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visualization analysis of Stock data Based on Tableau 18th

Visualization Analysis of Stock Data Based on Tableau

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18th International conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Deng, Chao Peng, Jiao Chen, Yeh-Cheng College of Computer Guangdong University of Science and Technology Guangdong Dongguan523083 China Department of Computer Science University of California DavisCA95616 United States

ISBN: (纸本)9789819906048

In the context of big data, with the rapid development of globalization and social evolution, the outbreak of COVID-19 in 2020 has brought a huge impact on all walks of life, especially the economy. The medical industry is closely related to the COVID-19 epidemic, especially the traditional Chinese medicine industry, which is a treasure of the Chinese nation, has also been affected. This paper takes the data of "SHIJIAZHUANG YILING PHARMACEUTICAL CO., LTD.", a Chinese traditional Chinese medicine enterprise, as an example, obtains the data of recent three years through Python, and uses Tableau, a visual analysis tool, to analyze the data and present it in an intuitive visual form. The statistical rules and development trends of the opening price, closing price, rise and fall, turnover rate, average price, and other data of "SHIJIAZHUANG YILING PHARMACEUTICAL CO., LTD." in the recent three years are shown in graphic form, so as to provide a certain reference for investors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Python

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Trajectory Vector Field Calculation and visualization Method for Regional Congestion Evaluation 3

Trajectory Vector Field Calculation and Visualization Method...

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3rd International conference on Internet of Things and Smart City, IoTSC 2023

作者： Li, Taizeng Zhang, Jianqin Yao, Zhixin Li, Zhuohang School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing106216 China Key Laboratory of Urban Spatial Information Natural Resources Ministry Beijing102616 China

ISBN: (纸本)9781510666375

Congestion status evaluation is a vital link and tool in urban traffic congestion management. To timely warn and evaluate the congestion status of urban hot spots, a new congestion situation visualization model based on vector field is proposed. The calculation method of congestion status evaluation index is simplified based on this method. At the model building level, combining the advantages of OD flow diagram and OD matrix diagram, a dynamic visualization model of traffic congestion situation monitoring is established by constructing grid division and extracting action quantities. A method for identifying the trend of traffic congestion characteristics in urban areas is proposed. Simplify the algorithm level, combine the model visualization and the calculation process of the congestion evaluation index, and calculate the average actual travel time according to the vector field data structure, to realize the rapid calculation of the congestion index. The research shows that the model has the ability of trend analysis based on the visual expression of many basic traffic flow parameters such as flow, flow direction, speed, and spatial distribution, and realizes effective identification and early warning of hotspot congestion areas. The simplified calculation results of congestion index Compared with the traditional traffic index algorithm, the average error is 0.016. While the calculation efficiency is optimized, the effectiveness of the regional congestion index is guaranteed. This method can apply the research results to urban traffic congestion monitoring and management. © 2023 SPIE.

关键词： Traffic congestion

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Research on the Competency Framework of Management Accounting Profession in the age of "Great Wisdom Moving Cloud" of China based on Knowledge Graph 7

Research on the Competency Framework of Management Accountin...

引用

7th International conference on Information Systems Engineering (ICISE)

作者： Li, Kaodui Yu, Xinyi Chu, Yanhong Yang, Xue Xu, Haochen Shen, Cuiqi Jiangsu Univ Sch Finance & Econ Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9781450397889

As China's economy steps into the new normal and its growth changes from extensive growth based on scale and speed to intensive growth based on quality and efficiency, enterprises are in urgent need of management accounting profession to help them improve their capital structure and realize transformation and upgrading. However, most of the enterprises in China still focus on the traditional accounting model and lack a reasonable and perfect competency framework of management accounting profession. This thesis, based on the data of the general database of online publications of Chinese academic journals and by means of information visualization software (Gephi) and keywords co-occurrence network analysis, makes a visual analysis of the documents on the competency framework of management accounting profession from the perspective of time distribution, high frequency keywords, authors and source journals. It explores the knowledge graph of research hot spots on the competency framework of management accounting profession and analyses its overall development trend.

关键词： visualization Analytics Management Accounting Competency Framework Knowledge Graph

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analysis and visualization of Heart Failure Prediction dataset 4

Analysis and Visualization of Heart Failure Prediction Datas...

