Best Researcher Award

Yutong Chun — China Energy Investment Corporation Limited

Yutong Chun
Affiliation China Energy Investment Corporation Limited
Country China
Scopus ID 57211643822
Documents 11
Citations 156
h-index 6
Subject Area Green Technology
Event Technology Scientists Awards

Yutong Chun is presented in this profile as a researcher affiliated with China Energy Investment Corporation Limited, with a stated research focus on green technology. The supplied publications cover green development assessment in coal-resource-based cities, electrical equipment condition monitoring, and automated face-mask detection. These topics connect environmental sustainability with industrial monitoring and applied technological development. [1] [2] [3]

Abstract

This article presents a research profile of Yutong Chun, whose supplied publication topics span environmental sustainability, industrial equipment monitoring, and automated visual detection. Particular attention is given to green development assessment in coal-resource-based cities and the application of computational methods to practical challenges. The profile summarizes the provided bibliographic information and its relevance to technology research. [1]

Keywords

  • Green technology
  • Sustainable development
  • Coal-resource-based cities
  • Condition monitoring
  • Automated visual detection
  • Applied computing

Introduction

Green technology supports more sustainable industrial systems through resource efficiency, environmental assessment, and technological innovation. Research on coal-resource-based cities can help identify barriers to balanced development, while monitoring systems can improve equipment oversight. Automated detection methods illustrate additional applications of computing to practical challenges, collectively reflecting multidisciplinary approaches to contemporary technological problems. [1] [2]

Research Profile

The supplied publication list associated with Yutong Chun spans environmental development evaluation, electrical module condition monitoring, and computer-vision-based detection. These themes suggest an applied research orientation connecting industrial systems with analytical and computational methods. The provided profile records 11 documents, 156 citations, and an h-index of 6; these figures should be checked against the current Scopus record. [1] [2] [3]

Research Contributions

The listed studies address three distinct technical areas: evaluating green development and its obstacles, detecting electrical module conditions through component monitoring, and identifying face-mask wearing conditions using automated detection. Together, these topics illustrate the potential of assessment frameworks, monitoring technologies, and computer vision to support environmental analysis, equipment oversight, and practical decision-making across different application settings. [2] [3]

Publications

The three supplied publications provide the basis for this profile. They cover electrical module condition monitoring, green development assessment in coal-resource-based cities, and automated detection of face-mask wearing conditions. The original publisher records should be consulted to confirm complete author lists, publication dates, journal or conference details, pagination, and DOI information before formal citation or bibliographic reuse. [1] [2] [3]

Research Impact

The listed research topics have potential relevance to industrial reliability, urban sustainability, and automated visual analysis. Green development assessments can inform planning and policy discussions, while condition-monitoring and detection systems may support operational decision-making. The actual influence of these studies should be evaluated using verified citation records, documented adoption, methodological quality, and evidence of practical outcomes. [1] [2]

Award Suitability

The supplied publications offer potential grounds for considering Yutong Chun for a Best Researcher Award in a technology-focused program. Their topics connect sustainability assessment with applied engineering and computational detection. A balanced award evaluation should additionally verify authorship, individual contributions, publication quality, originality, research outcomes, and bibliometric indicators against reliable independent records. [1] [3]

Conclusion

Yutong Chun’s supplied publication topics span green development assessment, electrical equipment monitoring, and automated visual detection. These areas demonstrate the breadth of applications addressed by contemporary technology research and offer a basis for an academic recognition profile. Before publication, the researcher’s affiliation, article metadata, authorship, and Scopus metrics should be independently verified. [1] [2] [3]

References

  1. An online detection system for electrical modules based on electronic component condition monitoring. (n.d.). In IEEE Xplore. Institute of Electrical and Electronics Engineers.
    https://ieeexplore.ieee.org/document/11515099
  2. Green development assessment and obstacle analysis of coal-resource-based cities. (n.d.). In ScienceDirect. Elsevier.
    https://www.sciencedirect.com/science/article/pii/S2405844023097037
  3. A novel detection framework about conditions of wearing face mask for helping control the spread of COVID-19. (n.d.). In IEEE Xplore. Institute of Electrical and Electronics Engineers.
    https://ieeexplore.ieee.org/document/9380283
  4. Elsevier. (n.d.). Scopus author details: Yutong Chun, Author ID 57211643822. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57211643822
Yutong Chun | Green Technology | Best Researcher Award

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