• Title/Summary/Keyword: principal component regression

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Attenuated total reflection Fourier transform infrared as a primary screening method for cancer in canine serum

  • Macotpet, Arayaporn;Pattarapanwichien, Ekkachai;Chio-Srichan, Sirinart;Daduang, Jureerut;Boonsiri, Patcharee
    • Journal of Veterinary Science
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    • v.21 no.1
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    • pp.16.1-16.10
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    • 2020
  • Cancer is a major cause of death in dogs worldwide, and the incidence of cancer in dogs is increasing. The attenuated total reflection Fourier transform infrared spectroscopic (ATR-FTIR) technique is a powerful tool for the diagnosis of several diseases. This method enables samples to be examined directly without pre-preparation. In this study, we evaluated the diagnostic value of ATR-FTIR for the detection of cancer in dogs. Cancer-bearing dogs (n = 30) diagnosed by pathologists and clinically healthy dogs (n = 40) were enrolled in this study. Peripheral blood was collected for clinicopathological diagnosis. ATR-FTIR spectra were acquired, and principal component analysis was performed on the full wave number spectra (4,000-650 cm-1). The leave-one-out cross validation technique and partial least squares regression analysis were used to predict normal and cancer spectra. Red blood cell counts, hemoglobin levels and white blood cell counts were significantly lower in cancer-bearing dogs than in clinically healthy dogs (p < 0.01, p < 0.01 and p = 0.03, respectively). ATR-FTIR spectra showed significant differences between the clinically healthy and cancer-bearing groups. This finding demonstrates that ATR-FTIR can be applied as a screening technique to distinguish between cancer-bearing dogs and healthy dogs.

Other faunas, coral rubbles, and soft coral covers are important predictors of coral reef fish diversity, abundance, and biomass

  • Imam Bachtiar;Tri Aryono Hadi;Karnan Karnan;Naila Taslimah Bachtiar
    • Fisheries and Aquatic Sciences
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    • v.26 no.4
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    • pp.268-281
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    • 2023
  • Coral reef fisheries are prominent for the archipelagic countries' food sufficiency and security. Studies showed that fish abundance and biomass are affected by biophysical variables. The present study determines which biophysical variables are important predictors of fish diversity, abundance, and biomass. The study used available monitoring data from the Indonesian Research Center for Oceanography, the National Board for Research and Innovation. Data were collected from 245 transects in 19 locations distributed across the Indonesian Archipelago, including the eastern Indian Ocean, Sunda Shelf (Karimata Sea), Wallacea (Flores and Banda Seas), and the western Pacific Ocean. Principal component analysis and multiple regression model were administered to 13 biophysical metrics against 11 variables of coral reef fishes, i.e., diversity, abundance, and biomass of coral reef fishes at three trophic levels. The results showed for the first time that the covers of other fauna, coral rubbles, and soft corals were the three most important predictor variables for nearly all coral reef fish variables. Other fauna cover was the important predictor for all 11 coral reef fish variables. Coral rubble cover was the predictor for ten variables, but carnivore fish abundance. Soft coral cover was a good predictor for corallivore, carnivore, and targeted fishes. Despite important predictors for corallivore and carnivore fish variables, hard coral cover was not the critical predictor for herbivore fish variables. The other important predictor variables with a consistent pattern were dead coral covered with algae and rocks. Dead coral covered with algae was an important predictor for herbivore fishes, while the rock was good for only carnivore fishes.

Gender differences in the association between food costs and obesity in Korean adults: an analysis of a population-based cohort

  • Soim Park;Jihye Kim
    • Nutrition Research and Practice
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    • v.17 no.5
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    • pp.984-996
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    • 2023
  • BACKGROUND/OBJECTIVES: Prior studies, mostly conducted in Western countries, have suggested that the low cost of energy-dense foods is associated with an increased risk of obesity. This study aimed to investigate the association between food costs and obesity risk among Koreans who may have different food cost and dietary patterns than those of Western populations. SUBJECTS/METHODS: We used baseline data from a cohort of 45,193 men and 83,172 women aged 40-79 years (in 2006-2013). Dietary intake information was collected using a validated food frequency questionnaire. Prudent and Western dietary patterns extracted via principal component analysis. Food cost was calculated based on Korean government data and market prices. Logistic regression analyses were performed to investigate the association of daily total, prudent, and Western food cost per calorie with obesity. RESULTS: Men in the highest total food cost quintile had 15% higher odds of obesity, after adjusting for demographic characteristics and lifestyle factors (adjusted odds ratio, 1.15; 95% confidence interval, 1.08-1.22; P-trend < 0.001); however, this association was not clear in women (P-trend = 0.765). While both men and women showed positive associations between prudent food cost and obesity (P-trends < 0.001), the association between Western food cost and obesity was only significant in men (P-trend < 0.001). CONCLUSIONS: In countries in which consumption of Western foods is associated with higher food costs, higher food costs are associated with an increased risk of obesity; however, this association differs between men and women.

