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IEEE International conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Zhicheng Dai Xuebing Wu XiaoLiang Zhu National Engineering Research Center for E-Learning Central China Normal University Wuhan China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China National Engineering Laboratory for Educational Big Data Central China Normal University Wuhan China

ISBN: (纸本)9781665436885

With the introduction of Education Informatization 2.0, smart education has gradually become a research hotspot in academia. As an important part of smart education, Smart Learning Environment (SLE) has become an increasingly important factor with board prospects. This study identified the research focus and development tendency of SLE in China from 2011 to 2020 using the metrological literature visualization software Citespace, which is based on the core database of academic journals of CNKI. The results show that the research hotspots focused on building SLE by using emerging technologies such as big data, artificial intelligence and 5G technology. In terms of application, it is no longer simply using information technology, but emphasizing the deep integration and innovation of information technology and subject teaching. This article combs the development process of SLE, hoping to provide ideas for the subsequent development of SLE research and application.

关键词： Technological innovation Education Bibliometrics Knowledge based systems Buildings data visualization Market research

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Quality scale adaptation applied to a communication platform for primary health care analysis 13

Quality scale adaptation applied to a communication platform...

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13th IADIS International conference Information Systems 2020, IS 2020

作者： Moita, Galba Freire Júnior, Galba Freire Moita Brazil Brazil Coimbra Portugal Brazil Omnielmaster Hem. Repr. Com. e Serv. em Saude Consultoria Trein. e Educ. Prof. Ltda

ISBN: (纸本)9789898704153

Nationally based opinion polls showed population dissatisfaction ranging from 54 to 93% (CFM, 2014, 2015, 2018). And yet, that high percentages of Brazilians evaluate public health as bad or terrible, which increased from 61% in 2011 to 75% in 2018 (CNI, 2012, 2018), which revealed a supposed dissatisfaction in public and supplementary health of Brazil. In an integrative bibliographical research on quality measurement and health user satisfaction in Brazil, the results obtained are timid and there are no records of standardization of quality and satisfaction measurement systems in Brazilian Health System whose acronym in Portuguese is SUS (Sistema Único de Saúde). Thus, the outlined objective was to adapt an international model by transliterating and revalidating the 22 questions on the Servqual scale (Berry, Parasuraman, Zeithaml, & Adsit, 1994;Parasuraman, Berry, & Zeithaml, 1991a), for quality assessment and satisfaction in health services to support the development of a virtual platform to capture the experience of SUS users. In a world where data is what most matter, which generate information and knowledge and can be a basis for new strategies, methodologies for its collection, manipulation, transformation and visualization enable diagnoses, solutions to help users’ perceptions of a system in relation of quality of provided services. This study involved 220 managers and professionals (stakeholders) as well as 506 users for the cross-cultural translation and validation of the Servqual scale constructs for the SUS context and presents a way of extracting knowledge of specialists and users through the cross-cultural adaptation of Servqual Scale, which resulted in the instrument QUALITY SAÚDE (Health quality in portuguese) of measuring expectation and perception from users of Brazilian health system (SUS), measuring their satisfaction. data were extracted from a relational database in order to be consulted in an organized way, quickly and mainly without unnecessar

关键词： visualization

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The Trend, Hotspots, Frontier and Path of Big data visualization Research in China——Based on the Knowledge Graph analysis of Citespace5.5.R2

The Trend, Hotspots, Frontier and Path of Big Data Visualiza...

