• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.199-208
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• 2021

Environmental DNA (eDNA) metabarcoding is effective method with high detection sensitivity for evaluating fish biodiversity and detecting endangered fish from natural water samples. We compared the richness of operational taxonomic units(OTUs) and composition of freshwater fishes according to filters(cellulose nitrate filter vs. glass fiber filter), extraction kits(DNeasy2^® Blood & Tissue Kit vs. DNeasy2^® PowerWater Kit), primer sets (12S rDNA vs. 16S rDNA), and PCR methods (conventional PCR vs. touchdown PCR) to determine the optimal conditions for metabarcoding analysis of Korean freshwater fish. The glass fiber filter and DNeasy2^® Blood & Tissue Kit combination showed the highest number of freshwater fish OTUs in both 12S and 16S rDNA. Among the four types, the primer sets only showed statistically significant difference in the average number of OTUs in class Actinopterygii (non-parametric Wilcoxon signed ranks test, p=0.005). However, there was no difference in the average number of OTUs in freshwater fish. The species composition also showed significant difference according to primer sets (PERMANOVA, Pseudo-F=6.9489, p=0.006), but no differences were observed in the other three types. The non-metric multidimensional scaling (NMDS) results revealed that species composition clustered together according to primer sets based on similarity of 65%; 16S rDNA primer set was mainly attributed to endangered species such as Microphysogobio koreensis and Pseudogobio brevicorpus. In contrast, the 12S rDNA primer set was mainly attributed to common species such as Zacco platypus and Coreoperca herzi. This study provides essential information on species diversity analysis using metabarcoding for environmental water samples obtained from rivers in Korea.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Genomics & Informatics
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• v.18 no.3
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• pp.33.1-33.7
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• 2020

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Pediatric Infection and Vaccine
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• v.26 no.2
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• pp.81-88
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• 2019

Purpose: Early detection of Mycoplasma pneumoniae is important for appropriate antimicrobial therapy in children with pneumonia. This study aimed to evaluate the diagnostic value of a rapid antigen test kit in detecting M. pneumoniae from respiratory specimens in children with lower respiratory tract infection (LRTI). Methods: A total of 215 nasopharyngeal aspirates (NPAs) were selected from a pool of NPAs that had been obtained from children admitted for LRTI from August 2010 to August 2018. The specimens had been tested for M. pneumoniae by culture and stored at $-70^{\circ}C$ until use. Tests with Ribotest $Mycoplasma^{(R)}$ were performed and interpreted independently by two investigators who were blinded to the culture results. Results: Among the 215 NPAs, 119 were culture positive for M. pneumoniae and 96 were culture negative. Of the culture-positive specimens, 74 (62.2%) were positive for M. pneumoniae by Ribotest $Mycoplasma^{(R)}$, and 92 of the 96 (95.8%) culture-negative specimens were negative for M. pneumoniae by Ribotest $Mycoplasma^{(R)}$. When culture was used as the standard test, the sensitivity and specificity of Ribotest $Mycoplasma^{(R)}$ were 62.2% and 95.8%, respectively. Additionally, the positive predictive value, negative predictive value, and overall agreement rates with Ribotest $Mycoplasma^{(R)}$ were 94.9%, 67.2%, and 77.2%, respectively. Conclusions: A positive test result of Ribotest $Mycoplasma^{(R)}$ suggests a high likelihood of culture-positive M. pneumoniae infection. However, a negative test result should be interpreted with caution because nearly one-third of negative test results reveal culture-positive M. pneumoniae infections.

• Journal of the Korean Applied Science and Technology
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• v.36 no.3
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• pp.1028-1040
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• 2019

The current study was performed to investigate the magnitude of exercise-induced muscle damage (EIMD) after downhill running (DR) of different intensities and to examine the availability of muscle echo intensity as biomarkers to detect regional damage within quadriceps muscle group (QG) following DR. Healthy college-age men (n=11) were experienced twice DR sessions [$50%HR_{max}$ DR, LDR; $70%HR_{max}$ DR, HDR] separated by a 2-week wash-out period with the random order. After DR, severity of EIMD according to exercise intensity were determined by serum creatine kinase (CK) activity, muscle tenderness, and neuromuscular function indicators such as a maximal voluntary isometric contraction (MVIC) and range of motion (ROM). Transvaginal B-mode imaging had been employed to evaluate regional muscle echo intensity within QG [rectus femoris, RF; vastus lateralis, VL; vastus medialis, VM; vastus intermedius, VI]. After both DR sessions, changes in serum CK activity and muscle tenderness have tended to more increase in HDR compared to those of LDR. There was a significant interaction effect between exercise intensity during DR and the time course of serum CK activity(p<.05). However, there were no statistical differences between sessions in muscle tenderness. The time course of changes in the neuromuscular functions after DR were similar to those of regional muscle echo intensity regardless exercise intensity. Although neuromuscular function showed to decline in HDR more than those of LDR after DR, no statistical differences between sessions. In contrast, there were significant interaction effects between sessions and time course of changes in RF and VL muscle echo intensity(p<.01), but not shown in those of VI and VM. These results indicated that each muscles within the QG show different response profiles for EIMD during DR, exercise intensity influences on these responses as well. In particular, current findings suggested that muscle echo intensity derived from ultrasound imaging is capable of detecting regional muscle damage in QG following DR.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.3
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• pp.309-315
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• 2019

