The purpose of this study is to compare and analyze the impact range of explosion damage due to gas leaks at LPG filling stations, focusing on propane and butane, which are components of vehicle LPG. The scenarios were designed based on the explosion incident at an LPG filling station in Gangwon-do, where an actual gas leak accident occurred, resulting in Scenario I and Scenario II. The ALOHA program, developed by the U.S. National Oceanic and Atmospheric Administration (NOAA), was used as the tool to analyze the impact range of the explosion damage for both substances. The results of the study indicated that, under identical conditions, propane had a wider impact range of damage than butane. This is presumed to be due to the greater explosion energy of propane, attributable to its physicochemical properties. Therefore, when preparing for LPG leak accidents, measures for propane need to be prioritized. As safety measures for propane, two suggestions were made to minimize human casualties. First, from a preventive perspective, it is suggested to educate workers about propane. Second, from the perspective of response measures and damage minimization, it is suggested to thoroughly prepare emergency evacuation and rescue plans, evacuation routes, designated shelters, and emergency response teams. This study compares and analyzes the impact range of radiative heat damage based on LPG components. However, hazardous accidents are critically influenced by the type of leaking substance, the form of the leak, and meteorological factors affecting the diffusion pattern of the substance. Therefore, for future research, it is proposed to model various leakage scenarios for the same substance to conduct a comprehensive risk assessment.

The purpose of this study is to compare and analyze the flame retardant performance of Japanese cypress(Chamaecyparis obtusa) plywood, commonly used in indoor decoration, furniture, and tableware, by treating it with three different fire retardants with different primary ingredients. The experiment was conducted in compliance with Article 31, Paragraph 2 of the Enforcement Decree of the Fire Facilities Installation and Management Act and Articles 4 and 7-2 of the Flame Retardant Performance Standards. After flame time, after glow time, char length, and char area were measured. As a result, first, after flame time was measured at 0 seconds regardless of whether the flame retardant treatment was applied. Second, after glow time was relatively long, measuring 22.7 seconds without treatment, which is likely due to the weak fire resistance and high concentration of carbon monoxide generated by the chemical characteristics of the Japanese cypress itself. Third, it was confirmed that the effects of the primary ingredient, phosphorus, in the flame retardant treatment varied depending on the technological development of the manufacturers of the same species of Japanese cypress plywood. In the future, it is expected that the results of this study will provide fundamental data to select flame retardant treatments that show high flame retardant performance according to the botanical characteristics of the wood.

In this paper the potential of the principal component analysis(PCA) technique for the application of detecting leaks in water pipe networks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study which were designed to extract a partial set of flow data from the original 24 hour flow data so that the effective outlier detection rate was maximized. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The developed algorithm may be applied in determining further leak detection field work for water distribution blocks that have more than 70% of the effective outlier detection rate. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks by considering series of leak reports happening in a relatively short period.

This study was applied to the PCA (Primary Components Analysis) for the sixteen table setting at the 2017 Yeongju local food contest. In this contest, we have developed a seonbibansang and a temple one-dish meal. As a result of the correlation analysis, the applicability and composition were 0.7980, harmony and taste were 0.7747 and easiness and composition were 0.7435. In the Primary Component Y1, all the variables X1…X10 mean that the quality of the food had positive values greater than zero. The second Primary Component Y2 has a large positive value while X4, X5, X6, X7, X9 have negative values. Y2 is a value representing the sanitation variable, and can be considered a traditional and characteristic table setting natural to the native food in Yeongju. In addition, we developed an-hyangbansang and seonmyoaecheong food content by applying PCA factors (the elements of harmony, ease and sanitation). Table setting of an-hyangbansang provided energy 61.5%, protein 20.0% and fat 18.5% and seonmyoaecheong provided energy 62.7%, protein 15.4% and fat 22.2%. This satisfied the necessary amount of caloric nutrient intake that could be provided in a meal. Especially through story-telling, a modern interpretation - or rebranding - of local and traditional foods could make these traditional food products familiar to consumers currently. The developed table setting is felt to be conductive to the possible commercialization and introduction of traditional food into the mainstream commercial food service industry.

The changes in the aroma and spoilage odor emitted from eleven ‘Hongro’ apples during ten weeks’ storage were investigated using six types of metal oxide semiconductor gas sensor arrays. The gas sensors used in the evaluation were sensitive to apple-emitted aroma or spoilage odor, and a high reproducibility of 5% relative standard deviation or less was confirmed. Significantly, the change in apple-emitted aroma or spoilage odor was easily distinguished by the optimal gas sensor and a significant correlation (r=0.992) between decay rate and sensitivity change was observed. The results of a principal component analysis of the signal patterns obtained by data standardization using the optimal gas sensor showed a clear classification between decayed sampler groups and undecayed sampler groups.

