• Journal of Korean Society for Atmospheric Environment
• /
• v.34 no.3
• /
• pp.493-507
• /
• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• Asian-Australasian Journal of Animal Sciences
• /
• v.21 no.12
• /
• pp.1703-1709
• /
• 2008

As genetic markers, single nucleotide polymorphisms (SNP) are very appropriate for the development of genetic tests for economic traits in livestock. Several microsatellite markers have been identified as useful markers for the genetic improvement of Hanwoo. Among those markers, ILSTS035 was recently mapped at a similar position with four SNPs (AH1_11, AH1_9, 31465_446, and 12273_165) in a linkage map of EST-based SNP in BAT6. Among the four SNPs, two SNPs (31465_446 and 12273_165) were analyzed using BLAST at the NCBI web site. The sequences including the 12273_165 SNP were identified at the intron region within the LOC534614 gene on the gene sequence map (Bos taurus NCBI Map view, build 3.1). The LOC534614 gene represents a protein similar to myosin heavy chain, fat skeletal muscle, embryonic isoform 1 in the dog, and myosin_1 (Myosin heavy chain D) in Macaca mulatta. In cattle, the myosin heavy chain was associated with muscle development. The phenotypic data for growth and carcass traits in the 415 animals were analyzed by the mixed ANCOVA (analysis of covariance) linear model using PROC GLM module in SAS v9.1. By the genotyping of Hanwoo individuals (n = 415) to evaluate the association of SNP with growth and carcass traits, it was shown that the 12273_165 SNP region within LOC534614 may be a candidate marker for growth. The results of the statistical analyses suggested that the genotype of the 12273_165 SNP significantly affected birth weight, weight of the cattle at 24 months of age, average daily gain and carcass cold weight (p<0.05). Consequently, the 12273_165 SNP polymorphisms at the LOC534614 gene may be associated with growth in Hanwoo, and functional validation of polymorphisms in LOC534614 should be performed in the future.

• Structural Engineering and Mechanics
• /
• v.62 no.5
• /
• pp.567-576
• /
• 2017

Structural failures are undesirable events that devastate the construction industry resulting in loss of life, injury, huge property loss, and also affect the economy of the region. Roof truss failures occur mainly due to excessive loading, improper fabrication, deterioration, inadequate repair, etc. Although very rare, a roof truss may even fail due to inappropriate location of supports. One such case was reported from the recent failure of a steel roof truss used in an indoor stadium at Kargil in India. Kargil region, being mountainous in nature, receives heavy snowfall and hence the steel roof trusses are designed for heavy snow loads. Due to inappropriate support location, the indoor stadium's steel roof truss had failed under heavy snow load for which it was designed and became an interesting structural engineering problem. The failure observed was primarily in terms of yielding of the bottom chord under the supports, leading to partial collapse of the roof truss. This paper summarizes the results of laboratory tests and analytical studies that focused on the validation of the proposed remedial measure for rehabilitating this distressed steel roof truss. The study presents the evaluation of (i) significant reduction in strength and stiffness of the distressed truss resulting in its failure, (ii) desired recovery in both strength and stiffness of the rectified truss contributed by the proposed remedial measure. Three types of models i.e., ideal truss model, as build truss model and rectified truss model were fabricated and tested under monotonic loading. The structural configuration and support condition varied in all the three models to represent the ideal truss, distressed truss and the rectified truss. To verify the accuracy of the experimental results, an analytical study was carried out and the results of this analytical study are compared with the experimental ones.

• The Korean Journal of Mycology
• /
• v.44 no.1
• /
• pp.8-15
• /
• 2016

Fungal contamination is a detrimental factor affecting sawdust media-based shiitake cultivation in greenhouses. During fungal monitoring of greenhouses used for shiitake cultivation, eight fungal species were isolated and identified from indoor air and mushroom flies collected in the greenhouses. The current study reported five species as new in Korea, viz. Ascochyta hordei, Discosia artocreas, Mucor nidicola, Perenniporia medulla-panis, and Pseudozyma prolifica, and confirmed two species, Penicillium charlesii and Penicillium brevicompactum, which were previously recorded in Korea without molecular taxonomic validation. The morphological characteristics and phylogenetic relationships based on nucleotide sequences of the internal transcribed spacer rDNA region or calmodulin gene were described for all identified species.

• Journal of the Society of Naval Architects of Korea
• /
• v.38 no.1
• /
• pp.52-61
• /
• 2001

It is necessary to obtain the well-documented local flow measurement data for the validation of CFD prediction of hydrodynamic performance. In the present paper the local flow fields around the stern region of a VLCC model with drift angles of $0^{\circ},\;5^{\circ},\;and\;10^{\circ}$ are measured. Mean velocity components are documented at St. 2 and A.P. of both port and starboard side of KVLCC in KRlSO towing tank. Flow information associated with the formation of four discrete vortices in the stern region is explored. The present experimental data can provide a good test case to validate the accuracy of numerical modeling for stern flow and maneuverability prediction of modern tanker hull forms.

