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Realization of Identity Card and Face Recognition Two-Factor Authentication System Based on Wechat

Realization of Identity Card and Face Recognition Two-Factor...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2019

作者： Kuang, Guofang Xu, Hongsheng Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783030251277

In this paper, based on image recognition technology, combined with WeChat Mini Program’s development technology, which is widely used in social field, the two-factor authentication technology of identity card and face recognition is deeply studied in this paper. Face recognition refers to face detection and face recognition. A feasible face detection scheme is obtained by experiments, and then a suitable face recognition scheme is designed according to the needs of users to make it suitable for mobile terminals. This paper designs and implements identity card and face recognition two-factor authentication system based on WeChat Mini Program. © 2020, Springer Nature Switzerland AG.

关键词： Face recognition

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Construction of big data analysis Platform Based on Semantic Rough Concept Lattice Model

Construction of Big Data Analysis Platform Based on Semantic...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2019

作者： Xu, Hongsheng Kuang, Guofang Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783030251277

This article first describes in detail big data mining technology based on semantic rough concept lattice model. data mining is facing practical application, even in the face of the same data set. SaaS service platform is mainly responsible for the realization of the function of the service layer, the layer of all business, application of public operation abstract. The external system of the platform is to store the data related to the platform and the data exchange. The paper presents construction of big data analysis platform based on semantic rough concept lattice model. Finally, the experimental results show that the proposed big data analysis method is effective. © 2020, Springer Nature Switzerland AG.

关键词： data mining

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Application of big data mining technology in intelligent safe production on cloud computing platform

Application of big data mining technology in intelligent saf...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

作者： Xu, Hongsheng Fan, Ganglong Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783319987750

Clustering and classification are two of the most important technology in data mining;they were respectively used to detect data and decision space to feature space dependent. The paper describe analysis of intelligent association rule extraction technology based on big data mining method firstly, then discusses application of cloud computing and Internet of things technology in intelligent security. The paper presents application of big data mining technology in intelligent safe production on cloud computing platform. The final experiment shows that the proposed method of big data mining is very effective. © Springer Nature Switzerland AG 2019.

关键词： data mining

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Construction of Search Engine System Based on Multithread Distributed Web Crawler 6th

Construction of Search Engine System Based on Multithread Di...

引用

6th International Conference on Frontier Computing, FC 2018

作者： Xu, Hongsheng Fan, Ganglong Li, Ke Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9789811336478

The search engine is mainly to the user request information carries on the automatic information collection. Web crawler is an important part of search engine, it is an automatic extraction of web pages for search engines to download web pages from the web. The search system faces hundreds of millions of pages across the Internet, and there are several search servers in each data center, and there may be several crawlers deployed on each grab server. This constitutes a multithread distributed web crawler search system. The paper presents construction of search engine system based on multithread distributed web crawler. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Web crawler

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An improved strategy of distributed network crawler based on hadoop and P2P

An improved strategy of distributed network crawler based on...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

作者： Xu, Hongsheng Li, Ke Fan, Ganglong Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783319987750

Crawler technology is a technology that uses web crawlers to capture information on a web page to get valuable information. The web crawler is a program that automatically extracts web pages. It downloads Web pages from WEB for search engines. It is an important part of the search engine. This paper introduces the architecture of distributed Hadoop platform, and by the principle of the web crawler puts forward design scheme of distributed crawler based on Hadoop and P2P technology, and ultimately determine the system layout of distributed crawler, module partition and distributed crawler flow control and power can be realized. © Springer Nature Switzerland AG 2019.

关键词： Web crawler

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Design of Improved Deep Convolution Network Model

Design of Improved Deep Convolution Network Model

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2019

作者： Xu, Hongsheng Wang, Lan Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing & Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783030251277

Convolution neural network is a feed-forward neural network which contains convolution calculation and has depth structure. In this paper, the basic structure and operation principle of convolution neural network are analyzed. CNN has the best effect in handwritten recognition, and the application of CNN in face-based gender recognition is also very good. In this paper, the factors that influence the convolution neural network model are analyzed. In this paper, the improved deep convolution network model is proposed, and the results show that the improved method can effectively improve the classification effect and classification accuracy of the convolution neural network. © 2020, Springer Nature Switzerland AG.

关键词： Convolution

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Improvement of semantic annotation method in semantic internet of things based on conceptual ontology model

Improvement of semantic annotation method in semantic intern...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

作者： Xu, Hongsheng An, Luosheng Fan, Ganglong Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783319987750

With the development of semantic Web technology, it provides a better solution to solve this problem, as the core of the semantic Web;ontology is a conceptual model of a clear specification. It provides a strong support for semantic similarity computation. This paper describes the semantic annotation method in the semantic web. This paper analyzes the construction of conceptual ontology in the semantic web. The paper presents improvement of semantic annotation method in semantic Internet of things based on conceptual ontology model. © Springer Nature Switzerland AG 2019.