In this paper, we investigate how the power consumption of a heat pump dryer depends on various factors in the drying process by analyzing variables that affect the power consumption. Since there are in general many variables that affect the power consumption, for a feasible analysis, we utilize the principal component analysis to reduce the number of variables (or dimensionality) to two or three. We find that the first component is correlated positively to the entrance temperature of various devices such as compressor, expander, evaporator, and the second, negatively to condenser. We then model the power consumption as a multiple regression with two and/or three transformed variables of the selected principal components. We find that fitted value from the multiple regression explains 80~90% of the observed value of the power consumption. This results can be applied to a more elaborate control of the power consumption in the heat pump dryer.

최근 사용자 제작 콘텐츠(UCC)를 포함한 다양한 콘텐츠의 생산으로 인해 데이터의 저장 및 재생성 과정에서 원본과 다른 데이터로 변형되는 경향이 있다. 특히 UCC의 경우 해상도 측면에서 화질의 저하가 발생되는데, 이때 발생되는 것이 바로 블록형 재깅 결함이다. 본 논문은 해상도의 급격한 변화가 있을 때 발생하는 블록형 결함을 제거하기 위하여 주성분 분석방법과 은닉 마코프 모델을 기반으로 블록형 재깅 결함을 제거하는 방법을 제안한다. 실험을 통해 제안한 방법은 기존 방법들에 비해 디테일을 유지하면서도 재깅 결함을 효과적으로 제거함을 확인하였다.

Although the history of the game of Go is more than 2,500 years, the theoretical studies of Go are still insufficient. In recent years a lot of studies using Artificial Intelligent (AI) have been conducted, but they do not provide the prominent theoretical reality. We applied traditional Principal Component Analysis (PCA) algorithm to the Go openings, which are the early stage in Go, to analyze them especially focused on the Go game records of the Korean top 10 professional Go players. We firstly analyzed the number of most significant eigenvectors capturing most of variance. Experimental result shows that among the 361 eigenvectors the eight most significant eigenvectors capture most of the variance (96.2%). We secondly used PCA classifier with Euclidean distance to recognize a pro player's opening to a class obtained from the training openings. Result shows that the best average recognition rate of 22% is so much lower than the recognition rates reported in face recognition research.

The taxonomy of the Isodon excisus complex, which comprises I. inflexus var. inflexus, var. transiticus, var. macrophyllus, var. microphyllus, and var. canescens, has been ambiguous and problematic because their morphological characters are variable. To elucidate the taxonomic structure of the I. inflexus complex in Korea, 42 characters were measured from 70 OTUs representing the I. inflexus complex and were analyzed by a principle component analysis (PCA). The principle component axes 1, 2, and 3 (PC1, PC2, and PC3) represents 55.7% of the total variance. The characters showing high loading values for PC1, which have of absolute loading values higher than 0.7, were characters related to the leaf base and leaf teeth and the length of corolla tube. The length of the broadest part to the apex in the leaf, the density of non-glandular hairs on the lower surface of the leaf, and the length and width of the calyx were highly related to PC2 with the absolute loading values higher than 0.7. PC3 does not have any characters which have absolute loading values higher than 0.5. Three-dimensional scatter plots of the OTUs for the PC1, PC2, and PC3 axes showed that there are three taxa in the complex. Each area of I. inflexus var. inflexus, var. transiticus, and var. macrophyllus was completely overlapped, demonstrating that this taxon is I. inflexus var. inflexus. Areas for var. microphyllus and var. canescens were separated from that of var. inflexus in both cases. Therefore, we recognized three varieties, which are I. inflexus var. inflexus, var. microphyllus and var. canescens in the I. inflexus complex in Korea. This result also indicates that I. inflexus var. inflexus has a wide range of morphological variation. The recognition of var. microphyllus and var. canescens is also supported by the result of recent SEM studies of the fruit surfaces of Korean Isodon.

이 연구는 입목축적과 산림관리정책 간의 전이함수(transfer function model)를 도출하기 위한 선행연구로, 입목축적변화를 유도하는 산림사업 간 다중공선성의 문제를 해결하기 위해 주성분 분석을 실시하였다. 분석자료는 9개의 대표적인 산림관리정책에 대해 1977~2008년까지 32년간의 연도별 시계열데이터를 활용하였으며, 분석 결과 추출된 3개의 주성분에 대한 전체 설명력은 91.4％로 상당히 높게 나타났다. 요약된 3개의 성분은 양호한 산림관리·병해충관리·산불발생이라는 새로운 변수명으로 개념화하였다.

