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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

共 2461 条记录，以下是311-320 订阅

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Understanding the Effects of visualizing Missing Values on visual data exploration

Understanding the Effects of Visualizing Missing Values on V...

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IEEE visualization conference (IEEE VIS)

作者： Song, Hayeong Fu, Yu Saket, Bahador Stasko, John Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781665433358

When performing data analysis, people often confront data sets containing missing values. We conducted an empirical study to understand the effect of visualizing those missing values on participants' decision-making processes while performing a visual data exploration task. More specifically, our study participants purchased a hypothetical portfolio of stocks based on a data set where some stocks had missing values for attributes such as PE ratio, beta, and EPS. The experiment used scatterplots to communicate the stock data. For one group of participants, stocks with missing values simply were not shown, while the second group saw such stocks depicted with estimated values as points with error bars. We measured participants' cognitive load involved in decision-making with data with missing values. Our results indicate that their decision-making workflow was different across two conditions.

关键词： Human-centered computing visualization Empiriacal evaluation Missing data

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Pheno-Mapper: An Interactive Toolbox for the visual exploration of Phenomics data 21

Pheno-Mapper: An Interactive Toolbox for the Visual Explorat...

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12th ACM conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)

作者： Zhou, Youjia Kamruzzaman, Methun Schnable, Patrick Krishnamoorthy, Bala Kalyanaraman, Ananth Wang, Bei Univ Utah Salt Lake City UT 84112 USA Univ Virginia Charlottesville VA USA Iowa State Univ Ames IA USA Washington State Univ Vancouver WA USA

ISBN: (纸本)9781450384506

High-throughput technologies to collect field data have made observations possible at scale in several branches of life sciences. The data collected can range from the molecular level (genotypes) to physiological (phenotypic traits) and environmental observations (e.g., weather, soil conditions). These vast swathes of data, collectively referred to as phenomics data, represent a treasure trove of key scientific knowledge on the dynamics of the underlying biological system. However, extracting information and insights from these complex datasets remains a significant challenge owing to their multidimensionality and lack of prior knowledge about their complex structure. In this paper, we present Pheno-Mapper, an interactive toolbox for the exploratory analysis and visualization of large-scale phenomics data. Our approach uses the mapper framework to perform a topological analysis of the data, and subsequently render visual representations with built-in data analysis and machine learning capabilities. We demonstrate the utility of this new tool on real-world plant (e.g., maize) phenomics datasets. In comparison to existing approaches, the main advantage of Pheno-Mapper is that it provides rich, interactive capabilities in the exploratory analysis of phenomics data, and it integrates visual analytics with data analysis and machine learning in an easily extensible way. In particular, Pheno-Mapper allows the interactive selection of subpopulations guided by a topological summary of the data and applies data mining and machine learning to these selected subpopulations for in-depth exploration.

关键词： phenomics topological data analysis interactive visualization multidimensional biological data

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visual Analytics for Industrial Sensor data analysis 23

Visual Analytics for Industrial Sensor Data Analysis

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23rd International conference on Enterprise Information Systems (ICEIS)

作者： Langer, Tristan Meisen, Tobias Univ Wuppertal Chair Technol & Management Digital Transformat Rainer Gruenter Str 21 D-42119 Wuppertal Germany

ISBN: (纸本)9789897585098

Due to the increasing digitalization of production processes, more and more sensor data is recorded for subsequent analysis in various use cases (e.g. predictive maintenance). The analysis and utilization of this data by process experts raises optimization potential throughout the production process. However, new analysis methods are usually first published as non-standardized Python or R libraries and are therefore not available to process experts with limited programming and data management knowledge. It often takes years before those methods are used in ERP, MES and other production environments and the optimization potential remains idle until then. In this paper, we present a visual analytics approach to facilitate the inclusion of process experts into analysis and utilization of industrial sensor data. Based on two real world exemplary use cases, we define a catalog of requirements and develop a tool that provides dedicated interactive visualizations along methods for exploration, clustering and labeling as well as classification of sensor data. We then evaluate the usefulness of the presented tool in a qualitative user study. The feedback given by the participants indicates that such an approach eases access to data analysis methods but needs to be integrated into a comprehensive data management and analysis process.

关键词： Time Series analysis Industrial Sensor data visual Analytics Analytic Provenance

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The Construction of a visual Quantum Interactive System for Fuzzy Evaluation of Financial Budget Performance based on Big data 6

The Construction of a Visual Quantum Interactive System for ...

