• Title/Summary/Keyword: Variable Important in Projection

Search Result 12, Processing Time 0.022 seconds

Projection of climate change effects on the potential distribution of Abeliophyllum distichum in Korea (기후변화에 따른 우리나라 미선나무의 분포변화 예측)

  • Lee, Sang-Hyuk;Choi, Jae-Yong;Lee, You-Mi
    • Korean Journal of Agricultural Science
    • /
    • v.38 no.2
    • /
    • pp.219-225
    • /
    • 2011
  • Changes in biota, species distribution range shift and catastrophic climate influence due to recent global warming have been observed during the last century. Since global warming affects various sectors, such as agriculture and vegetation, it is important to predict more accurate impact of future climate change. The purpose of this study is to examine the observed distribution of Abeliophyllum distichum in the Korean peninsula. For this purpose, two period (present and future) climate data were used. Mean data between 1950 and 2000, were used as the present value and the year 2050 and 2080 data from A1B senario in IPCC SRES were used for the future value. Potential habitation is analyzed by MaxEnt(Maximum Entropy model), and Abeliophyllum distichum's coordinates data were used as a dependent variable and independent variables are composed of environmental data such as BioClim, altitude, aspect and slope. The result of six types GCM mean calculation, the potential habitability decreased by 40-60% of the average existing distribution. The methodogies and results of this research can be applicable to the climate changing adaptation stratiegies for the biodiversity conservation.

Single-panel simulation on liquid crystal on silicon

  • Liao, Engle;Chiu, Jack;Peng, James
    • 한국정보디스플레이학회:학술대회논문집
    • /
    • 2004.08a
    • /
    • pp.939-942
    • /
    • 2004
  • In this study, we report simulation results of single-panel LCOS (liquid crystal on silicon). Reflective LCOS microdisplays are widely used in various projection and near-eye application. For one panel system, liquid crystal response time is an important variable. The panel must switch fast enough to support the display of Field color sequential with high field rates. In order to have fast response and good contrast, a vertical alignment (VA) cell was used in this study. With suitable selection on LC parameters like temperature, viscosity, elastic constant and birefringence, it is possible to get response time of around 2ms from a 2.0 um-thick vertical alignment cell. This result also indicates an ease of production control on 2.0 um cells than 1.0 um cells.

  • PDF

Development of Nondestructive Detection Method for Adulterated Powder Products Using Raman Spectroscopy and Partial Least Squares Regression (라만 분광법과 부분최소자승법을 이용한 불량 분말식품 비파괴검사 기술 개발)

  • Lee, Sangdae;Lohumi, Santosh;Cho, Byoung-Kwan;Kim, Moon S.;Lee, Soo-Hee
    • Journal of the Korean Society for Nondestructive Testing
    • /
    • v.34 no.4
    • /
    • pp.283-289
    • /
    • 2014
  • This study was conducted to develop a non-destructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression(PLSR). Garlic and ginger powder, which are used as natural seasoning and in health supplement foods, were selected for this experiment. Samples were adulterated with corn starch in concentrations of 5-35%. PLSR models for adulterated garlic and ginger powders were developed and their performances evaluated using cross validation. The $R^2_c$ and SEC of an optimal PLSR model were 0.99 and 2.16 for the garlic powder samples, and 0.99 and 0.84 for the ginger samples, respectively. The variable importance in projection (VIP) score is a useful and simple tool for the evaluation of the importance of each variable in a PLSR model. After the VIP scores were taken pre-selection, the Raman spectrum data was reduced by one third. New PLSR models, based on a reduced number of wavelengths selected by the VIP scores technique, gave good predictions for the adulterated garlic and ginger powder samples.

