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Digital Society and Intelligent Systems (DSInS), International Conference on

作者： Kun Zhang Jia Zhu Xuebin Huang Haifeng Wang Vaniushkina Dina Kaparova Kumushai Zhe Zhao Penghui Zeng Key Laboratory of Island Tourism Resource Data Mining and Monitoring Ministry of Culture and Tourism Hainan Tropical Ocean University Sanya China College of Art Hainan Tropical Ocean University Sanya China College of Computer Science and Technology Hainan Tropical Ocean University Sanya China Education Center of MTA College of Tourism Hainan Tropical Ocean University Sanya China Hainan Tropical Ocean University Sanya China College of Information and Communication Engineering Hainan University Haikou China

ISBN: (纸本)9781665406314

The article is a series of research results of the smart tourism construction research project in Asia. Through the preliminary research, it analyzes and studies the problems existing in the smart tourism construction of Sanya City, and gives the countermeasures and measures for the smart tourism construction of Sanya City from multiple angles. Suggestions and based on the federal migration algorithm, the Sanya smart tourism information platform was designed, and the comprehensive Sanya smart tourism construction was analyzed and researched.

关键词： Trade agreements Urban areas Asia Task analysis Intelligent systems Information technology

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Corrigendum to “GLRM: Logical pattern mining in the case of inconsistent data distribution based on multigranulation strategy” [Int. J. Approx. Reason. 143 (2022) 78–101]

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International Journal of Approximate Reasoning 2022年 151卷 271-271页

作者： Qian Guo Yuhua Qian Xinyan Liang Institute of Big Data Science and Industry Shanxi University Taiyuan 030006 Shanxi China Engineering Research Center for Machine Vision and Data Mining of Shanxi Province Taiyuan 030006 Shanxi China School of Computer and Information Technology Shanxi University Taiyuan 030006 Shanxi China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan 030006 Shanxi China

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A generalized FSM implementation framework 2nd

A generalized FSM implementation framework

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Hung, Mao-Hsiung College of Information Science and Engineering Fujian University of Technology No. 33 Xuefunan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 33 Xuefunan Road University Town Minhou Fuzhou350118 China

ISBN: (纸本)9783030045814

Finite State Machine (FSM) is a useful and powerful tool to model a dynamic system. On the traditional implementation of FSM, nested switch-case statement exists several problems of poor reusability and maintainability. The paper presents a generalized framework of algorithmic implementation to improve these disadvantages of nested switch-case statement. A lookup table and event handle is used to construct various FSMs in the proposed framework. In the experiments, we apply the proposed framework to practice a typical FSM. The experimental results demonstrates the framework’s generalization. © Springer Nature Switzerland AG 2019.

关键词： Reusability

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Application of UAV in Road Safety in Intelligent Areas

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Journal of Geographical Research 2019年第4期2卷 15-21页

作者： Yanan Xu Jianxin Qin Pengcheng He Zhuan Chen Hunan Key Laboratory of Geospatial Big Data Mining and Application Hunan Normal UniversityChangsha410081 China School of Surveying and Mapping Engineering East China University of TechnologyNanchang330013China

With the continuous development of remote sensing(RS)technology,the surface information can be collected conveniently and quickly by using the popular unmanned aerial vehicle(UAV).The application of UAV low altitude RS technology in road safety in intelligent area has certain practical *** can provide safety warning for most drivers,and provide auxiliary decision-making for the road supervision *** the collection,processing,calculation and analysis of the road image,the UAV can find out the road obstacles with potential safety hazards,identify the road pit,calculate the radius and depth of the road pit through the digital mapping system,predict the accident risk according to different speed and provide scientific basis for the road safety *** the same time,UAV can provide repair scheme for damaged roads,estimate the quantity of materials needed for repair,and achieve the target of resource saving and efficiency *** experimental results show that the UAV can not only provide scientific prediction information for driving safety,but also provide relatively accurate material consumption for road repair.

