• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.81-92
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• 2022

In this study, interview scripts written in the dropout application was analyzed using BERTopic,, and parental influence, academic adaptation, university dissatisfaction was derived as major topics. An empirical study was conducted through a survey of 199 current students with researchmodel composed of those factors affecting dropout intention. The result shows that parental influence had a negative effect on academic adaptation and university satisfaction. Academic adaptation and university satisfaction had a negative effect on the dropout intention. parental influence did not directly affect the dropout intention, but had an indirect positive effect through academic adaptation and university/major satisfaction. The result shows that university satisfaction and academic adaptation is important factor to lower the dropout intention of students who chose current university by parental influence.

• Journal of Adhesion and Interface
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• v.23 no.3
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• pp.75-79
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• 2022

Graphene is a two-dimensional carbon allotrope composed of honeycomb sp² hybrid orbital bonds. It shows excellent electrical and mechanical properties and has been spotlighted as a core material for next-generation electronic devices. However, it exhibits low environmental stability due to the easy penetration or adsorption of external impurities from the formation of an unstable interface between the materials in the electronic devices. Therefore, this work aims to improve and investigate the low environmental stability of graphene-based field-effect transistors through direct growth using solid hydrocarbons as a precursor of graphene. Graphene synthesized from direct growth shows high electrical stability through reduction of change in charge mobility and Dirac voltage. Through this, a new approach to utilize graphene as a core material for next-generation electronic devices is presented.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.213-224
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• 2022

This study aims to propose the directions of design strategies and product development by analyzing the style types and design features of sneakers using the knitted upper which has been rapidly increasing due to merits in a variety of aspects including goods, production and marketing aspects. To this end, this study analyzed total 924 style types which had been gaining popularity in online markets and brand products drawing attention in the sneaker market with the knitted upper and their design features. In accordance with the analysis results, uniqueness was identified as the first merit. The unique hybrid style and design of sneakers with the knitted upper have been established without complying with the conventional materials and production techniques. The next merit was multimodality. The sneakers with the knitted upper create multiple images highlighting each feature of colors and materials by mixing those elements in various ways. The third merit was experimentality. The sneakers with the knitted upper have been attempted decisive change of designs by combining more engineering approach and new materials and techniques than existing sneakers. In these days when the sneaker market has been gradually expanded, the analysis results of this study reflecting the industrial trends will provide the fundamental data for a variety of research activities related to shoes and for the direction of brand planning in the relevant industries.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.3
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• pp.211-216
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• 2022

Steganography technology protects the existence of hidden information by embedding a secret message in a specific location on the cover medium. Security and resistance are strengthened by applying various hybrid methods based on encryption and steganography. In particular, techniques to increase chaos and randomness are needed to improve security. In fact, the case where the shuffling method is applied based on the discrete cosine transform(DCT) and the least significant bit(LSB) is an area that needs to be studied. I propose a new approach to hide the bit information of Hangul messages by integrating the selective shuffling method that can add the complexity of message hiding and applying the spatial domain technique to steganography. Inverse shuffling is applied when extracting messages. In this paper, the Hangul message to be inserted is decomposed into the choseong, jungseong and jongseong. It improves security and chaos by applying a selective shuffling process based on the corresponding information. The correlation coefficient and PSNR were used to confirm the performance of the proposed method. It was confirmed that the PSNR value of the proposed method was appropriate when compared with the reference value.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.37-44
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• 2022

Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.70-70
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• 2023

강우 발생 중 용담댐 상류로부터 용담댐으로 유입되는 유입량을 정확하게 예측하는 것은 하류 지역의 홍수 피해를 최소화하기 위한 댐의 적절한 운영에 필수적이다. 물리 기반 강우-유출 시뮬레이션 모형은 물리적 과정의 이해를 바탕으로 홍수 예측 분야에 광범위하게 사용되고 있다. 그러나 복잡한 물리 과정을 완벽히 이해하는 것은 거의 불가능하므로 다양한 가정 조건들을 이용해 복잡한 과정을 단순화하여 계산해야 하는 한계가 존재한다. 최근에는 방대한 데이터의 축적과 컴퓨터 능력의 향상으로 인해 데이터 기반 모형이 다양한 실무 문제를 해결하는 데 강력한 도구로 활용되고 있을 뿐 아니라 시뮬레이션 및 예측 등에도 다양하게 이용되고 있다. 그러나 예측 시간이 늘어날수록 입력자료로 이용되는 과거 자료와 출력자료로 이용되는 미래자료와의 상관관계가 줄어들어 모형의 성능이 저하된다. 따라서 본 연구에서는 용담댐의 시간당 유입량을 예측하기 위해 물리 기반 강우-유출 모형과 오차 보정 모형을 결합한 하이브리드 접근 방식을 제안한다. 물리 기반 강우-유출 모형으로는 HEC-HMS 모형을 사용하였으며, 오차 보정 모형에는 기계학습 모형인 인공신경망(Artificial Neural Network, ANN) 모형을 사용하였다. HEC-HMS 모형, ANN 및 하이브리드 모형(HEC-HMS + ANN)의 성능을 비교하기 위해 20 개의 홍수 사상을 모형 구축 및 검증에 사용하였다. 그 결과 하이브리드 모형은 예측 시간이 늘어날수록 HEC-HMS 및 ANN 모형보다 우수한 성능을 나타냈다. 물리모형에 기계학습을 이용한 오차 보정 절차를 통합한 경우 홍수 유출 예측의 정확성이 향상되었다. 다양한 모형의 비교 결과 본 연구에서 적용한 하이브리드 모형이 물리기반 강우-유출 모형 및 순수 기계학습 모형보다 우수한 성능을 보여줌으로써, 하이브리드 모형은 물리모형과 순수 기계학습 모형의 단점들을 보완하는데 이용할 수 있음을 나타낸다. 이 연구의 주요 목적은 강우-유출 시물레이션 모형의 오차 보정 기술에 대한 더 깊은 이해를 제공하는데 있다.

