• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.745-748
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• 2020

국민연금이 2056 년 고갈될 수 있다는 전망이 나오면서 연금소득에 대한 국민들의 불안감이 커졌다. 노후를 위해 미리 대비해야한다는 인식이 커지며 자동으로 투자해주는 '로보어드바이저'에 대한 사회적 관심이 함께 높아졌다. 본 연구에서는 기존 시중 은행들의 펀드 기반 로보어드바이저가 아닌 기업 재무 정보, 수정 종가 데이터를 이용한 직접 투자를 고안하였다. LGBM 알고리즘으로 포트폴리오를 구현해본 결과 실제 퀀트 투자에서 사용되는 지표들이 주식의 변화를 예측하는데 효과가 있음을 확인할 수 있었다.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.39-53
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• 2013

Although the efficient formation of urban space structure is a key factor in energy saving and environmentally-friendly aspect, the maintenance of the center and sub-center of the city that are key factors has been becoming increasingly difficult due to the variability and complexity of urban activities. In the case of Busan, amid the expansion of urban scale due to rapid economic development and overpopulation, systematic approaches to professional diagnosis and maintenance have been significantly insufficient - other than the city basic plan which has been conducted at an interval of 20 years. For the effective management of urban central area, systematic monitoring of the CBD through demand forecast and blight forecast at a city level must first be implemented. In order to fulfill this goal, this study is to figure out the current state of the CBD through the diagnosis on blight of the urban central area in the viewpoint of rehabilitation of the CBD and to propose the measures for practical utilization of the information about space for the further management of the central area of the city. For analysis, the study looks into the present state in terms of physical index, economic index, and social index. And then as a micro-approach by utilizing economic index, the study has thoroughly examined the economic blight of the Seomyun urban central area of Busan. The outcome of the analysis shows that in terms of population distribution and land utilization the area is in the stage of inefficient dispersion after having gone through the stage of suburbanization. It is expected that this study, as the material that proves the necessity of enhancing the function of the CBD, can propose the direction for the management of the urban center of Busan through blight prediction and management of the urban center and can provide the basic data for the long-term urban development that aims at the efficient strengthening of functions of the CBD.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.2
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• pp.67-74
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• 2019

In this paper the response factor is investigated for middle and small size-RC slab aged bridges. The response factor consists of static and dynamic response factors and is a main parameter in the frequency based-bridge load carrying capacity prediction model. Static and dynamic response factors are determined based on the frequency variation and the impact factor variation respectively between current and previous (or design) states of bridges. Here, the impact factor variation is figured out using the impact factor response spectrum which provides the impact factor according to the natural frequency of bridges. In this study, four actual RC slab bridges aged over 30 years after construction are considered and their span length is 12m. The dynamic loading test in field using a dump truck and eigenvalue analysis with FE models are conducted to identify the current and previous (or design) state-natural frequencies of the bridges, respectively. For more realistic considerations in the moving loading situation, the impact factor response spectrum is developed based on tri-axle moving loads representing the dump truck load distribution and various supporting conditions such as simply supported and both ends fixed conditions. From the results, the response factor is widely ranged from 0.21to 0.91, showing that the static response factor contributes significantly on the results while the dynamic response factor has a small effect on the result. Compared to the results obtained from the impact factor response spectrum based on the single axle-simply supported condition, the maximum percentage difference of the response factors is below 3.2% only.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.7
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• pp.642-652
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• 2009

Most of lap jointed aircraft structures encounter the fretting damages, which provoke fretting cracks prematurely and lead to significant reduction of fatigue life. In the case of ageing aircrafts especially, this fretting fatigue problem is a fatal threat for the safety and airworthiness. Recently, as the service life extension program(SLEP) of ageing aircrafts has become a hot issue, the prediction of fretting fatigue life is also indispensable. On these backgrounds, a series of experimental tests of fretting fatigue on bolted lap joint specimens, were performed. And the fretting crack initiation and propagation life of each specimen were evaluated using existing and newly proposed prediction models with the fretting parameters obtained from the FEA results for elasto-plastic contact stress analyses. The validations of prediction models were also discussed, comparing the prediction results with experimental test ones.

