• Communications for Statistical Applications and Methods
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• 제31권4호
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• pp.377-391
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• 2024

Accurate household projections are essential for sectors such as housing supply and tax policy planning, given the rapid social changes like declining birthrates, an aging population, and a rise in single-person households that impact household size and type. Korea introduced its first register-based census in 2015, transitioning from five-year general survey-based approach to an annual administrative data-based census. This change in census allows for more frequent and effective capturing the rapid demographic shifts and trends. However, this change in census has caused challenges in future projection by the existing household projection model due to the rapid dynamics. This paper proposes a new household projection method, the N-point Modified Exponential Model (MEM), that accurately reflects register-based census data and mitigates the impact of rapid demographic changes, in three types: the Weighted N-point MEM, the Regression-based N-point MEM, and the Rolling Weighted N+point MEM. Using register-based census data from 2016 to 2020 to forecast household headship rates by age, household size, and household type to 2051, the N-point modified exponential model outperformed the existing model in both long- and short-term forecast accuracy, suggesting its suitability as a future household projection model for Korea.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.81-88
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• 2023

In the present scenario, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In Perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several perturbation strategies that may be used to protect data privacy. For this experiment, two perturbation techniques based on random projection and principal component analysis were used. These techniques include Improved Random Projection Perturbation (IRPP) and Enhanced Principal Component Analysis based Technique (EPCAT). The Naive Bayes classification algorithm is used for data mining approaches. These methods are employed to assess the precision, run time, and accuracy of the experimental results. The best perturbation method in the Nave-Bayes classification is determined to be a random projection-based technique (IRPP) for both the cardiovascular and hypothyroid datasets.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1073-1086
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• 2009

This paper considers the problems of martingale measures and risk-minimizing hedging strategies in the market with restricted information. By constructing a general restricted information market model, the explicit relation of arbitrage and the minimal martingale measure between two different information markets are discussed. Also a link among all equivalent martingale measures under restricted information market is given. As an example of restricted information markets, this paper constitutes a jump-diffusion process model and presents a risk minimizing problem under different information. Through $It\hat{o}$ formula and projection results in Schweizer[13], the explicit optimal strategy for different market information are given.

• 한국경영과학회지
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• 제42권1호
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• pp.29-41
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• 2017

Korea is expected to become a super-aged society by 2050. Given an aging population and the increasing pressure for the early retirement, a sufficient social safety net for elderly population becomes important. The Korean government introduced public reverse mortgage program in 2007, which is a product for aging seniors and the elderly, The number of reverse mortgage subscribers has also steadily grown. The demand continues to grow, but the reverse mortgage over a long period of time is a highly uncertain and risky product in the position of guarantee or lending institution. Thus, suitable demand prediction of the reverse mortgage subscribers is necessary for stable and sustainable operation. This study uses a Bass diffusion model to forecast the long-term demand for reverse mortgage and provides insight into reverse mortgage by forecasting demand for stability and substantiality of the loan product. We represent the projections of new subscribers on the basis of the data obtained from Korea Housing Finance Corporation. Results show that potential market size of Korean reverse mortgage reaches approximately 760,000-1,160,000 households by 2020. We validate the results by comparing the estimate of the cumulative number of subscribers with that found in literature.

• Journal of Computational Design and Engineering
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• 제2권2호
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• pp.113-118
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• 2015

An important problem in low-dose CT is the image quality degradation caused by photon starvation. There are a lot of algorithms in sinogram domain or image domain to solve this problem. In view of strong self-similarity contained in the special sinusoid-like strip data in the sinogram space, we propose a novel non-local filtering, whose average weights are related to both the image FBP (filtered backprojection) reconstructed from restored sinogram data and the image directly FBP reconstructed from noisy sinogram data. In the process of sinogram restoration, we apply a non-local method with smoothness parameters adjusted adaptively to the variance of noisy sinogram data, which makes the method much effective for noise reduction in sinogram domain. Simulation experiments show that our proposed method by filtering in both image and projection domains has a better performance in noise reduction and details preservation in reconstructed images.

• 응용통계연구
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• 제28권4호
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• pp.663-683
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• 2015

저출산과 고령화 등의 인구구조의 변화는 미래 건강보험 재정의 안전성을 위협하고 있다. 이에 본 논문에서는 2002년부터 2013년까지 국민건강보험 표본코호트 DB를 이용하여 유병율 및 진료비에 대한 통계적 모형을 추정하고 인구구조와 경제상황의 변화에 대한 다양한 미래 가정들을 반영하여 건강보험 재정의 연도별 수입과 지출을 2060년까지 추계하였다. 지출 추계에는 건강보험공단 표본 코호트 DB를 이용하여 유병율 및 진료비를 추계하였다. 유병율 모형은 VECM-LC모형을 그리고 1인당 공단 부담 진료비에 대한 추계는 이중지수평활법에 근거 하였다. 두 모형 모두를 의료기관별, 질병별, 성별, 연령별로 적합하고 경제상황의 변화에 대한 국회와 정부의 여러 가정들을 반영하여 최종 추계치를 산출하였다. 수입 추계는 고령화 속도에 대한 두 개의 다른 가정에 근거한 두 개의 미래 인구구조를 반영한 두 개의 피부양률 가정에 근거하고, 지출 추계에서와 마찬가지로 경제 상황의 변화에 대한 여러 가지 가정을 반영하여 최종 추계치를 산출하였다. 그 결과 건강보험 재정적자는 2015년 불변가격으로 2030년에는 2030조 원, 2060년에는 4070조 원이 될 것으로 추계되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.1946-1963
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• 2014

Most background subtraction methods focus on dynamic and complex scenes without considering robustness against noise. This paper proposes a background subtraction algorithm based on dictionary learning and sparse coding for handling low light conditions. The proposed method formulates background modeling as the linear and sparse combination of atoms in the dictionary. The background subtraction is considered as the difference between sparse representations of the current frame and the background model. Assuming that the projection of the noise over the dictionary is irregular and random guarantees the adaptability of the approach in large noisy scenes. Experimental results divided in simulated large noise and realistic low light conditions show the promising robustness of the proposed approach compared with other competing methods.

