• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.189-196
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• 2004

A modified generalized particle algorithm, MGPA, was suggested to improve the calculation efficiency of standard SPH Method in numerical analysis of high speed impact behavior. MGPA had a new weight function to reduce computation time. The efficiency of this method was proven through calculation for the sample problems of one dimensional rod impact problem and two dimensional plate impact problem. The MGPA method reduced the calculation error and stress oscillation near the boundaries. The validity of this approach was shown by the comparison with ABAQUS results in two dimensional plate impact problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.11-20
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• 2000

The Job Shop Scheduling Problem(JSSP) is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on single genetic algorithm(SGA) and parallel genetic algorithm (PGA) to address JSSP. In this scheduling method, new genetic operator, generating method of initial population are developed and island model PGA are proposed. The scheduling method based on PGA are tested on standard benchmark JSSP. The results were compared with SGA and another GA-based scheduling method. The PGA search the better solution or improves average of solution in benchmark JSSP. Compared to traditional GA, the proposed approach yields significant improvement at a solution.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.130-137
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• 1999

The criteria for determining the elements are the minimum zone method(MZM) and the least squares method(LSM). The LSM is deterministic and simple but is limited at the measurements whose errors are significant compared with form errors. For the precise condition, minimum zone method(MZM) has been selected to determine the elements. It is not deterministic and nonlinear so that a optimizing procedure is needed. The Straightness is the fundamental problem in the evaluating form error. In this paper, a new approach adapting the genius education concept is proposed to obtain an accurate results for the minimum zone problem of the straightness. Its computational algorithm is studied on a set of randomly generated data. To be of almost no account of the specification(the number and the standard devistion etc.) of the sample data, the results shows excellent reliability and high accuracy in estimating the straightness.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.2
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• pp.38-45
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• 2011

The criteria for determining the elements are the minimum zone method(MZM) and the least squares method(LSM). The LSM is deterministic and simple but is limited at the measurements whose errors are significant compared with form errors. For the precise condition, minimum zone method(MZM) has been selected to determine the elements. The roundness is the fundamental problem in the evaluating form errors. In this paper, anew approach adapting the genius education concept is proposed to obtain an accurate results for the MZM and the LSM of the roundness. Its computational algorithm is studied on a set of measured sample data. To be of almost no account of the specification(the number and the standard deviation etc.) of the sanple data, the results shoqs excellent reliability and high accuracy in estimating the roundness.

• Journal of Genetic Medicine
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• v.11 no.2
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• pp.43-48
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• 2014

Chorionic villus sampling has gained importance as a tool for early cytogenetic diagnosis with a shift toward first trimester screening. First trimester screening using nuchal translucency and biomarkers is effective for screening. Chorionic villus sampling generally is performed at 10-12 weeks by either the transcervical or transabdominal approach. There are two methods of analysis; the direct method and the culture method. While the direct method may prevent maternal cell contamination, the culture method may be more representative of the true fetal karyotype. There is a concern for mosaicism which occurs in approximately 1% of cases, and mosaic results require genetic counseling and follow-up amniocentesis or fetal blood sampling. In terms of complications, procedure-related pregnancy loss rates may be the same as those for amniocentesis when undertaken in experienced centers. When the procedure is performed after 9 weeks gestation, the risk of limb reduction is not greater than the risk in the general population. At present, chorionic villus sampling is the gold standard method for early fetal karyotyping; however, we anticipate that improvements in noninvasive prenatal testing methods, such as cell free fetal DNA testing, will reduce the need for invasive procedures in the near future.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.137-146
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• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.821-827
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• 2014

An isotope dilution liquid chromatography tandem mass spectrometry (ID LC-MS/MS) method has been developed and applied to the determination of arsenobetaine (AsB, ${(CH_3)_3}^+AsCH_2COO^-$) from oyster candidate certified reference material (CRM). The exact matching isotope dilution approach was adopted for accurate determination of AsB using $^{13}C_2$-labeled AsB as an internal standard. Efficiencies of different AsB extraction methods were evaluated using a codfish reference material and a simple sonication method was selected as the method of choice for the certification of the oyster candidate CRM. The hydrophilic interaction liquid chromatography (HILIC) combined with electrospray ionization tandem mass spectrometry (ESI/MS/MS) in selected reaction monitoring (SRM) mode was optimized for adequate chromatographic retention and robust quantification of AsB from codfish and oyster samples. By analyzing 12 subsamples taken from each 12 bottles systematically selected from the whole oyster CRM batch, the certified value of AsB was determined as $6.60mg{\cdot}kg^{-1}{\pm}0.31mg{\cdot}kg^{-1}$ and it showed excellent between-bottle homogeneity of less than 0.42%, which is represented by relative standard deviation of 12 bottles from the CRM batch. The major source of uncertainty was the certified value of the AsB standard solution.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.87-96
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• 2007

In this paper we propose a new noise reduction algorithm for stationary and nonstationary noisy environments. Our algorithm classifies the speech and noise signal contributions in time-frequency bins, and is not based on a spectral algorithm or a minimum statistics approach. It relies on calculating the ratio of the standard deviation of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. We show that good quality can be achieved for enhancement speech signal by choosing appropriate values for ${\delta}_t\;and\;{\delta}_f$. The proposed method greatly reduces the noise while providing enhanced speech with lower residual noise and somewhat higher mean opinion score (MOS), background intrusiveness (BAK) and signal distortion (SIG) scores than conventional methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.191-196
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• 2014

In the evaluation of measured noise data, tolerance shall be decided based on the uncertainty. The uncertainty has frequency variations due to the different standard deviations at each frequency. Therefore, tolerance shall be differently decided for each frequency with the same confidence probability. In the report, the evaluation method considering the frequency variation of uncertainty will be introduced. From the approach, considering the actual noise distribution characteristics of the ships, the tolerance shall be decided for each frequency with the same probability, but the overall averaged value shall be kept to the value designated in each notation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.714-717
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• 1996

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.