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Culture-oriented Science & Technology (ICCST), International conference on

作者： Guanghui Min Muhui Lin Zhe Li Yuexia Du Faculty of Education Fujian Normal University Fuzhou China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

In 2016, China has adopted big data visualization technology as its national development strategy, however relevant literature review research is deficient at present. In view of this, this study uses Citespace5.5.R2 to elaborately analyze 2875 documents in CNKI database from 1994 to 2020 by adopting the methods of keyword co-occurrence analysis, document co-citation analysis and high-cited document analysis, which reasonably draw a conclusion on the research trend, research hotspots distribution, research frontier and research path of big data visualization research field in China. In general, research on big data visualization in China keeps a steady growing trend; Research hotspots are divided into four major themes: journalism is the main application industry, big data visualization technology and platform research, the representation of big data visualization and big data visualization algorithm research. From the perspective of research frontier, research based on Knowledge Graph has become the latest research method and Echart has become the latest technology implementation method in this field. In view of the research path, Chinese big data visualization research has gone through three stages: 1994-2003 is in the embryonic stage, 2004-2011 is in the stage of stable development and 2012- 2020 is in the rapid development stage.

关键词： data visualization Big data Journalism Market research Industries Text analysis Visual databases

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VAP: A Visual analysis Tool for Energy Consumption Spatio-temporal Pattern Discovery 23

VAP: A Visual Analysis Tool for Energy Consumption Spatio-te...

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23rd International conference on Extending database Technology, EDBT 2020

作者： Liu, Xiufeng Niu, Zhibin Yang, Yanyan Wu, Junqi Cheng, Dawei Wang, Xin Technical University of Denmark Lyngby Denmark School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom Tianjin University Tianjin China Shanghai Jiaotong University Shanghai China Southwest Jiaotong University Chengdu China

ISBN: (纸本)9783893180837

In the context of urbanization and the rapid growth of energy demand, understanding the spatial and temporal dynamics of urban energy use is crucial for identifying energy-saving potentials. In this demo, we present a visual analysis tool, VAP, that allows users to explore the dynamics of urban energy use at different spatial and temporal scales. In contrast to traditional statistical and machine learning methods, the visual analysis based tool focuses on analytical thinking, user interactions and answering business questions by examining different visual analysis views. In the demonstration, conference attendees will interact with VAP and learn its capabilities in discovering typical consumption patterns and spatio-temporal shift patterns from a real-world case study of electricity. © 2020 Copyright held by the owner/author(s).

关键词： Energy utilization

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Understanding Gender Commuting Gap Using Geographic visualization

Understanding Gender Commuting Gap Using Geographic Visualiz...

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International conference on Mathematics and Computers in Science and Engineering (MACISE)

作者： Shariff, Noresah Mohd Univ Sains Malaysia Sch Distance Educ Geog Programme George Town Malaysia

ISBN: (纸本)9781538692042

This paper discusses the spatial patterns of gender commuting to work gap using geographic visualization. Geographic visualization is a tool to understand and communicate spatial patterns. Geographic visualization integrates many disciplines cartography, image analysis, visualization in scientific computing, information visualization, exploratory data analysis and geographic information system. Commuting to work is a global phenomenon. It involves number of vehicles on the roads and the consequences of this transportation event have impacts on the population, environment and the economy. Commuting to work is associated with daily travel, long distance journey and more time on the road. GIS is a system capable of geographic visualizing, analyzing and modelling spatially referenced real world data. It provides a framework that models the interactions of real world objects in space and time to find existing patterns and predicts what will happen. All transportation related events and attributes have space and time coordinates attached to them. This paper reviews the application of GIS in geographic visualizing and analyzing spatial patterns of commuting to work using different modes of transport and gender. data on commuting to work by motorized vehicles such as cars, buses, rail and underground trains in the United Kingdom by regions is used in this study. The sample includes all individuals in employment in the age group 16 to 64, with valid geographical coordinates of residence and work place in 2011. The discussion is focus on the commuting gap between male and female commuters by regions.

关键词： geographic visualization commuting to work gender spatial patterns United Kingdom

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analysis of the characteristics of hepatitis B in various regions of China from 2009 to 2011 and the analysis of TCM diagnosis and treatment plans

Analysis of the characteristics of hepatitis B in various re...

