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Enhanced Privacy Preserving for Social Networks Relational Data Based on Personalized Differential Privacy

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Chinese Journal of Electronics 2022年第4期31卷 741-751页

作者： KANG Haiyan JI Yuanrui ZHANG Shuxuan school of information Management Beijing Information Science and Technology University Computer school Beijing Information Science and Technology University

With the popularization and development of social software, more and more people join the social network, which produces a lot of valuable information, but also contains plenty of sensitive privacy information. To achieve the personalized privacy protection of massive social network relational data, a privacy enhancement method for social networks relational data based on personalized differential privacy is proposed. And a dimensionality reduction segmentation sampling(DRS-S)algorithm is proposed to implement this method. First, in order to solve the problem of inefficiency caused by the excessive amount of data in social networks, dimension reduction and segmentation are carried out to divide the data into groups. According to the privacy protection requirements of different users, we adopt sampling method to protect users with different privacy requirements at different levels, so as to realize personalized different privacy. After that, the noise is added to the protected data to satisfy the privacy budget. Then publish the social network data. Finally, the proposed algorithm is compared with the traditional personalized differential privacy(PDP) algorithm and privacy preserving approach based on clustering and noise(PBCN) in real data set, the experimental results demonstrate that the quality of privacy protection and data availability of DRS-S are better than that of PDP algorithm and PBCN algorithm.

关键词： enhanced privacy preserving privacy enhancement method DRS-S algorithm sampling methods personalized differential privacy algorithm Relational databases privacy protection requirements privacy budget data privacy Data security real data set clustering relational databases massive social network relational data social networking (online) sensitive privacy information personalized privacy protection Other topics in statistics information networks real data set noise pattern clustering social software dimensionality reduction segmentation sampling algorithm social network data protected data

Digital Signal Processing for High-Speed THz Communications

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Chinese Journal of Electronics 2022年第3期31卷 534-546页

作者： YU Jianjun WEI Yi School of Information Science and Technology Fudan University

The use of advanced digital signal processing(DSP) technology in the high-speed terahertz(THz) communication can effectively compensate the linear and nonlinear effects of the system and further improve the transmission performance of the system. This paper introduces the principle and application of advanced DSP algorithms such as probability shaping(PS)technology, Volterra series nonlinear compensation algorithm, Kramers-Kronig receiver, look-up table(LUT)pre-distortion compensation technology, pre-equalization and decision-directed least-mean-square equalization algorithm. Combined with DSP algorithms such as PS and LUT pre-distortion, using photon-assisted technology to successfully realize the wireless transmission of vector THz signals higher than 1 Tbit/s on the sub-THz band(D-band) 4 × 4 multiple input multiple output system.

关键词： Terahertz communication Digital signal processing Nonlinear compensation

A Short-Term Precipitation Prediction Model Based on Spatiotemporal Convolution Network and Ensemble Empirical Mode Decomposition

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 738-740页

作者： Yunan Qiu Zhenyu Lu Shanpu Fang the school of Electronics and information Engineering Nanjing University of Information Science and Technology the school of Artificial Intelligence Nanjing University of Information Science and Technology

Dear editor,Regional precipitation,as a very important component system of hydrology,plays a key role in the whole water cycle[1].The dramatic changes of regional precipitation in a short period can easily have a serious impact on the local ecological environment and daily life.Short-term heavy precipitation refers to precipitation events with rainfall of more than 20 mm in one hour or 50 mm in three hours[2].Therefore,how to accurately and timely predict future precipitation is an important research field in meteorology.However,precipitation prediction has always been a challenging task because of its complex spatial and temporal dependence.

关键词： system meteorology editor

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Speech Emotion Recognition Using Cascaded Attention Network with Joint Loss for Discrimination of Confusions

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Machine Intelligence Research 2023年第4期20卷 595-604页

作者： Yang Liu Haoqin Sun Wenbo Guan Yuqi Xia Zhen Zhao School of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China

Due to the complexity of emotional expression, recognizing emotions from the speech is a critical and challenging task. In most of the studies, some specific emotions are easily classified incorrectly. In this paper, we propose a new framework that integrates cascade attention mechanism and joint loss for speech emotion recognition (SER), aiming to solve feature confusions for emotions that are difficult to be classified correctly. First, we extract the mel frequency cepstrum coefficients (MFCCs), deltas, and delta-deltas from MFCCs to form 3-dimensional (3D) features, thus effectively reducing the interference of external factors. Second, we employ spatiotemporal attention to selectively discover target emotion regions from the input features, where self-attention with head fusion captures the long-range dependency of temporal features. Finally, the joint loss function is employed to distinguish emotional embeddings with high similarity to enhance the overall performance. Experiments on interactive emotional dyadic motion capture (IEMOCAP) database indicate that the method achieves a positive improvement of 2.49% and 1.13% in weighted accuracy (WA) and unweighted accuracy (UA), respectively, compared to the state-of-the-art strategies.

