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arXiv 2024年

作者： Wang, Jingyi Xia, Xiaobo Lan, Long Wu, Xinghao Yu, Jun Yang, Wenjing Han, Bo Liu, Tongliang The Department of Intelligent Data Science College of Computer Science and Technology National University of Defense Technology Changsha410073 China The Trustworthy Machine Learning Lab School of Computer Science Faculty of Engineering University of Sydney DarlingtonNSW2008 Australia The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China The Department of Automation University of Science and Technology of China Hefei230026 China The Department of Computer Science Hong Kong Baptist University Hong Kong

Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows that although the networks have the ability to memorize all noisy data, they would first memorize clean training data, and then gradually memorize mislabeled training data. A simple and effective method that exploits the memorization effect to combat noisy labels is early stopping. However, early stopping cannot distinguish the memorization of clean data and mislabeled data, resulting in the network still inevitably overfitting mislabeled data in the early training stage. In this paper, to decouple the memorization of clean data and mislabeled data, and further reduce the side effect of mislabeled data, we perform additive decomposition on network parameters. Namely, all parameters are additively decomposed into two groups, i.e. , parameters w are decomposed as w = σ + γ. Afterward, the parameters σ are considered to memorize clean data, while the parameters γ are considered to memorize mislabeled data. Benefiting from the memorization effect, the updates of the parameters σ are encouraged to fully memorize clean data in early training, and then discouraged with the increase of training epochs to reduce interference of mislabeled data. The updates of the parameters γ are the opposite. In testing, only the parameters σ are employed to enhance generalization. Extensive experiments on both simulated and real-world benchmarks confirm the superior performance of our method. The implementation is available at: https://***/wangjingyi9924/TNLPAD. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Serious Games in Digital Gaming: A Comprehensive Review of Applications, Game Engines and Advancements

arXiv

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arXiv 2023年

作者： Gazis, Alexandros Katsiri, Eleftheria Democritus University of Thrace School of Engineering Department of Electrical and Computer Engineering Xanthi67100 Greece Institute for the Management of Information Systems Athena Research & Innovation Center in Information Communication & Knowledge Technologies Marousi15125 Greece

- Serious games are defined as applied games that focus on the gamification of an experience (e.g., learning and training activities) and are not strictly for entertainment purposes. In recent years, serious games have become increasingly popular due to their ability to simultaneously educate and entertain users. In this review, we provide a comprehensive overview of the different types of digital games and expand on the serious games genre while focusing on its various applications. Furthermore, we present the most widely used game engines used in the game development industry and extend the Unity game machine advantages. Lastly, we conclude our research with a detailed comparison of the two most popular choices (Unreal and Unity engines) and their respective advantages and disadvantages while providing future suggestions for serious digital game development. © 2023, CC BY.

关键词： Serious games

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Low-phase-noise surface-acoustic-wave oscillator using an edge mode of a phononic band gap

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Physical Review Applied 2025年第2期23卷 024054-024054页

作者： Zichen Xi Joseph G. Thomas Jun Ji Dongyao Wang Zengyu Cen Ivan I. Kravchenko Bernadeta R. Srijanto Yu Yao Yizheng Zhu Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg Virginia 24061 USA Center for Quantum Information Science and Engineering (VTQ) Virginia Tech Blacksburg Virginia 24061 USA Center for Photonics Technology Virginia Tech Blacksburg Virginia 24061 USA School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85281 USA Center for Photonic Innovation Arizona State University Tempe Arizona 85281 USA Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak Ridge Tennessee 37830 USA

Low-phase-noise microwave-frequency integrated oscillators provide compact solutions for various applications in signal processing, communications, and sensing. Surface acoustic waves (SAWs), featuring orders-of-magnitude shorter wavelength than electromagnetic waves at the same frequency, enable integrated microwave-frequency systems with much smaller footprint on chip. SAW devices also allow higher-quality (Q) factors than electronic components at room temperature. Here, we demonstrate a low-phase-noise gigahertz-frequency SAW oscillator on 128°Y-cut lithium niobate, where the SAW resonator occupies a footprint of 0.05mm2. Leveraging phononic crystal band-gap-edge modes to balance between Q factors and insertion losses, our 1-GHz SAW oscillator features a low phase noise of −132.5 dBc/Hz at a 10-kHz offset frequency and an overlapping Hadamard deviation of 6.5 × 10−10 at an analysis time of 64 ms. The SAW resonator-based oscillator holds high potential in developing low-noise sensors and acousto-optic integrated circuits.

