• 응용통계연구
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• 제28권3호
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• pp.393-406
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• 2015

본 논문은 2요인(two-factor) 사망률 모형에 평균회귀모형(mean reverting process)을 적용하여 2요인의 확률적 변동을 모형화하여 사망률리스크(mortality risk)와 장수리스크(longevity risk)를 분석하였다. 최근 고령사회로 진입한 국가들에서 사망률 개선의 둔화가 관측되고 있는 시점에서 기존의 선형증가 또는 감소의 사망률 개선 모형을 보완함에 그 목적을 두었다. 영국의 1991~2015년 사망률 자료를 이용하여 제시한 모형의 모수를 메트로폴리스 알고리듬을 이용해 추정하였고 추정된 모수 값을 이용하여 다수 시뮬레이션을 통하여 장기간의 미래 사망률 예측값을 계산하였다. 평균회귀 모형의 특성으로 인해 약 60년의 시간이 지난 뒤부터는 사망률 개선이 거의 사라져 사망률이 일정한 값에 근접하였다. 사망률 개선이 둔화되는 현상이 관측되는 특정 집단(국가, 사회)의 경우 2요인 평균회귀 모형은 장기간 사망률 예측방법의 대안으로 간주될 것으로 기대되며, 모형의 응용으로서 평균회귀율의 추정결과로부터 사망률 개선의 속도를 계량화하는 기준을 제시하였다. 끝으로, 2014년~2040 기간의 사망률 예측값을 이용하여 25년 만기 장수채권의 발행가격을 산출하였다.

• 응용통계연구
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• 제28권4호
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• pp.703-719
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• 2015

본 논문은 평균회귀 2요인 사망률 모형에 코호트 효과를 반영한 개선된 확률론적 사망률 모형을 제시한다. 한국 남자의 사망률 자료를 바탕으로 가중평균최소제곱법과 메트로폴리스 알고리듬을 이용하여 사망률 모형을 추정한 결과 코호트 효과를 반영하는 것이 모형 적합도를 향상시킴을 발견하였다. 국민연금공단과 같은 연금사업자가 자신의 장수위험을 금융시장에 순차적으로 전가하는 수단으로서 옵션방식 이자지급 장수채권의 활용을 제안하고 발행채권의 가격 산출방법을 제시하는 것이 본 논문이 기여하는 점이다. 특히 생존지수에 의해 이자지급 현금흐름이 결정되는 장수채권 가격산출을 위하여 코호트 효과가 매우 중요한 요소임을 강조하였다.

• 한국인구학
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• 제26권2호
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• pp.33-62
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• 2003

이 연구의 목적은 사망수준의 저하에 영향을 미치는 세 요소-사회경제적 발전, 공공 보건의 발달, 사회경제적 발달의 균등상태-의 상대적 중요성을 분석하는 것이다. 종속변수인 사망 수준의 지표로는 영아사망률과 출생시 기대수명 등 두 변수가 사용되었다. 국민총생산(GNP)은 사회 경제적 발달지표로 여성의 초등학교 취학률과 기니계수(GINI index)는 사회경제적 균등상태 지표로 병원침대당 인구수는 공공보건 지표로 간주되었다. 변수들에 대한 자료는 두 시점에 걸쳐 수집되었다. 하나는 1970년 이전 53개국에서. 다른 하나는 1970-80년대 55개국에서 수집되었다. 탐색적 자료 분석 방법이 통계 분석 방법으로 사용되었다. 이 기법은 종속변수와 독립변수와의 관계가 선형인지 아닌지, 그리고 우리 모형에서 어느 것이 유력 사례인지를 파악할 수 있는 장점이 있다. 분석결과에 따르면, 첫째로 영아 사망률과 세 요소의 관계가 선형이 아니라 비선형임이 밝혀졌다. 영아 사망률 저하에 국민총생산이 가장 많이, 여성의 초등학교 취학률이 두 번째, 기니계수가 그 다음으로 영향을 미치는 것으로 나타났다. 반면 병원침대당 인구수는 통계적으로 유의미한 영향을 보여주지 않았다. 둘째, 출생시 기대수명은 여성의 취학률, 기니계수 등과 같은 변수와는 선형 관계를 가지는 반면 국민총생산 변수와는 비선형 관계를 가진다. 영아사망률 변수와는 달리 출생시 기대수명의 변이에는 여성의 초등학교 취학률이 국민총생산보다 더 커다란 영향을 미쳤다.

• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.521-536
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• 2021

As life expectancies increase continuously over the world, the accuracy of forecasting mortality is more and more important to maintain social systems in the aging era. Currently, the most popular model used is the Lee-Carter model but various studies have been conducted to improve this model with one of them being 6-parametric factor model (6-PFM) which is introduced in this paper. To this new model, long short-term memory (LSTM) and regularized LSTM are applied in addition to vector autoregression (VAR), which is a traditional time-series method. Forecasting accuracies of several models, including the LC model, 4-PFM, 5-PFM, and 3 6-PFM's, are compared by using the U.S. and Korea life-tables. The results show that 6-PFM forecasts better than the other models (LC model, 4-PFM, and 5-PFM). Among the three 6-PFMs studied, regularized LSTM performs better than the other two methods for most of the tests.

• 응용통계연구
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• 제31권4호
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• pp.529-538
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• 2018

결핵은 높은 이환과 사망을 일으키는 질병으로 현대의학의 발달에 따라 발생률과 사망률은 감소하고 있다. 그러나 한국은 아직까지 OECD 국가 중 결핵 발생률과 사망률이 가장 높다. 이에 따라 한국은 결핵의 예방 및 통제를 위해 여러 정책 사업을 실시하고 있다. 본 연구에서는 공공민간협력(public-private mix) 결핵관리사업이 치료결과에 미치는 영향을 분석하고 결핵환자의 치료 성공에 영향을 미치는 요인을 확인하고자 한다. 질병관리본부에서 관리하는 결핵환자 신고 자료를 이용하여 2012-2015년 전국 결핵 신환자 코호트 약 13만명을 대상으로 분석하였다. 누적 발생 함수(cumulative incidence function)를 이용하여 요인별로 누적 치료 성공률을 비교하였으며. 주 관심사건(치료성공) 및 경쟁사건(사망)을 고려한 두 가지 경쟁위험모형(cause-specific Cox's proportional hazards model and subdistribution hazard model)을 사용하여 분석 결과를 비교하였다.

• Journal of Microbiology and Biotechnology
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• 제24권11호
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• pp.1495-1502
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• 2014

Metarhizium anisopliae is a widely studied model to understand the virulence factors that participate in pathogenicity. Proteases such as subtilisin-like enzymes (Pr1) and trypsin-like enzymes (Pr2) are considered important factors for insect cuticle degradation. In four M. anisopliae strains (798, 6342, 6345, and 6347), the presence of pr1 and pr2 genes, as well as the enzymatic activity of these genes, was correlated with their virulence against two different insect pests. The 11 pr1 genes (A, B, C, D, E, F, G, H, I, J, and K) and pr2 gene were found in all strains. The activity of individual Pr1 and Pr2 proteases exhibited variation in time (24, 48, 72, and 96 h) and in the presence or absence of chitin as the inductor. The highest Pr1 enzymatic activity was shown by strain 798 at 48 h with chitin. The highest Pr2 enzymatic activity was exhibited by the 6342 and 6347 strains, both grown with chitin at 24 and 48 h, respectively. Highest mortality on S. exigua was caused by strain 6342 at 48 h, and strains 6342, 6345, and 6347 caused the highest mortality 7 days later. Mortality on Prosapia reached 30% without variation. The presence of subtilisin and trypsin genes and the activity of these proteases in M. anisopliae strains cannot be associated with the virulence against the two insect pests. Probably, subtilisin and trypsin enzyme production is not a vital factor for pathogenicity, but its contribution is important to the pathogenicity process.

