• 한국기계연구소 소보
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• s.18
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• pp.125-129
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• 1988

This paper proposes a sensitivity technique for analysis of the relationships between input variables (known values) and output variables(unknown values), These design variables are constrained by design equations. Thus, the output variables can be calculated by solving the equations with eliminating the input variables from the equations because the input variables become constants. If the output variables are not satisfied, the values of the input variables must be adjusted by increasing or decreasing the values and then the problem must be solved again. This is called as the iterative design procedure. The sensitivity technique, presented in this paper, gives the sensitivity on the changes of the values of the output variables to the input variables.

• Journal of the Korean Home Economics Association
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• v.32 no.3
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• pp.171-184
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• 1994

This study examined the characteristics of the relationship of environmental variables that is HOME socio-demographic variables and children's verbal ability at age five. Especially this study investigated causal relationships among the variables which are supposed to affect children's verbal ability. The subjects of this study were 60 children at age five and their mothers. Instruments included inventory of home stimulation(HOME) inventory of socio-demographic variables inventory of the children's verbal ability and intelligence test. The results obtained from study were as follows: 1. For the most part environmental variables had a significant positive correlation with children's verbal ability 2. The variables that significantly predicted boy's verbal ability were aspects of physical environment breadth of experienc. And the variables that significantly predicted girls' verbal ability were developmental stimulation economic status of the home. 3. The results of the analysis of the causal model showed that the kind of variables that affected boy's verbal ability directly were indirect stimulation direct stimulation. And the kind of variables that affected girls' verbal ability directly were direct stimulation econmic status of the home inditect stimulation. 4. Another causal model of the environmental variables affecting children's verbal ability were formulated by exogenous variables(socio-demographic variables) and by endogenous variables (HOME, children's intelligence). The results of the analysis of the causal model showed that only HOME variables significantly affected boy's and girls' verbal ability directly.

• Journal of Navigation and Port Research
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• v.43 no.2
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• pp.134-141
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• 2019

The objective of this study was to establish whether global macroeconomic indicators affect the profitability of Korean shipping companies by using panel regression analysis. OROA (operating return on assets) and ROA (ratio of net profit to assets) were selected as proxy variables for profitability. OROA and ROA were used as dependent variables. The world GDP growth rate, interest rate, exchange rate, stock index, bunker price, freight, demand and supply of the world shipping market were set as independent variables. The size of the firm was added to the control variable. For small-sized firms, OROA was not affect by macroeconomic indicators. However, ROA was affected by variables such as interest rates, bunker prices, and size of firms. For medium-sized firms, OROA was affected by demand, supply, GDP, freight, and asset variables. However, macroeconomic indicators did not affect ROA. For large-sized firms, freight, GDP, and stock index (SCI; Shanghai Composite Index) have an effect on OROA. ROA was analyzed to be influenced by bunker price and SCI.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.261-272
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• 2019

In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

• Journal of the Korean Home Economics Association
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• v.40 no.7
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• pp.83-100
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• 2002

The purpose of this study is to examine related variables to goods purchase by consumers using the home shopping of cable TV. For the purpose accomplishment, this study analyzed the variables which influence on the purchase by demographic variables, consumers'shopping propensity, perceived risk and benefit. The major findings are as follows; In the purchase of convenience goods, the variables which influence positively are sex, job(housewife), instantly impulse purchasing propensity, and diversity of goods information. On the other hand, the variables which influence negatively are risk of delivery & returned goods, and risk of quality. In the purchase of shopping goods, the variables which influence positively are state of marriage, job(nonspecialist), and diversity of goods information. On the other hand, the variables which influence negatively are pleasure of shopping-oriented, risk of delivery & returned goods, and risk of quality. In the purchase of specialty goods, the variables which influence positively are sex, income, convenience of time, and convenience of approach. On the other hand, the variables which influence negatively are pleasure of shopping-oriented, and risk of price & information restriction.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.130-138
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• 2023

The selection of the correct examination variables for diagnosing heart disease provides many benefits, including faster diagnosis and lower cost of examination. The selection of inspection variables can be performed by referring to the data of previous examination results so that future investigations can be carried out by referring to these selected variables. This paper proposes a model for selecting examination variables using an Artificial Bee Swarm Optimization method by considering the variables of accuracy and cost of inspection. The proposed feature selection model was evaluated using the performance parameters of accuracy, area under curve (AUC), number of variables, and inspection cost. The test results show that the proposed model can produce 24 examination variables and provide 95.16% accuracy and 97.61% AUC. These results indicate a significant decrease in the number of inspection variables and inspection costs while maintaining performance in the excellent category.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.2
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• pp.123-132
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• 2000

