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Electrodermal activity as an indicator of challenging road sections

JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES 2025年 94卷

作者： Sudrychova, Izabela Tomaszek, Lukas Saloun, Petr Miklosikova, Miroslava Janosik, Ladislav VSB Tech Univ Ostrava 17 Listopadu 15 Ostrava 70800 Czech Republic Palacky Univ Olomouc Krizkovskeho 8 Olomouc 77900 Czech Republic

The increasing traffic raises demands for road safety, both active and passive. One way to enhance safety is by detecting challenging sections on roads and alerting drivers accordingly. In this article, we focus on identifying challenging sections of a training course by measuring electrodermal activity and heart rate while driving afire truck. The results demonstrate that skin conductance measurements and heart rate can indicate areas where drivers are less attentive and also highlight spots that pose challenges to drivers. These findings can be utilized to detect difficult sections and preempt accidents by making necessary adjustments.

关键词： Electrodermal activity Heart rate Driving Challenging road sections visual data analysis

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A Space-Filling Multidimensional visualization (SFMDVis) for Exploratory data analysis

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INFORMATION SCIENCES 2017年 390卷 32-53页

作者： Huang, Tze-Haw Huang, Mao Lin Quang Vinh Nguyen Zhao, Laiping Huang, Weidong Chen, Jinjun Univ Technol Sydney Sch Software FEIT POB 123 Broadway NSW 2007 Australia Univ Western Sydney Locked Bag 1797 South Penrith Dc NSW 1797 Australia Tianjin Univ Sch Comp Software China 92 Weijin Rd Tianjin Peoples R China Univ Tasmania Sch Engn & ICT Newnham Tas 7248 Australia

The space-filling visualization model was first invented by Ben Shneiderman [28] for maximizing the utilization of display space in relational data (or graph) visualization, especially for tree visualization. It uses the concept of Enclosure which dismisses the "edges" in the graphic representation that are all too frequently used in traditional node-link based graph visualizations. Therefore, the major issue in graph visualization which is the edge crossing can be naturally solved through the adoption of a space filling approach. However in the past, the space-filling concept has not attracted much attention from researchers in the field of multidimensional visualization. Although the problem of 'edge crossing' has also occurred among polylines which are used as the basic visual elements in the parallel coordinates visualization, it is problematic if those 'edge crossings' among polylines are not evenly distributed on the display plate as visual clutter will occur. This problem could significantly reduce the human readability in terms of reviewing a particular region of the visualization. In this study, we propose a new Space-Filling Multidimensional data visualization (SFMDVis) that for the first-time introduces a space-filling approach into multidimensional data visualization. The main contributions are: (1) achieving the maximization of space utilization in multidimensional visualization (i.e. 100% of the display area is fully used), (2) eliminating visual clutter in SFMDVis through the use of the non-classic geometric primitive and (3) improving the quality of visualization for the visual perception of linear correlations among different variables as well as recognizing data patterns. To evaluate the quality of SFMDVis, we have conducted a usability study to measure the performance of SFMDVis in comparison with parallel coordinates and a scatterplot matrix for finding linear correlations and data patterns. The evaluation results have suggested that the accuracy

关键词： Multidimensional data visualization Space-filling data visualization visual data analysis Linear correlation data pattern Usability study

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Quantitative data graphics in 3D desktop-based virtual environments-an evaluation

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International Journal of Digital Earth 2015年第8期8卷 623-639页

作者： Susanne Bleisch Jason Dykes Geomatics Engineering FHNW University of Applied Sciences and Arts Northwestern SwitzerlandMuttenzSwitzerland giCentre City University LondonLondonUK

3D desktop-based virtual environments provide a means for displaying quantitative data in *** that are inherently spatial in three dimensions may benefit from visual exploration and analysis in relation to the environment in which they were collected and to which they *** empirically evaluate how effectively and efficiently such data can be visually analyzed in relation to location and landform in 3D versus 2D *** two experiments,participants performed visual analysis tasks in 2D and 3D visualizations and reported insights and their confidence in *** results showed only small differences between the 2D and 3D visualizations in the performance measures that we evaluated:task completion time,confidence,complexity,and insight ***,we found differences for different datasets and settings suggesting that 3D visualizations or 2D representations,respectively,may be more or less useful for particular datasets and contexts.

