• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.6-19
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• 2023

As data management and intelligence capability become proxy indicators of national power, the risk provoked by high depending on digital technology ironically increases. The quicker the changes come to be, the more important digitizing existing data and management of digital data are. The management of archaeological data could not be exceptional. It has to be performed in a more comprehensive, systematic and rapid manner. In order to perform the task, the nature of archaeological data contained in the digital archive should be properly recognized in advance: the primary data are generated by excavation as a process destroying their sources, the data are enormous in type and quantity, including long-term and various human experience, and the natural extinction of primary data in handwritten form is likely to be more crucial than in any other discipline. These characteristics of archaeological data unimaginably devastated the possibility of recovering archives, when we face a digital dark age. Considering both recent trend and the nature of archaeological data mentioned above, we can derive strategies for building a sustainable archaeological digital archive. As an archaeology-major consumer of the digital data, I propose four strategic considerations: ① establishing a system of digital data literacy; ② enhancing evaluation and capability of data reuse; ③ building an international data sharing system; ④ developing it into the platform for digital archaeology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.323-330
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• 2010

The time in port for vessels is one of the important factors for analyzing the operation status and the capacity of ports. In addition, the time in port for vessels can be directly used for estimating the greenhouse gas emissions resulted from vessels in port. However, it is unclear which variables can affect the time in port for vessels and what the marginal effect of each variable is. With these challenges in mind, the study analyzes the time in port for vessels arriving and departing port of Busan by using a parametric survival model. The results show that the log-logistic accelerated failure time model is appropriate to explain the time in port for 19,167 vessels arriving and departing port of Busan in 2008, in which the time in port is significantly affected by gross tonnage of vessels, service capacity of terminal, and vessel type. This study also shows that the greenhouse gas emission resulted from full-container vessels, which accounted for about 61% of all vessels with loading/unloading purpose arriving and departing port of Busan in 2008, is about "17 ton/vessel" in the boundary of port of Busan. However, the hotelling greenhouse gas emissions resulted from non-container vessels (3,774 vessels; 20%) are greater than those from the full-container vessels. Hence, it is necessary to take into account more efficient port management polices and technologies to reduce the service time of non-container vessels in port of Busan.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.419-430
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• 2019

The study sought to find out the actual process of adapting to social life through interviews with college students and adult women living as defectors in the South, and to find out how it would be desirable to move forward in terms of education in order for all of our lives to be happy. The method of research consisted of semi-structured interviews. The interview period was four months. Based on the results of the interview, the following conclusions are given. First, it is necessary to establish a direction for strengthening cooperation rather than conflict in education, and restoring homogeneity of the same people. It is also true that real challenges are not easy at a time when the fratricidal war like the 6.25 conflict has deepened the conflict. However, at this point, 65 years later, the nation cannot stay only in the past. Second, the perception that they disapprove of economic aid to North Korean defectors also exists in part among adults. Third, negative thoughts about reunification among South Koreans also appear relatively high. This is believed to be due to the argument that the growth of social welfare and economic growth is offset by the increase in unification costs. Fourth, the content of living in real life such as culture and art, along with knowledge-oriented education in school education, should be treated with the same weight. This should create an environment in which North Korean defectors can enjoy the same happiness as South Koreans.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.450-464
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• 2023

Pulse oximetry, a non-invasive technique for evaluating blood oxygen saturation, conventionally depends on isolated measurements, rendering it vulnerable to factors like illumination profile, spatial blood flow fluctuations, and skin pigmentation. Previous efforts to address these issues through imaging systems often employed red and near-infrared illuminations with distinct profiles, leading to inconsistent ratios of transmitted light and the potential for errors in calculating spatial oxygen saturation distributions. While an integrating sphere was recently utilized as an illumination source to achieve uniform red and near-infrared illumination profiles on the sample surface, its bulkiness presented practical challenges. In this work, we have enhanced the pulse oximetry imaging system by transitioning illumination from an integrating sphere to a multi-wavelength LED configuration. This adjustment ensures simultaneous emission of red and near-infrared light from the same position, creating a homogeneous illumination profile on the sample surface. This approach guarantees consistent patterns of red and near-infrared illuminations that are spatially uniform. The sustained ratio between transmitted red and near-infrared light across space enables precise calculation of the spatial distribution of oxygen saturation, making our pulse oximetry imaging system more compact and portable without compromising accuracy. Our work significantly contributes to obtaining spatial information on blood oxygen saturation, providing valuable insights into tissue oxygenation in peripheral regions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.735-747
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• 2023

