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Comparison of machine learning algorithms for smart license number plate detection system

Comparison of machine learning algorithms for smart license ...

引用

international conference on Image Processing and Capsule Networks, ICIPCN 2020

作者： Suresan, Anjali G, Divyaa Mahalakshmi Venkatraman, Meenakshi Suresh, Shruthi P, Supriya Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9783030518585

Identification of License plates of vehicles is significant in various monitoring and security applications. This paper involves two major processes: image processing of the License plate and classification of the individual characters. Preprocessing of the number plate image is done for noise removal by converting it to a grayscale image followed by conversion to a binary image. The Bounding Box method is implemented for the segmentation of individual characters that are to be classified. Two Supervised machine learning algorithms namely Support Vector Machine (SVM) and Decision Tree is used for the classification. The performance indices of the two algorithms are analysed to determine the more accurate method. It is proposed to implement the algorithm on a stand-alone model to employ it for real-time applications after improving the accuracy with more training and test data. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Decision trees

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Design of Multi-layer Industrial Internet of data Mine Network Model Based on Edge Computation

Design of Multi-layer Industrial Internet of Data Mine Netwo...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Peng, Haibo Wu, Qiaoshun Li, Jie Zhou, Rong Yunnan KISC Elect Informat Technol Co Ltd Kunming 650302 Yunnan Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The main role of edge computing in industrial systems is the absorption and screening of data, storage analysis, which maximizes efficiency. In this paper, we implement the multi-layer industrial IoT data mining network model design based on edge computing. In this design, the functional model and the architecture model design are mainly composed of two parts. The functional model design senses the data through various processes such as data acquisition devices, and then the MES system can transmit the collected data that is barrier-free, highly reliable, and highly secure. The architecture model design integrates all key sites into a network platform, adopts software and hardware comprehensive modeling, and multi-language hybrid development to establish an open bus network. In addition, the data transmission mechanism between each site adopts synchronous and asynchronous combination to effectively ensure normal data transmission. This design can be applied to many types of steel enterprise production, testing data requirements and changeable testing and analysis tasks, effectively solving the real-time, convenient and efficient process of data transmission, reducing the intensity of manual operations, and helping to improve profit. And the security of edge computing is very high, which is one of the reasons why it has won the favor of many large enterprises.

关键词： Edge computing Industrial Internet of Things Heterogeneous data exchange SCADA MES

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Towards visual data science - An exploration 1st

Towards visual data science - An exploration

引用

1st international conference on Human Interaction and Emerging Technologies, IHIET 2019

作者： Tropmann-Frick, Marina Andersen, Jakob Smedegaard Department of Computer Science Hamburg University of Applied Sciences Hamburg Germany

ISBN: (纸本)9783030256289

Visual perception is one of the most essential abilities for humans. This ability allows us to discover the world around us and to understand interdependencies with regard to both global context and particular concrete problem statement. We present in this paper an exploration of visualization and visual analytics approaches. Thereby, we focus on the field of data science with data-centric analytic methods and applications. data science is closing the gap between visualization techniques, traditional hypothesis-driven methods and processing of mostly huge, heterogeneous and noisy data. A combination of smart visualization, advanced analytical methods and additional (domain) knowledge, mostly provided by humans, makes it possible to gain insights and discover new opportunities for problem solving. © 2020, Springer Nature Switzerland AG.

关键词： Visualization

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Research on the Governance Ability of intelligent Government in the Era of Big data 2nd

Research on the Governance Ability of Intelligent Government...

引用

2nd international conference on Decision Science and Management, ICDSM 2019

作者： Chen, Sijing Hunan International Economics University Business School Changsha China

ISBN: (纸本)9789811535871

The arrival of the era of big data has provided new technologies and ways of thinking for the construction of "smart government," bringing opportunities for promoting social governance and transformation of government functions and improving government governance and public services. Therefore, based on the significance of building a smart government in the era of big data, this paper explores the three aspects of building a smart government and then puts forward countermeasures to improve the governance capacity of a smart government in the era of big data, so as to provide some references for improving the governance capacity of a smart government in the era of big data. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Research on 5G in Electric Power System 10th

Research on 5G in Electric Power System

引用

10th international conference on Computer Engineering and Networks, CENet 2020

作者： Liu, Long Kong, Wei-wei Bi, Shan-yu Hu, Guang-yu NARI Group Corporation/State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9789811584619

The collection, bearing, analysis and application of the basic electric power data from the ubiquitous Internet of things have put forward new and higher requirements for the data collection, bearing, analysis and application, and higher requirements for communication technologies and methods is raised. In view of this situation, the integration and development means of 5G technology and power system business are put forward, and the application of typical business scenarios in various power systems under 5G technology is analyzed. A typical accurate load control service is selected for testing, and the test results show that the delay is improved. The application analysis of 5G in electric power system supports the Internet of things application, provides the technical support, and lays a solid foundation for the popularization and application of 5G technology. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： smart power grids

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Novel Workload Balancing Method for UAV-based Edge Cloud computing Systems with Handover

Novel Workload Balancing Method for UAV-based Edge Cloud Com...

