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A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection

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Tsinghua science and technology 2024年第2期29卷 617-633页

作者： Weiqi Zhang Zhenzhen Xie Akshita Maradapu Vera Venkata Sai Qasim Zia Zaobo He Guisheng Yin College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China School of Computer Science and Technology Shandong UniversityQingdao 266237China Department of Computer Science Georgia State UniversityAtlantaGA 30303USA College of Information Science and Technology Jinan UniversityGuangzhou 510632China

The widespread availability of GPS has opened up a whole new market that provides a plethora of location-based ***-based social networks have become very popular as they provide end users like us with several such services utilizing GPS through our ***,when users utilize these services,they inevitably expose personal information such as their ID and sensitive location to the *** to untrustworthy servers and malicious attackers with colossal background knowledge,users'personal information is at risk on these ***,many privacy-preserving solutions for protecting trajectories have significantly decreased utility after *** have come up with a new trajectory privacy protection solution that contraposes the area of interest for ***,Staying Points Detection Method based on Temporal-Spatial Restrictions(SPDM-TSR)is an interest area mining method based on temporal-spatial restrictions,which can clearly distinguish between staying and moving ***,our privacy protection mechanism focuses on the user's areas of interest rather than the entire ***,our proposed mechanism does not rely on third-party service providers and the attackers'background knowledge *** test our models on real datasets,and the results indicate that our proposed algorithm can provide a high standard privacy guarantee as well as data availability.

关键词： local-differential privacy stay points detection trajectory data areas of interest temporal-spatial clustering

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Evaluation and Suppression of Vibrational Noise for Cryogenic Surface Electrode Ion Traps

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Chinese Physics Letters 2025年第3期42卷 52-62页

作者： Qingqing Qin Baoquan Ou Wei Wu Yi Xie Ting Chen Chunwang Wu Pingxing Chen Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha 410073China Hunan Key Laboratory of Mechanism and Technology of Quantum Information Changsha 410073China Department of Physics College of ScienceNational University of Defense TechnologyChangsha 410073China

Cryogenic ion traps offer substantial advantages over their room-temperature counterparts,particularly in terms of stable ion confinement and ***,this technological advancement has introduced a significant challenge,namely the generation of additional vibrational *** noise is pronounced during the compression and expansion phases of the Gifford–McMahon cycle refrigerator and stems from the mechanical operation of the cold *** residual vibrational noise can modulate the Rabi oscillation frequency,thereby compromising the fidelity of the quantum logic *** this study,we quantitatively assess the impact of residual vibrational noise and introduce an innovative strategy for its *** strategy was designed to reduce superimposed potential fluctuations within a cryogenic surface electrode ion *** measured residual vibrational noise was used for real-time feedback *** the inverse determination of the compensating potential for a stable superimposed trapping potential is an inherently ill-posed problem considering known measurement noise *** applying quadratic programming,we numerically calculated the optimal time series for the compensation *** ensemble of these compensation voltages was applied in real time to the static compensation *** this method is in the theoretical stage,we believe that it can effectively suppress the translation induced by vibrational noise and foster the creation of a stable superimposed harmonic *** deployment of this technique is expected to substantially improve the accuracy of quantum operations,thereby fueling the evolution of quantum technologies.

关键词： vibrational thereby quantum

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NeurDB: an AI-powered autonomous data system

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science China(Information sciences) 2024年第10期67卷 129-150页

作者： Beng Chin OOI Shaofeng CAI Gang CHEN Yanyan SHEN Kian-Lee TAN Yuncheng WU Xiaokui XIAO Naili XING Cong YUE Lingze ZENG Meihui ZHANG Zhanhao ZHAO School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology

In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.

关键词： AI$\times$DB in-database AI intelligent data system

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A Federated Learning Incentive Mechanism for Dynamic Client Participation:Unbiased Deep Learning Models

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computers, Materials & Continua 2025年第4期83卷 619-634页

作者： Jianfeng Lu Tao Huang Yuanai Xie Shuqin Cao Bing Li School of Computer Science and Technology Wuhan University of Science and TechnologyWuhan430065China College of Computer Science South-Central Minzu UniversityWuhan430074China School of Computer Science and Technology Zhejiang Normal UniversityJinhua321004China

