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An Efficient and Robust Facial Image Encryption Algorithm for Biometric Identity systems 4

An Efficient and Robust Facial Image Encryption Algorithm fo...

引用

4th IEEE international conference on Computing, Communication, and intelligent systems, ICCCIS 2023

作者： Kumar, Rajeev Santhanavijayan, A. National Institute of Technology Department of CSE Trichy India

ISBN: (纸本)9798350306118

In comparison to alternative identification methods such as graphical-based passwords, textual-based passwords, and email verification, biometric authentication systems provide improved convenience and security for accessing information systems. Nevertheless, biometric-based systems, including facial recognition, are at risk of tampering attacks on their databases. To guarantee the security of stored facial images and counteract tampering database attacks, it is essential to implement a robust encryption scheme specifically designed for facial images. through the implementation of encryption, the images become impervious to alterations by unauthorized individuals who may gain access to the storage infrastructure. this research paper introduces a robust facial image encryption algorithm specifically created to tackle database tampering attacks. the algorithm has been developed with the purpose of seamlessly integrating it into facial authentication systems. the suggested encryption technique uses the Henon map to shuffle the pixels and applies class-3 one-dimensional cellular automata rules for pixel substitution. the security analysis and experimental findings demonstrate that the proposed method offers an extensive key space and robustly withstands various attacks. the encrypted image shows a minimal correlation between adjacent pixels, indicating high effectiveness. © 2023 IEEE.

关键词： Database systems

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Research on Simulation System of intelligent Network Technology in Energy Management of New Energy Vehicles 4

Research on Simulation System of Intelligent Network Technol...

引用

4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Zhang, Kaixuan Fan, Lihua Automotive Data of China Co. Ltd Tianjin China

ISBN: (纸本)9798350361643

this paper develops IC&NEV simulation software based on UML object-oriented programming, Builder design pattern, MATLAB, PostgreSQL and SuMO. By using Python program, the road network document data is preprocessed and the road network GIS database is established. Builder provides the Director with an abstract interface for building a product that allows the Director to hide the appearance and structure of a particular product. the simulation program developed in this paper can provide help for the research of optimal control of integrated circuits and dynamic systems of new energy vehicles. Using abstract syntactic expression, the information transfer between TCP/IP interfaces is realized. the iec61499 compliant controller acts as a data server, while the separate GridlAB-D object acts as a client. In addition, based on the open and closed design ideas of UML, this system not only has the function of secondary development, but also is very suitable for the research of multi-vehicle coordination control. the road network model is generated by using OpenStreetMap editor and JOSM. Compared with manual modeling, this method is faster and more consistent with the actual road network. © 2024 IEEE.

关键词： Energy management

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Finger Pointnet: An End-to-end Embedded Network for 3D Fingerprint Verification 4

Finger Pointnet: An End-to-end Embedded Network for 3D Finge...

引用

4th IEEE international conference on pattern recognition and Machine Learning, PRML 2023

作者： Huang, Yixin Liu, Feng Yang, Dongliang Song, Changjiang Shenzhen University Shenzhen China Heilongjiang Academy of Sciences Intelligent Manufacturing Research Institute Heilongjiang China

ISBN: (纸本)9798350324303

Contactless 3D fingerprint gains significant attention in recent years. Much of previous works for 3D fingerprint verification were based on minutiae. they required a series of laborious preprocessing and relied on software to extract minutiae. To alleviate these problems, this research presents an end-to-end embedded network for fingerprint verification. Firstly, we propose to extract ridge lines from the original large and redundant 3D fingerprint point cloud data. then, we design two weight-shared encoders to extract features from a pair of positive 3D fingerprints. Finally, loss backpropagation from the hardest sample in a mini-batch permitted in our approach makes it can distinguish negative samples. the experiments on a public database and an in-house database verify that our approach achieves desirable performance and significantly speeds up feature extraction and matching compared with traditional approaches. © 2023 IEEE.

关键词： Computer vision

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A dual-stream spatial-temporal detector for action recognition 4

A dual-stream spatial-temporal detector for action recogniti...