• The Journal of Asian Finance, Economics and Business
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• 제6권1호
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• pp.91-105
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• 2019

The paper aims to combine balance sheet analysis at the firm level with the International Monetary Fund's public debt sustainability assessment framework to assess state-owned enterprises' (SOE) leverage as a contingent liability to the public sector. Based on company data and the interest coverage ratio as a measure of debt at risk, aggregate baseline scenarios are projected to gauge the magnitude of SOE debt as a contingency. SOE's financial and debt ratios are first bootstrapped to generate firm-level distributions and then averaged into a fan chart of the economy-wide SOE contingent liability. Applied to the People's Republic of China as an example, the study finds that by the end of 2015 SOE leverage had grown to a substantial liability. However arbitrary the assumptions underlying these projections, it would appear that even if authorities had to mop up as much as 20% of SOE debt at risk gone bad, this would have been manageable at roughly 2.7% of the gross domestic product in 2016 or 5.5% by 2021. This projection framework is fully amenable to alternative assumptions and settings, which makes it a useful analytical tool to monitor contingent liabilities from non-financial corporate debt that have been building in emerging and advanced economies alike.

• 디지털융복합연구
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• 제18권2호
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• pp.235-247
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• 2020

우리나라 상호금융조합은 안정적이고 지속가능한 성장과 경쟁력 확보를 위해 효율성 및 생산성을 높이기 위한 노력이 필요하다. 따라서 본 연구에서는 2012-2018 기간 중 상호금융조합의 효율성과 생산성을 분석하고, 효율성 및 생산성 제고를 위한 시사점을 제시한다. 분석을 위해 기존의 연구에서 사용된 전통적 블랙박스 DEA(Data Envelopment Analysis) 모형에서 벗어나, 단계 및 동태 분석이 보다 세부적으로 가능한 Dynamic-Network Slacks-Based Measure(DNSBM) 모형을 사용하였다. 분석결과, 첫째, 상호금융기관의 평균 효율성은 매우 낮게 나타났으나, 2015년 이후 개선되고 있는 것으로 분석되었다. 둘째, 우리나라 상호금융기관은 예수금과 대출금 확보 등 영업활동에서의 비효율 보다는 안정적인 이자수익의 확보 등 수익성 측면에서의 비효율이 더 높은 것으로 나타났다. 셋째, 대부분의 상호금융기관의 비효율은 투입요소에서 보다는 산출요소에서 비효율이 높은 것으로 나타났으며, 넷째, Malmquist 생산성 분석결과, 생산성은 효율성 변화(catch-up)에서 후퇴, 기술변화(frontier-shift)에서 성장한 것으로 분석되었다. 이상의 분석결과를 통해 우리나라 상호금융조합은 무수익여신의 관리, 이자수익을 위한 대출확보, 이자수익 외 다양한 수익기반 확보 등의 개선 노력이 필요하다.

• 응용통계연구
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• 제28권4호
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• pp.643-661
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• 2015

사학연금은 사립학교 교직원이 의무 가입하는 연금으로, 가입자들이 퇴직, 사망 등으로 경제적 위험에 처한 경우 연금을 수급하여 안정을 보장하기 위한 사회보장제도이다. 따라서 사학연금이 공적연금의 기능을 위해서는 기금의 안정성 및 지속가능성이 확보되어야 하며, 적절한 급여소득을 보장해야 할 것이다. 그러나 가장 대표적 공적연금인 공무원연금은 이미 2001년 재정수지 적자를 기록하였으며, 누적적자폭은 앞으로 더욱 커질 것으로 예상되어 최근 이에 대한 여러 개혁안이 활발히 논의되고 있다. 사학연금 제도는 기본적으로 공무원연금제도를 기초로 하는바, 이러한 국민연금 및 공무원연금 개혁 논의에서 자유롭지 못하다. 뿐만 아니라 한국의 고령화 및 인구구조 추세로 볼 때, 현행제도 하에서는 사학연금 기금 역시 향후 30년 내 기금 고갈이 예상되는 바, 현재의 사학연금 제도가 개선될 필요가 있음을 시사한다. 본 연구는 기존의 사학연금 제도의 문제점을 짚어보고, 이를 개선하기 위한 추계방법 및 개정방안을 제안한다. 이를 위해 사학연금의 장기재정추계를 통한 기금고갈시점 및 재정적자액의 규모를 예측하고, 현재 및 미래의 인구구조를 반영한 수급부담 구조를 비교 분석함으로써, 사학연금의 안정성과 적정성을 유지하기 위한 연금개혁 방안을 논의하고자 한다.