The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and ***,traditional DL methods compromise client privacy by collecting sensitive data,underscoring the necessity for privacy-preserving solutions like Federated Learning(FL).FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw *** that FL clients autonomously manage training data,encouraging client engagement is pivotal for successful model *** overcome challenges like unreliable communication and budget constraints,we present ENTIRE,a contract-based dynamic participation incentive mechanism for *** ensures impartial model training by tailoring participation levels and payments to accommodate diverse client *** approach involves several key ***,we examine how random client participation impacts FL convergence in non-convex scenarios,establishing the correlation between client participation levels and model ***,we reframe model performance optimization as an optimal contract design challenge to guide the distribution of rewards among clients with varying participation *** balancing budget considerations with model effectiveness,we craft optimal contracts for different budgetary constraints,prompting clients to disclose their participation preferences and select suitable contracts for contributing to model ***,we conduct a comprehensive experimental evaluation of ENTIRE using three real *** results demonstrate a significant 12.9%enhancement in model performance,validating its adherence to anticipated economic properties.

关键词： Federated learning deep learning non-IID data dynamic client participation non-convex optimization contract

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Dual-Branch Network with Mutual Guidance for Hyperspectral Image Super-Resolution

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 14368-14381页

作者： Zhang, Tiejun Zhang, Boqun Hu, Nan Li, Xinyu Li, Peng Harbin University of Science and Technology College of Computer Science and Software Harbin150080 China Jilin University College of Computer Science and Technology Changchun130012 China

Fusion-based hyperspectral image super-resolution has recently attracted increasing interest due to its superior reconstruction quality. This approach enhances the spatial resolution of low-resolution hyperspectral images (LR-HSIs) by fusing high-resolution multispectral images (HR-MSIs) of the same scene. However, most existing deep learning-based methods have not sufficiently considered the huge modality differences between these two types of images before feature fusion, potentially resulting in the loss of valuable information. To tackle this challenge, we introduce a novel dual-branch network with mutual guidance (DBMGNet). Specifically, we employ a dual-branch architecture to process the input LR-HSI and HR-MSI in parallel, with the aim of reconciling their modality differences. For this purpose, we designed a mutually guided dual-stream Transformer block that performs bidirectional calibration between the branches, enhancing their spatial and spectral consistency. To prevent excessive coupling of information, we proposed a multiscale feature enhancement block, which independently refines fine-grained details within each branch. Finally, a weighted feature fusion block is developed to effectively integrate the features from both branches. Experiments on three widely used datasets indicate that the proposed DBMGNet achieves stable and superior performance with lower computational cost in comparison with several state-of-the-art approaches. © 2008-2012 IEEE.

关键词： Image enhancement

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A Base Station Deployment Algorithm for Wireless Positioning Considering Dynamic Obstacles

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computers, Materials & Continua 2025年第3期82卷 4573-4591页

作者： Aiguo Li Yunfei Jia Department of Network Engineering Xi’an University of Science and TechnologyXi’an710600China College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710600China

In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of *** studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind ***,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic ***,research in this area still needs to be *** paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this *** algorithm considers the dynamic alterations in obstacle locations within the designated *** determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage *** experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle *** results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles *** 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.

关键词： Wireless positioning base station deployment dynamic obstacles dynamic obstacle wireless positioning

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Research on gesture recognition algorithm based on MME-P3D

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Mathematical Biosciences and Engineering 2024年第3期21卷 3594-3617页

作者： Jin, Hongmei He, Ning Liu, Boyu Li, Zhanli College of Computer Science and Technology Xi’an University of Science and Technology Xi’an710054 China

A Multiscale-Motion Embedding Pseudo-3D (MME-P3D) gesture recognition algorithm has been proposed to tackle the issues of excessive parameters and high computational complexity encountered by existing gesture recognition algorithms deployed in mobile and embedded devices. The algorithm initially takes into account the characteristics of gesture motion information, integrating the channel attention (CE) mechanism into the pseudo-3D (P3D) module, thereby constructing a P3D-C feature extraction network that can efficiently extract spatio-temporal feature information while reducing the complexity of the algorithmic model. To further enhance the understanding and learning of the global gesture movement’s dynamic information, a Multiscale Motion Embedding (MME) mechanism is subsequently designed. The experimental findings reveal that the MME-P3D model achieves recognition accuracies reaching up to 91.12% and 83.06% on the self-constructed conference gesture dataset and the publicly available Chalearn 2013 dataset, respectively. In comparison with the conventional 3D convolutional neural network, the MME-P3D model demonstrates a significant advantage in terms of parameter count and computational requirements, which are reduced by as much as 82% and 83%, respectively. This effectively addresses the limitations of the original algorithms, making them more suitable for deployment on embedded and mobile devices and providing a more effective means for the practical application of hand gesture recognition technology. © 2024 the Author(s), licensee AIMS Press.

