• Smart Structures and Systems
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• 제17권6호
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

• 전력전자학회논문지
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• 제22권2호
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• pp.159-165
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• 2017

Small-signal modeling and controller design methodology are proposed to improve the dynamics and stability of a DC-DC dual active bridge (DAB) converter. The state-space average method has a limitation when applied to the DAB converter because its state variables are nonlinear and have zero average values in a switching period. Therefore, the small-signal model and the frequency response of the DAB converter are derived and analyzed using a generalized average method instead of conventional modeling methods. The design methodology of a lead-lag controller instead of the conventional proportional-integral controller is also proposed using the derived small-signal model. The accuracy and performance of the proposed small-signal model and controller are verified by simulation and experimental results with a 500 W prototype DAB converter.

• 동아시아경상학회지
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• 제9권4호
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• pp.17-28
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• 2021

Purpose - This article aims to explore the mechanism in which environmental regulations have positive effects on corporate competitiveness through technological innovation. This study also attempts to examine the relationship between environmental regulation and corporate competitiveness from a technological innovation perspective and explore a desirable relationship between those two. Research design, data, and methodology - Discourse analysis and SWOT analysis is used in terms of methodology, and this study is based on literature review theoretically. The methodology is employed in various ways to describe a variety of environmental issues. Result - The results support that technological innovation is able to play a role in coordinating relationship between environmental regulations and corporate competitiveness. The uncertainty and time lag problems innate to technological innovation function as disturbing factors for individual companies to actively increase R&D investment in response to environmental regulations. Environmental regulations may be considered to be working as a factor consolidating corporate competitiveness through technological innovation to respond to the environmental regulations including climate change issue. Conclusion - This study proposes that to achieve two goals of environmental protection and corporate competitiveness consolidation, policy support from various aspects is implied to be required. This implies that environmental regulations and technical innovation must be harmoniously balanced for future corporate success.

• Journal of Astronomy and Space Sciences
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• 제36권3호
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• pp.149-157
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• 2019

In this study, we investigate the associations between the solar variability and teleconnection indices, which influence atmospheric circulation and subsequently, the spatial distribution of the global pressure system. A study of the link between the Sun and a large-scale mode of climate variability, which may indirectly affect the Earth's climate and weather, is crucial because the feedbacks of solar variability to an autogenic or internal process should be considered with due care. We have calculated the normalized cross-correlations of the total sunspot area, the total sunspot number, and the solar North-South asymmetry with teleconnection indices. We have found that the Southern Oscillation Index (SOI) index is anti-correlated with both solar activity and the solar North-South asymmetry, with a ~3-year lag. This finding not only agrees with the fact that El $Ni{\tilde{n}}o$ episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El $Ni{\tilde{n}}o$ periods appear similar. Conversely, other teleconnection indices, such as the Arctic Oscillation (AO) index, the Antarctic Oscillation (AAO) index, and the Pacific-North American (PNA) index, are weakly or only slightly correlated with solar activity, which emphasizes that response of terrestrial climate and weather to solar variability are local in space. It is also found that correlations between teleconnection indices and solar activity are as good as correlations resulting from the teleconnection indices themselves.

• 한국기계가공학회지
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• 제19권11호
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• pp.49-57
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• 2020

The forced vibration characteristics for two impulse forces with time lag was discussed in the vehicle dull progress model. Detailed numerical analyses of the time domain were performed systematically. By the two exciting impulse forces, the responses of displacement, the velocity, and the acceleration were investigated in detail for the vehicle's vibration. Notably, the forced vibration responses in the time domain can be used to identify and monitor several vehicle vibration models. In order to define the responses of displacement, the velocity, and the acceleration, we applied a numerical technique (i.e., the Runge-Kutta-Gill method[1,2]). These variables were subsequently used to analyze the vehicle's vibration according to the time lapse and while it passed over a bump stock; moreover, the characteristics of the variables were analyzed in detail according to their force conditions. Finally, the intrinsic characteristics of the forced vibration were discussed in the context of the automobile model. Overall, our results indicate that the tested method can be successfully applied under different damped conditions.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.625-633
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• 2021

Bangladesh's growing foreign aid has sparked controversy over whether it affects the country's economic performance. This review assesses foreign aid's influence on the country's economic growth with annual data covering the 1989-2018 period. The Autoregressive Distributed Lag (ARDL) model is applied to achieve the research objective, and the empirical results indicate a substantial and robust impact of foreign assistance on economic growth. The outcome further reveal that domestic investment also contributes significantly to the country's economic evolution. However, trade openness plays a substantial positive role in the short run, although the impact is immaterial in the long run. The empirical findings indicate that the association between aid, domestic investment, and growth has a confident meaningful effect at 1 per cent level in the long run, whereas aid influences more than domestic investment. However, in the short run, aid, domestic investment, trade openness, and growth show positive and noteworthy response also at 1 percent level. This review undertakes a detailed analysis about the country's economic growth, and grounded on its outcome, this work suggests that focus should be placed more on creating domestic investment, promoting more export, and allocation of aid should be determined by the relative needs of the country.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.181-190
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• 2021

