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visualization analysis of research hotspots and development trends of technological innovation efficiency based on COOC 2

Visualization analysis of research hotspots and development ...

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2nd International conference on Electronic Information Engineering, Big data, and Computer Technology, EIBDCT 2023

作者： Han, Changjuan Cao, Shikui School of Health Management Changchun University of Chinese Medicine China Graduate School Changchun University of Chinese Medicine China

ISBN: (纸本)9781510664968

Objective This study analyzes, summarizes and summarizes the hotspots and trends in the research literature on technological innovation efficiency, and provides a theoretical basis for future scientific research. Methods We searched the papers on "technological innovation efficiency" from 1999 to 2022 through the database of China Knowledge Network (CNKI), and used COOC13.4 software VOSviewer1.6.13 to analyze the key words, research institutions and authors in this field. The visual scientometric analysis was conducted using COOC13.4 software VOSviewer1.6.13 to visualize key words, research institutions and authors in this field. Results A total of 1,228 papers were included. The author found that the overall trend of the number of publications was on the rise through the knowledge mapping analysis, and the cooperation between the publishing institutions was not close. Research hotspots include technological innovation efficiency, technological innovation, data envelopment analysis (DEA), high-tech industry, enterprise scale, innovation environment, and influencing factors. Conclusion The research on technological innovation efficiency in recent years is divided into three main development stages respectively, the budding exploration stage, the rapid development stage, and the stable improvement stage. Future research needs to strengthen the cooperation between different institutions and authors. This paper predicts that this research field will be broadened in the future and the research on technological innovation efficiency will develop toward a diversified trend. © 2023 SPIE.

关键词： data envelopment analysis

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Dash: A Bimodal data exploration Tool for Interactive Text and visualizations

Dash: A Bimodal Data Exploration Tool for Interactive Text a...

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International conference on visualisation, VIS

作者： Dennis Bromley Vidya Setlur Tableau Research

ISBN: (数字)9798350354850

ISBN: (纸本)9798350354867

Integrating textual content, such as titles, annotations, and captions, with visualizations facilitates comprehension and takeaways during data exploration. Yet current tools often lack mechanisms for integrating meaningful long-form prose with visual data. This paper introduces DASH, a bimodal data exploration tool that supports integrating semantic levels into the interactive process of visualization and text-based analysis. DASH operationalizes a modified version of Lundgard et al.’s semantic hierarchy model that catego-rizes data descriptions into four levels ranging from basic encodings to high-level insights. By leveraging this structured semantic level framework and a large language model’s text generation capabilities, DASH enables the creation of data-driven narratives via drag-and-drop user interaction. Through a preliminary user evaluation, we discuss the utility of DASH’s text and chart integration capabilities when participants perform data exploration with the tool.

关键词： Annotations visual analytics Semantics data visualization Encoding Distance measurement data models

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INCREASING STRUCTURAL MODELLING EFFICIENCY USING COMPUTATIONAL visual WORKFLOWS 83

INCREASING STRUCTURAL MODELLING EFFICIENCY USING COMPUTATION...

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83rd EAGE conference and Exhibition 2022

作者： McLean, F. Reilly, C. Shearer, J. Petroluem Experts

ISBN: (纸本)9781713859314

The creation of geological models is an integral part of exploration and development. Advances in Artificial Intelligence and digitalization technology allow geoscientists to extract maximum value from seismic data, producing more comprehensive geological models than using traditional manual interpretation techniques alone. These technologies are typically of limited use when input data is of poor quality;often the case in structurally complex regions. Structural modelling techniques provide reliable, empirical approaches for supplementing incomplete or poor data to improve understanding and reduce uncertainty in geological models. Software-based structural modelling technologies are well-established and have traditionally been operated manually by domain specialists to perform structural analysis tasks. These processes, while allowing rigorous prediction of fault and horizon geometries where data are lacking, are time intensive and often inaccessible to generalists. Recent software developments have permitted automation of structural modelling techniques using computational visual workflows. The result is several orders of magnitude increase in modelling efficiency, reduction in subjectivity, reproducibility of modelling procedures and an increase in the accessibility of structural modelling to non-domain experts. Here, we present two case study examples using this new visual workflow modelling technology, which automates structural analysis techniques: fault shape prediction, and comprehensive analysis of fault propagation folding. © (2022) by the European Association of Geoscientists & Engineers (EAGE) All rights reserved

关键词： Structural analysis

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A Conceptual Framework for Immersive Behavioral data exploration Assisted by a Deep Learned Representation of data

A Conceptual Framework for Immersive Behavioral Data Explora...

