• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.12-21
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• 2017

From 1960, the government decided to build apartment houses on a large scale in order to resolve the rising housing problems. However, the maintenance issues that have arisen from the deterioration of housing has not received adequate attention. The policy focuses only on the supply of housing. By passing new laws, the durable period during which buildings allowed reconstruction was increased, and long term maintenance plans were treated as important issues. The government was then obligated to establish certain long term maintenance plans and costs by legislating a Housing Act and requiring it be adjusted every three years. However, when planning long-term repair costs, doing so without considering the time value of money would become a problem. In addition, if differences between the planned repair costs and actual costs occur, it becomes necessary to adjust the long-term repair costs but, as of yet, the criteria to adjust such things does not exist. For these reasons, if there is lack of money to execute large-scale repair work, a building is unlikely to respond to deterioration of housing; on the other hand, an unnecessary reserve or pool of money can lead to conflict among residents. Therefore, this paper will propose estimation and adjustment models considering the time value of money for long term maintenance costs of apartment houses.

• Journal of the Korean Geographical Society
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• v.28 no.4
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• pp.285-297
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• 1993

For the application of the diffusion equation, slope height and maximum slope angle are calculated from the plotted slope profile. Using denudation rate as a solution for the diffusion equation, an apparent age index can be calculated, which is the total amount of denudation through total time. Plots of slope angle versus slope height and apparent age index versus slope height are useful for determining relative or absolute ages and denudation rates. Mathematical simulation plots of slope angle versus slope height can generate equal denudation-rate lines for a given age. Mathematical simulations of slope angle versus age for a given slope height, for equal denudation-rate at a particular profile site, and for comparing to other sites having controlled ages.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.121-132
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• 2010

Soybean farms in Changnyeong were selected for hazard analysis to establish the Good Agricultural Practices (GAP) model of soybean, and physical, chemical(heavy metal) and biological(sanitary indications, foodborne pathogens) hazard analysis for cultivation environment (soil, water) was carried out. First, bow which is able to be mixed in soil and water was confirmed as physical hazard. Levels (Cd:0.01~0.103, Cu:0.001~6.036, As:0.006~3.045, Hg:ND~0.041, Pb:0.003~3.952, $Cr^{+6}$:0.007~0.496, Zn:0.001~66.500, Ni:0.003~18.010) of heavy metals in soil and water were appropriate for GAP criteria. In biological hazard, APC and coliform in soil were detected at the levels of $6.0{\pm}0.3$ and $3.6{\pm}1.6$ log CFU/g, and levels of water were $3.5{\pm}0.7$ and $1.9{\pm}0.7$ log CFU/mL, while E. coli wasn't detected in all sample. However, coliform in water wasn't appropriate for criteria, and E. coli O157 was detected about 22% in some farms, so it needs ways to prevent contamination by human and animals excrements. In conclusion, it needs proper management to prevent cross-contamination of hazards although physical and chemical hazard level were appropriate for GAP criteria while biological hazard wasn't.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1509-1521
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• 2020

Experiments for validation of surface reflectance produced by Korea Multi-Purpose Satellite (KOMPSAT-3A) were conducted using Chinese Baotou (BTCN) data among four sites of the Radical Calibration Network (RadCalNet), a portal that provides spectrophotometric reflectance measurements. The atmosphere reflectance and surface reflectance products were generated using an extension program of an open-source Orfeo ToolBox (OTB), which was redesigned and implemented to extract those reflectance products in batches. Three image data sets of 2016, 2017, and 2018 were taken into account of the two sensor model variability, ver. 1.4 released in 2017 and ver. 1.5 in 2019, such as gain and offset applied to the absolute atmospheric correction. The results of applying these sensor model variables showed that the reflectance products by ver. 1.4 were relatively well-matched with RadCalNet BTCN data, compared to ones by ver. 1.5. On the other hand, the reflectance products obtained from the Landsat-8 by the USGS LaSRC algorithm and Sentinel-2B images using the SNAP Sen2Cor program were used to quantitatively verify the differences in those of KOMPSAT-3A. Based on the RadCalNet BTCN data, the differences between the surface reflectance of KOMPSAT-3A image were shown to be highly consistent with B band as -0.031 to 0.034, G band as -0.001 to 0.055, R band as -0.072 to 0.037, and NIR band as -0.060 to 0.022. The surface reflectance of KOMPSAT-3A also indicated the accuracy level for further applications, compared to those of Landsat-8 and Sentinel-2B images. The results of this study are meaningful in confirming the applicability of Analysis Ready Data (ARD) to the surface reflectance on high-resolution satellites.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.193-215
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• 2022

