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检索条件"任意字段=3rd International Conference on Soft Computing in Data Science, SCDS 2017"

共 696 条记录，以下是191-200 订阅

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An Unsupervised Grey Incidence Clustering Method Based on Multi-Dimensional Dynamic Time Warping Distance 3

An Unsupervised Grey Incidence Clustering Method Based on Mu...

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3rd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Dai, Jin He, Yuhong Wang, Zu Wang, Mei Chongqing Univ Posts & Telecommun Sch Software Engn Chongqing 400065 Peoples R China

ISBN: (纸本)9781538643013

Grey incidence clustering is an effective tool for uncertainty information system processing. Existing grey incidence clustering methods can only deal with one-dimensional and complete sequences. This results in a lot of extra works to be done, such as alignment sequences and assignment cluster threshold artificially. It will greatly affect the clustering performance. To solve these problems, an unsupervised grey incidence clustering method based on multi-dimensional dynamic time warping distance is proposed. It measures the incidence degree between multi-dimensional sequences by calculating the minimum distance of a dynamic warping path. On the foundation, an improved k-means clustering method is constructed to realize grey incidence clustering by the strategy of gradually increasing the number of categories. The experiment result shows that the proposed method has a perfect performance on clustering especially on dealing with multi-dimensional or incomplete sequences.

关键词： dynamic time warping distance grey incidence degree k-means dynamic clustering grey incidence clustering

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Effects of Lecture Video Types on Student Learning: An Analysis of Eye-Tracking and Electroencephalography data 3rd

Effects of Lecture Video Types on Student Learning: An Analy...

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3rd international conference on Intelligent, Interactive Systems and Applications, IISA2018

作者： Cao, Xiaoming Cheng, Miaoting Xue, Xiya Zhu, Shan Normal College Shenzhen University Shenzhen China Division of Information and Technology Studies Faculty of Education The University of Hong Kong Hong Kong

ISBN: (纸本)9783030028039

Previous research studies have demonstrated the influence of different user interface designs on student learning. This paper aims to examine the effect of different lecture video types on student learning using the eye-tracking and electroencephalography (EEG) techniques jointly. A two-factor experimental study was conducted on 62 undergraduate students who were randomly assigned to two groups, one of which used lecture video without teacher presence (Group 1, N = 31) and the other used lecture video with teacher presence (Group 2, N = 31). A survey was also conducted on both groups of students to collect data on their cognitive load and perceived satisfaction towards the lecture videos. The results of eye-tracking and EEG data indicate that teacher presence influences learners’ concentration and attention towards lecture video learning. Moreover, the learners’ perceived satisfaction are also related to students’ learning. Results of this study could provide future directions for studies on massively open online courses (MOOCs) and insights for MOOCs designers and educators to improve student learning with online courses. © Springer Nature Switzerland AG 2019.

关键词： Electroencephalography

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Scene Text Detection Based on Enhanced Multi-channels MSER and a Fast Text Grouping Process 3

Scene Text Detection Based on Enhanced Multi-channels MSER a...

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3rd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Dai, Jin Wang, Zu Zhao, Xianjing Shao, Shuai Chongqing Univ Posts & Telecommun Sch Software Engn Chongqing Peoples R China

ISBN: (纸本)9781538643013

Scene text detection has become a popular research in computer vision and pattern recognition field in recent years because of the accurate and rich information carried by scene text. Now component-based methods have become the trend, and the detection result is largely determined by the success of filtering text-like non-text regions. The main task of this paper is to reduce the time complexity without a big fall in recall. First an enhanced multi-channels MSER model is introduced: Before extracting MSER, the image is sharpened by using the Laplacian and Gaussian blur and multi-channels is utilized, then the step of the threshold used in MSER algorithm is set to the minimum in order to get more refined MSERs. Second, two novel scene text features local contrast and boundary key points are proposed to better distinguish text regions from non-text regions. Finally, a fast text grouping algorithm is achieved which reduce the time complexity. Experiments on both ICDAR 2011 and ICDAR 2013 show that the recall of the proposed method is improved by 3%.

关键词： MSER multi-channels scene text text detection

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Impacts of Public Transportation Fare Reduction Policy on Urban Public Transport Sharing Rate Based on Big data Analysis 3

Impacts of Public Transportation Fare Reduction Policy on Ur...

