http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
李俊煥 全北大學校 1987 論文集 Vol.29 No.-
To regulate the temperature of an electric furnace, a fuzzy algorithm is developed and implemented. Not only the fuzzy algorithm has good behavior to surpress temperature overshoot, but it can be easily modified according to the knowledge of operators of process, so as to have better control strategy.
Binary-Decision방식을 이용한 프로그래머블 콘트롤러의 개발에 관한 연구
田炳實,李俊煥,嚴景培 全北大學校 1987 論文集 Vol.29 No.-
The binary decision method can evalutate any switching function in the number of steps not exceeding the number of input variables. A programmable controller module is designed using this method so as to improve scan speed. A compiler system is also developed to relieve the memory problem which the binary decision method entails. A communication channel between MDS and PC modules is also constructed to load the compiled PC object program in to the memory of BD machine.
A New Information Fusion Method with γ-Model
Lee, Joon-Whoan 전북대학교 전자산업개발연구소 1990 전자산업연구 Vol.1 No.-
인간의 정보 융합을 흉내내기 위해서는 종래의 합(union)및 교(intersection) 연산자 이외에 보상(compensation) 특성을 갖는 연산자의 이용이 필요하다. 본 논문에서는 보상 연산자의 일종인 감마 연산자의 성질을 탐색하고, 이 연산자를 이용한 정보융합 방법을 제시하고, 실험을 통해 타당성을 입증하였다.
이준환 ( Joon Whoan Lee ),정성환 ( Sung Hwan Jeong ),노정옥 ( Jeong Ok Rho ),박근호 ( Keun Ho Park ) 한국감성과학회 2013 감성과학 Vol.16 No.4
본 연구의 목적은 한국어의 맛을 표현하는 형용사들을 수집하고 분석하여 정성적 관능형가에 사용할 주요 형용사 척도를 발굴하는 일이었다. 이를 위해 본 논문에서는 음식의 관능평가에 사용되는 맛, 질감, 온도감 및 냄새 등을 포함하는 우리말 형용사 92개를 선별하여 유사성을 평정하고, 이 형용사 사이의 상관관계를 이용하여 요인분석, 군집분석 등을 실시하였다. 요인분석 결과 한국어에서 음식들의 맛을 표현하는 형용사를 설명하는 요인은 10개 이상으로 다양하였으며, 군집분석 결과 맛 표현 형용사는 보편적인 맛 표현 형용사, 부정적인 맛 표현 형용사, 음식의 질감, 온도감, 냄새 등을 표현하는 형용사 군 등으로 군집화 할 수 있음을 알 수 있었다. 또한 맛의 선호도에 해당하는 긍정적이거나 부정적인 맛을 표현하는 형용사들과 군집분석 결과로부터 얻어진 군집 대표 형용사들과의 관계역시 상관계수를 이용하여 분석하였다. 이러한 분석 결과는 향후 축약된 맛에 대한 관능평가 형용사 척도 발굴에 있어서는 음식 종류를 한정하여야 함을 의미할 수 있다. The purpose of this study was to find out the adjective scales, which will be used in the qualitative sensory evaluation of taste, by collecting and analyzing adjectives of expressing taste of Korean language. For the purpose, we rated the mutual similarities among selected 92 adjectives which include the sense of taste, texture, smell and temperature from foods, and then carried out factor analysis and clustering analysis by using correlation based on the similarities. According to the factor analysis there are more than 10 important factors involved in the linguistic representation of taste including food temperature, texture and smell as well as taste. Also, from the cluster analysis, we found that the adjectives can be clustered with groups of the adjectives representing general taste, negative taste, texture and temperature of food. In addition we analyzed the correlation between the adjectives to represent the generic preference of taste and the adjectives to express individual factors of the preferences that are resulted from cluster analysis. The analysis results could show that we need to restrict the type of foods to find out the meaningful limited number of sensory adjective scales for taste in the future.
고정밀 위성영상에서 도심지역 건물변화 탐지를 위한 중첩방법
이승희 ( Seung Hee Lee ),박성모 ( Sung Mo Park ),이준환 ( Joon Whoan Lee ),김준철 ( Joon Cheol Kim ) 大韓遠隔探査學會 2003 大韓遠隔探査學會誌 Vol.19 No.4
고정밀 위성영상의 자동분석은 지도제작, 감시, 자원탐사 등을 효율적으로 수행하는데 있어 중요하다. 그러나, 도심지역의 고정밀 위성영상의 자동분석은 그림자, 분광정보의 시변성, 영상의 복잡성 등 때문에 현재의 기술로 해결하기 어려운 부분들이 산재해 있다. 본 논문에서는 디지털 수치지도 상의 건물객체들을 고정밀 위성영상에 중첩하여 도심지역의 건물들의 변화 탐색을 용이하게 하는 방법을 제안한다. 제안된 방법에서는 수치지도상의 건물들을 매개변수화 하고, 전처리된 고정밀 위성영상에서 일반화된 Hough 변환 방법을 이용하여 탐색하고, 탐색된 부분에 중첩시킨다. 중첩 된 영상은 건물들의 변화 여부를 빠르게 찾는데 도움을 줄 수 있다. The automatic analysis of high-resolution satellite image is important in cartography, surveillance, exploiting resources etc. However, the automatic analysis of high resolution satellite image in the urban area has lots of difficulty including a shadow, the difference of illumination with time, the complexity of image so that the present techniques are seemed to be impossible to resolve. This paper proposes a new way of change detection of building objects in urban area, in which the objects in digital vector map are designated and superimposed on the high-resolution satellite image. The proposed way makes the buildings on the vector map parameterize, and searches them in the preprocessed high-resolution satellite image by using generalized Hough transform. The designated building objects are overlaid on the satellite image and the result can help to search the changes in building objects rapidly.
Vector Switching Function 의 일반화 및 단순화에 관한 연구
李俊煥,金準哲 전북대학교 공업기술연구소 1986 工學硏究 Vol.17 No.-
In this paper, we show that the vector switching function, which I used for the representation and design of multi-bus digital system, can be extended to represent the combinational logic which has not the same number of outputs as the dimension of a input space. We also show that the canonical forms, proposed by Samuel C. Lee, can have simplified forms which reduce the number of gates when a vector switching function is realized.
Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition
( Deepak Ghimire ),( Joon Whoan Lee ) 한국정보처리학회 2014 Journal of information processing systems Vol.10 No.3
An extreme learning machine (ELM) is a recently proposed learning algorithm for a single-layer feed forward neural network. In this paper we studied the ensemble of ELM by using a bagging algorithm for facial expression recognition (FER). Facial expression analysis is widely used in the behavior interpretation of emotions, for cognitive science, and social interactions. This paper presents a method for FER based on the histogram of orientation gradient (HOG) features using an ELM ensemble. First, the HOG features were extracted from the face image by dividing it into a number of small cells. A bagging algorithm was then used to construct many different bags of training data and each of them was trained by using separate ELMs. To recognize the expression of the input face image, HOG features were fed to each trained ELM and the results were combined by using a majority voting scheme. The ELM ensemble using bagging improves the generalized capability of the network significantly. The two available datasets (JAFFE and CK+) of facial expressions were used to evaluate the performance of the proposed classification system. Even the performance of individual ELM was smaller and the ELM ensemble using a bagging algorithm improved the recognition performance significantly.