• Title/Summary/Keyword: variable sample size

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Determinants of Consumer Preference by type of Accommodation: Two Step Cluster Analysis (이단계 군집분석에 의한 농촌관광 편의시설 유형별 소비자 선호 결정요인)

  • Park, Duk-Byeong;Yoon, Yoo-Shik;Lee, Min-Soo
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.3
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    • pp.1-19
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    • 2007
  • 1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.

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The Prediction of DEA based Efficiency Rating for Venture Business Using Multi-class SVM (다분류 SVM을 이용한 DEA기반 벤처기업 효율성등급 예측모형)

  • Park, Ji-Young;Hong, Tae-Ho
    • Asia pacific journal of information systems
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    • v.19 no.2
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    • pp.139-155
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    • 2009
  • For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

Carbon Reduction by and Quantitative Models for Landscape Tree Species in Southern Region - For Camellia japonica, Lagerstroemia indica, and Quercus myrsinaefolia - (남부지방 조경수종의 탄소저감과 계량모델 - 동백나무, 배롱나무 및 가시나무를 대상으로 -)

  • Jo, Hyun-Kil;Kil, Sung-Ho;Park, Hye-Mi;Kim, Jin-Young
    • Journal of the Korean Institute of Landscape Architecture
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    • v.47 no.3
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    • pp.31-38
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    • 2019
  • This study quantified, through a direct harvesting method, storage and annual uptake of carbon from open-grown trees for three landscape tree species frequently planted in the southern region of Korea, and developed quantitative models to easily estimate the carbon reduction by tree growth for each species. The tree species for the study included Camellia japonica, Lagerstroemia indica, and Quercus myrsinaefolia, for which no information on carbon storage and uptake was available. Ten tree individuals for each species (a total of 30 individuals) were sampled considering various stem diameter sizes at given intervals. The study measured biomass for each part of the sample trees to quantify the total carbon storage per tree. Annual carbon uptake per tree was computed by analyzing the radial growth rates of the stem samples at breast height or ground level. Quantitative models were developed using stem diameter as an independent variable to easily calculate storage and annual uptake of carbon per tree for study species. All the quantitative models showed high fitness with $r^2$ values of 0.94-0.98. The storage and annual uptake of carbon from a Q. myrsinaefolia tree with dbh of 10 cm were 24.0 kg and 4.5 kg/yr, respectively. A C. japonica tree and L. indica tree with dg of 10 cm stored 11.2 kg and 8.1 kg of carbon and annually sequestered 2.6 kg and 1.2 kg, respectively. The above-mentioned carbon storage equaled the amount of carbon emitted from the gasoline consumption of about 42 L for Q. myrsinaefolia, 20 L for C. japonica, and 14 L for L. indica. A tree with the diameter size of 10 cm annually offset carbon emissions from gasoline use of approximately 8 L for Q. myrsinaefolia, 5 L for C. japonica, and 2 L for L. indica. The study pioneers in quantifying biomass and carbon reduction for the landscape tree species in the southern region despite difficulties in direct cutting and root digging of the planted trees.

Factors Affecting Physicians who will be Vaccinated Every Year after Receiving the COVID-19 Vaccine in Healthcare Workers (의료종사자의 COVID-19 예방 백신 접종받은 후 향후 매년 예방접종 의향에 미치는 요인)

