• Proceedings of the Korean Environmental Health Society Conference
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• 2005.06a
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• pp.254-258
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• 2005

The purpose of this study is to characterize the indoor-outdoor relationship of airborne pollutants and recognize probable sources in inside and outside individual apartments in Seoul metropolitan. Simultaneous air monitoring in inside and outside of the 16 Korean Apartments classified into 2groups: less than 1 year old and more than 4 years old from October, 2004 to February, 2005were sampled f3r airborne pollutants(volatile organic compounds, formaldehyde, respiratory particles, carbon dioxide and bacteria) using the Korean Indoor Air Quality Official Method. The concentrations of $CO_2$, TVOCs, HCHO, bacteria and PM10 in the less than 1 year old apartments were determined to be $773.6{\pm}422.3ppm$, $4,393.8{\pm}2,758.2{\mu}g/m^3$, $98.0{\pm}56.4{\mu}g/m^3$, $254.0{\pm}186.3CFU/m^3$ and $31.7{\pm}14.8{\mu}g/m^3$, respectively, Also, the concentrations of those in the more than 4 years old apartments were determined to be $798.9{\pm}266.5ppm$, $792.7{\pm}398.3{\mu}g/m^3$, $70.0{\pm}30.7{\mu}g/m^3$, $245.6{\pm}122.0CFU/m^3$, $49.7f28.7{\pm}g/m^3$, respectively. The average ratios of the indoor and outdoor concentrations of $CO_2$, TVOCs, HCHO, bacteria and PM10 were 2.2, 3.6, 3.1, 3.9 and 1.4, respectively. These results of this analysis is suggested that $CO_2$, TVOCs, HCHO, bacteria and PM10 in indoor air are both emitted from source within the apartment environment and partly come from outdoor air. With the above considerations in mind, it is suggested that the research for source contribution of indoor air pollutants should be expanded and the detailed interpretation of the results on these needed further study(using principal component analysis(PCA).

• Korean journal of food and cookery science
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• v.17 no.4
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• pp.353-358
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• 2001

The leaves of Duchung(Eucommia ulmoides), an oriental medicinal plant, have a peculiar aroma of Chinese medicine and astringent taste, which make the consumer be reluctant to Duchung leaf tea. Therefore, the purpose of this study was to develop a mild flavored Duchung leaf tea by mixing with other plants. The flavor patterns of developed tea were analyzed using an electronic nose. Polygonatum odoratum and Elsholtzia splendens were used for improving the flavor of Duchung leaf tea. The addition of 20, 30 and 40% of Polygonatum odoratum improved the overall acceptance in hedonic sensory evaluation. The flavor pattern of the tea was described by principal component analysis(PCA) and the resistance ratio(R/cub gas/R$\_$air/) of sensors. The PCA plot was also used to explain the mild flavor of the tea, which was extended from the right side(positive value of the first principal component) to the left side(negative value). Analysis by using an electronic nose with metal oxide sensors could be applied to detect whether mixed Duchung leaf tea was acceptable or not.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.295-300
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• 2020

Since China opened its door to the world in 1978, its economic development had been concentrated in the Eastern and Western area compared with the middle area. From 2000s, the Chinese government started to develop the middle area in terms of balanced development. With this goal, "Plan on Zhengzhou Airport Economy Zone", and "One Belt and One Road" has implemented in Zhengzhou, where is the an important traffic center in middle area. Meanwhile, the foreign trade of Zhengzhou has been increased about 10 times between 2009 and 2018. In particular, its growth is the fastest among six central cities in 2018 from the lowest in 2009. This study investigates whether the Chinese government policy has an effect on the foreign trade of Zhengzhou. We find that based on the regression analysis of the Principal Component Analysis (PCA), the government policies has a positive impact on the development of Zhengzhou's foreign trade. It is meaningful that the government policy focused on the advantage of Zhengzhou contributes its development of foreign trade.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.1-10
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• 2022

As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m². The study is expected to play a major role in marine HNS monitoring.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.613-628
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• 2011

Restoration, prediction and noise analysis of geomagnetic data measured in the Korean Peninsula were performed. Restoration methods based on an optimized principal component analysis (PCA) and the geostatistical kriging approach were proposed, and its effectiveness was also interpreted. The PCA-based method seemed to be effective to restore the periodical signals and the geostatistical approach was stable to fill the gaps of measurements. To analyze the noise level for each observatory, the geomagnetic time-series was plotted by scattergram which reflects the spatial variation, using data observed during same period. The scattergram showed that the observation made at Cheongyang seemed to have better quality in spatial continuity and stability, and the restoration result was also better than that of Icheon site. For the restoration, both of the methods, geostatistical and optimizaed PCA, showed stable result when the missing of observation was within 20 points. However, in case of more missing observations than 20 points and prediction problem, the optimized PCA seemed to be closer to the real observation considering the frequency-domain characteristics. The prediction using the optimized PCA seems to be plausible for one day of period for interpretation.

• Analytical Science and Technology
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• v.33 no.2
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.889-899
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• 2017

Independent component analysis is a multivariate approach to separate mixed signals into original signals. It is the most widely used method of blind source separation technique. ICA uses linear transformations such as principal component analysis and factor analysis, but differs in that ICA requires statistical independence and non-Gaussian assumptions of original signals. PCA have a natural ordering based on cumulative proportion of explained variance; howerver, ICA algorithms cannot identify the unique optimal ordering of the components. It is meaningful to set order because major components can be used for further analysis such as clustering and low-dimensional graphs. In this paper, we compare the performance of several criteria to determine the order of the components. Kurtosis, absolute value of kurtosis, negentropy, Kolmogorov-Smirnov statistic and sum of squared coefficients are considered. The criteria are evaluated by their ability to classify known groups. Two types of data are analyzed for illustration.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.53-62
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• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.55-65
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• 2011

In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.

• Korean Journal of Human Ecology
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• v.24 no.5
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• pp.725-739
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• 2015

The purpose of this study was to investigate the quality characteristics and descriptive analysis of Yanggaeng prepared with Lycii fructus extract (LD). LD were added in ratios (w/w) of 0 (C), 1.5 (LY1), 3.0 (LY2), 4.5 (LY3), and 6% (LY4), and then proximate compositions, physicochemical properties, and sensory evaluations of the Yanggaeng were measured LY1~LY4 samples showed higher contents of crude lipid, crude protein and crude ash as well as $^{\circ}Brix$ compared to control (p<0.001). pH and lightness (L) of samples decreased as the LD increased. With regard to the texture of Yanggaeng samples, the scores of hardness, adhesiveness, springness, and cohesiveness was significantly increased by the Addition of LD (p<0.05, p<0.01). For the descriptive analysis, ten panelist generated and evaluated 29 sensory attributes for the Yanggaeng, and there were significant differences among the samples for all 26 sensory attributes. For the descriptive data, principal component analysis (PCA) was performed to summarize the sensory characteristics of the Yanggaeng. The results of PCA showed that the positive attributes, e.g. savoury, were closely in relationship with LY2 and LY3. Form the findings, this study suggests that 3~4.5% addition of LD was effective for preparation of Yanggaeng in the aspects of the consumer acceptability.