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Correlation of OD Matrix and Traffic Volume with Functional data analysis: A Simulation-Based Case Study in the City of Portici

Correlation of OD Matrix and Traffic Volume with Functional ...

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International conference on Environment and Electrical Engineering (EEEIC)

作者： Alessandra Marisa Tascione Luca Di Costanzo Davide Forcina Luigi Pariota Christian Capezza Fulvio Simonelli Department of Civil Architectural and Environmental Engineering University of Naples “Federico II” Naples Italy

ISBN: (数字)9798350355185

ISBN: (纸本)9798350355192

This paper addresses the dynamic fluctuations within a single day of origin-destination (OD) flows and traffic volumes within urban networks, crucial for effective transportation planning and management. In an urban network, travel patterns are represented by two main variables: origin-destination (OD) flows and traffic volumes. The former (input of the assignment problem) are defined as the number of movements that occur between two points within the study area using transportation infrastructure, while the latter (output of the assignment problem) are defined as the number of vehicles crossing the transportation infrastructure within a given time interval. Traditional approaches encounter challenges due to the unobservability of OD flows and limitations in traffic data coverage and quality. Motivated by these limitations, we use a methodology based on functional data analysis with linear regression (FDA-1r), which enables the exploration of functional relationships between predictor (OD flow) and response (link volume). We present a case study in Portici, Italy, utilizing the FDA-1r methodology to analyze the correlation between OD flows and link flows. Results demonstrate the efficacy of the method in modeling the relationship between OD flows and link flows, providing valuable insights for urban traffic management. This paper contributes to advancing Intelligent Transportation Systems (ITS) services by addressing real-time OD matrix correction challenges.

关键词： Solid modeling Fluctuations Correlation Linear regression Urban areas Transportation Real-time systems Vectors Vehicle dynamics Testing

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15th International conference on Intelligent Robotics and Applications (ICIRA ) - Smart Robotics for Society

作者： Zhang, Xin Jiang, Yi Hou, Wensheng He, Jiayuan Jiang, Ning Chongqing Univ Bioengn Coll Chongqing 400044 Peoples R China Sichuan Univ West China Hosp Chengdu 610041 Peoples R China

ISBN: (纸本)9783031138225;9783031138218

With the aggravation of the aging society, the proportion of senior is gradually increasing. The brain structure size is changing with age. Thus, a certain of researchers focus on the differences in EEG responses or brain computer interface (BCI) performance among different age groups. Current study illustrated the differences in the transient response and steady state response to the motion checkerboard paradigm in younger group (age ranges from 22 to 30) and senior group (age ranges from 60 to 75) for the first time. Three algorithms were utilized to test the performance of the four-targets steady state motion visual evoked potential (SSMVEP) based BCI. Results showed that the SSMVEP could be clearly elicited in both groups. And two strong transient motion related components i.e., P1 and N2 were found in the temporal waveform. The latency of P1 in senior group was significant longer than that in younger group. And the amplitudes of P1 and N2 in senior group were significantly higher than that in younger group. For the performance of identifying SSMVEP, the accuracies in senior group were lower than that in younger group in all three data lengths. And extended canonical correlation analysis (extended CCA)-based method achieved the highest accuracy (86.39% +/- 16.37% in senior subjects and 93.96% +/- 5.68% in younger subjects) compared with CCA-based method and task-related component analysis-based method in both groups. These findings may be helpful for researchers designing algorithms to achieve high classification performance especially for senior subjects.

关键词： Age Brain-computer interface Steady state motion visual evoked potential Motion visual evoked potential Electroencephalogram

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Enabling Comparative analysis of Election data in Ecuador 21

Enabling Comparative Analysis of Election Data in Ecuador

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14th International Symposium on visual Information Communication and Interaction, VINCI 2021

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

ISBN: (纸本)9781450386470

We present an interactive visualization tool that enables exploration and comparative analyses of election data in multi-partisan systems. We motivate and explain our design in the context of the Ecuadorian political landscape. We demonstrate the tool with data from Ecuador's three most recent presidential elections. Our tool enables both relative and absolute comparisons of the election results. © 2021 Owner/Author.

关键词： data visualization

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EuroVis 2021 - 23rd Eurographics conference on visualization 2021

EuroVis 2021 - 23rd Eurographics Conference on Visualization...

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23rd Eurographics conference on visualization, EuroVis 2021

The proceedings contain 44 papers. The topics discussed include: VEHICLE: validation and exploration of the hierarchical integration of conflict event data;topography of violence: considerations for ethical and collaborative visualization design;color nameability predicts inference accuracy in spatial visualizations;what are table cartograms good for anyway? an algebraic analysis;exploring multi-dimensional data via subset embedding;guided stable dynamic projections;texture browser: feature-based texture exploration;local extraction of 3D time-dependent vector field topology;compressive neural representations of volumetric scalar fields;thin-volume visualization on curved domains;public data visualization: analyzing local running statistics on situated displays;accessible visualization: design space, opportunities, and challenges;learning contextualized user preferences for co-adaptive guidance in mixed-initiative topic model refinement;a visual designer of layer-wise relevance propagation models;and leveraging topological events in tracking graphs for understanding particle diffusion.

