• Nuclear Engineering and Technology
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• v.15 no.2
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• pp.142-148
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• 1983

Distribution coefficients between cation exchange resin (Dowex 50W$\times$8) and $\alpha$-hydroxyisobutric acid ($\alpha$-HIBA) are measured in order to separate traces of Sm, Eu, Gd and Dy from nuclear material. Individual separations are performed by pH gradient technique with 0.40M $\alpha$-HIBA from 3.40 to 3.60 in cation exchange resin after a group separation. Each of separated elements is determined with a fluorometric method except Gd by colorimetry. The results are applied to analyze Sm, Eu, Gd and Dy in magnesium diuranate (yellow cake).

• YAKHAK HOEJI
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• v.36 no.4
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• pp.370-378
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• 1992

A simple and sensitive high performance liquid chromatographic method to quantitate ${\alpha}-keto$ acids in serum and urine was investigated. ${\alpha}-Keto$ acids react with 1,2-diamino-4,5-methylenedioxybenzene (DMB) in the presence of 2-mercapto-ethanol and sodium hydrogen sulfite to form highly fluorescent derivatives, substituted 6,7-methylenedioxyquinoxalinol. The derivatization procedure was performed in water bath at $100^{\circ}C$, and completed within 50 min. By the use of a reversed-phase column and multi-step gradient with two solvents, a mixture containing twelve of these derivatives were efficiently resolved within 35 minutes. The optimal wavelengh of the fluorescence detector are ${\lambda}_{ex}=364\;nm$ and ${\lambda}_{em}=445\;nm$. The quantitation of the individual ${\alpha}-Keto$ acids was reproducible with relative standard deviation of $3.0{\sim}7.9%$ and had a detection limits of $10{\sim}60$ fmol, except for p-hydroxyphenylpyruvic acid (960 fmol).

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.401-411
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• 2021

This study provides comprehensive assessment results for the most recent high-resolution regional climatology in the East/Japan Sea by comparing with the various existing climatologies. This new high-resolution climatology is generated based on the Optimal Interpolation (OI) method with individual profiles from the World Ocean Database and gridded World Ocean Atlas provided by the National Centers for Environmental Information (NCEI). It was generated from the recent previous study which had a primary focus to solve the abnormal horizontal gradient problem appearing in the other high-resolution climatology version of NCEI. This study showed that this new OI field simulates well the meso-scale features including closed-curve temperature spatial distribution associated with eddy formation. Quantitative spatial variability was compared to the other four different climatologies and significant variability at 160 km was presented through a wavelet spectrum analysis. In addition, the general improvement of the new OI field except for warm bias in the coastal area was confirmed from the comparison with serial observation data provided by the National Fisheries Research and Development Institute's Korean Oceanic Data Center.

• Coupled systems mechanics
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• v.8 no.1
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• pp.1-17
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• 2019

The present paper deals with delamination fracture analyses of the multilayered functionally graded non-linear elastic Symmetric Split Beam (SSB) configurations. The material is functionally graded in both width and height directions in each layer. It is assumed that the material properties are distributed non-symmetrically with respect to the centroidal axes of the beam cross-section. Sine laws are used to describe the continuous variation of the material properties in the cross-sections of the layers. The delamination fracture is analyzed in terms of the strain energy release rate by considering the balance of the energy. A comparison with the J-integral is performed for verification. The solution derived is used for parametric analyses of the delamination fracture behavior of the multilayered functionally graded SSB in order to evaluate the effects of the sine gradients of the three material properties in the width and height directions of the layers and the location of the crack along the beam width on the strain energy release rate. The solution obtained is valid for two-dimensional functionally graded non-linear elastic SSB configurations which are made of an arbitrary number of lengthwise vertical layers. A delamination crack is located arbitrary between layers. Thus, the two crack arms have different widths. Besides, the layers have individual widths and material properties.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.111-122
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• 2021

Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

• Food Science and Industry
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• v.50 no.1
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• pp.2-10
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• 2017

Human have eaten various traditional fermented foods for a numbers of million years for health benefit as well as survival. The beneficial effects of fermented foods have been resulted from complex microbial communications within the fermented foods. Therefore, the holistic approaches for individual identification and complete microbial profiling involved in their communications have been of interest to food microbiology fields. Microbiome is the ecological community of microorganisms that literally share our environments including foods as well as human body. However, due to the limitation of culture-dependent methods such as simple isolations of just culturable microorganisms, the culture-independent methods have been consistently developed, resulting in new light on the diverse non-culturable and hitherto unknown microorganisms, and even microbial communities in the fermented foods. For the culture-independent approaches, the food microbiome has been deciphered by employing various molecular analysis tools such as fluorescence in situ hybridization, quantitative PCR, and denaturing gradient gel-electrophoresis. More recently, next-generation-sequencing (NGS) platform-based microbiome analysis has been of interest, because NGS is a powerful analytical tool capable of resolving the microbiome in respect to community structures, dynamics, and activities. In this overview, the development status of analysis tools for the fermented food microbiome is covered and research trend for NGS-based food microbiome analysis is also discussed.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.499-510
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• 2022