The Dynamic Effects of Globalization on the Firm Performance: A Study on Korea Maritime and Fishery Companies

  • Donghyun Lee;Heedae Park;Joongsan Ko
    • Journal of Korea Trade
    • /
    • v.26 no.7
    • /
    • pp.127-144
    • /
    • 2022
  • Purpose - This study aimed to analyze the dynamic effects of progress in globalization on firm performance by employing individual companies' financial statement datasets. Design/methodology - The analysis leveraged the variables of operating revenue (OPRE) and pre-tax profit and loss (PLBT) as measurement variables for firm performance over 2011-2019. As a proxy variable for globalization, the trade index, a subordinate indicator of the KOF Globalization Index, was used. Through panel regression analysis, the relationship among those variables was ascertained, and the local projection (LP) method was subsequently utilized to identify dynamic effects. A subsample analysis was further performed by classifying companies based on their sizes and industries to determine the differential effects of globalization on each group. Findings - The panel regression analysis derived positive effects of an increasing degree of globalization on OPRE of Korea maritime and fishery firms. However, the impulse response functions, obtained from the LP, showed that in the short run, globalization affects PLBT negatively but in the long run, it gradually converted into a positive effect. In addition, according to the subsample analysis based on company size, the effects of globalization on OPRE became greater as each company became larger. Moreover, the industry-based analysis showed heterogeneous effects, depending on the industries in which the maritime and fishery companies operated. Originality/value - The analysis of the dynamic effects of globalization on firm performance, which revealed that the effects vary depending on the time points, is the important contribution of this study. The results also suggest that the effects of globalization vary depending on the company size and industry.

Evaluation of Firmness and Sweetness Index of Tomatoes using Hyperspectral Imaging

  • Rahman, Anisur;Faqeerzada, Mohammad Akbar;Joshi, Rahul;Cho, Byoung-Kwan
    • Proceedings of the Korean Society for Agricultural Machinery Conference
    • /
    • 2017.04a
    • /
    • pp.44-44
    • /
    • 2017
  • The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.

  • PDF

Spatio-Temporal Projection of Invasion Using Machine Learning Algorithm-MaxEnt

  • Singye Lhamo;Ugyen Thinley;Ugyen Dorji
    • Journal of Forest and Environmental Science
    • /
    • v.39 no.2
    • /
    • pp.105-117
    • /
    • 2023
  • Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.

NMR-based metabolomic profiling of the liver, serum, and urine of piglets treated with deoxynivalenol

  • Jeong, Jin Young;Kim, Min Seok;Jung, Hyun Jung;Kim, Min Ji;Lee, Hyun Jeong;Lee, Sung Dae
    • Korean Journal of Agricultural Science
    • /
    • v.45 no.3
    • /
    • pp.455-461
    • /
    • 2018
  • Deoxynivalenol (DON), a Fusarium mycotoxin, causes health hazards for both humans and livestock. Therefore, the aim of this study was to investigate the metabolic profiles of the liver, serum, and urine of piglets fed DON using proton nuclear magnetic resonance ($^1H-NMR$) spectroscopy. The $^1H-NMR$ spectra of the liver, serum, and urine samples of the piglets provided with feed containing 8 mg DON/kg for 4 weeks were aligned and identified using the icoshift algorithm of MATLAB $R^2013b$. The data were analyzed by multivariate analysis and by MetaboAnalyst 4.0. The DON-treated groups exhibited discriminating metabolites in the three different sample types. Metabolic profiling by $^1H-NMR$ spectroscopy revealed potential metabolites including lactate, glucose, taurine, alanine, glycine, glutamate, creatine, and glutamine upon mycotoxin exposure (variable importance in the projection, VIP > 1). Forty-six metabolites selected from the principal component analysis (PCA) helped to predict sixty-five pathways in the DON-treated piglets using metabolite sets containing at least two compounds. The DON treatment catalyzed the citrate synthase reactions which led to an increase in the acetate and a decrease in the glucose concentrations. Therefore, our findings suggest that glyceraldehyde-3-phosphate dehydrogenase, citrate synthase, ATP synthase, and pyruvate carboxylase should be considered important in piglets fed DON contaminated feed. Metabolomics analysis could be a powerful method for the discovery of novel indicators underlying mycotoxin treatments.