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4th International conference on Artificial Intelligence and Speech Technology, AIST 2022

作者： Patel, Dhyani Chopra, Sukanya Sharma, Nonita Mangla, Monika Department Delhi India Indira Gandhi Delhi Technical University for Women Department of Information Technology Delhi India Dwarkadas J Sanghvi College of Engineering Department of Information Technology Mumbai India

ISBN: (纸本)9781665499026

This research work is based on the analysis of dataset of heart failure patients to predict their chances of survival. Cardiovascular diseases (CVDs) is the highest reason for deaths across the world. According to the statistics of 2019, 17.9 million people died due to heart failure which forms around 32% of the global deaths. Early prediction of the disease may act as a helping aid to medical professional to take required actions for curing the disease. For the same, several factors like serum creatinine, ejection fraction, age and medical history of the patient are considered. This information is used to evaluate the chances of survival of the patient. The analysis of the dataset is performed by pre-processing followed by statistical and visual analysis for different attributes. The experimental simulation is implemented in python. The major contribution of the research work is to draw inferences from statistical and visual analysis of the data so as to make the model easily understandable for a naïve user. © 2022 IEEE.

关键词： visualization

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Design and Implementation of Wastewater Pollutant data analysis and visualization System for Vessels 4

Design and Implementation of Wastewater Pollutant Data Analy...

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2022 4th International conference on Artificial Intelligence Technologies and Applications, ICAITA 2022

作者： Lv, Taizhi Tang, Peiyi Zou, Yujuan College of Information Technology Jiangsu Maritime Institute Nanjing China General Manager Office Nanjing Huihai Transportation Technology Company Limited Nanjing China

To monitor the discharge of water pollutants from vessels, a monitoring system for the discharge of water pollutants from vessels has been established on the Yangtze River. The system generates tens of thousands of ship wastewater pollutant data every day. The analysis and visualization of wastewater pollutant discharge data can help the monitoring department to grasp the discharge situation and improve the accuracy of supervision. This system extracts the data to the data warehouse in real-time based on the data extraction technology, improves the query efficiency based on the three-level storage architecture, makes real-time pollutant data statistics based on the stream computing technology, and realizes the visual display of the data based on the front-end and back end-separation technology. The system has been applied in the maritime supervision department to provide a data basis for vessel wastewater pollutant supervision and decision-making. © Published under licence by IOP Publishing Ltd.

关键词： data warehouses

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The Use Leontief Input-Output Model to Estimate the Resource and Value Added

The Use Leontief Input-Output Model to Estimate the Resource...

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2022 International conference on Smart Information Systems and Technologies, SIST 2022

作者： Kerimkhulle, Seyit Alimova, Zhanar Slanbekova, Assylzat Baizakov, Nauryz Azieva, Gulmira Koishybayeva, Meruyert L.N.Gumilyov Eurasian National University Nur-Sultan Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The paper highlights that, the use of input-output theory and method and system dynamics enable the construction of the direct and dual Leontief models, and the realization of these models in the AnyLogic software environment, which produce output data -value estimation and prediction, simulation, and visualization of the results of computer experiments. And on the basis of analysis of the data of the table of inter-sectoral relations of the Republic of Kazakhstan in USD billion for 2019, from the OECD report, it justified, the budget of the distribution system of inputs and outputs and the budget of the generation system of production costs and value added in the use of resources are harmonized, in particular, the sum of outputs of 1.270 units or 82.629 billion and the sum of inputs of 3.000 units or 189.984 billion, facilitate equilibrium growth of the national economy of the Republic of Kazakhstan over the short-term development period of 4.270 physical output units, or USD 276.395 billion. © 2022 IEEE.

关键词： data visualization

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Understanding Classroom Interaction Using Epistemic and Social Network analysis 15th

Understanding Classroom Interaction Using Epistemic and Soci...

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15th International conference on Blended Learning (ICBL)

作者： Chen, Xieling Zou, Di Cheng, Gary Xie, Haoran Educ Univ Hong Kong Dept Math & Informat Technol Tai Po Hong Kong Peoples R China Educ Univ Hong Kong Dept English Language Educ Tai Po Hong Kong Peoples R China Lingnan Univ Dept Comp & Decis Sci Tuen Mun Hong Kong Peoples R China

ISBN: (纸本)9783031089381;9783031089398

This study focuses on understanding classroom interaction using epistemic and social network analysis. Based on the classroom interaction data concerning an online course named Justice with 12 episodes, we demonstrate epistemic and social network analyses' advantages in evaluating the quality of classroom interaction, instructors' performance in promoting students' higher-order thinking, and individual students' performance in the classroom interaction. Results suggest that to promote productive classroom interaction and students' high-level cognitive contributions, instructors can 1) ask questions that explicitly require explanations, 2) encourage students to think with others, 3) encourage children to think about counterexamples or to challenge others' opinions or ideas, and 4) arrange group discussion activities.

