• Architectural research
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• v.21 no.2
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• pp.41-48
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• 2019

The purpose of this study is to research and development of 'Korea B(Benefit)-impact Model' for Sustainable Development. A concept evaluation model is 'B(Benefit)-impact model' in U.S.A. We use the results of surveys that examined the importance of social value issues to stakeholders in Korea to implement the benefit-impact model in Korea. In particular, in this paper, we use the KSI(Korean Sustainability Index) survey data conducted by the Korea Standards Association to evaluate the social value of the construction industry for representative stakeholders in the construction industry. The social value pool and the activity indicator pool used for the survey are created based on relevant International Standards; ISO 26000, ISO 14001, ISO 37001. As a result, Korea B-impact model for construction industry included the following five core social value issues; Strengthen transparency of corporate management, Ensure fair employment and employment relations, Efforts to prevent corruption, Conduct fair competition, Efforts to prevent environmental pollution. In addition, the US B-impact model has three limitations. First, it is unclear whether the key indicators have been derived while considering all issues of social value. Second, US B-impact model indicators are developed by the social responsibility experts, so it is necessary to review by stakeholders in each industry. Finally, it would be more effective for companies to use the B-impact model index as a more detailed activity indicator. When developing a Korea B-impact model, the following methods are used to supplement it. First, we reviewed all social value issues using international standards. Secondly, we used the KSI(Korean Sustainability index) survey results to derive the importance of the social value issue of construction industry in Korea. Finally, we have clearly matched the activity indicators by social value core issues based on the GRI Standard so that companies can actually use the Korea B-impact model for the construction sector. The detailed development stages and results of this study are as follows;.

• Journal of Families and Better Life
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• v.16 no.3
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• pp.11-24
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• 1998

The purpose of this study was to develop the educational program model for adolescent substance abusers in relation to preventive and rehabilitative aspects. This educational program model was developed based not only on the social support theory ecological-developmental approach and cognitive-behavioral approach but also on previous studies. This model can be used both for adolescent substance abusers in early stage and in recovery stage. The main contribution of this study is that adolescent abusers will recover effectively through practicing this educational program model.

• Water for future
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• v.17 no.3
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• pp.211-219
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• 1984

A 4-level baroclinic numerical model is designed by using the vorticity equation and Omega equation. Block-Cyclic-Reduction method is applied to the solution of the Helmholtz defferential equation, which is proved to be better than the Relaxation method from the composite viewpoint of accuracy, stability and economy. It was investigated whether the model explains the physical process influenced by voricity and temperature advection. It was also examined if the model atmosphere describes the general circulation. This examination is similar to Phillips(1956). The result of this numerical experiment shows that the model explains qualitatively the Quasi-Geostrophic theory for the development of Baroclinic wave, as throughly described in Holton(1972).

• Korean Journal of Hydrosciences
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• v.1
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• pp.1-14
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• 1990

The analytical diffusion model is first formulated and its characteristics are critically reviewed. The flood events during the 1985-1986 flood seasons in the IHP Pyungchang Representative Basin are routed by this model and are compared with those routed by the kinematic wave model. The present model is proven to be an excellent means of taking the backwater effects due to lateral inflow or downstream river stage variations into consideration in channel routing of flood flows. It also requires much less effort and computing time at a desired station compared to any other reliable flood routing methods.

• Journal of Environmental Science International
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• v.25 no.8
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• pp.1107-1114
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• 2016

This research, sponsored by the Korean Ministry of Environment in 2014, was the first epidemiological study in Korea that investigated the health impact assessment of radon exposure. Its purpose was to construct a model that calculated the annual mean cumulative radon exposure concentrations, so that reliable conclusions could be drawn from environment-control group research. Radon causes chronic lung cancer. Therefore, the long-term measurement of radon exposure concentration, over one year, is needed in order to develop a health impact assessment for radon. Hence, based on the seasonal correction model suggested by Pinel et al.(1995), a predictive model of annual mean radon concentration was developed using the year-long seasonal measurement data from the National Institute of Environmental Research, the Korea Institute of Nuclear Safety, the Hanyang University Outdoor Radon Concentration Observatory, and the results from a 3-month (one season) survey, which is the official test method for radon measurement designated by the Korean Ministry of Environment. In addition, a model for evaluating the effective annual dose for radon was developed, using dosimetric methods. The model took into account the predictive model for annual mean radon concentrations and the activity characteristics of the residents.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.217-225
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• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• Water Engineering Research
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• v.4 no.3
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• The Korean Nurse
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• v.21 no.3 s.116
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• pp.49-58
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• 1982

The aim of this study, is twofold to investigate essential concept of Sister C. Roy''s Adaptation Model, and to make a case-study of nursing care about an Acute Myelaemia patient through the frame of this model. Seeing a human being as a bio-psycho-sociai

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.225-234
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• 2011

The purpose of this study was to survey the intervention model, intervention settings, intervention time, factors influencing selection of intervention model, relationship between intervention model and areas which supporting center for special education based occupational therapist was using. Study data were provided by 46 therapy supporting service professionals through e-mail and analyzed. The findings indicated that first, the therapy supporting service professionals often employed a direct therapy(individual) focusing on performance component of child. Second, they believed that direct therapy is most effective in improving children's performance and raising awareness of the importance of occupational therapy. Third, when choose intervention model, they took into consideration the child's performance components deficits and mind of team chief. Fourth, no correlation between the application time and the perception of effectiveness of intervention model. Also didn't find correlation between applying time of intervention model and intervention area. When putting the various research result together, the model school-based occupational therapists using was similar to medical model. Therefore it is need a study to develop effective intervention model and apply it in school environment.