Chinese Journal of Electronics最新文献_第3页

Optimization of Binary Randomized Response Based on Lanke Privacy and Utility Analysis

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.272

Yihui Zhou;Wenli Wang;Jun Yan;Zhenqiang wu;Laifeng Lu

{"title":"Optimization of Binary Randomized Response Based on Lanke Privacy and Utility Analysis","authors":"Yihui Zhou;Wenli Wang;Jun Yan;Zhenqiang wu;Laifeng Lu","doi":"10.23919/cje.2023.00.272","DOIUrl":"https://doi.org/10.23919/cje.2023.00.272","url":null,"abstract":"Currently, it has become a consensus to enhance privacy protection. Randomized response (RR) technique, as the mainstream perturbation mechanism for local differential privacy, has been widely studied. However, most of the research in literature managed to modify existing RR schemes and propose new mechanisms with better privacy protection and utility, which are illustrated only by numerical experiments. We study the properties of generalized binary randomized response mechanisms from the perspectives of Lanke privacy and utility. The mathematical expressions of privacy and utility for the binary RR mechanism are given respectively. Moreover, the comparison principle for privacy and utility of any two mechanisms is proved. Finally, the optimization problem of the binary RR mechanism is discussed. Our work is based on a rigorous mathematical proof of privacy and utility for the general binary RR mechanism, and numerical verification illustrates the correctness of the conclusions. It can provide theoretical support for the design of binary RR mechanism and can be applied in data collection, analysis and publishing.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"242-256"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891974","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy-Efficient D2D-Aided Dual UAV Data Collection

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.271

Qiulei Huang;Wei Wang;Zhaohui Song;Nan Zhao

引用次数: 0

Fault Diagnosis for Railway Point Machines Using VMD Multi-Scale Permutation Entropy and ReliefF Based on Vibration Signals

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.258

Yongkui Sun;Yuan Cao;Peng Li;Shuai su

引用次数: 0

Multimodal Cross-Attention Mechanism-Based Algorithm for Elderly Behavior Monitoring and Recognition 基于多模态交叉注意机制的老年人行为监测和识别算法

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.263

Hao Liu;Zhiquan Feng;Qingbei Guo

{"title":"Multimodal Cross-Attention Mechanism-Based Algorithm for Elderly Behavior Monitoring and Recognition","authors":"Hao Liu;Zhiquan Feng;Qingbei Guo","doi":"10.23919/cje.2023.00.263","DOIUrl":"https://doi.org/10.23919/cje.2023.00.263","url":null,"abstract":"In contrast to the general population, behavior recognition among the elderly poses increased specificity and difficulty, rendering the reliability and usability aspects of safety monitoring systems for the elderly more challenging. Hence, this study proposes a multi-modal perception-based solution for an elderly safety monitoring recognition system. The proposed approach introduces a recognition algorithm based on multi-modal cross-attention mechanism, innovatively incorporating complex information such as scene context and voice to achieve more accurate behavior recognition. By fusing four modalities, namely image, skeleton, sensor data, and audio, we further enhance the accuracy of recognition. Additionally, we introduce a novel human-robot interaction mode, where the system associates directly recognized intentions with robotic actions without explicit commands, delivering a more natural and efficient elderly assistance paradigm. This mode not only elevates the level of safety monitoring for the elderly but also facilitates a more natural and efficient caregiving approach. Experimental results demonstrate significant improvement in recognition accuracy for 11 typical elderly behaviors compared to existing methods.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"309-321"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10892001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.342

Dengyong Zhang;Feifan Qi;Jiahao Chen;Jiaxin Chen;Rongrong Gong;Yuehong Tian;Lebing Zhang

{"title":"Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise","authors":"Dengyong Zhang;Feifan Qi;Jiahao Chen;Jiaxin Chen;Rongrong Gong;Yuehong Tian;Lebing Zhang","doi":"10.23919/cje.2023.00.342","DOIUrl":"https://doi.org/10.23919/cje.2023.00.342","url":null,"abstract":"The rapid development of the Internet has led to the widespread dissemination of manipulated facial images, significantly impacting people's daily lives. With the continuous advancement of Deepfake technology, the generated counterfeit facial images have become increasingly challenging to distinguish. There is an urgent need for a more robust and convincing detection method. Current detection methods mainly operate in the spatial domain and transform the spatial domain into other domains for analysis. With the emergence of transformers, some researchers have also combined traditional convolutional networks with transformers for detection. This paper explores the artifacts left by Deepfakes in various domains and, based on this exploration, proposes a detection method that utilizes the steganalysis rich model to extract high-frequency noise to complement spatial features. We have designed two main modules to fully leverage the interaction between these two aspects based on traditional convolutional neural networks. The first is the multi-scale mixed feature attention module, which introduces artifacts from high-frequency noise into spatial textures, thereby enhancing the model's learning of spatial texture features. The second is the multiscale channel attention module, which reduces the impact of background noise by weighting the features. Our proposed method was experimentally evaluated on mainstream datasets, and a significant amount of experimental results demonstrate the effectiveness of our approach in detecting Deepfake forged faces, outperforming the majority of existing methods.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"212-221"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891978","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of Noise Margin Between Pure SET-SET and Hybrid SET-PMOS Inverters