A Study on Clinical Variables Contributing to Differentiation of Delirium and Non-Delirium Patients in the ICU (중환자실 섬망 환자와 비섬망 환자 구분에 기여하는 임상 지표에 관한 연구)

  • Ko, Chanyoung;Kim, Jae-Jin;Cho, Dongrae;Oh, Jooyoung;Park, Jin Young
    • Korean Journal of Psychosomatic Medicine
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    • v.27 no.2
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    • pp.101-110
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    • 2019
  • Objectives : It is not clear which clinical variables are most closely associated with delirium in the Intensive Care Unit (ICU). By comparing clinical data of ICU delirium and non-delirium patients, we sought to identify variables that most effectively differentiate delirium from non-delirium. Methods : Medical records of 6,386 ICU patients were reviewed. Random Subset Feature Selection and Principal Component Analysis were utilized to select a set of clinical variables with the highest discriminatory capacity. Statistical analyses were employed to determine the separation capacity of two models-one using just the selected few clinical variables and the other using all clinical variables associated with delirium. Results : There was a significant difference between delirium and non-delirium individuals across 32 clinical variables. Richmond Agitation Sedation Scale (RASS), urinary catheterization, vascular catheterization, Hamilton Anxiety Rating Scale (HAM-A), Blood urea nitrogen, and Acute Physiology and Chronic Health Examination II most effectively differentiated delirium from non-delirium. Multivariable logistic regression analysis showed that, with the exception of vascular catheterization, these clinical variables were independent risk factors associated with delirium. Separation capacity of the logistic regression model using just 6 clinical variables was measured with Receiver Operating Characteristic curve, with Area Under the Curve (AUC) of 0.818. Same analyses were performed using all 32 clinical variables;the AUC was 0.881, denoting a very high separation capacity. Conclusions : The six aforementioned variables most effectively separate delirium from non-delirium. This highlights the importance of close monitoring of patients who received invasive medical procedures and were rated with very low RASS and HAM-A scores.

Effect of Residential Environment on the Health Status in Apartment Inhabitants (아파트 주민의 건강상태에 거주 환경이 미치는 영향)

  • Kang, Ki-Won;Kim, Hwa-Joon;Kwon, Geun-Yong;Jung, Min-Soo
    • Journal of agricultural medicine and community health
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    • v.34 no.3
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    • pp.279-290
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    • 2009
  • Objectives: WHO insisted on that we should study about association between residential environment and health status and make 'health city' concept as practical motto. This study analyzed about that how community environment affected their health. Methods: We surveyed residential environment satisfaction and health status of a apartment complex residents. We transformed Chun's index about housing environment study and social capital index of WHO and used as community health survey. We analyzed the association between health status and related factor by using principal compound analysis and logistic regression analysis. Results: We found out that the perceived health status 1 years ago was highly related to the residential environment and also extracted five residential environment component (APT maintenance, House, APT complex, Neighbor, APT building) by principal component analysis. After residential environment component, demographic and socioeconomic variable were controlled, the high satisfaction group of APT complex and neighbor relationship was in lower risk of perceived health status 1 years ago than the low satisfaction group. Conclusions: Recently, the importance of residential environment and neighborhood is shaped as community capacity. Therefore, social relationship and residential environment should be the core variable for health promotion of community. After all, we should know the relationship of residential environment and perceived health status 1 years ago. This helps the concept of health city clearly.