关键词： UAV Low-altitude RS technology Road safety Road repair Road detection

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Co-training Based on Semi-Supervised Ensemble Classification Approach for Multi-label data Stream

Co-training Based on Semi-Supervised Ensemble Classification...

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IEEE International Conference on Big knowledge (ICBK)

作者： Zhe Chu Peipei Li Xuegang Hu Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education AnHui China School of Computer Science and Information Engineering Hefei University of Technology AnHui China

A large amount of data streams in the form of texts and images has been emerging in many real-world applications. These data streams often present the characteristics such as multi-labels, label missing and new class emerging, which makes the existing data stream classification algorithm face the challenges in precision space and time performance. This is because, on the one hand, it is known that data stream classification algorithms are mostly trained on all labeled single-class data, while there are a large amount of unlabeled data and few labeled data due to it is difficult to obtain labels in the real world. On the other hand, many of existing multi-label data stream classification algorithms mostly focused on the classification with all labeled data and without emerging new classes, and there are few semi-supervised methods. Therefore, this paper proposes a semi-supervised ensemble classification algorithm for multi-label data streams based on co-training. Firstly, the algorithm uses the sliding window mechanism to partition the data stream into data chunks. On the former w data chucks, the multi-label semi-supervised classification algorithm COINS based on co-training is used to training a base classifier on each chunk, and then an ensemble model with w COINS classifiers is generated ensemble model to adapt to the environment of data stream with a large number of unlabeled data. Meanwhile, a new class emerging detection mechanism is introduced, and the w+1 data chunk is predicted by the ensemble model to detect whether there is a new class emerging. When a new label is detected, the classifier is retrained on the current data chunk, and the ensemble model is updated. Finally, experimental results on five real data sets show that: as compared with the classical algorithms, the proposed approach can improve the classification accuracy of multi-label data streams with a large number of missing labels and new labels emerging.

关键词： data models Training Streaming media Adaptation models Partitioning algorithms Correlation knowledge engineering

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China’s NTB Market: A Liquidity Dilemma

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Journal of Systems Science & Complexity 2018年第2期31卷 493-507页

作者： LI Yumeng MENG Xiangying ZHANG Yueyan WEI Xianhua School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laborutory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Sino-Danish Center for Education and Research University of Chinese Academy of Sciences Beijing 100190 China The State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 China Department of Automotive Engineering Tsinghua University Beijing 100084 China

This paper introduces China＇s New Third Board Market（the NTB market） and tests the market-making system in the role of improving market liquidity. The NTB Market is the main part of China＇s OTC market, established in 2006. In comparing with China＇s Main Board Market and the Second Board Market, it attracts a lot of start-up companies that need financing with less strict listing requirements. Meanwhile, it is full of opportunities and challenges that appeal to numerous securities traders and investors with the rapid development momentum. Since its establishment, the NTB Market has been stuck in the lack of liquidity. The authority of the NTB Market introduced market maker system, so as to solve the problem of liquidity. Using the difference-in-difference method（DID method）, the market maker system has been proved to make little contribution to improving the stock liquidity. Although the problem of liquidity is difficult to solve in short term, the NTB Market is full of opportunities for all kinds of participants definitely.

关键词： China＇s stock market DID method liquidity market makers.

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data Analysis of Portfolio Optimization using Artificial Neural Network in China's Stock Market* 5

Data Analysis of Portfolio Optimization using Artificial Neu...

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5th IEEE International Conference on Big data Intelligence and Computing, dataCom 2019

作者： Wang, Chia-Hung Lee, Chia-Jung Fujian University of Technology College of Information Science and Engineering Fuzhou City350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications No. 33 South University Road University Town Fujian Province Fuzhou City350118 China Soochow University School of Big Data Management No. 70 Linhsi Road Shihlin District Taipei City11102 Taiwan

ISBN: (纸本)9781728141176

This paper presents a neural network model for studying the portfolio optimization in China's stock market. An investment scheme is proposed by using an artificial intelligence algorithm based on the trained neural network. In the empirical study, six key indicators of historical transaction data for stocks are used as the input characteristics of our neural network model, which are the opening price, the closing price, the trading volume, the highest and lowest price on the day, and Week time scale. Besides, we use Python technology to process the collected stock data and develop the learning process of the studied neural network for predicting the closing price for the next period. Based on the presented data analysis in the paper, the investors of the stock market in China could make a rational decision-making on the portfolio optimization. © 2019 IEEE.

