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检索条件"任意字段=Conference on Visualization and Data Analysis 2011"

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analysis and visualization of Published Literature on Healthcare Services Research from 2011 to 2022: a Bibliometric and Network analysis

Analysis and Visualization of Published Literature on Health...

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International conference on Biomedical Engineering and Applications (ICBEA)

作者： Bo Guo Nur Syufiza Ahmad Shukor Irny Suzila Ishak Department of Computing Faculty of Communication Visual Art and Computing Universiti Selangor Selangor Malaysia School of Computer and Information Engineering Fuyang Normal University Fuyang China

Healthcare services are one of the major public issues facing the world and have become a research hotspot in recent years. This paper provides a review and quantitative analysis of the literature related to healthcare services to sort out the research trends and hotspots in this field. This paper used bibliometric analysis to search keywords in the Web of Science database in TITLE-ABS-KEY format. After screening, the final 4188 articles from 2011 to 2022 were collated, and co-citation analysis was performed using VOSviewer literature visualization analysis software. The global healthcare services literature has grown steadily year after year. Health Care Sciences & Services (9.5%) and General & Internal Medicine (8.7%) were the most common areas of research, with the United States (N=1016) accounting for the largest share of research. “BMC Health Services Research” is the most active journal (N=149). Healthcare services are one of the current research focuses in the field of healthcare institutions. In the future, further research into assistive technologies and tools for healthcare services, such as the Internet of Things, cloud services, and big data analytics will be investigated. In addition, research on healthcare services focusing on special needs populations, especially the elderly, is a hotspot for future research, broadening the boundaries of research and having practical value.

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Research on Fine-Grained Image Classification Based on data Enhancement and Attention Mechanism

Research on Fine-Grained Image Classification Based on Data ...

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Information Science, Parallel and Distributed Systems (ISPDS), International conference on

作者： Haitao Xin Qilu Jiang School of Computer and Information Engineering Harbin University of Commerce Harbin China School of Computer and Information Engineering Harbin Business University Harbin China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

The research content of fine-grained image recognition is the problem of sub-category recognition under a broad category. Since fine-grained image classification has the data characteristics of little difference between classes and big difference within classes, it becomes a very challenging research task. The key to solving this task is to find the key regions in images and extract effective features from them. Based on the analysis and research of existing fine-grained image classification algorithms and models, this paper introduces a weakly supervised fine-grained classification method that utilizes cutmix data augmentation. SE attention module is introduced to enhance the significant regional features of images, and label smoothing mechanism is used to improve the model generalization ability. Compared with traditional methods on CUB_200_2011 dataset, the experimental results demonstrate that our method achieves improved classification performance.

关键词： Training visualization Attention mechanisms Smoothing methods Feature extraction Solids data models

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Improving Android Malware Detection with Entropy Bytecode-to-Image Encoding Framework

Improving Android Malware Detection with Entropy Bytecode-to...

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International conference on Computer Communications and Networks (ICCCN)

作者： Saleh J. Makkawy Abdalrahman H. Alblwi Michael J. De Lucia Kenneth E. Barner Department of Electrical and Computer Engineering University of Delaware Newark Delaware Department of Computer Science Umm Al Qura University Mecca Saudi Arabia

ISBN: (数字)9798350384611

ISBN: (纸本)9798350348439

Detecting malicious software applications is crucial in protecting user data and privacy. The increasing popularity of operating systems (OS) such as Android, iOS, and Windows has led to an expansion in the number of malicious software applications targeting these platforms. Several studies have explored various techniques to detect malware threats, including signature-based detection, behavioral analysis, dynamic analysis, and static analysis. However, these conventional methods may fail to detect new variants of malware with unique characteristics. This research paper introduces a unified approach that combines entropy bytecode-to-image visualization with ensemble learning to enhance the identification of malicious patterns. To validate the efficacy of the entropy encoder, the AndroZoo-2011 application data set was used as a training set, comprising 184,474 samples, including 49,150 and 13,324 malicious and benign applications, respectively. The applied method demonstrates improved performance with an accuracy of 95.77%, a precision of 90.60%, and an F1 score of 92.21% compared to other existing encoders, making our approach more applicable to real-world scenarios.

关键词： Training Accuracy Operating systems Neural networks Static analysis Malware Entropy

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A modular approach for integrating data science concepts into multiple undergraduate STEM+C courses 129

A modular approach for integrating data science concepts int...

