• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.154-154
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• 2019

Characterization of reliable field-scale root-zone soil moisture (RZSM) variability contribute to effective hydro-meterological monitoring. Although a promising cosmic-ray neutron probe (CRNP) holds the pontential for field-scale RZSM measurement, it is often restricted at deeper depths due to the non-unique sensitivity of CRNP-measured fast neutron signal to other hydrogen pools. In this study, a merging framework relied on coupling cosmic-ray soil moisture with a representative additional RZSM, was introduced to scale shallower CRNP effective depth to represent root-zone layer. We tested our proposed framework over a densely vegetated region in South Korea covering a network of one CRNP and nine in-situ point measurements. In particular, cosmic-ray soil moisture and ancillary RZSM retrieved from the most time stable location were considered as input datasets; whereas the remaining point locations were used to generate a reference RZSM product. The errors between these two input datasets and the reference were forecasted by a linear autoregressive model. A linear combination of forecasts was then employed to compute a suitable weight for merging two input products from the predicted errors. The performance of merging framework was evaluated against reference RZSM in comparison to the two original products and a commonly used exponential filter technique. The results of this study showed that merging framework outperformed other products, demonstrating its robustness in improving field-scale RZSM. Moreover, a strong relationship between the quality of input data and the performance merging framework in light of CRNP effective depth variation has been also underlined via the merging framework.

• Journal of Powder Materials
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• v.30 no.4
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• pp.346-355
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• 2023

Epoxy-based composites find extensive application in electronic packaging due to their excellent processability and insulation properties. However, conventional epoxy-based polymers exhibit limitations in terms of thermal properties and insulation performance. In this study, we develop epoxy-based siloxane/silica composites that enhance the thermal, mechanical, and insulating properties of epoxy resins. This is achieved by employing a sol-gel-synthesized siloxane hybrid and spherical fused silica particles. Herein, we fabricate two types of epoxy-based siloxane/silica composites with different siloxane molecular structures (branched and linear siloxane networks) and investigate the changes in their properties for different compositions (with or without silica particles) and siloxane structures. The presence of a branched siloxane structure results in hardness and low insulating properties, while a linear siloxane structure yields softness and highly insulating properties. Both types of epoxy-based siloxane/silica composites exhibit high thermal stability and low thermal expansion. These properties are considerably improved by incorporating silica particles. We expect that our developed epoxy-based composites to hold significant potential as advanced electronic packaging materials, offering high-performance and robustness.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• KDI Journal of Economic Policy
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• v.36 no.4
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• pp.135-169
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• 2014

This study empirically analyzes changes in production patterns of farmers by agricultural disaster insurance. The aim of this project is to achieve stability of farm management by paying insurance in case of a natural disaster. However, it causes farmers to change production patterns in the direction of increasing production, and leads the crop price to drop. This can be explained by producers' risk reduction through the disaster insurance. The empirical analysis is based on IV approach with using two stage least squares method. The first stage estimates by difference-in-differences methodology indicate that the production of insurable crops increases more about 80,000ton on average than that of non-insurable crops. In addition, to solve the endogeneity problem caused by general supply and demand model, I use the first stage estimates and find that the price index of the crops drops about 2.3% according to the production increase by 10,000ton. The credibility of these results is also attained by various robustness checks. These findings suggest that it is necessary for government to analyze the whole economy which consists of producer and consumer welfare when it determines the policy. Besides, it implies that it is essential to develop a new market to cope with the unintended effect.