关键词： Neural network models

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Examination of the energy trading status of China and India and the prospect for cooperation

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Procedia Computer Science 2019年 162卷 819-826页

作者： Shuying He Kun Guo Department of Economics Queen’s University Kingston Ontario Canada School of Economics and Management University of Chinese Academy of Science Beijing China Research Center on Fictitious Economy & Data Science Chinese Academy of Science Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Science Beijing China

China and India are two major contributors to the growth of global energy demand. As energy is one central part of the geopolitics, the energy security for both countries get complicated by the political environment. The paper investigates the positions of China and India in the trading relationships with different regions of the world. The paper also examines recent events that affect the energy security of China and India. The conclusion is that during the past decade, China and India have diversified sources of energy, especially from the Middle East, though China demonstrates a higher level of diversification and occupies a less passive position in its trading relationships. Shale revolution, the US energy sanctions on Iran and Venezuela and the US-Chinese trade conflicts, can bring China, India and Russia closer to each other due to the shrinking market influence of Russia in Europe and the needs of India and China to further diversify import sources so that energy supplies will not be disrupted by political chaos.

关键词： China India energy cooperation interdependence relations shale revolution US sanction

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Digital Certificate Based Security Payment for QR Code Applications 4th

Digital Certificate Based Security Payment for QR Code Appli...

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4th Euro-China Conference on Intelligent data Analysis and Applications, ECC 2017

作者： Zhang, Jing Liu, Shi-Jian Pan, Jeng-Shyang Ji, Xiao-Rong Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and Engineering Fujian University of Technology Fuzhou China

ISBN: (纸本)9783319685267

A rapidly growing social interaction technology is the use of Quick Response (QR) codes as physical entrances (i.e. the encoded URL address) to Internet resources. However, there exist various kind of security problems, for example, the URL may point to some phishing web sites. A digital certificate based signature and verification QR code is proposed in this paper. The public and private keys are generated by the authentication mechanism, which using the Public key Infrastructure (PKI) technology. The public key can be published with the designed scanning application (App). An authenticated QR code can be created based on the private key and the merchant information. Clients can authenticate the codes by the public key and scanning App. Test results prove that the security QR code designed by this system, which binds the digital certificate, can be verified by the decoding scanner. © 2018, Springer International Publishing AG.

关键词： Authentication

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Automatic Pointer Meter Reading Based on Machine Vision

Automatic Pointer Meter Reading Based on Machine Vision

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International Conference on Image, Vision and Computing (ICIVC)

作者： Mao-Hsiung Hung Chaur-Heh Hsieh Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Information Engineering Yango University Fuzhou China

ISBN: (纸本)9781728123264

Pointer meters in power systems are wildly used. Although smart meters gradually replace pointer meters to conveniently acquire measurement, digitalization of some special meters have not been available. The paper presents a new method based on machine vision to detect pointer meter reading automatically. Two phases of training and testing are proposed in this method. In the training phase, a template of meter feature points on a training image is extracted. In the testing phase, the template matching performs on a testing image to find feature points. Then, an elliptic arc fitting based on the feature points to generate a 1-D signal. Finally, the 1-D signal is used to locate the pointer and the reading result is obtained. Differing with existing methods, the proposed method performs effectively and efficiently automatic meter reading without using Hough transformation.

关键词： Pointer meter Automatic meter reading Machine vision robot vision automatic meter reading Pointer Meter reading Feature Points Smart meters TWO-PHASE

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