• Korean Journal of Heritage: History & Science
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• v.46 no.2
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• pp.114-135
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• 2013

Among the UNESCO World Heritage Sites, the proportion of natural heritage to cultural heritage is relatively small. In 2007, the "Jeju Volcanic Island and Larva Tubes" was the first one that was designated as an UNESCO World Natural Heritage Site in Korea. The growing Korean geological heritage condition and conservation case studies on management of the geological heritage were examined in this study. Furthermore, the purpose of this study is to show future driving strategy for conservation and improvement plan on our geological heritage. Natural Monuments as a state-designated natural property and Geoparks as a new application system for geological heritage are important to conserve our geological heritage. Public engagement through establishment of visitor centers is definitely needed to improve education and promotion. The study includes field investigation for the "Wadden Sea", an World Natural Heritage Site for a mud flat, interviews with staffs and experts who are responsible for investigating and managing the site. Three factors can likely be attributed to its successful management and conservation policy for the "Wadden Sea". First of all, there is an operation for integrated management system and joint secretariat for research and monitoring. Next, researchers invigorate the visitor centers for promotion and education on geological heritage. Finally, experts and staffs implement various research topics and projects based on a long-range plan. The study was carried out to evaluate the present condition of our geological heritage and to make a proposal as a policy to improve value and conserve them. In conclusion, this study provided future discussion that may help researchers to make a decision on long-term policies for the geological subject of Korean natural heritage.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.139-150
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• 2019

Though, fishing vessel accidents account for 70 % of all maritime accidents in Korean waters, most research has focused on identifying causes and developing mitigation policies in an attempt to reduce this rate. However, predicting and evaluating accident risk needs to be done before the implementation of such reduction measures. For this reasons, we havve performed a risk analysis to calculate the risk of accidents and propose a risk criteria matrix with 4 quadrants, within one of which forecasted risk is plotted for the relative comparison of risks. For this research, we considered 9 types of fishing vessel accidents as reported by Korea Maritime Safety Tribunal (KMST). Given that no risk evaluation criteria have been established in Korea, we established a two-dimensional frequency-consequence grid consisting of four quadrants into which paired frequency and consequence for each type of accident are presented. With the simple structure of the evaluation model, one can easily verify the effect of frequency and consequence on the resulting risk within each quadrant. Consequently, these risk evaluation results will help a decision maker employ more realistic risk mitigation measures for accident types situated in different quadrants. As an application of the risk evaluation matrix, accident types were further analyzed using accident causes including human error (factor) and appropriate risk reduction options may be established by comparing the relative frequency and consequence of each accident cause.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.187-195
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• 2019

The needs for precise diagnostics and farm management-decision aids have increased to reduce the risk of climate change and environmental stress. Crop simulation models have been widely used to search optimal solutions for effective cultural practices. However, limited knowledge on physiological responses to environmental variation would make it challenging to apply crop simulation models to a wide range of studies. Advanced research facilities would help investigation of plant response to the environment. In the present study, the sunlit controlled environment chambers, known as Korean SPAR (Soil-Plant-Atmosphere-Research) system, was developed by renovating existing SPAR system. The Korean SPAR system controls and monitors major environmental variables including atmospheric carbon dioxide concentration, temperature and soil moisture. Furthermore, plants are allowed to grow under natural sunlight. Key physiological and physical data such as canopy photosynthesis and respiration, canopy water and nutrient use over the whole growth period are also collected automatically. As a case study, it was shown that the Korean SPAR system would be useful for collection of data needed for understanding the growth and developmental processes of a crop, e.g., soybean. In addition, we have demonstrated that the canopy photosynthetic data of the Korean SPAR indicate the precise representation of physiological responses to environment variation. As a result, physical and physiological data obtained from the Korean SPAR are expected to be useful for development of an advanced crop simulation model minimizing errors and confounding factors that usually occur in field experiments.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.111-128
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• 2019