• Safety and Health at Work
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• 제11권3호
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• pp.353-360
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• 2020

Background: Urban bus drivers work under conditions that are among the most demanding, stressful, and unhealthy with higher rates of mortality and morbidity as well as absenteeism and turnover. Methods: Drawing on the job demand-resource model, this study investigates the impacts of job characteristics on emotional exhaustion and the effects of emotional exhaustion on job outcomes (including job satisfaction, life satisfaction, organizational commitment, and turnover intention) in the context of bus drivers. Results: Using self-reported survey data collected from a sample of 320 Taiwanese urban bus drivers, results reveal that role overload and work-family conflict (as job demand factors) positively relate to emotional exhaustion, and organizational support (as a job resource factor) is negatively associated with emotional exhaustion. Emotional exhaustion has negative effects on both job satisfaction and organizational commitment. Job satisfaction positively leads to life satisfaction, whereas organizational commitment negatively relates to turnover intention. Conclusion: This study concludes that role overload and work-family conflict as two stressors related to job demands and organizational support as the job resource factor to affect emotional exhaustion which further influence well-being in bus driver context. The moderating effects of both extraversion and neuroticism on the relationship between job demands and emotional exhaustion are evident.

• Asian Pacific Journal of Cancer Prevention
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• 제17권2호
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• pp.851-856
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• 2016

Background: Breast cancer is a major health problem among women around the world. Recent developments in screening and treatment have greatly improved the prognosis of patients with breast cancer in developed countries. However, in developing countries breast cancer mortality remains high.Breast cancer awareness is a first and important step in reducing breast cancer mortality. The development of a validated instrument to measure breast cancer awareness is crucial for the understanding and implementation of suitable health education programs to facilitate early deletion and minimize mortality. Objective: The objective of this study was to develop an instrument for the assessment of breast cancer awareness in Thai women. Materials and Methods: This methodological study was conducted in two stages: (1) literature searches and semi-structured interviews were conducted to generate items of the breast cancer awareness scale (B-CAS) which were subsequently examined for content and face validity, and (2) an exploration of the factor structure of the resulting instrument and an examination of its reliability. Data were collected using a self-administered questionnaire in Thai women aged 20-64 in August, 2015. Results: A total of 219 women (response rate 97.4 %) participated in this validation study. The B-CAS contains five domains with 53 items on breast cancer awareness: 1) knowledge of risk factors, 2) knowledge of signs and symptoms, 3) attitude to breast cancer prevention, 4) barriers of breast screening, and 5) health behavior related to breast cancer awareness. Items with a content validity index < 0.80 were excluded, and factor structure for the remaining items reflected the hypothesized five factor model. The scales based on all retained items was shown to have strongly internal consistency reliability (Cronbach's ${\alpha}=0.86$). Conclusions: The B-CAS provides good psychometric properties to assess breast cancer awareness in women. It can be used to examine breast cancer awareness in Thai women and it could lead to the development and evaluation of suitable educational interventions for raising breast cancer awareness. Future research should focus on further validating the B-CAS including an assessment of construct and criterion-based validity.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Asian Pacific Journal of Cancer Prevention
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• 제14권9호
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• pp.5043-5047
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• 2013

Background: This is a part of a larger effort to characterize the effects on socio-economic factors (SEFs) on cancer outcome. Surveillance, Epidemiology and End Result (SEER) bone and joint sarcoma (BJS) data were used to identify potential disparities in cause specific survival (CSS). Materials and Methods: This study analyzed SEFs in conjunction with biologic and treatment factors. Absolute BJS specific risks were calculated and the areas under the receiver operating characteristic (ROC) curve were computed for predictors. Actuarial survival analysis was performed with Kaplan-Meier method. Kolmogorov-Smirnov's 2-sample test was used to for comparing two survival curves. Cox proportional hazard model was used for multivariate analysis. Results: There were 13501 patients diagnosed BJS from 1973 to 2009. The mean follow up time (SD) was 75.6 (90.1) months. Staging was the highest predictive factor of outcome (ROC area of 0.68). SEER stage, histology, primary site and sex were highly significant pre-treatment predictors of CSS. Under multivariate analysis, patients living in low income neighborhoods and rural areas had a 2% and 5% disadvantage in cause specific survival respectively. Conclusions: This study has found 2-5% decrement of CSS of BJS due to SEFs. These data may be used to generate testable hypothesis for future clinical trials to eliminate BJS outcome disparities.