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.287

Fan Zhang;Yi Liu;Yibo Wang;Minghu Wu;Sheng Hu;Youli Dong

{"title":"Comparative Analysis of Noise Margin Between Pure SET-SET and Hybrid SET-PMOS Inverters","authors":"Fan Zhang;Yi Liu;Yibo Wang;Minghu Wu;Sheng Hu;Youli Dong","doi":"10.23919/cje.2023.00.287","DOIUrl":"https://doi.org/10.23919/cje.2023.00.287","url":null,"abstract":"Single-electron transistor (SET) is considered as one of the promising candidates for future electronic devices due to its advantages of low power consumption and high integration. The comparative analysis of SET-based inverters, especially the noise margin, is carried out. Pure SET-SET and hybrid SET with p type metal oxide semiconductor (SET-PMOS) inverters are designed for investigation. The effects of SET supply voltage, junction resistance and junction capacitance on noise tolerance and power consumption of inverters are studied. For hybrid SET-PMOS inverters, the noise margin for a logic high (NMH) is less than 60 mV under various conditions, which may become the bottleneck of its application. For pure SET-SET inverters, both NMH and the noise margin for a logic low (NML) could reach 300 mV at a supply voltage of 0.8 V. The minimum power consumption of pure SET-SET and hybrid SET-PMOS inverters is 2.85 nW and 58 nW, respectively. The pure SET-SET inverters have greater noise tolerance and lower power consumption, which is more conducive to large-scale integration. When junction capacitance <tex>$C_{mathrm{J}}=0.0273 text{aF}$</tex> and junction resistance <tex>$R_{mathrm{T}}geq 1 mathrm{M}Omega$</tex> in SET-SET inverters at a supply voltage of 0.8 V, the NMH and NML are not significantly affected by the junction resistance and the noise margin fluctuates at 300 mV.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"146-155"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891966","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on the Impact of Imbalance Between Transmission Lines on Crosstalk: A Novel Perspective of Displacement Current

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2024.00.049

Xiaozhu Lu;Lingnan Song;Hui Xu;Donglin Su

引用次数: 0

Research on Low-Frequency Multi-Directional Piezoelectric Energy Harvester with Combined Cantilever Beam

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.351

Qingying Ren;Yuxuan Liu;Debo Wang

引用次数: 0

A Study of Epileptogenic Foci Localization Algorithm Based on Automatic Detection of Comprehensive Feature HFOs and RF-LR

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.213

Yuxiao Du;Gaoming Li

{"title":"A Study of Epileptogenic Foci Localization Algorithm Based on Automatic Detection of Comprehensive Feature HFOs and RF-LR","authors":"Yuxiao Du;Gaoming Li","doi":"10.23919/cje.2023.00.213","DOIUrl":"https://doi.org/10.23919/cje.2023.00.213","url":null,"abstract":"Studies have shown that fast ripples of 250–500 Hz in epileptic electroencephalography (EEG) signals are more pathological and closer to the epileptogenic focus itself compared to ripples of 80–250 Hz. However, artifacts of fast ripples and high-frequency oscillations (HFOs) are easily confused and difficult to discriminate, and manual visual screening is both time-consuming and unable to avoid subjectivity. To this end, this paper presents a method for localizing epileptogenic foci based on the automatic detection of integrated feature HFOs and random forest-logistic regression (RF-LR). In this paper, we first extract multivariate features from the preprocessed epileptic EEG signals, and use the random forest algorithm to filter out three features with high importance, based on which, suspicious leads containing HFOs are identified. Then, wavelet time-frequency maps were used for the primary screening of suspected leads to improve the signal calibration efficiency and further localize HFOs in time and frequency. Finally, a logistic regression model was used to automatically classify and identify ripples and fast ripples in HFOs. The results show that the sensitivity, specificity, and accuracy of the model for detecting ripple are 89.37%, 88.26%, and 90.1%, respectively; the sensitivity, specificity, and accuracy for detecting fast ripple are 94.31%, 94.83%, and 93.46%, respectively. Compared with single features, the multivariate features in this paper more comprehensively characterize the complex epileptic EEG signals and provide more accurate information for the localization of epileptogenic foci. The automatic detection algorithm of HFOs proposed in this paper can analyze a large amount of data in a short time and has a good detection performance, which can help clinicians accurately determine the region of epileptogenic foci.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"338-349"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891998","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring Potential Barrier Estimation Mechanism Based on Quantum Dynamics Framework

IF 1.6 4区计算机科学

Chinese Journal of Electronics Pub Date : 2025-01-01 DOI: 10.23919/cje.2023.00.293

Quan Tang;Peng Wang

{"title":"Exploring Potential Barrier Estimation Mechanism Based on Quantum Dynamics Framework","authors":"Quan Tang;Peng Wang","doi":"10.23919/cje.2023.00.293","DOIUrl":"https://doi.org/10.23919/cje.2023.00.293","url":null,"abstract":"Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schrödinger equation as a quantum dynamics equation. Through three approximation of the objective function, quantum dynamics framework (QDF) is obtained which describes basic iterative operations of optimization algorithms. Based on QDF, this paper proposes a potential barrier estimation (PBE) method which originates from quantum mechanism. With the proposed method, the particle can accept inferior solutions during the sampling process according to a probability which is subject to the quantum tunneling effect, to improve the global search capacity of optimization algorithms. The effectiveness of the proposed method in the ability of escaping local minima was thoroughly investigated through double well function (DWF), and experiments on two benchmark functions sets show that this method significantly improves the optimization performance of high dimensional complex functions. The PBE method is quantized and easily transplanted to other algorithms to achieve high performance in the future.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 1","pages":"350-364"},"PeriodicalIF":1.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891997","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0