• Wind and Structures
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• v.35 no.4
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• pp.269-285
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• 2022

The pressure-mitigating effects of a high-speed train passing through a tunnel with a partially reduced cross-section are investigated via the numerical approach. A compressible, three-dimensional RNG k-ε turbulence model and a hybrid mesh strategy are adopted to reproduce that event, which is validated by the moving model test. Three step-like tunnel forms and two additional transitions at the tunnel junction are proposed and their aerodynamic performance is compared and scrutinized with a constant cross-sectional tunnel as the benchmark. The results show that the tunnel step is unrelated to the pressure mitigation effects since the case of a double-step tunnel has no advantage in comparison to a single-step tunnel, but the excavated volume is an essential matter. The pressure peaks are reduced at different levels along with the increase of the excavated earth volume and the peaks are either fitted with power or logarithmic function relationships. In addition, the Arc and Oblique-transitions have very limited gaps, and their pressure curves are identical to each other, whereas the Rec-transition leads to relatively lower pressure peaks in C_Pmax, C_Pmin, and ΔC_P, with 5.2%, 4.0%, and 4.1% relieved compared with Oblique-transition. This study could provide guidance for the design of the novel railway tunnel.

• Journal of Korea Trade
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• v.26 no.3
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• pp.23-44
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• 2022

Purpose - Recent issues such as vessel enlargement, strengthening of environmental regulations, and port smartization are expected to increase costs and intensify competition in the port industry. In the new normal era, when external growth has reached its limit, the efficient operation of ports is becoming indispensable for achieving sustainable growth. This study aims to identify the determinants of inefficiency by examining the cost structure and efficiency of container terminals in Korea and furthermore propose the political implications to derive the maximization of efficiency. Design/methodology - This study estimates the cost function of container terminal operators and identifies the efficiency of container terminals using stochastic cost frontier (SCF) in the first stage. In the second step, the SCF results are compared with the data envelopment analysis (DEA). Last, this paper proposes efficiency determinants on container terminal operation to establish appropriate strategies. Out of the 29 container terminal operators in South Korea, 13 operators participated in the survey. The translog cost function was estimated utilizing a total of 116 observations collected over the 2007-2017 period. Findings - Empirical analysis shows that economies of scale exist in Korea's container ports, which provides a rationale for the government's policy to establish the global terminal operator by integrating small terminal operators to enhance competitiveness. In addition, as a result of the determinants analysis, container throughput, weight of direct employment costs, and labour cost share have positive effects on improving cost efficiency, while inefficiency increases as the length of quay increases. More specifically, cost efficiency improves as the proportion of direct employment costs to outsourcing service costs increases. Originality/value - This study contributes to analyzing the inefficiency factors of container terminals through efficiency analysis with respect to a cost function. In addition, this study proposes the practical and political implications, such as establishing a long-term manpower pool, the application of the hybrid liner terminal system, and the construction of a statistical data system, to improve the cost inefficiency of terminal operators.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.2
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• pp.155-168
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• 2023

Health geography has gained importance due to healthy smart cities, regions, and the integration of geo-internet and blockchain technologies. This study explores the intersection of geography and health, focusing on specific health challenges faced by individuals and groups. Using observational and descriptive methods, the study takes a regional approach to illuminate the socio-economic factors that are critical to addressing global health challenges. Drawing on academic literature and practical research, a concise case study of health challenges in Uzbekistan is presented, offering valuable insights. The analysis of data from informative articles and UN publications highlights the interdisciplinary nature of health geography and its practical applicability for researchers and policymakers. The findings underscore the important role of geography and health sciences in addressing region-specific diseases while highlighting the importance of spatial analysis in understanding environmental hazards and health impacts, including disease outbreaks.