• Membrane Journal
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• v.33 no.6
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• pp.352-361
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• 2023

Steam methane reforming is currently the most widely used technology for producing hydrogen, a clean fuel. Hydrogen produced by steam methane reforming contains impurities such as carbon monoxide, and it is essential to undergo an appropriate post-purification step for commercial usage, such as fuel cells. Recently, membrane separation technology has been gaining great attention as an effective purification method; in this study, we evaluated the feasibility of using commercial polysulfone membranes for biogas upgrading to separate and recover hydrogen from a hydrogen/carbon monoxide gas mixture. Initially, we examined the physicochemical properties of the commercial membrane used. We then conducted performance evaluations of the commercial membrane module under various conditions using mixed gas, considering factors such as stage-cut and operating pressure. Finally, based on the evaluation results, we carried out simulations for process design. The maximum H₂ permeability and H₂/CO separation factor for the commercial membrane process were recorded at 361 GPU and 20.6, respectively. Additionally, the CO removal efficiency reached up to 94%, and the produced hydrogen concentration achieved a maximum of 99.1%.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.533-545
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• 2023

In this study, an investigation was conducted on the features, events, and processes (FEP) that could impact the long-term safety of the natural barriers constituting high-level radioactive waste geological repositories. The FEP list was developed utilizing the IFEP list 3.0 provided by the Nuclear Energy Agency (NEA) as foundational data, supplemented by geological investigations and research findings from leading countries in this field. A total of 49 FEPs related to the performance of the natural barrier were identified. For each FEP, detailed definitions, classifications, impacts on long-term safety, significance in domestic conditions, and feasibility of quantification were provided. Moreover, based on the compiled FEP list, three scenarios that could affect the long-term safety of the disposal facility were developed. Geological factors affecting the performance of the natural barrier in each scenario were selected and their relationships were visualized. The constructed FEP list and the visualization of interrelated factors in various scenarios are anticipated to provide essential information for selecting and organizing factors that must be considered in the development of mathematical models for quantitatively evaluating the long-term safety of deep geological repositories. In addition, these findings could be effectively utilized in establishing criteria related to the key performance of natural barriers for the confirmation of repository sites.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.49-56
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• 2023

Impact based forecast refers to providing information on potential socioeconomic risks according to weather conditions, away from the existing weather factor-oriented forecast. Developed weather countries are investing manpower and finances in technology development to provide and spread impact information, but awareness of impact based forecasts has not spread in Korea. In addition, the focus is on disasters such as floods and typhoons, which cause a lot of damage to impact based forecasts, and research on evaluating the impact of vehicle risks due to strong winds in the transportation sector with relatively low damage is insufficient. In Korea, there are not many cases of damage to vehicle conduction caused by strong winds, but there are cases of damage and the need for research is increasing. Road vulnerability is required to evaluate the risk of vehicles caused by strong winds, and the purpose of this study was to calculate the criteria for road vulnerability. The road vulnerability evaluation was evaluated by the altitude of the road, the number of lanes, the type of road. As a result of the analysis, it was found that the vulnerable area was well reproduced. It is judged that the results of this study can be used as a criterion for preparing an objective evaluation of potential risks for vehicle drivers.

• Genomics & Informatics
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• v.21 no.3
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• pp.33.1-33.11
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• 2023

Type 2 diabetes mellitus (T2DM) is a multifactorial, polygenic, and metabolically complicated disease. A large number of genes are responsible for the biogenesis of T2DM and calpain10 (CAPN10) is one of them. The association of numerous CAPN10 genetic polymorphisms in the development of T2DM has been widely studied in different populations and noticed inconclusive results. The present study is an attempt to evaluate the plausible association of CAPN10 polymorphism SNP-19 (rs3842570) with T2DM and T2DM-related anthropometric and metabolic traits in the Noakhali region of Bangladesh. This case-control study included 202 T2DM patients and 75 healthy individuals from different places in Noakhali. A significant association (p < 0.05) of SNP-19 with T2DM in co-dominant 2R/3R vs. 3R/3R (odds ratio [OR], 2.7; p=0.0014) and dominant (2R/3R) + (2R/2R) vs. 3R/3R (OR, 2.47; p=0.0011) genetic models was observed. High-risk allele 2R also showed a significant association with T2DM in the allelic model (OR, 1.67; p=0.0109). The genotypic frequency of SNP-19 variants showed consistency with Hardy-Weinberg equilibrium (p > 0.05). Additionally, SNP-19 genetic variants showed potential associations with the anthropometric and metabolic traits of T2DM patients in terms of body mass index, systolic blood pressure, diastolic blood pressure, total cholesterol, and triglycerides. Our approach identifies the 2R/3R genotype of SNP-19 as a significant risk factor for biogenesis of T2DM in the Noakhali population. Furthermore, a large-scale study could be instrumental to correlate this finding in overall Bangladeshi population.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.727-737
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• 2022

