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Research Hotspots and Development Trend of Blended Learning in China in the Past Two Decades: A Cite Space visual analysis Based on CSSCI Journal Literature 23

Research Hotspots and Development Trend of Blended Learning ...

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7th International conference on Education and Multimedia Technology, ICEMT 2023

作者： Zang, Wenjing School of Education Tianjin University China

ISBN: (纸本)9798400709142

In order to explore the research frontiers and hot topics of blended learning, the research on blended learning in China during the past two decades from 2004 to 2023 was visualized and analyzed with the help of CiteSpace, a software for visual metrics analysis, using CSSCI journals in the CNKI database as the source of data retrieval, and the method of bibliometric analysis and scientific knowledge mapping. The results of the study show that: (1) the current research on blended learning in China is rich in topics, but the cooperation between research authors is low, and the cohesion of research power is insufficient. (2) The research hotspots focus on the application of blended learning mode in flipped classroom, the practice of blended learning based on multiple teaching platforms, and the exploration of the integration of college English and blended learning. (3) In the future, the main trend of research will be to continue to carry out the theoretical study of blended learning, to explore the application of blended learning technology under the "Internet + technology", and to carry out the study of blended learning on the individual ability of students. CCS CONCEPTS: Applied computingĝ1/4Educationĝ1/4E-learning © 2023 ACM.

关键词： Engineering education

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ICMI 2024 - Proceedings of the 26th International conference on Multimodal Interaction

ICMI 2024 - Proceedings of the 26th International Conference...

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26th International conference on Multimodal Interaction, ICMI 2024

ISBN: (纸本)9798400704628

The proceedings contain 82 papers. The topics discussed include: LLM-powered multimodal insight summarization for UX testing;on multimodal emotion recognition for human-chatbot interaction in the wild;integrating multimodal affective signals for stress detection from audio-visual data;feeling textiles through AI: an exploration into multimodal language models and human perception alignment;decoding contact: automatic estimation of contact signatures in parent-infant free play interactions;ScentHaptics: augmenting the haptic experiences of digital mid-air textiles with scent;online multimodal end-of-turn prediction for three-party conversations;detecting deception in natural environments using incremental transfer learning;and exploring interlocutor gaze interactions in conversations based on functional spectrum analysis.

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VIVA: visual exploration and analysis of Videos with Interactive Annotation 28

VIVA: Visual Exploration and Analysis of Videos with Interac...

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28th Annual conference on Intelligent User Interfaces (IUI)

作者： Ruangrotsakun, Anita Oh, Dayeon Nguyen, Thuy-Vy Lee, Kristina Ser, Mark Hiew, Arthur Ngo, Rogers Shureih, Zeyad Khanna, Roli Kahng, Minsuk Oregon State Univ Corvallis OR 97331 USA Google Res Mountain View CA USA

ISBN: (纸本)9798400701078

This paper presents VIVA, a novel interactive tool for visually exploring long videos and searching for specific moments. Previous work on video data exploration and analytics often assumes that manually-created, rich annotations are available. However, such metadata may not be easily obtained. We design an interactively machine learning workflow for users to rapidly create annotations along a timeline. Combined with VIVA's focus+context visualization that effectively displays frame snapshots in the context of a video stream, VIVA enables users to explore and analyze long video clips by incrementally make sense of them. We present usage scenarios that demonstrate how users would use VIVA for video-related tasks.

关键词： visualization

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FitYou: A Personalized Dashboard for Health data 23

FitYou: A Personalized Dashboard for Health Data

引用

16th International Symposium on visual Information Communication and Interaction, VINCI 2023

作者： Zacheo, Giada Buzimkic, Amina La Roi, Andreas Van Schie, Alexander Staudt, Yves Burch, Michael Competence Centre for Data Analysis Visualisation and Simulation University of Applied Sciences Chur Switzerland

ISBN: (纸本)9798400707513

We introduce FitYou, an interactive dashboard for health data visualizations from wearable devices. It supports the exploration of health trends and health attribute correlations. Wearable devices are small enough to wear on the body and that can be equipped with sensors to track various physical and physiological attributes like heart rate, steps taken, and sleep quality, to just mention a few. By exploiting those attribute values we can visually monitor health-related issues, for example during sports activities like training, a sports competition, or a rehabilitation phase. Activity levels are hard to detect without such support but can help to improve someone's overall well-being. We illustrate the usefulness of FitYou by means of some application examples. Finally, we discuss the challenges and limitations of the dashboard by focusing on algorithmic, visual, and perceptual issues. © 2023 Owner/Author.