• Land and Housing Review
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• v.2 no.4
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• pp.415-427
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• 2011

This study is aiming at estimating the demolition cost of deterioration housing by the rational method in order to provide for the demolition and new build project of the rental multi-family housing of LH. We investigated the actual state of demolition construction and work process of small size housing, and analysed an actual condition of estimation for the demolition cost through an advice by the expert of construction cost estimate. Furthermore, the 'estimation standard for the predetermined amount', 'estimation standard for the disposal cost of construction wastes' and precedent studies in public construction work were considered. As one of results in this study, cost accounting system, breakdown system and construction cost for the demolition work based on the standard of estimate were proposed and the predetermined amount of demolition construction for the multi-family housing with 2 or 3 floors could be produced by them. Eventually, It is estimated that the demolition cost per a multi-family housing is about 18,331,000(won) and 104,000(won) per floorage($m^2$). To the details, the result indicated that the direct demolition cost needs about 14,339,000(won) per a multi-family housing and the consignment disposal cost of wastes needs 3,992,000(won) per one. The results of the study will be used as the fundamental data to estimate the project cost in the phase of budget establishment for demolition and new build project of the deteriorated rental multi-family housings, and also cost accounting system of demolition construction and breakdown system are expect to be used effectively at the ordering of public construction work.

• Korean Journal of Construction Engineering and Management
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• v.22 no.6
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• pp.107-119
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• 2021

Recently, interest in remodeling apartment houses has been increasing due to problems such as a lack of parking spaces for old apartment houses. However, no method was suggested to predict the construction period of the apartment remodeling project. Unlike general apartment new construction, apartment remodeling construction involves demolition or reinforcement work, so a realistic remodeling construction period calculation plan differentiated from the existing construction period should be proposed. Therefore, this study intends to present a model for deriving the construction period of the underground parking lot of the apartment remodeling construction. Each construction period was calculated based on 19 activities of underground parking lot remodeling work through review of previous studies and expert advice. Activity's workload data and productivity data were derived to calculate the construction period, and the number of inputs and equipment inputs by Activity were determined to correct the productivity data. The construction period of Activity was calculated using the derived data, and the criteria for calculating the overlapping period for each Activity were presented to enable realistic construction period and scheduled schedule. As a result of predicting the accuracy of the construction period through the verification of the case complex, it is expected that it will be possible to predict the approximate construction period of the underground parking lot of the apartment remodeling construction in the future.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.83-93
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• 1998

The twin aims of the present study are to develop a PC program for the statistical analysis of the measured cohesion data and to suggest a probabilistic corrosion rate estimation model for longitudinal members of tanker structures. A data analysis for the corrosion rate statistics(i.e., mean, standard deviation) as a function of the corrosion parameters is established for various structural member categories/locations of interest. Development of the computer program is focused on possible operation together with future addition of more corrosion data as they become available. To investigate the influence of the corrosion protection scheme a series of the corrosion analysis varying the life of coating are carried out and several different corrosion models as a function of time are suggested depending on the coating life.

• Korea journal of population studies
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• v.34 no.2
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• pp.113-133
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• 2011

The generation of babyboomers has a significant impact on the socio-economic development of the society in general. The Korean Babyboomers will soon leave from their workforce as they reach the retirement age. This, coupled with the low fertility rate, may cause a serious social problem in the society at large as well as the social welfare issues among the Korean elderly population. The Central Statistical Systems have estimated the future projection which plays critical role to establish fundamental basis for the social and economic policies of the nation. This study examined the effect of the babyboomers on the life expectancy by comparing forecasted life expectancies provided by the statistical office and the previous studies in the related areas. The study also suggested a future population projection based on fertility rates provided, along with the changes of the number of babyboomers as they become ageing. The study results with the comparison between the population projection by the statistical office are provided.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.703-710
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• 2018

Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.92-111
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• 2021

As fine dust negatively affects disease, industry and economy, the people are sensitive to fine dust. Therefore, if the occurrence of fine dust can be predicted, countermeasures can be prepared in advance, which can be helpful for life and economy. Fine dust is affected by the weather and the degree of concentration of fine dust emission sources. The industrial sector has the largest amount of fine dust emissions, and in industrial complexes, factories emit a lot of fine dust as fine dust emission sources. This study targets regions with old industrial complexes in local cities. The purpose of this study is to explore the factors that cause fine dust and develop a predictive model that can predict the occurrence of fine dust. weather data and fine dust data were used, and variables that influence the generation of fine dust were extracted through multiple regression analysis. Based on the results of multiple regression analysis, a model with high predictive power was extracted by learning with a machine learning regression learner model. The performance of the model was confirmed using test data. As a result, the models with high predictive power were linear regression model, Gaussian process regression model, and support vector machine. The proportion of training data and predictive power were not proportional. In addition, the average value of the difference between the predicted value and the measured value was not large, but when the measured value was high, the predictive power was decreased. The results of this study can be developed as a more systematic and precise fine dust prediction service by combining meteorological data and urban big data through local government data hubs. Lastly, it will be an opportunity to promote the development of smart industrial complexes.