• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.10
• /
• pp.1381-1386
• /
• 2014

In spite of variation in coat color, size, and production traits among indigenous Bangladeshi cattle populations, genetic differences among most of the populations have not been investigated or exploited. In this study, we used a high-density bovine single nucleotide polymorphism (SNP) 80K Bead Chip derived from Bos indicus breeds to assess genetic diversity and population structure of 2 Bangladeshi zebu cattle populations (red Chittagong, n = 28 and non-descript deshi, n = 28) and a semi-domesticated population (gayal, n = 17). Overall, 95% and 58% of the total SNPs (69,804) showed polymorphisms in the zebu and gayal populations, respectively. Similarly, the average minor allele frequency value was as high 0.29 in zebu and as low as 0.09 in gayal. The mean expected heterozygosity varied from $0.42{\pm}0.14$ in zebu to $0.148{\pm}0.14$ in gayal with significant heterozygosity deficiency of 0.06 ($F_{IS}$) in the latter. Coancestry estimations revealed that the two zebu populations are weakly differentiated, with over 99% of the total genetic variation retained within populations and less than 1% accounted for between populations. Conversely, strong genetic differentiation ($F_{ST}=0.33$) was observed between zebu and gayal populations. Results of population structure and principal component analyses suggest that gayal is distinct from Bos indicus and that the two zebu populations were weakly structured. This study provides basic information about the genetic diversity and structure of Bangladeshi cattle and the semi-domesticated gayal population that can be used for future appraisal of breed utilization and management strategies.

• The Korean Journal of Applied Statistics
• /
• v.21 no.1
• /
• pp.141-149
• /
• 2008

Recently we frequently analyze multivariate data with quite large number of variables. In such data sets, virtually duplicated variables may exist simultaneously even though they are conceptually distinguishable. Duplicate variables may cause problems such as the distortion of principal axes in principal component analysis and factor analysis and the distortion of the distances between observations, i.e. the input for cluster analysis. Also in supervised learning or regression analysis, duplicated explanatory variables often cause the instability of fitted models. Since real data analyses are aimed often at multiple purposes, it is necessary to reduce the number of variables to a parsimonious level. The aim of this paper is to propose a practical algorithm for selection of a subset of variables from a given set of p input variables, by the criterion of minimum trace of partial variances of unselected variables unexplained by selected variables. The usefulness of proposed method is demonstrated in visualizing the relationship between selected and unselected variables, in building a predictive model with very large number of independent variables, and in reducing the number of variables and purging/merging categories in categorical data.

• Journal of Korean Society on Water Environment
• /
• v.29 no.3
• /
• pp.317-328
• /
• 2013

The purpose of this study was to investigate the change of phytoplankton fluctuation and long term of water quality of Lake Juam and to evaluate the relationship between phytoplankton pattern and environmental factors data. Correlation and factor analyses were employed to identify key environmental factors affecting phytoplankton dynamics. Of 18 parameters, pH, temperature, COD, BOD and T-P were highly correlated with Chl-a. Phytoplankton data showed that cyanobacteria were dominant, and more than 60% of total algae density. Also Lake Juam received a lot of influence of the Asian monsoon climate. This study presents necessity of multivariate statistic techniques for evaluation of Lake Juam complex data set with a view to get better information data and effective management of water source.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1462-1466
• /
• 2009

우리나라 가뭄의 지역적 특성은 수문학적으로 동질한 지역의 구분 결과에 따라 달라진다. 지역의 구분에는 가뭄에 영향을 미치는 다양한 변수들이 사용될 수 있다. 가뭄을 특징짓는 요소로서 지속기간, 심도, 이외의 통계적 특성들이 있으며, 이 변수들을 정보화하여 변수의 유형을 구분지어 모든 변수들을 요약된 정보로 활용하여 가뭄의 특성을 구분할 수 있다. 본 연구에서는 우리나라 기상청 강우자료 75개 관측지점 중 30년 미만의 강우기록이 있는 17개의 지점을 제외한 58개 강우 관측 지점을 대상으로 가뭄지수(SPI)를 산정하여 가뭄사상의 특성을 정량화 과정으로 남한지역 가뭄특성을 분류하였다. SPSS를 활용한 다변량 분석기법인 주성분 분석(principal component analysis)을 통해 가뭄특성인자의 상관관계가 높은 변수들을 조합하여 그 변수들 중 가뭄정보를 가능한 많이 함축하고 있는 새로운 특성 변수를 만들어 내었으며, 선정된 변수들을 바탕으로 요인분석(factor analysis)의 직각회전 방식(Varimax)을 이용하여 변수들의 표준화를 통해 가뭄특성요인을 찾아내었다. 이를 통해 지역간 동질성을 파악하여 K-means기법을 적용하여 군집해석(clustering analysis)을 실시하였다.

• Journal of Biosystems Engineering
• /
• v.34 no.1
• /
• pp.37-43
• /
• 2009

Hyperspectral reflectance and fluorescence scattering have been researched recently for measuring fruit post-harvest quality and condition. And they are promising for nondestructive detection of fruit quality. The objective of this research was to develop a model, which measure the quality of apple by using hyperspectral reflectance and fluorescence. A violet laser (408 nm) and a quartz tungsten halogen light were used as light sources for generating laser induced fluorescence and reflectance scattering in apples, respectively. The laser induced fluorescence and reflectance of 'Golden Delicious' apples were measured by using a hyperspectral imaging system. Fruit firmness, soluble solids and acid content were measured using standard destructive methods. Principal component analyses were performed to extract critical information from both hyperspectral reflectance and fluorescence data and this information was then related to fruit quality indexes. The fluorescence models had poorer predictions of the three quality indexes than the reflectance models. However, the prediction models of integrating fluorescence and reflectance performed consistently better than the individual models of either reflectance or fluorescence. The correlation coefficient for fruit firmness, soluble solid content, and tillable acidity from the integrated model was 0.86, 0.75, and 0.66 respectively. Also the standard errors were 6.97 N, 1.05%, and 0.07% respectively.