引用

4th international conference on Computer Vision and pattern Analysis, ICCPA 2024

作者： Wei, Pingping Li, Jiale Liu, Peiran Li, Li Xu, Yifei Wang, Ling State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiao-Tong University Xi’an710049 China School of Software Xi’an Jiao-Tong University Shaanxi Xi’an710049 China Shaanxi Joint Key Laboratory for Artifact Intelligence Shaanxi 710054 China Xi’an Key Laboratory for Social Intelligence and Complex Data Processing Shaanxi 710054 China Alltuu Inc. Zhejiang Hangzhou310000 China

ISBN: (纸本)9781510682528

In response to the issue that existing human action recognition models can not make full use of complementary information from different modalities, this thesis proposes a multi-path attention module MA to form the MA-GCN model. modalities, this thesis proposes a dual-stream human action recognition model SRHAR that fuses skeleton data and RGB data. this model utilizes LAF proposed in this thesis to fuse skeleton features and RGB features. the introduction of skeleton modality enables the RGB modality to obtain the RGB features. the introduction of skeleton modality enables the RGB modality to obtain complementary information, resulting in more accurate prediction results. this algorithm focuses more on recognition accuracy and has a slower recognition speed, but achieves leading performance in terms of accuracy on public datasets. © 2024 SPIE.

关键词： Musculoskeletal system

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Research on intelligent Semantic recognition and Self-Organizing Feature Mapping of Chinese Linguistics under Big Data Informationization 4

Research on Intelligent Semantic Recognition and Self-Organi...

引用

4th international conference on Smart systems and Inventive Technology, ICSSIT 2022

作者： Chen, Zhihua Department of General Foundation Requisite Teaching and Research Guangxi Police College GuangXi NanNing China

ISBN: (纸本)9781665401180

In order to study the intelligent semantic recognition of Chinese linguistics under the informationization of big data, this paper designs a set of quantified pressure index system, and introduces a self-organizing feature map (SOM) neural network model with strong clustering and fault tolerance. Explain that on the basis of the SOM network model and algorithm, apply the clustering function of SOM to construct the SOM network model in MATLAB language, showing the visualization characteristics of the self-organizing feature map of Chinese linguistics for clustering, including the visualization and clustering process. Visualization of clustering results. © 2022 IEEE

关键词： Informatization

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Mining and recognition of English Learning patterns of Mobile Users Based on intelligent Algorithm 4

Mining and Recognition of English Learning Patterns of Mobil...

引用

4th international conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2022

作者： Li, Jingtai School of Foreign Languages Jiaying University Guangdong Meizhou China

ISBN: (纸本)9781665456357

the latest research results show that activity recognition based on frequent pattern mining is the main method. Its advantages are that the activity patterns obtained through learning mining are comprehensive and accurate, and the recognition effect of activities in the corresponding environment is good. Besides, some activities that can only be carried out in a specific environment can be identified. this study attempts to use data mining technology to help foreign language education systems to further transform massive data, so as to mine more valuable content, helping educators to further tap teaching potential, and improving the efficiency of teaching resources utilization. © 2022 IEEE.

关键词： Data mining

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intelligent Home Surveillance System using Convolution Neural Network Algorithms 4

Intelligent Home Surveillance System using Convolution Neura...

引用

4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Sathya, R. Bharathi, V.C. Ananthi, S. Vaidehi, K. Sangeetha, S. Kongunadu College of Engineering and Technology Department of It Tamil Nadu Trichy India VIT-AP University School of Computer Science and Engineering Andhra Pradesh Amaravati India Sri Eshwar College of Engineering Department of CSE Coimbatore India Stanley College of Engineering and Technology for Women Department of Artificial Intelligence and Data Science Telangana Hyderabad India Kongunadu College of Engineering and Technology Department of Information Technology Thottiam India

ISBN: (纸本)9798350300093

the creation of an automated security system aims to protect residences and workplaces by automating visitor entrance and enabling more flexibility in visitor record maintenance. Among all biometric authentications, face recognition is very secure because of unique facial features. there are two phases in authentication, face mask detection and face recognition. In first phase, Grassmann algorithm is used for face mask detection. If any mask is discovered, an alarm will sound for the user to remove the mask and in second phase face recognition is done through CNN. the CNN method is utilized to compare facial traits, and if an outsider is found, a warning message is then displayed to the user. Real time datasets are collected for training and testing the CNN model. the executed result gives 98.02% higher accuracy compared to existing method. © 2023 IEEE.

关键词： Face recognition

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intelligent Segmentation Framework and Data Hierarchy of Chinese Language and Literature Based on Semantic recognition 4

Intelligent Segmentation Framework and Data Hierarchy of Chi...

