• Journal of Digital Convergence
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• v.17 no.9
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• pp.79-88
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• 2019

This study analyzes the influential factors and patterns associated with death from aircraft accidents and incidents using data mining techniques. To this end, we used two datasets for aircraft accidents and incidents, one from the National Transportation Safety Board (NTSB) and the other from the Federal Aviation Administration (FAA). We developed our prediction models using the decision tree classifier to predict death from aircraft accidents or aircraft incidents and thereby derive the main cause factors and patterns that can cause death based on these prediction models. In the NTSB data, deaths occurred frequently when the aircraft was destroyed or people were performing dangerous missions or maneuver. In the FAA data, deaths were mainly caused by pilots who were less skilled or less qualified when their aircraft were partially destroyed. Several death-related patterns were also found for parachute jumping and aircraft ascending and descending phases. Using the derived patterns, we proposed helpful strategies to prevent death from the aircraft accidents or incidents.

• The Monthly Diabetes
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• s.256
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• pp.10-13
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• 2011

최근에 발표한 '성별, 사망원인별, 연령별로 조정한 인구예측' 보고서(2011)에 따르면 심장병은 한국인 최대 사망원인 2위에 해당해 2030년이 되면 5명 중 1명은 심장병 때문에 숨을 거둘 것으로 전문가들은 예측한다. 문제는 많은 사람이 이런 시한 폭탄과 함께 살고 있으면서도 여전히 부족하거나 잘못된 정보를 갖고 있다. 이에 분당21세기의원 김한수 박사가 말하는 정확한 심장 이야기를 들어본다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.384-390
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• 2020

Purpose: Organophosphate insecticide poisoning can have clinically fatal results. This study aimed to evaluate the relationship between the neutrophil/lymphocyte ratio (NLR) and the occurrence of death in patients with organophosphate insecticide poisoning. Methods: For this retrospective study, data on patients with organophosphate insecticide poisoning who visited the emergency room between January 2008 and November 2018 were collected. The NLR was measured at the time of arrival in the emergency room. The patients were divided into survival and death groups. Results: Overall, 150 patients were enrolled: 15 (10%) in the death group and 135 (90%) in the survival group. In the univariate analysis, the following variables were significantly different between the two groups: age, white blood cell count, amylase level, creatinine level, Acute Physiology And Chronic Health Evaluation (APACHE) II score, and NLR. In the logistic regression analysis of variables with significant differences in the univariate analysis, there were significant differences between the two groups with respect to age, APACHE II score, and NLR. The NLR was significantly higher in the death group than in the survival group (20.83 ± 22.24 vs. 7.38 ± 6.06, p=0.036). Conclusion: High NLR in patients with organophosphate insecticide poisoning may be useful in predicting mortality.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.7
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• pp.275-280
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• 2018

As the global population becomes aging, the demand for health services for the elderly is expected to increase. In particular, The elderly visiting the emergency department sometimes have complex medical, social, and physical problems, such as having a variety of illnesses or complaints of unusual symptoms. The proposed system is designed to predict the mortality of the elderly patients who are over 65 years old and have admitted the emergency department. For mortality prediction, we compare the support vector machines and Feed Forward Neural Network (FFNN) trained with medical data such as age, sex, blood pressure, body temperature, etc. The results of the FFNN with a hidden layer are best in the mortality prediction, and F1 score and the AUC is 52.0%, 88.6% respectively. If we improve the performance of the proposed system by extracting better medical features, we will be able to provide better medical services through an effective and quick allocation of medical resources for the elderly patients visiting the emergency department.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.55-64
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• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• The Journal of the Korean life insurance medical association
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• v.11
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• pp.88-103
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• 1992

• Journal of Climate Change Research
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• v.1 no.2
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• pp.109-120
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• 2010

