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arXiv 2023年

作者： Qian, Biao Wang, Yang Hong, Richang Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology China

data-free quantization (DFQ) recovers the performance of quantized network (Q) without accessing the real data, but generates the fake sample via a generator (G) by learning from full-precision network (P) instead. However, such sample generation process is totally independent of Q, specialized as failing to consider the adaptability of the generated samples, i.e., beneficial or adversarial, over the learning process of Q, resulting into non-ignorable performance loss. Building on this, several crucial questions — how to measure and exploit the sample adaptability to Q under varied bit-width scenarios? how to generate the samples with desirable adaptability to benefit the quantized network? — impel us to revisit DFQ. In this paper, we answer the above questions from a game-theory perspective to specialize DFQ as a zero-sum game between two players — a generator and a quantized network, and further propose an Adaptability-aware Sample Generation (AdaSG) method. Technically, AdaSG reformulates DFQ as a dynamic maximization-vs-minimization game process anchored on the sample adaptability. The maximization process aims to generate the sample with desirable adaptability, such sample adaptability is further reduced by the minimization process after calibrating Q for performance recovery. The Balance Gap is defined to guide the stationarity of the game process to maximally benefit Q. The theoretical analysis and empirical studies verify the superiority of AdaSG over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaSG. Copyright © 2023, The Authors. All rights reserved.

关键词： Game theory

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Adaptive data-Free Quantization

arXiv

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arXiv 2023年

data-free quantization (DFQ) recovers the performance of quantized network (Q) without accessing the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptability of the knowledge from generated samples, i.e., informative or not to the learning process of Q, resulting into the overflow of generalization error. Building on this, several critical questions - how to measure the sample adaptability to Q under varied bit-width scenarios? how to generate the samples with large adaptability to improve Q's generalization? whether the largest adaptability is the best? To answer the above questions, in this paper, we propose an Adaptive data-Free Quantization (AdaDFQ) method, which revisits DFQ from a zero-sum game perspective upon the sample adaptability between two players - a generator and a quantized network. Following this viewpoint, we further define the disagreement and agreement samples to form two boundaries, where the margin is optimized to address the over-and-under fitting issues, so as to generate the samples with adaptive adaptability to Q. Our AdaDFQ reveals: 1) the largest adaptability is NOT the best for sample generation to benefit Q's generalization;2) the knowledge of the generated sample should not be informative to Q only, but also related to the category and distribution information of the training data for P. The theoretical and empirical analysis validate the advantages of AdaDFQ over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaDFQ. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Secure RFID-Assisted Authentication Protocol for Vehicular Cloud Computing Environment

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IEEE Transactions on Intelligent Transportation Systems 2024年第9期25卷 12528-12537页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Tariq, Tayyaba Alenazi, Mohammed J. F. Das, Ashok Kumar University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Sichuan University Key Laboratory of Data Protection and Intelligent Management Ministry of Education Chengdu610065 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518000 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Yunlin Douliu64002 Taiwan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500032 India

Vehicular network technology has made substantial advancements in recent years in the field of Intelligent Transportation Systems. Vehicular Cloud Computing (VCC) has emerged as a novel paradigm with a substantial increase in data exchange within Vehicular ad-hoc networks (VANETs). VCC integrates cloud computing, vehicular networking, and Internet of Things (IoT) technologies. It enables Infrastructure-to-Vehicle (I2V), Vehicle-to-Vehicle (V2V), and Vehicle-to-Device (V2D) communication. VCC optimizes vehicle, cloud infrastructure, and IoT resources while addressing significant communication security and vehicle-user privacy challenges. To address these issues, we developed an RFID-based authentication protocol for VCC based on a Henon map using a hash function. In addition, we also incorporated a Physical Unclonable Function (PUF) to resist physical tampering attacks. We validate the protocol's security formally and informally. The formal security analysis is conducted through a widely used RoR model. We use the Scyther simulation tool to verify the proposed protocol's security against various attacks. Moreover, we compare the performance of our protocol with similar existing protocols across important performance parameters such as communication and computation overheads and security attributes. The proposed protocol yields substantial improvements, demonstrating a 40.74% reduction in computation overhead and a 13.03% decrease in communication overhead as compared to related protocols, delivering both enhanced performance and resource efficiency. The analysis demonstrates its capacity to support secure communication in the VCC environment and satisfy desirable security attributes. © 2024 IEEE.