关键词： Speech emotion recognition(SER) 3-dimensional(3D)feature cascaded attention network(CAN) triplet loss joint loss

A Novel Trustworthiness Measurement Model Based on Weight and User Feedback

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Chinese Journal of Electronics 2022年第4期31卷 612-625页

作者： ZHOU Wei MA Yanfang PAN Haiyu school of Computer science and technology Huaibei Normal University school of Computer science and information Engineering Changzhou Institute of Technology school of Computer science and information Security Guilin University of Electronic Technology

Software trustworthiness is an essential criterion for evaluating software quality. In componentbased software, different components play different roles and different users give different grades of trustworthiness after using the software. The two elements will both affect the trustworthiness of software. When the software quality is evaluated comprehensively, it is necessary to consider the weight of component and user feedback. According to different construction of components, the different trustworthiness measurement models are established based on the weight of components and user feedback. Algorithms of these trustworthiness measurement models are designed in order to obtain the corresponding trustworthiness measurement value automatically. The feasibility of these trustworthiness measurement models is demonstrated by a train ticket purchase system.

关键词： Component-based software Trustworthiness Weight User feedback Measurement

Secure cooperative output regulation for linear parameter-varying systems under DoS attacks: a resilient observer approach

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science China(information sciences) 2023年第9期66卷 35-49页

作者： Chengcheng FU Hao ZHANG Chao HUANG Zhuping WANG Huaicheng YAN school of Electronic and information Engineering Tongji University school of information science and Engineering East China University of Science and Technology

This paper investigates the cooperative output regulation problem of heterogeneous linear parameter-varying multi-agent systems under denial-of-service(DoS) attacks. The matrix and state of the exosystem are taken to be unknown to the followers. Moreover, with the assumption that only a directed spanning tree exists in the communication topology, a resilient observer is proposed to exponentially estimate the global information, which can also be effective under DoS attacks with a certain intensity. Afterward,to avoid using the exact value of the exosystem matrix, a distributed online algorithm is proposed, through which the linear parameter-varying output regulation equation is asymptotically solved. Based on the resilient observer and the solution of the output regulation equation, a distributed regulator is proposed to achieve asymptotic cooperative output regulation for all agents. Some numerical simulations are conducted to verify the effectiveness of the proposed observer, algorithm, and controller.

关键词： cooperative output regulation heterogeneous multi-agent systems DoS attacks linear parameter-varying systems

Hyperspectral Image Classification Based on A Multi-Scale Weighted Kernel Network

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Chinese Journal of Electronics 2022年第5期31卷 832-843页

作者： SUN Le XU Bin LU Zhenyu school of Computer science Nanjing University of Information Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology school of Artificial Intelligence Nanjing University of Information Science and Technology

Recently, many deep learning models have shown excellent performance in hyperspectral image(HSI) classification. Among them, networks with multiple convolution kernels of different sizes have been proved to achieve richer receptive fields and extract more representative features than those with a single convolution kernel. However, in most networks, different-sized convolution kernels are usually used directly on multibranch structures, and the image features extracted from them are fused directly and simply. In this paper, to fully and adaptively explore the multiscale information in both spectral and spatial domains of HSI, a novel multi-scale weighted kernel network(MSWKNet) based on an adaptive receptive field is proposed. First, the original HSI cubic patches are transformed to the input features by combining the principal component analysis and one-dimensional spectral convolution. Then, a three-branch network with different convolution kernels is designed to convolve the input features, and adaptively adjust the size of the receptive field through the attention mechanism of each branch. Finally, the features extracted from each branch are fused together for the task of classification.Experiments on three well-known hyperspectral data sets show that MSWKNet outperforms many deep learning networks in HSI classification.

关键词： Hyperspectral image classification Convolutional neural network Kernel network Multi-scale features Attention mechanism

A Constraint Adaptive Multi-Tasking Differential Evolution Algorithm:Designed for Dispatch of Integrated Energy System in Coal Mine

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Tsinghua science and technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang Dunwei Gong school of information and Control Engineering China University of Mining and TechnologyXuzhou 221116China School of Information Science and Technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions reduction.However,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong multi-constraint.Existing constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch performance.To tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint adaptive.Then we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks effectively.The helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible domain.The purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local search.Additionally,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and convergence.Finally,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM scenarios.Results demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

RFPose-OT:RF-based 3D human pose estimation via optimal transport theory

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Frontiers of information technology & Electronic Engineering 2023年第10期24卷 1445-1457页

作者： Cong YU Dongheng ZHANG ZhiWU Zhi LU Chunyang XIE Yang HU Yan CHEN school of information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China school of Cyber science and technology University of Science and Technology of ChinaHefei 230026China School of Information Science and Technology University of Science and Technology of ChinaHefei 230026China

This paper introduces a novel framework,i.e.,RFPose-OT,to enable three-dimensional(3D)human pose estimation from radio frequency(RF)signals.Different from existing methods that predict human poses from RF signals at the signal level directly,we consider the structure difference between the RF signals and the human poses,propose a transformation of the RF signals to the pose domain at the feature level based on the optimal transport(OT)theory,and generate human poses from the transformed features.To evaluate RFPose-OT,we build a radio system and a multi-view camera system to acquire the RF signal data and the ground-truth human poses.The experimental results in a basic indoor environment,an occlusion indoor environment,and an outdoor environment demonstrate that RFPose-OT can predict 3D human poses with higher precision than state-of-the-art methods.

关键词： Radio frequency sensing Human pose estimation Optimal transport Deep learning

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