This paper empirically examines the asymmetric response of the Indonesian Islamic stock market to macroeconomic variables encompassing money supply, domestic output, exchange rate, and Federal Reserve rate. Our study employs the Jakarta Islamic Index (JII) after the financial crisis in the Southeast Asian country using monthly data from January 2000 to December 2019. Non-linear Autoregressive Distributed lag (NARDL) is applied. Our study considers two models consisting of the model without the Federal Reserve rate and the model with it. Our findings confirm the long-run link between Jakarta Islamic Index and macroeconomic factors being studied. Furthermore, the Jakarta Islamic Index asymmetrically responds to broad money supply and exchange rate, but not to domestic output and Federal Reserve rate. A reduction in the money supply has a worse effect on Islamic stock prices as compared to an increase in the money supply. The Jakarta Islamic Index responds differently to depreciation and appreciation. The transmission of the exchange rate to Islamic stock prices occurs only for appreciation. Our study finds an absence of transmission mechanism from the domestic output and the interest rate to Islamic stock prices. Our results imply that the easy money policy and stabilizing currency are key to supporting Indonesian Islamic stock prices.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.91-101
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• 2021

The paper examines the impact of the COVID-19 pandemic on the stock market prices. The vector autoregression model (VAR) has been used in this analysis to survey 341 stocks on the Ho Chi Minh City Stock Exchange (HOSE) for the period from January 23, 2020 to December 31, 2020. The empirical results obtained from the analysis of 11 economic sectors suggest that there is a statistically significant impact relationship between COVID-19 and the healthcare and utility industries. Additional findings show a statistically significant negative impact of COVID-19 on the utility share price at lag 1. Analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) show an inverse reaction of utility stock prices to the impact of COVID-19 and a gradual disappearing shock after two steps. Major findings show that there is a clear negative effect of the COVID-19 pandemic on share prices, and the daily increase in the number of confirmed cases, indicate that, in future disease outbreaks, early containment measures and positive responses are necessary conditions for governments and nations to protect stock markets from excessive depreciation. Utility stocks are among the most severely impacted shares on financial exchanges during a pandemic due to the high risk of immediate or irreversible closure of manufacturing lines and poor demand for basic amenities.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.868-871
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• 2021

기후, 경영, 경제 등 여러 분야의 회귀분석에서 설명변수가 반응변수에 일정 시차를 두고 영향을 미치는 경우들이 많다. 하지만 지금까지 대부분의 회귀분석은 설명변수가 반응변수에 즉각적으로 영향을 미치는 경우만을 가정하고 있으며, 설명변수와 반응변수 간에 존재하는 시차를 탐색하는 연구는 거의 이루어지지 않았다. 그러나 보다 정확한 회귀분석을 위해서는 설명변수와 반응변수 간에 존재하는 시차를 파악하는 것이 중요하다. 본 논문은 회귀분석 데이터가 주어졌을 때 설명변수와 반응변수 간에 존재하는 시차를 파악하는 딥러닝 모델을 제안한다. 제안하는 딥러닝 모델은 설명변수의 과거 값들 중 어떤 값이 현재 반응변수에 가장 큰 영향을 미치는지를 노드 간 가중치로 표현하고, 회귀모델의 오차를 최소화하는 가중치를 탐색한다. 훈련이 끝나면 이 가중치들을 사용하여 각 설명변수와 반응변수 간에 존재하는 시차를 파악한다. 실험을 통해 제안 방법은 시차를 고려하지 않는 기존 회귀모델에 비해 시차까지 고려함으로써 오차가 1/100 수준에 불과한 더 정확한 회귀모델을 찾을 수 있음을 확인하였다.

• 한국산학기술학회논문지
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• 제17권7호
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• pp.63-76
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• 2016

R&D 연구 투자의 문제점의 하나는 불확실성이 크다는 점이다. 이러한 불확실성이 기업에는 많은 부담을 주는 요인이 될 수 있다. 이러한 면에서 R&D 투자가 기업 가치에 양(+)의 영향을 미치기까지의 시간을 측정할 수 있는 연구의 필요성이 있다고 보여진다. 본 연구는 GMM-PVAR(Panel Vector Autoregression) IRF(Impulse Response function)를 사용하여 1900년부터 2015년까지 한국거래소의 코스피와 코스닥시장에 상장된 기업을 대상으로 R&D 투자가 기업가치에 양(+)의 영향을 미치기까지 걸리는 시간을 측정 하였다. 또한 기업의 재무적 특성 변수 중 기업의 크기, 성장 가능성, 그리고 산업 집중율이 R&D 투자가 기업가치에 양(+) 영향을 미치기까지 걸리는 시간을 단축시킨다는 점을 발견하였다. 그것은 이들 재무적 특성변수 들이 R&D 투자와 기업가치간의 관계에 긍정적인 영향을 미칠수록 즉 경쟁이 심화될수록 크기가 클수록 시간이 단축되며 작은 기업의 경우는 성장 가능성이 높을수록 시간이 단축되는 경향을 보였다. 흥미 있는 점은 큰 기업들의 경우에는 성장가능성이 낮은 기업들이 성장가능성이 높은 기업들보다 더 큰 양의 결과를 보였다.