关键词： Authentication

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A Straw Coverage Rate Calculation Method Based on Single Image Processing 2

A Straw Coverage Rate Calculation Method Based on Single Ima...

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2nd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics, AIHCIR 2023

作者： Wu, Shiqi Guo, Xi Li, Jie Wulamu, Aziguli Li, Tian Zou, Qiping Xia, Chenglong School of Computer and Communication Engineering University of Science and Technology Beijing Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Beijing Agricultural Machinery Manager IoT Technology Co. Ltd Beijing China Hechi University Key Laboratory of Ai and Information Processing Hechi China

ISBN: (纸本)9798350360363

This paper proposes a straw coverage rate calculation method based on single-image processing. This method uses a convolutional neural network (CNN) to extract features from images of fields covered with straw, classifies the image based on the features, and then uses an image binarization method to distinguish the straw and the land parts in the image and calculate the straw coverage rate based on the proportion of the straw part. This method has been applied in the land classification project in a particular region. These results demonstrate that this method effectively calculates straw coverage rates and can be used in other fields of precision agriculture. © 2023 IEEE.

关键词： Image recognition

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Adaptive data-Free Quantization

Adaptive Data-Free Quantization

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Biao Qian Yang Wang Richang Hong Meng Wang Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology China

data-free quantization (DFQ) recovers the performance of quantized network (Q) without the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptability of the knowledge from generated samples, i.e., informative or not to the learning process of Q, resulting into the overflow of generalization error. Building on this, several critical questions — how to measure the sample adaptability to Q under varied bit-width scenarios? whether the largest adaptability is the best? how to generate the samples with adaptive adaptability to improve Q's generalization? To answer the above questions, in this paper, we propose an Adaptive data-Free Quantization (AdaDFQ) method, which revisits DFQ from a zero-sum game perspective upon the sample adaptability between two players — a generator and a quantized network. Following this viewpoint, we further define the disagreement and agreement samples to form two boundaries, where the margin between two boundaries is optimized to adaptively regulate the adaptability of generated samples to Q, so as to address the over-and-under fitting issues. Our AdaDFQ reveals: 1) the largest adaptability is NOT the best for sample generation to benefit Q's generalization; 2) the knowledge of the generated sample should not be informative to Q only, but also related to the category and distribution information of the training data for P. The theoretical and empirical analysis validate the advantages of AdaDFQ over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaDFQ.

关键词：

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PD-Refiner: An Underlying Surface Inheritance Refiner with Adaptive Edge-Aware Supervision for Point Cloud Denoising 24

PD-Refiner: An Underlying Surface Inheritance Refiner with A...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhang, Chengwei Zhang, Xueyi Yue, Xianghu Lao, Mingrui Jiang, Tao Wang, Jiawei Zhang, Fubo Chen, Longyong National Key Laboratory of Microwave Imaging Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Laboratory for Big Data and Decision National University of Defense Technology Hunan Changsha China Department of Electrical and Computer and Engineering National University of Singapore Singapore Singapore National Key Laboratory of Information Systems Engineering National University of Defense Technology Hunan Changsha China School of Software Engineering Tongji University Shanghai China

ISBN: (纸本)9798400706868

Point clouds from real-world scenarios inevitably contain complex noise, significantly impairing the accuracy of downstream tasks. To tackle this challenge, cascading encoder-decoder architecture has become a conventional technical route to iterative denoise. However, circularly feeding the output of denoiser as its input again involves the re-extraction of underlying surface, leading to unstable denoising process and over-smoothed geometric details. To address these issues, we propose a novel denoising paradigm dubbed PD-Refiner that employs a single encoder to model the underlying surface. Then, we leverage several lightweight hierarchical Underlying Surface Inheritance Refiners (USIRs) to inherit and strengthen it, thereby avoiding the re-extraction from the intermediate point cloud. Furthermore, we design adaptive edge-aware supervision to improve the edge awareness of the USIRs, allowing for the adjustment of the denoising preferences from global structure to local details. The results demonstrate that our method not only achieves state-of-the-art performance in terms of denoising stability and efficacy, but also enhances edge clarity and point cloud uniformity. © 2024 ACM.

