ahmed, Kishwar Department of Electrical Engineering and Computer Science The University of Toledo United States Department of Electrical and Computer Engineering New Mexico State University United States Department of Computer Science and Engineering The University of Texas Arlington United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory

The growing necessity for enhanced processing capabilities in edge devices with limited resources has led us to develop effective methods for improving high-performance computing (HPC) applications. In this paper, we introduce LASP (Lightweight Autotuning of Scientific Application Parameters), a novel strategy designed to address the parameter search space challenge in edge devices. Our strategy employs a multi-armed bandit (MAB) technique focused on online exploration and exploitation. Notably, LASP takes a dynamic approach, adapting seamlessly to changing environments. We tested LASP with four HPC applications: Lulesh, Kripke, Clomp, and Hypre. Its lightweight nature makes it particularly well-suited for resource-constrained edge devices. By employing the MAB framework to efficiently navigate the search space, we achieved significant performance improvements while adhering to the stringent computational limits of edge devices. Our experimental results demonstrate the effectiveness of LASP in optimizing parameter search on edge devices. © 2025, CC BY-NC-ND.

关键词： Edge computing

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Symbiotic Control of Uncertain Dynamical systems: Harnessing Synergy Between Fixed-Gain Control and Adaptive Learning Architectures

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IEEE Transactions on Automatic Control 2025年

作者： Yucelen, Tansel Sarsilmaz, Selahattin Burak Yildirim, Emre University of South Florida Department of Mechanical Engineering Laboratory for Autonomy Control Information and Systems TampaFL33620 United States Utah State University Department of Electrical and Computer Engineering LoganUT84322 United States

Both fixed-gain control and adaptive learning architectures aim to mitigate the effects of uncertainties. In particular, fixed-gain control offers more predictable closed-loop system behavior but requires the knowledge of uncertainty bounds. In contrast, while adaptive learning does not necessarily require such knowledge, it often results in less predictable closed-loop system behavior compared to fixed-gain control. To this end, this paper presents a novel symbiotic control framework that offers the strengths of fixed-gain control and adaptive learning architectures. Specifically, this framework synergistically integrates these architectures to mitigate the effects of uncertainties in a more predictable manner as compared to adaptive learning alone and it does not require any knowledge on such uncertainties. Both parametric and nonparametric uncertainties are considered, where we utilize neural networks to approximate the unknown uncertainty basis for the latter case. Counterintuitively, the proposed framework has the ability to achieve a desired level of closed-loop system behavior even with an insufficient number of neurons (e.g., when the neural network approximation error is large) or in the face of injudiciously selected adaptive learning parameters (e.g., high leakage term parameters). © 1963-2012 IEEE.

关键词： Closed loop control systems

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MEMS-based twisted bilayer flat optics for multidimensional optical modulation and hyperimaging 14

MEMS-based twisted bilayer flat optics for multidimensional ...

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High Contrast Metastructures XIV 2025

作者： Tang, Haoning Lou, Beicheng Du, Fan Gao, Guangqi Zhang, Mingjie Ni, Xueqi Yacoby, Amir Cao, Yuan Fan, Shanhui Mazur, Eric School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States

Our MEMS-based twistoptics device enables precise control of interlayer gaps and twist angles in photonic crystals, offering high-accuracy, multidimensional light manipulation. This finding holds potential for applica... 详细信息

ISBN: (纸本)9781510685048

关键词： Nanophotonics

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Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

引用

IEEE Transactions on Power systems 2025年

作者： Zhou, Yuqi Zhu, Hao National Renewable Energy Laboratory Power Systems Engineering Center GoldenCO80401 United States The University of Texas Chandra Family Department of Electrical & Computer Engineering AustinTX78712 United States

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations. © 1969-2012 IEEE.

关键词： Decentralized control

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GLOW-ENV: A Dual-Data IoE-Based Approach for Integrating Glucose and Environmental Data into a Diabetes Recommendation System

GLOW-ENV: A Dual-Data IoE-Based Approach for Integrating Glu...

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18th International Joint Conference on Biomedical engineering systems and Technologies, BIOSTEC 2025

作者： Gaitán-Guerrero, Juan F. Martínez-Cruz, Carmen López, José L. Mata-Mata, Francisco Pérez-Cordón, Luis G. Serrano, José-María Morcillo-Martínez, Juana M. Verdejo-Espinosa, Ángeles Cuevas-Martínez, Juan C. Viciana-Abad, Raquel Reche-López, Pedro J. Pérez-Lorenzo, José M. Díaz-Jiménez, David Espinilla, Macarena Department of Computer Science University of Jaén Jaén23071 Spain Department of Languages and Computer Systems University of Granada Granada18071 Spain Psycology Department Faculty of Social Work University of Jaén Jaén23071 Spain Electrical Engineering Department University of Jaén Jaén23071 Spain Telecommunication Engineering Department University of Jaén Jaén23071 Spain

This paper introduces GLOW-ENV, an intelligent Internet of Everything (IoE)-driven mobile application designed with the objective of integrating real-time glucose monitoring data and environmental metrics to enhance diabetes care and management. The proposed IoE ecosystem integrates a continuous glucose monitoring with a personalized Artificial Intelligence model designed to predict glycemic fluctuations in a near-future. Additionally, GLOW-ENV integrates a rule-based recommendation system to dynamically adapt its suggestions based on contextual glucose and environmental data. This framework advances personalized diabetes care, contributing to their progression and well-being offering valuable insights and improving decision-making. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Electronic health record

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