본 논문에서는 쪽을 이용한 천연염색에서 염색의 횟수에 따른 발색 재현 기술을 개발함으로써 반복 염색에 따른 발색 시뮬레이터의 개발에 기여하고자 한다. 천연염료로는 쪽을 사용하였고 염색의 매질로는 닥원료를 사용하였다. 닥원료를 1회에서 70회까지 반복하여 염색한 닥죽을 만들고 이를 제지하여 천연염색된 감지(紺紙)를 제작하였다. 원지로부터 반복 염색된 감지의 발색을 재현하기 위하여 주성분 분석법을 이용하였다. 주성분 분석을 위해 모집단으로는 멘셀색시료를 사용하였으며 RGB카메라를 고려하여 3개의 기저함수로 부터 직물의 분광반사율을 모델링하였다. 그리고 닥원료로 만든 원지(原紙)와 염색된 감지의 분광반사율을 기저함수의 선형조합으로 표현하고 이로부터 염색횟수에 따른 감지의 분광 반사율의 변화를 예측하기 위한 감쇄함수를 구하는 방법을 제안하였다. 제안된 방법의 성능평가를 위해 염색 횟수별로 실제 염색한 감지와 원지로 부터 예측한 영상을 비교하고 정량적인 색차평가를 수행하였다. 결과 반복 염색시 재현성이 일정하다는 가정에서 색차 1미만의 범위에서 천연염색에 따른 감지의 발색을 재현 할 수 있음을 확인하였다.

  이 논문은 자동차 차체 조립과정에서, 품질관리의 일환으로써, 비접촉 자동측정시스템을 이용하여 검사해야 하는 수많은 비독립적인 검사점을 다변량분산분석과 주성분분석을 이용하여 효율적으로 검사점을 감소시키는 방법을 설명하고 있다. 이 연구의 목적은 다변량분산분석, 주성분 분석의 개념과 이러한 기법들을 산업체 제조분야에서 응용하는 방법을 설명하여 독자의 사례 응용 이해를 돕는데 있으며, 또한 특히 주성분분석을 이용하여 수 많은 비독립적인 검사점을 어떻게 유

Process capability indices, Cp, Cpk, Cpm, and Cpmk can be used to evaluate single quality characteristic. Recently, many of the multivariate capability indices have been developed to assess a part which has several correlated quality characteristics. Principal component analysis(PCA) can transform the correlated quality characteristics into the newly independent factors. The existing formula calculates the Mutivariate Process Capability Index using the geometrical average. But, the result value notably differs from the number of principle component. In this paper, We proposed a new multivariate capability using PCA & RSS.

1986년부터 1988년까지 3년 동안 우리나라 주변 해역에서 발생한 1680건의 해난사고를 주성분분석법에 의한 전산프로그램을 작성하여 분석한 결과를 요약하면 다음과 같다. 1. 해난사고의 주된 원인은 운항부주의, 기관 정비불량 등 인적요인에 있으며, 사고유형으로서는 기관고장이, 선종으로서는 어선이 특히 해난사고의 큰 비중을 차지한다. 2. 어선, 관공선의 경우에는 기관고장이나 추진기장애 등이 경미한 해난사고가 많은 경향인데 비해 화물선, 여객선, 유조선의 경우에는 좌초, 충돌, 전복, 침수 등 재산과 인명의 피해가 큰 대형해난사고가 많은 경향이다. 3. 대형해난사고 중 좌초, 충돌, 전복 등은 그 주된 원인이 운항부주의에 있고, 침수의 경우는 재질구조결함에 기인하는 바가 크다.

1980년부터 1985년까지 6년 간의 우리나라 해난사고 중 기관손상사고를 발췌하여 주성분분석법에 의하여 분석한 결과는 다음과 같다. 1. 여러 가지의 기관손상사고 중 축계, 실린더 계통 및 추진기의 손상사고율이 매우 높은 비중을 차지하고 있다. 2. 치차, 실린더 계통의 손상은 재질불량, 노후마모 등의 기계적 원인에 의한 사고율이 높으며 추진기, 각종 관계통의 사고는 취급 부주의, 불완전 수리 등 soft적인 원인에 의한 경우가 많다. 3. 치차, 축계 등의 사고는 매우 중손이며 관계통이나 추진기 사고는 비교적 경손이다. 4. 대부분의 사고는 인간의 실수, 부주의 등 soft적인 원인에 의하여 발생한다.

최근 선박의 배기가스 규제가 강화되면서 연료소비량을 저감하기 위한 많은 방안들이 검토되고 있다. 그중에서도 선박으로부터 수 집한 데이터를 활용하여 연료소모량을 예측하는 기계학습 모델을 개발하고자 하는 연구가 활발히 수행되고 있다. 하지만 많은 연구들이 학습 모델의 주요 변수 선정이나 수집데이터의 처리 방법에 대한 고려가 미흡하였으며, 무분별한 데이터의 활용은 변수 간의 다중공선성 문제를 야기할 수도 있다. 본 연구에서는 이러한 문제점을 해결하기 위하여 주성분 분석을 이용하여 선박의 연료소비를 예측하는 방법을 제시하였다. 13K TEU 컨테이너 선박의 운항데이터에 주성분 분석을 수행하였으며, 추출한 주성분으로 회귀분석을 수행하여 연료소비 예측모델을 구현하 였다. 평가용 데이터에 대한 모델의 설명력은 82.99%이었으며, 이러한 예측모델은 항해 계획 수립 시 운항자의 의사결정을 지원하고 항해 중 에너지 효율적인 운항상태 모니터링에 기여할 수 있을 것으로 기대된다.