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Personalized Local Differential Privacy for Multi-dimensional Range Queries over Mobile User data

IEEE Transactions on Mobile Computing 2025年

作者： He, Yuanyuan Wang, Meiqi Deng, Xianjun Yang, Peng Xue, Qiao Yang, Laurence T. Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210000 China

Multi-dimensional range queries performed on the mobile user data records become increasingly important and popular in the fields of e-commerce, social media, transportation logistics, etc. Meanwhile, mobile users usually have different privacy requirements for different attributes of the records. A straightforward and effective approach is to first get low-dimensional range query outcomes by using existing LDP mechanisms at different privacy levels, and then derive high-dimensional range query results at each level, and finally aggregate the results from all levels. However, it incurs low utility of the query results, since the non-fixed privacy budgets and the correlation between dimensions (attributes) detrimentally impact the utility of LDP methods, ultimately rendering them ineffective in practice. In this paper, we propose a new Personalized LDP approach for Multi-dimensional Range queries (PLDP-MR) over mobile user data, consisting of the user grouping, data perturbing, data re-perturbing, and range query results aggregating steps. First, PLDP-MR offers flexible dual grouping based on user-selected privacy levels and relevant attributes to obtain the corresponding one-dimensional and two-dimensional grids. PLDP-MR optimizes the grid granularity to minimize errors from perturbing users' attribute data with different LDP noises at non-fixed privacy levels. Furthermore, PLDP-MR carefully re-perturbs the LDP-noisy data from mobile users at lower privacy levels (i.e., having the higher utility) to achieve LDP with higher privacy levels and supplement the data volume of the corresponding groups. Thus, the data utility is effectively improved without additional privacy losses. Finally, PLDP-MR aggregates the frequencies in all the one-dimensional and two-dimensional grids related to the multi-dimensional range query at all query intervals and all privacy levels to derive the final query result with considering the correlation between attributes. The aggregations use

关键词： data privacy

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-Neural network-based optimization of hydrogen fuel production energy system with proton exchange electrolyzer supported nanomaterial

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Fuel 2023年 332卷

作者： Hai, Tao Hikmat Hama Aziz, Kosar Zhou, Jincheng Dhahad, Hayder A. Sharma, Kamal Fahad Almojil, Sattam Ibrahim Almohana, Abdulaziz Fahmi Alali, Abdulrhman Ismail Kh, Teeba Mehrez, Sadok Abdelrahman, Anas School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Guizhou Duyun 558000 China nstitute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia Department of Chemistry College of Science University of Sulaimani Qlyasan Street Kurdistan Region 46001 Iraq Department of Medical Laboratory of Science College of Health Sciences University of Human Development Sulaimaniyah Iraq Mechanical Engineering Department University of Technology Baghdad Iraq Institute of Engineering and Technology GLA University Uttar Pradesh Mathura 281406 India Department of Civil Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Computer Engineering College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq Department of Mechanical Engineering College of Engineering at Al Kharj Prince Sattam bin Abdulaziz University 16273 Saudi Arabia Department of Mechanical Engineering University of Tunis El Manar ENIT BP 37 Le Belvédère Tunis 1002 Tunisia Department of Chemical Engineering Faculty of Engineering & Technology Future University in Egypt New Cairo 11500 Tunisia Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan Duyun 558000 China

In this research, we try to investigate a solar-geothermal energy system. This system includes three turbines for power production, a PEM electrolyzer for hydrogen production, and a thermoelectric for generating electricity from excess heat. In addition, the seawater will be passed through the osmotic cycle to gain fresh water. The required power for this osmotic cycle will be obtained through the energy produced by the main turbines. The generated load, hydrogen production flow rate, purified water flow rate, and heating consumption are assessed in this study. The results showed that this system can produce 3.8 megawatts of electricity as well as 8 g per second of hydrogen fuel at the operating point. Also, the energy efficiency of this system is estimated to be 19%. Afterward, machine learning methods are used to optimize designing parameters, and the optimum operating point in terms of useful power and stored fuel flow rate is obtained by a genetic algorithm. The optimum operating point of this energy system has a useful power output of 4.099 megawatts and a hydrogen flow rate of 29 g per second. In the end, the distribution of the design parameters is displayed for points of the beam curve. © 2022

关键词： Biofuel Electrolyzer Fuel production Hydrogen fuel Optimization Solar energy

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data privacy quantification and de-identification model based on information theory

Data privacy quantification and de-identification model base...

