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3rd International conference on Web Studies: Emergent of the Web in Multicultural Contexts, WS.3 2020

作者： Isaac, Carlos G Mexico

ISBN: (纸本)9781450388856

The tasks of judgment and criticism in cinema have been based predominantly on interpretive methods to establish their disciplinary mechanisms. Nowadays, the web's possibilities for supporting artificial intelligence, mathematics, and statistical computing techniques applied to the communication and humanities phenomena, such as the visual narrative arts, allows the development of new tools that aim at exploring the use of quantitative instrumentation for film analysis. Color grouping via K-Means Clustering and JavaScript based graphic visualization and data management, are procedures that web-based services can exploit for a quantitative film analysis. The methods discussed in this paper are examined under Miyazaki's animated films and shows a measurable relationship between the director's creative process and the perceptual dominant colors in the films. Furthermore, our proposed solution applies the combination and the exploration of such technologies for a web-based tool that helps researchers, scholars, filmmakers, and designers to gather color data from video media and to visualize them according to a 3D HSV/HSB graphical model. © 2020 ACM.

关键词： Color

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BDCAT 2019 - Proceedings of the 6th IEEE/ACM International conference on Big data Computing, Applications and Technologies

BDCAT 2019 - Proceedings of the 6th IEEE/ACM International C...

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6th IEEE/ACM International conference on Big data Computing, Applications and Technologies, BDCAT 2019

ISBN: (纸本)9781450370165

The proceedings contain 23 papers. The topics discussed include: rapid, progressive sub-graph explorations for interactive visual analytics over large-scale graph datasets;GPU acceleration of range queries over large data sets;going deeper or wider: throughput prediction for cluster tools with machine learning;accelerating machine learning I/O by overlapping data staging and mini-batch generations;cryptocurrency price prediction using time series and social sentiment data;an exploration of commuter travel time through social media analytics on the cloud;a simple and efficient federated recommender system;an analysis of slant in tweets: case study;and crowd-counting through a cascaded, multi-task convolutional neural network.

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analysis on the performance of VIO according to Trajectory Planning of UAV 20

Analysis on the performance of VIO according to Trajectory P...

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20th International conference on Control, Automation and Systems (ICCAS)

作者： Lee, EungChang Mason Myung, Hyun Korea Adv Inst Sci & Technol Sch Elect Engn KI AI KI R Daejeon 34141 South Korea

ISBN: (纸本)9788993215199

Recently, Unmanned Aerial Vehicles (UAVs) have been widely researched to accomplish tasks such as structural inspection, drone racing, and exploration of an unknown environment. To make the most of UAV and correctly estimate its pose with inexpensive and light-weight sensors such as Inertial Measurement Unit (IMU) and cameras, visual Inertial Odometry (VIO) has been intensively researched. There were a few analyses on the performance of VIO methods where only estimated pose error and utilization of the computing resources were considered. However, the performance of them according to trajectory planning was not treated. Trajectory planning can be one of the main reasons for the drift of localization from VIO since the sensors acquire the data at their sampling rates. In this paper, we analyze the performance of VIO on various trajectories that have different orders of polynomials for the desired position over time and hence different velocity, acceleration, and the first, second derivative of acceleration, using simulator which reflects the real dynamics of UAV. As a result, the higher the order of polynomial for trajectory, the better performance of VIO can be observed.

关键词： Indoor Navigation visual Inertial Odometry Unmanned Aerial Vehicle Trajectory Planning Control

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visual exploration of migration patterns in gull data

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INFORMATION visualIZATION 2019年第1期18卷 138-152页

作者： Konzack, Maximilian Gijsbers, Pieter Timmers, Ferry van Loon, Emiel Westenberg, Michel A. Buchin, Kevin TU Eindhoven POB 513 NL-5600 MB Eindhoven Netherlands Univ Amsterdam Amsterdam Netherlands

