• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.343-356
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• 1994

In this study, a statistical investigation was carried out for the evaluation of any relationship between polycyclic aromatic hydrocarbons (PAHss) associated with ambient aerosols and other air quality parameters under varying meteorological conditions. Daily measurements for PAHs and air quality/meteorological parameters were selected from a data-base constructed by a comprehensive air monitoring in London during 1985-1987. Correlation coefficients were calculated to examine any significant relationship between the PAHs and other individual variables. Statistical analysis was further Performed for the air quality/meteorological data set using a principal component analysis to derive important factors inherent in the interactions among the variables. A total of six components were identified, representing vehicle emission, photochemical activity/volatilization, space heating, atmospheric humidity, atmospheric stability, and wet deposition. It was found from a stepwise multiple regression analysis that the vehicle emission component is overall the most important factor contributing to the variability of PAHs concentrations at the monitoring site. The photochemical activity/volatilzation component appeared to be also an important factor particularly for the lower molecular weight PAHs. In general, the space heating component was found to be next important factor, while the contributions of other three components to the variance of each PAHs did not appear to be as much important as the first three components in most cases. However, a consistency for these components in their negative correlations with PAHs data was found, indicating their roles in the depletion of PAHs concentrations in the urban atmosphere.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.625-632
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• 2001

Principal component analysis(PCA) is a multivariate technique falling under the general title of factor analysis. The purpose of PCA is to Identify the dependence structure behind a multivariate stochastic observation In order to obtain a compact description of it. In engineering field PCA is utilized mainly (or data compression and restoration. In this paper we propose a new robust Hebbian algorithm for robust PCA. This algorithm is based on a hyperbolic tangent function due to Hampel ef al.(1989) which is known to be robust in Statistics. We do two experiments to investigate the performance of the new robust Hebbian learning algorithm for robust PCA.

• Korean Journal of Community Nutrition
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• v.5 no.1
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• pp.83-91
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• 2000

The aims of this study are to evaluate the quality of hospital food services and the evaluate the quality in selected hospitals trough the use of the questionnaires. A survey of 30 hospital food and nutrition service department was undertaken and detailed information was collected from each, including, surveys of 1, 016 patient. Statistical data analysis was completed using the SAS/win 6.11 package for descriptive analysis, t-test X$^2$-test ANOVA principal component analysis , and cluster analysis and cluster analysis. In the case of patient satisfaction with hospital food and food services, overall satisfaction scores of male and female were 3.54 and 3.45 showing higher levels than the average score(3.00) The aspect of the food and food service which received the lowest ratings by patients was 'meal rounding while dining'. After conduction of factor analysis of variables affecting the patients meal satisfaction 3 groups including the 'menu satisfaction factor', 'service satisfaction factor ' and 'nutrition management satisfaction factor ' were selected. 3 clusters were categorized by the 'service cluster' 'nutrition management cluster', 'men cluster', and 'menu nutrition service cluster' after conducting a cluster analysis with influencing variables affecting patients meal satisfaction. The overview results of patient satisfaction by cluster were : in the case of the service group, such factors as taste, portion size, dealing with complaints while dining meal rounding while dining should be managed with caution In case of the nutrition management group, such factors as taste, portion size, temperature of the food intake, and dependence on hospital food should be managed with care, In the case of the menu groups, such factors as punctuality of meal times, contaminated substances in meals and serving mistakes, cleanliness of dishes, kindness of the server meal rounding while dining should by particularly managed with importance.

• Journal of Environmental Impact Assessment
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• v.22 no.2
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• pp.171-181
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• 2013

In this study, we report the water quality characteristics of pollutants for 4 major tributaries in the Yeongsan and Sumjin river basins using statistical analysis, such as regression equation and factor analysis. The flow rate and water qualtiy data collected from 4 sampling sites(Hwangryoung A, Jiseok A, Chooryeong A, Osu A) in the Yeonsan and Sumjin river basin during the past 3 years were analyzed for 11 parameters(flow rate, dissolved oxgen, pH, water temperature, electric conductivity, biochemical oxygen demand, chemical oxygen deman, total organic carbon, total nitorgen, total phosphorus, suspended solid). The results showed that the concentrations of BOD, COD, TOC, T-N, T-P in Hwangryoung A(HW) and Jiseok A(JS) of the Yeongsan river basin were decreased as the flow rate was increased. This means that rather than nonpoint soources, point sources affect water quality. In the cases of Chooryeong A(CR) and Osu A(OS) in the Sumjin river basin, howerever, nonpoint sources than point sources are an important factor that affects the water quality. Also, the factor analysis technique was employed to analyze principal component influencing on water quality. The results revealed that the first principal component in HW was correlated with EC, DO, T-N, water temperature. This "nitrogen influx according to seasonal pattern" factor may be interpreted. In JS, the first principal component was correlated with BOD, COD, TOC and is likely to represent "organic matter" processes. In CR and OS, BOD, COD, TOC, SS and T-P were significantly correlated and is considered as representing "Organic matter and adsorption of phosphorus on sediments influx". This study is expected to contribute to the effective pollution control/management of the surfac waters in the study sites.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Journal of the Korean Home Economics Association
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• v.20 no.4
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• pp.83-89
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• 1982

