• Land and Housing Review
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• v.13 no.3
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• pp.39-55
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• 2022

In this study, we investigate the interrelationship between housing tenure and childbirth by exploiting the correlation probability effect method that accounts for household heterogeneity. Using the newlywed household panel from 2011 to 2022, we find that home ownership has a positive impact on childbirth in newlyweds. Specifically, newlywed households with housing tenure show a 6.2%p higher birth rate and a 5.7%p higher second childbirth than newlywed households living in rented houses. For the case of first childbirth, we employ the probability effect probit model since the endogeneity was not detected between housing tenure and birth rate. We document the differential effects of housing tenure on childbirth in that the first childbirth rate is higher for households without housing tenures. The negative effects on first childbirth could be attributed to the economic burden due to initial housing ownership, while housing tenure could eventually provide housing stability, leading to positive effects on more than one childbirth. Finally, we identify that households with childbirth over the last year show a 4.2%p and 3.9%p lower probabilities of housing tenure in the total sample and second childbirth sample, respectively. This suggests that the increased living cost due to childbirth could delay home ownership.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.249-255
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• 2022

Alzheimer's disease (AD) represents a major public health concern and has been identified as a research priority. Clinical research evidence supports that the core cerebrospinal fluid (CSF) biomarkers for AD, including amyloid-β (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau), reflect key elements of AD pathophysiology. Nevertheless, advances in the clinical identification of new indicators will be critical not only for the discovery of sensitive, specific, and reliable biomarkers of preclinical AD pathology, but also for the development of tests that facilitate the early detection and differential diagnosis of dementia and disease progression monitoring. The early detection of AD in its presymptomatic stages would represent a great opportunity for earlier therapeutic intervention. The chance of successful treatment would be increased since interventions would be performed before extensive synaptic damage and neuronal loss would have occurred. In this study, the importance of developing an early diagnostic method using cognitive decline biomarkers that can discriminate between normal, mild cognitive impairment (MCI), and AD preclinical stages has been emphasized.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.109-141
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• 2014

Recently, the interests of consumers in firms that implement the social commitment activities have been consistently growing. Consumers' evaluation about the level of corporate social responsibility(CSR) can affect the overall image for product or service of corporation. This recent changes make a marketer to have to consider direct and indirect effects of CSR efforts on the market performance. This phenomena is also found in the franchise industry. The importance of CSR is more critical rather than other industries since each franchisor should care franchisees as well as end users. Franchisors' execution of CSR could increase satisfaction of end user through consonance of activities provided by franchisees. However most franchisor stay in focusing on the traditional CSR activities. Therefore, this study aims to enhance the understanding the CSR in franchise and provide the phase model of CSR development for general firms including franchise. After diagnosis the firms with the proposed model, the study found many franchisors have huge gap between current CSR activities and higher level of CSR policies that franchisor have to make facing. This study call franchisors to reduce this gap by implementing new CSR efforts. If they answer for this calling, franchise industry could leap for making the best practice of creating shared value with other stakeholders.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.56.1-56.1
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• 2020

한국의 고문헌 중에는 다양한 고천문 기록들이 한문 형태로 존재하며, 이를 학술적으로 활용하기 위해서는 전문 번역가 투입에 따른 많은 비용과 시간이 요구된다. 이에 인공신경망 기계학습에 의한 인공지능 번역기를 개발하여 비록 초벌 번역 수준일지라도 문장 형태의 한문을 한글로 자동번역해 주는 학술 도구를 소개하고자 한다. 이 자동번역기는 한국천문연구원이 한국정보화진흥원이 주관하는 2019년도 Information and Communication Technology 기반 공공서비스 촉진사업에 한국고전번역원과 공동 참여하여 개발 완료한 것이다. 이 연구는 고천문 도메인에 특화된 인공지능 기계학습용 데이터인 천문 고전 코퍼스를 구축하여 이를 기반으로 천문 고전 특화 자동번역 모델을 개발하고 번역 서비스하는 것을 목적으로 한다. 이를 위해 구축되는 시스템은 크게 세 가지이다. 첫째, 로그인이 필요 없이 누구나 웹 접속을 통해 사용이 가능한 클라우드 기반의 고문헌 자동번역 대국민서비스 시스템이다. 둘째, 참여 기관별로 구축된 코퍼스와 도메인 특화된 번역 모델의 생성 및 관리할 수 있는 클라우드 기반의 대기관 서비스 플랫폼 구축이다. 셋째, 개발된 자동번역 Applied Programmable Interface를 활용한 한국천문연구원 내 자체 서비스가 가능한 AITHA 시스템이다. 연구 결과로서 먼저 구축된 천문 고전 코퍼스 60,760건에 대한 샘플링 검수 결과는 품질 순도 99.9% 이상이다. 아울러 도출된 천문 고전 특화 번역 모델 총 20개 중 대표 모델에 대한 성능 평가 결과는 기계 번역 텍스트 품질 평가 알고리즘인 Bilingual Evaluation Understudy 평가에서 40.02점이며, 전문가에 의한 휴먼 평가에서 5.0 만점 중 4.05점이다. 이는 당초 연구 목표로 삼았던 초벌 번역 수준에 충분하며, 현재 개발된 시스템들은 자체 시험 운영 중이다. 이 연구는 특수 고문헌에 해당되는 고천문 기록들의 번역 장벽을 낮춰 관련 연구자들의 학술적 접근 및 다양한 연구에 도움을 줄 수 있다는 점에서 의의가 있다. 또한 고천문 분야가 인공지능 자동번역 확산 플랫폼 시범의 첫 케이스로써 추후 타 학문 분야 참여 시 시너지 효과도 기대해 볼 수 있다. 고문헌 자동번역기는 점차 더 많은 학습 데이터와 학습량이 쌓일수록 더 좋은 학술 도구로 진화할 것이다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.67-71
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• 2023

