• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.53-63
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• 1985

This paper presents a multi-costraint optimization model for redundant system reliability. The optimization model is usually formulated as a nonlinear integer programming (NIP) problem. This paper reformulates the NIP problem into a linear integer programming (LIP) problem. Then an efficient 'Branch and Straddle' algorithm is proposed to solve the LIP problem. The efficiency of this algorithm stems from the simultaneous handling of multiple variables, unlike in ordinary branch and bound algorithms. A numerical example is given to illustrate this algorithm.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.140-145
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• 2000

The objective of experimental study is to apply simultaneous measurement by PIV(Particle Image Velocimetry) to high_speed flow characteristics within ginseng cleaner model. Three different kinds of flow rate(15.20 27ℓ/min) are selected as experimental condition. Optimized cross correlation identification to obtain velocity vectors is implemented by direct calculation of correlation coefficients. The instantaneous velocity distribution time0mean velocity distribution and velocity profile are represented quantitatively for the deeper understanding of the flow characteristics in a ginseng cleaner model.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.161-169
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• 2005

In this paper we propose a fuzzy c-regression model based on weighted least squares support vector machine(LS-SVM), which can be used to detect outliers in the switching regression model while preserving simultaneous yielding the estimates of outputs together with a fuzzy c-partitions of data. It can be applied to the nonlinear regression which does not have an explicit form of the regression function. We illustrate the new algorithm with examples which indicate how it can be used to detect outliers and fit the mixed data to the nonlinear regression models.

• Transactions of Materials Processing
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• v.9 no.4
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• pp.372-378
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• 2000

A process model including the effects of both the texture development and ductile damage evolution In plane strain rolling is presented. In this process model, anisotropy from deformation texture and deterioration of mechanical properties due to growth of micro voids are directly coupled Into the virtual work expressions for the momentum and mass balances. Special treatments in obtaining the initial values of field variables in the nonlinear simultaneous equations for the anisotropic, dilatant viscoplastic deformation are also given. Mutual effects of the texture development and damage evolution during plate rolling are carefully examined in terms of the distribution of strain components, accumulated damage, R-value as well as yield surfaces.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.99-108
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• 1999

B-ISDN link dimensioning is often known as a difficult problem because of the characteristics of Asynchronous Transfer Mode(ATM) such as various Quality of Services of different service requirements, and the statistical multiplexing resulting from virtual path/virtual circuit connections. In this paper, we propose a nonlinear integer optimization model for dimensioning B-ISDN considering the statistical multiplexing effects of virtual path connections(VPCs) and the modularity of resources allocated to a transmission link. The algorithm based on the simultaneous linear approximation technique as well as some numerical results will be also presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.81-98
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• 2013

Since Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) were introduced, many revised or extended topic models have appeared. Due to the intractable likelihood of these models, training any topic model requires to use some approximation algorithm such as variational approximation, Laplace approximation, or Markov chain Monte Carlo (MCMC). Although these approximation algorithms perform well, training a topic model is still computationally expensive given the large amount of data it requires. In this paper, we propose a new method, called non-simultaneous sampling deactivation, for efficient approximation of parameters in a topic model. While each random variable is normally sampled or obtained by a single predefined burn-in period in the traditional approximation algorithms, our new method is based on the observation that the random variable nodes in one topic model have all different periods of convergence. During the iterative approximation process, the proposed method allows each random variable node to be terminated or deactivated when it is converged. Therefore, compared to the traditional approximation ways in which usually every node is deactivated concurrently, the proposed method achieves the inference efficiency in terms of time and memory. We do not propose a new approximation algorithm, but a new process applicable to the existing approximation algorithms. Through experiments, we show the time and memory efficiency of the method, and discuss about the tradeoff between the efficiency of the approximation process and the parameter consistency.

• Journal of Korea Water Resources Association
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• v.37 no.12
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• pp.1009-1018
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• 2004

A systematic method using an optimal estimation algorithm is presented for simultaneous estimation of diffuse pollution distributed along a stream reach and model parameters for a stream water quality model. It was applied with the QVAL2E model to the South Han River for optimal estimation of kinetic constants and diffuse loads along the river. Initial calibration results for kinetic constants selected from a sensitivity analysis reveal that diffuse source inputs for nitrogen and phosphorus are essential to satisfy the system mass balance. Diffuse loads for total nitrogen and total phosphorus were estimated solving the expanded inverse problem. Comparison of kinetic constants estimated simultaneously with diffuse sources to those estimated without diffuse loads, suggests that diffuse sources must be included in the optimization not only for its own estimation but also for adequate estimation of the model parameters. Application of optimization method to river water quality modeling is discussed in terms of the sensitivity coefficient matrix structure.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.4
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• pp.331-340
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• 2004

This paper presents a feasibility study of a fresh air load reduction system by using an underground double floor space. The fresh air is introduced into the double slab space and passes through the opening bored into the footing beam. The air is cooled by the heat exchange with the inside surface of the double slab space in summer, and heated in winter. This system not only reduces sensible heat load of the fresh air by heat exchange with earth but also reduces latent heat load of the fresh air by ad/de-sorption of underground double slab concrete. In this paper, we used a model for evaluation of fresh air latent heat load reduction by hygroscopic of air to earth exchange system taking into account coupled heat and moisture transfer of underground double floor space. In conclusion it shows the validity of the proposed method for a design tool and the quantitative effect of the system.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.442-448
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• 2011

There are many research results about a self-localization technique of mobile robot. In this paper we present a self-localization technique based on the features of ceiling vision using a fisheye lens. The features obtained by SIFT(Scale Invariant Feature Transform) can be used to be matched between the previous image and the current image and then its optimal function is derived. The fisheye lens causes some distortion on its images naturally. So it must be calibrated by some algorithm. We here propose some methods for calibration of distorted images and design of a geometric fitness model. The proposed method is applied to laboratory and aile environment. We show its feasibility at some indoor environment.