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arXiv 2023年

作者： Li, Chenming Zhang, Daoan Huang, Wenjian Zhang, Jianguo Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Peng Cheng Laboratory Shenzhen China

Domain generalization (DG) aims to learn a robust model from source domains that generalize well on unseen target domains. Recent studies focus on generating novel domain samples or features to diversify distributions complementary to source domains. Yet, these approaches can hardly deal with the restriction that the samples synthesized from various domains can cause semantic distortion. In this paper, we propose an online one-stage Cross Contrasting Feature Perturbation (CCFP) framework to simulate domain shift by generating perturbed features in the latent space while regularizing the model prediction against domain shift. Different from the previous fixed synthesizing strategy, we design modules with learnable feature perturbations and semantic consistency constraints. In contrast to prior work, our method does not use any generative-based models or domain labels. We conduct extensive experiments on a standard DomainBed benchmark with a strict evaluation protocol for a fair comparison. Comprehensive experiments show that our method outperforms the previous state-of-the-art, and quantitative analyses illustrate that our approach can alleviate the domain shift problem in out-of-distribution (OOD) scenarios. https://***/hackmebroo/CCFP Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Dubins Vehicle Intercept of a Brownian Target on a Sphere

Dubins Vehicle Intercept of a Brownian Target on a Sphere

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IEEE Conference on Decision and Control

作者： Dejan Milutinović David W. Casbeer Department of Electrical and Computer Engineering University of California Santa Cruz CA USA Control Science Center Air Force Research Laboratory Wright-Patterson AFB OH USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper focuses on a navigation of a Dubins vehicle (DV) to intercept a moving target on a sphere. The uncertainty in the target motion is described by a Brownian motion model. An Itô-type stochastic differential equation for the relative motion between DV and the Brownian moving target is derived. This stochastic differential equation is used to formulate an intercept controller as a minimum time optimal controller. The properties of the controller are incorporated into the numerical computations of the controller, which by its construction can intercept a Brownian target. Our numerical simulation results show that the computed controller can intercept both stationary and moving targets on the sphere.

关键词： Space vehicles Uncertainty Planets Space debris Stochastic processes Optimal control Differential equations Satellite navigation systems Numerical simulation Numerical models

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Modeling and Optimization of a Through-Metal Acoustic Wireless Power Transfer System

Modeling and Optimization of a Through-Metal Acoustic Wirele...

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IEEE Workshop on computers in Power Electronics

作者： Kody Froehle Daniel Costinett Sarah S. Bedair Victor Farm-Guoo Tseng Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA U.S. Army Combat Capabilities Development Command Army Research Laboratory USA

ISBN: (数字)9798350307238

ISBN: (纸本)9798350307245

This paper presents the design of a through-metal acoustic wireless power transfer (AWPT) system using piezoelectric transducers (PT) as transmitter (TX) and receiver (RX). An equivalent circuit model using measured impedance parameters is used to model the complete PT-to-PT electromechanical conversion. The system is designed by sweeping frequency, load resistance, and compensation design to maximize transferred power. Boundary constraints are presented based on temperature and voltage limits the PTs can withstand. An optimal design staying within the operating bounds is then chosen and tested in hardware. The designed system is fabricated and verified experimentally for varying voltage levels. The prototype system has been tested up to 160 V dc input and 41 W output.

关键词： Temperature measurement Voltage measurement Transmitters Prototypes Wireless power transfer Thermal management Acoustics

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Triple Point Masking

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IEEE Transactions on circuits and systems for Video Technology 2025年

作者： Liu, Jiaming Kong, Linghe Wu, Yue Gong, Maoguo Li, Hao Miao, Qiguang Ma, Wenping Qin, Can The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Computer Science and Technology Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China The School of Electronic Engineering Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China The College of Mathematics Science Inner Mongolia Normal University Hohhot010022 China The School of Artificial Intelligence Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education Xidian University Xi’an710071 China The Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