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IEEE International conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Victor Duvivier Matthieu Perreira Da Silva Yannick Prié École Centrale Nantes CNRS LS2N UMR 6004 Nantes Université Nantes France

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

By allowing to conduct experiments involving eco-logically valid tasks within controlled environments, Virtual Real-ity (VR) offers novel opportunities for studying human behavior. Several modalities can be leveraged, including event logs, motion trajectories, eye-tracking data, or physiological signals. However, analyzing such multimodal data presents considerable challenges due to their inherent complexity, the varied structures they imply, as well as the necessity to use exploratory approaches. There is therefore a need to design visual analytics tools for the exploration of immersive behavioral data without prior knowledge. Our idea is to integrate deep learned computational models -which leverage advanced techniques to extract valuable high-level features from unlabeled data- into exploratory visual Analytics tools. We introduce a conceptual framework for integrating deep learning models into the visual Analytics process of immersive behavioral data analysis, also focusing on the services that such systems should provide to the analysts.

关键词： Deep learning Solid modeling Analytical models visual analytics Biological system modeling Computational modeling Virtual reality Feature extraction Transformers data models

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EXTENDING VISUOSPATIAL analysis IN DESIGN COMPUTING: An exploration with a Novel GPU-Based Algorithm and Form-Based Codes 28th

EXTENDING VISUOSPATIAL ANALYSIS IN DESIGN COMPUTING: An Expl...

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28th International conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2023

作者： Kimm, Geoff White, Marcus Burry, Mark Swinburne University of Technology Australia

ISBN: (纸本)9789887891796

This paper responds to a gap observed between the contemporary capacity for calculation and analysis of visibility of built environment features, such as buildings, in digital urban and architectural computational research models and the functionality of off-the-shelf software tools available to professionals. The research investigates the potential of visibility analysis to be embedded and extended within computational-based workflows of software tools to better meet urban design and planning industry needs. We introduce a novel method for visibility calculation that exposes output data for further analysis within a computational workflow and implement it in a game development engine used by software tool providers. Based in our engagement with a local government authority, we then use that method to demonstrate a workflow in the context of form-based building codes in which the visual impact of a building is considered rather than prescriptive limits on dimensions and use. Our results indicate the novel method has substantial performance improvements compared to an alternative mode of visibility calculation and that software providers could more thoroughly integrate and extend visibility analysis to meet industry needs. © 2023 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.

关键词： Graphics processing unit

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analysis of Users’ Demand for visual Images of Chinese Medicine Time-Honored Brands Based on the Kano Model 2nd

Analysis of Users’ Demand for Visual Images of Chinese Medi...

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2nd International conference on Image, Vision and Intelligent Systems, ICIVIS 2022

作者： Yu, Mengyao He, Changhua Ma, Yue Yunnan University of Business Management Yunnan Kunming650106 China

ISBN: (纸本)9789819909223

Objective-based on the relevant research methods of the Kano model, this paper makes a specific exploration of the principles and design ideas of Chinese medicine’s time-honored brand image according to users’ needs. Methods the relevant data of the user needs of the time-honored brand image of Chinese medicine were obtained through the questionnaire survey method. And then, through the Kano model, the user needs were divided into basic needs (m), charm needs (a), no special difference needs (I), reverse needs (R), and expectation needs (o), to explore the internal needs of users for the visual image of the Chinese medicine brand. Moreover, integrate the sensory experience of users for the brand image. The perception process of interactive experience and emotional experience and the most original needs of users are transformed into reliable data. The needs are calculated through the calculation method of better worse coefficient. Results it is proposed that the brand image of time-honored pharmaceutical brands needs to unify the visual images and create the IP images, to make the brand image of time-honored Chinese pharmaceutical brands have the characteristics of the times and interest. Conclusion according to the needs of users, summarizing the methods and strategies suitable for optimizing the visual image of Chinese medicine time-honored brands is not only the inheritance and tolerance of Chinese traditional medicine culture but also provides reference and reference for the continuous growth of Chinese medicine time-honored brands. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Behavioral research

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Development of A Vision-based Ship Behavior Characteristics Extraction Approach and Comparison with K-means Clustering 32nd

Development of A Vision-based Ship Behavior Characteristics ...

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32nd International Ocean and Polar Engineering conference, ISOPE 2022

作者： Cai, Zhiyuan Yu, Long Fan, Qidong Li, Lecheng Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration State Key Laboratory of Ocean Engineering School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781880653814

The poor quality of real ship data and the lack of navigation status marks make it different from the experimental data recorded with experimental conditions, which is difficult to be effectively used in the study of ship performance. In this paper, a visual analysis system of navigation logic is developed to assist in abnormal data processing. At the same time, the visual analysis is used to divide the real ship data sub units, and the small sample navigation state determination set is obtained. The results of K-means clustering are compared with the determined set, and the navigation state class is obtained by semantic classification. Factor analysis is used to analyze the characteristics of navigation state data, so as to reduce the dimension of data and make the classification result better. Taking the inland navigation mark maintenance work boat data as an example, this method is realized to label the ship navigation status for the unknown large sample data set. © 2022 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： K-means clustering

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3rd International conference of International Society for Intelligent Construction, ISIC 2022

3rd International Conference of International Society for In...