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visual analysis of Biomechanical of lower limbs in 2001-2020 based on VOSviewer

Visual analysis of Biomechanical of lower limbs in 2001-2020...

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2021 International conference on Health Big data and Smart Sports, HBDSS 2021

作者： Wei, Xinyi Chen, Qian Yang, Sijie Huang, Ruhao Sport and Health School Nanjing Sport Institute Nanjing China SuqianZeda Vocational College Suqian China Hunan Normal University Changsha China

ISBN: (纸本)9781665421881

Taking WOS (web of Science) as the retrieval platform, the retrieval time is from 2001 to 2021. 2180 English core journals on lower limbs biomechanics in recent 20 years are visually included by using "vosviewer1.6.17". By analyzing the existing research literature, the number of papers, research countries and key words related to lower limb biomechanics are sorted and summarized hope to understand the current research situation and judge the future research trend, so as to provide reference for further *** is a commonly used visual analysis software, but there are few related analyses on lower limb biomechanics. It is found that in the past two decades, the exploration in related fields has been deepening, among which the United States, Britain and Australia are the active countries with more research in this field, and coordination, speed, model are the most popular words, which reflect the current research trend. © 2021 IEEE.

关键词： Biomechanics

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exploration of Spatial and Temporal Modeling Alternatives for HOI

Exploration of Spatial and Temporal Modeling Alternatives fo...

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IEEE Winter conference on Applications of Computer Vision (WACV)

作者： Dabral, Rishabh Sarkar, Srijon Reddy, Sai Praneeth Ramakrishnan, Ganesh Indian Inst Technol Dept Comp Sci Mumbai Maharashtra India

ISBN: (纸本)9780738142661

Human-Object Interaction detection from a video clip can be considered as a special case of video-based visual-Relationship Detection wherein the subject must be a human. Specifically, it involves detecting the humans and objects in the clip as well as the interactions between them. Conventionally, the problem has been formulated as a space-time graph inference problem over the video clip features. In this work, we explore alternate spatial approaches for detecting Human-Object Interactions. We consider a hierarchical setup that decouples spatial and temporal aspects of the problem and analyse the impacts of a variety of design choices for the spatial networks. Particularly, to capture spatial relationships in the scene, we analyze the effectiveness of the traditionally used Graph Convolutional Networks against Convolutional Networks and Capsule Networks. Unlike current approaches, we avoid using ground truth data like depth maps or 3D human pose during inference, thus increasing generalization across non-RGBD datasets as well. We demonstrate a comprehensive analysis of the exploration, both quantitatively and qualitatively, while achieving state-of-the-art results in human-object interaction detection (88.9% and 92.6%) and anticipation tasks of CAD-120 and competitive results on image based HOI detection in V-COCO dataset, setting a new benchmark for visual features based approaches.

关键词： visualization Computer vision Three-dimensional displays conferences Pipelines Benchmark testing Feature extraction

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Audio Perception in Robotic Assistance for Human Space exploration: A Feasibility Study

Audio Perception in Robotic Assistance for Human Space Explo...

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IEEE conference on Aerospace

作者： Marco Sewtz Werner Friedl Adrian Bauer Anne Köpken Florian Lay Nicolai Bechtel Peter Schmaus Rudolph Triebel Neal Y. Lii German Aerospace Center (DLR) Institut of Robotics and Mechatronics Weßling Germany

Future crewed missions beyond low earth orbit will greatly rely on the support of robotic assistance platforms to perform inspection and manipulation of critical assets. This includes crew habitats, landing sites or assets for life support and operation. Maintenance and manipulation of a crewed site in extra-terrestrial environments is a complex task and the system will have to face different challenges during operation. While most may be solved autonomously, in certain occasions human intervention will be required. The telerobotic demonstration mission, Surface Avatar, led by the German Aerospace Center (DLR), with partner European Space Agency (ESA), investigates different approaches offering astronauts on board the International Space Station (ISS) control of ground robots in representative scenarios, e.g. a Martian landing and exploration site. In this work we present a feasibility study on how to integrate auditory information into the mentioned application. We will discuss methods for obtaining audio information and localizing audio sources in the environment, as well as fusing auditory and visual information to perform state estimation based on the gathered data. We demonstrate our work in different experiments to show the effectiveness of utilizing audio information, the results of spectral analysis of our mission assets, and how this information could help future astronauts to argue about the current mission situation.

