• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.1-17
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• 2014

In this study, various characteristics of R&D related economic variables were studied to analyze complexity of science and technology activities in Korea, as reliance of R&D activities of the private sector is growing by the day. In comparison to other countries, this means that it is likely to be fluctuated by economic conditions. This complexity characteristic signifies that the result of science and technology activities can be greatly different from the anticipated results - depending on the influences from economic conditions and the results of science and technology activities which may be unpredictable. After reviewing the results of 17 variables related to science and technology characteristics of complex systems intended for time-series data - in the total R&D expenditure, and private R&D expenditure, numbers of SCI papers, the existence of chaotic characteristics were. using Lyapunov Exponent, Hurst Exponent, BDS test. This result reveals science and technology activity of the three most important components in Korea which are; heavy dependence on initial condition, the long term memory of time series, and non-linear structure. As stable R&D investment and result are needed in order to maintain steady development of Korea economy, the R&D structure should be less influenced by business cycles and more effective technology development policy for improving human resource development must be set in motion. And to minimize the risk of new technology, the construction of sophisticated technology forecasting system should take into account, for development of R&D system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.571-575
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• 2010

Drought is a natural hazard with different properties that are usually dependent to each other. Therefore, a multivariate model is often used for drought frequency analysis. The Copula based bivariate drought severity and duration frequency analysis is applied in the current study in order to show the effect of tail behavior of drought severity and duration on the selection of a copula function for drought bivariate frequency analysis. Four copula functions, namely Clayton, Gumbel, Frank and Gaussian, were fitted to drought data of four stations in Iran and Canada in different climate regions. The drought data are calculated based on standardized precipitation index time series. The performance of different copula functions is evaluated by estimating drought bivariate return periods in two cases, [$D{\geq}d$ and $S{\geq}s$] and [$D{\geq}d$ or $S{\geq}s$]. The bivariate return period analysis indicates the behavior of the tail of the copula functions on the selection of the best bivariate model for drought analysis.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.247-253
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• 2013

It has long been known that the magnetospheric particles can precipitate into the atmosphere of the Earth. In this paper we examine such precipitation of energetic electrons using the data obtained from low-altitude polar orbiting satellite observations. We analyze the precipitating electron flux data for many periods selected from a total of 84 storm events identified for 2001-2012. The analysis includes the dependence of precipitation on the Kp index and the electron energy, for which we use three energies E1 > 30 keV, E2 > 100 keV, E3 > 300 keV. We find that the precipitation is best correlated with Kp after a time delay of < 3 hours. Most importantly, the correlation with Kp is notably tighter for lower energy than for higher energy in the sense that the lower energy precipitation flux increases more rapidly with Kp than does the higher energy precipitation flux. Based on this we suggest that the Kp index reflects excitation of a wave that is responsible for scattering of preferably lower energy electrons. The role of waves of other types should become increasingly important for higher energy, for which we suggest to rely on other indicators than Kp if one can identify such an indicator.

• Journal of muscle and joint health
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• v.28 no.2
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• pp.161-173
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• 2021

Purpose: This study examined: 1) what it meant for patients to have multimorbidity 2) how they manage their illness using health care facilities, and 3) what contextual backgrounds exist regarding the health care system. Methods: This qualitative research obtained individual in-depth interviews from 22 patients. Participants were selected by purposive sampling among those who saw physicians more often than the national average from the 2013 medical-claim data. The transcribed data were analyzed using Ground theory. Results: Multimorbidity patients suffered from "chain-like serial symptoms" and "pain without a breakthrough". They expressed themselves as "indeed patients among patients", "my body is a general hospital", and "an incompletely normal person". There was a demand to resolve the anxiety arising from the situation in which the body keeps getting sicker without showing any signs of recovery. In a state of reduced social support and a lack of trust in the doctor, their desire to be healed led them to receive a temporary relief through dependence on medical institutions. Conclusion: This research recognized the desire of multimorbidity patients to seek temporary relief through dependence on medical institutions. A more patient-centered directed care plan, specific to the needs of the patients with multimorbidity is required.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.302-310
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• 2022

Efficient use of limited blood products is becoming very important in terms of socioeconomic status and patient recovery. To predict the appropriateness of patient-specific transfusions for the intensive care unit (ICU) patients who require real-time monitoring, we evaluated a model to predict the possibility of transfusion dynamically by using the Medical Information Mart for Intensive Care III (MIMIC-III), an ICU admission record at Harvard Medical School. In this study, we developed an explainable machine learning to predict the possibility of red blood cell transfusion for major medical diseases in the ICU. Target disease groups that received packed red blood cell transfusions at high frequency were selected and 16,222 patients were finally extracted. The prediction model achieved an area under the ROC curve of 0.9070 and an F1-score of 0.8166 (LightGBM). To explain the performance of the machine learning model, feature importance analysis and a partial dependence plot were used. The results of our study can be used as basic data for recommendations related to the adequacy of blood transfusions and are expected to ultimately contribute to the recovery of patients and prevention of excessive consumption of blood products.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.325-338
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• 1997

This paper suggests a sequence of dependence models as a statistical analysis model for vaccination data on chickenpox and discusses a method for evaluating maximum likelihood estimates of unknown parameters in the suggested model.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.135-142
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• 2001

A multivariate statistic based on interdirection is proposed for detecting dependence among many vectors. The asymptotic distribution of the proposed statistic is derived under the null hypothesis of independence. Also we find the asymptotic distribution under the alternatives contiguous to the null hypothesis, which is needed for later use of computing relative efficiencies.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2008.11a
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• pp.101-101
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• 2008

The effect of oxygen partial pressure on the surface tension data of liquid alloys was investigated by means of comparing the calculated data and the measured one. Two binary alloy systems were chosen to observe the dependence of oxygen adsorption behavior on different oxygen partial pressures. It was found that the difference between the computed values and the experimental of the surface tension was within the range of maximum 10%.

• Journal of applied mathematics & informatics
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• v.37 no.3_4
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• pp.207-217
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• 2019

We are presented of several basic properties for negatively superadditive dependent(NSD) random variables. By using this concept we are obtained complete convergence for maximum partial sums of rowwise NSD random variables. These results obtained in this paper generalize a corresponding ones for independent random variables and negatively associated random variables.