This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

• Computers and Concrete
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• v.33 no.2
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• pp.137-145
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• 2024

The technique of experimentally determining concrete's compressive strength for a given mix design is time-consuming and difficult. The goal of the current work is to propose a best working predictive model based on different machine learning algorithms such as Gradient Boosting Machine (GBM), Stacked Ensemble (SE), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), and Deep Learning (DL) that can forecast the compressive strength of ternary geopolymer concrete mix without carrying out any experimental procedure. A geopolymer mix uses supplementary cementitious materials obtained as industrial by-products instead of cement. The input variables used for assessing the best machine learning algorithm not only include individual ingredient quantities, but molarity of the alkali activator and age of testing as well. Myriad statistical parameters used to measure the effectiveness of the models in forecasting the compressive strength of ternary geopolymer concrete mix, it has been found that GBM performs better than all other algorithms. A sensitivity analysis carried out towards the end of the study suggests that GBM model predicts results close to the experimental conditions with an accuracy between 95.6 % to 98.2 % for testing and training datasets.

• Korean Journal of Medicinal Crop Science
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• v.27 no.5
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• pp.322-329
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• 2019

Background: Studies have suggested that the northern provinces of Gangwon-do are good sites for licorice (Glycyrrhiza uralensis Fisch.) cultivation in Korea, as they have similar temperatures to its original locations in northern China. However, poor growth and freezing injury are often reported in Korea. Therefore, it is necessary to reassess the domestic cultivation site of licorice. Methods and Results: To determine the optimum temperature for cultivating licorice, the growth, yield, and pharmacological characteristics of G. uralensis were assessed in a temperature gradient tunnel at Eumseong, Chungcheongbuk-do, Korea in 2017. Plant height increased until the temperature rose to $5.9^{\circ}C$ above the local external temperature. Yield (㎏/10a) increased by 46.9% when the growing temperature was $1.5^{\circ}C$ to $3.0^{\circ}C$ (T2) above the external temperature and by 72.6% when the growing temperature was $3.0^{\circ}C-4.5^{\circ}C$ (T3) above the external temperature. However, a difference of $4.5^{\circ}C-5.9^{\circ}C$ (T4) above the external temperature, decreased the yield by 9.8% compared to that at T2. The glycyrrhizin content of G. uralensis roots in each temperature band was 0.72%, 0.53%, 0.91%, and 0.84% (T1, T2, T3, T4), these differences appear to result form individual plant variation rather than growth temperature. Conclusions: Based on the results of this study, we estimate that the temperature-based optimum cultivation site for G. uralensis in Korea is the south central region, rather than the northern province of Gangwon-do. Improvement in growth and yield maybe observed if the plantations in the central Jecheon (Chungcheongbuk-do, Korea) are expanded into the south central region.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.66.3-67
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• 2015

Without scrutinizing reflection, the plasma comprising a coronal loop is usually regarded to reside within a flux rope. This picture seems to have been adopted from laboratory plasma pinches, in which a plasma of high density and pressure is confined in the vicinity of the flux rope axis by magnetic tension and magnetic pressure of the concave inward magnetic field. Such a configuration, in which the plasma pressure gradient and the field line curvature vector are almost parallel, however, is known to be vulnerable to ballooning instabilities (to which belong interchange instabilities as a subset). In coronal loops, however, ideal MHD (magnetohydrodynamic) ballooning instabilities are impeded by a very small field line curvature and the line-tying condition. We, therefore, focus on non-ideal (resistive) effects in this study. The footpoints of coronal loops are constantly under random motions of convective scales, which twist individual loop strands quite randomly. The loop strands with the axial current of the same direction tend to coalesce by magnetic reconnection. In this reconnection process, the plasma in the loop system is redistributed in such a way that a smaller potential energy of the system is attained. We have performed numerical MHD simulations to investigate the plasma redistribution in coalescence of many small flux ropes. Our results clearly show that the redistributed plasma is more accumulated between flux ropes rather than near the magnetic axes of flux ropes. The Joule heating, however, creates a different temperature distribution than the density distribution. Our study may give a hint of which part of magnetic field we are looking to in an observation.