引用

IEEE international conference on Communications (IEEE ICC) / Workshop on NOMA for 5G and Beyond

作者： Shimada, Hayato Kawamoto, Yuichi Kato, Nei Tohoku Univ Grad Sch Informat Sci Sendai Miyagi Japan

ISBN: (纸本)9781728150895

Internet of Things (IoT) has become an integral and pervasive part of everyday life, e.g. the infrastructure of intelligent traffic systems and smart cities. Such next-generation IoT applications require intelligent data processing that is performed via edge cloud computing (ECC) within a short period. In ECC, the edge server executes data processing;this is expected to reduce service delay. However, in the existing ECC research, infrastructure such as radio towers for communication and base stations for installing edge servers is indispensable;thus, it cannot respond to the demand for computing resources in the event of large-scale disasters and in infrastructureless areas. Therefore, researchers are studying the provision of computing resources using unmanned aerial vehicles (UAVs). On account of these studies, computation resources may be provided in several situations. However, in the face of this technology, to provide services with the delay time that the application allows, it is necessary to consider the workload balance and communication range of the UAV. In this paper, we propose a handover solution method considering workload balance and create a mathematical model with a transparent system. Moreover, numerical analyses show the effectiveness of the proposed method. With this contribution, it is possible to provide communication and computational resources in infrastructureless areas.

关键词： Internet of things

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Research on theoretical structure design of smart community large data platform 4th

Research on theoretical structure design of smart community ...

引用

4th international conference on intelligent computing, Communication and Devices, ICCD 2018

作者： Jia, Nan An, Xiao Qian, Jing Chen, Yongqiang Liu, Yi Department of Engineering Physics Institute of Public Safety Research Tsinghua University Beijing100084 China Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9789811394058

smart community is the basic unit of smart city, and a community large data platform is an important guarantee to realize the safety of an intelligent community. It is pointed out in this paper that monitoring and control, forecasting and alarm, and intelligent prevention are the key techniques of risk prevention of smart community. Thus, large data platform is the foundation of risk prevention in the smart community. Finally, the structure and the construction process to carry out the theoretical structure design of intelligent community risk prevention of large data platform. The research provides theoretical and technical support for the next step of big data platform construction and risk prevention. © Springer Nature Singapore Pte Ltd 2020.

关键词： smart city

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intelligent terminal data compression method based on edge computing 3

Intelligent terminal data compression method based on edge c...

引用

3rd international conference on Information Technologies and Electrical Engineering, ICITEE 2020

作者： Zhao, Zijing Lu, Jingya Dong, Delong Lu, Jizhe Yang, Guang Chen, Xin State Grid Tianjin Electric Power Company Tianjin China Metrology Institute China Electric Power Research Institute Beijing China

ISBN: (纸本)9781450388665

With the rapid economic and social development, China has basically achieved full coverage of smart meters. Power companies have accumulated massive amounts of smart meter measurement data, which increases the workload of data analysis and processing on the server side, and also greatly increases the pressure on the channel. In order to achieve efficient compression of metering data and reduce pressure on data analysis and processing, this paper proposes an intelligent terminal data compression method based on edge computing. Under the framework of edge computing, this method uses the empirical mode decomposition algorithm to decompose the original distribution information data, based on the wavelet threshold denoising algorithm to reduce the noise of the components, and uses the set partitioning in hierarchical trees algorithm to compress the cleaned data. Finally, an example analysis verifies the effectiveness and optimization effect of the proposed method. It reduces the pressure of the intelligent measurement system on the data transmission of the communication channel, and at the same time achieves the purpose of effectively cleaning and compressing the measurement data. © 2020 ACM.

关键词： data compression

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Prediction of Diabetes Using Ensemble Learning Model 1

引用

international conference on Machine Intelligence and Soft computing, ICMISC 2020

作者： Singh, Sapna Gupta, Sonali J.C. Bose University of Science and Technology YMCA Faridabad India

ISBN: (数字)9789811595165

ISBN: (纸本)9789811595158

Diabetes is an illness which may cause blood sugar, by producing insufficient amount of insulin. Untreated diabetes can increase the danger of heart attack, cancer, liver problem and other disorders. All over the world, billions of people are affected by diabetes disease. Early treatment of diabetes is very important to maintain a healthy lifestyle and culture. Diabetes is a major reason of global concern as the cases of diabetic patients are increasing rapidly day by day. Machine learning is an advance technical growing field which helps to understand the meaning of real data. It is widely used in healthcare community for detecting and analyzing serious and complex situations. Machine learning is a mathematical computational model which is used for learning new knowledge from its old knowledge and improves model efficiency to make more accurate results. Machine learning is the process of gathering, selecting, analyzing, and designing large real-time dataset. This research work using a special class of machine learning technique called bagging and boosting which is also known ensemble learning techniques. In this work, ensemble learning techniques are experimented on Pima Indians dataset to analyze and identify diabetic patient with highest risk factors using Python language. To classify a diabetic patient and non-diabetic patient, five different predictive models, namely random forest (RF), light gradient boost (LG Boost), extreme gradient boost (XGBoost), gradient boost (GB), and adaptive boost (AdaBoost) have been used for better prediction of diabetes. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Predictive analytics

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Novel of Web Search Strategy Based on Web Page Block Granularity Analysis Algorithm and Correlation Calculation Model

Novel of Web Search Strategy Based on Web Page Block Granula...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Fan, Ganglong Xu, Hongsheng Luoyang Normal Univ Luoyang 471934 Peoples R China Henan Key Lab Big Data Proc & Analyt Elect Commer Luoyang 471934 Peoples R China

ISBN: (纸本)9783030152352;9783030152345

In this paper, the running parameters of crawler nodes are dynamically adjusted to make them more manageable and configurable. The running parameters include crawling speed, crawling depth, number of crawler threads. After processing and organizing the information, the search engine provides Web information query service for users, crawls continuously on Internet, collects web information. Then the information is understood, extracted, organized and processed by the indexer, and the index database is established. The paper presents novel of web search strategy based on web page block granularity analysis algorithm and correlation calculation model.

关键词： Web search strategy Web page block granularity Correlation calculation Search engine URL

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