关键词： data visualization

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Exploratory and statistical data analysis of Indian economy 5

Exploratory and statistical data analysis of Indian economy

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5th IEEE International conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Singh, Bhawna Vandana Umrao, Sandhya Katiyar, Sanjay Sharma, Vanshika G.L. Bajaj Institute Of Technology And Management Department Of Cse Greater Noida India Noida Institute Of Engineering And Technology Department Of Cse Greater Noida India Greater Noida Institute Of Engineering And Technology Department Of Cse Greater Noida India

ISBN: (纸本)9798350330861

Exploratory data analysis provides visual exploration of data and also allows for the identification of trends and relationships between variables. The aim of this research is to study about different factors involved in the economy of India. The dataset has been collected from year 1960 to 2020 and is analyzed by looking at the factors such as GDP, import and export value of goods and services, total reserves(include gold, current US Dollar) and health status of nation's citizens. Thus, it suggests that all factors are important for a stable economy and it also provides different ways to improve these factors. © 2023 IEEE.

关键词： Information analysis

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Context-Based Annotation visualisation in Virtual Reality: A Use Case in Archaeological data exploration 21st

Context-Based Annotation Visualisation in Virtual Reality: A...

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21st EuroXR International conference, EuroXR 2024

作者： De Bonis, Michele Nguyen, Huyen Bourdot, Patrick Université Paris-Saclay CNRS LISN Gif-sur-Yvette France

ISBN: (纸本)9783031785924

In this paper we present a Virtual Reality (VR) tool that facilitates the visualisation and exploration of context-based, multi-level annotations in archaeology. Indeed, thanks to photogrammetry and laser scanning techniques, archaeologists can capture and reconstruct almost faithfully ruins and excavations in 3D. Thus, they can maximise their work performance on the field within their limited excavation time and leave deep, but often slow, analysis tasks at later stages offsite. Using VR, we can enrich 3D captured and reconstructed environments by adding extra information for ex situ analysis of archaeological data. This approach can also help the archaeologists speed up their collaboration with other experts or easily share the information with the public. We aim to assist the exploration of numerous annotations and information at disposal that can be densely clustered in a 3D reconstructed world. We collaborated closely with archaeologists at AOROC in the process of designing annotations that convey information with increasing Levels of Detail (LoDs), reflecting the complexity of the contained data. We then developed different interaction techniques that allow users to explore the annotations by switching between LoDs, including active selection by clicking, proximity approach, and the combination of both. Additionally, we proposed and evaluated the effectiveness of annotation grouping mechanism to enhance visual clarity by aggregating annotations in close spatial proximity. The results of our user study with non-experts, aggregated with a qualitative study with the archaeologists, showed user preference for the combination of the interaction techniques, but evidenced some limitations for the grouping of annotations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Virtual reality

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VIRTUAL SAMPLE GENERATION OF HYPERSPECTRAL MINERAL data

VIRTUAL SAMPLE GENERATION OF HYPERSPECTRAL MINERAL DATA

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International conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS)

作者： Yadav, Palla Parasuram Shetty, Amba Raghavendra, B. S. Narasimhadhan, A. V. Natl Inst Technol Karnataka Surathkal India

ISBN: (纸本)9798350345421

Identification of earth surface features or useful resources even at inaccessible locations for humans made possible with the help of spatial-spectral information provided by remote sensing data especially hyperspectral images. At present deep learning (DL) based models have become a best choice to address the issues and provide better solutions in many fields including remote sensing data analysis. Due to very subtle differences exhibited by mineral signatures and also lack of sufficient training samples, geo-science and remote sensing research community has not much explored the DL techniques in analyzing mineral data. Therefore, in this paper, a virtual sample generation technique using vector rotation is proposed to increase the mineral data for training DL models. The proposed virtual sample generation technique is explored on a spectral library of 5 minerals that is formed from Cuprite scene, a benchmark mineral data set. The quality of the mineral samples generated are assessed using visual inspection as well as a relative spectral discriminating power of target minerals with respect to non-target or remaining minerals. Results show that mineral samples generated by the proposed virtual sample generation technique are not only qualitative in nature but also helpful or encouraging in exploration of DL in mineral data analysis.

