• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.908-928
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• 2022

Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.3
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• pp.17-22
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• 2015

This paper examines the effect of impulsiveness of euro on Indian stock market. In order to examine the problem, we select rupee-euro exchange rates and S&P CNX NIFTY and BSE30 SENSEX to represent stock price. We select euro as it considered as second most widely used currency at the international level after dollar. The data are collected a daily basis over a period of 3-Apr-2007 to 30-Mar-2012. The statistical and time series properties of each and every variable have examined using the conventional unit root such as ADF and PP test. Adopting a generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) model, the study suggests a negative relationship between exchange rate and stock prices in India. Even though India is a major trade partner of European Union, the study couldn't find any significant statistical effect of fluctuations in Euro-rupee exchange rates on stock prices. The study also reveals that shocks to exchange rate have symmetric effect on stock prices and exchange rate fluctuations have permanent effects on stock price volatility in India.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.1
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• pp.127-134
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• 1985

On two type regenerator which is represented by their parameters f(t), f(x,t) for generalized regenerating heat exchanger, the temperature distributions are studied analytically in this paper. For f(x,t) regenerator type, particularly, we are able to induce the simplified temperature distribution and convection heat transfer coefficient in heating which apply on condition that regenerator having short transfer period from above theoretical analysis.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.661-671
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• 2017

The objective of this study was to analyze the flood stage considering the uncertainty caused by the river roughness coefficients and discharge. The methodology of this study involved the GLUE (Generalized Likelihood Uncertainty Estimation) to quantify the uncertainty bounds applying three different storm events. The uncertainty range of the roughness was 0.025~0.040. In case of discharge, the uncertainty stemmed from parameters in stage-discharge rating curve, if h represents stage for discharge Q, which can be written as $Q=A(h-B)^C$. Parameters in rating curve (A, B and C) were estimated by non-linear regression model and assumed by t distribution. The range of parameters in rating curve was 5.138~18.442 for A, -0.524~0.104 for B and 2.427~2.924 for C. By sampling 10,000 parameter sets, Monte Carlo simulations were performed. The simulated stage value was represented by 95% confidence interval. In storm event 1~3, the average bound was 0.39 m, 0.83 m and 0.96 m, respectively. The peak bound was 0.52 m, 1.36 m and 1.75 m, respectively. The recurrence year of each storm event applying the frequency analysis was 1-year, 10-year and 25-year, respectively.

• Investigative Magnetic Resonance Imaging
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• v.24 no.3
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• pp.95-122
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• 2020

In this article, we evaluated the performance of radiofrequency (RF) coils in terms of the signal-to-noise ratio (S/N) and homogeneity of magnetic resonance images when used for ultrahigh-frequency (UHF) 7T magnetic resonance imaging (MRI). High-quality MRI can be obtained when these two basic requirements are met. However, because of the dielectric effect, 7T magnetic resonance imaging still produces essentially a non-uniform magnetic flux (|B₁|) density distribution. In general, heterogeneous and homogeneous RF coils may be designed using electromagnetic (EM) modeling. Heterogeneous coils, which are surface coils, are used in consideration of scalability in the |B₁| region with a high S/N as multichannel loop coils rather than selecting a single loop. Loop coils are considered state of the art for their simplicity yet effective |B₁|-field distribution and intensity. In addition, combining multiple loop coils allows phase arrays (PA). PA coils have gained great interest for use in receiving signals because of parallel imaging (PI) techniques, such as sensitivity encoding (SENSE) and generalized autocalibrating partial parallel acquisition (GRAPPA), which drastically reduce the acquisition time. With the introduction of a parallel transmit coil (pTx) system, a form of transceiver loop arrays has also been proposed. In this article, we discussed the applications and proposed designs of loop coils. RF homogeneous coils for volume imaging include Alderman-Grant resonators, birdcage coils, saddle coils, traveling wave coils, transmission line arrays, composite right-/left-handed arrays, and fusion coils. In this article, we also discussed the basic operation, design, and applications of these coils.

• Asian Journal of Business Environment
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• v.10 no.2
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• pp.23-31
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• 2020

Purpose: The purpose of this paper is to find out the impact of financial leverage on firm's profitability in the listed textile sector of Bangladesh. Research design, data and methodology: A sample of 22 DSE listed textile firms has been used to conduct the study. In this study, firm profitability is measured by Return on Equity (ROE) and both short term debt and long term debt are used as the as proxies of financial leverage. Pooled Ordinary Least Squares (OLS), Fixed Effect (FE), and Generalized Method of Moments (GMM) models have been used to test the relationship between financial leverage and profitability of firms. Result: This study finds a significant negative relationship between leverage and firm's profitability using the Pooled OLS method. The result is also consistent with the fixed effect and GMM method. This result implies that firm's profitability is negatively affected by the firm's capital structure. Conclusion: The study concludes that maximum textile firms use external debt as a source of finance as they don't have sufficient internally generated funds. This study recommends that firm should give more emphasize on generating fund internally to meet up their financing needs.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.83-93
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• 2020

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.517-525
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• 2021

The study investigates the behavior of Asian banks in response to the subprime mortgage crisis and examines how countries that have experimented with a mix of conventional and Islamic banking managed their balance sheet during that period. The study carries out an independent mean t-test comparing the difference of leverage of 464 conventional commercial Asian banks pre- and post-crisis from the largest twenty-five Asian economies based on GDP (2007). The analysis uses 10-year unbalanced panel data of conventional banks and employs the generalized least squares estimation using a dummy variable event window method to capture the response of Asian banks. The study finds evidence of a structural change in the capital structure of Asian commercial banks in response to the financial crisis. Findings suggest that conventional banks increased their capital position more in countries that have both Islamic and conventional banking than those countries without Islamic banking services. By having Islamic banking in their product portfolio, countries can exert market discipline on conventional banks. The study identifies a significant role of global macroeconomic shocks on banks liability structure decision-making. Evidence shows that this increase in capital positioning by banks was a permanent rather than a temporary response.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.895-904
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• 2021

This study aims to investigate the impact of innovation on firm efficiency. Panel data of fourteen finance companies and nine technology companies from 2011 to 2019 on the Vietnam Stock Exchange Market is derived from audited financial statements, annual reports, and other crucial reports that are provided by Vietstock; macroeconomic variables are collected from the World Bank Database. A two-stage approach is used. First, use of the Data Envelopment Analysis methodology to measure firm efficiency. Second, use of the Pooled ordinary least squares, the Fixed effects model, and the Random effects model to investigate the impact of innovation on firm efficiency. Furthermore, the Generalized Method of Moments and the Tobit model are used to validate the impact of innovation on firm efficiency, and the t-test is used to confirm the difference in efficiency with and without the impact of innovation between two industries. The results show that there is a significant impact of innovation on efficiency, and innovation plays a more important in increasing the efficiency of the finance industry than the technology industry. Moreover, the relation between age and efficiency is like the U-shaped, and between size and efficiency is like the inverted U-shaped, whereas efficiency is not associated with inflation.