In the current procurement system in Korean military, the army, navy and air force have their own distributors, military branches and warehouses. However, especially, it has been hard to have the economy of scale because most of suppliers have shipped their order from the suppliers to each of Korean military directly. Koran military considers the transportation cost as one of the management cost factors among various kinds of cost. Furthermore they have contracted with the suppliers in annual and collectively on the transportation. Hence they have been in trouble with getting efficiency of Defense budget execution because it is hard to make a decision of Defense budget with real transportation cost. Moreover Korean army, navy and air force have their own supply chain separately, so they can not cooperate flexible and quickly when they need. Therefore, in this research, we provide a benchmarking of DTCI (Defense Transportation Coordination Initiative) which has been proved that it has improved the procurement system in US implementing the integrated transportation system with 3PL and military. In addition we propose advanced integrated shipping model using Hub & Spoke system for Korean military. In order to prove its effect, we simulate our model based on the real data of the suppliers' delivery to compare with the current system when it comes to how much we can save the cost. Our research can provide evidence that the integrated procurement system in Korean military will improve Korean military procurement system.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.31-40
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• 2018

With the development of IT technology recently, medical information systems are being constructed in an integrated u-health environment through cloud services, IoT technologies, and mobile applications. These kinds of medical information systems should provide the medical staff with authorities to access patients' medical information for emergency status treatments or therapeutic purposes. Therefore, in the medical information systems, the reliable and prompt authentication processes are necessary to access the biometric information and the medical information of the patients in charge of the medical staff. However, medical information systems are accessing with simple and static user authentication mechanism using only medical ID / PWD in the present system environment. For this reason, in this paper, we suggest a dynamic situation authentication mechanism that provides transparency of medical information access including various authentication factors considering patient's emergency status condition and dynamic situation authentication system supporting it. Our dynamic Situation Authentication is a combination of user authentication and mobile device authentication, which includes various authentication factor attributes such as emergency status, role of medical staff, their working hours, and their working positions and so forth. We designed and implemented a dynamic situation authentication system including emergency status decision, dynamic situation authentication, and authentication support DB construction. Finally, in order to verify the serviceability of the suggested dynamic situation authentication system, the medical staffs download the mobile application from the medical information server to the medical staff's own mobile device together with the dynamic situation authentication process and the permission to access medical information to the patient and showed access to medical information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.

• Korean Journal of Environment and Ecology
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• v.35 no.2
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• pp.193-203
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• 2021

As endangered species are gradually increasing due to land development by humans, it is essential to secure sufficient protected areas (PAs) proactively. Therefore, this study checked priority conservation areas to select candidate PAs when considering the impact of land development. We determined the conservation priorities by analyzing four scenarios based on existing conservation areas and reflecting the development impact using MARXAN, the decision-making support software for the conservation plan. The development impact was derived using the developed area ratio, population density, road network system, and traffic volume. The conservation areas of endangered species were derived using the data of the appearance points of birds, mammals, and herptiles from the 3rd National Ecosystem Survey. These two factors were used as input data to map conservation priority areas with the machine learning-based optimization methodology. The result identified many non-PAs areas that were expected to play an important role conserving endangered species. When considering the land development impact, it was found that the areas with priority for conservation were fragmented. Even when both the development impact and existing PAs were considered, the priority was higher in areas from the current PAs because many road developments had already been completed around the current PAs. Therefore, it is necessary to consider areas other than the current PAs to protect endangered species and seek alternative measures to fragmented conservation priority areas.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.603-613
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• 2021

As a core policy for achieving the goal of reducing greenhouse gas emissions in the building sector, Korea has enforced the mandatory certification of zero energy buildings for new public buildings from 2020. This study suggests energy-saving technologies and economic factors that building officials can refer to for decision-making on the implementation of zero energy buildings. For this study, the construction cost for the energy item of a building was analyzed by collecting the building energy efficiency level certification data and detailed construction cost statement data from public institutions for the last three years. Based on the building energy efficiency certification data, each energy item of the baseline building was derived, and the energy performance of the zero energy building was derived through repetitive simulations by gradually increasing the energy performance value of the baseline building. By applying the analyzed construction cost, the construction cost for each energy item of the baseline and zero energy buildings was derived. As a result, the lighting equipment contributed up to 10.5% energy savings, and the increase in construction cost of the cooling and heating system was at least 9.1%.