关键词： Hyperspectral data Mineral signatures virtual sample generation

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Interactive visualization of BioMedical data

Interactive Visualization of BioMedical Data

引用

2024 IEEE International conference on Big data, Bigdata 2024

作者： Islam, Mohammad Shafiqul Ibn Rafiq, Rahat Tusch, Guenter Grand Valley State University College of Computing MI United States

ISBN: (纸本)9798350362480

Public databases such as the NCBI Gene Expression Omnibus (GEO) house millions of experimental gene expression datasets invaluable for transcriptome meta-analysis, enabling researchers to identify genes, pathways, and biomarkers with enhanced accuracy. However, while these datasets offer great potential, finding relevant biological pathways in disease-related contexts remains challenging. To address this, we introduce a web-based visualization tool that utilizes PubMed abstracts to extract key biomedical entities, such as genes, pathways, diseases, species, and chemicals, and represent their relationships through an interactive graph. By leveraging PubMed's annotated MeSH terms, our tool allows users to explore the literature more intuitively, bypassing traditional dataset search limitations and focusing on published results. The tool transforms complex query outputs into a graph-based network, providing a visual interface for navigating connections between biological entities. This interactive approach helps researchers to analyze relationships within large-scale biomedical data and uncover potential pathways for drug repurposing and disease understanding. We discuss the tool's design using ***, its application in biomedical research, and the challenges faced when visualizing large datasets, offering new insights for improved data interpretation and exploration. © 2024 IEEE.

关键词： BioInformatics BioMedical data visualization PubMed

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visual Analytics for Profiling Land Use Changes 36

Visual Analytics for Profiling Land Use Changes

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36th SIBGRAPI conference on Graphics, Patterns and Images (SIBGRAPI)

作者： Santos, Claudio Hosseini, Maryam Rulff, Joao Miranda, Fabio Wilson, Luc Silva, Claudio Ferreira, Nivan Lage, Marcos Univ Fed Fluminense Niteroi RJ Brazil MIT Cambridge MA USA NYU New York NY USA Univ Illinois Chicago IL USA Kohn Pedersen Fox Associates PC New York NY USA Univ Fed Pernambuco Recife Brazil

ISBN: (纸本)9798350338737;9798350338720

The growth of cities calls for regulations and zoning rules on how each piece of urban space will be used. Tracking land use can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of the shape and the attributes of land units. The complex nature of land-use data, however, makes the analysis of such data challenging and time-consuming. To address these challenges, we propose URBAN CHRONICLES, a visual analytics system that enables interactive exploration of land-use changes. Using New York City's Primary Land Use Tax Lot Output (PLUTO), we show the system's capabilities to explore the data from several years at different scales. URBAN CHRONICLES supports on-the-fly aggregation and filtering operations that leverage the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. Finally, we demonstrate the system's utility through case studies that analyze the impact of Hurricane Sandy on land use attributes and the effects of rezoning plans in Brooklyn.

关键词： visual analytics

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Navigating Exascale Operational data Analytics: From Inundation to Insight

Navigating Exascale Operational Data Analytics: From Inundat...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and analysis, SC Workshops 2024

作者： Shin, Woong Osborne, Tim Karimi, Ahmad Maroof Palumbo, Rachel May, Alex Lester, Corwin Hines, Jesse Sattar, Naw Safrin Huk, Leah Simmerman, Scott Brewer, Wesley Miller, Jeffrey Adamson, Ryan Kuchar, Olga Prout, Ryan Wang, Feiyi Atchley, Scott Oral, Sarp Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350355543

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments. © 2024 IEEE.

关键词： data Analytics data Governance HPC Post-Exascale Challenges Machine Learning Applications Monitoring Operational data Analytics Telemetry visual Analytics

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