• Journal of Pharmaceutical Investigation
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• v.35 no.6
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• pp.437-443
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of a major metabolite of terfenadine, fexofenadine, in human serum was developed, validated, and applied to the pharmacokinetic study of terfenadine. Fexofenadine and internal standard, haloperidol were extracted from human serum by liquid-liquid extraction with acetonitrile and analyzed on a $Symmetry^{TM}$ C8 column with the mobile phase of 1% triethylamine phosphate (pH 3.7)-acetonitrile (67:33, v/v, adjusted to pH 5.6 with triethylamine). Detection wavelength of 230 nm for excitation, 280 nm for emission and flow rate of 1.0 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^{3}$ factorial design using a fixed fexofenadine concentration (50 ng/mL) with respect to its peak area and retention time. In addition, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 10-500 ng/mL with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of serum was 10 ng/mL, which was sensitive enough for the pharmacokinetic studies of terfenadine. The overall accuracy of the quality control samples ranged from 95.70 to 114.58% for fexofenadine with overall precision (% C.V.) being 3.53-14.39%. The relative mean recovery of fexofenadine for human serum was 90.17%. Stability studies (freeze-thaw, short-term, extracted serum sample and stock solution) showed that fexofenadine was stable during storage, or during the assay procedure in human serum. However, the storage at $-70^{\circ}C$ for 4 weeks showed that fexofenadine was not stable. The peak area and retention time of fexofenadine were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of fexofenadine in human serum samples for the pharmacokinetic studies of orally administered Tafedine tablet (60 mg as terfenadine) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.4
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• pp.265-271
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of etodolac in human serum was developed, validated, and applied to the pharmacokinetic study of etodolac. Etodolac and internal standard, ibuprofen were extracted from human serum by liquid-liquid extraction with hexane/isopropanol (95:5, v/v) and analyzed on a Luna C18(2) column with the mobile phase of 1% aqueous acetic acid-acetonitrile (4:6, v/v). Detection wavelength of 227 nm and flow rate of 1.0 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^3$ factorial design using a fixed etodolac concentration $(1\;{\mu}g/mL)$ with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of $0.05-40\;{\mu}g/mL$ with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of serum was 0.05 ${\mu}g/mL$, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 92.00 to 110.00% for etodolac with overall precision (% C.V.) being 1.08-10.11%. The percent recovery for human serum was in the range of 76.73-115.30%. Stability studies showed that etodolac was stable during storage, or during the assay procedure in human serum. The peak area and retention time of etodolac were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of etodolac in human serum samples for the pharmacokinetic studies of orally administered Lodin XL tablet (400 mg as etodolac) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.36 no.1
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• pp.45-51
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• 2006

A rapid, selective and sensitive reversed-phase HPLC method for the determination of dipyridamole in human serum was developed, validated, and applied to the pharmacokinetic study of dipyridamole. Dipyridamole and internal standard, loxapine, were extracted from human serum by liquid-liquid extraction with diethyl ether and analyzed on a Nova Pak $C_{I8}$ column with the mobile phase of 40 mM ammonium acetate:methanol:acetonitrile (35:35:30)(v/v/v, pH 7.8). Detection wavelength of 280 nm and flow rate of 1.0 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^3$ factorial design using a fixed dipyridamole concentration (50 ng/mL) with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 2-2000 ng/mL with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of serum was 2 ng/mL, which was sensitive enough for pharmacokinetic studies of dipyridamole. The overall accuracy of the quality control samples ranged from 103.94 to 105.86% for dipyridamole with overall precision (% C.V.) being 4.60-11.49%. The relative mean recovery of dipyridamole for human serum was 97.64%. Stability studies showed that dipyridamole was stable during storage, or during the assay procedure in human serum. The peak area and retention time of dipyridamole were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of dipyridamole in human serum samples for the pharmacokinetic studies of orally administered Dimor tablet (75 mg as dipyridamole) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.36 no.1
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• pp.23-29
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• 2006