Existing 3D mask learning methods encounter performance bottlenecks under limited data, and our objective is to overcome this limitation. In this paper, we introduce a triple point masking scheme, named TPM, which serves as a scalable plug- and-play framework for MAE pre-training to achieve multi-mask learning for 3D point clouds. Specifically, we augment the baseline methods with two additional mask choices (i.e., medium mask and low mask) as our core insight is that the recovery process of an object can manifest in diverse ways. Previous high-masking schemes focus on capturing the global representation information but lack fine-grained recovery capabilities, so that the generated pre-training weights tend to play a limited role in the fine-tuning process. With the support of the proposed TPM, current methods can exhibit more flexible and accurate completion capabilities, enabling the potential autoencoder in the pre-training stage to consider multiple representations of a single 3D point cloud object. In addition, during the fine-tuning stage, an SVM-guided weight selection module is proposed to fill the encoder parameters for downstream networks with the optimal weight, maximizing linear accuracy and facilitating the acquisition of intricate representations for new objects. Extensive experimental results and theoretical analysis show that five baselines equipped with the proposed TPM achieve comprehensive performance improvements on various downstream tasks. © 2025 IEEE. All rights reserved.

关键词： 3D modeling

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Inverse Design of Multiple-Input Multiple-Output Perfectly-Matched Metamaterials

Inverse Design of Multiple-Input Multiple-Output Perfectly-M...

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International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： Shrey Thakkar Jorge Ruiz-Garcia Luke Szymanski Gurkan Gok Anthony Grbic Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA MIT Lincoln Laboratory Lexington USA RTX Technology Research Centre East Hartford USA

ISBN: (数字)9781733509671

ISBN: (纸本)9798350362978

Inverse design has been applied to a variety of complex electromagnetic structures including multifunctional and multiple-input multiple-output (MIMO) devices, where analytical design methods are limiting. We have previously reported on the inverse design of single-input, single-output Perfectly-Matched Metamaterials (PMMs). PMMs are inhomogeneous, anisotropic 2D metamaterials composed of unit cells that remain impedance-matched to each other and the surroundings under all excitations. PMMs rely primarily on refractive effects and exhibit broadband operation. This work presents the inverse design of a compact MIMO device based on PMMs: a 2D beamformer with prescribed amplitude and phase profiles that exhibits zero scan loss.

关键词： Limiting Design methodology Anisotropic Nonhomogeneous media Computational electromagnetics Metamaterials Broadband communication

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A Comparative Analysis of SiC MOSFET Performance in a Traction Inverter

A Comparative Analysis of SiC MOSFET Performance in a Tracti...

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IEEE Asia-Pacific Conference on circuits and systems

作者： Chih-Chiang Wu Uma Sankar Rout Yu-Long Wang Yi-Ling Lin Jwu-Sheng Hu Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu R.O.C. Department of Electrical Engineering&Computer Science National Yang Ming Chiao Tung University

ISBN: (数字)9798350378771

ISBN: (纸本)9798350378788

This study rigorously tests and verifies silicon carbide (SiC) power modules within a developed 800 V electric vehicle traction inverter. SiC traction inverters offer high efficiency, power density, and compact size. The developed SiCbased traction inverter is thoroughly evaluated on the established platform with various switching frequency, achieving a peak drive efficiency exceeding 98% at 6 kHz and a power density of $50 \mathrm{~kW} / \mathrm{L}$.

关键词： Power system measurements MOSFET Silicon carbide Density measurement circuits and systems Switching frequency Asia Multichip modules Electric vehicles Inverters

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Energy-Efficient Federated Learning-enabled Digital Twin in UAV-aided Vehicular Networks

Energy-Efficient Federated Learning-enabled Digital Twin in ...

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Asia-Pacific Conference on Communications

作者： Giang H. Pham Hoang D. Le Thanh V. Pham Chuyen T. Nguyen Anh T. Pham Computer Communications Laboratory The University of Aizu Japan Department of Mathematical and Systems Engineering Shizuoka University Japan School of Electrical and Electronic Engineering Hanoi University of Science and Technology Vietnam

Federated learning (FL)-enabled digital twin (DT) has recently attracted research attention to bring intelligent applications. However, enabling the FL-enabled DT in vehicular networks becomes challenging due to vehicle mobility’s impact on communication channels. In this regard, we propose to deploy an unmanned aerial vehicle (UAV) as a relay node to support the vehicular network. The objective is to minimize energy consumption under the trade-off with the latency and accuracy constraints of the DT model via a joint optimization of local accuracy, the local computation frequency, relay decision, and transmission power. To do so, we derive instantaneous formulas to update the accuracy and latency constraints, then solve the proposed problem using an iterative algorithm with convex optimization techniques. Numerical results show that the proposed dynamic optimization for UAV-aided vehicular networks can reduce up to 39.9% of consumption energy compared to conventional methods.

