• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.603-612
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• 2014

Lots of networks are constructed in a large scale industrial complex. Each network meet their demands through production or transportation of materials which are needed to companies in a network. Network directly produces materials for satisfying demands in a company or purchase form outside due to demand uncertainty, financial factor, and so on. Especially utility network and hydrogen network are typical and major networks in a large scale industrial complex. Many studies have been done mainly with focusing on minimizing the total cost or optimizing the network structure. But, few research tries to make an integrated network model by connecting utility network and hydrogen network In this study, deterministic mixed integer linear programming model is developed for integrating utility network and hydrogen network. Steam Methane Reforming process is necessary for combining two networks. After producing hydrogen from Steam-Methane Reforming process whose raw material is steam vents from utility network, produced hydrogen go into hydrogen network and fulfill own needs. Proposed model can suggest optimized case in integrated network model, optimized blueprint, and calculate optimal total cost. The capability of the proposed model is tested by applying it to Yeosu industrial complex in Korea. Yeosu industrial complex has the one of the biggest petrochemical complex and various papers are based in data of Yeosu industrial complex. From a case study, the integrated network model suggests more optimal conclusions compared with previous results obtained by individually researching utility network and hydrogen network.

• Research in Community and Public Health Nursing
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• v.10 no.1
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• pp.5-18
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• 1999

The aim of this study is the development of a fee - based model day care center for the elderly by inquiring into the current condition of facilities in America and in Korea, and in surveying the opinion of domestic elderly about day care facilities. A field trip to U.S. day care services was held between July 5 and July 15 in 1997, and an on-the-spot study for domestic facilities took place during March in 1998. Our research reveals that the overall supply of day care facilities can not meet future demand in terms of quality and quantity. Therefore a model must be created for day care centers of a that consists of a director from a professional group. an adequate environment, and a standardized in order to offer a qualified public health service linked to the home and community in Korea. The director of a day care center is a critical variable in determining the quality of service. Professional skills related to the needs of the elderly and the person's quality of service should be considered in appointing director for the center. This study belleves that a professional nurse should be the director of a day care center. The operating environment of a day care facility should be made up of considerable space comparable to the number of residents, should be in a comfortable and safe location, and should have equipment that provides a qualified, safe service to the elderly. Our model is designed for 20 persons and allocates 4 Peng per person. This model is comprised of a reading room. a craft room, a health room, a room for physical therapy, a dining room, a staff office, and a multi -purpose room connected to other rooms. Day care service should be a comprehensive service program meeting the multidimensional needs of the elderly. A comprehensive service program needs a team of various professionals made up of the elderly family, participants, nurses, social workers, physical therapists, nutritionists, and medical doctors. The program will also include health care service, physical therapy, speech therapy. diet, occupational therapy, transportation service, health and an education program, etc. In conclusion, a model of a day care center is developed with the following components: a professional director and an environment and program, that considers the physical, mental, and social characteristics of the elderly. A model should also motivate self-reliance self-fulfillment in the elderly in order to fulfill their health needs and to prevent isolation from society and mental depression. Furthermore, This facility will be a beneficial factor in reducing a family's burden on caring for the elderly that includes unnecessary hospital expenses. The following is a suggestion based on results this study: A service program should be developed to fit the conditions of the elderly in Korea by specifically analyzing the needs of the elderly.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.245-259
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• 2023

The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.353-358
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• 2001

Since the financial crisis broke out, liquidity has become the critical issue in housing construction industry. In order to secure liquidity, it is prerequisite to precisely forecast cash flow. However, construction companies have failed to come up with a systematic process to manage and forecast cash flow. Until now, companies have solely relied on the prediction of profits and losses, which is carried out as they review business feasibility. To obtain more accurate cash flow forecast model, practical pattern of payments should be taken into account. In this theory, basic model that analyzes practical housing payment collection pattern resulting from prepayments and arrears is described. This model is to complement conventional cash flow forecast scheme in the phase of business feasibility review. Analysis result on final losses in cash that occur as a result of prepayment and arrears is considered in this model. Additionally, in the estimation of construction cost in the phase of business feasibility review, real construction prices instead of official prices are applied to enhance accuracy of cash outflow forecast. The proportion of payment made by a bill and changes in payment date caused by rescheduling of a bill are also factored in to estimate cash outflow. This model would contribute to achieving accurate cash flow forecast that better reflect real situation and to enhancing efficiency in capital management by giving a clear picture with regard to the demand and supply timing of capital.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.105-119
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• 2021