Relative Efficiency and Statistical Analysis of Kimchi-related Manufacturers in Jeollabuk-do (전라북도 김치관련 제조업체의 상대적 효율성 및 통계적 분석)

  • Choi, Kyoung-Ho;Jung, Eun-Young;Kwag, Hee-Jong
    • Journal of Digital Convergence
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    • v.12 no.8
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    • pp.139-146
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    • 2014
  • We investigated the relative efficiency and statistical analysis of Kimchi-related manufactures in Jeollabuk-do for their management efficiency and improvement plans. We used data enveloped analysis (DEA) for the relative efficiency, and principal component analysis (PCA) and t-test for the statistical analysis. We analyzed 34 DMUs among 67 DMUs located in Jeollabuk-do. The results were as follows; the statistical efficiency, pure statistical efficiency, scale efficiency for 34 DMUs were 0.653, 0.761, and 0.863, respectively. The correlated component regression (CCR) showed that DMUs above efficiency 1 were 61.5% among -si (urban area), and 23.8% among -gun (rural area), respectively. However, there were not the significant differences of and BCC, CCR, and scale efficiency between urban area and rural area. This study will be useful for local industry's promotion by providing the information on Kimchi-related manufactures.

Development of Predicting Models of the Operating Speed and Operating environment Satisfaction Model in Expressways (고속도로의 주행속도예측 및 주행환경만족도 모형 개발에 관한 연구)

  • Kim, Jang-Uk;Jang, Il-Jun;Kim, Jeong-Hyeon;Lee, Su-Beom
    • Journal of Korean Society of Transportation
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    • v.27 no.2
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    • pp.117-131
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    • 2009
  • When most drivers take to the freeway, they don't necessarily pay attention to the geometric design. They expect proper design by depending on their own senses and recognition. When they evaluate the features of traveling on the freeway, they can think differently than engineers. The design needs to predict the exact speed of the driver to satisfy the driver's expectation, safety, pleasure and so on. This study categorized the factors influencing the speed of six freeways considering geometric and operational features to make a prediction model of speed. The model used multiple regression with these factors and produced statically appropriate results. This study utilized the principle component analysis and the quantification II analysis based on the image data of the satisfaction of the traveling environment collected through individual interviews. As a result, this study found the factors of satisfaction in a traveling environment. It made a satisfaction model of the traveling environment on freeways considering the change of driver's actual recognition and societal recognition using structural equations and the quantification II theory. Through the model made in this study, This model can present not only qualitative factors like satisfaction of traveling environment on freeways, but also the quantitative elements like speed. What is important is the evaluation of features of traveling on freeways reflected in the recognition and traffic environment felt by drivers.

NEAR-INFRARED STUDIES ON STRUCTURE-PROPERTIES RELATIONSHIP IN HIGH DENSITY AND LOW DENSITY POLYETHYLENE

  • Sato, Harumi;Simoyama, Masahiko;Kamiya, Taeko;Amari, Trou;Sasic, Slobodan;Ninomiya, Toshio;Siesler, Heinz-W.;Ozaki, Yukihiro
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1281-1281
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    • 2001
  • Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

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Alternative hitting ability index for KBO (한국프로야구에서 타자력 지수 제안)

  • Hong, Chong Sun;Kim, Jae Young;Shin, Dong Sik
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.3
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    • pp.677-687
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    • 2016
  • Among lots of sabermetric statistics for baseball batters' ability, the wins above replacement (WAR) is the most popular statistic in MLB. However, there exists a difficulty applying WAR to KBO, since KBO data do not have position adjustment, league adjustment and park factor which are essential in calculating WAR. In this paper, using five statistics for both KBO and MLB qualified batters, we propose hitting ability index (HAI), an alternative sabermetric indices to represent batters' ability. Comparing HAI with WAR of MLB batters, we evaluate the validity of HAI and then applied HAI to 2015 KBO data in which HAI is analyzed statistically with respect to different teams, ages, and positions. Moreover, the linear relationship between KBO batter's HAI and their annual salary is discussed. Grouping 46 KBO batters based on confidence region of the regression model for annual salary, we also statistically investigate batter's annual salary in these groups with respect to several factors.

Determination of Nitrogen in Fresh and Dry Leaf of Apple by Near Infrared Technology (근적외 분석법을 응용한 사과의 생잎과 건조잎의 질소분석)

  • Zhang, Guang-Cai;Seo, Sang-Hyun;Kang, Yeon-Bok;Han, Xiao-Ri;Park, Woo-Churl
    • Korean Journal of Soil Science and Fertilizer
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    • v.37 no.4
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    • pp.259-265
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    • 2004
  • A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.