• The Journal of Asian Finance, Economics and Business
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• 제9권6호
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• pp.23-32
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• 2022

This paper examines the effects of regulatory capital on a bank's profitability and risk. We employ annual data from Vietnamese commercial banks from 2005 to 2020 and use the dynamic GMM regression method to address the potential endogeneity issue, more suitable for panel data with relatively low time dimensions. Our panel regressions indicate that higher regulatory capital would significantly improve the bank's profitability and lower the bank risks. In particular, a one percent increase in the regulatory capital would significantly increase the bank's return on assets by 1.9%. We further explore the heterogeneous impacts of regulatory capital on the Vietnamese bank's performance across bank characteristics. We find that smaller, non-state-owned and non-listed banks would benefit from stringent regulatory capital requirements. The improvements in bank performance are mainly driven by reductions in the risk premium of the banks, resulting in lower funding costs and higher profitability. These findings are essential since Vietnam, as an emerging market, has only implemented the Basel II reform recently on a stable and fast-growing background rather than as a reaction to the global financial crisis. Thus, our empirical results support stringent regulatory capital in emerging countries to ensure a stable banking sector and boost economic growth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.813-829
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• 2022

In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.

• Membrane and Water Treatment
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• 제13권3호
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• pp.147-166
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• 2022

Liquid-liquid membrane contactor (LLMC), a device that exchanges dissolved gas molecules between the two sides of a hydrophobic membrane through membrane pores, can be employed to extract ammoniacal nitrogen from a feed solution, which is transported across the membrane and accumulated in a stripping solution. This LLMC process offers the promise of improving the sustainability of the global nitrogen cycle by cost-effectively recovering ammonia from wastewater. Despite recent technological advances in LLMC processes, a comprehensive review of their feasibility for ammonia recovery is rarely found in the literature. Our paper aims to close this knowledge gap, and in addition to analyze the challenges and provide potential solutions for improvement. We begin with discussions on the operational principles of the LLMC process for ammonia recovery and membrane types and membrane configurations commonly used in the process. We then assess the performance of the process by reviewing publications that demonstrate its practical application. Challenges involved in the implementation of the LLMC process, such as membrane fouling, membrane wetting, and chemical requirements, are presented, along with discussions on potential strategies to address each. These strategies, including membrane modification, hybrid process design, and process optimization based on cost-benefit analysis, guide the reader to identify key areas of future research and development.

• 스마트미디어저널
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• 제12권2호
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• pp.15-26
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• 2023

전 세계적인 COVID-19 팬데믹으로 인해 업무처리 방식이 원격으로 전환됨에 따라 기업의 외부에서 내부 중요리소스에 접근하는 빈도가 기하급수적으로 증가하였고 기업은 각종 보안 위협에 쉽게 노출되었다. 이러한 접근 보안 문제를 해결하기 위해 ZTA(Zero Trust Architecture) 솔루션이 주목받고 있다. ZTA는 사전에 설정한 정책에 따라 접근에 대한 인증과 허가를 엄격하게 관리하며 외부 유저는 물론 내부 유저도 신뢰하지 않는다는 원칙을 기반으로 동작한다. 본 논문에서는 ZTA의 정의를 포함해 주요 연구 동향을 분석하였고 각 기업별로 상이한 ZTA 솔루션을 정리하였다.

• 한국건설관리학회논문집
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• 제24권5호
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• pp.83-94
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• 2023

In order to devise a rebar usage optimization algorithm, it is necessary to calculate the exact rebar length and revise the arrangement of rebars into special lengths. However, the process of rearranging numerous rebars and manually calculating their quantities is time-consuming and requires significant human resources. To address this challenge, it is necessary to develop an algorithm that can automatically estimate the length of rebars and calculate their quantities. This study aims to create an automatic estimation algorithm that improves work efficiency while ensuring accurate and reliable calculations of rebar quantities. The algorithm considers various factors such as concrete cover, hook length, development length, and lapping length, mandated by the building codes, to calculate the quantity of rebars for wall structures. The effectiveness of the proposed method is validated by comparing the rebar quantities generated by the algorithm with manually calculated quantities, resulting in a difference rate of 1.14% for the hook case and 1.37% for the U-bar case. The implementation of this method enables fast and precise estimation of rebar quantities, adhering to relevant regulatory codes.

• KDI Journal of Economic Policy
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• 제44권4호
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• pp.43-78
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• 2022

The arena of strategic competition between the US and China is expandable from international politics, trade and commerce to finance. What would happen if financial sanctions against China are imposed by the US? Would US financial sanctions lead to a sudden outflow of foreign capital and a liquidity crisis in China? We try to address these questions by estimating China's capital flows-at-risk with the CDS premium on Chinese sovereign funds. We follow Gelos et al. (2019) in setting up a quantile regression model from which China's foreign capital flow-at-risks are estimated. Based on our analysis of China's monthly capital flow data, we find that a rise in the CDS premium has statistically significant negative impacts on China's foreign capital flows-at-risk, mainly in banking flows. However, the analysis also found that due to favorable global conditions, an increase in the CDS premium is unlikely to trigger a shift to a sudden outflow of foreign capital at the moment. Meanwhile, this study found no statistically significant correlation between Korea's capital flows-at-risk and the CDS premium, suggesting that the negative impact of US financial sanctions on China would not increase the probability of capital flight from Korea in a significant manner.

• Tribology and Lubricants
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• 제39권3호
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.734-735
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• 2015

Currently, effective energy management of buildings is necessary because of accelerated global climate change and resource crisis. Especially, in the case of South Korea, city gas consumption occupies 11.8% of the total energy and 39.6% is residential use among them. Therefore, for reducing the city gas consumption, the effectiveness of residential use is needed. To address this issue, the objective of this study is to analyze the difference of the city gas consumption according to the space arrangement in the apartment building. To achieve this objective, an apartment complex having over 1,000 households was selected then, according to the space arrangement such as south-east and south-west, the data of 59.97m2 and 84.96m2 were analyzed by using statistics method. As a result, in 59.97m2 and 84.96m2, the total city gas amount in 2012 showed that 9.2% and 8.4% were more increased at south-west than southeast respectively. In the future, the findings of this study can be used to develop the prediction model of city gas consumption in apartment building.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.192-194
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• 2015

The growing size and complex process in construction project recently leads to increase risk and the losses as well. Even though researchers have identified the major risk indicators, there is lack of comprehensive and quantitative research for identifying the relationship between the risk indicators and economic losses associated with construction projects. To address this shortage of research, this study defines risk indicators and create a framework to assess the influence of economic losses from the indicators. An insurance company's claim payout record was accepted as the dependent variable to reflect the real economic losses. Based on the claims, we categorized the causes and results of accidents. To establish framework, built environment vulnerability indicators and geographical vulnerability indicators were employed as the risk indicators. A Pearson correlation analysis was adopted to validate the relationship with loss ratio and risk indicators. Consequently, this framework and its results may offer significant references for under writers of insurance companies and loss prevention activities.