A rapid, selective and sensitive reversed-phase HPLC method for the determination of promethazine in human serum was developed, validated, and applied to the pharmacokinetic study of promethazine. Promethazine and internal standard, chlorpromazine, were extracted from human serum by liquid-liquid extraction with n-hexane containing 0.8% isopropanol and analyzed on a Capcell Pak CN column with the mobile phase of acetonitrile-0.2 M potassium dihydrogen phosphate (42:58, v/v, adjusted to pH 6.0 with 1 M NaOH). Detection wavelength of 251 nm and flow rate of 0.9 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^{3}$ factorial design using a fixed promethazine concentration (10 ng/mL) with respect to its peak area and retention time. In addition, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 1-40 ng/mL with correlation coefficients greater than 0.999. The lower limit of quantification using 1 mL of serum was 1 ng/mL, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 96.15 to 105.40% for promethazine with overall precision (% C.V.) being 6.70-11.22%. The relative mean recovery of promethazine for human serum was 63.54%. Stability (freeze-thaw and short-term) studies showed that promethazine was stable during storage, or during the assay procedure in human serum. However, the storage at $-80^{\circ}C$ for 4 weeks showed that promethazine was not stable. Extracted serum sample and stock solution were not allowed to stand at ambient temperature for 12 hr prior to injection. The peak area and retention time of promethazine were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of promethazine in human serum samples for the pharmacokinetic studies of orally administered Himazin tablet (25 mg as promethazine hydrochloride) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.6
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• pp.423-429
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• 2005

A selective and sensitive reversed-phase HPLC method for the determination of fenoprofen in human serum was developed, validated, and applied to the pharmacokinetic study of fenoprofen calcium. Fenoprofen and internal standard, ketoprofen, were extracted from human serum by liquid-liquid extraction with diethyl ether and analyzed on a Luna C18(2) column with the mobile phase of acetonitrile-3 mM potassium dihydrogen phosphate (32:68, v/v, adjusted to pH 6.6 with phosphoric acid). Detection wavelength of 272 nm and flow rate of 0.25 mL/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^{3}$ factorial design using a fixed fenoprofen concentration $(2\;{\mu}g/mL)$ with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of $0.05-100\;{\mu}g/mL$ with correlation coefficients greater than 0.999. The lower limit of quantification using 1 mL of serum was $0.05\;{\mu}g/mL$, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 92.27 to 109.20% for fenoprofen with overall precision (% C.V.) being 5.51-11.71 %. The relative mean recovery of fenoprofen for human serum was 81.7%. Stability (freeze-thaw, short and long-term) studies showed that fenoprofen was not stable during storage. But, extracted serum sample and stock solution were allowed to stand at ambient temperature for 12 hr prior to injection without affecting the quantification. The peak area and retention time of fenoprofen were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of fenoprofen in human serum samples for the pharmacokinetic studies of orally administered Fenopron tablet (600 mg as fenoprofen) at three different laboratories, demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
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• v.35 no.3
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• pp.137-142
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• 2005

A rapid, selective and sensitive reversed-phase HPLC method for the determination of glipizide in human serum was validated and applied to the pharmacokinetic study of glipizide. Glipizide and internal standard, tolbutamide, were extracted from human serum by liquid-liquid extraction with benzene and analyzed on a Nova Pak $C_{18}\;60{\AA}$ column with the mobile phase of acetonitrile-potassium dihydrogen phosphate (10 mM, pH 3.5) (4:6, v/v). Detection wavelength of 275 nm and flow rate of 0.7 ml/min were fixed for the study. The assay robustness for the changes of mobile phase pH, organic solvent content, and flow rate was confirmed by $3^3$ factorial design using a fixed glipizide concentration (500 ng/ ml) with respect to its peak area and retention time. And also, the ruggedness of this method was investigated at three different laboratories using same quality control (QC) samples. This method showed linear response over the concentration range of 10-1000 ng/ml with correlation coefficient greater than 0.999. The lower limit of quantitation using 0.5 ml of serum was 10.0 ng/ml, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the quality control samples ranged from 82.6 to 105.0% for glipizide with overall precision (% C.V.) being 1.13-13.20%. The percent recovery for human serum was in the range of 85.2 93.5%. Stability studies showed that glipizide was stable during storage, or during the assay procedure in human serum. The peak area and retention time of glipizide were not significantly affected by the changes of mobile phase pH, organic solvent content, and flow rate under the conditions studied. This method showed good ruggedness (within 15% C.V.) and was successfully used for the analysis of glipizide in human serum samples for the pharmacokinetic studies at three different laboratories, demonstrating the suitability of the method.