• Journal of Biomedical Engineering Research
• /
• v.42 no.4
• /
• pp.150-158
• /
• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.45-51
• /
• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.37 no.6
• /
• pp.528-533
• /
• 1992

Soybean seeds contain lipoxygenase, which is responsible for the objectionable beany flavors in soybean seeds. The isozymes of lipoxygenase (1$\times$1, 1$\times$2, 1$\times$3) were discovered in United States of America, Japan, and Korea, and the mode of inheritance of the mutant genes was determined. This investigation was conducted to screen lipoxygenase-1, 2, and 3 lacking soybean lines from the Korean soybean land race population. Two lipoxygenase-1lacking lines, KAS 610-8 and KAS 621-8 were found in this investigation. In general, lipoxygenase acking varieties were small in seed size and low in oil content. A severe pod borer damage was observed in the two selected lipoxygenase-1 lacking lines. Lipoxygenase lacking line was not found in Korean wild soybean population used in this study and the lipoxygenase lacking lines were found only in Kyung-Nam province and the results imply that lipoxygenase lacking mutants were induced recently in cultivars.

• Journal of Pharmacopuncture
• /
• v.26 no.1
• /
• pp.27-37
• /
• 2023

Objectives: Moroccan Arbutus unedo is an essential medicinal plant; however, little is known about the biological properties of its leaves mentioned in Moroccan traditional medicine. Methods: Various standard experiments were performed to evaluate the phytochemical, antidiabetic, antioxidant, antibacterial, and acute and sub-chronic toxicity characteristics of A. unedo leaves. Results: Phytochemical screening led to the identification of several phytochemical classes, including tannins, flavonoids, terpenoids, and anthraquinones, with high concentrations of polyphenols (31.83 ± 0.29 mg GAEs/g extract) and flavonoids (16.66 ± 1.47 mg REs/g extract). Further, the mineral analysis revealed high levels of calcium and potassium. A. unedo extract demonstrated significant antioxidant and anti-diabetic activities by inhibiting α-amylase (1.350 ± 0.32 g/mL) and α-glucosidase (0.099 ± 1.21 g/mL) compared to the reference drug Acarbose. Also, the methanolic extract of the plant exhibited significantly higher antibacterial activity than the aqueous extract. Precisely, three of the four examined bacterial strains exhibited substantial susceptibility to the methanolic extract . Minimum bactericidal concentration (MBC)/minimum inhibitory concentration (MIC) values indicated that A. unedo harbor abundant bactericidal compounds. For toxicological studies, mice were administered with A. unedo aqueous extract at single doses of 2,000 and 5,000 mg/kg. They did not exhibit significant abnormal behavior, toxic symptoms, or death during the 14-day acute toxicity test and the 90-day sub-chronic toxicity test periods. The general behavior, body weight, and hematological and biochemical status of the rats were assessed, revealing no toxicological symptoms or clinically significant changes in biological markers observed in the mice models, except hypoglycemia, after 90 days of daily dose administration. Conclusion: The study highlighted several biological advantages of A. unedo leaves without toxic effects in short-term application. Our findings suggest that conducting more comprehensive and extensive in vivo investigations is of utmost importance to identify molecules that can be formulated into pharmaceuticals in the future.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.111-111
• /
• 2021

