• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.109-121
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• 2021

As the global COVID-19 pandemic is prolonged, the Corona Blue phenomenon, combined with COVID-19 and blue, is intensifying. The purpose of this study is to analyze the current trend of Corona Blue in consideration of the possibility of increasing mental illness and the need for countermeasures, especially after COVID-19. This study tried to find out the relationship between stress and leisure activities before and after COVID-19 by using Corona Blue news article analysis through the topic modeling method, and questionnaire find out the help of stress and leisure activities. This study was compared and analyzed using two research methods. First, a total of 363 news articles were analyzed through topic modeling based on newspaper articles from January 2020, when COVID- 19 was upgraded to the "border" stage, until September, where the social distancing stage was strengthened to stage 2.5 in Korea. As a result of the study, a total of 28 topics were extracted, and similar topics were grouped into 7 groups: mental-demic, generational spread, causes of depression acceleration, increased fatigue, attitude to coping with long-term wars, changes in consumption, and efforts to overcome depression. Second, the SPSS statistical program was used to analyze the level of stress change according to leisure activities before/after COVID-19 and the main help according to leisure activities. As a result of the study, it was confirmed that the average difference in stress reduction according to participation in leisure activities before COVID-19 was larger than after COVID-19. Also, leisure activities were found to be effective in stress relief even after COVID-19. In addition, if the main help from leisure activities before COVID-19 was the meaning of relaxation and recharging through physical and social activities. After COVID-19, psychological roles such as mood swings through nature, outdoor activities, or intellectual activities were found to play a large part. As such, in this study, it was confirmed that understanding the current status of Corona Blue and coping with leisure in extreme stress situations has a positive effect. It is expected that this research can serve as a basis for preparing realistic and desirable leisure policies and countermeasures to overcome Corona Blue.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.09a
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• pp.125-153
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• 2005

It has been widely known that the seismic piezo-cone penetration test (SCPTU) is one of the most useful techniques for investigating the geotechnical characteristics including dynamic soil properties. As the practical applications in Korea, SCPTU was carried out at two sites in Busan and four sites in Incheon, which are mainly composed of alluvial or marine soil deposits. From the SCPTU waveform data obtained from the testing sites, the first arrival times of shear waves were and the corresponding time differences with depth were determined using the cross-over method, and the shear wave velocity profiles (VS) were derived based on the refracted ray path method based on Snell's law and similar to the trend of cone tip resistance (qt) profiles. In Incheon area, the testing depths of SCPTU were deeper than those of conventional down-hole seismic tests. Moreover, for the application of the conventional CPTU to earthquake engineering practices, the correlations between VS and CPTU data were deduced based on the SCPTU results. For the empirical evaluation of VS for all soils together with clays and sands which are classified unambiguously in this study by the soil behavior type classification Index (IC), the authors suggested the VS-CPTU data correlations expressed as a function of four parameters, qt, fs, $\sigma$, v0 and Bq, determined by multiple statistical regression modeling. Despite the incompatible strain levels of the down-hole seismic test during SCPTU and the conventional CPTU, it is shown that the VS-CPTU data correlations for all soils clays and sands suggested in this study is applicable to the preliminary estimation of VS for the Korean deposits and is more reliable than the previous correlations proposed by other researchers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.136-152
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• 2017

The thermodynamic models, PC-SAFT (Perturbed-Chain Statistical Associated Fluid Theory) state equation and the Two-model approach liquid activity coefficient model NRTL (Non Random Two Liquid) + Henry + Peng-Robinson, for modeling the Rectisol process using methanol aqueous solution as the $CO_2$ removal solvent were compared. In addition, to determine the new binary interaction parameters of the PC-SAFT state equations and the Henry's constant of the two-model approach, absorption equilibrium experiments between carbon dioxide and methanol at 273.25K and 262.35K were carried out and regression analysis was performed. The accuracy of the newly determined parameters was verified through the regression results of the experimental data. These model equations and validated parameters were used to model the carbon dioxide removal process. In the case of using the two-model approach, the methanol solvent flow rate required to remove 99.00% of $CO_2$ was estimated to be approximately 43.72% higher, the cooling water consumption in the distillation tower was 39.22% higher, and the steam consumption was 43.09% higher than that using PC-SAFT EOS. In conclusion, the Rectisol process operating under high pressure was designed to be larger than that using the PC-SAFT state equation when modeled using the liquid activity coefficient model equation with Henry's relation. For this reason, if the quantity of low-solubility gas components dissolved in a liquid at a constant temperature is proportional to the partial pressure of the gas phase, the carbon dioxide with high solubility in methanol does not predict the absorption characteristics between methanol and carbon dioxide.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.207-224
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• 2006