In recent times, the sharp increase in extreme flood damages due to climate change has posed a challenge to effectively address flood-related issues solely relying on conventional flood management infrastructure. In response to this problem, this study aims to consider the effectiveness of nature-based flood management approaches, specifically levee retreat and relocation. To achieve this, we utilized a 1D numerical model, HEC-RAS, to analyze the flood reduction effects concerning floodwater levels, flow velocities, and time-dependent responses to a 100-year frequency flood event. The analysis results revealed that the effect of creating a flood buffer zone of the nature-based solution extends from upstream to downstream, reducing flood water levels by up to 30 cm. The selection of the flow roughness coefficient in consideration of the nature-based flood buffer space creation characteristics should be based on precise criteria and scientific evidence because it is sensitive to the flood control effect analysis results. Notably, floodwater levels increased in some expanded floodplain sections, and the reduction in flow velocities varied depending on the ratio of the expanded cross-sectional area. In conclusion, levee retreat and floodplain expansion are viable nature-based alternatives for effective flood management. However, a comprehensive design approach is essential considering flood control effects, flow velocity reduction, and the timing of peak water levels. This study offers insights into addressing the challenges of climate-induced extreme flooding and advancing flood management strategies.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1059-1069
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• 2023

Dam-break flow occurs when an elevated dam suddenly collapses, resulting in the catastrophic release of rapid and uncontrolled impounded water. This study compares laminar and turbulent closure models for simulating three-dimensional dam-break flows using OpenFOAM. The Reynolds-Averaged Navier-Stokes (RANS) model, specifically the k-ε model, is employed to capture turbulent dissipation. Two scenarios are evaluated based on a laboratory experiment and a modified multi-layered block obstacle scenario. Both models effectively represent dam-break flows, with the turbulent closure model reducing oscillations. However, excessive dissipation in turbulent models can underestimate water surface profiles. Improving numerical schemes and grid resolution enhances flow recreation, particularly near structures and during turbulence. Model stability is more significantly influenced by numerical schemes and grid refinement than the use of turbulence closure. The k-ε model's reliance on time-averaging processes poses challenges in representing dam-break profiles with pronounced discontinuities and unsteadiness. While simulating turbulence models requires extensive computational efforts, the performance improvement compared to laminar models is marginal. To achieve better representation, more advanced turbulence models like Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) are recommended, necessitating small spatial and time scales. This research provides insights into the applicability of different modeling approaches for simulating dam-break flows, emphasizing the importance of accurate representation near structures and during turbulence.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.55-62
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• 2023

Recent ransomware attacks employ various techniques and pathways, posing significant challenges in early detection and defense. Consequently, the scale of damage is continually growing. This paper introduces a machine learning-based approach for effective ransomware detection by focusing on file encryption and encryption patterns, which are pivotal functionalities utilized by ransomware. Ransomware is identified by analyzing password behavior and encryption patterns, making it possible to detect specific ransomware variants and new types of ransomware, thereby mitigating ransomware attacks effectively. The proposed machine learning-based encryption behavior detection technique extracts encryption and encryption pattern characteristics and trains them using a machine learning classifier. The final outcome is an ensemble of results from two classifiers. The classifier plays a key role in determining the presence or absence of ransomware, leading to enhanced accuracy. The proposed technique is implemented using the numpy, pandas, and Python's Scikit-Learn library. Evaluation indicators reveal an average accuracy of 94%, precision of 95%, recall rate of 93%, and an F1 score of 95%. These performance results validate the feasibility of ransomware detection through encryption behavior analysis, and further research is encouraged to enhance the technique for proactive ransomware detection.