메콩지역은 최근 연 7%에 육박하는 경제성장률을 달성하며 아세안의 고성장을 지속 견인하고 있으나, 기후변화 및 급속한 도시화로 매년 가뭄·홍수 등 물 관련 재해 발생 빈도 및 강도 증가와 이에 따른 상·하류 국가간 물 분쟁 등으로 인해 메콩지역 지속가능 발전에 지장이 초래되고 있다. 이에 한국과 미국은 메콩우호국(Friends of the Lower Mekong, FLM) "메콩지역 수자원 데이터 관리 및 정보공유 강화에 관한 공동성명(2018년 8월)"을 계기로 메콩유역의 실시간 수자원 변동 모니터링 및 분석과 수자원 데이터 공동활용 역량을 강화하여 효율적이고 과학적인 수자원관리 지원과 함께 한국의 신남방정책과 미국의 인도-태평양 전략 시너지효과를 극대화하고자 메콩 주변국 재해경감 및 수자원 데이터 활용 역량강화를 위한 글로벌 위성기반 수문자료의 생산·활용 및 홍수·가뭄 등의 수재해 분석기술을 개발하고 있다. 여기에는 한국 K-water의 물관리 기술과 미국 NASA, USACE의 위성활용 및 수자원분석 기술을 접목하여 메콩지역의 체계적인 물관리 및 재해로부터 안전성 확보 기여에 목표를 두고 연구를 진행 중에 있다. 본 연구에서는 전 세계적으로 광범위하게 활용되고 있는 미공병단(USACE, U.S. Army Corps of Engineers)의 HEC software 프로그램을 메콩 시범지역(pilot area)에 적용하여 수리/수문모델 구축을 진행코자 한다. 구축되는 모형은 유역 상류 댐의 연계 모의운영 및 하류 홍수분석이 동시 가능한 HEC-RTS(Real-Time Simulation)로 이는 HEC-HMS, -ResSim, -RAS와 -FIA 모형이 순차적으로 결합된 수리/수문 모델링 시스템이다. 모형의 시범적용 지역은 현지 메콩위원회(MRC, Mekong River Comission)의 의견 등을 반영, 메콩강 하류지역(Lower Mekong) 본류 유역에 위성 자료 활용 및 준실시간(near real-time)으로 댐 모의운영 등을 고려할 수 있는 JingHong댐(중국 란창강 최하류)에서 라오스 Xayaburi댐(메콩강 최상류)까지의 구간을 선정하였다. 한편, 금번 연구에서는 HEC-RTS 중 HMS 모형 적용을 중심으로 가용한 위성자료(GPM IMERG)와 K-LIS 지표 모형 생산 자료를 활용하여 과거 홍수사상에 대한 모의를 고려하였다. 아울러, 연구에서 구축된 HMS 모형은 HEC-RTS에 포함되어 메콩 시범지역의 종합적 수리/수문분석에 적용될 예정이다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.121-121
• /
• 2022

한국과 미국은 2018년 8월에 발표한 메콩우호국(Friends of the Lower Mekong, FLM) "메콩지역 수자원 데이터 관리 및 정보공유 강화에 관한 공동성명"을 계기로 메콩유역의 실시간 수자원 변동 모니터링 및 분석과 수자원 데이터 공동활용 역량을 강화하여 효율적이고 과학적인 수자원관리 지원과 함께 한국의 신남방정책과 미국의 인도-태평양 전략 시너지효과를 극대화하고자 메콩 주변국 재해경감 및 수자원 데이터 활용 역량강화를 위한 글로벌 위성기반 수문자료의 생산·활용 및 홍수·가뭄 등의 수재해 분석기술을 개발하고 있다. 여기에는 한국 K-water의 물관리 기술과 미국 NASA, USACE의 위성활용 및 수자원분석 기술을 접목하여 메콩지역의 체계적인 물관리 및 재해로부터 안전성 확보 기여에 목표를 두고 연구를 진행 중에 있다. 본 연구에서는 전 세계적으로 광범위하게 활용되고 있는 미공병단(USACE, U.S. Army Corps of Engineers)의 HEC software 프로그램을 메콩 시범지역(pilot area)에 적용하여 수리/수문모델 구축을 진행하고 있다. 구축되는 모형은 유역 상류 댐의 연계 모의운영 및 하류 홍수분석이 동시 가능한 HEC-RTS(Real-Time Simulation)로 이는 HEC-HMS, -ResSim, -RAS와 -FIA 모형이 순차적으로 결합된 수리/수문 모델링 시스템이다. 모형의 시범적용 지역은 현지 메콩위원회(MRC, Mekong River Comission)의 의견 등을 반영, 메콩강 하류지역(Lower Mekong) 본류 유역에 위성자료 활용 및 준실시간(near real-time)으로 댐 모의운영 등을 고려할 수 있는 JingHong댐(중국 란창강 최하류)에서 라오스 Xayaburi댐(메콩강 최상류)까지의 구간을 선정하였으며, 전년도에는HEC-RTS 중 HMS(Hydrologic Modeling System) 모형 적용을 중심으로 가용한 위성자료(GPM IMERG)를 활용하여 과거 홍수사상에 대한 모의를 고려한 강우-유출모형의 구축을 완료하였다. 이에 연속하여 금년도에는 동일유역 내 하천 단면 등이 확보된 Chiang Saen 지점에서 Xayaburi 댐까지의 구간에 대해 RAS(River Analysis System)을 구축할 예정으로 구축된 RAS 모형은 HEC-RTS에 포함되어 메콩 시범지역의 종합적 수리/수문분석에 적용될 예정이다.