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6th International conference on Computing Methodologies and Communication, ICCMC 2022

作者： Wei, Yong Yunnan Grain Industry Group Co. LTD Kunming650000 China

ISBN: (纸本)9781665410281

This paper proposes a new fuzzy evaluation system of financial budget performance based on big data. Based on the characteristics of budget security and efficiency, this paper constructs a four-layer indicator system: target layer, category layer, indicator layer and sub-indicator layer. In the weight analysis and index calculation, a new comprehensive fuzzy evaluation operator including a master-slave multiplication operator and a 0-1 multiplication operator is proposed. Combined with the fuzzy analytic hierarchy process, a multi-operator analytic hierarchy fuzzy evaluation model and corresponding solution method are established. Finally, combined with the visualization of quantum interaction, an exploratory conversation search model based on quantum interference is proposed. In the non-classical correlation judgment theory exploration part, it is pointed out that users have a certain quantum interaction system in the process of correlation judgment. © 2022 IEEE.

关键词： Big data

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LegisLatio: A visualization Tool for Legislative Roll-call Vote data 22

LegisLatio: A visualization Tool for Legislative Roll-call V...

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15th International Symposium on visual Information Communication and Interaction, VINCI2022

作者： Méndez, Gonzalo Gabriel Moreno, Oscar Mendoza, Patricio Escuela Superior Politécnica Del Litoral Guayaquil Ecuador

ISBN: (纸本)9781450398077

Appropriate communication and understanding of political data are key to achieve a healthy dialogue between civil society and political institutions. This is particularly important for data generated by bodies that most directly represent citizens, such as congresses, senates, parliaments, and other forms of legislatures. visualization tools have the potential to support the exploration and understanding of such data and make it more accessible and appealing to the general public. With this vision, we present LegisLatio, an interactive visualization tool that enables open-ended analysis of legislative roll-call vote data from multi-party electoral systems. We describe the design of the tool and illustrate its effectiveness with data generated by the Ecuadorian legislature. We also discuss the findings of a qualitative observation that hints at LegisLatio's potential to promote citizen engagement and participation. © 2022 ACM.

关键词： data visualization

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Localization of Emotion via EEG analysis using 3D Trilateration 25

Localization of Emotion via EEG Analysis using 3D Trilaterat...

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25th International conference Information visualisation (iv) - AI and visual Analytics and data Science

作者： Blaiech, Hayfa Liouane, Noureddine Saafi, Mohamed Ali Natl Engn Sch Monastir ENIM Tunisia Lab Automat Signal & Image Proc LARATSI Monastir Tunisia Neurologist Hosp Sahloul Sousse Tunisia

ISBN: (纸本)9781665438278

Localization of cerebral electrical activity of emotional states on the basis of electrophysiological recordings is an important area of investigation in recent years. This field was explored to locate the sources of the emotions in the cortex. The theory that every emotion can have a unique trigger center in the cortex was followed. A precise and accurate method was used, the Trilateration, recognized in the GPS networks, which deduces the points of interest from the distances. This method gave the exact coordinates of the generating points of emotions in the surface area of cortex under the influence of modulating thalamic nuclei. It was found that the energies are stronger in the occipital and parietal part of the brain. Moreover the frontal part plays the role of inhibitor and stimulator of emotions.

关键词： Trilateration Localization EEG signals Emotion

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6th Iberian Robotics conference, Robot 2023

6th Iberian Robotics Conference, Robot 2023

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6th Iberian Robotics conference, Robot 2023