Evaluation method of soil fertility by combination of soil color characteristics and survey data from soil map as well as chemical properties was investigated on total 35 field and pot experiments. Total 35 tobacco fields including 11 fields located at Cheonweon county in Chungnam Province, 9 fields located at Goesan county in Chungbuk Province, and 15 fields located at Youngcheon county in Kyongbuk Province were selected in 1984 to cover the wide range of distribution in landscape and soil attributes. Yields of tobacco grown on the plots of both the pot and field experiment which were not applied with any fertilizer were considered as basic fertility of the soil (BFS). The BFS was estimated by 32 independent variables including 15 chemical properties, 3 color characteristics, and 14 soil survey data from soil map. Twenty-four independent variables containing 16 quantitative variables selected from 24 quantitative variables by collinearity diagnostics and 8 qualitative variables, were classified and analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Tobacco yield of field experiment showed high variations by eight times in difference between minimum and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including quantitative variables was still more confidential than that by a single index and that showed more improvement of coefficient of determination ($R^2$) in pot experiment than in field experiment. Evaluation for the BFS by MLR in field experiment was still improved by adding qualitative variables as well as quantitative variables. The variability in the BFS of field experiment was explained 43.2% by quantitative variables and 67.95% by adding both the quantitative and qualitative variables compared with 21.7% by simple regression with NO$_3$-N content in soil. The regression evaluation for the best evaluation of the BFS of field experiment by MLR included NO$_3$-N content, L value, and a value of soil color as quantitative variables and available soil depth and topography as qualitative variables. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for tobacco field.

• Journal of the Korean Society of Clothing and Textiles
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• v.12 no.3 s.28
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• pp.309-318
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• 1988

The purposes of this study were: 1) to develop specific AIO variables(clothing variables) based on clothing behavior studies, 2) to segment apparel market by clothing variables, 3) to discribe the profile of each segment with clothing variables, lifestyle variables and demographic variables, 4) to Suggest effective strategies on apparel market of women's clothing. The Likert Type clothing questionnaires measured 6 aspects of clothing (fashion, conformity-individuality, practicality, aesthetics, modesty and brand consciousness & status symbols) dealing with activities, interests and opinions. In addition, lifestyle variables were measured with general AIO statements. The questionnaires were administered to 563 young women (students, career women and homemakers) living in Seoul. The data were analysed by factor analysis, ctustering analysis, multiple discriminant analysis, one-way ANOVA ana Duncan's multiple range test. The results of the study were as follow: 1) 4 factors emerged from factor analysis of clothing variables. Factor 1: lower interest in modesty and higher interest in aesthics, Factor 2: brand consciousness and status symbols, Factor 3: conformity, Factor4 : fashion. 2) Lifestyle variables clustered into 3 factors. Factor 1: positive social activity, Factor 2: family-oriented type, Factor S: materialism. 3) By cluster analysis of the 4 factors of the clothing variables, the apparel market of women's clothing was categorised into 3 segments (innovative aesthetics seeker group, brand and status symbols conscious group, clothing unconscious group). 4) The above three segmented groups were also significantly discriminated by lifestyle and demosraphic variables. 5) On the basis of the findings, effective marketing strategies of women's clothing were suggested.

• Journal of Families and Better Life
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• v.25 no.4
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• pp.43-55
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• 2007

The Purpose of this study was to investigate the ecological variables on adolescent's sociometric popularity. Independent variables were organism(sex, age, aggression, self-esteem, impulsiveness, prosocial behavior, dominance), microsystem(parenting style, family support, friends relationship, teacher support), mesosystem(family-peer relationship, family-school relationship), and exosystem(positive community environment, social support of extended family, school's policy). The subjects were 835 - 1st and 2nd graders of two middle and two high schools in Daegu. Adolescent's sociometric popularity and ecological variables were measured with questionnaire. Adolescent's sociometric popularity was measured with sociometric popularity questionnaire. Organism variables were measured with sex, age, aggression, self-esteem, impulsiveness, prosocial behavior and dominance questionnaire. Microsystem variables were measured with parenting style, family support, friends relationship and teacher support questionnaire. Mesosystem variables were measured with family-peer relationship and family-school relationship questionnaire. Exosystem variables were measured with positive community environment, social support of extended family and school's policy questionnaire. The data analyzed by frequency, percentage, mean, cronbach's $\alpha$, and multiple regression. The major findings were as follows: First, adolescent's sociometric popularity was affected by age, overt aggression, academic self-esteem, social self-esteem, and impulsiveness of organism variables. Second, adolescent's sociometric popularity was affected by mother's affectional parenting, mother's control parenting, and attachment to friends of microsystem variables. Third, adolescent's sociometric popularity was affected by family - peer relationship and family - school relationship of mesosystem variables. Fourth, adolescent's sociometric popularity was affected by appraisal support of extended family, after-school activity, and circle activity of exosystem variables.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.147-150
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• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.