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8th International conference on Electronic Information Technology and Computer Engineering, EITCE 2024

作者： Shi, Jinmei Wen, Xinyuan Dong, Chunyang Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

Digitalization of education is one of the major strategies for my country’s current education reform and development, and market-oriented online education companies are one of the frontier practitioners in promoting digitalization of education. The work is based on the Vscode programming tool, and uses the Echarts graphics library and the Vue framework to perform Web front-end data visualization interaction design in a knowledge graph visualization manner. Use the Scrapy crawler framework in Python to crawl data from relevant websites, summarize and analyze the industry status, forward-looking areas and research hotspots of online education worldwide, and show the current development history and industry prospects of the global online education industry. By adding the random forest algorithm, we can deeply analyze the profound impact of my country’s double reduction policy on the development of domestic online education and the establishment of a new generation of industry standards. The relevant literature data of the past ten years from CNKI were exported, and the screened literature data were imported into the bibliometric tool COOC and the visualization software CiteSpace for sorting and analysis, presenting the research status and hot trends in the field of online education industry. Help relevant practitioners, researchers, learners, etc. to enhance their business understanding in the field of online education, and provide reference for the digital transformation of education in educational institutions at all levels and types. © 2024 Copyright held by the owner/author(s).

关键词： Decision trees

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MyOmics: A Galaxy-based analysis and visualization Platform for Omics data 2

MyOmics: A Galaxy-based Analysis and Visualization Platform ...

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2nd International conference on Electronic Information Engineering and Computer Communication, EIECC 2022

作者： Tao, Xin Chang, Cheng Yang, Chunde Xu, Kaikun School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Beijing Institute of Lifeomics Beijing102206 China Research Unit of Proteomics Driven Cancer Precision Medicine Chinese Academy of Medical Sciences Beijing102206 China

ISBN: (纸本)9781510663121

High-throughput omics technologies have been widely used in biomedical research. While it's still challenging for researchers without statistical foundations or programming skills to obtain biological insights from omics data. The published tools have some deficiencies in the environment configuration and analysis workflow definition. Here, we propose a one-stop analysis and visualization platform for omics data named MyOmics, which is freely available at http://***/. Its functions include data preprocessing, statistical analysis, functional enrichment analysis and visualization based on multi-index data frame structure. To evaluate the performance of MyOmics for omics studies of clinical cohorts, we re-analyzed a published Hepatocellular Carcinoma dataset and reproduced their main findings, which demonstrated that MyOmics is reliable and efficient to analyze omics data. Based on the Galaxy framework, MyOmics provides an easy-to-use solution for exploring omics data. © 2023 SPIE.

关键词： data visualization

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Development of HUB-enabled component for remote sensing data visualization and analysis 4

Development of HUB-enabled component for remote sensing data...

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4th International conference on Geology, Mapping, and Remote Sensing, ICGMRS 2023

作者： Wan, Wei Zhu, Xiaobo Yulong, Feixue Chen, Weirong Department of Applications China Centre for Resources Satellite Data and Application Beijing China Department of Satellite Engineering China Siwei Surveying and Mapping Technology Co. Ltd Beijing China

ISBN: (纸本)9781510672741

visualization of geospatial data has traditionally played a critical role in analysis and decision-making, but recent developments have also brought a revolution in widespread online access to remote sensing data and integration tools, particularly for map-based interfaces. Building the effective tools to support user-centered geographic visualization faces a significant challenge. In this paper, we described the design, development and use of a library package to address the demand for an easy-to-use mapping library for use in online geospatial tool development, especially remote sensing applications. Although original developed for HUB platform, the library is independent and can be used in any standalone applications hosted in a cloud environment. It offers a new way for non-expert programmers such as researchers and students to quickly map-enable their scientific tools which was not an easy task previously, and hence accelerate the time for tool development and knowledge dissemination. © 2024 COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Remote sensing

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Learning Analytics Tools to Analyze Progress and Results With Moodle LMS data 15

Learning Analytics Tools to Analyze Progress and Results Wit...