The purpose of this study is to investigate the effect of a community-based cognitive stimulation program on cognitive function and subjective memory in the elderly with mild cognitive impairment. This study was applied by selecting 15 users who understood the purpose of this study and agreed to participate in the shelter program for more than 3 months from April 2019 to August 2019 at the D Dementia Center in G located, Gyeonggi-do. The program consisted of a total of 36 cognitive stimulation programs 3 times a week a total of 3 months. Cognitive stimulation program stimulates cognitive function through various activities such as orientation reinforcement, cognitive training, recall, music, art, and physical play, and is used for the purpose of improving social function. It consists of folk songs, percussion instruments, national gymnastics, dance, games, and traditional games. As a result of the cognitive stimulation program, the average cognitive function increased by 2.13 points from 26.33 points before implementation to 28.46 points after implementation, and a statistically significant result was obtained (p=0.000). Subjective memory decreased by 3.53 points from the average of 7.13 points before the cognitive stimulation program was implemented to 3.60 points after the implementation, and a statistically significant result was obtained (p=0.000). It can be confirmed that this works. Dementia is leading to a cost burden, and congnitive function decreases the aqulity of life. It brings various burdens. It is necessary to study cognitive stimulation programs applied to various environments in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• 한국노년학
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• v.31 no.2
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• pp.371-380
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• 2011

This study was to address changes on hospital-based home care utilization after long-term care insurance(LTCI) was launched. National electronic data information(EDI) on hospital-based home care from Health Insurance Review Agency in 2007.7~2008.6(prior to LTCI) and in 2009(posterior to LTCI) was analyzed. After the launch of long-term care insurance, 40 hospital-based home health care agencies(HHCA) were diminished and regions not having any HHCA were increased from 53% to 59%. Hospital-based home care utilization was decreased in the elderly(clients 13.4%, visits 20.9%) as well as non-elderly(clients 3.5%, visits 3.9%). It is presumed that diminished HHCAs result in decreased accessibility to hospital-based home health care for non-elderly. The clients, visits, and reimbursed cost per agency were not changed. It is presumed that small agencies were closed already. The total reimbursed cost per agency in 2009 was 121,850,000 won. Results suggest that the government has to give support to open more HHCA to increase the accessibility for non-elderly. Also, hospital-based home care services utilization has to be monitoring regularly.

• 한국노년학
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• v.31 no.2
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• pp.259-276
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• 2011

If frail elderly could use home care services adequately, quality of their life might improve and their costs of service would be decreased. The purpose of this study is to examine the factors on institutionalization of elderly using home care services in Korean long-term care insurance system. This study used the data of '2009 satisfaction survey of Korean long-term care system'. The survey proceeded using sampling data by region, level of long-term care need, and insurance type among beneficiaries from August 2009 to September 2010. The onset dates of institutionalization of 1,230 participants were ascertained from long-term care insurance claim data. This study calculated hazard ratio through Cox Proportional Hazard Model. The results showed that if elderly using home care services suffer a fracture, the hazard ratio of institutionalization is higher significantly. Although not significant, if older persons have more items of damaged cognitive functions, the hazard ratio of institutionalization is higher. The results have policy implications to supplement of home care service system and postpone institutionalization of elderly.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.