It has been widely known that the seismic piezo-cone penetration test (SCPTu) is one of the most useful techniques for investigating the geotechnical characteristics such as static and dynamic soil properties. As practical applications in Korea, SCPTu was carried out at two sites in Busan and four sites in Incheon, which are mainly composed of alluvial or marine soil deposits. From the SCPTu waveform data obtained from the testing sites, the first arrival times of shear waves and the corresponding time differences with depth were determined using the cross-over method, and the shear wave velocity $(V_S)$ profiles with depth were derived based on the refracted ray path method based on Snell's law. Comparing the determined $V_S$ profile with the cone tip resistance $(q_t)$ profile, both trends of profiles with depth were similar. For the application of the conventional CPTu to earthquake engineering practices, the correlations between $V_S$ and CPTu data were deduced based on the SCPTu results. For the empirical evaluation of $V_S$ for all soils together with clays and sands which are classified unambiguously in this study by the soil behavior type classification index $(I_C)$, the authors suggested the $V_S-CPTu$ data correlations expressed as a function of four parameters, $q_t,\;f_s,\;\sigma'_{v0}$ and $B_q$, determined by multiple statistical regression modeling. Despite the incompatible strain levels of the downhole seismic test during SCPTu and the conventional CPTu, it is shown that the $V_S-CPTu$ data correlations for all soils, clays and sands suggested in this study is applicable to the preliminary estimation of $V_S$ for the soil deposits at a part in Korea and is more reliable than the previous correlations proposed by other researchers.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.12
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• pp.1880-1892
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• 2010

The purposes of this study were to: a) provide evidence concerning the effects of emotional intelligence on job outcomes, b) examine the impacts of emotional intelligence on employee-related variables such as 'job satisfaction', 'organizational commitment', 'organizational performance', and 'turnover intention' c) identify the conceptual framework underlying emotional intelligence. A survey was conducted to collect data from foodservice managers (N=231). Statistical analyses were completed using SPSS Win (16.0) for descriptive analysis, reliability analysis, factor analysis, t-test, correlation analysis, cluster analysis and AMOS (16.0) for confirmatory factor analysis and structural equation modeling. The concept of emotional intelligence (EI) has been on the radar screens of many leaders and managers over the last several decades. The emotional intelligence is generally accepted to be a combination of emotional and interpersonal competencies that influence behavior, thinking and interaction with others. The main results of this study were as follows. The four EI (Emotional Intelligence) dimensions correlated significantly with age. The means of job satisfaction score were above the midpoint (3.04 point) scale. The organizational commitment score was above the midpoint (3.41 point) scale and was higher at 'loyalty' factor than 'commitment' factor. The means of organizational performance score were above the midpoint (3.34) scale. The correlations among the four EI (emotional intelligence) factors were significant with job satisfaction; organizational commitment, organizational performance and turnover intention. The test of hypothesis using structural equation modeling found that emotional intelligence produced positive effects on job attitude and job performance. Emotional intelligence enhanced organizational commitment, and in turn, managers' attitude produced positive effects on organizational performance; emotional intelligence also had a direct impact on organizational performance. This study has identified the effect of emotional intelligence on organizational performance and attitudes toward one's job.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Journal of the Korean association of regional geographers
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• v.6 no.2
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• pp.1-19
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• 2000