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IEEE International conference on Bioinformatics and Biomedicine (BIBM)

作者： Yating Yin Guo-Zheng Li Yiguo Wang Qiming Zhang Mingqiang Wang Lei Zhang China Academy of Chinese Medical Science Institute of Information on Traditional Chinese Medicine Beijing China Information Office Henan University of Chinese Medicine Zhengzhou China Experimental Research Center China Academy of Chinese Medical Science Beijing China National Data Center of TCM China Academy Of Chinese Medical Sciences Beijing China

ISBN: (纸本)9781665429825

Objectives: To sort out the regional distribution characteristics of viral hepatitis B in China and Chinese medicine treatment plans, summarize the rules, and explore the regional characteristics to provide references for clinical diagnosis and treatment decision-making and related research. Technology or Method: Collect the electronic medical record information of 25,549 visits of 8544 patients with 117 doctors in 20 tertiary A hospitals in different regions of China. The correlation between the epidemic characteristics of hepatitis B and regional factors is analyzed, and visualization technology is used to display it. Results: After inclusion and exclusion criteria, the medical records of 2573 patients with 2573 visits were finally used as the data source of this study. After analysis, it can be seen that for the Chinese region, there are more hepatitis B patients in the south than in the north. The south is dominated by Syndrome of dampness-heat blocking collaterals, and the north is dominated by Syndrome of stagnation of liver qi and spleen deficiency. Qinggan Lishi Decoction is commonly used in southern treatment, and Xiaoyao powder is commonly used in northern treatment. Conclusion: The incidence of viral hepatitis B has regional characteristics. Diagnosis and treatment of viral hepatitis B in various regions have many common features. The TCM symptoms of the disease and the distribution of TCM prescriptions have certain regularities and differences. The diagnosis and treatment plan of Chinese medicine needs to consider various factors such as climate and patient’s physical condition to achieve the best treatment effect.

关键词： Epidemics Powders Liver diseases Hospitals Soft sensors Real-time systems Electronic medical records

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Towards understanding the synergetic relationship of data visualization with learning analytics: A review

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AIP conference Proceedings 2022年第1期2644卷

作者： Nur Maisarah Shahril Khuzairi Zaihisma Che Cob Thaharah Hilaluddin Universiti Tenaga Nasional Jalan lkram-Uniten 43000 Kajang Selangor Malaysia.

As online learning and the use of learning management systems grows rapidly, large amounts of educational data are made available for learning analytics. data visualization plays an important role within learning analytics, as it generates complex analysis and data into a visual representation for easy comprehension by the user to support better decision-making among stakeholders (e.g. students, educators, administrators). The purpose of this paper is to review the existing studies to provide an overview of data visualization in learning analytics within the educational communities. First we analyze the use of data visualization and learning analytics purposes in the contexts of its stakeholders. Second, we examine the relationship between data visualization and learning analytics in the development of learning management systems and then we discuss the challenges found. A systematic literature review was conducted based on the research keywords from reputable databases and 62 journal articles published from 2011 to 2021 were identified. The results from this review suggest there is an indispensable synergetic relationship between data visualization and learning analytics for successful learning management systems. Also there is a lack of studies that consider data visualization and learning analytics from the technological theories perspective.

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Applying data visualization Guideline on Forest Fires in Argentina

Applying Data Visualization Guideline on Forest Fires in Arg...