ISBN: (纸本)9783031586750

The proceedings contain 90 papers. The special focus in this conference is on Iberian Robotics. The topics include: Map Merge and Accurate Localization in Multi-robot Systems in Real Environments;category Theory for Autonomous Robots: The Marathon 2 Use Case;Development of a Low-Cost 3D Mapping Technology with 2D LIDAR for Path Planning Based on the A* Algorithm;synPhoRest - A Procedural Generation Tool of Synthetic Photorealistic Forest datasets;Evaluation of Point Cloud data Augmentation for 3D-LiDAR Object Detection in Autonomous Driving;Green Deep Learning: Comparative Study of Road Object Detectors Between Jetson Boards and PC;Exploring Domain Adaptation with Depth-Based 3D Object Detection in CARLA Simulator;improving Energy Performance of Camera Lidar Fusion by Intermittent Human Detection for Social Navigation;visual Tracking of Synthetic Space Platforms in Low Orbit Using International Space Station Video Stream and Rendered Earth Model;driver Activity Recognition by Fusing Multi-object and Key Points Detection;cross-View Generalisation in Action Recognition: Feature Design for Transitioning from Exocentric To Egocentric Views;assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation;A Feasibility Study of a Leader-Follower Multi-robot Formation for TDLAS Assisted Methane Detection in Open Spaces;studying Exploitation and exploration Trade-Off of Cognitive Odour-Guided Search;Performance analysis of ORB-SLAM in Foggy Environments;socially Reactive Navigation Models for Mobile Robots in Dynamic Environments;human Motion Trajectory Prediction Using the Social Force Model for Real-Time and Low Computational Cost Applications;DeepRL-Based Robot Local Motion Planning in Unknown Dynamic Indoor Environments;parallel Curves Path Planning Based on Tangent Segments to Concentric Circles;fuzzy Logic Based Decision-Making for Urban Platooning on Urban Roundabout Scenarios;fast Tunnel Traversal for Ground Vehicles by Bearing Estimation with Neura

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6th Iberian Robotics conference, Robot 2023

6th Iberian Robotics Conference, Robot 2023

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6th Iberian Robotics conference, Robot 2023

ISBN: (纸本)9783031591662

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Preprocessing and visualisation of dataset for Neonatal Sepsis Prediction Using MIMIC-iv

Preprocessing and Visualisation of Dataset for Neonatal Seps...

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visual Analytics and data visualization (ICVADV), International conference on

作者： Madhura Devendra Ranade Dept. of Electronics Engineering SVKM's Shri Bhagubhai Mafatlal Polytechnic and College of Engineering Mumbai India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

This paper aims at exploring MIMIC-iv dataset for extraction for neonatal patients diagnosed with “Septicemia [sepsis] of newborn”. The term neonate is used for newborn babies less than four weeks old. Medical Information Mart for Intensive Care version 4 (MIMIC-iv) is a large, open access electronic health record database having more than 3 lakhs patients' data. The main objective of this paper is to access and filter this database using Google Big query. The Neonatal Sepsis is one of the reasons affecting neonatal mortality. Neonatal mortality reduction is one of the goal for sustainable development as mentioned by World Health Organization. This paper serves as the first step in identifying trends from the neonatal records from MIMIC dataset thereby paving away for creation of Sepsis prediction dataset and feature extraction. This paper deals with assessing the combined effect of various modules available in MIMIC database such as patient's demographic information, admission and diagnosis related details. It was found that there were total 96564 entries with sepsis diagnosis out of which 42.3 % were females and 57.7% were male neonates. The highest number of neonates diagnosed with Sepsis were of “White” ethnicity. The highest number of neonates were prescribed to perform “Blood Culture Neonate” test. The majority of neonates were found to have micro-organism named “Staph Aureus Coag+” in their body. This paper successfully concludes that the exploratory analysis of neonates with sepsis would be a foundation step in developing the neonatal sepsis prediction model using machine learning techniques.

关键词： Pediatrics Microorganisms databases MIMICs data visualization Mortality Predictive models Sepsis Market research Internet

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VarCopy: a visual Exploratory data analysis Platform for Copy Number Variation Studies 24

VarCopy: a Visual Exploratory Data Analysis Platform for Cop...

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24th International conference Information visualisation (iv)

作者： Bove, Fabio Mandreoli, Federica Martoglia, Riccardo Pisi, Valentino Taccioli, Cristian Vischioni, Chiara Univ Modena & Reggio Emilia FIM Modena Italy Univ Padua MAPS Padua Italy

ISBN: (纸本)9781728191348

The study of such a complex phenomenon as cancer, which depends on several but unexplored and unclear factors, needs new ways to visualize, analyze and combine different data both on species characteristics and genes function. To this respect, we propose a novel platform, named VarCopy, supporting visual Exploratory data analysis (EDA) in the context of Copy Number Variation (CNV) data. The platform will be publicly available as a web application soon, and is, to our best knowledge, the first tool allowing visual, interactive exploration and analysis of the CNV landscape of multiple species, allowing the identification of new target genes that might be useful for biomedical research.

关键词： Copy Number Variations interactive visualization Exploratory data analysis scalable data science data analysis models

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