Heat wave is a disaster, which increases morbidity and mortality in temperate regions. Climate model results indicate that both intensity and frequency of heat wave in the future will be increased. This study shows the result about relationship between excess mortality and offensive airmass in 7 metropolitan cities, and an operational Heat-Health Warning System (HHWS) in Korea. Using meteorological observations, the Spatial Synoptic Classification (SSC) has been used to classify each summer day from 1982 to 2007 into specific airmass categories for each city. Through the comparative study analysis of the daily airmass type and the corresponding daily mortality rate, Dry Tropical (DT), and Moist Tropical plus (MT+) were identified as the most offensive airmasses with the highest rates of mortality. Therefore, using the multiple linear regression, forecast algorithm was produced to predict the number of the excess deaths that will occur with each occurrence of the DT and MT+ days. Moreover, each excess death forecast algorithm was implemented for the system warning criteria based on the regional acclimatization differences. HHWS will give warnings to the city's residents under offensive weather situations which can lead to deterioration in public health, under the climate change.

• Environmental Analysis Health and Toxicology
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• v.20 no.2 s.49
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• pp.133-141
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• 2005

다양한 유해오염물질에 급성 노출된 단각류 Monocorphium acherusicum의 노출 기간 이후에 발생하는 지연 사망(latent mortality)이 반수치사농도(LC5O)산출에 어떤 영향을 미치는 지를 규명하기 위한 일련의 실험이 수행되었다. 본 연구에서는 실험생물을 카드뮴, 구리, 수은과 같은 중금속, tributyltin(TBT), 암모니아 그리고 방향성탄화수소인 phenanthrene에 각각 96시간 동안 노출시킨 후 깨끗한 해수에 옮겨 다시 6일 동안 배양하면서 사망률을 조사하였다. 실험결과 구리, TBT, 암모니아, phenanthrene과 같은 물질에 노출된 M. acherusicum의 사망률은 노출이 끝난 이후에도 계속적으로 증가하는 지연 사망이 관찰되었으며, 이에 따라 기존의 방법_으로 산출된 96-h LC50보다 지연 사망을 고려한 새로운 LC50이 크게 낮아지는 경향이 관찰되었다. 지연사망률을 고려하지 않은 기존의 독성시험 결과는 지연 사망의 영향을 반영하지 못하므로 실제 현장에서 발생할 수 있는 오염물질의 영향을 과소평가 할 가능성이 있다. 따라서 지연 사망률에 대한 고려는 실제 현장 개체군에 대한 유해오염물질의 영향을 보다 정화하게 예측하는 데에 활용될 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.567-568
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• 2024

이 연구는 통계청의 치매 사망자수 및 사망률 자료와 공공데이터포털의 서울시 치매안심센터를 분석하여 치매 문제에 초점을 맞추어 치매 환자와 그 가족들에게 지원을 제공하는 치매안심센터의 역할을 조명합니다. 연구 목적은 서울시 각 자치구에 설치된 치매안심센터의 자원과 인프라가 치매 사망률에 미치는 영향을 분석하여, 치매 예방 및 관리 정책의 개선 방향을 제시하는 것입니다. 데이터는 한국통계정보원(KOSIS)과 사망원인통계에서 수집되었으며, 2022 년에 보고된 치매로 인한 사망자 수와 치매관리센터의 자원 정보를 포함합니다. 데이터 전처리 과정에서는 정확성 검증, 정규화, 표준화, 분류 작업이 이루어졌습니다.분석 방법으로는 통계적 접근과 예측 모델링을 통해 치매 치료 센터 자원과 치매 사망률의 관계를 다각적으로 조사했습니다. 본 연구의 결론은 치매 안심 센터의 자원이 치매 사망률에 미치는 영향을 이해하는 데 중요한 정보를 제공하며, 이는 치매 관리와 예방에 있어서 인력의 중요성을 강조합니다.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1998.11a
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• pp.185-190
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• 1998

한국의 산업재해를 2000년대에 선진국 수준에 도달할 수 있는지 여부와 이를 달성하기 위한 대책을 수립하기 위하여 한국의 2000년대 산업재해를 예측하였다. 예측모형은 여러 시계열 분석방법중 MAD가 가장 작은 모형을 선택하여 Q/S S/W로 분석하였다. 분석결과 도수율은 2000년에 선진국 수준에 달성할 수 있으나 사망 만인율과 같은 강도율은 거의 불가능하다. 본 논문에서는 이에 대한 여러 효율적인 대책안을 제시하였다.