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12th International conference on Clean and Green Energy, ICCGE 2023

作者： Tao, Jian Liu, Mingliang Zhegn, Yuanmao Fu, Haiyan Xiamen University of Technology Xiamen361024 China Fuzhou University Fuzhou350116 China Key Lab of Urban Environment and Health Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China

ISBN: (纸本)9781839539237

This study focuses on exploring the spatial and temporal evolution characteristics of the implied carbon emission efficiency of Chinese provinces and promoting the improvement of the implied carbon emission efficiency, with a view to supply reference for the low-carbon sustainable development of China. Based on the data of each province onto China in 2007, 2012 and 2017, this study applies the environmentally extended input-output model and the super-efficient SBM model to measure the implied carbon emission efficiency and investigates the spatial and temporal evolution characteristics of the implied carbon emission efficiency of Chinese provinces through kernel density estimation and ArcGIS visualization. The results show that the implied carbon emission efficiency of China's provinces and regions as a whole increased from 2007 to 2017, and that differences in implied carbon emission efficiency between provinces and regions exist and are gradually increasing. At present, China's provincial implied carbon emission efficiency is still at a low level, and the level of implied carbon emission efficiency varies significantly between regions. Overall, from 2007 to 2017, the overall carbon emission efficiency in China has been considerably improved. © The Institution of Engineering & Technology 2023.

关键词： Efficiency

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Technology Diffusion Studies in the Digital Age: a scientometric analysis using CiteSpace 23

Technology Diffusion Studies in the Digital Age: a scientome...

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9th International conference on Industrial and Business Engineering, ICIBE 2023

作者： Wang, Yingming Wang, Yining Zhao, Dali School of Economics and Management North China University of Technology Beijing China School of Humanities and Law North China University of Technology Beijing China

ISBN: (纸本)9798400708824

In order to explore the development process and evolution trend of technology diffusion research in the digital age, 4543 papers related to technology diffusion published in SSCI source journals in WOS database from 2007 to 2022 were taken as the data source. And based on CiteSpace literature visualization software, the knowledge overview, keyword co-occurrence, evolution trend and hot themes of technology diffusion research were analyzed. The research shows that the popularity of technology diffusion research is increasing and its influence is expanding;the cooperation between scholars and research institutions is loose;the hot topics are mainly the transfer and recipient of technology diffusion, the process of technology diffusion and the diffusion of technology related to renewable energy. This paper makes a systematic synthesis and analysis of the past research on technology diffusion, which can theoretically provide reference for the future research of technology diffusion, and conducts more research on hot spots, difficulties and pain points. In practice, it provides enlightenment for China's technology introduction and technology spillover, and seeks more technology diffusion paths to strengthen its own technological innovation ability. © 2023 ACM.

关键词： Technology transfer

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Sentiment analysis of Professional Social Network Like Linkedin Using Textblob

Sentiment Analysis of Professional Social Network Like Linke...

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Intelligent Systems and Embedded Design (ISED), International conference on

作者： Prasant Kumar Dash Aniket Kumar Tripti Singh Tarun Kumar Gope Pranab Kumar Singh Bichitrananda Behera Dept. of Computer Science and Engineering C. V Raman Global University Bhubaneshwar Odisha India

ISBN: (数字)9798331522612

ISBN: (纸本)9798331522629

In the evolving landscape of professional social networks, LinkedIn represents a robust ecosystem for professional interactions, content sharing, and career-oriented networking. This research employs a structured sentiment analysis pipeline utilizing the TextBlob library to classify user-generated content-such as posts, comments, and recommendations-into positive, negative, and neutral sentiments. By analyzing the polarity and subjectivity of user interactions, the study aims to identify patterns in professional engagement and connection strategies. The analysis investigates two key hypotheses: (1) Professionals' connection strategies on LinkedIn are predominantly driven by career-oriented motivations, reflecting intentional rather than random networking behaviors; and (2) the type, frequency, and sentiment of shared content are significantly influenced by factors such as a professional's seniority level, career stage, and industry sector. The methodology integrates data preprocessing, sentiment analysis, and result visualization to generate actionable insights into professional interactions on this dynamic platform. This study enhances the understanding of LinkedIn's role in shaping professional identity and engagement, providing implications for network optimization and content strategy development. The findings align with broader research on professional social network analysis, such as the work by Boyd and Ellison (2007), underscoring the evolution of online professional interactions in the digital age.

关键词： Sentiment analysis Social networking (online) data preprocessing User-generated content Pipelines Information age Libraries Intelligent systems Optimization Testing

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Exploring the Performance of You Only Look Once Model for Object Detection in VQA Images

Exploring the Performance of You Only Look Once Model for Ob...