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129th ASEE Annual conference and Exposition: Excellence Through Diversity, ASEE 2022

作者： Naseri, Mohammad Yunus Snyder, Caitlin McLoughlin, Brendan Bhandari, Sambridhi Aryal, Niroj Biswas, Gautam Henrick, Erin Hotchkiss, Erin R. Jha, Manoj K. Jiang, Steven Kern, Emily Lohani, Vinod K. Marston, Landon Todd Vanags, Christopher Xia, Kang

With increasingly technology-driven workplaces and high data volumes, instructors across STEM+C disciplines are integrating more data science topics into their course learning objectives. However, instructors face significant challenges in integrating additional data science concepts into their already full course schedules. Streamlined instructional modules that are integrated with course content, and cover relevant data science topics, such as data collection, uncertainty in data, visualization, and analysis using statistical and machine learning methods can benefit instructors across multiple disciplines. As part of a cross-university research program, we designed a systematic structural approach-based on shared instructional and assessment principles-to construct modules that are tailored to meet the needs of multiple instructional disciplines, academic levels, and pedagogies. Adopting a research-practice partnership approach, we have collectively developed twelve modules working closely with instructors and their teaching assistants for six undergraduate courses. We identified and coded primary data science concepts in the modules into five common themes: 1) data acquisition, 2) data quality issues, 3) data use and visualization, 4) advanced machine learning techniques, and 5) miscellaneous topics that may be unique to a particular discipline (e.g., how to analyze data streams collected by a special sensor). These themes were further subdivided to make it easier for instructors to contextualize the data science concepts in discipline-specific work. In this paper, we present as a case study the design and analysis of four of the modules, primarily so we can compare and contrast pairs of similar courses that were taught at different levels or at different universities. Preliminary analyses show the wide distribution of data science topics that are common among a number of environmental science and engineering courses. We identified commonalities and differences i

关键词： data visualization

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Current Status of the Application of Metaverse in Education: Visual analysis Based on Knowledge Graphs

Current Status of the Application of Metaverse in Education:...

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Educational Technology (ICET), IEEE International conference on

作者： Xiaochun Zhou Ruotian Jia Xing Li Minmin Tang Liu Qi Institute of Education Jianghan University Wuhan China Luzhou Normal Affiliated Primary School Chengxi School Luzhou China

ISBN: (数字)9798350376944

ISBN: (纸本)9798350376951

Based on the relevant papers and citation data on the application of the metaverse in education published in SSCI and SCI-E in Web of Science from 2011 to 2024, this study uses VOSviewer and CiteSpace for visual analysis. From the perspectives of literature authors, countries, research hotspots, and research trend evolution, the mainstream research hotspots in this field are summarized to grasp the development pulse of this field. Research has found that: (1) The application of the metaverse in education has received increasing attention in the academic community. Countries/affiliated institutions located in the same region are close partners in scientific cooperation; (2) There is a clear evolutionary path in the research focus, shifting from understanding the educational potential of the metaverse to understanding its application value and its impact on learner performance and perception; (3) The application of the metaverse in education requires further exploration of future directions to address challenges.

关键词： Training visualization Metaverse Education Focusing Knowledge graphs Educational technology Market research Problem-solving Protection

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Visual analysis of English curriculum research based on knowledge graph

Visual analysis of English curriculum research based on know...

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2021 IEEE International conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2021

作者： Yu, Bei International Education School Guangzhou College of Technology and Business Guangzhou Guangdong510850 China

ISBN: (纸本)9780738146492

The visualization analysis based on knowledge graph is one of the fastest developing science and technology in recent years. This technology uses visual software. This technology can clearly and intuitively get the information contained in a large number of literature, and completely show the process of data analysis and the trend of data link. In this paper, 5,439 articles related to English curriculum research in China from CNKI full-text database during 2011-2021 are taken as data samples. Based on the method of graph analysis of scientific knowledge, using visual software, combining quantitative and qualitative methods, this paper mainly analyzes the current situation of English development in China, the shortcomings of English classroom, the feasibility of English curriculum reform, and how to reform English curriculum. © 2021 IEEE.

关键词： Curricula

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analysis on Various Approaches to Visualize and Interpret Convolution Neural Network 3

Analysis on Various Approaches to Visualize and Interpret Co...

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3rd IEEE International conference on Frontiers Technology of Information and Computer, ICFTIC 2021

作者： Bai, Langxing Keystone Academy Beijing China

ISBN: (纸本)9781665406055

The paper aims to explore and evaluate the efficacy of methods that visualizes the internal structure of convolution neural networks as well as neural networks that are inherently interpretable. The paper implements three data set, including MNIST digits, MNIST Fashion, and CUB 200-2011. Tow base structures implemented to construct the convolution neural network are VGG 19 and a two-convolution layer CNN to provide intuitions upon analyzation. The paper toke the two approaches in analyzing the various methods: post hoc interpretation, which includes visualization of convolution kernels, and interpretable models, which includes a novel convolution neural network-based model. As for the outcomes, while the post hoc interpretations only offer superficial and unfaithful explanations to the CNN behavior, the use of the ProtoPNet in real-time interpretation provides an in-depth analysis of the model's reasoning process in decision making in contrast to the inexplicability of mainstream deep learning models. © 2021 IEEE.