关键词： Microwave oscillators

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How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? 39

How Does the Smoothness Approximation Method Facilitate Gene...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Ding, Wenjun An, Ying Chen, Lixing Kan, Shichao Wu, Fan Qu, Zhe School of Computer Science and Engineering Central South University Changsha China Xiangjiang Laboratory Changsha China Big Data Institute Central South University Changsha China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai China

ISBN: (纸本)157735897X

Federated Adversarial Learning (FAL) is a robust framework for resisting adversarial attacks on federated learning. Although some FAL studies have developed efficient algorithms, they primarily focus on convergence performance and overlook generalization. Generalization is crucial for evaluating algorithm performance on unseen data. However, generalization analysis is more challenging due to non-smooth adversarial loss functions. A common approach to addressing this issue is to leverage smoothness approximation. In this paper, we develop algorithm stability measures to evaluate the generalization performance of two popular FAL algorithms: Vanilla FAL (VFAL) and Slack FAL (SFAL), using three different smooth approximation methods: 1) Surrogate Smoothness Approximation (SSA), (2) Randomized Smoothness Approximation (RSA), and (3) Over-Parameterized Smoothness Approximation (OPSA). Based on our in-depth analysis, we answer how to properly set the smoothness approximation method to mitigate generalization error in FAL. Moreover, we identify RSA as the most effective generalization error reduction method. In highly data-heterogeneous scenarios, we also recommend employing SFAL to mitigate the deterioration of generalization performance caused by heterogeneity. Based on our theoretical results, we provide insights to help develop more efficient FAL algorithms, such as designing new metrics and dynamic aggregation rules to mitigate heterogeneity. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Federated learning

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The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

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30th Annual Network and Distributed System Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.

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Self-Refined Generative Foundation Models for Wireless Traffic Prediction

arXiv

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arXiv 2024年

作者： Hu, Chengming Zhou, Hao Wu, Di Chen, Xi Yan, Jun Liu, Xue The School of Computer Science McGill University MontrealQCH3A 0E9 Canada The School of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada The Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada

With a broad range of emerging applications in 6G networks, wireless traffic prediction has become a critical component of network management. However, the dynamically shifting distribution of wireless traffic in non-stationary 6G networks presents significant challenges to achieving accurate and stable predictions. Motivated by recent advancements in Generative AI (GAI)-enabled 6G networks, this paper proposes a novel self-refined Large Language Model (LLM) for wireless traffic prediction, namely TrafficLLM, through in-context learning without parameter fine-tuning or model training. The proposed TrafficLLM harnesses the powerful few-shot learning abilities of LLMs to enhance the scalability of traffic prediction in dynamically changing wireless environments. Specifically, our proposed TrafficLLM embraces an LLM to iteratively refine its predictions through a three-step process: traffic prediction, feedback generation, and prediction refinement. Initially, the proposed TrafficLLM conducts traffic predictions using task-specific demonstration prompts. Recognizing that LLMs may generate incorrect predictions on the first attempt, we subsequently incorporate feedback demonstration prompts designed to provide multifaceted and valuable feedback related to these initial predictions. Following this comprehensive feedback, our proposed TrafficLLM introduces refinement demonstration prompts, enabling the same LLM to further refine its predictions and thereby enhance prediction performance. The evaluations on two realistic datasets demonstrate that the proposed TrafficLLM outperforms state-of-the-art methods with performance improvements of 23.17% and 17.09%, respectively. © 2024, CC0.

关键词： Demonstrations

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Spectral phase singularity and topological behavior in perfect absorption

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Physical Review B 2023年第24期107卷 L241403-L241403页

作者： Mengqi Liu Weijin Chen Guangwei Hu Shanhui Fan Demetrios N. Christodoulides Changying Zhao Cheng-Wei Qiu Institute of Engineering Thermophysics MOE Key Laboratory for Power Machinery and Engineering School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore Department of Electrical Engineering Ginzton Laboratory Stanford University Stanford California 94305 USA Center for Research and Education in Optics and Lasers (CREOL) The College of Optics and Photonics University of Central Florida Orlando Florida 32816 USA

Perfect absorbers, which can achieve total absorption of all incoming energy, have been extensively studied in the last decades for various important technologies in general wave systems. Here, we show that perfect absorption (PA) is generically associated with topological spectral phase singularity (SPS), carrying conserved and tunable quantized topological invariants in spectral space. The order of topological invariant ṽ depends on the number of degenerate outgoing channels. Two commonly studied absorbers, mirror-backed and all-dielectric structures, are reexamined from a topological perspective to reveal the generation, evolution, and annihilation of SPSs with ṽ=±1 or even high orders (i.e., ṽ=±2,±4). A strategy based on charge conservation of SPSs to design dual-band perfect absorbers has been established. Our findings establish the topological origin of the robust existence of PA. More broadly, in this letter, we highlight topology as the fundamental property of conventional scattering behaviors. This insight could lead to opportunities in applications such as biosensing, topological metasurfaces, and micro/nano thermal radiation.