  • Hyeun-Woo Choi;Sung-Hwa Park;Eun-Kyung Cho;Chang-hyun Han;Jong-Min Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.2
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    • pp.257-265
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    • 2023
  • The purpose of this study was to vaccinate every year according to the general characteristics of COVID-19, whether to vaccinate every year according to the vaccination experience, whether to vaccinate every year according to knowledge/attitude about vaccination, and negative responses to the vaccinate every year In order to understand the factors affecting the vaccination physician every year by identifying the factors of Statistical analysis is based on general characteristics, variables based on vaccination experience, and knowledge/attitudes related to vaccination. The doctor calculates the frequency and percentage, A square test (-test) was performed, and if the chi-square test was significant but the expected frequency was less than 5 for 25% or more, a ratio difference test was performed with Fisher's exact test. Through multiple logistic regression analysis using variables that were significant in simple analysis, a predictive model for future vaccination and the effect size of each independent variable were estimated. As statistical analysis software, SAS 9.4 (SAS Institute Inc., Cary, NC, USA) was used, and because the sample size was not large, the significance level was set at 10%, and when the p-value was less than 0.10, it was interpreted as statistically significant. In the simple logistic regression analysis, the reason why they answered that they would not be vaccinated every year was that they answered 'to prevent infection of family and hospital guests' rather than 'to prevent my infection' as the reason for the vaccination. It was 11.0 times higher and 3.67 times higher in the case of 'for the formation of collective immunity of the local community and the country'. The adverse reactions experienced after the 1st and 2nd vaccination were 8.42 times higher in those who did not experience pain at the injection site than those who did not, 4.00 times higher in those who experienced swelling or redness, and 5.69 times higher in those who experienced joint pain. There was a 5.57 times higher rate of absenteeism annually than those who did not. In addition, the more anxious they felt about vaccination, the more likely they were to not get the vaccine every year by 2.94 times.

Relationships Among Employees' IT Personnel Competency, Personal Work Satisfaction, and Personal Work Performance: A Goal Orientation Perspective (조직구성원의 정보기술 인적역량과 개인 업무만족 및 업무성과 간의 관계: 목표지향성 관점)

  • Heo, Myung-Sook;Cheon, Myun-Joong
    • Asia pacific journal of information systems
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    • v.21 no.4
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    • pp.63-104
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    • 2011
  • The study examines the relationships among employee's goal orientation, IT personnel competency, personal effectiveness. The goal orientation includes learning goal orientation, performance approach goal orientation, and performance avoid goal orientation. Personal effectiveness consists of personal work satisfaction and personal work performance. In general, IT personnel competency refers to IT expert's skills, expertise, and knowledge required to perform IT activities in organizations. However, due to the advent of the internet and the generalization of IT, IT personnel competency turns out to be an important competency of technological experts as well as employees in organizations. While the competency of IT itself is important, the appropriate harmony between IT personnel's business capability and technological capability enhances the value of human resources and thus provides organizations with sustainable competitive advantages. The rapid pace of organization change places increased pressure on employees to continually update their skills and adapt their behavior to new organizational realities. This challenge raises a number of important questions concerning organizational behavior? Why do some employees display remarkable flexibility in their behavioral responses to changes in the organization, whereas others firmly resist change or experience great stress when faced with the need to alter behavior? Why do some employees continually strive to improve themselves over their life span, whereas others are content to forge through life using the same basic knowledge and skills? Why do some employees throw themselves enthusiastically into challenging tasks, whereas others avoid challenging tasks? The goal orientation proposed by organizational psychology provides at least a partial answer to these questions. Goal orientations refer to stable personally characteristics fostered by "self-theories" about the nature and development of attributes (such as intelligence, personality, abilities, and skills) people have. Self-theories are one's beliefs and goal orientations are achievement motivation revealed in seeking goals in accordance with one's beliefs. The goal orientations include learning goal orientation, performance approach goal orientation, and performance avoid goal orientation. Specifically, a learning goal orientation refers to a preference to develop the self by acquiring new skills, mastering new situations, and improving one's competence. A performance approach goal orientation refers to a preference to demonstrate and validate the adequacy of one's competence by seeking favorable judgments and avoiding negative judgments. A performance avoid goal orientation refers to a preference to avoid the disproving of one's competence and to avoid negative judgements about it, while focusing on performance. And the study also examines the moderating role of work career of employees to investigate the difference in the relationship between IT personnel competency and personal effectiveness. The study analyzes the collected data using PASW 18.0 and and PLS(Partial Least Square). The study also uses PLS bootstrapping algorithm (sample size: 500) to test research hypotheses. The result shows that the influences of both a learning goal orientation (${\beta}$ = 0.301, t = 3.822, P < 0.000) and a performance approach goal orientation (${\beta}$ = 0.224, t = 2.710, P < 0.01) on IT personnel competency are positively significant, while the influence of a performance avoid goal orientation(${\beta}$ = -0.142, t = 2.398, p < 0.05) on IT personnel competency is negatively significant. The result indicates that employees differ in their psychological and behavioral responses according to the goal orientation of employees. The result also shows that the impact of a IT personnel competency on both personal work satisfaction(${\beta}$ = 0.395, t = 4.897, P < 0.000) and personal work performance(${\beta}$ = 0.575, t = 12.800, P < 0.000) is positively significant. And the impact of personal work satisfaction(${\beta}$ = 0.148, t = 2.432, p < 0.05) on personal work performance is positively significant. Finally, the impacts of control variables (gender, age, type of industry, position, work career) on the relationships between IT personnel competency and personal effectiveness(personal work satisfaction work performance) are partly significant. In addition, the study uses PLS algorithm to find out a GoF(global criterion of goodness of fit) of the exploratory research model which includes a mediating variable, IT personnel competency. The result of analysis shows that the value of GoF is 0.45 above GoFlarge(0.36). Therefore, the research model turns out be good. In addition, the study performs a Sobel Test to find out the statistical significance of the mediating variable, IT personnel competency, which is already turned out to have the mediating effect in the research model using PLS. The result of a Sobel Test shows that the values of Z are all significant statistically (above 1.96 and below -1.96) and indicates that IT personnel competency plays a mediating role in the research model. At the present day, most employees are universally afraid of organizational changes and resistant to them in organizations in which the acceptance and learning of a new information technology or information system is particularly required. The problem is due' to increasing a feeling of uneasiness and uncertainty in improving past practices in accordance with new organizational changes. It is not always possible for employees with positive attitudes to perform their works suitable to organizational goals. Therefore, organizations need to identify what kinds of goal-oriented minds employees have, motivate them to do self-directed learning, and provide them with organizational environment to enhance positive aspects in their works. Thus, the study provides researchers and practitioners with a matter of primary interest in goal orientation and IT personnel competency, of which they have been unaware until very recently. Some academic and practical implications and limitations arisen in the course of the research, and suggestions for future research directions are also discussed.

