DGIST Deep Dive 2013~2022 : Dept. of EECS
DGIST 전기전자컴퓨터학과의 논문 출판 동향은? 전기전자컴퓨터학과 진학을 고민 중이거나, 연구 결과를 발표할 투고 저널을 선택 중이라면 클릭하세요! 2013-2022 10년 간의 논문 분석을 통해 DGIST 전기전자컴퓨터학과의 인기 주제와 저널, 영향력 높은 논문 등을 소개합니다! ※ 피인용 관련 지수 기준일: 2023.11.2
 
 
 
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. Sungjin Lee (이성진 교수)
- corresponding author, FWCI 8.82
Im, J., Bae, J., Chung, C., & Lee, S. (2020). PinK: High-speed In-storage Key-value Store with Bounded Tails. In 2020 USENIX Annual Technical Conference (USENIX ATC 20) (pp. 173-187).
Read the article
Prof. Jae Youn Hwang (황재윤 교수)
- corresponding author, FWCI 8.34
Lee, H., Park, J., & Hwang, J. Y. (2020). Channel attention module with multiscale grid average pooling for breast cancer segmentation in an ultrasound image. IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 67(7), 1344-1353.
Read the article
Prof. Jin Ho Chang (장진호 교수) - corresponding author, FWCI 7.76
Jang, Y., Kim, H., Yoon, S., Lee, H., Hwang, J., Jung, J., ... , Chang, J. H., Choi, J. & Kim, H. (2021). Exosome-based photoacoustic imaging guided photodynamic and immunotherapy for the treatment of pancreatic cancer. Journal of Controlled Release, 330, 293-304.
Read the article
Prof. Yongsoon Eun (은용순 교수) - corresponding author, FWCI 6.40
Park, J., Lee, B. H., & Eun, Y. (2020). Virtual coupling of railway vehicles: Gap reference for merge and separation, robust control, and position measurement. IEEE Transactions on Intelligent Transportation Systems, 23(2), 1085-1096.
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Prof. Yeseong Kim (김예성 교수) - corresponding author, FWCI 6.39
Hernández-Cano, A., Kim, Y., & Imani, M. (2021, February). A framework for efficient and binary clustering in high-dimensional space. In 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1859-1864). IEEE.
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 878 publications