• Korean Circulation Journal
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• v.53 no.4
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• pp.254-267
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• 2023

Background and Objectives: Although the shortage of donor is a common problem worldwide, a significant portion of unutilized hearts are classified as marginal donor (MD) hearts. However, research on the correlation between the MD and the prognosis of heart transplantation (HTx) is lacking. This study was conducted to investigate the clinical impact of MD in HTx. Methods: Consecutive 73 HTxs during 2014 and 2021 in a tertiary hospital were analyzed. MD was defined as follows; a donor age >55 years, left ventricular ejection fraction <50%, cold ischemic time >240 minutes, or significant cardiac structural problems. Preoperative characteristics and postoperative hemodynamic data, primary graft dysfunction (PGD), and the survival rate were analyzed. Risk stratification by Index for Mortality Prediction after Cardiac Transplantation (IMPACT) score was performed to examine the outcomes according to the recipient state. Each group was sub-divided into 2 risk groups according to the IMPACT score (low <10 vs. high ≥10). Results: A total of 32 (43.8%) patients received an organ from MDs. Extracorporeal membrane oxygenation was more frequent in the non-MD group (34.4% vs. 70.7, p=0.007) There was no significant difference in PGD, 30-day mortality and long-term survival between groups. In the subgroup analysis, early outcomes did not differ between low- and high-risk groups. However, the long-term survival was better in the low-risk group (p=0.01). Conclusions: The outcomes of MD group were not significantly different from non-MD group. Particularly, in low-risk recipient, the MD group showed excellent early and long-term outcomes. These results suggest the usability of selected MD hearts without increasing adverse events.

• Journal of Gastric Cancer
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• v.22 no.2
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• pp.120-134
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• 2022

Purpose: This study aimed to identify prognostic factors for patients with distant lymph node-involved gastric cancer (GC) using a machine learning algorithm, a method that offers considerable advantages and new prospects for high-dimensional biomedical data exploration. Materials and Methods: This study employed 79 features of clinical pathology, laboratory tests, and therapeutic details from 289 GC patients whose distant lymphadenopathy was presented as the first episode of recurrence or metastasis. Outcomes were measured as any-cause death events and survival months after distant lymph node metastasis. A prediction model was built based on possible outcome predictors using a random survival forest algorithm and confirmed by 5×5 nested cross-validation. The effects of single variables were interpreted using partial dependence plots. A contour plot was used to visually represent survival prediction based on 2 predictive features. Results: The median survival time of patients with GC with distant nodal metastasis was 9.2 months. The optimal model incorporated the prealbumin level and the prothrombin time (PT), and yielded a prediction error of 0.353. The inclusion of other variables resulted in poorer model performance. Patients with higher serum prealbumin levels or shorter PTs had a significantly better prognosis. The predicted one-year survival rate was stratified and illustrated as a contour plot based on the combined effect the prealbumin level and the PT. Conclusions: Machine learning is useful for identifying the important determinants of cancer survival using high-dimensional datasets. The prealbumin level and the PT on distant lymph node metastasis are the 2 most crucial factors in predicting the subsequent survival time of advanced GC.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.37
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• pp.187-216
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• 2008

Risk regarding the possibility of loss can be especially problematic. If a loss is certain to occur, it may be planned for in advance and treated as a definite, known expense. It is when there is uncertainty about the occurrence of a loss that risk becomes an important problem. The word risk is often used in connection with insurance. No one generally accepted definition of risk exists, however. Of the many definitions, two distinctive ones are commonly used. One defines risk as the variation in possible outcomes of an event based on chance. That is, the greater the number of different outcomes that may occur, the greater the risk. Another way of expressing this concept is to state: The greater the variation around an average expected loss, the greater the risk. The second definition of risk is the uncertainty concerning a possible loss. The definition of risk as a useful one because it focuses attention on the degree of risk in given situations. The degree of risk is a measure of the accuracy with which the outcome of an event based on chance can be predicted. For now, it will serve our purpose to note the more accurate the prediction of the outcome of an event based on chance, the lower the degree of risk. After sources of risks are identified and measured, a decision can be made as to how the risk should be handled. A pure risk that is not identified does not disappear, the business merely loses the opportunity to consciously decide on the best technique for dealing with that risk. The process used to systematically manage risk exposures is known as risk management. Some persons use the term risk management only in connection with businesses, and often the term refers only to the management of pure risks. In this sense, the traditional risk management goal has been to minimize the cost of pure risk to the company. But as firms broaden the ways that they view and manage many different types of risk, the need for new terminology has become apparent. The terms integrated risk management and enterprise risk management reflect the intent to manage all forms of risk, regardless of type. International trade transaction is called between countries has features of globalism, cultural gap, long distance and long terms for the transaction. It is riskier than domestic transaction has its specific risks, such as foreign exchange risk and political risk, and requires various active risk management skills. Risks in relation to the international trade transaction are the contract risk, transit risk and payment risk, etc. The risk management in relation to the international trade transaction is to identify and measure these risks. The purpose of this study is to analyse the practical problems and its solution plan by analyzing various cases related to the risk management of bill of lading in the international trade transaction.

