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RESEARCH HOTSPOTS AND DEVELOPMENT TRENDS OF STEM EDUCATION AT HOME AND ABROAD -BASED ON THE analysis OF CITESPACE visualization 4

RESEARCH HOTSPOTS AND DEVELOPMENT TRENDS OF STEM EDUCATION A...

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4th International conference on Computer Science and Educational Informatization, CSEI 2022

作者： Lv, Jinyi Zhang, Yarning Dong, Qingjiang Zhang, Quanfu Key Laboratory of Education Informatization for Nationalities Ministry of Education Yunnan Normal University Yunnan Province Kunming China Rocket Force University of Engineering Shaanxi Province Xi'an China

ISBN: (数字)9781839537882

ISBN: (纸本)9781839537882

STEM education is regarded as a strategic choice for implementing the new educational reform in the 21st century. To sort out the evolution path of STEM education research at home and abroad in the past 14 years and reveal the research hotspots and trends of STEM education. In this paper, CiteSpace literature visualization analysis software is used to perform knowledge mapping visualization analysis on literature data with the theme of "STEM education" in the CNKI Chinese database and WOS core database during 2008-2021. The results show that STEM education is widely used in science education, curriculum design and information technology education at home and abroad. Domestic STEM education research focuses on K-12 education, which cultivates students' core literacy and innovation ability. Foreign STEM education research focuses on student development, student academic achievement and gender research in STEM education in higher education. This situation reveals the interdisciplinary, trans-regional and pluralistic nature of STEM education at home and abroad, presenting a trend of continuous integration and remodelling between STEM education and various disciplines. © 2022 IET conference Proceedings. All rights reserved.

关键词： Students

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Visualizing Automated HVAC Performance analysis on Floor Plans for Meaningful Insights

Visualizing Automated HVAC Performance Analysis on Floor Pla...

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ASHRAE Winter conference

作者： Saadatifar, Sanaz Surapaneni, Amulya Lee, Kathryn VanderSluis, Benjamin Williams, John G. Carnegie Mellon Univ Sch Architecture Pittsburgh PA 15213 USA Design Studio Harris Oakland CA USA Data Driven Solut Harris St Paul MN USA

ISBN: (纸本)9781955516471

Building Information Modeling (BIM) has been rapidly transforming the Architectural, Engineering, & Construction (AEC) industry throughout the lifecycle of the building. BIM functions as a single database of fully integrated and interoperable information that can be used by all members of the design and construction team and ultimately, by operators throughout a facility's lifecycle (Holenss G.V.R 2008). The advantages of utilizing BIM in the Facility Management (FM) stage have been well documented in the literature (Stravoravdis and Ashworth 2015.), (Gokstorp 2012.) & (Becerik-Gerber et al. 2012.). The initial hypothesis for this study was that the use of BIM by our in-house FM staff would significantly reduce the amount of time needed to locate HVAC equipment in the building that needs maintenance or repair. However, currently, BIM is not as widely implemented in the FM stage as it is in the design stage (Akcamete et al 2010.). Lack of or restricted access to the BIM model for multiple existing buildings is the first major challenge to BIM adoption for FM. The lack of BIM software experience for FM personnel and the high purchase cost of the software also presents significant challenges. Most of the latest Building Management Systems (BMS) inform the FM personnel about the problematic equipment through their equipment IDs but fail to locate the coordinates of that equipment. The FM personnel mostly use paper-based drawings and spend hours locating problematic equipment in the building that is flagged by the BMS. For many building managers and design professionals, the visualization of building information for analysis, benchmarking, and diagnostics remains a time-intensive, do-it-yourself undertaking (Lehrer 2010.). Hence, the goal of the study is to provide FM personnel with a simple-to-use spatial visualization dashboard that would save them time and money. This study showcases a methodology to spatially visualize the performance of buildings' HVAC systems syste

关键词： Office buildings

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An analysis of International conference Proceedings on Artificial General Intelligence (AGI) from 2008 to 2020: A data-Mining Mapping analysis

An Analysis of International Conference Proceedings on Artif...

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International conference on Information and Communication Technology and Accessibility (ICTA)

作者： Boulus Shehata Ahmed Tlili Ronghuai Huang Smart Learning Institute Beijing Normal University Beijing China

ISBN: (纸本)9781665466424

This paper analyzes the proceedings of 13 international conferences on Artificial General Intelligence AGI, that are part of the lecture notes in artificial intelligence. The motivation for this study is to explore the publication networks and areas where AGI could be useful to Information & Communication Technology ICT in education. SPSS and Microsoft Excel were used to enter, screen, clean and visualize the analysis of the data. Furthermore, all published proceedings were uploaded into Voyant Tools and VOSviewer for data mining and visualization. After obtaining the most frequently used keywords and terms, certain patterns lead to trends in the research on AGI. The analysis leads to discussions and suggestions of possible opportunities where AGI may be integrated with education to assist people with or without a disability. The contribution of the study is in the overall mapping analysis of the conference proceedings, which would inspire further exploration and collaboration with potential scholars, institutions, and countries.

