• Proceedings of the KSR Conference
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• 2003.10c
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• pp.230-235
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• 2003

최근의 무선통신 시스템은 유지, 보수 및 구축이 유선통신 시스템에 비해 용이하고 이동성을 제공할 수 있다는 장점에 의해, 열차, 차량, 미사일 등의 이동체 제어와 관련된 분야에서의 연구가 활발히 진행되고 있다. 열차 또는 차량 제어와 같이 안전성이 중요시되는 분야에 있어서 전파에 의한 무선 링크는 가장 문제가 되는 부분으로서, 일반적으로 통신시스템은 어느 한 경로에서 고장이 발생하더라도 설계시 정해진 일정수준의 기능을 제공하는 생존성(survivability)을 지니도록 설계되어진다. 이와 관련한 연구와 개발은 대부분 공중 전화망과 고속 데이터 통신망을 대상으로 수행되었다. 본 논문에서는 유럽의 차세대 열차제어시스템에 적용하기 위해 기존의 유럽 표준 이동통신 시스템인 GSM(Global System for Mobile Communications)을 철도분야의 특수성에 맞도록 보완한 GSM-R(GSM-Railway)을 사례로 무선통신 시스템의 생존성을 검토한다.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.37-45
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• 1998

We consider the problem of obtaining the confidence bands for the survival function with incomplete data. It is a rather simple procedure for constructing confidence bands of survival function. This method uses the weak convergence of normalized cumulative hazard estimator to a mean zero Gaussian process whose distribution can be easily approximated through simulation. Finally, we compare the performance of the proposed confidence bands through Monte Carlo simulation and we applied to construct the proposed bands with the Leukemia patient data.

• Journal of the Korean Data and Information Science Society
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• v.2
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• pp.45-62
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• 1991

In this paper we propose new nonparametric estimators of the survival function using spline function under the progressively random censoring scheme. This sampling scheme is applied in many practical situations such as clinical trials or the life testing problems. We also investigate the behaviors for some estimators in the proposed class and the performance of progressively random censoring scheme through the numerical examples and Monte Carlo simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.96-98
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• 2020

최근 연안 활동자의 사고율이 높아짐에 따라 구명조끼의 의무 착용에 대한 논의가 되고 있다. 이에, 본 연구에서는 국내외 구명조끼 착용 배경 및 동향을 살펴보고 현재 생산되고 있는 구명조끼의 종류 및 부력시험에 대해 분석하였다. 구명조끼 착용 여부에 따른 생존율과 해외에서의 사례인 영국 등을 조사하였다. 이를 바탕으로 구명조끼의 착용의 의무화가 연안 해역 활동자의 안전를 제고하는데 역할을 할 수 있음을 알 수 있었다.

• Journal of Technology Innovation
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• v.25 no.4
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• pp.189-209
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• 2017

Financial institutions around the world, including financially advanced nations, widely operate a credit information sharing system to ease off information asymmetry between financial institutions and financial consumers. This study analyzed the credit problem data that is actually being shared among financial institutions in Korea, and classified credit problem data into three categories; Frequency, Period, Amount. In survival analysis, this study analyzed how different types of credit problem influence on survival period of companies. Next, in comparative analysis, this study verified a difference between start-up companies and existing companies on classified conditions of the credit problems. After conducting a survival and comparative analysis of the credit information of 449,579 companies of 8 years' actual information sharing in Korea, it showed that the number of the frequency of accidents showed a positive(+) correlation with the survival period. This provides contrary evidence to the financial institutions' risk policies that the number of the frequency of accidents is a negative factor. Furthermore, since the start-up companies that are under 7 years old show more positive aspect in the survival period than existing companies, it draws a policy implication that the credit information sharing system need to be improved by taking account of characteristics of the start-up companies.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.9 s.339
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• pp.85-96
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• 2005

A ' Virtual Private Network (YPN) over Internet' has the benefits of being cost-effective and flexible. However, given the increasing demands for high bandwidth Internet and for reliable services in a 'VPN over Intemet,' an IP/GMPLS over DWDM backbone network is regarded as a very favorable approach for the future 'Optical VPN (OVPN)' due to the benefits of transparency and high data rate. Nevertheless, OVPN still has survivability issues such that a temporary fault can lose a large amount of data in seconds, moreover unauthorized physical attack can also be made on purpose to eavesdrop the network through physical components. Also, logical attacks can manipulate or stop the operation of GMPLS control messages and menace the network survivability of OVPN. Thus, network survivability in OVPN (i.e. fault/attack tolerant recovery mechanism considering physical structure and optical components, and secured transmission of GMPLS control messages) is rising as a critical issue. In this Paper, we propose a new path establishment scheme under shared risk link group (SRLG) constraint for physical network survivability. And we also suggest a new logical survivability management mechanism by extending resource reservation protocol-traffic engineering extension (RSVP-TE+) and link management protocol (LMP). Finally, according to the results of our simulation, the proposed algorithms are revealed more effective in the view point of survivability.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.1-9
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• 2023

Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1225-1238
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• 2015

In this research, we fit various survival models and conduct tests and estimation for the hazard change-point with the rectal cancer data. By the log-rank tests, at significance level ${\alpha}=0.10$, survival functions are significantly different according to the uniporter of glucose (GLUT1), clinical stage (cstage) and pathologic stage (ypstage). From the Cox proportional hazard model, the most significant covariates are GLUT1 and ypstage. Assuming that the rectal cancer data follows the exponential distribution, we estimate one hazard change-point using Matthews and Farewell (1982), Henderson (1990) and Loader (1991) methods.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.1-11
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• 2012

When the microarray experiment developed, main interest was limited to detect differentially expressed genes associated with a phenotype of interest. However, as human diseases are thought to occur through the interactions of multiple genes within a same functional category, the unit of analysis of the microarray experiment expanded to the set of genes. For the phenotype of censored survival time, Gene Set Enrichment Analysis(GSEA), Global test and Wald type test are widely used. In this paper, we modified the Wald type test by adopting normal score transformation of gene expression values and developed a parametric test which requires much less computation than others. The proposed method is compared with other methods using a real data set of ovarian cancer and a simulation data set.

• Smart Media Journal
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• v.9 no.4
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• pp.126-133
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• 2020

The treatment policy and prognosis are determined based on the final stage of lung cancer patients. The final stage of lung cancer patients is determined based on the T, N, and M stage classification table provided by the American Cancer Society (AJCC). However, the final stage of AJCC has limitations in its use for various fields such as patient treatment, prognosis and survival days prediction. In this paper, clustering algorithm which is one of non-supervised learning algorithms was assessed in order to check whether using only T, N, M stages with a data science method is effective for classifying the group of patients in the aspect of survival days. The final stage groups and T, N, M stage clustering groups of lung cancer patients were compared by using the cox proportional hazard model. It is confirmed that the accuracy of prediction of survival days with only T, N, M stages becomes higher than the accuracy with the final stages of patients. Especially, the accuracy of prediction of survival days with clustering of T, N, M stages improves when more or less clusters are analyzed than the seven clusters which is same to the number of final stage of AJCC.