关键词： Classroom interaction Epistemic network analysis Social network analysis visualization

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Study on the Organization and Governance of Bigdata for Lifelong Education 6th

Study on the Organization and Governance of Bigdata for Life...

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6th International conference on Smart Computing and Communication (SmartCom)

作者： Ma, Li Yang, Zexian Yang, Wenyin Yang, Huihong Lao, Qidi Foshan Univ Elect & Informat Engn Sch Foshan Peoples R China Foshan Univ Mechatron Engn & Automat Sch Foshan Peoples R China

ISBN: (纸本)9783030977740;9783030977733

The open university is carrying out various types of academic and non-academic education to serve the city's citizens and usually has gained a good reputation in the local area. However, previously, due to its inadequate hardware system, fragmented information system, and incomplete data collection, it carried out various operations more by empirical judgment and lacked objective data support, thus making it impossible to promote the development of a lifelong education system accurately. By collecting, integrating, and analyzing these lifelong education projects, converting them into lifelong education big data, and establishing various lifelong education data visualization and analysis models, we can promote the transformation of life-long education from discrete demand to education big data precision-driven development mode, provide support for the supply-side structural reform of lifelong education, and at the same time improve the leading role of the open university in the construction of lifelong education system, thus promoting the high-quality development of lifelong education for citizens.

关键词： Lifelong education analysis model Big data

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Effective Use of Likert Scales in visualization Evaluations: A Systematic Review

Effective Use of Likert Scales in Visualization Evaluations:...

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24th Eurographics/IEEE VGTC conference on visualization (EuroVis)

作者： South, Laura Saffo, David Vitek, Olga Dunne, Cody Borkin, Michelle A. Northeastern Univ Boston MA 02115 USA

Likert scales are often used in visualization evaluations to produce quantitative estimates of subjective attributes, such as ease of use or aesthetic appeal. However, the methods used to collect, analyze, and visualize data collected with Likert scales are inconsistent among evaluations in visualization papers. In this paper, we examine the use of Likert scales as a tool for measuring subjective response in a systematic review of 134 visualization evaluations published between 2009 and 2019. We find that papers with both objective and subjective measures do not hold the same reporting and analysis standards for both aspects of their evaluation, producing less rigorous work for the subjective qualities measured by Likert scales. Additionally, we demonstrate that many papers are inconsistent in their interpretations of Likert data as discrete or continuous and may even sacrifice statistical power by applying nonparametric tests unnecessarily. Finally, we identify instances where key details about Likert item construction with the potential to bias participant responses are omitted from evaluation methodology reporting, inhibiting the feasibility and reliability of future replication studies. We summarize recommendations from other fields for best practices with Likert data in visualization evaluations, based on the results of our survey. A full copy of this paper and all supplementary material are available at https://***/exbz8/.

关键词： visualization

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analysis of Research Paper Titles Containing Covid-19 Keyword Using Various visualization Techniques 1

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2nd International conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS)

作者： Bedekar, Mangesh Desai, Sharmishta Dr Vishwanath Karad World Peace Univ Sch Comp Enginering & Technol Pune 411038 Maharashtra India

ISBN: (数字)9789811925412

ISBN: (纸本)9789811925412;9789811925405

It's been around two years from the outbreak of the coronavirus, thus labeled as Covid-19, and there has been an explosion of literature being published by research scholars related to work done on Covid-19. Covid-19 as a keyword has been mentioned in the titles of most of these papers. It was thought to analyse the number of papers and the titles of papers which include Covid-19 in the title of the research papers. The various combinations of other words like, prefixes, suffixes, N-gram combinations with the keyword Covid-19 in the titles of these papers were also analysed. The research publication repositories analysed were: IEEE Explore, ACM Digital Library, Semantic Scholar, Google Scholar, Cornel University etc. The domains of research publication title analysis were restricted to computer science/computer engineering related papers. As the term labeling the corona virus outbreak as Covid-19 was labeled in 2020, the timeline of title analysis was restricted from 2019 till December 2021. The term Covid-19 is also one of the most searched terms in most of these research repositories as is evident from the search suggestions offered by them. Considering the usefulness of Bag of Words and N Gram algorithm in analytics and data visualization, a methodology is proposed and implemented based on bag of words algorithm to do prefix and suffix words analysis. This methodology is working correctly to state different prefix and suffix words used by various researchers to demonstrate significance of their titles. Methodology based on N Gram analysis is found effective to find topic on which most of the researchers have done work. Word Clouds are generated to demonstrate different buzz words used by researchers in their respective paper titles. These are useful for providing visualization of the data if it is in big size.

关键词： Bag of words Covid-19 N Gram Research titles Tag cloud Word cloud

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