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Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), International conference on

作者： Deepak Suresh Asudani Naresh Kumar Nagwani Pradeep Singh Department of Computer Science and Engineering National Institute of Technology Raipur Chhattisgarh India

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

Identifying objects is among the most crucial and complex problems in computer vision. The effectiveness of object detection tasks has significantly increased due to advancements in deep learning architectures. Object detectors are classified into single-stage (SSD) and two-stage (TSD). SSD model architecture evaluates the spatial region proposals in a single pass. TSDs employ a more complex architecture to focus on selective region proposals. Object detection is an essential component of visual question answering (VQA), which requires algorithms to respond to text-based inquiries about images. While many object detection algorithms are available, real-time application is still somewhat difficult. This paper explores the object detection approaches for VQA systems through a comparative analysis of various YOLO variants. The study compares the effectiveness of YOLOv8s and YOLOv8n architectures against TSD approaches in detecting object positions with bounding boxes. Experiments were conducted on the MS-COCO and two versions of the PASCAL-VOC (2007 and 2012) datasets. The paper outlines the data preprocessing steps required to convert source datasets to the YOLO model format. The experimental evaluations on the PASCAL-VOC dataset indicate that the TSD Faster-RCNN model, using ResNet101 pretrained architecture, achieves the highest mAP of 78.80. In contrast, the SSD YOLOv8s model achieves the highest mAP of 89.63 using the CSPDarkNet53 model architecture. YOLO is essential for real-time object detection, allowing VQA systems to process images in a single forward pass. The study concludes that the SSD YOLOv8s model efficiently identifies objects and generates bounding boxes with higher accuracy compared to other models.

关键词： YOLO Computer vision visualization Accuracy Computational modeling Computer architecture Detectors Real-time systems Object recognition Proposals

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Understanding data Science Instruction in Multiple STEM Disciplines

Understanding Data Science Instruction in Multiple STEM Disc...

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2021 ASEE Virtual Annual conference, ASEE 2021

作者： Snyder, Caitlin Asamen, Dawit M. Naseri, Mohammad Yunus Aryal, Niroj Biswas, Gautam Dubey, Abhishek Henrick, Erin Hotchkiss, Erin R. Jha, Manoj K. Jiang, Steven X. Kern, Emily C. Lohani, Vinod K. Marston, Landon Todd Vanags, Christopher P. Xia, Kang Vanderbilt University United States North Carolina Agricultural and Technical State University United States Virginia Polytechnic Institute and State University United States

As technology advances, data driven work is becoming increasingly important across all disciplines. data science is an emerging field that encompasses a large array of topics including data collection, data preprocessing, data visualization, and data analysis using statistical and machine learning methods. As undergraduates enter the workforce in the future, they will need to "benefit from a fundamental awareness of and competence in data science"[9]. This project has formed a research practice partnership that brings together STEM+C instructors and researchers from three universities and an education research and consulting group. We aim to use high frequency monitoring data collected from real-world systems to develop and implement an interdisciplinary approach to enable undergraduate students to develop an understanding of data science concepts through individual STEM disciplines that include engineering, computer science, environmental science, and biology. In this paper, we perform an initial exploratory analysis on how data science topics are introduced into the different courses, with the ultimate goal of understanding how instructional modules and accompanying assessments can be developed for multidisciplinary use. We analyze information collected from instructor interviews and surveys, student surveys, and assessments from five undergraduate courses (243 students) at the three universities to understand aspects of data science curricula that are common across disciplines. Using a qualitative approach, we find commonalities in data science instruction and assessment components across the disciplines. This includes topical content, data sources, pedagogical approaches, and assessment design. Preliminary analyses of instructor interviews also suggest factors that affect the content taught and the assessment material across the five courses. These factors include class size, students' year of study, students' reasons for taking class, and students' background e

关键词： Students

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Mesh saliency analysis via local curvature entropy 37

Mesh saliency analysis via local curvature entropy

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37th Annual conference on European Association for Computer Graphics, EUROGRAPHICS 2016

作者： Limper, M. Kuijper, A. Fellner, D.W. TU Darmstadt Germany Fraunhofer IGD Germany TU Graz Austria

We present a novel approach for estimating mesh saliency. Our method is fast, flexible, and easy to implement. By applying the well-known concept of Shannon entropy to 3D mesh data, we obtain an efficient method to determine mesh saliency. Comparing our method to the most recent, state-of-the-art approach, we show that results of at least similar quality can be achieved within a fraction of the original computation time. We present saliency-guided mesh simplification as a possible application. © 2016 The Eurographics Association.