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2019 International Conference on Networking and Network Applications, NaNA 2019

作者： Zhang, Zeyu Lu, Zhiyang Tian, Youliang State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China College of Electrical Engineering Guizhou University Guiyang550025 China

ISBN: (纸本)9781728126296

De-identification enables to protect privacy of data from different attacks. At present, the specific de-identification standards and privacy quantification methods are given in many models, such as K-anonymity model and differential privacy model. But, the K-anonymity model does not provide an effective method to prove its degree of privacy protection, and when the model parameters change, the degree of privacy protection cannot be quantified. And due to rigorous calculation method of the differential privacy model, which quantifies the degree of privacy protection based on a mathematical basis, it is difficult to be used widely in organizations and institutions. So, this paper proposes a de-identification model, which includes quantification solution of identifying the sensitivity of the personal information, de-identification approach for adaptively matching different standard de-identification methods to personal information with different sensitivities and de-identification effect detection function. The objective is to provide an automatic, efficient and widely used de-identification model, which is built by quantitatively analyzing degree of privacy protection based on conditional entropy. Finally, performance analysis results show that the model makes the trade-off between privacy and secure of data and the widespread use of data. © 2019 IEEE.

关键词： data privacy

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Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

Extremely Short Chinese Text Classification Method Based on ...

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作者： Yongzeng Yue Yuhong Zhang Xuegang Hu Peipei Li Key Laboratory of knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology

Short text classification methods have achieved significant progress and wide application on text data such as Twitter and Weibo. However, the extremely short chinese texts like tax invoice data are different with traditional short texts in lackness of contextual semantic information, feature sparseness and extremely short length. The existing short text classification methods are difficult to achieve a satisfactory performance in these texts. To address these problems, this paper proposes a text classification method based on bidirectional semantic extension for extremely short texts like Chinese tax invoice data. More specifically, firstly, the Chinese knowledge graph is introduced for extending bidirectional semantic of texts and label data to expand the extremely short texts and ease the problem of feature sparseness;secondly,the hash vectorization is used to avoid the semantic problem caused by the lackness of contextual information. Experimental results conducted the real tax invoice dataset demonstrate the effectiveness of our proposed method.

关键词： Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

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Solar-driven MEA/ChCl/2-MPZ/MXene-based nanofluid for efficient CO2 adsorption–desorption

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Separation and Purification Technology 2025年 376卷

作者： Wang, Jianjie Yu, Wei Zhu, Dahai Lyu, Qingyun Ye, Jiayi Wei, Xing Wu, Jiajia Xie, Huaqing Xing, Xing Li, Yifan School of Energy and Materials Shanghai Key Laboratory of Engineering Materials Application and Evaluation Shanghai Polytechnic University Shanghai 201209 China Shanghai Thermophysical Properties Big Data Professional Technical Service Platform Shanghai Engineering Research Center of Advanced Thermal Functional Materials Shanghai 201209 China China Faculty of Engineering McMaster University Hamilton L8S 4L8 Canada

