• Title/Summary/Keyword: Rental

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Housing Choice Determinants of the Youth and Newlyweds Households: A Case Study of Incheon (청년·신혼부부의 주거선택요인에 관한 연구: 인천시를 중심으로)

  • Key, Yunhwan
    • Land and Housing Review
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    • v.13 no.4
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    • pp.13-26
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    • 2022
  • This study analyzes housing choice determinants of the youth and newlyweds households by using housing survey data in Incheon. A multinomial logit model is employed for analysis with the following variables: housing characteristics, housing market characteristics, and residential and neighborhood environment characteristics. The findings from the analysis are as follows. First, for the continued residence of the youth, the important factors were the relief assistance of housing maintenance costs. For the newlyweds, the important factors were the quality improvement of residential environments to ensure residential stability. Second, the housing choice factors to attract the youth were residential support for rent, maintenance costs, and relocation, and the improvements of residential environments such as security, noise levels, and medical facilities. For the newlyweds, the important factors were housing loan assistance for a home purchase or a cheonsei deposit and residential quality improvements for air pollution and parking facilities. Third, the youth were likely to move out due to high rental costs, and the newlyweds were likely to move out for the purchase of a new apartment or higher-quality housing.

Change Attention-based Vehicle Scratch Detection System (변화 주목 기반 차량 흠집 탐지 시스템)

  • Lee, EunSeong;Lee, DongJun;Park, GunHee;Lee, Woo-Ju;Sim, Donggyu;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
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    • v.27 no.2
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    • pp.228-239
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    • 2022
  • In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

A Study on the Utilization of Empty Houses in Rural Village - Focused on the Hacheon Village in Gimje City - (농촌마을 빈집의 활용방안에 관한 연구 - 김제 하천마을 중심으로 -)

  • Shim, Yu-Hyeon;Shin, Byeong-Uk;Nam, Hae-Kyeong
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.1
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    • pp.27-36
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    • 2022
  • Currently the population of rural areas in Korea continue to decline due to low birth rate, aging population, and migration. This phenomenon is accelerated over time. And as a result, there are some declining phenomenon in rural society. And it is same in the residential and basic living conditions of rural villages. The increase ratio of empty houses exacerbates the rural landscape, acts as a cause of crime and bring out various social and economic problems such as worsening settlement conditions and local slums. The study is carried out to prevent this phenomenon by investigating the architectural contents of empty houses in the village, surveyed residents and owners and finally analyzed and synthesized to make a plan to utilize empty houses in the village. This study was conducted from June to December 2021. The conclusions are followings: 1. The empty houses in Korea were 1,511 million in 2020, 8.2% of the total number of houses, whereas those in Jeollabuk-do were 95,412, 12.9% of those of houses, and those in Gimje-city, the subject of this study, were 5,944. It is up to 15.8%. In particular, empty houses in Hacheon village, the site of this study, accounted for the highest ratio, with 25% of the total number of houses. 2. To understand the utilization and improvement of empty houses, surveys and interviews were conducted to residents and owners of Hacheon village in Gimje, and most of the residents submit proposals that empty houses were not desirable in terms of village landscape and safety. The owners don't have intentions of selling or leasing them. They want to remodel them and rent for a specific period. 3. As the physical condition of the empty houses(9empty houses) 6 empty houses of them are good. 4 of them are in poor condition. 4. By synthesizing these contents, nine empty houses in Hacheon village will be remodeled as the space for those of rural start-up young people, smart farm area, community space and rental housings for rural returnees.

Effects on the Housing Market by Supplying "New Stay" Apartments: Focused on the Two Areas, Michuhol-Gu, Incheon and Gwonseon-Gu, Suwon (뉴스테이 공급에 따른 주택시장 반응과 효과: 인천 미추홀구와 수원 권선구 지역에 관한 연구)

  • Koh, Young Chon;Shin, Jong Hwa
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.433-442
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    • 2021
  • This study analyzed the housing market before and after the New Stay movement which was introduced in 2015. In this study, the territories having a New Stay Project and non-involved territories were analyzed based on the apartment price changes according to supply for 12 months before and after the movement date. This study used the difference-in-differences statistical technique. A comparison was carried out in Michuhol-gu, Incheon between Dowha-dong where a New Stay Project was executed, and Sungeui-dong where no project was executed, based on the movement date. It was seen that the price level in the former territory was higher than the latter demonstrating that the introduction of the New Stay Project in Dowha-dong lowered the apartment prices nearby (Sungeui-dong). A comparison in Gwonseon-gu, Suwon between Omogcheon-dong where a New Stay Project was executed and Gosaek-dong where there was no such project, based on the movement date showed that the introduction of the New Stay Project in Omogcheon-dong seemed to lower or stabilize the apartment prices nearby (Gosaek-dong). These results imply that the apartment prices in nearby areas can be stabilized if the supply volume of company-type rental houses is increased.

Comparing the Effects of the Access to the International School on Apartment Sales and Rental Prices: A Case of Songdo International School in Incheon (국제학교 입지가 아파트 매매 및 전월세 가격에 미치는 영향 비교·분석 -인천 송도국제도시 사례 -)

  • Kim, Yoon-Jae;Shin, Gwang-Mun;Lee, Jae-Su
    • Journal of the Korean Regional Science Association
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    • v.38 no.4
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    • pp.45-58
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    • 2022
  • This study intends to compare the factors influencing the location of international schools on apartment sales and monthly rent prices for Songdo International School in Incheon, which has a history of more than 10 years. At the latest point, 10 years after the opening of the school, apartments in areas near international schools are divided into sales and monthly rent markets and analyzed. Songdo International City, designed as a planned city, was set as a spatial scope, and 2018-19, which is a relatively stable real estate period, was set as a temporal analysis period to avoid the overheating period of real estate after COVID-19. Considering the urban image of the "New Special Education Zone," such as the opening of Songdo Campus by private academies formed around international schools and domestic and foreign universities, the multiple regression model was applied based on the traditional Hedonic price model. As a result of the empirical analysis, first, differences in the price determinants of sales and monthly rent were confirmed. Second, the price influence of international schools was much higher than that of the variables. Third, the influence of international schools was more pronounced in the monthly rent market than in the sales market.

