• Journal of Information Processing Systems
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• 제20권3호
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• pp.345-359
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• 2024

A regression model represents the relationship between explanatory and response variables. In real life, explanatory variables often affect a response variable with a certain time lag, rather than immediately. For example, the marriage rate affects the birth rate with a time lag of 1 to 2 years. Although deep learning models have been successfully used to model various relationships, most of them do not consider the time lags between explanatory and response variables. Therefore, in this paper, we propose an extension of deep learning models, which automatically finds the time lags between explanatory and response variables. The proposed method finds out which of the past values of the explanatory variables minimize the error of the model, and uses the found values to determine the time lag between each explanatory variable and response variables. After determining the time lags between explanatory and response variables, the proposed method trains the deep learning model again by reflecting these time lags. Through various experiments applying the proposed method to a few deep learning models, we confirm that the proposed method can find a more accurate model whose error is reduced by more than 60% compared to the original model.

• 한국지역사회생활과학회지
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• 제11권2호
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• pp.1-14
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• 2000

The purpose of this study was to empirically verify influence of objective variables and subjective variables of time management strategy of unmarried men and women and provide a basis for the development of time management. The subject of this study were 370 unmarried men and women and interviewed with a questionnaire. The data were analyzed by SPSS/PC+ program for the frequency, mean, standard deviation, and regression analysis. The major results of this study were as follows: 1. The score of implementing time management strategy of unmarried men and women was the highest. The score of getting support time management strategy of unmarried men and women was the lowest. 2. Variables that affect overall time management strategy were age, academic career, sex, degree of information using fate control orientation and communication. 3. The relative contribution of subjective variables on time management strategy were higher than objective variables.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.985-994
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• 2007

We note that the time of adolescents is very important time for obtaining informations about their jobs, exploring and making appropriate their career decision. In order to understand the career decision level of adolescents, we needed a study on effects of personal variables and family variables affecting the career decision level. For this, we provide direct, indirect and total effects of family variables and personal variables on the career decision level using the path analysis. Therefore, in this study, we give the real usefulness for making a different diagnosis and strategy solving some problems of career decision level.

• 한국시뮬레이션학회논문지
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• 제7권2호
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• 가족자원경영과 정책
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• 제12권1호
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• pp.41-55
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• 2008

The purpose of this study was to clarify variables affecting time management practice and the relationship between the practice and academic achievement of middle school students. Questionnaires including a time management scale were used for this study and the survey data were taken from 352 middle school students in Seoul and Gyeonggi-do. The statistical methods for the analysis were frequency, percentage, average, t-test, ANOVA and Pearson's correlation. The variables affecting student time management were gender, their standard of living, parental educational level and parental occupation. Religion and residential area were indicated as variables affecting several subscales of time management but the academic year of student had no effect on student time management behavior. The relationship between time management and the academic achievement of middle school students was slightly positive. Developing programs for time management in the field of family resource management is also necessary.

• 대한가정학회지
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• 제30권4호
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• pp.261-278
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• 1992

The purpose of this study is to compare the time use of urban housewives 1980 and 1990, and to investigate significant variables affect to the time spent, the independent effect of variables to the time use of her them. For this purpose, the data from 261(1980) and 287(1990) were analyzed. The major findings are follows: 1. There was 3-4 hours decreasing for household work in 1980 & 1990, and the significant variables were age, number of children, years of youngest child, education, type of kitchen, and type of heating, but in 1990, number of children and education of housewife. 2. In 1990, the independent effect of variables to household work time are number of children, years of youngest child, and cooking fuel to household work time and income to physiological time.

• 한국조리학회지
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• 제20권5호
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• pp.71-75
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• 2014

The purpose of this study is to verify antecedent variables that affect emotional labor. The results are as follows. First, display rules positively affected deep acting and negatively affected surface acting. Second, customer contact time positively affected deep acting but did not affect surface acting. Third, the interaction between display rules and customer contact time did not have significant effects on surface acting but negatively affected deep acting. The implications based on these results are as follows. First, theoretically, this study extends the range of leading variables that affect emotional labor and verifies the moderation effects between these variables. Next, practically, this study suggests that presenting harmonious criteria with regards to display rules and customer contact time that fit well into the concept of food service company is a very useful tool to manage emotional labor of the employees. The limitation of this study is that the causal relationship between variables demonstrated in this study cannot be generalized due to convenience sampling and cross sectional research.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권7호
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• pp.363-369
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• 2000

To flexibly evaluate performance and reliability of an electric power system in the aspect of the real-time system which is intrinsically characterized by stringent timing constraints fails catastrophically if its control input is not updated by its digital controller computer within a certain time limit called the hard deadline, we propose fuzzy-random variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas as well.

• Maxillofacial Plastic and Reconstructive Surgery
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• 제23권3호
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• pp.238-243
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• 2001

Purpose : The purpose of this study was to determine radiologic variables affecting extraction of impacted mandibular third molar. Materials and Methods : This study was investigated on 44 consecutive extractions of unilateral impacted mandibular third molars (Male;34, Female;10, Mean age;24.98, Age range;19-35). Fourteen radiologic variables, which were actual value except only one, were evaluated to establish their relation to the operation time. The Pearson correlation coefficient and Stepwise procedures for regression analysis were carried out. Results : Eight variables (depth, angulation, ramus width, relationship to the second molar, distal ramus depth, mesial ramus depth, mesial periodontal ligament width and follicle) showed a statistically significant relation to the operation time(Pearson correlation coefficient, p<0.05). Two variables, depth and mesial periodontal ligament width, showed the most powerful and just relation to the operation time($r^2$ = 0.349, p<0.05). Conclusion : This study shows that our results can help general practioner to estimate the operation time of extraction of impacted mandibular third molars by measuring two radiologic variables ; depth and mesial periondontal ligament width.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.450-456
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• 2003

This paper proposes a multiple time-series model with dummy variables for one-hour ahead load forecasting. We used 11 dummy variables that were classified by day characteristics such as day of the week, holiday, and special holiday. Also, model specification and selection of input variables including dummy variables were made by test statistics such as AIC(Akaike Information Criterion) and t-test statistics of each coefficient. OLS (Ordinary Least Squares) method was used for estimation and forecasting. We found out that model specifications for each hour are not identical usually at 30％ of optimal significance level, and dummy variables reduce the forecasting error if they are classified properly. The proposed model has much more accurate estimates in forecasting with less MAPE (Mean Absolute Percentage Error).