关键词： visualization

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Mapping Research Trends and visualization of E-learning in Entrepreneurship in the Last Ten Years 1

Mapping Research Trends and Visualization of E-learning in E...

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1st International conference on Electrical and Information Technology, IEIT 2021

作者： Maulana, Fairuz Iqbal Candra Pratama, Febby Permana, Frihandhika Khaeruddin Herasmara, Ridho School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

ISBN: (纸本)9781665417860

E-learning is a system or concept of education or learning process that utilizes information technology in the teaching and learning process anywhere and anytime. E-learning is widely applied in various fields of science. In this study, we draw scientific efforts on e-learning and entrepreneurship from publications in the Scopus database. We reviewed 218 academic documents published over the last 10 years, from 2011 to 2020. Our method is a global bibliometric analysis by visualizing connected networks using Vosviewer. The method used consists of five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. We researched several countries, affiliations, authors, subject areas, to types of publications that have relations in this field. Among the most published and indexed articles by Scopus, papers published by researchers in the China have the highest number of publications is 36 academic documents, followed by United States 18 academic publications, and Italy with 16 academic publications. The results showed that it had a limited impact, and through visualization, the network presented research gaps that future researchers should fill. The processed data shows the pattern and trend of increasing the number of international publications on E-learning in the field of entrepreneurship indexed by Scopus. Finally, we address the limitations of this study. © 2021 IEEE.

关键词： visualization

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Smart cities concept and innovative strategies in mexico: A bibliometric analysis using vosviewer

Smart cities concept and innovative strategies in mexico: A ...

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2021 IEEE International conference on Engineering, Technology and Innovation, ICE/ITMC 2021

作者： Alvarez-Sosa, Damaris Abbas, Asad King Abdullah University of Science and Technology Biological and Environmental Sciences and Engineering Division Thuwal Saudi Arabia Institute for the Future of Education Tecnologico de Monterrey Writing Lab Monterrey Mexico

ISBN: (纸本)9781665449632

Due to a cumulation on economic growth and the population movement to urban environments, more than half of the world population living in cities. Also, this population growth and movement do not appear to be decreasing for Mexico in the upcoming future. Hence, environmental and management strategies were studied and applied in few Mexican cities (Puebla, Mexico City, Estado de Mexico, and Chihuahua) to ensure order as well as a better quality of life. For analysis of gathered data through the Scopus database, data visualization and network analysis were performed using the VOSviewer program. The results consist of co-citation analysis, keyword analysis, and authorship, and company analysis. This present study affirms the fact that;smart city research in Mexico has undergone several changes. It has evolved from being a collaborative front between four institutions from North America in 2011 to a diverse initiative conducted by multiple institutions across the country. Likewise, the overall focus has shifted from Smart cities through technology-based initiatives to management and data. The fact that these initiatives are being considered as population density. Also, the need for effective use of resources enhances urban environments nationwide, placing them as a viable mechanism to produce and apply strategies towards sustainability for the present and near future. © 2021 IEEE.

关键词： Sustainable development

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Hotspots and Trends of Research on Smart Learning Environments in China: Bibliometric analysis by Citespace

Hotspots and Trends of Research on Smart Learning Environmen...

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IEEE International conference on Engineering, Technology and Education (IEEE TALE)

作者： Dai, Zhicheng Wu, Xuebing Zhu, XiaoLiang Cent China Normal Univ Natl Engn Res Ctr E Learning Wuhan Peoples R China Cent China Normal Univ Fac Artificial Intelligence Educ Wuhan Peoples R China Cent China Normal Univ Natl Engn Lab Educ Big Data Wuhan Peoples R China

ISBN: (纸本)9781665436878

With the introduction of Education Informatization 2.0, smart education has gradually become a research hotspot in academia. As an important part of smart education, Smart Learning Environment (SLE) has become an increasingly important factor with board prospects. This study identified the research focus and development tendency of SLE in China from 2011 to 2020 using the metrological literature visualization software Citespace, which is based on the core database of academic journals of CNKI. The results show that the research hotspots focused on building SLE by using emerging technologies such as big data, artificial intelligence and 5G technology. In terms of application, it is no longer simply using information technology, but emphasizing the deep integration and innovation of information technology and subject teaching. This article combs the development process of SLE, hoping to provide ideas for the subsequent development of SLE research and application.

关键词： smart learning environment scientific knowledge graph visualization CiteSpace smart campus smart classroom

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