关键词： edge-aware supervision

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Multiple valence states of Fe boosting SERS activity of Fe_(3)O_(4) nanoparticles and enabling effective SERS-MRI bimodal cancer imaging

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Fundamental Research 2024年第4期4卷 858-867页

作者： Jie Lin Xuehua Ma Anran Li Ozioma Udochukwu Akakuru Chunshu Pan Meng He Chenyang Yao Wenzhi Ren Yanying Li Dinghu Zhang Yi Cao Tianxiang Chen Aiguo Wu Cixi Institute of Biomedical Engineering International Cooperation Base of Biomedical Materials Technology and ApplicationChinese Academy of Science Key Laboratory of Magnetic Materials and DevicesZhejiang Engineering Research Center for Biomedical MaterialsNingbo Institute of Materials Technology and EngineeringCASNingbo315201China School of Engineering Medicine Key Laboratory of Big Data-Based Precision Medicine(Beihang University)Ministry of Industry and Information TechnologyBeihang UniversityBeijing100191China Advanced Energy Science and Technology Guangdong Laboratory Huizhou 516000China University of Chinese Academy of Sciences Bejing 100049China

Developing novel nanoparticle-based bioprobes utilized in clinical settings with imaging resolutions ranging from cell to tissue levels is a major challenge for tumor diagnosis and ***,an optimized strategy for designing a Fe_(3)O_(4)-based bioprobe for dual-modal cancer imaging based on surface-enhanced Raman scattering(SERS)and magnetic resonance imaging(MRI)is *** SERS activity of ultrasmall Fe_(3)O_(4) nanoparticles(NPs)was discovered,and a 5×10^(-9)M limit of detection for crystal violet molecules was successfully *** high-efficiency interfacial photon-induced charge transfer in Fe_(3)O_(4) NPs was promoted by multiple electronic energy levels ascribed to the multiple valence states of Fe,which was observed using ultraviolet-visible diffuse reflectance *** functional theory calculations were utilized to reveal that the narrow band gap and high electron density of states of ultrasmall Fe_(3)O_(4) NPs significantly boosted the vibronic coupling resonances in the SERS system upon *** subtypes of cancer cells were accurately recognized via high-resolution SERS imaging in vitro using the prepared Feg Og-based bioprobe with high sensitivity and good ***,Fe_(3)O_(4)-based bioprobes simultaneously exhibited T,-weighted MRI contrast enhancement with an active targeting capability for tumors in *** the best of our knowledge,this is the first report on the use of pure semiconductor-based SERS-MRI dual-modal nanoprobes in tumor imaging in vivo and in vitro,which has been previously realized only using semiconductor-metal complex *** non-metallic materials with SERS-MRI dual-modal imaging established in this report are a promising cancer diagnostic platform,which not only showed excellent performance in early tumor diagnosis but also possesses great potential for image-guided tumor treatment.

关键词： Fe_(3)O_(4)NPs SERS-MRI dual-modal nanoprobes PICT Multiple valence states Cancer diagnosis

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CompressStreamDB: Fine-Grained Adaptive Stream Processing without Decompression

CompressStreamDB: Fine-Grained Adaptive Stream Processing wi...

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International Conference on data engineering

作者： Yu Zhang Feng Zhang Hourun Li Shuhao Zhang Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering (MOE) and School of Information Renmin University of China Information Systems Technology and Design Pillar Singapore University of Technology and Design

Stream processing prevails and SQL query on streams has become one of the most popular application scenarios. For example, in 2021, the global number of active IoT endpoints reaches 12.3 billion. Unfortunately, the increasing scale of data and strict user requests place much pressure on existing stream processing systems, requiring high processing throughput with low latency. To further improve the performance of current stream processing systems, we propose a compression-based stream processing engine, called CompressStreamDB, which enables adaptive fine-grained stream processing directly on compressed streams, without decompression. Particularly, CompressStreamDB involves eight compression methods targeting various data types in streams, and it also provides a cost model for dynamically selecting the appropriate compression methods. By exploring data redundancy among streams, CompressStreamDB not only saves space in data transmission between client and server, but also achieves high throughput with low latency in SQL query on stream processing. Our experimental results show that compared to the state-of-the-art stream processing system on uncompressed streams, CompressStreamDB achieves 3.24× throughput improvement and 66.0% lower latency on average. Besides, CompressStreamDB saves 66.8% space.

