• Journal of the Korean Magnetics Society
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• v.23 no.3
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• pp.110-116
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• 2013

This paper proposes a sampling-based sensitivity method for dealing with electromagnetic coupled design problems effectively. The black-box modeling technique is basically applied to obtain an optimum regardless of how strong the electromagnetic, thermal and structural analyses are coupled with each other. To achieve this, Kriging surrogate models are produced in a hyper-cubic local window with the center of a current design point. Then design sensitivity values are extracted from the differentiation of basis functions which consist of the models. The proposed method falls under a hybrid optimization method which takes advantages of the sampling-based and the sensitivity-based methods. Owing to the aforementioned feature, the method can be applied even to electromagnetic problems of which the material properties are strongly coupled with thermal or structural outputs. To examine the accuracy and validity of the proposed method, a strongly nonlinear mathematical example and a coil design problem for local induction heating are tested.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.479-485
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• 2007

In this paper, a hierarchical simulation with an approximate implicit method is proposed in order to efficiently and plausibly animate mass-spring based cloth models. The proposed hierarchical simulation method can generate realistic motion of extremely fine mesh in interactive rate. The proposed technique employs a fast and stable simulation method which approximates the implicit integration. Although the approximate method is efficient, it is extremely inaccurate and shows excessively damped behavior. The hierarchical simulation technique proposed in this paper constructs multi-level mesh structure in order to represent the realistic appearance of cloth model and performs simulation on each level of the mesh with constraints that enforce some of the mass-points of current level to follow the movement of the previous level. This hierarchical method efficiently generates a plausible movement of a cloth model composed of large number of mass points. Moreover, this hierarchical method enables us to generate realistic wrinkles on the cloth, and the wrinkle pattern on the cloth model can be easily controlled because we can specify different contraction resistance force of springs according to their hierarchical level.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.88-102
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• 2006

In multimedia information retrieval, multimedia data are represented as vectors in high dimensional space. To search these vectors effectively, a variety of indexing methods have been proposed. However, the performance of these indexing methods degrades dramatically with increasing dimensionality, which is known as the dimensionality curse. To resolve the dimensionality curse, dimensionality reduction methods have been proposed. They map feature vectors in high dimensional space into the ones in low dimensional space before indexing the data. This paper proposes a method for dimensionality reduction based on a function approximating the Euclidean distance, which makes use of the norm and angle components of a vector. First, we identify the causes of the errors in angle estimation for approximating the Euclidean distance, and discuss basic directions to reduce those errors. Then, we propose a novel method for dimensionality reduction that composes a set of subvectors from a feature vector and maintains only the norm and the estimated angle for every subvector. The selection of a good reference vector is important for accurate estimation of the angle component. We present criteria for being a good reference vector, and propose a method that chooses a good reference vector by using Levenberg-Marquardt algorithm. Also, we define a novel distance function, and formally prove that the distance function lower-bounds the Euclidean distance. This implies that our approach does not incur any false dismissals in reducing the dimensionality effectively. Finally, we verify the superiority of the proposed method via performance evaluation with extensive experiments.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.36-43
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• 2001

• The Journal of the Acoustical Society of Korea
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• v.33 no.4
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• pp.232-237
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• 2014

A passive sonar of warship is composed of several directional or omni-directional sensors. In order to model the acoustic signal received into a warship sonar, the wave propagation modeling is usually required from arbitrary noise source to all sensors equipped to the sonar. However, the full calculation for all sensors is time-consuming and the performance of sonar simulator deteriorates. In this study, we suggest an asymptotic method to estimate the sonar signal arrived to sensors adjacent to the reference sensor, where it is assumed that all information of eigenrays is known. This method is developed using Taylor series for the time delay of eigenray and similar to Fraunhofer and Fresnel approximation for sonar aperture. To validate the proposed method, some numerical experiments are performed for the passive sonar. The approximation when the second-order term is kept is vastly superior. In addition, the error criterion for each approximation is provided with a practical example.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.219-228
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• 2004

Confidence interval estimators for proportions using normal approximation have been commonly used for coverage analysis of simulation output even though alternative approximate estimators of confidence intervals for proportions were proposed. This is -because the normal approximation was easier to use in practice than the other approximate estimators. Computing technology has no problem with dealing these alternative estimators. Recently, one of the approximation methods for coverage analysis which is based on arcsin transformation has been used for estimating proportion and for controlling the required precision in [12]. In this paper, we compare three approximate interval estimators, based on a normal distribution approximation, an arcsin transformation and an F-distribution approximation, of a single proportion. Three estimators were applied to sequential coverage analysis of steady-state means, in simulations of the M/M/1/$\infty$ and W/D/l/$\infty$ queueing systems on a single processor and multiple processors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.17-27
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• 2014

As the importance of Cooperative Engagement Capability and network-centric warfare has been dramatically increasing, it is necessary to develop distributed tracking systems. Under the development of distributed tracking systems, it requires tracking filters and data fusion theory for nonlinear systems. Therefore, in this paper, the problem of nonlinear track fusion, which is suitable for distributed networks, is formulated, four algorithms to solve the problem of nonlinear track fusion are introduced, and performance of introduced algorithms are analyzed. It is a main problem of nonlinear track fusion that cross-covarinaces among multiple platforms are unknown. Thus, in order to solve the problem, two techniques are introduced; a simplification technique and a approximation technique. The simplification technique that help to ignore cross-covariances includes two algorithms, i.e. the sample mean algorithm and the Millman formula algorithm, and the approximation technique to obtain approximated cross-covariances utilizes two approaches, by using analytical linearization and statistical linearization based on the sigma point approach. In simulations, BCS fusion is the most efficient scheme because it reduces RMSE by approximating cross-covariances with low complexity.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.742-746
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• 2010

In this paper, we propose new randomness testing methods based on approximate periods in order to improve the previous randomness testing method using exact pattern matching. Finding approximate periods of random sequences enables us to search similarly repeated parts, but it has disadvantages since it takes long time. In this paper we propose randomness testing methods whose time complexity is O($n^2$) by reducing the time complexity of computing approximate periods from O($n^3$) to O($n^2$). Moreover, we perform some experiments to compare pseudo random number generated by AES cryptographic algorithms and true random number.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.118-123
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• 2008

This paper proposes a frequency transfer function synthesis for approximating a high-order model with resonance to a low-order model in the frequency domain. The presented model approximation method is based on minimizing the error function weighted by the numerator polynomial of approximated models, which is used of the RLS(Recursive Least Square) technique to estimate the coefficient vector of approximated models. The proposed method provides better fitting in a low frequency and peak resonance. And an example is given to illustrate feasibilities of the suggested schemes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.375-381
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• 2023

Fully homomorphic encryption enables algebraic operations on encrypted data, and recently, methods for approximating non-algebraic operations such as the maximum function have been studied. However, precise approximation of max-pooling operations for four or more numbers have not been researched yet. In this study, we propose a precise max-pooling approximation method using the composition of approximate polynomials of the maximum function and theoretically analyze its precision. Experimental results show that the proposed approximate max-pooling has a small amortized runtime of less than 1ms and high precision that matches the theoretical analysis.