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Human-Guided Artificial Intelligence (HGAI), a Framework for Overcoming AI's Blind Spots

Human-Guided Artificial Intelligence (HGAI), a Framework for...

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IEEE Southeastcon

作者： Ziyu Chen Selam B. Kelil Mohammad Y. M. Naser Jason S. Metcalfe Sylvia Bhattacharya Electrical & Computer Engineering Department Kennesaw State University Marietta USA Computer Science Department Kennesaw State University Marietta USA US DEVCOM Army Research Laboratory Aberdeen Proving Ground Aberdeen USA Engineering Technology Department Kennesaw State University Marietta USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Artificial Intelligence (AI) systems frequently exhibit systematic blind spots, often referred to as hallucinations in Large Language Models (LLMs), posing risks in high-stakes applications such as autonomous systems, security, and military operations. This paper explores how human intuitive responses, along with conscious reasoning processes, can be integrated to mitigate AI blind spots and enhance decision-making effectiveness within Human-AI teams. We introduce Human-Guided Artificial Intelligence (HGAI) as a framework for achieving this goal. Specifically, we examine the role of System-1 intuitive processing, as captured through physiological signals such as electroencephalography (EEG) and electrocardiography (ECG), System-2 reasoning-based decision-making, and Multi-Modal Fusion (MMF) mechanisms while assessing the knowledge required to develop more reliable, context-aware, and ethically aligned intelligent decision-making systems for highly complex environments.

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Methodology,progress and challenges of geoscience knowledge graph in International Big science Program of Deep-Time Digital Earth

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Journal of Geographical sciences 2025年第5期35卷 1132-1156页

作者： ZHU Yunqiang WANG Qiang WANG Shu SUN Kai WANG Xinbing LV Hairong HU Xiumian ZHANG Jie WANG Bin QIU Qinjun YANG Jie ZHOU Chenghu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China University of Chinese Academy of Sciences Beijing 100049China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing 210023China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Command Center of Natural Resources Comprehensive Survey China Geological SurveyBeijing 100055China School of Computer Science China University of GeosciencesWuhan 430074China

Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary *** advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological sciences initiated the“Deeptime Digital Earth International Big science Program”(DDE)in *** the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big *** DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience *** its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.

关键词： deep-time Earth geoscience knowledge graph Deep-time Digital Earth International Big science Program

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Double-Blockchain Assisted Secure and Anonymous Data Aggregation for Fog-Enabled Smart Grid

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engineering 2022年第1期8卷 159-169页

作者： Siguang Chen Li Yang Chuanxin Zhao Vijayakumar Varadarajan Kun Wang Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Anhui Provincial Key Laboratory of Network and Information Security Anhui Normal UniversityWuhu 241000China School of Computer Science and Engineering Vellore Institute of TechnologyChennai 600127India Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

As a future energy system,the smart grid is designed to improve the efficiency of traditional power systems while providing more stable and reliable ***,this efficient and reliable service relies on collecting and analyzing users’electricity consumption data frequently,which induces various security and privacy *** address these challenges,we propose a double-blockchain assisted secure and anonymous data aggregation scheme for fog-enabled smart grid named ***,we design a three-tier architecture-based data aggregation framework by integrating fog computing and the blockchain,which provides strong support for achieving efficient and secure data collection in smart ***,we develop a secure and anonymous data aggregation mechanism with low computational overhead by jointly leveraging the Paillier encryption,batch aggregation signature and anonymous *** particular,the system achieves fine-grained data aggregation and provides effective support for power dispatching and price adjustment by the designed double-blockchain and two-level data ***,the superiority of the proposed scheme is illustrated by a series of security and computation cost analyses.

关键词： Blockchain Fog computing Homomorphic encryption Smart grid Anonymity

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