• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.458-463
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• 2004

This paper presents a fast IA(integer ambiguity) resolution method that determines the IA within short epochs with guaranteed reliability. Based on the fact that the search volume and the cost function are influenced by the selection of primary IAs in the plane intersection method, an IA resolution method is proposed that evaluates IA candidates repeatedly in an epoch with different combinations of primary IAs. In order to guarantee the reliability of the resolved IA with a certain probability, an inequality condition for selecting differencing operator is derived. Experiment results show that the proposed method consistently provides the true IA estimates within short time.

• Pediatric Infection and Vaccine
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• v.16 no.1
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• pp.47-53
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• 2009

Purpose : This study was performed to investigate the serotype distribution of group B streptococcus (GBS) isolated from pregnant Korean women using molecular methods. Methods : The study materials included 42 GBS isolates obtained from the vagina and anorectum of pregnant women in Goyang, Korea between 2005 and 2006. Four clinical isolates with known serotypes (Ia, Ib, III, and V) were used for validation of molecular serotyping. We used serotype-specific primers for identification of the serotypes (Ia, Ib, III, V, and VI). To determine the ambiguous serotypes by serotype-specific PCR, sequence analysis of the PCR amplicons which had been amplified with GBS-common primers was used. Results : The serotypes determined by the molecular methods agreed with the previously known 4 serotypes (Ia, Ib, III, and V). The serotypes of all 42 isolates were successfully determined by molecular methods. The distribution of the GBS serotype was as follows in order of frequency: serotype III was found in 12 isolates (28.6%), serotype V was found in 11 isolates (26.2%), serotype Ia was found in 11 isolates (26.2%), serotype VI was found in 4 isolates (9.5%), serotype Ib was found in 2 isolates (4.8%), and serotype II was found in 2 isolates (4.8%). Conclusion : Serotypes III, V, and Ia were the most frequently identified serotypes in pregnant Korean women. Molecular serotyping is useful for surveillance of the serotype distribution of GBS in colonized pregnant women and GBS diseases of neonates.

• Korean Journal of Clinical Pharmacy
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• v.29 no.2
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• pp.89-100
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• 2019

Background: Invasive aspergillosis (IA) is associated with high morbidity and mortality, particularly among immunocompromised patients, such as lung transplant recipients. Voriconazole, the first-line therapy for IA, shows a non-linear pharmacokinetic profile and has a narrow therapeutic range. Careful and appropriate administration is necessary, primarily because it is used for critically ill patients; however, the clinical usefulness of therapeutic drug monitoring (TDM) has not been sufficiently verified. Therefore, in this study, we validated the safety and efficacy of voriconazole TDM in lung transplant recipients receiving only voriconazole for IA treatment. Methods: The electronic medical records of lung transplant recipients (${\geq}19$ years of age) administered only voriconazole for > 7 days for treatment of IA from June 1, 2013 to May 31, 2018 were analyzed retrospectively. Results: Among the 54 patients, 27 each were allocated to TDM and non-TDM groups, respectively. There were no significant differences in patient characteristics between the two groups except for ICU-hospitalization status. Of the TDM group patients, 81.5% needed adjustment of voriconazole dosage because the levels were out of target range. Comparison of two groups showed that treatment response was higher throughout treatment and switching rates of second-line agents were significantly lower in the TDM group, but it was insufficient to confirm safety improvements through voriconazole TDM. Conclusions: Considering that the treatment response tended to be higher and the rates of switching to second-line antifungal agents were lower in the TDM group, voriconazole TDM may increase the therapeutic effect on IA in lung transplant patients.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.645-654
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• 2004

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using Immune Algorithm (IAs). This IA-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using Immune Algorithm (IAs) in the HSE.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.92-94
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• 2003

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic instruments (Continuous Harmonic Analysis in Real Time : CHART) is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using Immune Algorithm (IAs). This HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using IAs in the HSE.

• Environmental Engineering Research
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• v.21 no.4
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• pp.333-340
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• 2016

An Artificial Neural Network including a Radial Basis Function (RBF) and a Time Delay Neural Network (TDNN) was used to predict total dissolved solid (TDS) in the river Zayanderud. Water quality parameters in the river for ten years, 2001-2010, were prepared from data monitored by the Isfahan Regional Water Authority. A factor analysis was applied to select the inputs of water quality parameters, which obtained total hardness, bicarbonate, chloride and calcium. Input data to the neural networks were pH, $Na^+$, $Mg^{2+}$, Carbonate ($CO{_3}^{-2}$), $HCO{_3}^{-1}$, $Cl^-$, $Ca^{2+}$ and Total hardness. For learning process 5-fold cross validation were applied. In the best situation, the TDNN contained 2 hidden layers of 15 neurons in each of the layers and the RBF had one hidden layer with 100 neurons. The Mean Squared Error and the Mean Bias Error for the TDNN during the training process were 0.0006 and 0.0603 and for the RBF neural network the mentioned errors were 0.0001 and 0.0006, respectively. In the RBF, the coefficient of determination ($R^2$) and the index of agreement (IA) between the observed data and predicted data were 0.997 and 0.999, respectively. In the TDNN, the $R^2$ and the IA between the actual and predicted data were 0.957 and 0.985, respectively. The results of sensitivity illustrated that $Ca^{2+}$ and $SO{_4}^{2-}$ parameters had the highest effect on the TDS prediction.