Analysis of Spatial Characteristics Affecting the Use of Public Bicycles: Case of 'Tashu' in Daejeon (공공자전거 이용에 영향을 미치는 공간 특성 분석 - 대전광역시 '타슈'를 대상으로 -)

  • Ahn, Minsu;Yi, Changhyo
    • Journal of the Korean Regional Science Association
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    • v.38 no.4
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    • pp.75-91
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    • 2022
  • With the recent increase in interest in climate change issues, the use of bicycles is complementing public transportation and attracting attention as one of the eco-friendly means of transportation. Daejeon Metropolitan City has been operating Tashu, a public bicycle, since 2008. This study empirically analyzed the spatial characteristics that affect the use of public bicycles by grasping the current status and characteristics of public bicycles and applying spatial econometrics analysis, an analysis model that considers the spatial dependence of spatial data. In addition, a comparative analysis was performed by deriving the results of analyzing six models in terms of rental, return, peak time, non-peak time, weekday, and weekend based on the spatial error model identified as the optimal spatial econometrics model. The analysis model results showed that significant spatial characteristics differed according to the type of public bicycle use. In general, the use of public bicycles was high in areas with a high proportion of young people, a high number of public transportation users, good access to universities and rivers, and relatively low land use mix, and high proportion of apartments. These results indicated that public bicycles are used for commuting purposes on weekdays and leisure purposes on weekends, and if the convenience of using bicycles is improved, the use of public bicycles can be further increased.

Analysis of Major Factors of Window Work in Construction Phase Considering Recurrence of Defects in the Maintenance Phase (유지관리단계의 하자 재발생을 고려한 창호공사 시공단계의 중점관리요소 분석)

  • Jeong, U Jin;Kim, Dae Young;Lim, Jeeyoung;Park, Hyun Jung
    • Journal of the Korea Institute of Building Construction
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    • v.21 no.6
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    • pp.653-664
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    • 2021
  • As the construction standards for energy-saving eco-friendly housing have recently been strengthened, the proportion of window work has increased with the demand for high-efficiency housing. Windows have high frequency of use, and there is the potential for many defects to occur depending on the characteristics of construction. According to a government agency's survey of defects in public rental apartment housing, defects in the windows work accounted for the highest portion of complaints received. Accordingly, related previous studies were considered, and it was found that the existing studies in Korea lacked research that reflected the construction characteristics of window work and the importance of maintenance. In addition, existing overseas studies considered both the constructor and the resident's position, considering the cost aspect together, and showed a trend of structuring the relationship between defects and causes. Therefore, this study will analyze the causes of defects that can occur in the construction phase of the windows work, reflect the construction characteristics, and derive major factors that consider the importance of maintenance based on the possibility of recurrence after repairing defects. Ultimately, this research will contribute to preventing defects in the construction phase and reducing maintenance costs by presenting a highly effective defect management plan through selecting the major factors for each defect type that can be intuitively judged by analyzing the causal relationship between defect types and causes.

Analysis of Perception on Happy Housing Using Blog Mining Technique (블로그 마이닝을 활용한 행복주택의 인식 분석)

  • Hwang, Ji Hyoun
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.211-223
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    • 2022
  • This study aims to verify the possibility of using the blog mining to collect public opinion in the field of housing policy, thus, it collected blog posts with the keyword 'Happy Housing', extracted the main keywords from them, and analyzed the public's perception through keyword and word cluster analysis. 137,002 blog posts were used as analysis data from May 2013, when social discussion about happy housing spread, to August 2021, and the words derived by dividing the period into three stages in consideration of major housing policies and data collection were analyzed. The results are as follows. In the keyword analysis, overall, the importance of words related to the location, the number, the size, and the conditions for occupancy of Happy Housing is high. In the first stage, government policy implementation, in the second stage, the application process for Happy Housing, and in the third stage, recruitment notices, occupancy qualifications, and rental conditions are found to be highly important. In cluster analysis, project progress, application process, and project area were drawn as main themes at all stages. In particular, policy implementation and implementation plan in the first stage, occupancy qualification and financial support in the second stage, and policy implementation and occupancy qualification in the third stage were drawn as main themes. These results present the possibility of the blog mining as a method of collecting public opinion by sharing policy-related information, reflecting social issues, evaluating whether policies are delivered, and inferring the public's participation in policies.

A Study on the Effect of Macroeconomic Variables on Apartment Rental Housing Prices by Region and the Establishment of Prediction Model (거시경제변수가 지역 별 아파트 전세가격에 미치는 영향 및 예측모델 구축에 관한 연구)

  • Kim, Eun-Mi
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.2
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    • pp.211-231
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    • 2022
  • This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

Estimating Travel Frequency of Public Bikes in Seoul Considering Intermediate Stops (경유지를 고려한 서울시 공공자전거 통행발생량 추정 모형 개발)

  • Jonghan Park;Joonho Ko
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.1-19
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    • 2023
  • Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.