Recently, ground structures have reached saturation, and underground construction using underground structures such as tunnels has been in the spotlight as a way to solve increasing traffic difficulties and environmental problems. However, due to the increasing number of underground structures, close construction is inevitable for continuous underground development. When a new underground structure is constructed closely, stability may become weak due to the influence on the existing tunnel, which may cause collapse. Therefore, analyzing the stability of existing tunnels due to new structures is an essential consideration. In this study, the effect of excavating new tunnels under parallel tunnels on existing parallel tunnels was analyzed using numerical analysis. Using the Displacement Control Model (DCM), the volume loss generated during construction was simulated into three case (0.5%, 1.0%, and 1.5%). Based on the center of the pillar, the distance where the new tunnel is located was set to 5 m, 6 m, 7 m, 8 m, 9 m, and the space for each distance were set to 5 (0D₁, 0.37D₁, 0.75D₁, 1.13D₁, 1.5D₁). In general, as the volume loss increased and the distance approached, the maximum displacement and angular displacement increased, and the strength/stress ratio to evaluate the stability of the pillar also decreased. As a result, when the distance between the new tunnel and the center of the pillar is 5 m, the space is 0D₁, and the volume loss is 1.5%, the stability of the existing parallel tunnel is the weakest.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.3
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• pp.13-22
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• 2022

In order to improve water quality of the water system contaminated with dyes, biochars prepared using discarded waste resources were applied in this study. Biochars with a large specific surface area were manufactured using street tree pruning products or waste wood, and were applied to remove an organic dye in synthetic water. Biochars were made by pyrolysis of typical street tree porch products (Platanas, Ginkgo, Aak) and waste wood under air-controlled conditions. Methylene blue (MB), which is widely used in phosphofibers, paper, leather, and cotton media, was selected in this study. The adsorption capacity of Platanas for MB was the highest and the q_max value obtained using the Langmuir model equation was 78.47 mg/g. In addition, the adsorption energy (E) (kJ/mol) of MB using the Dubinin-Radushkevich (D-R) model equation was 4.891 kJ/mol which was less than 8 kJ/mol (a criteria distinguishing physical adsorption from chemical adsorption). This result suggests a physical adsorption with weak interactions such as van der Waals force between the biochar and MB. In addition, the physical adsorption may resulted from that Platanas-based biohar has the largest specific surface area and pore volume. The ∆G value obtained through the adsorption experiment according to temperature variation was -3.67 to -7.68, which also suggests a physical adsorption. Considering these adsorption results, the adsorption of MB onto Platanas-based biochar seems to occur through physical adsorption. Overall, it was possible to suggest that adsorption capacity of the biochr prepared from this study was equal to or greater than that of commercial activated carbon reported in other studies.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.473-483
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• 2022