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3rd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Zhang, Sijia Jia, Shunping Ma, Cunrui Wang, Yuqiong Beijing Jiaotong Univ MOE Key Lab Urban Transportat Complex Syst Theory Beijing Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China

ISBN: (纸本)9781538643013

Urban transport is an important support system to the city. With the city's development, traffic congestion has become a major traffic problem nowadays and it is badly in need of solutions. Big data analysis has been widely used in the domain of transportation in recent years and it does great help to find solutions to different kinds of problems from historical data. In order to solve the urban traffic problems fundamentally, developing the public traffic is one of the major effective ways and bus priority policies and strategies are such important measures that they have contributions to the increase of public transport sharing rate. This paper mainly studied the influences of two bus fare adjustment policies in Beijing on urban public transport sharing rate based on big data analysis through the computer software SPSS, and then put forward corresponding recommendations to the reform of bus fares in Beijing.

关键词： big data analysis urban public transport fare reduction policy data fitting model SPSS

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Robust Recommendation Algorithm Using an Iterative Group-Based Reputation 3

Robust Recommendation Algorithm Using an Iterative Group-Bas...

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3rd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Qian Fulan Yue Ruxia Zhao Shu Zhang Yanping Anhui Univ Ctr Informat Support & Assurance Technol Sch Comp Sci & Technol Hefei Anhui Peoples R China Anhui Univ Sch Comp Sci & Technol Hefei Anhui Peoples R China

ISBN: (纸本)9781538643013

Collaborative filtering recommender systems have been widely applied in e-commerce and have brought huge economic benefits. Malicious users can deliberately inject attack profiles into a recommender system to affect the recommendation result. Detecting and defending against shilling attacks in recommender systems is very important. The existing algorithms, which are based on the latent factor model, have poor robustness and low recommendation accuracy under shilling attacks. Thus, we proposed a robust collaborative recommendation algorithm that is based on users' reputations, which are determined based on their grouping behaviours. We group users according to their rating histories and iteratively compute each user's reputation. This algorithm has two advantages: It has high recommendation accuracy and stronger robustness and does not destroy the user distribution of the original dataset. Experiments on the real datasets MovieLens 100K and MovieLens 1M show that the proposed robust algorithm outperforms previous robust algorithms in terms of both accuracy and robustness.

关键词： recommender system collaborative filtering reputation shilling attack

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A Study of Practical Education Program on AI, Big data, and Cloud computing through Development of Automatic Ordering System 3

A Study of Practical Education Program on AI, Big Data, and ...

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3rd IEEE/ACIS international conference on Big data, Cloud computing, data science and Engineering (BCD)

作者： Saiki, Sachio Fukuyasu, Naoki Ichikawa, Kohei Kanda, Tetsuya Nakamura, Masahide Matsumoto, Shinsuke Yoshida, Shinichi Kusumoto, Shinji Kobe Univ Grad Sch Syst Informat Kobe Hyogo Japan Wakayama Univ Fac Syst Engn Wakayama Japan Nara Inst Sci & Technol Grad Sch Sci & Technol Ikoma Nara Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka Japan Kochi Univ Technol Sch Informat Kochi Japan

ISBN: (纸本)9781538656051

An innovative engineer who can address a social challenge using big data processing, AI and cloud computing technologies with the generation of new business and value is required from industry. enPiT is an education project to develop the advanced IT engineer based on practical education in cooperation between industry and academia promoted by Ministry of Education, Culture, Sports, science and Technology (MEXT) of Japan. In this paper, we introduce how we designed PBL centered curriculum named AiBiC Spiral under the framework of enPiT education project, and analyze educational effect of our program based on work products and the questionnaire result targeting students who took and completed to the program of 2017.

关键词： Big data Predictive models Cloud computing Meteorology Seminars Machine learning

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Design of personal learning management platform based on information technology 2019

Design of personal learning management platform based on inf...

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3rd international Workshop on Education, Big data and Information Technology, EBDIT 2019

作者： Guan, Jingjing Ma, Zhiyuan Liu, Quan Chen, Haiyan WanG, Shengping Wuhan University Institute of Education Science 110 Baishazhou Avenue Wuhan Hubei Province China Zhongnan University of Economics and Law 182 Nanhu Avenue East Lake New Technology Development Zone Wuhan Hubei Province China Wuchang Institute of Technology Dean's Office 299 Bayi Road Wuchang District Wuhan Hubei Province China

ISBN: (纸本)9781450372053

The management of individualized learning has always been a difficult problem. The development of computer technology can effectively promote the development of individualized learning in primary and secondary schools, and the way of modern teaching management level can effectively improve the efficiency of individualized management. According to the specific situation of individualized learning of primary and secondary school students, this paper carries out relevant needs analysis, feasibility study, design by using mainstream framework technology, and uses database software to manage and distribute all data in the system. A set of template of MVC framework is designed. According to the standard software design process, the market demand, the overall system architecture and the subsequent testing practice of the system are introduced. The correctness of the system function design is verified on the original basis, and the original intention of the development system is completed. To meet the development needs of university management system. After testing, the system is stable and safe, fast and durable, efficient and reliable. © 2019 Association for computing Machinery.