引用

4th international conference on Smart systems and Inventive Technology, ICSSIT 2022

作者： Wang, Dan College of Education Yunnan Technology and Business University Yunnan651700 China

ISBN: (纸本)9781665401180

Based on semantic recognition, this paper studies the intelligent segmentation framework and data layering of Chinese language and literature. First of all, in this paper, in the study of predicting Chinese semantic word-building patterns, based on binary classification Logistic regression and naive Bayes to construct Chinese sentence segmentation patterns for intelligent simulation experiments. then the eight types of data in the annotated corpus are grouped in pairs, and each sample set is divided into data stratification, so that the two-class Logistic regression model and the naive Bayes model are first based on the training set of each group to learn semantic word formation rules., And then predict the semantic word formation mode on the test set of each group, and the result shows that the sentence segmentation efficiency is increasedby 6.5%. © 2022 IEEE

关键词： Semantics

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Research on Fault Analysis and Remote Fault Diagnosis Technology of New Large Capacity Synchronous Condenser 4

Research on Fault Analysis and Remote Fault Diagnosis Techno...

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4th IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Chen, Jiang Chuan, Sun Chao, Xia Jiangsu Fangtian Electric Technology Co. Ltd Nanjing China China Electric Power Research Institute Beijing China

ISBN: (纸本)9798350359589

Synchronous condensers offer significant benefits in large reactive power capacity and strong voltage support ability, which can effectively solve prominent problems such as commutation failure and voltage drop of ultra-high voltage DC converters. they are increasingly widely used in power grids. However, the large-capacity condenser has a large volume and complex structure and is prone to faults, which urgently requires research on fault feature analysis and diagnosis technology. this article analyzes the features of large-capacity synchronous condensers and their engineering advantages, such as increasing the short-circuit ratio of the receiving power grid, improving the transmission limit power, working in a forced excitation state for voltage support in the event of a commutation failure at the UHVDC receiving end, absorbing excess reactive power to suppress sudden voltage rise during DC blocking, and providing dynamically adjustable reactive power support for the AC power grid through flexible switching of late or leading phase states. this article provides common faults, such as mass imbalance, misalignment, friction, oil film oscillation, etc. At the same time, the fault characteristics are analyzed using computer simulation analysis, laboratory simulation analysis, and on-site measurement testing methods. A standard fault diagnosis method for synchronous condensers is proposed on this basis, utilizing fault pattern recognition and credibility evaluation. By establishing a library of fault models for the synchronous condenser and employing time-domain and frequency-domain signal analysis techniques, the credibility and nature of the fault are determined by calculating the instantaneous values and rate of change of the sampled signal using eigenvalues. through the comparison and analysis of pertinent standards and historical data, the severity of the fault is ascertained, along with the trend and severity of the problematic synchronous condenser. the findings

关键词： condenser Credibility evaluation Fault analysis fault diagnosis pattern recognition

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Partial Discharge pattern recognition in High Voltage Transmission Cable Project 4

Partial Discharge Pattern Recognition in High Voltage Transm...

引用

4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Zhu, Guangxiuyuan Wang, Shengjie Zhang, Yongsheng Jiang, Ling Li, Qiuyang Zhang, Daping Electric Power Research Institute of State Grid Qinghai Electric Power Company Xining810008 China Qinghai Key Laboratory of High Altitude Electric Power Research Xining810008 China Qinghai High Altitude Power Engineering Technology Research Center Xining810008 China State Grid Qinghai Electric Power Company Xining810001 China Xining Power Supply Company State Grid Qinghai Electric Power Company Xining810003 China

ISBN: (纸本)9798350361643

this paper aims to improve the reliability and safety of cables, prolong the service life of cables and reduce the operating cost of power systems. the paper examines in detail how partial discharge (PD) patterns are identified in high-voltage transmission cable projects. this paper tests the performance of several layers of a convolutional neural network (CNN) to increase recognition efficiency and accuracy. During the experiment, unified network parameters are set, including the use of maximum pooling mode, ReLU activation function, and 32 33-size convolution kernels in each layer. By contrasting the recognition accuracy of 1-layer, 2-layer, 3-layer, 4-layer, 6-layer, and 9-layer CNN, the paper's findings indicate that: (1) CNN's recognition accuracy peaks at 90.77% when there are two network layers. However, as the number of layers increases, the accuracy of recognition gradually declines. this result reveals that moderately increasing the network depth is helpful to improve the performance in PD pattern recognition of high voltage transmission cables, but too deep network may lead to over-fitting. (2) CNN is stable in the detection of most defect types, while Support Vector Machine (SVM) is the best in some specific defects. Back propagation neural network (BPNN) performs well in some cases, but its overall performance fluctuates greatly. these results are influenced by many factors, such as defect characteristics, model parameters and data set size. therefore, in practical application, it is necessary to select a suitable model for defect detection according to specific scenarios and requirements. this paper provides a useful reference for the follow-up research in high voltage transmission cable project. © 2024 IEEE.

关键词： Defects

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