Metabolomics Analysis of the Beef Samples with Different Meat Qualities and Tastes

  • Jeong, Jin Young;Kim, Minseok;Ji, Sang-Yun;Baek, Youl-Chang;Lee, Seul;Oh, Young Kyun;Reddy, Kondreddy Eswar;Seo, Hyun-Woo;Cho, Soohyun;Lee, Hyun-Jeong
    • Food Science of Animal Resources
    • /
    • v.40 no.6
    • /
    • pp.924-937
    • /
    • 2020
  • The purpose of this study was to investigate the meat metabolite profiles related to differences in beef quality attributes (i.e., high-marbled and low-marbled groups) using nuclear magnetic resonance (NMR) spectroscopy. The beef of different marbling scores showed significant differences in water content and fat content. High-marbled meat had mainly higher taste compounds than low-marbled meat. Metabolite analysis showed differences between two marbling groups based on partial least square discriminant analysis (PLS-DA). Metabolites identified by PLS-DA, such as N,N-dimethylglycine, creatine, lactate, carnosine, carnitine, sn-glycero-3-phosphocholine, betaine, glycine, glucose, alanine, tryptophan, methionine, taurine, tyrosine, could be directly linked to marbling groups. Metabolites from variable importance in projection plots were identified and estimated high sensitivity as candidate markers for beef quality attributes. These potential markers were involved in beef taste-related pathways including carbohydrate and amino acid metabolism. Among these metabolites, carnosine, creatine, glucose, and lactate had significantly higher in high-marbled meat compared to low-marbled meat (p<0.05). Therefore, these results will provide an important understanding of the roles of taste-related metabolites in beef quality attributes. Our findings suggest that metabolomics analysis of taste compounds and meat quality may be a powerful method for the discovery of novel biomarkers underlying the quality of beef products.

A Study on Relationships among University Students' Self-differentiation, Self-esteem and Mental Health : Focused on Depression and Anxiety (대학생의 자아분화, 자아존중감과 정신건강간의 관계 - 우울, 불안을 중심으로)

  • Kim, Sang Ok;Jeon, Young Ja
    • Korean Journal of Human Ecology
    • /
    • v.22 no.4
    • /
    • pp.539-558
    • /
    • 2013
  • The purpose of this study is to examine relationships among university students' self-differentiation, self-esteem and mental health. The subjects were 400 students of four universities in Busan and Gyungnam area. A questionnaire survey was done. The results of this study are as follows : First, the levels of university students' self-differentiation and self-esteem were high. Second, university students' self-differentiation and self-esteem were correlated positively. Third, the levels of university students' depression and anxiety were relatively low. It showed that the subjects' mental health of this study were not bad. Fourth, depression had no significant difference by gender. However, female students had higher anxiety than male students had. Fifth, university students' self-differentiation and self-esteem had negative correlation with depression and anxiety, and self-esteem played a role of mediating variable between self-differentiation and mental health. Sixth, family projection, family regression and self integration of self-differentiation had indirect influence upon the students' mental health through self-esteem, while cognitive-emotional function had direct influence upon mental health and had indirect influence upon mental health through self-esteem as well. In this study, university students' self-differentiation and self-esteem were found to be important variables having influence upon mental health, and self-differentiation had indirect influence upon mental health through self-esteem. Counselling intervention strategies should be established considering self-differentiation and self-esteem of the students who complained about their maladjusted emotion and human relation problems at schools. Also, programs enhancing self-differentiation and self-esteem of university students should be developed and the execution of these programs will be needed to help the university students who experienced mental health problems such as depression, anxiety and so on.

Text extraction from camera based document image (카메라 기반 문서영상에서의 문자 추출)

  • 박희주;김진호
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.8 no.2
    • /
    • pp.14-20
    • /
    • 2003
  • This paper presents a text extraction method of camera based document image. It is more difficult to recognize camera based document image in comparison with scanner based image because of segmentation problem due to variable lighting condition and versatile fonts. Both document binarization and character extraction are important processes to recognize camera based document image. After converting color image into grey level image, gray level normalization is used to extract character region independent of lighting condition and background image. Local adaptive binarization method is then used to extract character from the background after the removal of noise. In this character extraction step, the information of the horizontal and vertical projection and the connected components is used to extract character line, word region and character region. To evaluate the proposed method, we have experimented with documents mixed Hangul, English, symbols and digits of the ETRI database. An encouraging binarization and character extraction results have been obtained.

  • PDF