关键词： Convolution

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Interface engineering strategy via electron-defect trimethyl borate additive toward 4.7 V ultrahigh-nickel LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)battery

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Journal of Energy Chemistry 2024年第5期92卷 639-647页

作者： Yilin Zhang Yuqing Chen Qiu He Jinlong Ke Wei Wang Jian-Fang Wu Peng Gao Yanhua Li Jilei Liu College of Materials Science and Engineering Hunan Joint International Laboratory of Advanced Materials and Technology for Clean EnergyHunan Province Key Laboratory for Advanced Carbon Materials and Applied TechnologyHunan UniversityChangsha 410082HunanChina College of Materials Science and Engineering Sichuan UniversityChengdu 610065SichuanChina School of Materials Science and Engineering Hunan Institute of TechnologyHengyang 421002HunanChina

The Li metal battery with ultrahigh-nickel cathode(LiNi_(x)M_(1-x)O_(2),M=Mn,Co,and x≥0.9)under high-voltage is regarded as one of the most promising approaches to fulfill the ambitious target of 400 Wh/***,the practical application is impeded by the instability of electrode/electrolyte interface and Ni-rich cathode *** we proposed an electron-defect electrolyte additive trimethyl borate(TMB)which is paired with the commercial carbonate electrolyte to construct highly conductive fluorine-and boron-rich cathode electrolyte interface(CEI)on LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)(NCM90)surface and solid electrolyte interphase(SEI)on lithium metal *** modified CEI effectively mitigates the structural transformation from layered to disordered rock-salt phase,and consequently alleviate the dissolution of transition metal ions(TMs)and its“cross-talk”effect,while the enhanced SEI enables stable lithium plating/striping and thus demonstrated good compatibility between electrolyte and lithium metal *** a result,the common electrolyte with 1 wt%TMB enables 4.7 V NCM90/Li cell cycle stably over 100 cycles with 70%capacity *** work highlights the significance of the electron-defect boron compounds for designing desirable interfacial chemistries to achieve high performance NCM90/Li battery under high voltage operation.

关键词： NCM90 batteries Electrolyte additive Trimethyl borate

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IIN-FFD:Intra-Inter Network for Face Forgery Detection

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Tsinghua science and technology 2024年第6期29卷 1839-1850页

作者： Qihua Zhou Zhili Zhou Zhipeng Bao Weina Niu Yuling Liu School of Software Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Artificial Intelligence Guangzhou UniversityGuangzhou 510006China School of Computer Science University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina School of Computer Science Hunan UniversityChangsha 410082HunanChina

Since different kinds of face forgeries leave similar forgery traces in videos,learning the common features from different kinds of forged faces would achieve promising generalization ability of forgery ***,to accurately detect known forgeries while ensuring high generalization ability of detecting unknown forgeries,we propose an intra-inter network(IIN)for face forgery detection(FFD)in videos with continual *** proposed IIN mainly consists of three modules,i.e.,intra-module,inter-module,and forged trace masking module(FTMM).Specifically,the intra-module is trained for each kind of face forgeries by supervised learning to extract special features,while the inter-module is trained by self-supervised learning to extract the common *** a result,the common and special features of the different forgeries are decoupled by the two feature learning modules,and then the decoupled common features can be utlized to achieve high generalization ability for ***,the FTMM is deployed for contrastive learning to further improve detection *** experimental results on FaceForensic++dataset demonstrate that the proposed IIN outperforms the state-of-the-arts in ***,the generalization ability of the IIN verified on DFDC and Celeb-DF datasets demonstrates that the proposed IIN significantly improves the generalization ability for FFD.

关键词： deep learning information security image classfication neural networks face forgery face forgery detection

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The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

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computers, Materials & Continua 2024年第4期79卷 329-349页

作者： Qiang Fu JunWang Changfu Si Jiawei Liu College of Computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China College of Computer Science and Engineering Northeastern UniversityShenyang110169China

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.

关键词： Key nodes dynamic model industrial control network simulation

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