Spatial Distribution Patterns and Prediction of Hotspot Area for Endangered Herpetofauna Species in Korea (국내 멸종위기양서·파충류의 공간적 분포형태와 주요 분포지역 예측에 대한 연구)

  • Do, Min Seock;Lee, Jin-Won;Jang, Hoan-Jin;Kim, Dae-In;Park, Jinwoo;Yoo, Jeong-Chil
    • Korean Journal of Environment and Ecology
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    • v.31 no.4
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    • pp.381-396
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    • 2017
  • Understanding species distribution plays an important role in conservation as well as evolutionary biology. In this study, we applied a species distribution model to predict hotspot areas and habitat characteristics for endangered herpetofauna species in South Korea: the Korean Crevice Salamander (Karsenia koreana), Suweon-tree frog (Hyla suweonensis), Gold-spotted pond frog (Pelophylax chosenicus), Narrow-mouthed toad (Kaloula borealis), Korean ratsnake (Elaphe schrenckii), Mongolian racerunner (Eremias argus), Reeve's turtle (Mauremys reevesii) and Soft-shelled turtle (Pelodiscus sinensis). The Kori salamander (Hynobius yangi) and Black-headed snake (Sibynophis chinensis) were excluded from the analysis due to insufficient sample size. The results showed that the altitude was the most important environmental variable for their distribution, and the altitude at which these species were distributed correlated with the climate of that region. The predicted distribution area derived from the species distribution modelling adequately reflected the observation site used in this study as well as those reported in preceding studies. The average AUC value of the eigh species was relatively high ($0.845{\pm}0.08$), while the average omission rate value was relatively low ($0.087{\pm}0.01$). Therefore, the species overlaying model created for the endangered species is considered successful. When merging the distribution models, it was shown that five species shared their habitats in the coastal areas of Gyeonggi-do and Chungcheongnam-do, which are the western regions of the Korean Peninsula. Therefore, we suggest that protection should be a high priority in these area, and our overall results may serve as essential and fundamental data for the conservation of endangered amphibian and reptiles in Korea.

