• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.172-178
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• 2015

Constructing a bilingual multi-word lexicon is confronted with many difficulties such as an absence of a commonly accepted gold-standard dataset. Besides, in fact, there is no everybody's definition of what a multi-word unit is. In considering these problems, this paper evaluates and analyzes the context vector approach which is one of a novel alignment method of constructing bilingual lexicons from parallel corpora, by comparing with one of general methods. The approach builds context vectors for both source and target single-word units from two parallel corpora. To adapt the approach to multi-word units, we identify all multi-word candidates (namely noun phrases in this work) first, and then concatenate them into single-word units. As a result, therefore, we can use the context vector approach to satisfy our need for multi-word units. In our experimental results, the context vector approach has shown stronger performance over the other approach. The contribution of the paper is analyzing the various types of errors for the experimental results. For the future works, we will study the similarity measure that not only covers a multi-word unit itself but also covers its constituents.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.265-271
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• 1997

A bond graph modeling approach which is equivalent to a finite element method is formulated in the case of the piezoelectric thickness vibrator. This formulation suggests a new definition of the generalized displacements for a continuous system as well as the piezoelectric thickness vibrator. The newly defined coordinates are illustrated to be easily interpreted physically and easily used in analysis of the system performance. Compared to the Mason equivalent circuit model, the bond graph model offers the primary advantage of physical realizability. Compared to circuit models based on standard discrete electrical elements, the main advantage of the bond graph model is a greater physical accuracy because of the use of multiport energic elements. While results are presented here for the thickness vibrator, the modeling method presented is general in scope and can be applied to arbitrary physical systems.

• Advances in Computational Design
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• v.1 no.2
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• pp.175-194
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• 2016

Nature has provided inspiration for most of the man-made technologies. Scientists believe that dolphins are the second to humans in smartness and intelligence. Echolocation is the biological sonar used by dolphins for navigation and hunting in various environments. This ability of dolphins is mimicked in this paper to develop a new optimization method. Dolphin Echolocation Optimization (DEO) is an optimization method based on dolphin's approach for hunting food and exploration of environment. DEO has already been developed for discrete optimization search space and here it is extended to continuous search space. DEO has simple rules and is adjustable for predetermined computational cost. DEO provides the optimum results and leads to alternative optimality curves suitable for the problem. This algorithm has a few parameters and it is applicable to a wide range of problems like other metaheuristic algorithms. In the present work, the efficiency of this approach is demonstrated using standard benchmark problems.

• Coupled systems mechanics
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• v.4 no.1
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• pp.1-18
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• 2015

The state-based peridynamics is considered a nonlocal method in which the equations of motion utilize integral form as opposed to the partial differential equations in the classical continuum mechanics. As a result, the enforcement of boundary conditions in solid mechanics analyses cannot follow the standard way as in a classical continuum theory. In this paper, a new approach for the boundary condition enforcement in the state-based peridynamic formulation is presented. The new method is first formulated based on a convex kernel approximation to restore the Kronecker-delta property on the boundary in 1-D case. The convex kernel approximation is further localized near the boundary to meet the condition that recovers the correct boundary particle forces. The new formulation is extended to the two-dimensional problem and is shown to reserve the conservation of linear momentum and angular momentum. Three numerical benchmarks are provided to demonstrate the effectiveness and accuracy of the proposed approach.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.137-146
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• 2005

In parametric approach to a signature verification, it generally uses so many redundant features unsuitable for each individual signature that it causes harm, instead. This paper proposes a method of determining personalized weights of a feature set in signature verification with parametric approach by identifying the characteristics of each feature. For an individual signature, we define a degree of how difficult it is for any other person to forge the one's (called 'DFD' as the Degree of Forgery Difficulty). According to the statistical characteristics and the intuitional characteristics of each feature, the standard features are classified into four types. Four types of DFD functions are defined and applied into the distance calculation as a personalized weight factor. Using this method, the error rate of signature verification is reduced and the variation of the performance is less sensitive to the changes of decision threshold.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.1-6
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• 2001

This paper proposes a pattern classification method of interval vectors by interval neural networks. The proposed method can be applied to pattern classification where attribute values of each sample are given as interval numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Next, a learning algorithm is derived from the cost function. a cost function is defined using the interval output from the interval neural network and the corresponding target output. Last, using numerical examples, the proposed approach is illustrated and compared with other approach based on the standard back-propagation neural networks.

• Interaction and multiscale mechanics
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• v.7 no.1
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• pp.525-542
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• 2014

The state-based peridynamics is considered a nonlocal method in which the equations of motion utilize integral form as opposed to the partial differential equations in the classical continuum mechanics. As a result, the enforcement of boundary conditions in solid mechanics analyses cannot follow the standard way as in a classical continuum theory. In this paper, a new approach for the boundary condition enforcement in the state-based peridynamic formulation is presented. The new method is first formulated based on a convex kernel approximation to restore the Kronecker-delta property on the boundary in 1-D case. The convex kernel approximation is further localized near the boundary to meet the condition that recovers the correct boundary particle forces. The new formulation is extended to the two-dimensional problem and is shown to reserve the conservation of linear momentum and angular momentum. Three numerical benchmarks are provided to demonstrate the effectiveness and accuracy of the proposed approach.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.32-38
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• 2021

This paper suggests an approach to evaluate the reliability of an intelligent power module with information deficiency of prior distribution and the characteristics of censored data through Bayesian statistics. This approach used a prior distribution of Bayesian statistics using the lifetime information provided by the manufacturer and compared and evaluated diffuse prior (vague prior) distributions. To overcome the computational complexity of Bayesian posterior distribution, it was computed with Gibbs sampling in the Monte Carlo simulation method. As a result, the standard deviation of the prior distribution developed using simple information was smaller than that of the posterior distribution calculated with the diffuse prior. In addition, it showed excellent error characteristics on RMSE compared with the Kaplan-Meier method.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.105-111
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• 2003

This paper presents an approach to automate process planning of press dies for manufacturing of car bodies. Considering that the press-dies used at the same press operations regardless of the panels they produce or the car models of which they produce panels have similar shapes except for the forming part of the dies, general approaches to recognize manufacturing features from CAD models are not necessary. Therefore, a hybrid approach is proposed combining feature-based design and feature-extraction approaches. The proposed method recognizes features by parsing the parameters extracted from CAD models and finds proper operations by querying the database by the recognized features. An internet-based process planning system is developed to demonstrate the proposed approach and to suggest a new paradigm of process planning system that utilizes an internet access to the CAD system.