• The Korea Journal of Herbology
• /
• v.37 no.5
• /
• pp.9-16
• /
• 2022

Objectives : The purpose of this study is to report that applying the genetic discrimination method to Pinelliae Tuber is suitable as a countermeasure for the limitations of morphological identification announced publicly in the Ministry of Food and Drug Safety(MFDS). Methods : Randomly selected fifty samples in Pinelliae Tuber imported from China were used for morphological and genetic identification. The morphological identification was applied method announced publicly by the MFDS. The traits of morphological identification were classified as Pinellia ternata, P. tripartita, Pinellia pedatisecta, and Typhonium flagelliforme, according to the formation of tuberous root and tuber morphology. The genetic identifications were conducted by Sequence Characterized Amplified Region(SCAR) marker and DNA barcoding analysis for cross-validation, respectively. SCAR marker was verified according to the presence or absence of amplicon through PCR amplification using species-specific primers. DNA barcoding analysis used sequence information of the matK region. Results : As a result of the morphological identification, 27 out of 50 samples were identified as original species 'P. ternata' of genuine 'Pinelliae Tuber', and 23 were identified as adulterant species 'P. pedatisecta'. Unlike this, the genetic identification was identified as the original species 'P. ternata' in all 50 samples in the SCAR marker and matK regional sequence analysis. Conclusions : Pinelliae Tuber of morphological mutant that can not be classified by morphological identification is imported from China. The SCAR marker would be used as accurate and efficient assays for species identification of the morphological mutant.

• Wind and Structures
• /
• v.37 no.1
• /
• pp.25-38
• /
• 2023

Due to the complexity and difficulty in meeting the multiphase flow complexity, similarity, and multiscale characteristics, the mechanism of snow drift is so complicated that the snow deposition prediction is still inaccurate and needs to be far improved. Meanwhile, the validation of prediction methods is also limited due to a lack of field-measured data about snow deposition. To this end, a field measurement activity about snow deposition around a cube with time was carried out, and the snow accumulation process was measured under blowing snow conditions in northwest China. The maximum snow depth, snow profile, and variation in snow depth around the cube were discussed and analyzed. The measured results indicated three stages of snow accumulation around the cube. First, snow is deposited in windward, lateral and leeward regions, and then the snow depth in windward and lateral regions increases. Secondly, when the snow in the windward region reaches its maximum, the downwash flow erodes the snow against the front wall. Meanwhile, snow range and depth in lateral regions have a significant increase. Thirdly, a narrow road in the leeward region is formed with the increase in snow range and depth, which results in higher wind speed and reforming snow deposition there. The field measurement study in this paper not only furthers understanding of the snow accumulation process instead of final deposition under complex conditions but also provides an important benchmark for validating prediction methods.

• Imaging Science in Dentistry
• /
• v.54 no.1
• /
• pp.33-41
• /
• 2024

Purpose: The aims of this study were to create a deep learning model to distinguish between nasopalatine duct cysts (NDCs), radicular cysts, and no-lesions (normal) in the midline region of the anterior maxilla on panoramic radiographs and to compare its performance with that of dental residents. Materials and Methods: One hundred patients with a confirmed diagnosis of NDC (53 men, 47 women; average age, 44.6±16.5 years), 100 with radicular cysts (49 men, 51 women; average age, 47.5±16.4 years), and 100 with normal groups (56 men, 44 women; average age, 34.4±14.6 years) were enrolled in this study. Cases were randomly assigned to the training datasets (80%) and the test dataset (20%). Then, 20% of the training data were randomly assigned as validation data. A learning model was created using a customized DetectNet built in Digits version 5.0 (NVIDIA, Santa Clara, USA). The performance of the deep learning system was assessed and compared with that of two dental residents. Results: The performance of the deep learning system was superior to that of the dental residents except for the recall of radicular cysts. The areas under the curve (AUCs) for NDCs and radicular cysts in the deep learning system were significantly higher than those of the dental residents. The results for the dental residents revealed a significant difference in AUC between NDCs and normal groups. Conclusion: This study showed superior performance in detecting NDCs and radicular cysts and in distinguishing between these lesions and normal groups.

• Journal of Plant Biotechnology
• /
• v.42 no.1
• /
• pp.60-70
• /
• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.17 no.11
• /
• pp.1050-1059
• /
• 2005

Heat and $SF_6$ gas dispersions over a complex terrain were investigated using wind tunnel. The wind speed, temperature and concentration profiles were measured for the 1/1000 scale complicated terrain model in an Eiffel type boundary layer wind tunnel with test section of 2.5m in height and 4.5m in width. The scale model was mounted on the top of a plate which can rotate with respect to the approaching wind. Dispersion processes from a continuous emission source driven by various wind direction were investigated, including plume climbing over the steep up-slope of the mountain and down-spreading toward the lower level of the valley. Extensive dispersion experiment data (wind speeds and concentration profiles) were provided for verification and validation of dispersion models. Under the identical flow and emission conditions, the independently measured profiles of the temperature and $SF_6$ concentration showed an excellent agreement which ensured the credibility of the results.