Risk factors associated with complicated methicillin-resistant Staphylococcus aureus bacteremia in neonates (신생아의 MRSA 균혈증에서 합병증 발생과 연관된 위험인자)

  • Lee, Young Jin;Kim, Hyen Jin;Byun, Shin Yun;Park, Su Eun;Park, Hee Ju
    • Clinical and Experimental Pediatrics
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    • v.53 no.2
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    • pp.173-177
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    • 2010
  • Purpose : Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen that causes nosocomial infection in NICU. It contributes to neonatal morbidity and mortality with variable complications. This study was conducted to identify the risk factors associated with complicated MRSA bacteremia in neonates. Methods : We reviewed the medical records of 44 neonates with positive blood culture for MRSA who were admitted to the NICU of Pusan National University Hospital from January 2002 to December 2007. We compared various factors of the complicated and uncomplicated MRSA bacteremia cases. Results : Of the 44 neonates, 31 were male and 13, female. The mean gestational age and birth weight were $33.2{\pm}4.9$ weeks and $1,859.9{\pm}962.2g$, respectively. Twenty-one of infants were treated with a mechanical ventilator during a mean of $8.8{\pm}13.8$ days. There were 13 cases of complicated and 31 cases of uncomplicated MRSA bacteremia. Between the 2 groups, we compared the following variables: gestational age, birth weight, ventilator use, umbilical catheter use and central catheter insertion, $O_2$ inhalation, first oral feeding day after birth, underlying disease, transfusion, and initial vancomycin use. The underlying disease and transfusion were the risk factors related to complicated MRSA bacteremia. Conclusion : Complicated MRSA bacteremia is related to underlying disease and transfusion. Since this was a retrospective study with a small sample size, it offered limited capacity to compare complicated and uncomplicated MRSA bacteremia. A prospective study with a larger population is needed to determine the exact characteristics of MRSA bacteremia in NICU.

Carbon Reduction Effects of Urban Landscape Trees and Development of Quantitative Models - For Five Native Species - (도시 조경수의 탄소저감 효과와 계량모델 개발 - 5개 향토수종을 대상으로 -)

  • Jo, Hyun-Kil;Kim, Jin-Young;Park, Hye-Mi
    • Journal of the Korean Institute of Landscape Architecture
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    • v.42 no.5
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    • pp.13-21
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    • 2014
  • This study generated regression models to quantify storage and annual uptake of carbon from five native landscape tree species through a direct harvesting method, and established essential information to estimate carbon reduction effects from urban greenspaces. Tree species for the study included the Chionanthus retusus, Prunus armeniaca, Abies holophylla, Cornus officinalis, and Taxus cuspidata, which are usually planted in cities of middle Korea, but for which no information on carbon reduction is available. Ten tree individuals for each species were sampled reflecting various stem diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute total carbon storage per tree. The annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at breast height or ground level. Regression models were developed using diameter at breast height (dbh) or ground level (dg) as an independent variable to easily estimate storage and annual uptake of carbon per tree for each species. All the regression models showed high fitness with $r^2$ values of 0.92~0.99. Storage and annual uptake of carbon from a tree with dbh of 10 cm were greatest with C. retusus (20.0 kg and 5.9 kg/yr, respectively), followed by P. armeniaca (17.5 kg and 4.5 kg/yr) and A. holophylla (13.2kg and 1.8 kg/yr) in order. A C. officinalis tree and T. cuspidata tree with dg of 10 cm stored 9.3 and 6.3 kg of carbon and annually sequestered 3.2 and 0.6 kg, respectively. The above-mentioned carbon storage equaled the amount of carbon emitted from gasoline consumption of about 23~35 L for C. retusus, P. armeniaca, and A. holophylla, and 11~16 L for C. officinalis and T. cuspidata. A tree with the diameter size of 10 cm annually offset carbon emissions from gasoline use of about 6~10 L for C. retusus, P. armeniaca, and C. officinalis, and 1~3 L for A. holophylla and T. cuspidata. The study breaks new ground to easily quantify biomass and carbon reduction for the tree species by overcoming difficulties in direct cutting and root digging of urban landscape trees.