We present a visual analytics approach to explore and analyze movement data as collected by ecologists interested in understanding migration. Migration is an important and intriguing process in animal ecology, which may be better understood through the study of tracks for individuals in their environmental context. Our approach enables ecologists to explore the spatio-temporal characteristics of such tracks interactively. It identifies and aggregates stopovers depending on a scale at which the data is visualized. Statistics of stopover sites and links between them are shown on a zoomable geographic map which allows to interactively explore directed sequences of stopovers from an origin to a destination. In addition, the spatio-temporal properties of the trajectories are visualized by means of a density plot on a geographic map and a calendar view. To evaluate our visual analytics approach, we applied it on a data set of 75 migrating gulls that were tracked over a period of 3 years. The evaluation by an expert user confirms that our approach supports ecologists in their analysis workflow by helping to identifying interesting stopover locations, environmental conditions or (groups of) individuals with characteristic migratory behavior, and allows therefore to focus on visual data analysis.

关键词： visual analytics animal behavior data visualization spatio-temporal visualization geovisualization

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Research on visualization data of hotspots and development trend of domestic smart scenic spots 21

Research on visualization data of hotspots and development t...

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Proceedings of the 2021 4th International conference on E-Business, Information Management and Computer Science

作者： Yuanjing Zhang Wuhan Business University China

ISBN: (纸本)9781450395687

In this paper, Knowledge Map is used to make a visual analysis of 802 Chinese papers related to smart scenic spot research collected by CNKI, discuss the hot spots and development trends of smart scenic spot research in China. The research finds that the promotion of smart tourism policy plays a positive role in promoting the national smart tourism reform plan and realizing the establishment and implementation of smart tourism scenic spots in various regions, thus driving the growth of literature quantity. Nowdays the hotspots of smart tourism research in China focus on "smart scenic spots" "smart tourism" "scenic spot management" and "tourist attractions", with increasing heat. However, core authors and institutions published fewer papers, and their cooperation with each other was scattered, so no representative academic group was formed. At the same time, the cooperation of most research institutions in China is divided by regional scope, and trans-regional, cross-disciplinary and cross-institutional cooperation needs to be further strengthened. At present, domestic researches on smart scenic spots have gone deep into the practical application level, at the present stage, the development results are uneven, and the efficiency of production, education and research institutes is not obvious. In the future, the high-quality development of smart scenic spots still needs the exploration and deepening of scientific researchers.

关键词： Artificial intelligence

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Research on visual Programming System of Gesture Interaction Interface in VR 20

Research on Visual Programming System of Gesture Interaction...

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4th International conference on Big data and Internet of Things, BDIOT 2020

作者： Xiao, Wei-Ye Duan, Jun-Zou Xue, Cheng-Qi Dept.ID Southeast University Jiang-Su Province China Zhejiang University Zhe-jiang Province China

ISBN: (纸本)9781450375504

The emergence of virtual Reality(VR) has brought tremendous challenges to user interface(UI) design. The lack of a systematic summary of VR environment characteristics and UI models prevents us from developing mature design tools. This article intends to build a development system for VR interface based on gesture interaction and visual programming. Derived from a analysis of interface characteristics and interaction features in three-dimensional(3D) environment, an efficient UI development workflow is formed. This workflow can conveniently develop and debug the 3D interface in VR. The exploration of VR interface design methods in this article has important reference value for interface design in future. © 2020 ACM.

关键词： User interfaces

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Sentiment analysis as an Indicator to Evaluate Gender disparity on Sexual Violence Tweets in South Africa

Sentiment Analysis as an Indicator to Evaluate Gender dispar...

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International SAUPEC/RobMech/PRASA conference

作者： Imuede, Jude Raborife, Mpho Ranchod, Pravesh Univ Witwatersrand Sch Comp Sci & Appl Math Johannesburg South Africa Univ Johannesburg Sch Consumer Intelligence & Informat Syst Johannesburg South Africa

ISBN: (纸本)9781728141626

South Africa has one of the highest rates of sexual violence in the world, and with this technology era being the information age, it is not suprising that people are turning to social media to voice their views on this matter. As tweets on sexual violence grow continually, extracting insights from such data demands a robust, real-time, and scalable tools with flexibility in the database schema. Elasticsearch (ES) is an example of a free-license search engine written in Java and developed on Apache Lucene that meets the stated requirements. On the other hand, Kibana facilitates intuitive dashboard development, visual exploration, and real-time analysis of an index in ES through an intuitive graphical user interface. This study demonstrates how gender was inferred and evaluated through the integration of deep neural networks and Google's TensorFlow. We used the AFINN model to infer sentiment analysis as our measure of gender disparity in this instance. The Indexer, built of Node. js, and defined as the hub of the system connects with the Twitter streaming API to ingest tweets found within the boundaries of sexual violence. This system runs persistently with tweets through the ES search engine and visualised in Kibana.

