• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.936-946
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• 2009

A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.219-243
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• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.765-771
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• 2019

With the increase in the speed of ships and the size of ocean structures, the importance of flow noise has become increasingly critical in meeting regulatory standards. However, unlike active investigations in aeroacoustics fields for airplanes and trains, which are based on acoustic analogy methods for tonal and broadband frequency noise, only the discrete blade passing frequency noise from propellers is considered in marine fields. In this study, prediction methods for broadband noise in marine propellers and underwater appendages are investigated using FW-H Formulation1B, which can consider the mechanism of primary noise generation of trailing edge noise. The original FW-H Formulation 1B is based on the pressure correlation function tolackitsgeneralityandaccuracy. To overcome these limitations, wall-pressure spectrum models are adopted to improve the generality in fluid mediums. The comparison of the experimental results obtained in air reveals that the proposed model exhibits a higher accuracy within 5 dB. Furthermore, the prediction procedures for broadband noise for hydrofoils are established, and the estimation of broadband noise is conducted based on the results of the computational fluid dynamics.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.223-232
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• 2017

Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.3
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• pp.179-196
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• 1986

In this paper, the peformance of a statistical packet voice/data multiplexer is studied. In ths study we assume that in the packet voice/data multiplexer two separate finite queues are used for voice and data traffics, and that voice traffic gets priority over data. For the performance analysis we divide the output link of the multiplexer into a sequence of time slots. The voice signal is modeled as an (M+1) - state Markov process, M being the packet generation period in slots. As for the data traffic, it is modeled by a simple Poisson process. In our discrete time domain analysis, the queueing behavior of voice traffic is little affected by the data traffic since voice signal has priority over data. Therefore, we first analyze the queueing behavior of voice traffic, and then using the result, we study the queueing behavior of data traffic. For the packet voice multiplexer, both inpur state and voice buffer occupancy are formulated by a two-dimensional Markov chain. For the integrated voice/data multiplexer we use a three-dimensional Markov chain that represents the input voice state and the buffer occupancies of voice and data. With these models, the numerical results for the performance have been obtained by the Gauss-Seidel iteration method. The analytical results have been verified by computer simylation. From the results we have found that there exist tradeoffs among the number of voice users, output link capacity, voic queue size and overflow probability for the voice traffic, and also exist tradeoffs among traffic load, data queue size and oveflow probability for the data traffic. Also, there exists a tradeoff between the performance of voice and data traffics for given inpur traffics and link capacity. In addition, it has been found that the average queueing delay of data traffic is longer than the maximum buffer size, when the gain of time assignment speech interpolation(TASI) is more than two and the number of voice users is small.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.2
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• pp.133-141
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• 2007

The excavation damaged zone (EDZ) is an area around an excavation where in situ rock mass properties, stress condition, displacement, groundwater flow conditions have been altered due to the processes induced by the excavation. Various studies have been carried out on EDZ, but most studies have focused on the mechanical bahavior of EDZ by in situ experiment. Even though the EDZ could potentially form a high permeable pathway of groundwater flow, only a few studies were performed on the analysis of groundwater flow in EDZ. In this study, the 'hydraulic EDZ' was defined as the rock zone adjacent to the excavation where the hydraulic aperture has been changed due to the excavation by using H-M coupling analysis. Fundamental principles of distinct element method (DEM) were used in the analysis. In the same groundwater level, the behavior of hydraulic aperture near the cavern was analyzed for different stress ratios, initial apertures, fracture angles and fracture spacings by using a two-dimensional DEM program. We evaluate the excavation induced hydraulic aperture change. Using the results of the study, hydraulic EDZ was defined as an elliptical shape model perpendicular to the joint.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.835-841
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• 2013

Modern solid-state gyroscopes (HRG) with hemispherical resonators from high-purity quartz glass and special surface superfinishing and ultrathin gold coating become the best instruments for precise-grade inertial reference units (IRU) targeting long-term space missions. Designing of these sensors could be a notable contribution into development of Korea as a space nation. In participial, 40mm diameter thin-shell resonator from high-purity fused quartz, fabricated as a single-piece with its supporting stem has been designed, machined, etched, tuned, tested, and delivered by STM Co. (ATS of Ukraine) several years ago; an extremely-high Q-factor (upto 10~20 millions) has been shown. Understanding of the best way how to match such a unique sensor with inner glass assembly of the gyro means how to use the high potential in a maximal extent; and this has become the urgent task. Inner quartz glass assembly has a very thin indium (In) layer soldered the resonator and its silica base (case), but effects of internal resonances between operational modal pair of the shell-cup and its side (parasitic) modes can notable degrade the potential of the sensor as a whole, instead of so low level of resonator's intrinsic losses. Unfortunately, there are special combinations of dimensions of the parts (so-called, "resonant sizes"), when intensive losses of energy occurs. The authors proposed to use the length of stem's fixture as an additional design parameter to avoid such cases. So-called, a cyclic scheme of finite element method (FEM) and ANSYS software were employed to estimate different combinations of gyro assembly parameters. This variant has no mismatches of numerical origin due to FEM's discrete mesh. The optimum length and dangerous "resonant lengths" have been found. The special attention has been paid to analyses of 3D effects in a cup-stem transient zone, including determination of a difference between the positions of geometrical Pole of the resonant hemisphere and of its "dynamical Pole", i.e., its real zone of oscillation node. Boundary effects between the shell (cup) and 3D short "beams" (inner and outer stems) have been ranged. The results of the numerical experiments have been compared with the classic model of a quasi-hemispherical shell band with inextensional midsurface, and the solution using Rayleigh's functions of the $1^{st}$ and $2^{nd}$ kinds. To guarantee the truth of the recommended sizes to a designer of the real device, the analytical and FEM results have been compared with experimental data for a party of real resonators. The consistency of the results obtained by different means has been shown with errors less than 5%. The results notably differ from the data published earlier by different researchers.