关键词： Electronic learning Education Government Collaboration data visualization Market research Information and communication technology

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IPL data analysis and visualization for Team Selection and Profit Strategy

IPL Data Analysis and Visualization for Team Selection and P...

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International conference on Computing Methodologies and Communication (ICCMC)

作者： Saranya G Aravind Swaminathan Joel Benjamin J Surendran R Leema Nelson Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai campus Chennai India MSc student Data Science Middlesex University Dubai Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Chitkara University Institute of Engineering & technology Chitkara University Punjab India

Day by day, the role of data science and machine learning in cricket is increasing due to the large amount of data generated from a single player on a whole line. The field of data science is the intensive study of data to extract insights and knowledge from the data and apply the acquired knowledge and actionable insights. These available data and statistics are used to predict things like the team's first-innings score and the probability of winning the second team, etc. This study works on Indian Premier League (IPL) data analysis 2022 and data visualization for the duration (2008–2020) using Python. This application modules are followed by preprocessing, data analysis, and visualization, and finally create a model that predicts the team's overall score and the probability of winning. When building models, python algorithms such as Numpy is used for Scientific Computing, Pandas used to perform data analysis, and finally Matplotlib and Seaborn to enable data visualization. Finally, this paper helps the trainers and owners of the team during the auction to select an emerging player to win the matches in the entire season and to win the trophy and to get profit to the owners by the profit strategy done in this analysis report.

关键词： Analytical models Scientific computing Computational modeling data visualization Machine learning data science Probability

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An Empirical Study on the Knowledge Structure and Hotspot Mapping of Reverse Innovation Based on VOSviewer Software and Big data 2

An Empirical Study on the Knowledge Structure and Hotspot Ma...

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2nd International conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2022

作者： Li, Hongyan School of Management Guangdong University of Technology Guangzhou510520 China

ISBN: (纸本)9781643683522

From the aspects of annual publications, journals and cited literatures, this paper uses content analysis and bibliometric analysis to study the papers on reverse innovation collected in Web of Scienc database from 2008 to 2020. Based on VOSviewer software and Big data, this paper research data processing and data visualization aiming at reverse innovation, summarizes the development status of reverse innovation research in foreign countries, and puts forward suggestions for further development of reverse innovation research in Chinese management research from two aspects of multi-factor scenario application and main role switch. © 2022 The authors and IOS Press.

关键词： Big data

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IPL data analysis and visualization Using Microsoft Power BI Tool

IPL Data Analysis and Visualization Using Microsoft Power BI...

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International conference on Computing and Networking Technology (ICCNT)

作者： Manasvi Jaipurkar Neha Ragit Chetana Tambuskar Pranay Deepak Saraf G H Raisoni College of Engineering Nagpur

Cricket represents the most popular activity in India, and it is played there in all of its regions in various formats. Indian regional teams, international competitions all field players in the Indian Premier League (IPL), a national cricket championship. Cricket involves lots of data, analysis, prediction and statistics. Several parameters can be used to predict the outcome of a cricket match. This paper's main topics are the process model, Microsoft Power BI operations like numerous related graphical insights, dashboards, visualizations. To make accurate visualizations, predictions about things like the actual and predicted team's score and the likelihood that the team will win, overall match analysis by currently available data, Using machine learning models and Power BI tools. The research started by using Python libraries used in Power BI. The IPL match data played between 2008 and 2022, then moved on to per-processing, data analysis, and visualization, and finally developed a dashboard and reports that forecasts the teams' overall score and likelihood of winning. It is concerned with the interactive visualization of IPL databases utilizing the various modules of the Microsoft Power BI Tool and the Random Forest algorithm outperforms other algorithms in terms of accuracy, scoring 93.27 %.

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data visualization analysis of Research Hotspots and Trends in Low Carbon Campus Studies

Data Visualization Analysis of Research Hotspots and Trends ...

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Artificial Intelligence and Computer Engineering (ICAICE), International conference on

作者： Fei Li School of Marxism Hohai University Nanjing Jiangsu China

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

Based on the background of the ‘dual-carbon’ goal, the construction of low-carbon campuses is still in its infancy. In order to understand the development of low-carbon campus research and study the research hotspots and future development trends of low-carbon campus in domestic and foreign academia, this paper uses CiteSpace software to visualise and analyse the literature in CNKI and WoS databases from 2014–2024, and draws the conclusions that (1) domestic and foreign scholars have continued to pay attention to the issue, and there has been a significant surge in research progress in this field in 2008. (2) Domestic and foreign research collaboration networks have not yet been completed, and teamwork is weak. (3) There is a focus bias in domestic and foreign research hotspots, with domestic research focusing on low-carbon culture, concepts and conceptual interpretations, and foreign research focusing on quantitative research on energy conservation and emission reduction. In the future, the research in this field should further promote the sharing of resources, innovate the mode of cooperation, deepen the integration of disciplines, and establish visualisation standards, so as to provide certain theoretical references and practical help for the construction of low-carbon campuses.