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An Efficient Direct Downlink Sensing Method Using 5G NR SSB Signals in Perceptive Mobile Networks

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IEEE Internet of Things Journal 2025年第11期12卷 15360-15369页

作者： Li, Hang Xiang, Yang Guo, Qinghua Liu, Lizhe Huang, Xiaojing Cheng, Zhiqun Pang, Yashan Hangzhou Dianzi University School of Electronics and Information Hangzhou310018 China Academy of Network and Communications of CETC National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang050081 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Technology Sydney Global Big Data Technologies Centre UltimoNSW2007 Australia

In perceptive mobile networks (PMNs), using 5G new radio (NR) signals for direct sensing poses a significant challenge to practical implementation due to the high computational complexity involved in estimating sensing parameters. In this article, an efficient sensing method is proposed to incorporate both downlink active sensing and passive sensing to estimate multiple sensing parameters, including delays, Angle of Arrival (AoA), Angle of Departure (AoD), and Doppler. In particular, it exploits the synchronization signal blocks (SSBs) to facilitate sensing with multiple remote radio units (RRUs). To reduce the computational complexity of direct sensing, a sparse model is developed to decouple multiple sensing parameter estimation, enabling efficient sensing method design. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we propose an efficient method to achieve parameter estimation and association with corresponding RRUs. This method is further extended to general scenarios involving multiple path components with the same delay. Extensive simulations demonstrate the effectiveness of the proposed method, showing that it outperforms the existing ones in terms of sensing accuracy and complexity. © 2014 IEEE.

关键词： 5G mobile communication systems

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Theoretical Analysis of Self-Shrinkage Spheroidization of Irregular Degradable Polymer Powder under Thermodynamic Nonequilibrium State

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Additive Manufacturing Frontiers 2024年第4期3卷 232-241页

作者： Xiong Shuai liuyimei Yang Fangwei Qi Mingli Yang Youwen Yang Cijun Shuai Institute of Additive Manufacturing Jiangxi University of Science and TechnologyNanchang330013China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou341119China School of Mechanical and Electrical Engineering Jiangxi University of Science and TechnologyGanzhou341000China State Key Laboratory of Precision Manufacturing for Extreme Service Performance College of Mechanical and Electrical EngineeringCentral South UniversityChangsha410083China School of Sino-German Robotics Shenzhen Institute of Information TechnologyShenzhen518172China

Laser three-dimensional(3D)printing offers significant advantages in integrating the shape and function of regen-erative tissues through biomimetic ***,its effectiveness is limited by the lack of specialized biopolymer powders-while solvent methods that use residual solvents produce powders with poor biocompati-bility,mechanical methods result in irregularly shaped *** this study,a biopolymer powder spheroidiza-tion and shaping technology,which utilizes the evolution of irregular powders into spheres with minimal surface free energy in the molten state,is proposed based on the thermodynamic principle of minimum ***,the motion trajectory and temperature field of the poly(L-lactic acid)(PLLA)powder during spheroidization were quantitatively assessed and optimized using Stokes’law and Fourier’s ***,the cohesive forces and aggregation kinetics of the polymer chains were calculated using molecular ***,based on these calculations,a phase-field model was constructed to simulate the evolution of the spheroidization rate and deduce the optimal parameters for the *** precise approach enhances PLLA spheroidization control for laser 3D printing,improves part densification and surface quality,and offers a clean and efficient path for preparing high-quality PLLA spheroidized powder for laser 3D printing.

关键词： Polymer powder Spheroidization PLLA Selective laser sintering 3D printing

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