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대형 액상분사식 LPG 엔진의 희박연소특성에 관한 연구
오승묵,김창업,이진욱,김창기,강건용,배충식,O, Seung-Muk,Kim, Chang-Eop,Lee, Jin-Uk,Kim, Chang-Gi,Gang, Geon-Yong,Bae, Chung-Sik 한국기계연구원 2003 硏究論文集 Vol.33 No.-
Fuel distribution, combustion, and flame propagation characteristics of heavy duty engine with the liquid phase LPG injection(LPLI) were studied in a single cylinder engine. Optically accessible single cylinder engine and laser diagnostics system were built for quantifying fuel concentration by acetone PLIF(planar laser induced fluorescence) measurements. In case of Otto cycle engine with large bore size, the engine knock and thermal stress of exhaust manifold are so critical that lean burn operation is needed to reduce the problems. It is generally known that fuel stratification is one of the key technologies to extend the lean misfire limit. The formation of rich mixture in the spark plug vicinity was achieved by open valve injection. With higher swirl strength(Rs=3.4) and open valve injection, the cloud of fuel followed the flow direction and the radial air/fuel mixing was limited by strong swirl flow. It was expected that axial stratification was maintained with open-valve injection if the radial component of the swirling motion was stronger than the axial components. The axial fuel stratification and concentration were sensitive to fuel injection timing in case of Rs=3.4 while those were relatively independent of the injection timing in case of Rs2.3. Thus, strong swirl flow could promote desirable axial fuel stratification and, in result, may make flame propagation stable in the early stage of combustion.
텍스트마이닝(Text mining)을 활용한 한의학 원전 연구의 가능성 모색 -黃帝內經에 대한 적용례를 중심으로 -
배효진(Bae Hyo-jin),김창업(Kim Chang-eop),이충열(Lee Choong-yeol),신상원(Shin Sang-won),김종현(Kim Jong-hyun) 대한한의학원전학회 2018 대한한의학원전학회지 Vol.31 No.4
Objectives : In this paper, we investigated the applicability of text mining to Korean Medical Classics and suggest that researchers of Medical Classics utilize this methodology. Methods : We applied text mining to the Huangdi’s internal classic, a seminal text of Korean Medicine, and visualized networks which represent connectivity of terms and documents based on vector similarity. Then we compared this outcome to the prior knowledge generated through conventional qualitative analysis and examined whether our methodology could accurately reflect the keyword of documents, clusters of terms, and relationships between documents. Results : In the term network, we confirmed that Qi played a key role in the term network and that the theory development based on relativity between Yin and Yang was reflected. In the document network, Suwen and Lingshu are quite distinct from each other due to their differences in description form and topic. Also, Suwen showed high similarity between adjacent chapters. Conclusions : This study revealed that text mining method could yield a significant discovery which corresponds to prior knowledge about Huangdi’s internal classic. Text mining can be used in a variety of research fields covering medical classics, literatures, and medical records. In addition, visualization tools can also be utilized for educational purposes.
한의학에서 딥러닝의 뜻밖의 역할: 딥러닝의 과학으로 한의학 이해하기
배효진(Hyojin Bae),김창업(Chang-Eop Kim) 대한미병의학회 2023 대한미병의학회지 Vol.4 No.1
Deep learning is revolutionizing in many scientific fields today. When it comes to Traditional Korean Medicine(TKM), it is commonly expected that deep learning will be able to assist TKM doctors to diagnose and prescribe treatments. We believe, however, there is another way to revolutionize TKM using deep learning. Mathematically, deep learning is a universal approximation function and can be a powerful model that explains cognitive processes in the brain. Since all of the decision-making processes in TKM are cognitive processes in the TKM doctors’ brain, they could also be modeled and explained using deep learning framework. As the science of deep learning advances, we will be able to better understand TKM through deep learning framework.
장동엽(Dongyeop Jang),김창업(Chang-Eop Kim) 대한미병의학회 2020 대한미병의학회지 Vol.1 No.1
Objectives With the development of the Internet of things and big data, it becomes possible to analyze large medical records. However, a lack of data and a risk of private information disclosure act as a barrier to this possibility, and generating synthetic patient records can be used as an alternative to circumvent this limitation. In this paper, we reviewed the researches on the rapidly developing synthetic patient records. Methods We searched for articles that studied the synthetic patient records and sorted them according to data types, generation methods and evaluation methods. Results The types of synthetic patient data could be largely divided into binary, ordinal, image, and sequential data. But the studies of models that could handle a dataset of several mixed types were relatively scarce, and more researches are needed. In terms of generation methods, researches could be divided into researches about rule-based models and data- driven model, and the data-driven models could be divided into classical machine learning and deep learning models. The criteria for evaluating the model were largely the reproducibility and risk of privacy disclosure. Both quantitative evaluation and qualitative evaluation were used to evaluate the reproducibility, on the other hand, most the studies lacked privacy assessments and it needs to be supplemented in future studies. Conclusions Applying methods for generating synthetic patient records to Korean traditional medical data will facilitate the data science researches of Korean traditional medicine and this can be an opportunity to understand the structure of Korean traditional medical data.
Correlation 분석 기법을 적용한 요통 환자에 관한 레지스트리 데이터의 탐색적 분석
박창현,박무순,김형석,차윤엽,김순중,고연석,오민석,황의형,신병철,김창업,송윤경,Park, Chang-Hyun,Park, Mu-Sun,Kim, Hyung-Suk,Cha, Yun-Yeop,Kim, Soon-Joong,Ko, Youn-Suk,Oh, Min-Seok,Hwang, Eui-Hyoung,Shin, Byung-Cheul,Kim, Chang-Eop,Song 한방재활의학과학회 2017 한방재활의학과학회지 Vol.27 No.4
Objectives The aim of this study is to analyze the patients who have low back pain through registry. Methods We registered patients with low back pain who visited department of korean rehabilitation medicine in university hospitals on study. We collected data from 116 subjects consisted of 51 inpatients and 65 outpatients and ruled out 8 who didn't have pattern identification data at the point of inpatient or outpatient visit so we analyzed 108 in total. We used Pearson's product moment correlation to find correlationship among variables, and analyzed statistical data using Phyton scipy library stats package. Results We set general features, region of the pain, physical examination, ROM, questionnaire results, pattern identification as variables and draw a conclusion by analyzing these variables. Conclusions Registry aimed at low back pain patients was established in department of korean rehabilitation medicine of university hospitals and exploratory analysis based on data were made. Through the registry, we expect that more advanced studies will be performed; for example, executing research which verifies effectiveness and stability of korean medical treatment or developing tools to fill the gap between pattern identification and disease identification.