• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.45-53
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• 2019

As the urbanization progresses, the demand for parking in large cities surges compared with that for parking lots. However, the space for securing a parking lot in a large city is physically limited and a budget problem also arises. Therefore, a shared parking system that can utilize existing parking lots is becoming important. This study was carried out to analyze the parking area efficiently for the residents parking area. As a result of the questionnaire survey, it was the most frequent passage to work / commuting and business purposes. The most important factors in parking were 'Parking charge', 'Walking distance to the destination after parking', 'Parking lot searching time' Approximately 46 % of the respondents were female. As a result of the quantitative analysis of the factors influencing the potential use of the intention to use as a dependent variable, it was analyzed that the policy was effective to reduce the parking fee to less than 500 won per 10 minutes and take about 3-6 minutes to search.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.122-129
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• 2019

Due to its nature the manufacturing industry faces a cyclical economy, and therefore there is an urgent need for a companion industry to cope with this cyclic pattern in the long run. The sector suitable for meeting this demand is the repair and shipbuilding industry. In order to operate a shipbuilding repair business, a floating dock is indispensable, and most obsolete floating docks were imported from overseas and operated through repair/maintenance. However, there is no precise guideline for floating dock safety, and most models have been in use for at least 30 years without being required to enter classification at the time of operation. In this study, structural strength analysis was carried out using measured thickness information of aged floating docks, and the residual structural strength of floating docks in operation was analyzed. The main results derived from this study can be referred to as guidelines for the review of the structural safety of similar equipment, and it is expected that an optimal solution will be found within a short time using this method for repair/maintenance.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Membrane Journal
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• v.31 no.4
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• pp.241-252
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• 2021

Rapid industrialization with growing population leads to environmental water pollution. Demand in generation of clean water from waste water is ever increasing by scarcity of rain water due to change in weather pattern. Colorimetric detection of heavy metal present in clean water is very simple and effective technique. In this review membrane based colorimetric detection of mercury (II) ions are discussed in details. Membrane such as cellulose, polycaprolactone, chitosan, polysulfone etc., are used as support for metal ion detection. Nanofiber based materials have wide range of applications in energy, environment and biomedical research. Membranes made up of nanofiber consist up plenty of functional groups available in the polymer along with large surface area and high porosity. As a result, it is easy for surface modification and grafting of ligand on the fiber surface enhanced nanoparticles attachment.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.50-58
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• 2021

The demand for eco-friendly energy is expected to increase due to the recently strengthened environmental regulations. In particular, the flow inside the pipe used in a cargo handling system (CHS) or fuel gas supply system (FGSS) of hydrogen transport ships and hydrogen-powered ships exhibits a very complex pattern of multiphase-thermal flow, including the boiling phenomenon and high accuracy analysis is required concerning safety. In this study, a feasibility study applying the boiling model was conducted to analyze the multiphase-thermal flow in the pipe considering the phase change. Two types of boiling models were employed and compared to implement the subcooled boiling phenomenon in nucleate boiling numerically. One was the "Rohsenow boiling model", which is the most commonly used one among the VOF (Volume-of-Fluid) boiling models under the Eulerian-Eulerian framework. The other was the "wall boiling model", which is suitable for nucleate boiling among the Eulerian multiphase models. Moreover, a comparative study was conducted by combining the nucleate site density and bubble departure diameter model that could influence the accuracy of the wall boiling model. A comparison of the Rohsenow boiling and the wall boiling models showed that the wall boiling model relatively well represented the process of bubble formation and development, even though more computation time was consumed. Among the combination of models used in the wall boiling model, the simulation results were affected significantly by the bubble departure diameter model, which had a very close relationship with the grid size. The present results are expected to provide useful information for identifying the characteristics of various parameters of the boiling model used in CFD simulations of multiphase-thermalflow, including phase change and selecting the appropriate parameters.

