DGIST Deep Dive 2013~2022 : Dept. of Robotics and Mechatronics Engr.,
DGIST 로봇및기계전자공학과의 논문 출판 동향은? 로봇및기계전자공학과 진학을 고민 중이거나, 연구 결과를 발표할 투고 저널을 선택 중이라면 클릭하세요! 2013-2022 10년 간의 논문 분석을 통해 DGIST 로봇및기계전자공학과의 인기 주제와 저널, 영향력 높은 논문 등을 소개합니다! ※ 피인용 관련 지수 기준일: 2023.11.10.
 
 
 
Q. What is FWCI? (상대적 피인용 지수 의미)
Field-Weighted Citation Impact is the ratio of the total citations actually received by the denominator output and the total citations expected based on the average of the subject field. 

A Field-Weighted Citation Impact of: 
 - Exactly 1 means that the output performs just as expected for the global average.
 - More than 1 means that the output is more cited than expected according to the global average. For example, 1.48 means 48% more cited than expected.
 - Less than 1 means that the output is cited less than expected according to the global average. 

Field-Weighted Citation Impact takes into account the differences in research behavior across disciplines. It is particularly useful for a denominator that combines a number of different fields, although it can be applied to any denominator: Researchers working in fields such as medicine and biochemistry typically produce more output with more co-authors and longer reference lists than researchers working in fields such as mathematics and education; this is a reflection of research culture and not performance. In a denominator comprising multiple disciplines, the effects of outputs in medicine and biochemistry dominate the effects of those in mathematics and education. This means that using non-weighted metrics, an institution that is focused on medicine will appear to perform better than an institution that specializes in social sciences. The methodology of Field-Weighted Citation Impact accounts for these disciplinary differences.

Field-Weighted Citation Impact is sourced directly from SciVal. The data in SciVal is updated every week. SciVal makes a copy of the Scopus database and then structures it to optimally support its metrics and functionality. This means that SciVal data may be slightly behind Scopus in its data currency. 
FWCI Manual
FWCI Top 5 Publications (상대적 피인용지수 상위 5개 문헌)
Prof. Hongsoo Choi (최홍수 교수)
- corresponding author, FWCI 16.77
Jeon, S., Kim, S., Ha, S., Lee, S., Kim, E., Kim, S. Y., ... & Choi, H. (2019). Magnetically actuated microrobots as a platform for stem cell transplantation. Science Robotics, 4(30), eaav4317.
Read the article
Prof. Hoe Joon Kim (김회준 교수)
- corresponding author, FWCI 15.45
Panda, S., Hajra, S., Mistewicz, K., Nowacki, B., In-Na, P., Krushynska, A., ... & Kim, H. J. (2022). A focused review on three-dimensional bioprinting technology for artificial organ fabrication. Biomaterials Science, 10(18), 5054-5080.
Read the article
Prof. Kyung In Jang (장경인 교수) - lead author, FWCI 11.13
Jang, K. I., Li, K., Chung, H. U., Xu, S., Jung, H. N., Yang, Y., ... & Rogers, J. A. (2017). Self-assembled three dimensional network designs for soft electronics. Nature Communications, 8(1), 15894.
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Prof. Sang Hyun Park (박상현 교수) - corresponding author, FWCI 10.17
Shoaib, M., Hussain, T., Shah, B., Ullah, I., Shah, S. M., Ali, F., & Park, S. H. (2022). Deep learning-based segmentation and classification of leaf images for detection of tomato plant disease. Frontiers in Plant Science, 13, 1031748.
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Prof. Sang Hyun Park (박상현 교수) - corresponding author, FWCI 10.17
Chikontwe, P., Kim, M., Nam, S. J., Go, H., & Park, S. H. (2020). Multiple instance learning with center embeddings for histopathology classification. In Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V 23 (pp. 519-528). Springer International Publishing.
Read the article
 
 
Q. Topic Clusters (주요 연구 주제)
A Topic is a collection of documents with a common focused intellectual interest, and Scopus publications are clustered into Topics based upon a direct citation analysis. 

Topic Clusters are formed by aggregating Topics with similar research interests together to form a broader, higher-level area of research. Each of the 96,000 Topics has been matched with one of the 1,500 Topic Clusters. 

Calculating a Topic’s Prominence combines 3 metrics to indicate the momentum of the Topic: 
1. Citation Count in year n to papers published in n and n-1 
2. Scopus Views Count in year n to papers published in n and n-1 
 3. Average CiteScore for year n
SciVal & Evaluation Metrix
Keyphrase analysis (키워드 분석)
(Word Cloud) Top 50 keyphrases by relevance, based on 688 publications