关键词： Ontology

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Research on topic crawler strategy based on web page extension and best priority search algorithm

Research on topic crawler strategy based on web page extensi...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

作者： Xu, Hongsheng Lv, Yanqing Fan, Ganglong Luoyang Normal University Luoyang471934 China Henan Key Laboratory for Big Data Processing and Analytics of Electronic Commerce Luoyang471934 China

ISBN: (纸本)9783319987750

The topic crawler filters the topic independent links according to a certain web page analysis algorithm, keeps the topic related links and puts them into the URL queue to be fetched. Then, according to a certain search strategy, the next page URL is selected from the queue and repeated until a certain condition of the system is reached. The best priority search strategy predicts the similarity between candidate URL and target pages according to a certain web page analysis algorithm, and selects one or more URL which is the best evaluation to grab. The crawler algorithm based on Web page extension is to evaluate the web page or website with indirect relation through known web pages or data. The paper presents research on topic crawler strategy based on web page extension and best priority search algorithm. © Springer Nature Switzerland AG 2019.

关键词： Learning algorithms

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Multi-scale fusion clustering algorithm for urban travel features 3

Multi-scale fusion clustering algorithm for urban travel fea...

引用

2023 3rd International Conference on Intelligent Traffic Systems and Smart City, ITSSC 2023

作者： Zhang, Zixiang Zhao, Zhilong Deng, Jiaming Zhao, Yingying Xu, Tao Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Key Laboratory of Geographical Information Science Ministry of Education East China Normal University Shanghai200241 China School of Computer and Information Engineering Henan University Kaifeng475004 China International Education College Henan University Zhengzhou450046 China Henan Technology Innovation Center of Spatio-Temporal Big Data Henan University Zhengzhou450046 China Henan Industrial Technology Academy of Spatio-Temporal Big Data Henan University Zhengzhou450046 China

ISBN: (纸本)9781510672963

Urban travel data typically encompass various temporal and spatial scales and features. Nonetheless, existing traffic travel feature analysis often focuses on a single spatial scale, which may overlook crucial information and hinder features at different scales. Consequently, this could reduce the accuracy of travel pattern recognition. To solve this problem, we introduce a multi-scale fusion transformation algorithm. In our approach, we first establish a multi-level taxi travel data grid system. Then, we apply the I-Clique clustering algorithm to perform grid clustering at each level of the system to identify taxi travel feature regions of different scales. Subsequently, a multi-scale fusion pyramid model is constructed utilizing the acquired travel feature regions at various scales. Finally, we determine the transformation relationships between scales in the pyramid model, enabling the identification of travel feature areas across both known and unknown scales. This approach facilitates the recognition of travel features within cities at any scale. Experimental results demonstrate that the multi-scale fusion transformation algorithm enhances our understanding of spatial aggregation patterns and the hierarchical structure of geographical entities, offering a novel approach for multi-scale urban traffic analysis. © 2024 SPIE. All rights reserved.

关键词： Clustering algorithms

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An application-oriented multi-granularity vehicle trajectory data indexing structure based on concept lattice 5

An application-oriented multi-granularity vehicle trajectory...

引用

5th International Conference on Computer Information Science and Application Technology, CISAT 2022

作者： Xu, Tao Zhang, Zixiang Ma, Xiaqing Deng, Jiaming Zhao, Yingying Li, Xiang Key Laboratory of Geographical Information Science Ministry of Education East China Normal University Shanghai200241 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China School of Computer and Information Engineering Henan University Kaifeng475004 China International Education College Henan University Zhengzhou450046 China Henan Technology Innovation Center of Spatio-Temporal Big Data Henan University Zhengzhou450046 China Henan Industrial Technology Academy of Spatio-Temporal Big Data Henan University Zhengzhou450046 China

ISBN: (纸本)9781510660076

Massive amount of vehicle trajectory data is an important data source and has been widely used in many research fields. However, due to the huge volume and variety of application scenarios, it is still not easy to achieve the application-oriented and efficient retrieval of vehicle trajectory. The paper proposes a multi-granularity vehicle trajectory index method based on the concept lattice model. The method identifies the multi-granularity feature regions for application requirements to segment vehicle trajectory and employs the concept lattice model to maintain the complex relationships between vehicle trip and the feature regions, to realize the vehicle travel trajectory data retrieval for the multi-granularity feature regions. In this experiment, shanghai city is divided into 21 feature regions according to the county-level area of Shanghai, and the concept lattice index structure of vehicle trips is constructed. The availability and efficiency of the proposed method are verified by the comparative experimental results. © 2022 SPIE.

关键词： Vehicles

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