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Dijkstra의 mini 언어를 Pascal로 변환할 경우 병렬 치환문의 처리
이수현(Lee Su-Hyun),최광무(Choe Kwang-Moo) 한국정보과학회 1988 한국정보과학회 학술발표논문집 Vol.15 No.1
Mini 언어는 Dijkstra가 설계한 언어로서 병렬 치환문(concurrent assignment), 비결정적 수행(guarded command)등의 특징을 가진 block-structured 언어이다. 본 논문에서는 mini 언어로 작성된 프로그램을 Pascal 프로그램으로 변환시켜 주는 변환기를 설계하였고 변환된 프로그램을 수행시켜 보았다. 특히 병렬 치환문을 일련의 순차 치환문으로 바꾸는 과정에서 임시 변수를 줄이는 문제에 대하여 고찰하여 보았다.
이수현(Su-Hyun Lee) 한국컴퓨터정보학회 2017 韓國컴퓨터情報學會論文誌 Vol.22 No.1
In recent years there has been a rise in the use and interest of the flipped learning as a teaching and learning paradigm. The flipped learning model includes any use of Internet technology to enrich the learning in a classroom, so that a professor can spend more time interacting with students instead of lecturing. In the flipped model, students viewed video lectures online outside of class time. Students then performed two kinds of assignments, a teamwork assignment and an individual work assignment, through the class time. In this paper, we propose a flipped educational model for a college class. This experimental research compares class of college algorithm using the flipped classroom methods and the traditional lecture-homework structure and its effect on student achievement. The result data of mid-term exam and final exam were analyzed and compared with previous year data. The findings of this research show that there was not a significant difference in the scores of student between two lecturing methods. The survey result and lecture evaluation by students show that students are in favor of the flipped learning.
데이터마이닝 기법을 활용한 비외감기업의 부실화 유형 분석
이수현(Su Hyun Lee),박정민(Jung Min Park),이형용(Hyoung Yong Lee) 한국지능정보시스템학회 2015 지능정보연구 Vol.21 No.4
There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms’ distress prediction in the future.
이수현(Lee Su-Hyun),이재홍(Lee, Jae-Hong) 대한건축학회 2011 大韓建築學會論文集 : 構造系 Vol.27 No.11
This paper presents form-finding of Tensegrity structures by using Force method. The Force method is generalized to all types of skeletal structures, such as rigid-jointed frames, pin-jointed planar trusses and ball-jointed space trusses. This method has easier basic concept, which is based on equilibrium equation, than Finite Element Method. In addition, this method is appealing to engineers because the properties of members of structures most often depend on the member force than joint displacement. Therefore, this study applies to analyze about form-finding of Tensegrity structures by using Force method’s merit.
지역난방 방식 건축물의 난방 급탕 통합배관 시스템 실증연구
이수현(Su Hyun Lee),안희수(Hui su Ahn),김성범(Seong Beom Kim),홍영기(Young Gi Hong) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.11
The purpose of this study is to verify the efficiency of the integrated piping system that has been recently distributed in Korea through empirical research. The peak and average usage of the integrated pipe system was lower than that of the 4-pipe system, and the primary return temperature of the district heating was maintained at an appropriate temperature. In addition, the heat return temperature of the HIU(Heat interface unit) installed in the integrated pipe system was maintained at a low temperature to prove its efficiency.
이수현(Su-Hyun Lee) 한국컴퓨터정보학회 2016 한국컴퓨터정보학회 학술발표논문집 Vol.24 No.1
본 연구에서는 컴퓨터공학의 대표적인 교과목인 알고리즘 교과목에 대하여 거꾸로 학습을 적용한 결과를 보여준다. 학생들은 집에서 온라인 컨텐츠로 학습을 하고 수업 시간에는 숙제를 수행하는 방식으로 수업을 진행하였다. 수업시간에 진행하는 과제는 그룹 과제와 개인 과제로 구성되어 있어, 토론을 활성화 하여 학습 효과를 높이도록 하였다. 성과 분석 결과, 거꾸로 학습이 전통적인 수업에 비하여 동등하거나 또는 더 나은 효과가 있음을 보여 주었다.
Intelligent Backtracking의 대수학적 모델
이수현(Lee Su-Hyun),최광무(Choe Kwang-Moo) 한국정보과학회 1992 한국정보과학회 학술발표논문집 Vol.19 No.2
Chang의 정적인 자료종속 관계분석(static data dependency analysis)을 기본으로 하는 효율적인 백트랙킹 방법의 대수학적 모델을 제안하였다. 대수학적 모델의 기초로는 Milner의 Calculus of Communicating Systems(CCS)를 사용하였다. 이러한 접근방법을 이용하면 백트랙킹에 대한 수학적이고 정형적(formal)인 접근이 가능하다.
이수현(Su-Hyun Lee),김윤구(Yun-Gu Kim),김영진(Yung-Jin Kim),정용진(Yong-Jin Jeong) 대한전자공학회 2007 대한전자공학회 학술대회 Vol.2007 No.7
본 논문에서는 실시간 처리를 위한 얼굴 검출 임베디드 시스템을 설계하고 검증하였다. 얼굴 검출 시스템을 설계하기위해 새로운 MCT(Modified Census Transform) 기반의 얼굴 검출 알고리즘을 사용하였다. 해당 알고리즘을 하드웨어 설계를 위하여 기능별로 10개의 모듈로 구분하고, 11개의 내부 SRAM을 설계하였으며, 입력영상 및 필터 정보를 저장하기 위하여 외부 SDRAM을 사용하였다. 삼성전자의 S3C2440A 프로세서를 사용한 EMlinux사의 Bluesky 보드와 Xilinx사의 Virtex4LX60을 이용하여 플랫폼을 구축하고, USB 카메라를 통하여 실제 얼굴의 영상을 입력받아 얼굴 검출을 실시간으로 구동시켜 검증하였다.