• Journal of Korea Trade
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• v.27 no.5
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• pp.91-112
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• 2023

Purpose - This study empirically investigates how the effects of localized knowledge spillovers on technology adoption are conditional on the organizational capabilities of potential adopters. Design/methodology - The empirical model utilized in this study examines how the presence of prior adopters of advanced manufacturing technologies affects a plant's technology adoption decision differently based on its organizational capabilities, measured by plant size and plant status (single-plant firm vs. multi-plant firm). Moreover, this study investigates how the scope of knowledge spillovers from prior adopters, both in terms of geographical and functional proximities, differ for plants with different organizational capabilities. Findings - The main findings of this study are as follows: 1. Although plants with lower organizational capabilities are less likely to adopt advanced technologies, such plants receive greater marginal benefits from knowledge spillovers from prior adopters in their region. 2. Plants with greater organizational capabilities can benefit from knowledge spillovers from a wider set of prior adopters. In other words, while plants with lower organizational capabilities tend to benefit from knowledge spillovers from "similar" and "local" adopters, plants with greater organizational capabilities can also benefit from knowledge spillovers from "not-too-similar" or are geographically distant prior adopters. Originality/value - While existing studies mainly focus on the effects of the various kinds of regional agglomeration, few studies investigate localized knowledge spillovers in technology adoption. Moreover, no prior studies have explored how the effects of knowledge spillovers on technology adoption depend on a plant's organizational capabilities and how the scope of knowledge spillovers differs for plants with different organizational capabilities. This study is the first to empirically investigate this topic.

• Atmosphere
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• v.27 no.4
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• pp.455-466
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• 2017

In Korea, property and human damages occur annually due to heavy precipitation during the summer. On August 8, 2015, heavy rainfall occurred in the Seoul metropolitan area due to an outflow boundary, and $77mmhr^{-1}$ rainfall was recorded in Gwangju, Gyeonggi Province. In this study, the simulation of the WRF numerical model is performed to understand the cause and characteristics of heavy rainfall using the Conditional Instability of the Second Kind (CISK), potential vorticity (PV), frontogenesis function, and convective available potential energy (CAPE) analyses, etc. Convective cells initiated over the Shandong Peninsula and located on the downwind side of an upper level trough. Large amounts of water vapor were supplied to the Shandong Peninsula along the southwestern edge of a high pressure system, and from the remnants of typhoon Soudelor. The mesoscale convective system (MCS) developed through CISK process and moved over to the Yellow Sea. The outflow boundary from the MCS progressed east and pushed cold pool eastward. The warm and humid air over the Korean Peninsula further enhanced convective development. As a result, a new MCS developed rapidly over land. Because of the latent heat release due to convection and precipitation, strong potential vorticity was generated in the lower atmosphere. The rapid development of MCS and the heavy rainfall occurred in an area where the CAPE value was greater than $1300Jkg^{-1}$ and the fronto-genesis function value of 1.5 or greater coincided. The analysis result shows that the MCS driven by an outflow boundary can be identified using CISK process.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.119-130
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• 2017

In many literatures on VaR and CTE for multivariate distribution, these are estimated by using transformed univariate distribution with a specific ratio of many kinds of portfolios. Even though there are lots of works to define quantiles for multivariate distributions, there does not exist a quantile uniquely. Hence, it is not easy to define the VaR and CTE. In this paper, we propose the weighted CTE vectors corresponding to various ratio combinations of many kinds of portfolios by extending the researches on the alternative VaR and integrated multivariate CTE based on multivariate quantiles. We extend relation equations about univariate CTEs to multivariate CTE vectors and discuss their characteristics. The proposed weighted CTEs are explored with some data from multivariate normal distribution and illustrative examples.

• Korean Journal of Environmental Biology
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• v.22 no.1
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• pp.167-170
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• 2004

A self-directing optimization procedure was applied to determine the best environmental factors in operating the bioreactor. The self-directing optimization process was employed to determine the best conditional combination of multi parameters, pH, temperature, aeration rate and mixing rate toy maximal production of chitinase by Trichoderma harzianum SJG-99721 in batch mode fermentation. Among these factors, the parameters of pH and aeration rate were found to be particularly important on mycellial growth and chitinase activity. pH 4.89, an aeration rate of 3.22 ι per minute and an agitation rate of 225 rpm was found to be the best combination. By the optimization, chitinase activity was dramatically increased from an initial value of 4.221 U under basic conditions to n final value of 16.825 U.