The purpose of this study was to analyze the 45 measuring items for the clothing construction in order to observe the factorial structure of items and to extract the common factor and the special unique factor from data. The sample for the study was drawn randomly out of senior high schoolgirls in Seoul urban area. The size of sample was 301 girls between age 16 and 18. The method of analysis was applied by the principal component analysis with orthogonal rotation after extraction of 9 major factors. All of the above data was analyzed by the computer installed at Seoul National University. From these analyses, the major findings can be summerized as follows: 1. The results of factor analysis generally indicated that the first factor was clustered with 15 items, length measures and height measures. The eigenvalue of the first factor was 16.5 and the cumulative percentage of variables 36.6%. 2. The second factor was clustered with width measures, girth measures and weight of 19 items. The eigenvalue of the second factor was 6.5 and the cumulative percentage of variables 51.0%.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.905-913
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• 2011

This study was conducted to characterize the discharge feature of pollutant load from the upper and lower watershed influencing on the water quality of South Han River using the empirical equation and Factor Analysis. The results of regression analysis between flow rate and pollutant load were as follows. In the streams of the upper watershed of South Han river, $BOD_5$ and $COD_{Mn}$ were increased as the flow rate was increased. Also, steep increases in SS and TP were observed with positive correlation with the flow rate while change in TN was slightly shown. On the other hand, in the streams of the lower watershed of South Han river, $BOD_5$ was negatively correlated with the flow rate, being decreased with the increase in the flow rate. However, changes in $COD_{Mn}$, TN, SS, and TP showed a similar trend with those observed in the upper watershed. With Factor Analysis of the water quality and various components, it was appeared that the flow rate, SS, and TP were significantly correlated each other and they were indicated as the principal component influencing on water quality in the streams of the upper watershed. In contrast, $BOD_5$, $COD_{Mn}$ and TOC were significantly correlated each other and they were included as the principal pollution component of the streams in the lower watershed. From these results, it was conclusive that the upper watershed of South Han River was mainly affected by non point source pollutants while the lower watershed was influenced by point source pollutants from the developed areas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.15-21
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• 2010

In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

• Journal of Environmental Health Sciences
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• v.26 no.4
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• pp.1-8
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• 2000

The objective of this study was to identify the sources and to estimate the source contributions to the atmospheric TSP(total suspended particulate matter) and PM-10(particulate matter with aerodynamic diameters less than 10$\mu\textrm{m}$) concentration in Taegu area. A total of 84 samples was collected during the January to December 1999. TSP and PM-10 were collected on filters by portable air sampler, and heavy metals in TSP and PM-배 were analyzed by ICO(Inductively Coupled Plasma Spectrometery) after preliminary treatment. The results were follow as : First, annual average of TSP and PM-10 concentration was 123 and 69$\mu\textrm{g}$/㎥ respectively. The concentration of TSP and PM-10 were highest in winter season compared to other seasons. Second, the concentration of Al, Fe, Mn were higher in TSP than in PM-10, indicating that these heavy metals are generally associate with natural contributions. Third, metal combinations showed that a high correlation among concentrations of heavy metals were follows: As Al, Fe and Mn in TSP ; Ni, Cr, Cd and Pb in PM-10. Finally, Statistical analysis was performed using Principal Components Analysis(PCA) in order to find possible sources of the pollutants. The factor analysis was permitted to identify four major sources(soil/road dust resuspension, waste incineration, furl combustion, vehicular emission) in each fraction. These source accounted for at least 83, 85% of variance of TSP and PM-10 concentration in Taegu area.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.2
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• pp.12-23
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• 1994

In order to investigate the effect of turbulent intensity on combustion characteristics, new flame factor model was developed. The principal study is the evaluation of interaction of swirl, tumble and unstrutural component of flow characteristics and correlation between turbulent intensity and flame factor. Computational and experimental study has been, performed such as quasi-dimensional cycle simulation, three dimensional flow analysis, engine performance test and diagnostic simulation. From these studies, it was found that flame factor was a function of engine speed and turbulent intensity.