An increase in the frequency and intensity of both floods and droughts has been recently observed due to an increase in climate variability. Especially, land-use change associated with industrial structure and urbanization has led to an imbalance between water supply and demand, acting as a constraint in water resource management. Accurate rainfall-runoff analysis plays a critical role in evaluating water availability in the water budget analysis. This study aimed to explore various continuous rainfall-runoff models over the Soyanggang dam watershed. Moreover, the ensemble modeling framework combining multiple models was introduced to present scenarios on streamflow considering uncertainties. In the ensemble modeling framework, rainfall-runoff models with fewer parameters are generally preferred for effective regionalization. In this study, more than 40 continuous rainfall-runoff models were applied to the Soyanggang dam watershed, and nine rainfall-runoff models were primarily selected using different goodness-of-fit measures. This study confirmed that the ensemble model showed better performance than the individual model over different flow regimes.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.29-41
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• 2022

As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.69-79
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• 2019

In Korea, more than 60% of the whole lands are mountainous area. Since many decades ago, hydroelectric power plants have been constructed and eco-friendly energy has been produced. Hydropower can cope with the rapidly changing energy supply and demand, and produce eco-friendly energy. However, when the reservoir is built, it is often inevitable to damage the environment due to construction of large structure. In this study, the optimal reservoir operation model was developed to maximize power generation by monthly operation for long-term operation planning. The dam operation model was developed using the linear programming which is widely used in the optimal resources allocation problems. And the reservoir operation model can establish monthly operation plan for 1 year. Linear programming requires both object function and constraints to be linear. However, since the power generation equation is nonlinear, it is linearized using the Taylor Expansion technique. The optimization results were compared with the 2009-2018 historical data of five hydropower reservoirs. As a result, the total optimal generation is about 10~37% higher than the historical generation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.3
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• pp.63-74
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• 1986

A methodology for the probabilistic determination of active storage capacity of an impounding reservoir is proposed with due considerations to the durations and return periods of the low flow series at the reservoir site. For more reliable probabilistic analysis the best-fit stochastic generation model of Monte Carlo type was first selected for the generation of monthly flow series, the models tested being the Month Carlo Model based on the month-by-month flow series (Monte Carlo-A Type), Monte Carlo Model based on the standardized sequential monthly flow series (Monte Carlo-B Type), and the Thomas-Fiering Model. Monte Carlo-B Model was final1y selected and synthetic monthly flows of 200 years at Hong Cheon dam site were generated. With so generated 200 years' monthly flows partial duration series of low flows were developed for various durations. Each low flow series was further processed by a nonsequential mass analysis for specified draft rates. This mass analysis furnished the storage-draft-recurrence interval relationship which gives the reservoir storage requirement for a specified water demand from the reservoir during a drought of given return period. Illustrations are given on the application of these results in analyzing the water supply capacity of a particlar reservoir, existing or proposed.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.779-793
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• 1998

In this study, for the purpose of water supply planning, we propose a sophisticated multi-period mixed integer programming model that can coordinate the behavior of multi-reservoir operation, minimizing unnecessary spill. It can simulate the system with operating rules which are self- generated by the optimization engine in the algorithm. It is an optimization model in structure, but it indeed simulates the coordinating behavior of multi-reservoir operation. It minimizes the water shortfalls in demand requirements, maintaining flood reserve volume, minimizing unnecessary spill, maximizing hydropower generation release, keeping water storage levels high for efficient hydroelectric turbine operation. This optimization model is a large scale mixed integer programming problem that consists of 3.920 integer variables and 68.658 by 132.384 node-arc incidence matrix for 28 years of data. In order to handle the enormous amount of data generated by a big mathematical model, the utilization of DBMS (data base management system)seems to be inevitable. It has been tested with the Han River multi-reservoir system in Korea, which consists of 2 large multipurpose dams and 3 hydroelectric dams. We demonstrated successfully that there is a good chance of saving substantial amount of water should it be put to use in real time with a good inflow forecasting system.