The chemical adsorption method for CO2 capture exhibits exceptional selectivity and capture efficiency. However, conventional strategies still face challenges such as relatively high energy consumption and the inability to self-regenerate captured CO2. This study proposed a solar-driven CO2 adsorption/desorption solution by incorporating MXene nanoparticles with the 2-methylpiperazine (2-MPZ) into a green absorbent eutectic solvent (MEA/ChCl). The prepared MEA/ChCl/2-MPZ/MXene (MC2M) nanofluids exhibit a remarkable enhancement in CO2 adsorption capacity, which increases from the initial 0.286 g/g for MEA/ChCl to 0.530 g/g. Additionally, the incorporation of MXene plays a pivotal role in boosting the photothermal conversion efficiency, reaching an impressive 89 % under one-sun illumination. This improvement enables the nanofluids to achieve a peak temperature of 62.8℃. Density functional theory calculations reveal that the addition of 2-MPZ accelerates the CO2 adsorbent adsorption rate, while the incorporation of MXene facilitates efficient desorption. MC2M nanofluid exhibits excellent recyclability, maintaining the adsorption capacity of 0.467 g/g after 10 adsorption–desorption cycles. The practical application highlights the great potential of the developed nanofluid in regulating the CO2 concentration in a 150 m³ conference room. The nanofluid developed in this study demonstrates the potential to use CO2 in closed environments, offering valuable insights for future research.

关键词： CO2 adsorption/desorption MC2M nanofluids Photothermal conversion Solar-driven

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Evaluation Methods of English Advanced Pronunciation Skills Based on Speech Recognition 4th

Evaluation Methods of English Advanced Pronunciation Skills ...

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4th International Conference on Intelligent, Interactive Systems and Applications, IISA2019

作者： Meng, Feng Jia, Yanming Wang, Wufeng Ning, Xu School of Computer Science and Technology Wuhan University of Technology Wuhan430070 China Center for Artificial Intelligence and Big Data Research Global Wisdom Inc. Beijing100085 China Zhongshan Institute of Advanced Engineering Technology of WUT Zhongshan528437 China Hubei Key Laboratory of Transportation Internet of Things Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9783030343866

The assessment of English advanced pronunciation skills evaluates the pronunciation fluency, employing techniques from various fields including artificial neural network, speech recognition and linguistics. The pronunciation fluency includes 4 main parts of pronunciation skills, including speech stress, pause, liaison and plosive. This paper mainly studies liaison and plosive. In the aspect of liaison recognition, GRU (Gated Recurrent Unit) are used to train the classification model. In the field of plosive recognition, words both with l plosive label or not are added to the process of language model construction;and acoustic features both with plosive pronunciation skill or not are used to the process of acoustic model construction, with these two parts, static decoding network WFST (Weight Finite-State Transducer) is constructed. The experimental results show that, for different types of liaison, the average accuracy of GRU models are up to 92.34%;for plosive model, the accuracy of the static decoding network model is 72.17%. © 2020, Springer Nature Switzerland AG.

关键词： Speech recognition

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An Improved Adam Optimization Algorithm Combining Adaptive Coefficients and Composite Gradients Based on Randomized Block Coordinate Descent

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Computational intelligence and neuroscience 2023年第1期2023卷 4765891页

作者： Miaomiao Liu Dan Yao Zhigang Liu Jingfeng Guo Jing Chen School of Computer and Information Technology Northeast Petroleum University Daqing 163318 China. Heilongjiang Key Laboratory of Petroleum Big Data and Intelligent Analysis Daqing 163318 China. College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China.

An improved Adam optimization algorithm combining adaptive coefficients and composite gradients based on randomized block coordinate descent is proposed to address issues of the Adam algorithm such as slow convergence, the tendency to miss the global optimal solution, and the ineffectiveness of processing high-dimensional vectors. The adaptive coefficient is used to adjust the gradient deviation value and correct the search direction firstly. Then, the predicted gradient is introduced, and the current gradient and the first-order momentum are combined to form a composite gradient to improve the global optimization ability. Finally, the random block coordinate method is used to determine the gradient update mode, which reduces the computational overhead. Simulation experiments on two standard datasets for classification show that the convergence speed and accuracy of the proposed algorithm are higher than those of the six gradient descent methods, and the CPU and memory utilization are significantly reduced. In addition, based on logging data, the BP neural networks optimized by six algorithms, respectively, are used to predict reservoir porosity. Results show that the proposed method has lower system overhead, higher accuracy, and stronger stability, and the absolute error of more than 86% data is within 0.1%, which further verifies its effectiveness.