BIM(Building Information Modeling) is a technology that can manage information throughout the entire life cycle of the construction industry and serves as a platform for improving productivity and integrating the entire construction industry. Currently, BIM is actively applied in developed countries, and its use at various overseas construction sites is increasing This is unclear. due to air shortening and budget savings. However, there is still a lack of institutional basis and technical limitations in the domestic construction sector, which have led to the lack of utilization of BIM. Various activation measures and institutional frameworks will need to be established for the early establishment of these productive BIMs in Korea. Therefore, as part of the research for the domestic settlement and revitalization of BIM, this study derived a number of key factors necessary for the development of the construction industry through brainstorming and expert surveys using AHP techniques and analyzed the relative importance of each factor. In addition, prior surveys by a group of experts resulted in 1, 3 items in level, 2, 9 items in level, and 3, 27 items in level, and priorities analysis was performed through pairwise comparisons. As a result of the AHP analysis, it was found that the relative importance weight of policy aspects was highest in level 1, and the policy factors in level 2 and the cost-based and incentive system introduction factors were considered most important in level 3. These findings show that the importance of the policy guidance or institutions underlying the activation of BIM rather than research and development or corporate innovation is relatively high, and that the preparation of policy plans by public institutions should be the first priority. Therefore, it is considered that the development of a policy system or guideline must be prioritized before it can be advanced to the next activation stage. The use of BIM technologies will not only contribute to improving the productivity of the construction industry, but also to the overall development of the industry and the growth of the construction industry. It is expected that the results of this study can provide as useful information when establishing policies for activating BIM in central government, relevant local governments, and related public institutions.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.59-69
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• 2023

FIDIC White Book is a Model Services Agreement between the Client and the Consultant. This study aimed to derive the Key Risk Sub-Clauses out of 63 Sub-Clauses of General Conditions of the FIDIC White Book by using the Delphi technique. A panel of 40 experts with more than 10 years of experience and expertise in overseas construction services agreements and FIDIC White Book was formed, and the reliability was improved in the direction of increasing the consensus of experts through a total of three Delphi survey processes. In the first Delphi survey, a closed-type survey was conducted on the impact of risk among 63 Sub-Clauses of General Conditions on a Likert 5-point scale, and 26 main risk Sub-Clauses were derived. The Content Validity of the results of the first Delphi survey was verified with the CVR value. In the 2nd and 3rd Delphi surveys, a closed-type survey was conducted on a Likert 10-point scale for 26 main risk Sub-Clauses and the risk possibility and impact of each main risk Sub-Clause were evaluated. The reliability of the 3rd Delphi survey result was verified with the COV value. Total 14 Key Risk Sub-Clauses were derived by applying the average risk possibility and impact of each of the 26 main risk Sub-Clauses to the PI Risk Matrix. The results of deriving Key Risk Sub-Clauses showed that agreement on specific scope of service, delay management, and change management were the most important. As a result of this study, from a practical point of view, consultants of consulting companies provide guidelines that should be reviewed to minimize contractual risks when signing service contracts with clients. From an academic point of view, the direction of research on deriving key risks related to service contracts for consultants participating in overseas construction is presented.

• Journal of the Korean Society of International Agriculture
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• v.31 no.1
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• pp.8-16
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• 2019

Alternatives for increasing the competitiveness of locally manufactured agricultural machinery in domestic and foreign markets has been proposed. This was done by analyzing the major agricultural machinery's price and market share as well as their performance and quality. In the Korean domestic market, the market share of Japanese agricultural machinery has been identified to be 14.5% for tractors, 31.1% for combine harvesters, and 35.8% for rice transplanters, and on track for further increase. Japanese manufacturers' domestic patent shares are 58.5% for tractors, 79.9% for combine harvesters, and 69.8% for rice transplanters, showing the dire need for Korean domestic firms to expand their technological rights. To strengthen the industrial competitiveness of agricultural machinery, therefore, researches that develop the fundamental and elemental technology to reduce the frequency of breakdown should be needed in the short term. To achieve this, it is imperative to establish technology roadmap, promote greater cooperation between academia and industry, and systematically increase research funding. In addition, as a long-term solution for enhancing the competitiveness, an establishment of Agricultural Equipment Technology Institute is strongly recommended to systematically support R&D for developing core technologies, particularly high-quality components that guarantee durability and quality.