关键词： visualization

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Hotspots and Frontiers of Foreign Consumers' Online Purchase Intention - visualization analysis of Bibliometrics Based on WOS (2007-2019) 1

Hotspots and Frontiers of Foreign Consumers' Online Purchase...

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1st International conference on Computer Applied Science and Information Technology, ICCASIT 2020

作者： Gou, Qingxin Duan, Renji Guo, Yunfeng Wang, Cong Yang, Shenglan Zu, Xu Business School Sichuan Agricultural University Chengdu China

In order to objectively reflect the development status and hotspots of foreign consumers'online purchase intention research, this article uses the core journal literature included in the core collection retrieval platform SSCI database of WOS as the data source, and uses Citespace software to visualize the research results of foreign consumers' online purchase intention analysis. The study found that foreign consumers'online purchase intention research focuses on hot topics such as trust, consumer behavior, information systems, and e-commerce models, focusing on cutting-edge content such as online shopping product development and e-commerce marketing models. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Consumer behavior

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visualization of Time Series data Change on Fertility Rate and Education in Indonesia Provinces 5

Visualization of Time Series Data Change on Fertility Rate a...

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5th International conference on Information Management (ICIM)

作者： Shirota, Yukari Presekal, Alfan Sari, Riri Fit Ri Gakushuin Univ Dept Management Facuty Econ Tokyo Japan Univ Indonesia Comp Engn Dept Elect Engn Depok West Java Indonesia

ISBN: (纸本)9781728134307

A new visualization method of time series data change, a statistical shape analysis method, is presented. The shape analysis method was originally developed for image analyses in biology. However the analysis power can also be used in economics and socio-science, and the visualization is effective to understand the changes. The statistical shape analysis method has a feature to extract separately an Affine transformation part and a non-Affine one. The Affine transformation shows the total trend of all the data and the non-Affine one shows a local movement of one landmark which is specific to the landmark. To see the both, we can visually understand changes among the time series data. In this paper, we will present the visualization using Indonesia data on fertility rate and education status between the year 2007 and 2012.

关键词： statistical shape analysis Affine/non-Affine transformation partial warp eigenvectors fertility rates education level

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STEM education: A bibliometric overview

STEM education: A bibliometric overview

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International conference of Modelling and Simulation in Engineering, Economics, and Management, MS 2018

作者： Gil-Doménech, Dolors Berbegal-Mirabent, Jasmina Merigó, José M. Department of Economy and Business Organisation Universitat Internacional de Catalunya C. Immaculada 22 Barcelona08017 Spain Department of Management Control and Information Systems University of Chile Av. Diagonal Paraguay 257 Santiago8330015 Chile School of Information Systems and Modelling Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway UltimoNSW2007 Australia

ISBN: (纸本)9783030154127

In the recent years, STEM (science, technology, engineering and mathematics) education has received increasing attention, and many calls for a fundamental change in this field have emerged. In this context, the analysis of the evolution and development of this scientific domain results crucial. In order to do so, the present study presents a bibliometric overview of the academic research developed in STEM education over the last years. The work uses the Web of Science database and a wide range of bibliometric indicators including the number of publications and citations, the h-index, and citation thresholds. The article also develops a graphical visualisation of the bibliographic data using the visualisation of similarities (VOS) viewer software. Results indicate that the amount of works addressing this topic has substantially increased in the recent years, although the number of citations has not experienced a similar growth rate. Also, when analysing journals and research areas, it can be deduced that the research on STEM education is diverse. The bibliometric analysis performed provides a rigorous and comprehensive view of research on STEM education that might be useful for those researchers interested in advancing future knowledge in this area. © 2020, Springer Nature Switzerland AG.

关键词： visualization

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Evolution of the Socio-cognitive Structure of Knowledge Management(1986–2015): An Author Co-citation analysis

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Journal of data and Information Science 2019年第2期4卷 36-55页

作者： Carlos Luis González-Valiente Magda León Santos Ricardo Arencibia-Jorge Biblioteca Nacional de Cuba "José Martí" ave.Independencia Facultad de Comunicación Universidad de la Habana San Pedro entre Ermita y Avenida Independencia Empresa de Tecnologías de la Información

Purpose: The evolution of the socio-cognitive structure of the field of knowledge management(KM) during the period 1986–2015 is described. Design/methodology/approach: Records retrieved from Web of Science were submitted to author co-citation analysis(ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their ***: KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–*** limitations: Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM *** implications: These results might be useful for managers and academicians to understand the evolution of KM field and to(re)define research activities and organisational ***/value: The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.

关键词： Knowledge management Bibliometrics Author co-citation analysis Knowledge domain visualization Social network analysis Intellectual structure

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