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15th IEEE Global Engineering Education conference (IEEE EDUCON)

作者： Alonso-Fernandez, Cristina Jorro-Aragoneses, Jose L. Alaiz, Carlos M. Rodriguez, Pilar Univ Autonoma Madrid Dept Comp Sci Madrid Spain

ISBN: (纸本)9798350394023;9798350394030

Teachers can benefit from the information provided by learning analytics data for multiple purposes. Visual learning analytics dashboards provide near real-time information while more complex offline tools are commonly used to synthesize and transform the data gathered into interpretable information for teachers. The extended use of Learning Management Systems in universities, such as Moodle or Canvas, provides a rich environment to capture learning analytics data from students' interactions while they are progressing in their courses. In this paper, we present two different learning analytics tools aimed at teachers to obtain information about students' progress and results using data from the Moodle LMS at different stages of their learning process: (1) a progress visualization plugin for Moodle, which provides teachers with real-time information about the progress achieved by students in their courses, and the different goals set for their plans;and (2) an analytics Jupyter Notebook tool with a pre-defined set of analysis and visualizations to apply to data gathered from default activities in Moodle. The plugin is in an initial validation stage, while the analysis tool has been tested in a case study in a university course. Combined, both contributions can enrich the information that teachers have during and after the academic year, adapting their classes to better fit students' progress and needs, as well as providing overall results and comparison between groups after the course has finished.

关键词： learning analytics dashboards visualization LMS Moodle

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Using flow analysis of bike-sharing system for finding spatiotemporal mobility patterns in Kuopio city region 9

Using flow analysis of bike-sharing system for finding spati...

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9th IEEE International Smart Cities conference, ISC2 2023

作者： Honkanen, Jesse Leppanen, Laura Auvinen, Harri Savonia University of Applied Sciences Wellness Technology Kuopio Finland Savonia University of Applied Sciences Bio and Circular Economy Kuopio Finland

ISBN: (纸本)9798350397758

There have been an increasing number of studies related to analyzing bike-sharing systems (BSS) in the recent years. In this article a method for finding interesting interstation routes and doing temporal analysis for them is portrayed. Analyzing flows between stations supports both planning of new station locations and improving biking infrastructure. It also gives information about mobility patterns of citizens. data for this analysis is from Kuopio city's BSS for four seasons from 2019 to 2022. Kuopio's BSS is a hybrid fourth generation system with e-bikes, virtual stations, mobile passes and limited free-floating bike area. BSS first came to Kuopio in May of 2019 and by the end of 2022 there were 350 e-bikes and 41 stations in use. dataset for years from 2019 to 2022 consists of total 1 180 494 rows of trip data of which 913 995 are trips between stations. This dataset is published freely available. The analysis concentrates to find out spatiotemporal flow patterns between stations and temporal activity patterns of each station. For singular route analysis two data visualization types were enough to give sufficient overview. Flow maps were used for identifying these routes of interest and getting general idea of spatiotemporal traffic flows. The results of this analysis can be used for further improvement of city's biking infrastructure to better serve mobility needs of citizens. © 2023 IEEE.

关键词： data visualization

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A visual data analysis system of used cars based on Python and ECharts

A visual data analysis system of used cars based on Python a...

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2022 International conference on Computer Application and Information Security, ICCAIS 2022

作者： Fan, Luqiao Duan, Banxiang Gao, Jie Computer Engineering and Technical College Guangdong Institute of Science and Technology Guangdong Guangzhou510640 China

ISBN: (纸本)9781510663459

This paper develops a data visualization and analysis system for used cars data in response to the requirement that used cars information is complex and buyers need to obtain objective and comprehensive used cars information in a short period of time. Selenium+XPath crawler was used to crawl the used cars data in ***, and then import the data. The dirty data was cleaned using the Pandas data analysis toolkit in Python. The data is then stored as the corresponding CSV file and converted into JSON file. Finally, ECharts is used to read JSON files for data visualization and HTML for web display. © 2023 SPIE.