• Journal of the Korean Medical Association
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• v.61 no.12
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• pp.765-775
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• 2018

With growing interest in novel digital healthcare devices, such as artificial intelligence (AI) software for medical diagnosis and prediction, and their potential impacts on healthcare, discussions have taken place regarding the regulatory approval, coverage, and clinical implementation of these devices. Despite their potential, 'digital exceptionalism' (i.e., skipping the rigorous clinical validation of such digital tools) is creating significant concerns for patients and healthcare stakeholders. This white paper presents the positions of the Korean Society of Radiology, a leader in medical imaging and digital medicine, on the clinical validation, regulatory approval, coverage decisions, and clinical implementation of novel digital healthcare devices, especially AI software for medical diagnosis and prediction, and explains the scientific principles underlying those positions. Mere regulatory approval by the Food and Drug Administration of Korea, the United States, or other countries should be distinguished from coverage decisions and widespread clinical implementation, as regulatory approval only indicates that a digital tool is allowed for use in patients, not that the device is beneficial or recommended for patient care. Coverage or widespread clinical adoption of AI software tools should require a thorough clinical validation of safety, high accuracy proven by robust external validation, documented benefits for patient outcomes, and cost-effectiveness. The Korean Society of Radiology puts patients first when considering novel digital healthcare tools, and as an impartial professional organization that follows scientific principles and evidence, strives to provide correct information to the public, make reasonable policy suggestions, and build collaborative partnerships with industry and government for the good of our patients.

• Journal of Korean Society on Water Environment
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• v.32 no.3
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• pp.243-252
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• 2016

In cases of water pollution accidents, accurate prediction for arrival time and concentration of contaminants in a river is essential to take proper measures and minimize their impact on downstream water intake facilities. It is critical to fully understand the behavior characteristics of contaminants on river surface, especially in case of oil spill accidents. Therefore, in this study, the effects of main parameters of advection and diffusion of contaminants were analyzed and validated by comparing the results of Lagrangian particle tracking (LPT) simulation of Environmental Fluid Dynamic Code (EFDC) model with those of Global Position System (GPS)-equipped drifter experiment. Prevention scenario modeling was accomplished by taking cases of movable weir operation into account. The simulated water level and flow velocity fluctuations agreed well with observations. There was no significant difference in the speed of surface particle movement between 5 and 10 layer modeling. Therefore, 5 layer modeling could be chosen to reduce computational time. It was found that full three dimensional modeling simulated wind effects on surface particle movements more sensitively than depth-averaged two dimensional modeling. The diffusion range of particles was linearly proportional to horizontal diffusivity by sensitivity analysis. Horizontal diffusivity estimated from the results of GPS-equipped drifter experiment was 0.096 m²/sec, which was considered to be valid for applying the LPT module in this area. Finally, the scenario analysis results showed that particle movements could be stagnant when discharge from the upstream weir was reduced, implying the possibility of securing time for mitigation actions such as oil boom installation and wiping oil contaminants. The outcomes of this study can help improve the prediction accuracy of particle tracking simulation to establish the most suitable mitigation plan considering the combination of movable weir operation.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.114-126
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• 2016

