• Journal of the Korean Geotechnical Society
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• v.22 no.10
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• pp.111-120
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• 2006

In this research, numerical simulations by PFC considering discrete element method are conducted to predict experimental results of large triaxial compression test with rockfill material for dam construction. For generation of compacted assembly with specific grain size distribution and initial material porosity, the clump logic method and expansion of generated particles are adapted. To predict stress-stain behavior of large triaxial test, discrete particle modelling is applied with micro parameters which are chosen by calibration process. It is expected that distinct particle modelling method could be used as a useful tool to investigate micro and macro behavior associated with geotechnical problems and develop a numerical laboratory.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.47-52
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• 2009

A sand replacement method is commonly used to determine the density of the compacted soils. The density of the test or compacted soil is computed on the assumption that the calibration container has approximately the same size or volume and allows the sand to deposit approximately in the same way as a test hole in the field. The sand filling process is simulated in the laboratory and its effect on the determination of density is investigated. Artificially-made holes with different heights and bottom shapes are prepared to simulate various shapes of the test hole in the field. Three sands with different gradations are used in the testing to examine how sand grain size influences the determination of density in the field. As the height of a test hole increases, the error between known density and calculated density decreases, regardless of the types of test hole and sand used. The results of this study can be used to reevaluate and revise the test method for soil density by the sand replacement method.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.275-275
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• 2021

A fixed Z-R relationship approach, such as the Marshall-Palmer relationship, for an entire year and for different seasons can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian regression framework. This study also investigates seasonal differences in the Z-R relationship and their roles in reducing systematic error. Distinct differences in the Z-R parameters in space are identified, and more importantly, an inverse relationship between the parameters is clearly identified with distinct regimes based on the seasons. A spatially structured pattern in the parameters exists, particularly parameter α for the wet season and parameter β for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Finally, the radar rainfall estimates through the calibrated Z-R relationship are compared with the existing Z-R relationships for estimating stratiform rainfall and convective rainfall. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields, whereas the radar rainfall fields obtained from the existing Marshall-Palmer Z-R relationship show a systematic underestimation. The obtained Z-R relationships are validated by testing the predictions on unseen radar-gauge pairs in the year 2018, in the context of cross-validation. The cross-validation results are largely similar to those in the calibration process, suggesting that the derived Z-R relationships fit the radar-gauge pairs reasonably well.

• Analytical Science and Technology
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• v.19 no.6
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• pp.519-528
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• 2006

An analytical method for the determination of thyroid hormones in urine samples has been studied by using solid-phase extraction and high-performance liquid chromatography/diode array detector/electro-spray mass spectrometry. Seven thyroid hormones were successfully separated by gradient elution on the reverse phase Hypersil ODS column (4.6 mm I.D., 100 mm length, particle size $5{\mu}m$) with ammonium formate buffer and acetonitrile, and UV spectra and mass fragment could be confirmed. The extraction recoveries of thyroid hormones in the urine samples (pH 3) were in the range of 89.0-113.1% with solid-phase extraction by C18, followed by elution with 4 ml of methanol/ammonium hydroxide (9 : 1). The calibration curves showed good linearity with the correlation coefficients ($r^2$) varying from 0.992 to 0.998 and the detection limits of all analytes were obtained in the range of 2-4 ng/ml (3.8-13.0 pmol/ml).

• Journal of Drive and Control
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• v.20 no.4
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• pp.71-79
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• 2023

In the field of agricultural machinery, various on-field tests are conducted to measure design load for optimal design of agricultural equipment. However, field test procedures are costly and time-consuming, and there are many constraints on field soil conditions due to weather, so research on utilizing simulation to overcome these shortcomings is needed. Therefore, this study aimed to model agricultural soils using discrete element method (DEM) software. To simulate draft force, predictions are made according to travel speed and compared to field test results to validate the prediction accuracy. The measured soil properties are used for DEM modeling. In this study, the soil property measurement procedure was designed to measure the physical and mechanical properties. DEM soil model calibration was performed using a virtual vane shear test instead of the repose angle test. The DEM simulation results showed that the prediction accuracy of the draft force was within 4.8% (2.16~6.71%) when compared to the draft force measured by the field test. In addition, it was confirmed that the result was up to 72.51% more accurate than those obtained through theoretical methods for predicting draft force. This study provides useful information for the DEM soil modeling process that considers the working speed from the perspective of agricultural machinery research and it is expected to be utilized in agricultural machinery design research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3383-3397
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• 2023

Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.143-151
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• 2024

In this study, we present a mapping framework for 3D spatial reconstruction of digital twin model using navigation and perception sensors mounted on an Autonomous Surface Vehicle (ASV). For improving the level of realism of digital twin models, 3D spatial information should be reconstructed as a digitalized spatial model and integrated with the components and system models of the ASV. In particular, for the 3D spatial reconstruction, color and 3D point cloud data which acquired from a camera and a LiDAR sensors corresponding to the navigation information at the specific time are required to map without minimizing the noise. To ensure clear and accurate reconstruction of the acquired data in the proposed mapping framework, a image preprocessing was designed to enhance the brightness of low-light images, and a preprocessing for 3D point cloud data was included to filter out unnecessary data. Subsequently, a point matching process between consecutive 3D point cloud data was conducted using the Generalized Iterative Closest Point (G-ICP) approach, and the color information was mapped with the matched 3D point cloud data. The feasibility of the proposed mapping framework was validated through a field data set acquired from field experiments in a inland water environment, and its results were described.