• Nutrition Research and Practice
• /
• v.10 no.4
• /
• pp.424-432
• /
• 2016

BACKGROUND/OBJECTIVES: Most consumers are able to recognize allergenic foods. However, the frequency of checking such foods is reportedly low, resulting in higher prevalence of food-related allergic reactions in Korea compared to other countries. Thus, this study was performed to investigate the overall perception of allergenic food labeling and its practice level in food manufacturing company employees. SUBJECTS/METHODS: The survey was administered to food safety employees and food development teams at food companies located in metropolitan areas. A total of 399 (93.8%) valid samples were used in the final analysis. Statistical analyses, including Frequency Analysis, t-test, Anova, PCA (Principal Component Analysis), and Pearson Correlation Analysis using SPSS ver. 21.0, were performed. RESULTS: The correct answer rate in the analysis of allergy-related knowledge level ranged from 15.0% to 89.7%. Analysis of differences in allergy-related perception by knowledge level showed significant differences in introduction of a food recall system, strengthening of relevant laws and regulations, content labeling, description of substitutional food, and differentiated package by age. CONCLUSIONS: It can be concluded that labeling of allergenic foods should be made easier and more convenient for checking by employees, developers, and consumers, and it is necessary to provide contents through the development of publicity, guidelines, or APP along with labeling.

• Asian-Australasian Journal of Animal Sciences
• /
• v.15 no.11
• /
• pp.1527-1530
• /
• 2002

Factor analysis was applied to the phenotypic correlation matrix of 15 linear type traits (scored linearly 1 to 50 points) for 2035 Holstein cows of 38 sires computed from data collected between 1988 and 1992 in Beijing Shuangqiao Farm and Beijing Xijiao Farm. The 15 linear type traits were stature, body strength, body depth, dairy form, rump angle, rump length, rump width, rear leg side view, foot angle, fore udder attachment, rear udder height, rear udder width, udder cleft, udder depth and teat placement rear view. The first four components accounted for 49.1% of the total variance in type scores. Factor 1 reflected strong cows, with deep bodies, with long and wide rumps, and tall in stature. Factor 2 reflected cows with well attached fore udders, wide rear udders and whose udders were supported by strong suspensory ligaments with close teat placement. Factor 3 reflected cows with good dairyness, sickled in the hocks, high rear udders and udder floors above the hocks. Factor 4 reflected cows with sloping rumps from hooks to pins and with steep foot angle. Principal component and factor analyses are useful to clarify the relationships among type traits.

• Journal of Korean Society of Rural Planning
• /
• v.10 no.2 s.23
• /
• pp.1-6
• /
• 2004

This study tried to construct a direction in regional planning concerning the structural relationship between the ratio of aged population and the industrial characteristics. We investigated this structural relationship incorporating the aged population index and the number of classified companies. We applied diverse statistical analyses to understand the relationship. We classified the number of companies to reflect regional industrial characteristics using the principal component analysis. We applied a multiple regression model to understand the relationship between these two indices. The aged population index represents the degree of being old divided by the ratio of juvenile population and aged population. We found that such industries as manufacturing, service, and conveyance increase the ratio of juvenile population. However, industries such as tourism, waterworks, forestry, agriculture and etc. have a positive effect on the aged population index. In addition to these findings, we believe that the efficacy of this study is the possibility that can be used as the basic data when central or local autonomous entities need to adopt rural development planning.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.23 no.4
• /
• pp.198-203
• /
• 1987

The basis of all approaches to improve reliability of marine engines exists in analyzing the field data of troubles and failures on marine engines. This paper analyses the data of troubles and failures on marine engines by Principal Component Analysis Method, one of Multivariate Data Analysis Method. The total number of data investigated is 211 and the observation period is 9 years. The analyzed factors are categorized among five groups respectively; electric.automatic control equipments, auxiliary machinery, pipings, refrigerators.air conditioners, and main engine. The failures in main engine are discovered by a definite fact of disorder, on the contrary, the failures in auxiliary machinery, refrigerators and air conditioners are discovered by sensible judgement of the operators.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.17 no.4
• /
• pp.487-497
• /
• 2010

Purpose: This study examined the validity and reliability to develop a lifestyle evaluation tool for metabolic syndrome patients. Methods: A methodological research design was used. The construct factors and preliminary items were identified by reviewing previous researches and tools related to lifestyle and reviewed by ten experts. It was tested with 195 patients with metabolic syndrome in a university hospital. The data were analyzed with SPSS/WIN 14.0. Results: To test the validity, principal component analyses were used and resulted in the extraction of six components. The convergent validity resulted r= .72 (p<.001) with Health Promotion Lifestyle Profile. The discriminant validity with Center for Epidemiologic Studies Depression Scale resulted r= -.15 (p=.004). The Internal consistency of the tool had an Cronbach's a of .92. The self-report format Lifestyle Evaluation Tool for the patients with metabolic syndrome was developed with 36 items and four-rating scales:'physical activity and weight control' eight items, 'dietary habits' sixteen items, 'drinking and smoking' three items, 'sleep and rest' two items, 'stress' three items, 'drug and health management' four items. Conclusion: This Tool will evaluate health behaviors in patients with metabolic syndrome. Also, it will contribute to the development of nursing intervention to improve the metabolic syndrome patients' lifestyle.