• Journal of the Korea Institute of Building Construction
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• v.10 no.1
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• pp.163-173
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• 2010

A significant number of projects have been managed by US Army Corps of Engineers FED. Today, more information must be provided to the parties involved in the projects by phase than ever before. Specifically, USFK`s construction projects have been managed by FED(Far East District). Recently, however, large US private construction companies have been filling the role previously taken by FED. However, there is few construction managers to implement FED project in Korea. Accordingly, this study analyzes FED projects practices with focus on the construction management actors in order to suggest guideline. This study suggests a model FED construction process(Bid, Contract, Construction, As-Built Phase) by analyzing the existing FED project process using a IDEF0 methodology.

• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.223-248
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• 2009

The purpose of this empirical study is to examine and explore the relationships between three variables; shipping companies' service quality, customer satisfaction and customer loyalty. Special features of this study could be summarized as following. First, this is empirical study based on market research according to the definition of 'customer' as freight forwarders and actual exporter/importer together contrary to previous studies. Second, to evaluate shipping companies' service quality, 5 components of SERVPERF model was used. Third, to test correlations between 3 variables; service quality, customer satisfactions and customer loyalty, statistical analysis was used with tools of SPSSWIN ver 15.0 and AMOS ver 7.0. For effective study, many thesis have been obtained through literature survey. However, major results were compiled from directly structured questionnaire, which were collected from Korean import/ export companies and freight forwarders.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7990-8000
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• 2015

Plant factories are plant cultivation systems which produce farm products uniformly under the controlled environmental condition regardless of seasons and places. Thermal flow in the plant factory is an important parameter in cultivating plants. In this research, we study thermal flow characteristics for a hybrid plant factory with multi-layer cultivation shelves using computer simulation techniques. In order to obtain numerical solutions for thermal flow characteristics, a finite volume method was applied. We consider a low-Reynolds-number ${\kappa}-{\epsilon}$ turbulence model, incompressible viscous flows, and pressure boundary conditions for numerical simulation. Commercial software Solid Works Flow Simulation is then used to investigate characteristics of thermal flows in the plant factory applying several different inflow air velocities and arrangements of cultivation shelves. From numerical analysis results, we found that temperatures in cultivation shelves were uniformly distributed for Case 3 when the inflow air velocity was 1.6 m/s by using a blower in the plant factory. However in Case 1 lower temperature distributions were observed in test beds, TB2 and TB3, which indicated that additional temperature control efforts would be required. Average shelf temperature increased by $3^{\circ}C$ using artificial light source (DYLED47) with 50% blue and 50% red LED ratios. Korea Academia-Industrial cooperation Society.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.3
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• pp.195-203
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• 2012

In this study, The effects of three different biological activated carbon (BAC) materials (each coal, coconut and wood based activated carbons) and anthracite, empty bed contact time (EBCT) and water temperature on the removal of MK, HHCB and AHTN in BAC filters were investigated. Experiments were conducted at three water temperatures (5, 15 and $25^{\circ}C$) and four EBCTs (5, 10, 15 and 20 min). The results indicated that coal based BAC retained more attached bacterial biomass on the surface of the activated carbon than the other BAC, increasing EBCT or increasing water temperature increased the synthetic musk compounds (SMCs) removal in BAC columns. The kinetic analysis suggested a first-order reaction model for MK, HHCB and AHTN removal at various water temperatures (5, 15 and $25^{\circ}C$). The pseudo-first-order biodegradation rate constants and half-lives were also calculated for MK, HHCB and AHTN removal at 5, 15 and $25^{\circ}C$. The pseudo-first-order biodegradation rate constants and half-lives of MK, HHCB and AHTN ranging from 0.0082 $min^{-1}$ to 0.4452 $min^{-1}$ and from 1.56 min to 84.51 min could be used to assist water utilities in designing and operating BAC filters for SMCs removal.

• Journal of Korea Water Resources Association
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• v.39 no.3 s.164
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• pp.275-288
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• 2006

This study develops ESP (Ensemble Streamflow Prediction) system by using medium-term numerical weather prediction model which is GDAPS(T213) of KMA. The developed system forecasts medium- and long-range exceedance Probability for streamflow and RPSS evaluation scheme is used to analyze the accuracy of probability forecasts. It can be seen that the daily probability forecast results contain high uncertainties. A sensitivity analysis with respect to forecast time resolution shows that uncertainties decrease and accuracy generally improves as the forecast time step increase. Weekly ESP results by using the GDAPS output with a lead time of up to 28 days are more accurately predicted than traditional ESP results because conditional probabilities are stably distributed and uncertainties can be reduced. Therefore, it can be concluded that the developed system will be useful tool for medium- and long-term reservoir inflow forecasts in order to manage water resources.

• Journal of Animal Environmental Science
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• v.15 no.2
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• pp.131-138
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• 2009

This study was conducted to find ways to control environment with the difference between body temperature and background temperature based on swine activity, and to apply to the environment control system of swine barns based on the findings. Following are the results. 1. Swine activity related to background temperature was achieved as color images and swine activity status was categorized into cold, comfortable, and hot periods with visualization system (thermal image system). 2. Thermal image system consisted of an infrared CCD camera, an image processing board - DIF (TH3100), an main computer (400Hz, 128M, 586 Pentium model) with C++ program installed. 3. Thermal image system categorizing temperatures into cold, comfortable, and hot was applicable to the environment control system of swine barns 4. Feed intake was higher in cold temperature, and finishing weight and weight gain per day in cold temperature were lower than others (p<0.05).

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.55-61
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• 2021

In this paper, we proposed a DeepLabv3+ based encoder-decoder model utilizing an attention mechanism for precise semantic segmentation. The DeepLabv3+ is a semantic segmentation method based on deep learning and is mainly used in applications such as autonomous vehicles, and infrared image analysis. In the conventional DeepLabv3+, there is little use of the encoder's intermediate feature map in the decoder part, resulting in loss in restoration process. Such restoration loss causes a problem of reducing segmentation accuracy. Therefore, the proposed method firstly minimized the restoration loss by additionally using one intermediate feature map. Furthermore, we fused hierarchically from small feature map in order to effectively utilize this. Finally, we applied an attention mechanism to the decoder to maximize the decoder's ability to converge intermediate feature maps. We evaluated the proposed method on the Cityscapes dataset, which is commonly used for street scene image segmentation research. Experiment results showed that our proposed method improved segmentation results compared to the conventional DeepLabv3+. The proposed method can be used in applications that require high accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.47-60
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• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.237-248
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• 2021

Based on sports known to reduce adolescents' smartphone addiction, this study aims to identify the structural causal relationship between sport commitment and smartphone addiction. First of all, based on prior studies, it was intended to show that adolescents' sport commitment is effective in reducing smartphone addiction through social support and ego-resilience, and that such causal relationships vary significantly depending on gender. To this end, a survey of 605 middle and high school students was conducted, and the structural relationship between the four established latent variables was analyzed by analyzing the structural equation model using the SPSS 25.0 and AMOS 23.0 programs. According to the analysis, adolescents' sport commitment was found to have an adverse effect on smartphone addiction, and social support and ego-resilience in the relationship between the two variables were found to have a mediated effect. In addition, these results showed significant differences in gender. This study expanded the field of smartphone addiction and sports convergence study by revealing the relationship between sport commitment as psychological recognition variable and addiction Unlike previous studies using a participation time, duration, and intensity, and suggested that structural relationships with personal characteristic variables and gender-specific approaches are important. Through this, it is meaningful that it provided basic data for in-depth convergence study in the smartphone addiction and development of gender-specific programs.