Cervical cancer is the fourth most common malignant neoplasm in women worldwide. Most cases of cervical cancer are caused by an infection by the human papillomavirus. Molecular diagnostic methods have emerged to detect the HPV for sensitivity, specificity, and objectivity. In particular, real-time PCR has been introduced to acquire a more sensitive target DNA or RNA. RNA extraction and complementary DNA synthesis are proceeded before performing real-time PCR targeting RNA. To identify an adequate and sensitive cDNA synthesis kit, this study evaluated the two commonly used kits for cDNA synthesis. The results show that the $R^2$ and efficiency (%) of the two cDNA synthesis kits were similar in the cervical cancer cell lines. On the other hand, the Takara kit compared to Invitrogen kit showed P<0.001 in the $10^2$ and $10^3$ SiHa cell count. The Takara kit compared to the Invitrogen kit showed P<0.001 in the $10^1$ and $10^2$ HeLa cell count. Furthermore, 8, 4, 2, 1, and 0.5 ml of forty exfoliated cell samples were used to compare the cDNA synthesis kits. The Takara kit compared to the Invitrogen kit showed P<0.01 in 8, 4, and 1 ml and P<0.05 in 0.5 mL. The study was performed to identify the most appropriate cDNA synthesis kit and suggests that a cDNA synthesis kit could affect the real-time PCR results.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.74-78
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• 2018

Purpose $[^{11}C]$acetate has been proved useful in detecting the myocardial oxygen metabolism and various malignancies including prostate cancer, hepatocellular carcinoma, renal cell carcinoma and brain tumors. The purpose of study was to improve the radiosynthesis yield of $[^{11}C]$acetate on a automated radiosynthesis module. Materials and Methods $[^{11}C]$acetate was prepared by carboxylation of grignard reagent, methylmagnesium chloride, with $[^{11}C]$$CO_2$ gas, followed by hydrolysis with 1 mM acetic acid and purification using solid phase extraction cartridges. The effect of the reaction temperature ($0^{\circ}C$, $10^{\circ}C$, $-55^{\circ}C$) and cyclotron beam time (10 min, 15 min, 20 min, 25 min) on the radiosynthesis yield were investigated in the $[^{11}C]$acetate labeling reaction. Results The maximum radiosynthesis yield was obtained at $-10^{\circ}C$ of reaction temperature. The radioactivities of $[^{11}C]$acetate acquired at $-10^{\circ}C$ reaction temperature was 2.4 times higher than those of $[^{11}C]$acetate acquired at $-55^{\circ}C$. Radiosynthesis yield of $[^{11}C]$acetate increased with increasing cyclotron beam time. Conclusion This study shows that radiosynthesis yield of $[^{11}C]$acetate highly dependent on reaction temperature. The best radiosynthesis yield was obtained in reaction of grignard reagent with $[^{11}C]$$CO_2$ at $-10^{\circ}C$. This radiolabeling conditions will be ideal for routine clinical application.

• Pediatric Infection and Vaccine
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• v.28 no.2
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• pp.92-100
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• 2021

Purpose: Rapid detection of etiologic organisms is crucial for initiating appropriate therapy in patients with central nervous system (CNS) infection. This study aimed to evaluate the diagnostic value of the BioFire^® Meningitis/Encephalitis (ME) panel in detecting etiologic organisms in cerebrospinal fluid (CSF) samples from febrile infants. Methods: CSF samples from infants aged <90 days who were evaluated for fever were collected between January 2016 and July 2019 at the Seoul National University Children's Hospital. We performed BioFire^® ME panel testing of CSF samples that had been used for CSF analysis and conventional tests (bacterial culture, Xpert^® enterovirus assay, and herpes simplex virus-1 and -2 polymerase chain reaction) and stored at -70℃ until further use. Results: In total, 72 (24 pathogen-identified and 48 pathogen-unidentified) CSF samples were included. Using BioFire^® ME panel testing, 41 (85.4%) of the 48 pathogen-unidentified CSF samples yielded negative results and 22 (91.7%) of the 24 pathogen-identified CSF samples yielded the same results (enterovirus in 19, Streptococcus agalactiae in 2, and Streptococcus pneumoniae in 1) as those obtained using the conventional tests, thereby resulting in an overall agreement of 87.5% (63/72). Six of the 7 pathogen-unidentified samples were positive for human parechovirus (HPeV) via BioFire^® ME panel testing. Conclusions: Compared with the currently available etiologic tests for CNS infection, BioFire^® ME panel testing demonstrated a high agreement score for pathogen-identified samples and enabled HPeV detection in young infants. The clinical utility and cost-effectiveness of BioFire^® ME panel testing in children must be evaluated for its wider application.