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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

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A Visual Data Science Solution for visualization and Visual Analytics of Big Sequential Data 25

A Visual Data Science Solution for Visualization and Visual ...

引用

25th International conference information Visualisation (IV) - AI and Visual Analytics and Data Science

作者： Leung, Carson K. Wen, Yan Zhao, Chenru Zheng, Hao Jiang, Fan Cuzzocrea, Alfredo Univ Manitoba Dept Comp Sci Winnipeg MB Canada Univ Northern British Columbia UNBC Dept Comp Sci Prince George BC Canada Univ Calabria iDEA Lab Arcavacata Di Rende Italy

ISBN: (纸本)9781665438278

In the current era of big data, huge volumes of valuable data have been generated and collected at a rapid velocity from a wide variety of rich data sources. In recent years, the initiates of open data also led to the willingness of many government, researchers, and organizations to share their data and make them publicly accessible. An example of open big data is healthcare, disease and epidemiological data such as privacy-preserving statistics on patients who suffered from epidemic diseases like the coronavirus disease 2019 (COVID-19). Analyzing these open big data can be for social good. For instance, analyzing and mining the disease statistics helps people to get a better understanding of the disease, which may inspire them to take part in preventing, detecting, controlling and combating the disease. As "a picture is worth a thousand words", having the pictorial representation further enhances people's understanding of the data and the corresponding results for the analysis and mining. Hence, in this paper, we present a visual data science solution for the visualization and visual analytics of big sequential data. We illustrate the ideas through the visualization and visual analytics of sequences of real-life COVID-19 epidemiological data. Our solution enables people to visualize COVID-19 epidemiological data and their temporal trends. It also allows people to visually analyze the data and discover relationships among popular features associated with the COVID-19 cases. Evaluation of these real-life sequential COVID-19 epidemiological data demonstrates the effectiveness of our visual data science solution in enhancing user experience in the visualization and visual analytics of big sequential data.

关键词： information visualization big data sequences data science visual data science data mining data analytics visual analytics COVID-19

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Geospatial Intelligence in Business: A Geographic information System-Based Approach 2

Geospatial Intelligence in Business: A Geographic Informatio...

引用

2nd International conference on Computing and Data Analytics, ICCDA 2024

作者： Ugalde, Bernard Dalan, Edgardo Decena, Lilibeth Fanshawe Colege LondonON Canada University of Technology and Applied Sciences Shinas Oman

ISBN: (纸本)9798331542573

Geographic information Systems (GIS) have become a pivotal tool in modern business strategies, offering geospatial intelligence that significantly enhances decision-making processes. This paper analyzes recreational and sports facilities across Quebec using data from the Open Database of Recreational and Sport Facilities (ODRSF) sourced from Statistics Canada. The research identifies trends and patterns in facility distribution and density to provide insights into regional recreational infrastructure. The study utilizes descriptive analysis, geographic visualization, and heat map techniques to examine the concentration of facilities in various Census Subdivisions (CSDs). Key findings reveal that Gatineau, Montréal, Shawinigan, Laval, Québec, Longueuil, and Sherbrooke exhibit the highest recreational and sports facilities densities, indicating significant community engagement in these areas. The analysis also highlights the prevalence of parks, pools, and sports fields, with parks being the most common facility type, followed by pools and sports fields. The implications of these findings are substantial for businesses and policymakers. High-density regions present opportunities for targeted market strategies, including optimal site selection for new facilities and tailored product offerings. The study also suggests the potential for community-focused programs and partnerships to enhance recreational investments. Overall, the research provides substantial insights into the spatial distribution of recreational facilities, offering a basis for strategic planning and further investigation in the sports and leisure sector. © 2024 ieee.

关键词： Site selection

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Parallel Computing Algorithm and visualization of Particles wave Functions in a Quantum System 17

Parallel Computing Algorithm and Visualization of Particles ...

引用

ieee 17th International conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Sus, Bogdan Zagorodnyuk, Sergiy Bauzha, Oleksandr Ivanyshyn, Alla Taras Shevchenko Natl Univ Kyiv Inst High Technol Kiev Ukraine Taras Shevchenko Natl Univ Kyiv Fac Radio Phys Elect & Comp Syst Kiev Ukraine Lviv Polytech Natl Univ Inst Comp Technol Automat & Metrol Lvov Ukraine

ISBN: (纸本)9781665424103

The article presents the procedure for solving a comlex computational scientific problem and visualization of the obtained results. The effect of the magnetic field was taken into account in calculations. This procedure is a clear example of mutual integration and combination of own developed software and existing specialized mathematical editors. The article demonstrates the advantages of developed specialized software for interactive graphics and physical visualization at the basic initial stage. The results of theoretical research in this article can be useful for experimental.