Many cohort studies have reported associations of individual-level long-term exposures to $PM_{10}$ and health outcomes. Individual exposures were often estimated by using exposure prediction models relying on $PM_{10}$ data measured at national regulatory monitoring sites. This study explored spatial and temporal characteristics of regulatory $PM_{10}$ measurement data in South Korea and suggested $PM_{10}$ concentration metrics as long-term exposures for assessing health effects in cohort studies. We obtained hourly $PM_{10}$ data from the National Institute of Environmental Research for 2001~2012 in South Korea. We investigated spatial distribution of monitoring sites using the density and proximity in each of the 16 metropolitan cities and provinces. The temporal characteristics of $PM_{10}$ measurement data were examined by annual/seasonal/diurnal patterns across urban background monitoring sites after excluding Asian dust days. For spatial characteristics of $PM_{10}$ measurement data, we computed coefficient of variation (CV) and coefficient of divergence (COD). Based on temporal and spatial investigation, we suggested preferred long-term metrics for cohort studies. In 2010, 294 urban background monitoring sites were located in South Korea with a site over an area of $415.0km^2$ and distant from another site by 31.0 km on average. Annual average $PM_{10}$ concentrations decreased by 19.8% from 2001 to 2012, and seasonal $PM_{10}$ patterns were consistent over study years with higher concentrations in spring and winter. Spatial variability was relatively small with 6~19% of CV and 21~46% of COD across 16 metropolitan cities and provinces in 2010. To maximize spatial coverage and reflect temporal and spatial distributions, our suggestion for $PM_{10}$ metrics representing long-term exposures was the average for one or multiple years after 2009. This study provides the knowledge of all available $PM_{10}$ data measured at national regulatory monitoring sites in South Korea and the insight of the plausible longterm exposure metric for cohort studies.

• Journal of Korean Neurosurgical Society
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• v.30 no.8
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• pp.970-975
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• 2001

Objective : By conducing a review of clinical outcomes for patients with aneurysm treated using current microneurosurgical techniques and intensive care unit management, we speculated that grading systems based only on clinical condition or CT finding after admission failed to provide a significant stratification of outcome between individual grades of patients, because these systems did not include the factor for postoperative vasospasm. We hypothesized that postoperative blood flow velocity could have a significant impact on outcome prediction for patients surgically treated for intracranial aneurysms. Methods : We conducted a analysis on patient- and lesion-specific factors that might have been associated with outcome in a series of 55 aneurysm operations performed with measurements of blood-flow velocity with transcranial Doppler ultrasonography(TCD). In the new scale(NS) score system, 1 point is assigned additionally for the case with Hunt and Hess(H-H)/World Federation of Neurological Surgeons(WFNS) Grade IV or V, Fisher Scale(FS) score 3 or 4, aneurysm size greater than 10mm, patient age older than 60 years, blood-flow velocity higher than 120cm/sec, and posterior circulation lesion. By adding the total points, a 6-point scale score(score 0-6) is obtained. Results : Age of patient, size of aneurysm, clinical condition(H-H grade and WFNS), FS score, and blood flow velocity(TCD 1day after operation) were independently and strongly associated with long-term outcome. When NS scores were applied to 55 patients with at least 6 months follow-up, the correlation of individual scores with outcome was strongly validated the retrospective findings. Conclusion : It was speculated that TCD could be used to assess postoperative vasospasm and to monitor noninvasively the patients with aneurysmal SAH. This NS score system is easy to apply, divide patients into groups with different outcome, and is comprehensive, allowing for more accurate prediction of surgical outcome.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.1-6
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• 2011

A perceptual reaction to human being's gaits has "regularity" that possibly obtains sympathy among people. This thesis is in the vein of the study that performs the research on the quantificational extraction of the regularity, reconstitute the result, and apply it to controlling behavior. The purpose of this thesis lies in assuring the validity of the future research by demonstrating the following hypothesis: when the physical numerical values of the gait "A" whose perceptual reaction is "a" and those of the gait "B" whose perceptual reaction is "b" are arbitrarily blended, the perceptual reaction to this blended gait also corresponds to the blend of "a" and "b", "a/b". I blended the samples of two types of gaits in the form of Bipeds using the EAM made by 3D Studio Max Script. Blending outcomes were obtained successfully for four times out of the six tries in total. It implies that without utilizing other methods such as Motion Capturing, the basic Bipeds data itself has an enough capability to generate various gaits of Bipeds. Although the present research targets only the Bipeds samples equipped with the 1Cycle moving condition of arms and legs, I acknowledge that a tool that makes blending possible under various moving conditions is necessary for a completed system.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.15-32
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• 2016

Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people's choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.