This study was conducted to identify the factors Influencing the burnout of general hospital nurses. Method: The study subjects were 150 nurses in three general hospital. The collected data were analyzed by t-test, ANOVA, Scheffe's test, Pearson's correlation coefficient, and Multiple regression analysis. Results: The factors affecting the burnout of the subjects, multiple regression analysis results showed that emotional intelligence(β=-.441, p<.001), emotional labor(β=.403, p<.001), current position was more than responsible nurse(β=-.111, p<.018), and health status was healthy(β=-.100, p<.029). In addition, the F statistics for the fitness of the estimated regression model were 35.51(p<.001), which was very significant. The explanatory power was 79.7%. Conclusion: The results of this study showed that emotional intelligence of the general hospital nurse was the most influential factor on burnout, and the higher the position, the better the health status, the lower the emotional labor, the lower the burnout. Therefore, the results of this study suggest that it is necessary to find ways to reduce emotional labor and improve health and emotional intelligence in order to reduce burnout of nurses, and it is considered to be useful as basic data for developing intervention programs to lower burnout.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.434-440
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• 2022

The ICAO (International civil aviation organization)recommended the implementation of the GANP (global air navigation plan) for strategic decision-making and air traffic management evaluation. In this study, we proposed a new method for finding the route distance from KPI (key performance indicator) 05 actual route extension presented for air traffic management evaluation. For this purpose, we collected trajectory data for one month and calculated the en-route distances using the methods presented in ICAO and the methods presented by this author. In the ICAO method, the intersection point must be estimated through the equation of a circle for radius 40 NM and the equation of a straight line for an inner and outer point close to a circle in the track data, and four flight distances are calculated to calculate the en-route distance. In the method presented in this study, two flight distances are calculated without estimating the intersection point to calculate the en-route distance. To determine the error between the two methods, we used the performance evaluation index RMSE (root mean square error) and the determination factor R² of the regression model.

• Analyses & Alternatives
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• v.7 no.3
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• pp.115-144
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• 2023

Under the Trump administration, the U.S. has made clear that "China is America's strategic competitor, revisionist power and a major challenge to America's prosperity and security." The Biden administration has largely inherited this perception of China. China has also responded without backing down. Therefore, the U.S.-China strategic competition has become the most important background factor in the international system and has a great impact on the security situation in Northeast Asia. Nevertheless, if you look at the recent process of establishing trilateral security cooperation among ROK, the U.S. and Japan, we can find that ROK's foreign strategy adjustment has played a key role. This is because establishing trilateral security cooperation among ROK, the U.S. and Japan depends on improving ROK-Japan relations. And the Yoon Suk Yeol government is pushing for rapid improvement in ROK-Japan relations regardless of domestic political constraints. The trilateral summit at Camp David laid the groundwork for future cooperation among ROK, the U.S. and Japan in security and other broader areas. China is strongly dissatisfied with the formation of trilateral security cooperation among ROK, the U.S. and Japan. However, this paper argues that although ROK agrees to form trilateral security cooperation with the U.S. and Japan, ROK's strategic objectives are not exactly the same as those of the U.S. and Japan. For example, looking back at the development of the U.S.-Japan alliance after the end of the Cold War, both the U.S. and Japan share similar views and perceptions of China's rise. The real goal of the strengthening of the U.S.-Japan alliance in recent years is also how to cope with China's rise. On the other hand, ROK's previous administrations have been negative about trilateral security cooperation with the U.S. and Japan. This is because ROK's main strategic goal is to reduce or eliminate threats from DPRK rather than respond to China. Faced with increasing DPRK's provocations and threats, more than half of South Koreans are in favor of reinforcing trilateral security cooperation with the U.S. and Japan to contain or mitigate threats from DPRK. As a result, if North Korea's nuclear and missile threats to ROK continue, then ROK's foreign strategy is likely to be to strengthen trilateral security cooperation between the U.S. and Japan to ensure its own safety and survival. If China wants to reduce the strategic pressure from the trilateral security cooperation among ROK, the U.S. and Japan, the best way is to reduce DPRK's provocations and threats to ROK and play a more substantive role in getting DPRK to give up its nuclear program.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.127-135
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• 2023

With the development of information and communication technology, the amount of information produced and shared in the battlefield and stored and managed in the system dramatically increased. This means that the amount of information which cansupport situational awareness and decision making of the commanders has increased, but on the other hand, it is also a factor that hinders rapid decision making by increasing the information overload on the commanders. To overcome this limitation, this study proposes a method to automatically search, select, and summarize documents that can help the commanders to understand the battlefield situation reports that he or she received. First, named entities are discovered from the battlefield situation report using a named entity recognition method. Second, the documents related to each named entity are discovered. Third, a language model and collaborative filtering are used to select the documents. At this time, the language model is used to calculate the similarity between the received report and the discovered documents, and collaborative filtering is used to reflect the commander's document reading history. Finally, sentences containing each named entity are selected from the documents and sorted. The experiment was carried out using academic papers since their characteristics are similar to military documents, and the validity of the proposed method was verified.