• Proceedings of the KSME Conference
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• 2001.06b
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• pp.216-221
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• 2001

The equivalent source method(ESM) is used for the calculation of the internal pressure field for an enclosure which can have arbitrary boundary conditions and may include internal objects which scatter the sound field. The advantage of using ESM is that it requires relatively low computing cost and is easy to model the internal diffracting objects. In the ESM modelling, some of the equivalent positions are chosen to be the same as the first order images of the source inside the enclosure, some are positioned on a spherical surface some distance outside the enclosure. The normal velocity on the surfaces of the enclosure walls is evaluated at a larger number of positions than there are equivalent sources. The sum of the squared difference between this velocity and the expected is minimized by adjusting the strength of the equivalent sources. This study is on the optimal equivalent source positions, the far field sources. Typically, the far field sources are evenly distributed on a surface of a virtual sphere which is centered at the enclosure with a sufficiently large radius. In this study, optimal far field source locations are searched using simulated annealing method and simulation results showed that optimally located sources gave better accuracy even with a smaller number of far field sources.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.431-440
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• 2013

We consider the problem of estimating the parameters of heavy tailed distributions. In general, maximum likelihood estimation(MLE) is the most preferred method of parameter estimation because it has good properties such as asymptotic consistency, normality and efficiency. However, MLE is not always the best solution because MLE is unstable or does not exist in some cases. This paper proposes another parameter estimation method, non-linear least squares(NLS) and compares its performance to MLE. The NLS estimator is achieved by minimizing sum of squared difference between empirical cumulative distribution function(CDF) and a theoretical distribution function. In this article, we compare the NLS method to MLE using simulated data from heavy tailed distributions. The NLS method is shown to perform better than MLE in Burr distribution when the sample size is small; in addition, it performs well in a Frechet distribution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.143-152
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• 2012

It is well-known that image matching is necessary for automatic generation of 3D data such as digital surface data from aerial images. Recently developed aerial digital cameras allow to capture multi-strip images with higher overlaps and less occluded areas than conventional analogue cameras and that much of researches on multi-image matching have been performed, particularly effective methods of measuring a similarity among multi-images using point features as well as linear features. This research aims to investigate similarity measuring methods such as SSD and SNCC incorporated into a area based multi-image matching method based on vertical line locus. In doing this, different similarity measuring entities such as grey value, grey value gradient, and average of grey value and its gradient are implemented and analyzed. Further, both dynamic and pre-fixed adaptive-window size are tested and analyzed in their behaviors in measuring similarity among multi-images. The aerial images used in the experiments were taken by a DMC aerial frame camera in three strips. The over-lap and side-lap are about 80% and 60%, respectively. In the experiment, it was found that the SNCC as similarity measuring method, the average of grey value and its gradient as similarity measuring entity, and dynamic adaptive-window size can be best fit to measuring area-based similarity in area based multi-image matching method based on vertical line locus.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.3
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• pp.277-288
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• 2017

Previous studies of health effects of $PM_{2.5}$ performed spatial monitoring campaigns to assess spatial variability of $PM_{2.5}$ across people's residences. Highly reliable portable and cost-effective samplers will be useful for such campaigns. This study aimed to investigate applicability of the Deployable Particulate Impact Sampler(DPIS), one of the compact impact samplers, to spatial monitoring campaigns of $PM_{2.5}$ in Seoul, Korea. The investigation focused on the consistency of $PM_{2.5}$ concentrations measured by DPISs compared to those by the Low-volume Cyclone sampler (LCS). LCS has operated at a fixed site in the Seoul National University Yeongeon campus, Seoul, Korea since 2003 and provided qualified $PM_{2.5}$ data. $PM_{2.5}$ sampling of DPISs was carried out at the same site from November 17, 2015 through February 3, 2016. $PM_{2.5}$ concentrations were quantified by the gravimetric method. Using a duplicated DPIS, we confirmed the reliability of DPIS by computing relative precision and mean square error-based R squared value ($R^2$). Relative precision was one minus the difference of measurements between two samplers relative to the sum. For accuracy, we compared $PM_{2.5}$ concentrations from four DPISs (DPIS_Tg, DPIS_To, DPIS_Qg, and DPIS_Qo) to those of LCS. Four samplers included two types of collection filters(Teflon, T; quartz, Q) and impaction discs(glass fiber filter, g; pre-oiled porous plastic disc, o). We assessed accuracy using accuracy value which is one minus the difference between DPIS and LCS $PM_{2.5}$ relative to LCS $PM_{2.5}$ in addition to $R^2$. DPIS showed high reliability (average precision=97.28%, $R^2=0.98$). Accuracy was generally high for all DPISs (average accuracy=83.78~88.88%, $R^2=0.89{\sim}0.93$) except for DPIS_Qg (77.35~78.35%, 0.82~0.84). Our results of high accuracy of DPIS compared to LCS suggested that DPIS will help the assessment of people's individual exposure to $PM_{2.5}$ in extensive spatial monitoring campaigns.

• Journal of Korean Neurosurgical Society
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• v.47 no.5
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• pp.345-351
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• 2010

Objective : In this study, the Mindfulness Based Stress Reduction (MBSR) program was applied to patients presenting with depression and anxiety after surgery from spontaneous subarachnoid hemorrhage (SAH) and the effects were assessed. Methods : The subjects were patients admitted for cerebral aneurysm rupture and treated by means of surgery from March to December, 2007. More than 6 months had passed after surgery, without any special lesions showing up on computed tomography (CT), and the Glasgow outcome scale (GOS) was 5 points. Among patients with anxiety and depression symptoms, 11 patients completed the program. The MBSR program was conducted once a week, 2.5 hours each, for 8 weeks. The evaluation criteria were : 1) the Beck Depression Inventory (BDI): it measures the type and level of depression, 2) the State-Trait Anxiety Inventory : the anxiety state of normal adults without mental disorder, and 3) Heart Rate Variability (HRV) : the influence of the autonomous nervous system on the sinoarterial node varies continuously in response to the change of the internal/external environment. Results : The BDI value was decreased from 18.5 ${\pm}$ 10.9 to 9.5 ${\pm}$ 7.1 (p = 0.013) : it was statistically significant, and the depression level of patients was lowered. The state anxiety was decreased from 51.3 ${\pm}$ 13.9 to 42.3 ${\pm}$ 15.2; the trait anxiety was reduced from 50.9 ${\pm}$ 12.3 to 41.3 ${\pm}$ 12.8, and a borderline significant difference was shown (p = 0.091, p = 0.056). In other words, after the treatment, although it was not statistically significant, a decreased tendency in anxiety was shown. In the HRV measurement, standard deviation normal to normal (SDNN), square root of the square root of the mean sum of squared differences between adjacent normal to normal intervals (RMSSD), and total power (TP) showed significant increase, Physical Stress Index (PSI) showed a significant reduction, and thus an improvement in the homeostatic control mechanism of the autonomic nervous system was ween. Conclusion : The MBSR program was applied to the patients showing anxiety and depression reaction after SAH treatment, and a reduction in depression symptoms and physiological reactions were observed. The application of the MBSR program may be considered as a new tool in improving the quality of life for patients after surgery.