关键词： visualization wave function energy level energy spectrum quantum ring

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Boiler Monitoring based on Data Analytics Tools 29

Boiler Monitoring based on Data Analytics Tools

引用

29th Mediterranean conference on Control and Automation (MED)

作者： Garces, Hugo O. Morales, Eduardo Espinosa, Eduardo Rojas, Alejandro J. Shah, Sirish L. Univ Catolica Santisima Concepcion Comp Sci Dept Concepcion Chile Univ Catolica Santisima Concepcion Elect Engn Dept Concepcion Chile Univ Concepcion Elect Engn Dept Concepcion Chile Univ Alberta Dept Chem & Mat Engn Edmonton AB Canada

ISBN: (纸本)9781665422581

The availability of large volumes of data in industrial automation is not directly related to the extraction of valuable information or process monitoring for a enhanced performance. Typically, data is visualized as tables, or trend plots;hiding information to increase energy-savings or decrease environmental impact. This paper presents a boiler operational monitoring design by considering alarms visualization plots that provide useful information, combined with a virtual sensor design used to predict the energy efficiency, which in turn defines the steam boiler operational performance.

关键词： Process monitoring Automation Data analysis Data visualization Tools Boilers Market research

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A Lightweight AI Model for Anomaly Detection in Wireless Networks 2

A Lightweight AI Model for Anomaly Detection in Wireless Net...

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2nd International conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Kopcho, Thomas J. Fouda, Mostafa M. Krome, Cameron J. Idaho State University Department of Computer Science PocatelloID United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Idaho National Laboratory Ai Data & Visualization Idaho FallsID United States

ISBN: (纸本)9798331529529

Detecting network anomalies is critical for wireless network security and reliability. Traditional AI methods often require substantial computational resources, particularly when deployed on cloud servers, leading to increased network load and latency. In contrast, deploying AI models directly on end devices enables real-time data processing at the source, facilitating faster anomaly detection and mitigation. We propose a lightweight hierarchical AI model where initial inferences are made by a simple model and outputs confidence scores. Using a modified TOPSIS-based method, we determine an optimal confidence score threshold. Inferences below this threshold are forwarded to a more complex model for accurate analysis, reducing overall computational demands while maintaining high detection performance. Our approach is tested on a 5 G network dataset, demonstrating competitive performance compared to other anomaly detection models. © 2024 ieee.

关键词： 5G mobile communication systems

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A Web-Based Learning Platform for Teaching Data Science to Non-Computer Majors 53

A Web-Based Learning Platform for Teaching Data Science to N...

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53rd ieee ASEE Frontiers in Education International conference, FIE 2023

作者： Liu, Xumin Golen, Erik Raj, Rajendra Fluet, Kimberly Rochester Institute of Technology Department of Computer Science RochesterNY United States School of Information Rochester Institute of Technology RochesterNY United States University of Rochester Center for Professional Development and Education Reform RochesterNY United States

ISBN: (纸本)9798350336429

A web-based learning platform is useful as it allows students with limited or no programming background to conduct in-depth hands-on practice in data science. Background: The need for data science coursework for non-computing majors has grown in recent years, given the demand in various disciplines. However, a substantial number of current data science courses are inappropriate for non-computing majors as they typically require a long chain of prerequisite courses in computer science and mathematics. Moreover, courses designed for computing majors do not match the preparation and interests of students majoring in other disciplines. Outcomes: This paper presents a platform for Learning Data Science (DSLP), a web-based platform, which assists in the teaching and learning of data science topics by students with limited or no coding experience, including those that have completed a high school AP Computer Science Principles (CSP) class or an equivalent CSP course increasingly offered in many colleges. Application Design: The platform helps students understand fundamental data science concepts and techniques, as well as provides them with an in-depth hands-on experience that goes beyond their coding capabilities. The platform offers various data visualization supports to help students understand data and analysis results. Students can use the platform to work on in-house datasets or their own data. This allows students to focus more on how to solve data science problems in various domains than how to write code. The platform also has several unique features that make it particularly helpful for teaching and learning data science topics such as code exemplification and sandbox, informative instructions, and progress monitoring. Findings: The platform has been used multiple times in data science courses for non-computing majors offered at the authors' institution. Preliminary student feedback indicated that the platform is effective in terms of improving student understand

关键词： component formatting insert style styling

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Real-time Clustering and visualization of Customers’ Load Consumption in Electrical Distribution Networks

Real-time Clustering and Visualization of Customers’ Load C...

