• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.202-210
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• 2017

For the target tracking in cluttered environment using a bistatic sonar whose transmitter and receiver are separately positioned, it is necessary to use data association algorithm via applying a proper measurement modelling to the bistatic sonar. The measurements obtained from the interval of ownship's maneuver have an increased error due to uncertainty of the position of transmitter and receiver. Using the measurements from this interval results in poor target tracking performance. In this paper, an improved tracking performance for the proposed data association based multiple model algorithm is validated by a monte carlo simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.225-237
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• 2021

The current study aims to classify what determines entrepreneurial leadership among small and medium enterprises (SMEs) in the Saudi Arabian context. It also attempted to recognize the role played by entrepreneurial leadership by supporting SMEs in the nation's sustainable economic growth. The study is based on a primary survey administered among SMEs in the Riyadh region of Saudi Arabia. Overall, 152 responses were collected. However, after data cleaning, only 107 were found to be fit for final analysis. Structural Equation Modelling using SmartPLS® Software was applied for analysis. The findings emerged from the study immensely concluded that entrepreneurial leadership is an essential instrument for managers/owners of the SMEs sector who aim to improve the efficiency of tasks and contextual performance in Saudi Arabia. The study came across that "ability to absorb uncertainty," "ability to build commitment," "the ability to frame the Challenge," "the ability of path-clearing," and "ability to specify limits," are the five constructs that help frame the entrepreneurial leadership in the Saudi context. The study suggests that leadership trainers, SME policymakers must focus on precisely these skills to inculcate the ability of entrepreneurial leadership among Saudi entrepreneurs, SMEs owners, and managers.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.608-616
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• 2015

In this study, we have estimated the storm surge heights using numerical modeling on coastal area, and then evaluated the vulnerability index by applying the vulnerability assessment techniques. Surge modelling for 27 typhoons affected from 2000 to 2014 were simulated by applying the ADCIRC model. The results of validation and verification was in significant agreement as compared with observations for the top 6 ranking typhoons affected. As results, the storm surge heights in Jinhae Bay, Sacheon Bay, Gwangyang Bay, Cheonsu Bay and Gyeonggi Bay were higher than other inner coastal areas, then storm surge vulnerability assessment was performed using a standardization, normalization and gradation of storm surge heights. According to results of storm surge vulnerability assessment, index of Jinhae Bay, Sacheon Bay, Gwangyang Bay etc. are estimated to be vulnerable(4~5) because of the characteristics of storm surge such as inner bay are vulnerable compared with exposed to the open sea areas. However, index in the inner bay of western Jeonnam are not vulnerable(1~3) relatively. It may not appear the typhoons affected significantly for the past 15 years. So, the long-term vulnerability assessment with the sensitivity of geomorphology are necessary to reduce the uncertainty.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.4
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• pp.246-257
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• 2015

The progressive degradation paths of structures have quantitatively been tracked by using stochastic processes, such as Wiener process, gamma process and compound Poisson process, in order to consider both the sampling uncertainty due to the usual lack of damage data and the temporal uncertainty associated with the deterioration evolution. Several important features of stochastic processes which should carefully be considered in application of the stochastic processes to practical problems have been figured out through assessing cumulative damage and lifetime distribution as a function of time. Especially, the Wiener process and the gamma process have straightforwardly been applied to armors of rubble-mound breakwaters by the aid of a sample path method based on Melby's formula which can estimate cumulative damage levels of armors over time. The sample path method have been developed to calibrate the related-parameters required in the stochastic modelling of armors of rubble-mound breakwaters. From the analyses, it is found that cumulative damage levels of armors have surely been saturated with time. Also, the exponent of power law in time, that plays a significant role in predicting the cumulative damage levels over time, can easily be determined, which makes the stochastic models possible to track the cumulative damage levels of armors of rubble-mound breakwaters over time. Finally, failure probabilities with respect to various critical limits have been analyzed throughout its anticipated service life.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.51-64
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• 2002

Observational results of ground movement during the construction were very different from those predicted during the analysis of design step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc., however accurately numerical analysis method was applied for prediction of ground movement per the excavation step. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until now, the measurement system restricted by 'Absolute Value Management system'analyzing only the stability of present step has been executed. So, it was difficult to expect the prediction of ground movement fur the next excavation step. In this situation, this study developed 'The Management system TOMAS-EXCAV'consisted of 'Absolute value management system'analyzing the stability of present step and 'Prediction management system'expecting the ground movement of next excavation step and analyzing the stability of next excavation step by 'Back Analysis'. TOMAS-EXCAV could be applied to all the uncertainty of earth retaining structures analysis by connecting 'Forward analysis program'and 'Back analysis program'and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The applicability of TOMAS-EXCAV was confirmed by back analysis selecting two earth retains construction fields.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.11
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• pp.763-768
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• 2013

The simulation investigation on the availability with failure density function of major equipment for a sewage treatment plant has been carried out. This study focuses on the availability of the plant and criticality with equipment module induced by component layout and its failure function. The equipment classification of sewage treatment plant and its failure function are established. Also solution methodologies are introduced as Monte-Carlo simulation method and event algorithm for uncertainty problem. The availability in the case of serial connection of equipment with all exponential function is calculated as around 50.4%. In other case of parallel combination with back up equipment, the availability showed over 80.1%. The criticality that a ffects availability showed high value over 77% in the dehydration and concentration process of sludge.

• Journal of Korea Port Economic Association
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• v.34 no.1
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• pp.99-110
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• 2018

This study empirically examines simple methodology to quantify the risk resulted from the uncertainty of bunker price and foreign exchange rate, which cause main resources of the cost in shipping industry during the periods between $1^{st}$ of January 2010 and $31^{st}$ of January 2018. To shed light on the risk measurement in cash flows we tested GBM(Geometric Brownian Motion) frameworks such as the model with conditional heteroskedasticity and jump diffusion process. The main contribution based on empirical results are summarized as following three: first, the risk analysis, which is dependent on a single variable such as freight yield, is extended to analyze the effects of multiple factors such as bunker price and exchange rate return volatility. Second, at the individual firm level, the need for risk management in bunker price and exchange rate is presented as cash flow. Finally, based on the scale of the risk presented by the analysis results, the shipping companies are required that there is a need to consider what is appropriate as a means of risk management.