关键词： visualization data visualization Focusing Market research Software Teamwork Visual databases Carbon Surges Standards

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data visualization Can Shifts our Sharing Economy Perceptions: Austin, Texas Airbnb Landscape Completed Research 27

Data Visualization Can Shifts our Sharing Economy Perception...

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27th Annual Americas conference on Information Systems (AMCIS)

作者： Nash, Kyle Baylor Univ Waco TX 76798 USA

ISBN: (纸本)9781733632584

During the last few years, we have witnessed remarkable growth in the sharing economy. Since 2008, Airbnb revolutionizes the travel industry;Airbnb is an enabled digital sharing economy platform that is a profoundly alternative to the lodging sectors. Have you ever used Airbnb services (as a host or guest)?. This study is an exploratory analysis study to understand the rental landscape in Austin, Texas (ATX) through various static and interactive visualizations methods. Our study focuses on the impact of a peer-to-peer accommodation platform on the local economy and the lodging industry;and how positives reviews promote the most lucrative listing, accommodation, or host. Our findings elevate Airbnb's colossal impact on the Austin economy and lodging sectors. We found that offering the entire property in a good location with high cleaning standards is attractive on the Airbnb platform, which means more lucrative.

关键词： data visualization Sharing Economy Airbnb Topic Modeling

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Big data analysis for Structuring FX Market Volatility due to Financial Crises and Exchange Rate Overshooting 5

Big Data Analysis for Structuring FX Market Volatility due t...

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5th International conference on Computational Linguistics and Intelligent Systems (COLINS)

作者： Veres, Oleh Ilchuk, Pavlo Kots, Olha Bondarenko, Lidiia Lviv Polytech Natl Univ Stepana Bandery Str 12 UA-79013 Lvov Ukraine

Big data analysis is used in various spheres. Financial crises, which are an integral part of the modern economy, require new approaches to analysis. The research hypothesizes the existence of a link between financial crises and shocks in foreign exchange (FX) market, and it is proven using Big data analysis information technology. The information base of the research was data on exchange rate fluctuations during the financial crises in Ukraine ( 2008, 2015, 2020), as well as similar data on COVID-19 Pandemic Crisis in Ukraine, Russia, Belarus, Georgia and Poland. In the course of the research, data structuring, data visualization, analysis of statistical links and regularities among data series were performed, in particular, using Fstatistics and Student's t-test. The results of the research have showed that the Big data analysis makes it possible to identify trends in unstructured and poorly structured data, in particular regarding exchange rate fluctuations.

关键词： data analysis Big data financial crisis panic exchange rate overshooting volatility FX market COVID-19 Pandemic Crisis

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CellProfiler Analyst Web (CPAW) - Exploration, analysis, and classification of biological images on the web

CellProfiler Analyst Web (CPAW) - Exploration, analysis, and...

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IEEE visualization conference (IEEE VIS)

作者： Baidak, Bella Hussain, Yahiya Kelminson, Emma Jones, Thouis R. Franke, Loraine Haehn, Daniel Univ Massachusetts Boston Boston MA 02125 USA Broad Inst MIT & Harvard Cambridge MA 02142 USA

ISBN: (纸本)9781665433358

CellProfiler Analyst (CPA) has enabled the scientific research community to explore image-based data and classify complex biological phenotypes through an interactive user interface since its release in 2008. This paper describes CellProfiler Analyst Web (CPAW), a newly redesigned and web-based version of the software, allowing for greater accessibility, quicker setup, and facilitating a simple workflow for users. Installation and managing new versions has been challenging and time-consuming, historically. CPAW is an alternative that ensures installation and future updates are not a hassle to the user. CPAW ports the core iteration loop of CPA to a pure server-less browser environment using modern web-development technologies, allowing computationally heavy activities, like machine learning, to occur without freezing the user interface (UI). With a setup as simple as navigating to a website, CPAW presents a clean UI to the user to refine their classifier and explore phenotypic data easily. We evaluated both the old and the new version of the software in an extensive domain expert study. We found that users could complete the essential classification tasks in CPAW and CPA 3.0 with the same efficiency. Additionally, users completed the tasks 20 percent faster using CPAW compared to CPA 3.0. The code of CellProfiler Analyst Web is open-source and available at https://***/CellProfilerAnalystWeb/.

关键词： Biological Images visualization Machine Learning Classification Evaluation Methods

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