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3rd International conference of International Society for Intelligent Construction, ISIC 2022

ISBN: (纸本)9783031202407

The proceedings contain 38 papers. The special focus in this conference is on International Society for Intelligent Construction. The topics include: Additive Manufactured (3D-Printed) Connections for Thermoplastic Facades;auto(mated)nomous Assembly;BIM-to-FEM: Development of a Software Tool to Increase the Operational Efficiency of Dam Construction Projects;converting Algorithms into Tangible Solutions: A Workflow for Materializing Algorithmic Facade Designs;Development of a BIM Model for Facility Management with Virtual/Augmented Reality Interaction;improv-Structure: Exploring Improvisation in Collective Human-Robot Construction;An exploration of Graph-Based FEM Optimization for Construction Industry;assessing Hazardous Spills Impact on Road Surface Performances by 3D High Resolution Surveying Techniques;integrating Smart and Sustainable Construction: A Review of Present Status, and Possible Opportunities;digital Construction Strategy for Project Management Optimization in a Building Renovation Site: Machine Learning and Big data analysis;integration of Spot Tests and Vibratory Roller data in Rural Road Pavement Layers Made with Recycled Aggregates;multiphysical Coupling analysis of the Transition Zone Behaviour in Corroded Reinforced Concrete Structures;the Influence of the visual Factor on the Efficiency of visualization Method in the Production Environment;waste Elimination and Value Management Framework Based on Lean Design Methods;Aggregating High-Precision GNSS Intelligent Construction data for Quality Asphalt Pavements;construction Sector Transformation: Developing a New Learning Paradigm;digitalization of the Asphalt Paving Workflow and Process – Its Challenges and Opportunities;discrete Aggregate Mass Calculation Method for visual Detection of Aggregate Gradation and Elongated and Flat Aggregate Contents;a New Sustainable System for Piped Water Cooling of Mass Concrete Structures.

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An Interactive visual System for data Analytics of Social Media 21st

An Interactive Visual System for Data Analytics of Social Me...

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21st International conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Zhang, Yi Li, Zhaohui Xi, Dewei Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Tianjin Univ Sch New Media & Commun Tianjin Peoples R China

ISBN: (纸本)9783030953911;9783030953904

With the development of the Internet, Big data analysis of social media has become a hot research topic in recent years. However, a challenging problem in social media analysis is how to intelligently detect event information from massive media data and how to help users quickly understand event content. Therefore, we propose a method to extract important time periods of events from media data to analyze the media event information, and develop an interactive visual system based on the "5W" principle. The system provides an interactive analysis platform for exploring media Big data (e.g., Twitter data). The system uses a dynamic topic model to extract topics, a Naive Bayesian classifier to distinguish emotions, and explores events based on the evolution of time, topics, and emotions. In terms of visualization, the system allows users to add some annotations based on segmentation of complex information and highlight important events by adding different story cards to the timeline so that users can get a quick overview of events. Users can also interactively modify the story cards during the exploration process. Finally, several case studies show that our system can effectively reduce the time required to understand social media data and allow users to quickly explore the full picture of an event through an interactive approach.

关键词： Social media analysis Big data analysis Important time period extraction Interactive visualization Social media event

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visualization Research of Big data in Higher Education Based on the Web of Science 3

Visualization Research of Big Data in Higher Education Based...

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3rd International conference on Electronics, Communications and Information Technology, CECIT 2022

作者： She, Linwei Lai, Liqi Jinan University International Business School Zhuhai519070 China Jinan University GBA and B&R International Joint Research Center for Smart Logistics Zhuhai519070 China Modern Education Technology Center Jinan University Zhuhai519070 China

ISBN: (纸本)9798350331974

With the rapid development of information technology such as artificial intelligence and cloud computing, big data of higher education has received a lot of attention. This article uses the visual software Citespace from 2013 to 2022 to research higher education in big data in the Web of Science database. Through visual analysis, and uses of the keyword co-occurrence function and cluster analysis function, this article clarifies the main research directions, key documents, hotspots, and limitations in the field of big data in higher education, education big data technology, learning behavior analysis, learning style exploration, education resource management, and personalized teaching reform are the development direction and research hotspots. This article can provide readers and other researchers with some references and help. © 2022 IEEE.

关键词： Big data

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