关键词： Light-matter interaction Nanophotonics Optical & microwave phenomena Topological effects in photonic systems

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Near-field chiral excitation of universal spin-momentum locking transport of edge waves in microwave metamaterials

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Advanced Photonics 2022年第4期4卷 46-55页

作者： Zhixia Xu Jie Chang Jinye Tong Daniel F.Sievenpiper Tie Jun Cui Southeast University State Key Laboratory of Millimeter WavesNanjingChina Dalian Maritime University School of Information Science and TechnologyDalianChina University of California San Diego Department of Electrical and Computer EngineeringSan DiegoCaliforniaUnited States

Controlling energy flow in waveguides has attractive potential in integrated devices from radio frequencies to optical *** to the spin-orbit coupling,the mirror symmetry will be broken,and the handedness of the near-field source will determine the direction of energy *** with well-established theories about spin-momentum locking,experimental visualization of unidirectional coupling is usually challenging due to the lack of generic chiral sources and the strict environmental *** this work,we design a broadband near-field chiral source in the microwave band and discuss experimental details to visualize spin-momentum locking in three different metamaterial waveguides,including spoof surface plasmon polaritons,line waves,and valley topological *** similarity of these edge waves relies on the abrupt sign change of intrinsic characteristics of two media across the *** addition to the development of experimental technology,the advantages and research status of interface waveguides are summarized,and perspectives on future research are presented to explore an avenue for designing controllable spin-sorting devices in the microwave band.

关键词： chirality metamaterials microwaves spoof surface plasmon polaritons waveguides

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Solid-state non-volatile memories based on vdW heterostructure-based vertical-transport ferroelectric field-effect transistors

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Science China(Information Sciences) 2024年第6期67卷 198-206页

作者： Qiyu YANG Zheng-Dong LUO Fei XIAO Junpeng ZHANG Dawei ZHANG Dongxin TAN Xuetao GAN Yan LIU Zhufei CHU Yinshui XIA Genquan HAN Hangzhou Institute of Technology Xidian University State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University School of Artificial Intelligence Xidian University School of Materials Science and Engineering University of New South Wales (UNSW) Sydney ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) University of New South Wales (UNSW) Sydney Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical University Faculty of Electrical Engineering and Computer Science Ningbo University

Driven by the explosive development of data-centric computation applications, it is becoming urgent to develop in-memory computing devices that are beyond the von Neumann architecture with an arrangement of separated logic and memory components. The transistor-type solid-state non-volatile memories,such as ferroelectric field-effect transistors(Fe FETs), have long been regarded as a competitive candidate for future in-memory computing architectures. However, the density scaling towards high-density arrays would require advanced Fe FETs with reduced footprints, which remains a great challenge so far. Here, a vertical-transport(VT) Fe FET that flips the charge transport channel perpendicular to the substrate plane is proposed, in which a ferroelectric gate and a van der Waals(vd W) heterojunction channel are vertically integrated, effectively reducing the device footprints. The proposed VT-Fe FET shows not only the robust binary non-volatile memory states but also several key synaptic functionalities at the device level. An artificial neural network with supervised learning was simulated based on the device conductance switching properties,showing excellent classification accuracy for the MNIST handwritten digits. These findings suggest that the proposed VT-Fe FET could offer a new solution for future non-volatile memories as well as more advanced neuromorphic systems.

关键词： vdW heterostructure non-volatile memory vertical-transport transistor ferroelectric field-effect transistor memristive devices

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Secure Group Testing

Secure Group Testing

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作者： Cohen, Alejandro Cohen, Asaf Gurewitz, Omer Research Laboratory of Electronics MIT CambridgeMA02139 United States School of Electrical and Computer Engineering Ben-Gurion University of the Negev Beer-Sheva84105 Israel

The principal goal of Group Testing (GT) is to identify a small subset of 'defective' items from a large population, by grouping items into as few test pools as possible. The test outcome of a pool is positive if it contains at least one defective item, and is negative otherwise. GT algorithms are utilized in numerous applications, and in many of them maintaining the privacy of the tested items, namely, keeping secret whether they are defective or not, is critical. In this paper, we consider a scenario where there is an eavesdropper (Eve) who is able to observe a subset of the GT outcomes (pools). We propose a new non-adaptive Secure Group Testing (SGT) scheme based on information-theoretic principles. The new proposed test design keeps the eavesdropper ignorant regarding the items' status. Specifically, when the fraction of tests observed by Eve is 0 ≤ δ © 2005-2012 IEEE.

关键词： Decoding

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