关键词： 3D geovisualization quantitative data graphics visual data analysis empirical evaluation

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Left, Right, and Gender: Exploring Interaction Traces to Mitigate Human Biases

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2022年第1期28卷 966-975页

作者： Wall, Emily Narechania, Arpit Coscia, Adam Paden, Jamal Endert, Alex Emory Univ Atlanta GA 30322 USA Georgia Tech Atlanta GA USA

Human biases impact the way people analyze data and make decisions. Recent work has shown that some visualization designs can better support cognitive processes and mitigate cognitive biases (i.e., errors that occur due to the use of mental "shortcuts"). In this work, we explore how visualizing a user's interaction history (i.e., which data points and attributes a user has interacted with) can be used to mitigate potential biases that drive decision making by promoting conscious reflection of one's analysis process. Given an interactive scatterplot-based visualization tool, we showed interaction history in real-time while exploring data (by coloring points in the scatterplot that the user has interacted with), and in a summative format after a decision has been made (by comparing the distribution of user interactions to the underlying distribution of the data). We conducted a series of in-lab experiments and a crowd-sourced experiment to evaluate the effectiveness of interaction history interventions toward mitigating bias. We contextualized this work in a political scenario in which participants were instructed to choose a committee of 10 fictitious politicians to review a recent bill passed in the U.S. state of Georgia banning abortion after 6 weeks, where things like gender bias or political party bias may drive one's analysis process. We demonstrate the generalizability of this approach by evaluating a second decision making scenario related to movies. Our results are inconclusive for the effectiveness of interaction history (henceforth referred to as interaction traces) toward mitigating biased decision making. However, we find some mixed support that interaction traces, particularly in a summative format, can increase awareness of potential unconscious biases.

关键词： Measurement Decision making Task analysis data visualization visualization History Motion pictures Human bias bias mitigation decision making visual data analysis

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Mixed-type distribution plots

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INFORMATION visualIZATION 2019年第3期18卷 311-317页

作者： Weld, Christopher Leemis, Lawrence Coll William & Mary Dept Appl Sci POB 8795 Williamsburg VA 23187 USA Coll William & Mary Dept Math Williamsburg VA 23185 USA

Plotting is among the most effective ways to quickly and accurately describe a probability distribution. It makes often complex information accessible, enabling intuition for respective outcomes at a glance. Matters complicate, however, for mixed-type distributions. Mixed-type distributions contain both continuous and discrete components, and accurately portraying those on a single axis can prove difficult-misleading intuition as a consequence of pulling two otherwise disjoint components into focus together. This article examines the challenges of maintaining the simple, concise, and accurate format of traditional probability distribution plots for mixed-type distributions. We illustrate issues arising within this plot classification paradigm, and why a secondary axis is uniquely suited to improve its communication. An algorithm is devised to consistently scale such plots so that they better coincide with intuition. National Football League football starting field position, meteorological data, and financial instruments provide examples demonstrating effectiveness of this plot technique.

关键词： Algorithms data analysis data visualization graphical perception multidimensional scaling plots statistical graphics visual data analysis

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Spatio-temporal convolutional residual network for regional commercial vitality prediction

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第19期81卷 27923-27948页

作者： Yu, Dongjin Wang, Xinfeng Liang, Ping Sun, Xiaoxiao Hangzhou Dianzi Univ Sch Comp Sci & Technol Hangzhou 310018 Peoples R China

The vitality of commercial entities reflects the business condition of their surrounding area, the prediction of which helps identify the trend of regional development and make investment decisions. The indicators of business conditions, like revenues and profits, can be employed to make a prediction beyond any doubt. Unfortunately, such figures constitute business secrets and are usually publicly unavailable. Thanks to the rapid growing of location based social networks such as Yelp and Foursquare, massive amount of online data has become available for predicting the vitality of commercial entities. In this paper, a Spatio-Temporal Convolutional Residual Neural Network (STCRNN) is proposed for regional commercial vitality prediction, based on public online data, such as reviews and check-ins from mobile apps. Firstly, a commercial vitality map is built to indicate the popularity of business entities. Afterwards, a local convolutional neural network is employed to capture the spatial relationship of surrounding commercial districts on the vitality map. Then, a 3-dimension convolution is applied to deal with both recent and periodic variations, i.e., the sequential and seasonal changes of commercial vitality. Finally, long short-term memory is introduced to synthesize these two variations. In particular, a residual network is used to eliminate gradient vanishing and exploding, caused by the increase of depth of neural networks. Experiments on public Yelp datasets from 2013 to 2018 demonstrate that STCRNN outperforms the current methods in terms of mean square error.

关键词： Commercial vitality prediction Commercial district Spatio-temporal analysis Convolutional neural network Residual network visual data analysis Yelp

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An eddy current approach to the detection of damage caused by low-energy impacts on carbon fibre reinforced materials

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MATERIALS & DESIGN 1995年第3期16卷 167-173页

作者： Gros, XE ROBERT GORDON UNIV SCH COMP & MATH SCIABERDEEN AB1 1HGSCOTLAND

The combination of high strength, high stiffness and low weight, compared to more conventional materials, has contributed to the increasing use of carbon fibre reinforced polymer (CFRP) composites in the aerospace industry. However, the structural integrity and the airworthiness of an aircraft can be severely affected by low-energy impacts. In order to ensure the quality standards of a component and safety level of a vehicle, these impacts need to be unambiguously detected and characterized. Several non-destructive testing methods have been developed for the inspection of composites. This paper presents experimental results of an eddy current non-destructive examination (NDE) of CFRP helicopter panels and discusses the use of visual data analysis (VDA) for rapid defect location and quantification. The performance of eddy current testing of CFRP composites, assessed using a probability of detection (POD) analysis approach, is also described.