• Analytical Science and Technology
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• v.37 no.2
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• pp.98-113
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• 2024

The current investigation entails the characterization of five degradation products (DPs) formed under different stress conditions of loteprednol using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, this study developed a stable high-performance liquid chromatography (HPLC) method for evaluating loteprednol along with impurities. The method conditions were meticulously fine-tuned which involved the exploration of the appropriate solvent, pH, flow of the mobile phase, columns, and wavelength. The method conditions were carefully chosen to successfully resolve the impurities of loteprednol and were employed in subsequent validation procedures. The stability profile of loteprednol was exposed to stress degradation experiments conducted under five conditions, and DPs were structurally characterized by employing LC-MS/MS. The chromatographic resolution of loteprednol and its impurities along with DPs was effectively achieved using a Phenomenex Luna 250 mm C18 column using 0.1 % phosphoric acid, methanol, and acetonitrile in 45:25:30 (v/v) pumped isocratically at 0.8 mL/min with 243 nm wavelength. The method produces an accurate fit calibration curve in 50-300 ㎍/mL for loteprednol and LOQ (0.05 ㎍/mL) - 0.30 ㎍/mL for its impurities with acceptable precision, accuracy, and recovery. The stress-induced degradation study revealed the degradation of loteprednol under basic, acidic, and photolytic conditions, resulting in the formation of seven distinct DPs. The efficacy of this method was validated through LC-MS/MS, which allowed for the verification of the chemical structures of the newly generated DPs of loteprednol. This method was appropriate for assessing the impurities of loteprednol and can also be appropriate for structural and quantitative assessment of its degradation products.

• The Korean Journal of Pesticide Science
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• v.19 no.4
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• pp.370-393
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• 2015

This study was conducted to compare STQ method, multi-residue method in Korean food code and QuEChERS method for validated selected and accuracy, reproducibility and efficiency. A total of 45 selected and targeted pesticides were the analyzed by GC and 5 of them were crops (apple, potato, green pepper, rice, soy bean). $R^2$ values were calculated in the standard calibration curve was over 0.990. Recovery tests were performed by three replications in two levels and the relative standard deviation of the repeated experiments was less than 30%. The average percentage of recoveries in the multi-residue method in Korean food code was 89.13%, QuEChERS method was 92.45% and STQ method was 85.28%. In addition, matrix effects in multi-residue method in Korean food code was 24.61%, QuEChERS method was 23.98% and STQ method showed 11.24%. The STQ method is easy and showed high clean-up effect in extracting the sample solution than the QuEChERS method and clean-up with C18, PLS, PSA cartridge columns. A large volume of the sample was injected in order to compensable for the problem, that occurred due to high detection limit in the analyser. When the STQ method was applied using a large volume injector, the standard calibration curve showed a higher linearity $R^2=0.990$, and method detection limit was 0.01 mg/kg. It showed an average recovery of 91.84% and the relative standard deviations of three replications repeated in two level process was less than 30% and had an average matrix effect of 17.90%.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3104-3104
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• 2001

The research described here was undertaken with the aim of monitoring, optimizing and ultimately controlling the production of heterofermentative microbes used as starters in the salami industry. The use of starter cultures in the fermented meats industry is a well-established technique used to shorten and standardize the ripening process, and to improve and control the organoleptic quality of the final product. Starter cultures are obtained by the submerged cultivation of suitable microorganisms in stirred, and sometimes aerated, fermenters where monitoring of key physiological parameters such as the concentration of biomass, substrates and metabolites suffers from the general lack of real-time measurement techniques applicable to aseptic processes. In this respect, the results of the present work are relevant to all submerged fermentation processes. Previous work on the application of on-line NIR spectroscopy to the lactic acid fermentation (Dosi et al. - Monreal NIR1995) had successfully used a system based on a measuring cell included in a circulation loop external to the fermenter. The fluid handling and sterility problems inherent in an external circulation system prompted us to explore the use of an in-line system where the NIR probe is immersed in the culture and is thus exposed to the hydrodynamic conditions of the stirred and aerated fluid. Aeration was expected to be a potential source of problems in view of the possible interference of air bubbles with the measurement device. The experimental set-up was based on an in-situ sterilizable NIR probe connected to the instrument by means of an optical fiber bundle. Preliminary work was carried out to identify and control potential interferences with the measurement, in particular the varying hydrodynamic conditions prevailing at the probe tip. We were successful in defining the operating conditions of the fermenter and the geometrical parameters of the probe (flow path, positioning, etc.) were the NIR readings were reliable and reproducible. The system thus defined was then used to construct and validate calibration curves for tile concentration of biomass, carbon source and major metabolites of two different microorganisms used as salami starters. Real-time measurement of such parameters coupled with the direct interfacing of the NIR instrument with the PC-based measurement and control system of the fermenter enabled the development of automated strategies for the interactive optimization of the starter production process.