关键词： Information management

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Determination of soft Lithology Causes The Land Subsidence in Coastal Semarang City by Resistivity Methods 3

Determination of Soft Lithology Causes The Land Subsidence i...

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3rd international conference on Tropical and Coastal Region Eco Development (ICTCRED)

作者： Widada, Sugeng Saputra, Sidhi Hariadi Diponegoro Univ Dept Oceanog Fac Fisheries & Marine Sci Jl Prof H SoedartoSH Tembalang 50275 Semarang Indonesia

Semarang City is located in the northern coastal plain of Java which is geologically composed of alluvial deposits. The process of the sediment diagenesis has caused a land subsidence. On the other hand, the development of the industrial, service, education and housing sectors has increased the number of building significantly. The number of building makes the pressure of land surface increased, and finally, this also increased the rate of land subsidence. The drilling data indicates that not all layers of lithology are soft layers supporting the land subsidence. However, vertical distribution of the soft layer is still unclear. This study used Resistivity method to map out the soft zone layers of lithology. Schlumberger electrode configuration with sounding system method was selected to find a good vertical resolution and maximum depth. The results showed that the lithology layer with resistivity less than 3 ohm is a layer of clay and sandy clay that has the low bearing capacity so easily compressed by pressure load. A high land subsidence is happening in the thick soft layer. The thickness of that layer is smaller toward the direction of avoiding the beach. The improvement of the bearing capacity of this layer is expected to be a solution to the problem of land subsidence.

关键词： Land subsidence Semarang Resistivity

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Community Detection Based on Unified Bayesian Nonnegative Matrix Factorization 3

Community Detection Based on Unified Bayesian Nonnegative Ma...

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3rd IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Huang, Haihui Wang, Xin Yu, Guo Chongqing Univ Posts & Telecommun Software Engn Chongqing Peoples R China Chongqing Univ Posts & Telecommun Commun & Informat Engn Chongqing Peoples R China

ISBN: (纸本)9781538643013

Community detection is of great importance to social networks analysis. It is widely acknowledged that the number of inner partitions (or dimensions) is related to the link information which exists in communities. But in fact, it is difficult to uncover the underlying community structure in traditional community detection approaches especially in real-world condition where rich attribute information exists. Therefore, how to integrate with link information and attribute information in community detection is a challenging problem. In this paper, we present a novel method based on Unified Bayesian Nonnegative Matrix Factorization: UBNMF, we develop a Bayesian approach for link and attribute information, and then we apply it into the Nonnegative Matrix Factorization (NMF) for community detection. Experiments on real data shows that the community detection approach has an ideal calculate result, the framework can easily detect the internal community structure, as well as can find the overlapping communities effectively, especially in complex networks.

关键词： community detection link information attribute information unified Bayesian probability distribution NMF

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Reliability enhanced data processing system capable of runtime fault recovery 3

Reliability enhanced data processing system capable of runti...

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3rd IEEE international conference on Big data Analysis, ICBDA 2018

作者： Shen, Beichen Peng, Libiao Xie, Yongle College of Software Engineering Sichuan University Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781538647936

In order to enhance the reliability of Big data transmission and real-time processing in radiation environment, a reliability enhanced FPGA system with runtime fault recovery is presented in this work. This technique is proposed based on selective module redundancy and dynamic partial reconfiguration in order to improve the performance and reliability of systems implemented on SRAM-based FPGAs with fault tolerance and runtime recovery. Coarse-grained TMR architecture and fine-grained TMR architecture combining with dynamic reconfiguration are used to protect the system against soft errors caused by SEU. Fault detection units based on majority voter and XNOR gate are inserted in each redundancy module, and the built in-slice carry-chains are used to merge the large number of error flags produced by the fault detection units. The results show that the improvements in recovery time and reliability are achieved by the proposed technique. © 2018 IEEE.

关键词： Fault tolerance

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