关键词： impact damage carbon fibre reinforced composites non-destructive examination eddy current testing visual data analysis

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An exploratory analysis of COVID-19 vaccination administration

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PROCEEDINGS OF THE INDIAN NATIONAL SCIENCE ACADEMY 2022年第1期88卷 43-52页

作者： Rathinasamy, Muthusami Kandhasamy, Saritha Dr Mahalingam Coll Engn & Technol Dept Comp Applicat Pollachi Tamil Nadu India PA Coll Engn & Technol Dept Math Pollachi Tamil Nadu India

The goal of this research is to analyze data on vaccinations, vaccination administration, and forecasting vaccination rates on a country-by-country basis for the general public, policymakers, vaccine manufacturers, national governments, and international governments to better understand the current state of COVID-19 vaccination. In this study, two public datasets were used: the Johns Hopkins University coronavirus 2019 dataset and Our World in data - Coronavirus Pandemic dataset. With datasets, two approaches have been used: visual data analysis for COVID-19 vaccine administration and the autoregressive integrated moving average (ARIMA) model for forecasting vaccination rates. The findings confirm that Oxford/AstraZeneca is the top vaccine used across the globe with 26.54%, the United States is the top in vaccination, with 277,290,173, India is the top in number of daily vaccinations with 3.659357M, and in total vaccinations per hundred people, the United States has the highest count with 82.91, among the top five countries. It is also estimated that the vaccination rate in the United States will reach almost 60%, while India, Brazil, France, and Turkey will reach about 15%, 28%, 60%, and 23%, respectively, in the following 50 days beginning 20 May 2021. This exploratory study of COVID-19 vaccination data was carried out to effectively show the current state of COVID-19 vaccine administration and to anticipate vaccination rates in the United States, India, Brazil, France, and Turkey.

关键词： COVID-19 Infectious disease Coronavirus vaccinations visual data analysis Forecasting vaccination rate Public health

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Highlighting space-time patterns: Effective visual encodings for interactive decision-making

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2007年第8期21卷 879-893页

作者： Sips, M. Schneidewind, J. Keim, D. A. Stanford Univ Stanford CA 94305 USA Univ Konstanz D-78457 Constance Germany

The research reported in this paper focuses on integrating analytical and visual methods in order to explore complex patterns in geo-related multivariate data sets and to understand the changes in patterns over time. The goal is to provide techniques that are able to analyse real-world data Warehouses, a typical architecture to manage such geo-related multidimensional data sets, in order to support the analyst's decision-making process. Challenges arise because realworld applications usually have to deal with millions of records, with dozens of dimensions, and spatio-temporal context. Therefore, a tight integration of automated analysis and interactive visualizations is needed (as proposed in the context of visual Analytics). Our approach uses the well-studied capabilities provided by data Warehouses supporting knowledge discovery and decision making to analyse spatio-temporal behaviour of pattern in high-dimensional spaces. The topic of the paper is to show possible interplays between automated analysis and geo-spatial visualization.

关键词： visual data analysis data warehouse space-time pattern

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You get by with a little help:The effects of variable guidance degrees on performance and mental state

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visual Informatics 2019年第4期3卷 177-191页

作者： Davide Ceneda Theresia Gschwandtner Silvia Miksch TU Wien Faculty of InformaticsInstitute of Visual Computing&Human-Centered TechnologyFavoritenstrasse 9-11/193A-1040 ViennaAustria

Since it can be challenging for users to effectively utilize interactive visualizations,guidance is usually provided to assist users in solving *** is mentioned as an effective mean to overcome stall situations occurring during the ***,the effectiveness of a peculiar guidance solution usually varies for different analysis *** same guidance may have different effects on users with(1)different levels of *** choice of the appropriate(2)degree of guidance and the type of(3)task under consideration also affect the positive or negative outcome of providing *** these three factors,we conducted a user study to investigate the effectiveness of variable degrees of guidance with respect to the user’s previous knowledge in different analysis *** results shed light on the appropriateness of certain degrees of guidance in relation to different tasks,and the overall influence of guidance on the analysis outcome in terms of user’s mental state and analysis performance.

关键词： Guidance User study Knowledge Trust Mixed-initiative visual data analysis

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