• The Journal of Bigdata
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• v.5 no.2
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• pp.85-95
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• 2020

In this study, a mobility analysis method is suggested to estimate an O/D trip demand estimation using Mobile Phone Signaling Data. Using mobile data based on mobile base station location information, a trip chain database was established for each person and daily traffic patterns were analyzed. In addition, a new algorithm was developed to determine the traffic characteristics of their mobilities. To correct the ping pong handover problem of communication data itself, the methodology was developed and the criteria for stay time was set to distinguish pass by between stay within the influence area. The big-data based method is applied to analyze the mobility pattern in inter-regional trip and intra-regional trip in both of an urban area and a rural city. When comparing it with the results with traditional methods, it seems that the new methodology has a possibility to be applied to the national survey projects in the future.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.11-21
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• 2022

The COVID-19 started to spread at early 2020 in South Korea and has been threatening our life in many aspects. Countermeasures such as social distancing to prevent COVID-19 spread have brought many changes in our society an human life. In this study, as a part of the COVID-19 pandemic management, drinking water usage change is analyzed to evaluate potential risks on water supply service. We collected hourly water use data of residential area in S city, which is a mid-size city in South Korea, before and after the COVID-19 pandemic. The collected data were analyzed to reveal the changes in total water consumption, water usage weight, and hourly water-demand pattern caused by the COVID-19 pandemic. The case study revealed the noticeable changes in water consumption caused by the COVID-19 pandemic and required more secured and adaptive operation of drinking water system under the pandemic situation caused by infectious disease.

• Applied Chemistry for Engineering
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• v.33 no.4
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• pp.335-342
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• 2022

In the agricultural sector where the fossil fuels are primary energy resources, the current global energy crisis together with the dissemination of smart farming has led to the new phase of energy pattern in which the electricity demand is growing faster particularly. Therefore, the fuel cell combined heat and power system, coupling the environmentally friendly fuel cell to biomass treatment and feeding, can be regarded as the most effective energy system in agriculture. In this mini-review, we discuss the R&D trend of the fuel cell combined heat and power system aimed at utilizing agricultural by-products as fuels and highlight the issues in terms of the process configuration and interconnection of individual processes.

• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.79-89
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• 2023

As the demand for environmental-friendly agricultural products continues to rise due to increased concerns regarding food safety and ecosystem conservation, it is becoming important to identify regions and spatial locations where environmental-friendly should be intensively established for production integration. This study aims to analyze the spatial distribution of environmental-friendly certified farms in Jeollanam-do, South Korea. Spatial statistical analysis based on Local Moran's I and Getis-Ord Gi^* were used to identify spatial cluster characteristics and landscape indices were utilized to analyze spatial patterns of environmental-friendly certified farms. The results indicated that Haenam-gun, Gangjin-gun, Muan-gun, and Jindo-gun were identified as hotspots, while Muan-gun, Goheung-gun, and Jindo-gun exhibited high connectivity. This suggests that environmental-friendly certified farms in Muan-gun and Jindo-gun were clustered and closely connected to one another. Based on the results of the spatial distribution of environmental-friendly certified farms, areas belonging to the hotspot and with high connectivity should be managed as clustered districts to secure the foundation and system of environmental-friendly certified farms. Areas that belong to cold spots and have low connectivity should be preceded by measures to promote conversion to environmental-friendly agriculture. In addition, it is necessary to make it possible to create a large-scale cluster district through a long-term spatial planning strategy to expand the environmental-friendly certified farms. The findings of this study can provide quantitative data on policies and discussions for developing a model for rural spatial planning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.322-323
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• 2022

The most necessary thing for the optimal operation of a water purification plant is to accurately predict the pattern and amount of tap water used by consumers. The required amount of tap water should be delivered to the drain using a pump and stored, and the required flow rate should be supplied in a timely manner using the minimum amount of electrical energy. The short-term demand forecasting required from the point of view of energy optimization operation among water purification plant volume predictions has been made in consideration of seasons, major periods, and regional characteristics using time series analysis, regression analysis, and neural network algorithms. In this paper, we analyzed energy management methods through AI-based complex sensor applicability analysis such as LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Units), which are types of cyclic neural networks.