• Journal of computational fluids engineering
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• v.3 no.1
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• pp.22-29
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• 1998

Parallel implementation is conducted for a SIMPLER finite volume model. The present parallelism is based on domain decomposition and explicit message passing using MPI and SHMEM. Two parallel solvers to tridiagonal matrix equation are employed. The implementation is verified on the Cray T3E system for a benchmark problem of natural convection in a sidewall-heated cavity. The test results illustrate good scalability of the present parallel models. Performance issues are elaborated in view of convergence as well as conventional parallel overheads and single processor performance. The effectiveness of a localized matrix solution algorithm is demonstrated.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.793-800
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• 2004

The purpose of this study is to develope a servo system with faster and more accurate response. This paper describes a method of approximate reasoning for fuzzy control of servo system based on the decomposition of $\alpha$-level fuzzy sets. We propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion cases where the output variable u directly is generated PWM The effectiveness for robust and faster response of the fuzzy control scheme are verified for a variable parameter by comparison with a PID control and fuzzy control A position control of DC servo system with a fuzzy logic controller is demonstrated successfully.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.225-237
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• 2012

This study proposes a quantification algorithm for a PLS method with several sets of variables. We called the quantification method for PLS with more than 2 sets of data a generalization. The basis of the quantification for PLS method is singular value decomposition. To derive the form of singular value decomposition in the data with more than 2 sets more easily, we used the constraint, $a^ta+b^tb+c^tc=3$ not $a^ta=1$, $b^tb=1$, and $c^tc=1$, for instance, in the case of 3 data sets. However, to prove that there is no difference, we showed it by the use of 2 data sets case because it is very complicate to prove with 3 data sets. The keys of the study are how to form the singular value decomposition and how to get the coordinates for the plots of variables and observations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1424-1428
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• 1999

This paper presents a mathematical decomposition coordination method to implementing the distributed optimal power flow (OPF), wherein a regional decomposition technique is adopted to parallelize the OPT. The proposed approach is based on the Alternating Direction Method (ADM), a variant of the conventional Augmented Lagrangian approach, and makes it possible the independent regional AC-OPF for each control area while the global optimum for the entire system is assured. This paper is an extension of our previous work based on the auxiliary problem principle (APP). The proposed approach in this paper is a completely new one, however, in that ADM is based on the Proximal Point Algorithm which has long been recognized as one of the attractive methods for convex programming and min-max-convex-concave programming. The proposed method was demonstrated with IEEE 50-Bus system.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.863-875
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• 2017

The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.90-90
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• 2011

Long-term nonstationary oscillations (NSOs) are commonly observed in hydrological and climatological data series such as low-frequency climate oscillation indices and precipitation dataset. In this work, we present a stochastic model that captures NSOs within a given variable. The model employs a data-adaptive decomposition method named empirical mode decomposition (EMD). Irregular oscillatory processes in a given variable can be extracted into a finite number of intrinsic mode functions with the EMD approach. A unique data-adaptive algorithm is proposed in the present paper in order to study the future evolution of the NSO components extracted from EMD.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.21-31
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• 2014

Singular value decomposition (SVD) has been widely used to identify unique features from a data set in various fields. However, a complex matrix calculation of SVD requires tremendous computation time. This paper improves the performance of a representative one-sided block Jacoby algorithm using a two-dimensional (2D) multi-core system. In addition, this paper explores an optimal multi-core system by varying the number of processing elements in the 2D multi-core system with the same 400MHz clock frequency and TSMC 28nm technology for each matrix-based one-sided block Jacoby algorithm ($128{\times}128$, $64{\times}64$, $32{\times}32$, $16{\times}16$). Moreover, this paper demonstrates the potential of the 2D multi-core system for the one-sided block Jacoby algorithm by comparing the performance of the multi-core system with a commercial high-performance graphics processing unit (GPU).

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.274-284
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• 2002

Word segmentation errors occurring in text preprocessing often insert incorrect words into recognition vocabulary and cause poor language models for Korean large vocabulary continuous speech recognition. We propose an automatic word segmentation algorithm using Markov chains and syllable-based n-gram language models in order to correct word segmentation error in teat corpora. We assume that a sentence is generated from a Markov chain. Spaces and non-space characters are generated on self-transitions and other transitions of the Markov chain, respectively Then word segmentation of the sentence is obtained by finding the maximum likelihood path using syllable n-gram scores. In experimental results, the algorithm showed 91.58% word accuracy and 96.69% syllable accuracy for word segmentation of 254 sentence newspaper columns without any spaces. The algorithm improved the word accuracy from 91.00% to 96.27% for word segmentation correction at line breaks and yielded the decomposition accuracy of 96.22% for compound-noun decomposition.

• Smart Structures and Systems
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• v.22 no.5
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.197-201
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• 2011

The use of gestures provides an attractive alternate to cumbersome interfaces for human-computer devices interaction. This has motivated a very active research area concerned with computer vision-based recognition of hand gestures. The most important issues in hand gesture recognition is to recognize the directivity of finger. The primitive elements extracted to a hand gesture include in very important information on the directivity of finger. In this paper, we propose the recognition algorithm of finger directivity by using the cross points of circle and sub-primitive element. The radius of circle is increased from minimum radius including main-primitive element to it including sub-primitive elements. Through the experiment, we demonstrated the efficiency of proposed algorithm.