• Journal of Korean Academy of Nursing
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• v.22 no.3
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• pp.389-406
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• 1992

This study was designed to identify nursing students' attitudes toward life through a Q-methodology. A Q-sample was formed through a review of the literature and interviews(n＝160)l The final Q-sample consisted of 37 statements out of an initial 100 statements after consultation with an expert panel and pilot testing. The P-sample consisted of 14 university nursing students and 27 junior college nursing students, which was selected by convenience sampling method. Data were analyzed by the Q-analysis method. The correlation between type 2 and type 3 was relatively high (r＝0.539) ; that between type 1 and type 3 was lowest (r＝0.014). The first type of attitude was the “rational utilitarian” type. Students in this type valued life relative to the quality of life. They agreed with euthanasia and artificial abortion if the quality of life was threatened. The criteria for their judgement were scientific knowledge and rationality. The second type of attitude was the “Christian deontologic” type. These students appreciated the sanctity of life according to Christian dogma. They disagreed with euthanasia and artficial abortion. And they disagreed strongly that life should be created by scientific development, because only God creates life. The third type of attitude was the “unconditional deontologic” type. These students agreed with the sanctity of life, not from Christian belief but from belief in the sanctity of life. The final type of attitude was the “prima facie(conditional) deonologic” type. These students appreciated the value of life and humanity. They expressed concern for others' life and suffering. They do not want to afflict others with their own miseries. This group showed a dual value system toward themselves and others. So they experience conflict between their concern for their on and others' conditions. These nursing students' values may have been influenced by their clinical experience in hospitals and other nursing fields. Through this study, we may realize the importance of education in nursing ethics for discussion of ethical conflicts and to support ethical nursing practice.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.203-210
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• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.493-500
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• 2014

This paper presents findings from the assessment of the volcanic ash fragility for multi-hazard resisting vinyl greenhouse and livestock shed among the agricultural facilities. The volcanic ash fragility was evaluated by using a combination of the FOSM (first-order second-moment) method, available statistics of volcanic load, facility specifications, and building code. In this study, the evaluated volcanic ash fragilities represent the conditional probability of failure of the agricultural facilities over the full range of volcanic ash loads. For the evaluation, 6 types(ie., 2 single span, 2 tree crop, and 2 double span types) of multi-hazard resisting vinyl greenhouses and 3 types(ie., standard, coast, and mountain types) of livestock sheds are considered. All volcanic ash fragilities estimated in this study were fitted by using parameters of the GEV(generalized extreme value) distribution function, and the obtained parameters were complied into a database to be used in future. The volcanic ash fragilities obtained in this study are planning to be used to evaluate risk by volcanic ash when Mt. Baekdu erupts.

• Industry Promotion Research
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• v.8 no.4
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• pp.69-79
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• 2023

This study sought to propose ways to improve the happiness of Chinese product designers by verifying whether grit moderates the effect of job stress on happiness through professional values. A purposively sampled participants of 335 Chinese product designers living in Guangdong Province, southern China, were selected. Data analysis was performed using SPSS PC+ Win. Ver. 26.0 and PROCESS Macro ver. 4.2. The statistical techniques applied were frequency analysis, reliability analysis, correlation analysis, and moderated mediation effect analysis. The research results are as follows. First, job stress showed a negative correlation with professional value and grit, but did not show a significant correlation with happiness. Except for job stress, there was a positive significant correlation between other variables. Second, the conditional indirect effect was significant when grit was M-SD, M, or M+SD. M+SD. Therefore, the moderated mediating role of grit was verified. However, as professional value increased, grit played a role in increasing happiness. Still, in the path of job stress -> professional value -> happiness, grit did not buffer the negative effect of job stress on happiness through professional stress. Suggestions were made to improve the happiness of product designers using professional values and grit.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7134-7147
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• 2014

This study examined one of the contemporary issues that may be interesting to academics and practitioners regarding the driving force of the growth rate for the firms belonging to the chaebols in the Korean capital markets. With respect to the empirical results obtained from two hypothesis tests, the first hypothesis was to identify any financial determinants on the growth rate by applying both dynamic panel data and static panel data models. The debt ratios relevant to the book- and market-value showed their positive relationships with the DV of GROWTH1, along with other significant IDVs such as one-period lagged DV of GROWTH_1, SIZE1 and FOS with statistical significance. Second, by employing conditional quantile regression (CQR) analysis, the control variables, such as ROA, SMARKET, time dummy variable of F2010 and F2011, and the industry dummies of IND3 and IND10, provided evidence of their significant influences on DV of GROWTH1.

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.249-264
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• 2011

A multi-Gaussian kriging approach extended to space-time domain is presented for uncertainty modeling as well as time-series mapping of environmental variables. Within a multi-Gaussian framework, normal score transformed environmental variables are first decomposed into deterministic trend and stochastic residual components. After local temporal trend models are constructed, the parameters of the models are estimated and interpolated in space. Space-time correlation structures of stationary residual components are quantified using a product-sum space-time variogram model. The ccdf is modeled at all grid locations using this space-time variogram model and space-time kriging. Finally, e-type estimates and conditional variances are computed from the ccdf models for spatial mapping and uncertainty analysis, respectively. The proposed approach is illustrated through a case of time-series Particulate Matter 10 ($PM_{10}$) concentration mapping in Incheon Metropolitan city using monthly $PM_{10}$ concentrations at 13 stations for 3 years. It is shown that the proposed approach would generate reliable time-series $PM_{10}$ concentration maps with less mean bias and better prediction capability, compared to conventional spatial-only ordinary kriging. It is also demonstrated that the conditional variances and the probability exceeding a certain thresholding value would be useful information sources for interpretation.