关键词： visualization European Space Agency Low earth orbit satellites Inspection International Space Station Space exploration Task analysis

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Visitors Vis: Interactive Mining of Suspected Medical Insurance Fraud Groups 18th

Visitors Vis: Interactive Mining of Suspected Medical Insura...

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18th CCF conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2023

作者： Dong, Rixin Liu, Hanlin Guo, Xu Zhou, Jiantao College of Computer Science Inner Mongolia University Hohhot China National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolia Hohhot China Engineering Research Center of Ecological Big Data Ministry of Education Hohhot China Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Hohhot China Inner Mongolia Key Laboratory of Social Computing and Data Processing Hohhot China Inner Mongolia Key Laboratory of Discipline Inspection and Supervision Big Data Hohhot China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Hohhot China

ISBN: (纸本)9789819996360

As medical insurance continues to grow in size, the losses caused by medical insurance fraud cannot be underestimated. Current data mining and predictive techniques have been applied to analyze and explore the health insurance fraud population. However, previous studies only provide summary results and do not show the details of comparative analysis during the visit, resulting in the inability of auditors to quickly identify anomalous behavior. In this paper, we propose a visual analytics system for interactive medical insurance fraud detection to support the exploration and interpretation of different access processes. We propose a weighted MinDL to improve the accuracy of visit pattern classification in the time-series modeling process, and design a data analysis model and visual analysis view based on medical insurance fraud characteristics to reveal and explore the characteristics of medical insurance fraud groups. We collaborate with related organizations to design and implement an interactive visualization for medical insurance fraud group detection using real Medicare data and expert interviews The system is effective and practical in detecting and analyzing medical insurance fraud syndicates. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Health insurance

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16th International Joint conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 12th International conference on Information visualization Theory and Applications (IVAPP)

作者： Jekic, Nikolina Mutlu, Belgin Schreyer, Manuela Neubert, Steffen Schreck, Tobias Pro2Future GmbH Inffeldgasse 25f A-8010 Graz Austria AMAG Austria Metall AG Lamprechtshausener Str 61 A-5282 Ranshofen Austria Graz Univ Technol Inst Comp Graph & Knowledge Visualisat Inffeldgasse 16c A-8010 Graz Austria Graz Univ Technol Inst Interact Syst & Data Sci Inffeldgasse 16c A-8010 Graz Austria

ISBN: (纸本)9789897584886

Monitoring, analyzing and determining the production quality in a complex and long-running process such as in the aluminum production is a challenging task. The domain experts are often overwhelmed by the flood of data being generated and collected and have difficulties to analyze and interpret the results. Likewise, experts find it difficult to identify patterns in their data that may indicate deviations and anomalies that lead to unstable processes and lower product quality. We aim to support domain experts in the production data exploration and identifying meaningful patterns. The existing research covers a broad spectrum of pattern recognition methodologies that can be potentially applied to elicit patterns in data collected from industrial production. Hence, in this paper, we further analyze the applicability of different similarity measures to effectively recognize specific ultrasonic patterns which may indicate critical process deviations in aluminum production.

关键词： Similarity Measures visual analysis Aluminum Casting

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CNN Based Model for Underwater Image Classification and Enhancement

CNN Based Model for Underwater Image Classification and Enha...

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Advances in Modern Age Technologies for Health and Engineering Science (AMATHE), International conference on

作者： Sahit Jamandlamudi Deva Priya Isravel Julia Punitha Malar Dhas Division of Data Science and Cyber Security Karunya Institute of Technology and Sciences Coimbatore India Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

The challenge of enhancing underwater images is difficult because of several issues, including color distortion, inadequate illumination, and dispersion from suspended particles in the water. Conventional picture enhancing methods frequently find it difficult to resolve these problems. Thanks to its ability to learn intricate representations and pick up on minute features, deep learning has become a potent tool for picture improvement tasks in recent years. In this work, we suggest a novel deep learning-based method for improving underwater images. To automatically learn and improve the visual quality of underwater scenes, we use a convolutional neural network architecture that is specifically made to handle underwater photos. A sizable dataset of underwater photos is used to train the network, with an emphasis on contrast improvement and color correction. We compare our method with many state-of-the-art techniques and undertake extensive tests on a benchmark dataset to evaluate our approach. The outcomes show that our strategy performs much better than current approaches both in terms of subjective visual quality and objective criteria. Our technique improves visibility, minimizes noise, and successfully restores colors in underwater photos. By presenting a deep learning-based method that enhances the visual quality of underwater photographs, this work advances the field of underwater image processing and aids in marine research, underwater exploration, and surveillance.

关键词： Deep learning visualization Adaptation models Image color analysis Surveillance Lighting Distortion

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