关键词： Terms Twitter API Tweet Gender Sentiment analysis Sexual violence TensorFlow South Africa

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PolyVis: Cross-Device Framework for Collaborative visual data analysis

PolyVis: Cross-Device Framework for Collaborative Visual Dat...

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IEEE International conference on Systems, Man and Cybernetics (SMC)

作者： Alsaiari, Abeer Johnson, Andrew Nishimoto, Arthur Univ Illinois Elect Visualizat Lab Chicago IL 60607 USA

ISBN: (纸本)9781728145693

Multi device environments present new opportunities for collaborative visual data analysis and sense making by utilizing each device's strengths and capabilities. However, one of the associated challenges with visual data analysis in multi device environments is the sharing of visual components across devices. We present a framework developed on top of SAGE2 platform for cross-device collaborative visual data exploration. As part of our framework, we contribute the concept of rapid development and assembling of visualizations that can span multiple devices of different modalities. It provides the users with an environment for visualization compositions that delegate the rendering to the target device, allowing them to augment their large display workspace with portable devices for further exploration territories. Facilitated by its intuitive visualization composition pipeline, users with no programming skills such as data analysts can enhance their analytical scope with no coding barriers. We describe the framework, its implementation with a use case, and the rationale behind its design.

关键词： visualization

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A gaze-contingent system for foveated multiresolution visualization of vector and volumetric data

A gaze-contingent system for foveated multiresolution visual...

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2020 conference on visualization and data analysis, VDA 2020

作者： Ananpiriyakul, Thanawut Anghel, Joshua Potter, Kristi Joshi, Alark SnapLogic Amazon NREL United States USF Department of Computer Science University of San Francisco San FranciscoCA United States

Computational complexity is a limiting factor for visualizing large-scale scientific data. Most approaches to render large datasets are focused on novel algorithms that leverage cutting-edge graphics hardware to provide users with an interactive experience. In this paper, we alternatively demonstrate foveated imaging which allows interactive exploration using low-cost hardware by tracking the gaze of a participant to drive the rendering quality of an image. Foveated imaging exploits the fact that the spatial resolution of the human visual system decreases dramatically away from the central point of gaze, allowing computational resources to be reserved for areas of importance. We demonstrate this approach using face tracking to identify the gaze point of the participant for both vector and volumetric datasets and evaluate our results by comparing against traditional techniques. In our evaluation, we found a significant increase in computational performance using our foveated imaging approach while maintaining high image quality in regions of visual attention. © 2020, Society for Imaging Science and Technology.

关键词： Large dataset

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Educational big-data practice: A model for combining requirements and technologies 2nd

Educational big-data practice: A model for combining require...

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2nd International Cognitive Cities conference, IC3 2019

作者： Hsu, Sheng-Kuei Zhaoqing University Zhaoqing China

ISBN: (纸本)9789811561122

Institutional research (IR) has revealed the need for data processing in a university, and big-data technology can be regarded as a technical approach. The combination of the two methods can help universities introduce data-driven decision-making models. On the demand side of big-data processing on campus, we proposed three groups of university stakeholders—university, student, and society—with student learning outcomes as the main research topic. On the technical side, we proposed a data processing model from the perspective of big-data processing, including data gathering, pre-processing, storage and integration, analysis and exploration, and visual presentation. We applied the proposed learning outcomes and the big-data processing model to Tzu-Chi University, exploring student learning outcomes with big-data technology. In an initial experiment, this application model is feasible. Finally, we proposed several relevant conclusions to promote educational big-data research as a reference for related research. © Springer Nature Singapore Pte Ltd 2020.

关键词： Big data

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