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International conference on Confluence The Next Generation Information Technology Summit (Confluence)

作者： María Laura Sánchez Reynoso Mario José Diván Data Science Research Group Economy School National University of La Pampa Santa Rosa La Pampa Argentina

ISBN: (数字)9781728127910

ISBN: (纸本)9781728127927

Nowadays, the data has a dynamic never seen before. They have continuous growth which is associated with the permanent generation from both data entered by users and new data derived from systems. In this context, the data visualization plays a highlighted role because it allows synthetically communicating high-data volume making them understandable for the End-user. This aspect constitutes a key asset throughout the decision-making process in any organization because incorporates dynamism and fosters different kinds of analysis. For that reason, the use of guidelines allows tutoring a process and in particular, those related to data visualizations. In this work, the general visualization process is described in order to schematize the way in which user requirements and sketches converge. Next, the visualization design describes the way in which the sketches could be implemented using the software. As a contribution, here an application case using the forest's fires dataset of Argentina between 2011 and 2017 is shown in order to serve as a reference for the guidelines' using. The case was implemented using Qlik Sense Cloud, incorporating a set of dynamic behaviors included in the platform, such as the possibility of making zoom on maps or sharing the selections between visual components. The employed data are freely available on ***, the Open-data platform of Argentina's Government. The case allows exemplifying the use of guidelines, its applicability, and the chosen data visualization strategy in a consistent way.

关键词： data visualization visualization Guidelines Forestry Fires Big data

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Illiteracy spatial analysis as an effort to improve the quality of human resources in Indonesia

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AIP conference Proceedings 2023年第1期2720卷

作者： Tuti Purwaningsih Rochmad Novian Inderanata Rahmi Anadra Statistics Department Universitas Islam Indonesia Yogyakarta Indonesia Graduate School of Technology and Vocational Education Yogyakarta State University Yogyakarta Indonesia Mechanical Engineering Vocational Education Department Universitas Sarjanawiyata Yogyakarta Indonesia

Illiterate is someone who can’t read and can’t write to communicate. The large number of people who are still illiterate in a country is one indicator that shows the country is still not developed. The percentage of illiteracy in 2011 was 4.63 percent of the population in Indonesia, and in 2019 it fell to 1.78 percent of the population in Indonesia who are still illiterate from the total population of Indonesia. The factors that cause illiteracy can be identified from the poverty of the population, dropping out of elementary school (SD), and the condition of the community’s social environment. This study aims to improve the literacy skills of the Indonesian people. The data used is sourced from the Central Statistics Agency. The data entered is the population aged 10 years and over who are illiterate (percent) in Indonesia. The number of records used is 34 provinces which are divided into the last 3 years, 2018, 2019, and 2020. The data processing process is carried out using the Geoda application for later visualization. Based on the research conducted, it was found that there has been a decline in illiteracy in the provinces in Indonesia from year to year which shows that the quality of Indonesian human resources can be said to be much better. It is hoped that this research can be used as a basis for decision making for the government in an effort to eradicate illiteracy by province in Indonesia in order to produce quality Indonesian human resources.

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Selecting Auxiliary data Using Knowledge Graphs for Image Classification with Limited Labels

Selecting Auxiliary Data Using Knowledge Graphs for Image Cl...

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IEEE Computer Society conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Elaheh Raisi Stephen H. Bach Brown University

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

In this paper, we propose a learning algorithm for training deep neural networks when there is not sufficient labeled data. To improve the generalization capabilities of the deep model, we adopt a learning scheme to train two related tasks simultaneously. One is the original task (target), and the other is an auxiliary task (source). In order to create a related auxiliary task, we leverage an available knowledge graph to query for semantically related concepts that are grounded in labeled images; hence we call our method KGAuxLearn. We jointly train the target and source tasks in a multi-task architecture. We evaluate our method on two fine-grained visual categorization benchmarks: Oxford Flowers 102 and CUB-200-2011. Our experiments demonstrate that the error rate reduced by at least 2.1% over finetuning for both datasets. We also improve the error rate by 1.36% and 2.93% over using randomly selected concepts as an auxiliary task for Oxford Flowers 102 and CUB-2002011, respectively. In addition, comparing our method with auxiliary data selection methods that do not use a knowledge graph, the error rate improves by 0.69% and 2.57% on Oxford Flowers 102 and CUB-200-2011, respectively.

关键词： Task analysis Training visualization Neural networks Error analysis Computational modeling Semantics

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