关键词： Big data

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The research landscape on the artificial intelligence: a bibliometric analysis of recent 20 years

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第9期81卷 12973-13001页

作者： Gao, Hui Ding, Xiuhao Hubei Univ Sch Business Youyi Ave 368 Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Management Luoyu Rd 1037 Wuhan Peoples R China

Artificial intelligence (AI), a general term that implies the imitation of information process of intelligent behavior and sense with minimal intervention, is one of the most promising research areas and has received a considerable attention with coexisting pros and cons. In order to understand the research status quo and future trends on AI technology, this work uses bibliometric analysis method to obtain this objective. By analyzing the datasets including journal article data collected from Web of Science (WOS), conference paper data retrieved from Scopus and the patent data extracted from Derwent Innovations Index (DII) in the period of 2000-2019, we primarily provide a comprehensive overview to better understand the research status of AI. Bibliometric analysis results can also shed light on the evolution and trends in AI.

关键词： Artificial intelligence (AI) Bibliometric methods Patent analysis visualization

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Proceedings - 2024 2nd International conference on Technology Innovation and Its Applications, ICTIIA 2024

Proceedings - 2024 2nd International Conference on Technolog...

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2nd International conference on Technology Innovation and Its Applications, ICTIIA 2024

ISBN: (纸本)9798350351613

The proceedings contain 164 papers. The topics discussed include: enhancement of indonesian language learning motivation using trivia game;identifying non-conforming process in automobile insurance claims using process mining and COBIT 2019;big data analytics for proactive financial fraud detection and prevention;UX law implementation at Sevima edLink from design science research perspective;a comparative analysis of macroeconomic indicators in optimizing credit risk prediction;a multi-perspective process explorer method to identify anomaly of an education ERP;the role of data visualization in improving the sustainability of smallholdings;analysis of the impact of ChatGPT utilization on the levels of laziness and productivity;and fake job vacancy detection using ensemble voting classifier.

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Emotion analysis and design of internet users based on big data 3

Emotion analysis and design of internet users based on big d...

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3rd International conference on Electronics, Electrical and Information Engineering, ICEEIE 2023

作者： Wang, Chen Tang, Luyao Liu, Qingjie Teng, Yuntian Institute of Geophysics China Earthquake Administration Beijing China School of Information Engineering Institute of Disaster Prevention Hebei Sanhe China

ISBN: (纸本)9781510671423

In the era of rapid development of the Internet, interactive platforms such as Weibo, Zhihu and Douban have developed very rapidly. The appearance of each hot event will bring the heated discussion of netizens, showing all kinds of netizens' emotions. By analyzing the emotional data, we can quickly obtain the positive and negative emotions of netizens, which can provide technical support for the marketing of commodities and the prevention of cyber crimes. This paper designs a netizen emotion analysis and visualization system based on social data by using platforms such as Douban and Weibo. This model takes the novel coronavirus outbreak event as the case for analysis, uses data mining, machine learning, data visualization and other methods to mine potential important information in the data, and uses the clustering method to analyze and classify emotions. Quickly obtain the positive and negative emotions of Internet users, study the emotional changes of Internet users under different states of the epidemic, and conduct correlation analysis between the epidemic events and the emotions of Internet users. It will help governments at all levels to accurately grasp the situation of online public opinion and conduct public opinion guidance and epidemic prevention and control work. © 2023 SPIE.

关键词： data visualization

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Web-Based visualization and analysis Framework for Graph data 1

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2nd International Semantic Intelligence conference (ISIC)

作者： Senturk, Fatmana Bilici, Mehmet Ali Tanisman, Sezercan Aytac, Vecdi Pamukkale Univ Dept Comp Engn Denizli Turkiye Ege Univ Dept Comp Engn Izmir Turkiye

ISBN: (数字)9789811971266

ISBN: (纸本)9789811971280;9789811971266;9789811971259

Graph theory has many applications in computer science. Graphs are involved in the mathematical modeling of problems belonging to very popular computer and data science, such as datamining, data clustering, computer network, image segmentation, etc. Graph theory is used in computer science to solve problems modeled as graphs. However, many applications do not have an interface that displays and edits graphs instantly. Moreover, these applications are not supported with a web interface. In this study, a web interface has been developed that support graph theory concepts, display more than one graph simultaneously, have a user-friendly interface, and include algorithms to analyze graphs. Also, we present a web service for these graph analyzing algorithms.

关键词： Graph theory

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