引用

ieee Green Technologies conference (ieee-Green)

作者： Asmaa Romia Mohamad El Hariri Department of Electrical Engineering Colorado School of Mines CO USA

Recognizing and visualizing customers’ electricity consumption behaviors plays a vital role in enhancing the reliability and efficiency of distribution networks. This paper presents a clustering and visualization platform in real-time and shows the level of consumption using simple visualization means. Based on the level of consumption at each feeder, the tool changes the color to indicate Low, Medium, or High consumption. The platform was applied to a clustering algorithm that was applied to the ieee 33 Bus test feeder considering Golden, CO, USA. Such a platform will help network operator to improve distribution planning, demand response, market segmentation and management, and energy efficiency.

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VisMLB: An Hybrid Data visualization Model for Major League Baseball Matches Using Tableau

VisMLB: An Hybrid Data Visualization Model for Major League ...

引用

Industrial Electronics: Developments & Applications (ICIDeA), ieee International conference on-

作者： Deepak Pandey Rajeev Gupta M.M. Institute of Computer Technology & Business Management Maharishi Markandeshwar (Deemed to be University) Mullana Ambala Haryana India Computer Sc. and Engineering M.M. Engineering College Maharishi Markandeshwar (Deemed to be University) Mullana Ambala Haryana India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

This manuscript provides an in-depth analysis of Major League Baseball (MLB) team performance from 2005 to 2023 using data visualization in Tableau and proposed an hybrid data visualization model (VisMLB) for Major League Baseball matches. The objective is to identify key metrics, such as batting, fielding, and pitching, that influence team success, including championship wins. The authors analyze the total number of championships won by each team, compare top-performing teams based on a variety of performance metrics, and explore the relationship between On-Base Percentage (OBP) and Slugging Percentage (SLG) for home and visitor teams in relation to home victories. Using Tableau, feature importance is visualized, and predictive models are evaluated for accuracy, precision, and recall. The findings offer a comprehensive overview of MLB performance trends over nearly two decades.

关键词： Measurement Analytical models Solid modeling Accuracy Visual analytics Data visualization Predictive models Solids Data models Sports

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4th ieee Global conference on Life Sciences and Technologies, LifeTech 2022

作者： Akiyama, Souta Umezu, Nobuyuki Ibaraki University Dept. Mechanical System Engineering Hitachi Japan

ISBN: (纸本)9781665419048

We propose a support system for instructing sports forms by comparing the forms of a user and those of a model using their similarity and visualizing differences. Captured images of the model performance are scaled to fit to those of the user and overlaid to visualize differences between them. Our system has 2 modes, A) practice mode and B) test mode. In mode A), the user repeats motions to receive real time feedback using similarity based on body joint positions. Mode B) visualizes motion trajectories of the model and user to differentiate their motions. Our system also outputs advice for user's improvements such as adjusting motion timing. We conducted a series of experiments with an implemented prototype of the proposed method. Although our method's superiority was not clearly confirmed, we have found several advantages in our method. © 2022 ieee.

关键词： Deep learning

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Development of a visualization for Developers of a Distributed System Including Idle Computers

Development of a Visualization for Developers of a Distribut...

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ieee International conference on High Performance Computing and Communications (HPCC)

作者： Shosuke Tsutsumi Masayuki Higashinc Kenichi Takahashi Takao Kawamura Department of Engineering Tottori University Tottori Japan

This paper proposes a visualization function for developers in volunteer computing. In recent years, information systems such as e-Learning systems and groupware have been introduced in companies and educational institutions to promote DX, but the introduction and operation of these systems incur a large cost burden. Therefore, we are developing a distributed information system that can be introduced and operated at low cost by utilizing surplus computers (idle computers) in an organization. Idle computers are unstable depending on the operations of their original users and have different performances. In order to use idle computers efficiently, it is necessary to improve the performance of the system and modify it to add new functions, taking into account the differences in behavior and performance of each machine. In this paper, visualization for developers to easily check the behavior and performance of a computer in an idle state is developed, and its usefulness is evaluated through experiments using a real system.

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