Minor Physical Anomalies in Patients with Schizophrenia (정신분열병 환자에서 신체미세기형에 관한 연구)

  • Joo, Eun-Jeong;Jeong, Seong Hoon;Maeng, So Jin;Yoon, Se Chang;Kim, Jong Hoon;Kim, Chul Eung;Shin, Youngmin;Kim, Yong Sik
    • Korean Journal of Biological Psychiatry
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    • v.9 no.2
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    • pp.140-151
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    • 2002
  • Object and Method:Minor physical anomalies(MPAs) are frequently seen in patients with schizophrenia. MPAs are considered to arise from the anomalous development of ectoderm-originated tissues in the developing fetus. Since the central nervous system originates from ectoderm, MPAs can be regarded as externally observable and objective indicators of the aberrant development which might have taken place in the central nervous system. To investigate whether MPAs are more frequent in schizophrenic patients, the frequencies of MPAs were compared between schizophrenic patients and normal controls. Total 245 schizophrenic patients diagnosed with DSM-IV(male : 158, female : 87), and 418 normal control subjects(male : 216, female : 202) were included in this study. The MPAs were measured using the modified Waldrop scale with fifteen items in six bodily regions; head, eye, ear, mouth, hand, and foot. Result:The total scores of Waldrop scale were $4.40{\pm}1.93$($mean{\pm}standard$ deviation) in patients and $3.43{\pm}1.68$ in controls for females, and for males, $4.58{\pm}1.75$ in patients and $4.28{\pm}1.59$ in controls. For females, the excess of MPAs in schizophrenic patients was statistically significant(t-test : p<0.001). For males, schizophrenic patients also showed more MPAs than normal controls, but this tendency did not reach statistical significance (t-test : p=0.094). When the modified Waldrop total scores excluding head circumference were compared, the total scores in schizophrenic patients were significantly higher for both male and female subjects(t-test : male p<0.001, female p=0.001). The individual anomaly items included in Waldrop scale were also investigated. The items of epicanthus, hypertelorism, malformed ears, syndactylia were significantly more frequent in schizophrenic patients. In contrast, the items of adherent ear lobes, asymmetric ears, furrowed tongue, curved fifth finger, single palmar crease and big gap between toes did not show any differences in frequency between schizophrenic patients and normal controls. Since a lot of statistical analyses showed different results between male and female subjects, it seems to be necessary to consider gender as an important controlling variable for the analysis, however only the item of head circumference showed statistically significant gender-related difference according to log-linear analysis. Conclusion:With a relatively large sample size, the frequencies of MPAs enlisted in Waldrop scale were compared between schizophrenic patients and normal controls in this study. MPAs were more frequently seen in schizophrenic patients and, especially, several specific items in the Waldrop scale showed prominent excess in schizophrenic patients. Although definite conclusions cannot be drawn due to the inherent limitation of the study using Waldrop scale, these results seem to support the possibility that aberrant neurodevelopmental process might be involved in the pathogenesis of schizophrenia in some of the patients.

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The Relationships between Dry Matter Yield and Days of Summer Depression in different Regions with Mixed Pasture (혼파초지에서 지역별 건물수량과 하고일수 간 관계)

  • Oh, Seung Min;Kim, Moonju;Peng, Jinglun;Lee, Bae Hun;Kim, Ji Yung;Chemere, Befekadu;Kim, Si Chul;Kim, Kyeong Dae;Kim, Byong Wan;Jo, Mu Hwan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.38 no.1
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    • pp.53-60
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    • 2018
  • Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.