This study is to investigate and analyze regional patterns of aging in Taejeon Metropolitan city-the overpopulated area of Choong-Cheong Province-by cohort analysis method. According to the population structure transition caused by rapid social and economic changes, Korea has made a rapid progress in population aging since 1970. This trend is so rapid that we should prepare for and cope with aging society. It is not only slow to cope with it in our society, but also there are few studies on population aging of the geographical field in Korea. The data of this study are the reports of Population and Housing Censuses in 1975 and 1985 and General Population and Housing Censuses with 10% sample survey in 1995 taken by National Statistical Office. The research method is to sample as the aging district the area with high aged population rate where the populations over 60 reside among total population during the years of 1975, 1985, 1995 and to sample the special districts of decreasing population where the population decreases very much and the special districts of increasing population in which the population increases greatly, presuming that the reason why aged population rate increases is that non-elderly population high in mobility moves out. It is then verified and ascertained whether it is true or not with cohort analysis method by age. Finally regional patterns in the city are found through the classification and modeling by type based on the aging district, the special districts of decreasing population, and the special districts of increasing population. The characteristics of the regional patterns show that there is social population transition and that non-elderly population moves out. The aging district with the high aged population rate is divided into high-level keeping-up type, relative falling type below the average of Taejeon city in aging progress, and relative rising type above the average of the city. This district can be found at both the central area of the city and the suburbs because Taejeon city has the characteristic of over-bounded city. But it cannot be found at the new built-up area with the in-migration of large population. The special districts of decreasing population where the population continues to decrease can be said to be the population doughnuts found at the CBD and its neighboring inner area. On the other hand, the special districts of increasing population where the population continues to increase are located at the new built-up area of the northern part in Taejeon city. The special districts of decreasing population are overlapping with the aging district and higher in aged population rate by the out-migration of non-elderly population. The special districts of increasing population are not overlapping with the aging district and lower in aged population rate by the in-migration of non-elderly population. To clarify the distribution map of the aging district, the special districts of decreasing and increasing population and the aging district are divided into four groups such as the special districts of decreasing population group-the same one as the aging district, the special districts of decreasing population group, the special districts of increasing population group, and the other district. With the cohort analysis method by age used to investigate the definite increase and decrease of aging population through population transition of each group, it is found that the progress of population aging is closely related to the social population fluctuation, especially that aged population rate is higher with the out-migration of non-elderly population. This is to explain each model of CBD, inner area, and the suburbs after modeling the aging district, the special districts of decreasing population, and the special districts of increasing population in Taejeon city. On the assumption that the city area is a concentric circle, it is possible to divide it into three areas such as CBD(A), the inner area(B), and the suburbs(C). The special districts of increasing and decreasing population in the city are divided into three districts-the special districts of decreasing population(a), the special districts of increasing population(b), and the others(c). The aging district of this city is divided into the aging district($\alpha$) and the others($\beta$). And then modeling these districts, it is probable to find regional patterns in the city. $Aa{\alpha}$ and $Ac{\beta}$ patterns are found in the CBD, in which $Aa{\alpha}$ is the special district of decreasing population and is higher in aged population rate because of aged population low in mobility staying behind and out-migration of non-elderly population. $Ba{\alpha}$, $Ba{\beta}$, $Bb{\beta}$, and $Bc{\beta}$ patterns are found in the inner area, in which neighboring area $Ba{\alpha}$ pattern is located. $Bb{\beta}$ pattern is located at the new developing area of newly built apartment complex. $Cb{\beta}$, $Cc{\alpha}$, and $Cc{\beta}$ patterns are found in the suburbs, among which $Cc{\alpha}$ pattern is highest in population aging. It is likely that the $Cc{\beta}$ under housing land readjustment on a large scale will be the $Cb{\beta}$ pattern. As analyzed above, marriage and out-migration of new family, non-elderly population, with house purchase are main factors in accelerating population aging in the central area of the city. Population aging is responsible for the great increase of aged population with longer life expectancy by the low death rate, the out-migration of non-elderly population, and the age group of new aged population in the suburbs. It is necessary to investigate and analyze the regional patterns of population aging at the time when population problems caused by aging as well as longer life expectancy are now on the increase. I hope that this will help the future study on population aging of the geographical field in Korea. As in the future population aging will be a major problem in our society, local autonomy should make a plan for the problem to the extent that population aging progresses by regional groups and inevitably prepare for it.