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BLOWN: A Blockchain Protocol for Single-Hop Wireless Networks under Adversarial SINR

arXiv

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arXiv 2021年

作者： Xu, Minghui Zhao, Feng Zou, Yifei Liu, Chunchi Cheng, Xiuzhen Dressler, Falko The School of Computer Science and Technology Shandong University Qingdao266510 China The Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin China Ernst & Young Shanghai200120 China The School of Electrical Engineering and Computer Science TU Berlin Berlin10587 Germany

Known as a distributed ledger technology (DLT), blockchain has attracted much attention due to its properties such as decentralization, security, immutability and transparency, and its potential of servicing as an infrastructure for various applications. Blockchain can empower wireless networks with identity management, data integrity, access control, and high-level security. However, previous studies on blockchain-enabled wireless networks mostly focus on proposing architectures or building systems with popular blockchain protocols. Nevertheless, such existing protocols have obvious shortcomings when adopted in wireless networks where nodes may have limited physical resources, may fall short of well-established reliable channels, or may suffer from variable bandwidths impacted by environments or jamming attacks. In this paper, we propose a novel consensus protocol named Proof-of-Channel (PoC) leveraging the natural properties of wireless communications, and develop a permissioned BLOWN protocol (BLOckchain protocol for Wireless Networks) for single-hop wireless networks under an adversarial SINR model. We formalize BLOWN with the universal composition framework and prove its security properties, namely persistence and liveness, as well as its strengths in countering against adversarial jamming, double-spending, and Sybil attacks, which are also demonstrated by extensive simulation studies. Copyright © 2021, The Authors. All rights reserved.

关键词： Blockchain

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Multiobjective Bilevel Evolutionary Approach for Off-Grid Direction-of-Arrival Estimation

arXiv

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arXiv 2021年

作者： Yan, Bai Zhao, Qi Zhang, Jin Zhang, J. Andrew Yao, Xin Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China School of Computer Science and Technology University of Science and Technology of China Hefei230027 China Global Big Data Technologies Centre University of Technology SydneyNSW2007 Australia

The source number identification is an essential step in direction-of-arrival (DOA) estimation. Existing methods may provide a wrong source number due to inferior statistical properties (in low SNR or limited snapshots) or modeling errors (caused by relaxing sparse penalties), especially in impulsive noise. To address this issue, we propose a novel idea of simultaneous source number identification and DOA estimation. We formulate a multiobjective off-grid DOA estimation model to realize this idea, by which the source number can be automatically identified together with DOA estimation. In particular, the source number is properly exploited by the l0 norm of impinging signals without relaxations, guaranteeing accuracy. Furthermore, we design a multiobjective bilevel evolutionary algorithm to solve the proposed model. The source number identification and sparse recovery are simultaneously optimized at the on-grid (lower) level. A forward search strategy is developed to further refine the grid at the off-grid (upper) level. This strategy does not need linear approximations and can eliminate the off-grid gap with low computational complexity. Simulation results demonstrate the outperformance of our method in terms of source number and root mean square error. Copyright © 2021, The Authors. All rights reserved.

关键词： Impulse noise

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Optimum Consecutive Preventive Maintenance Scheduling Model Considering Reliability

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Journal of Shanghai Jiaotong university(Science) 2019年第4期24卷 490-495页

作者： LIU Gehui LONG Xiangyu TONG Shuo ZHANG Rui CHEN Shaokuan MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong UniversityBeijing100044China CHELBI Engineering Consultants Inc.Beijing100029China Beijing Transport Institute Beijing100073China

As an effective means for improving system condition and reducing failures, a reasonable preventive maintenance scheduling guarantees the stability and safety of the system. This paper studies a consecutive maintenance scheduling problem for single-component systems with imperfect maintenance, and an optimum model with minimum reliability constraint for minimal cost rate is developed based on the renewal theory. The agebased and reliability-based maintenance strategies are modeled and compared according to a numerical example based on the degradation data of the actual system, which also verifies the optimality of the reliability-based strategy. At last, the influence of some key parameters is discussed by sensitive analysis.

关键词： reliability imperfect maintenance maintenance scheduling sensitivity analysis cost rate

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