• Journal of Naturopathy
• /
• v.8 no.1
• /
• pp.1-10
• /
• 2019

Purpose: The purpose of this study was to investigate the increase or decrease of important intestinal beneficial bacteria and inhibitory bacteria in 30 stools of clinical subjects after ingesting Zen fermentation broth as a mixed microbial fermentation solution for eight weeks. Methods: Intestinal bacteria were identified by PCR amplification using specific primers. Results: Bifidobacterium genus gi% of test group ingested Zen-fermented broth was 55.15% before and 70.1% after ingestion, so it was a significant difference (p<.009). Lactobacillus genus of the test group was 46.87% before and 60.91% after ingestion, it was a significant difference (p<.01). Clostridium genus of the test group was 85.64% before and 65.99% after ingestion. There was a significant difference (p<.017) as the pre-post-difference decreased to -19.65%. Bacteroides genus of the test group was 17.11% before and 20.22% after ingestion. There was a significant difference (p<.048) as the pre-post-difference increased to 3.11%. Prevotella genus of the test group was 14.01% before and 16.79% after ingestion, so it was not a significant difference. Conclusions: Intestinal bacteria increased the proliferation of beneficial bacteria and suppressed harmful bacteria in the intestines after ingesting the Zen-fermented broth of the mixed microorganism. The Zen fermentation broth evaluated as a beneficial drink for intestinal health.

• Journal of Naturopathy
• /
• v.8 no.1
• /
• pp.21-28
• /
• 2019

Purpose: The purpose of this study was to examine the impact of 12 Lactobacillus strains and four yeast mixed fermentation broth on the blood characteristics of subjects who consumed for eight weeks. Methods: Blood samples taken from the subjects and clinicopathologic blood components examined. Results: In the white blood cell count the mean pre-test value of the experimental group consumed Zen fermentation broth was 5.73×10³ cells/µl, and the mean after-treatment was 5.37×10³ cells/µl, but the difference was not significant. The control group was not significant. In the hemoglobin content, the mean value before the intake of the Zen-test group was 13.58 g/dl, and the consumption after the consumption was 14.77 g/dl, which significantly increased. Albumin content was 4.33 g/dl before intake and 4.36 g/dl after ingestion in the Zen-test group, but it increased without significance. Triglyceride content was 109.8 mg/dl in the Zen-test group and 99.83 mg/dl in the post-test group, but it was not significant. In the LDL-content the mean of the premeasured value was 109 mg/dl in the Zen-test group, and that of the post-test was 97.87 mg/dl, and the difference significantly decreased to 11.13 mg/dl. In the HDL content, the mean value of the pre-test was 51.4 mg/dl in the Zen-test group and 56.87 mg/dl in the post-test. Conclusion: After intake of Zen fermentation broth, mean values of leukocyte, albumin, and triglyceride were not significantly different in the experimental group, but hemoglobin, LDL and HDL were significantly different.

• Journal of Naturopathy
• /
• v.7 no.2
• /
• pp.27-38
• /
• 2018

Purpose: The purpose of this study was to investigate whether intestinal proliferation is promoted in beneficial intestinal bacteria or decreased in harmful bacteria before and after ingesting Bacillus fermentation broth (ENM) for 8 weeks in the 16 subjects. Method: Intestinal bacteria were identified by PCR amplification using specific 16S rRNA primers. Results: The Bifidobacterium gene index(%)(gi%) increased to 58.92% in the control group and 69.53% in the test group after the ingestion of ENM, but there was no significant difference. Lactobacillus gi% increased significantly (49.37% in the control and 66.43% in the test) (p<.029). Clostridium gi% was significantly decreased after treatment (83.16% in the control and 67.76% in the test) (p<.077). Bacteroides gi% increased significantly (12.58% in the control and 20.87% in the test) after ingesting (p<.095). Prevotella gi% increased significantly (7.55% in the control and 17.28% in the test) after ingesting (p<.005). After ingesting, the median bacteria increased significantly in the control (20.06%) and the test (35.88%) (p<.001). Conclusions: After ingestion of the ENM, the number of beneficial bacteria increased and the number of harmful bacteria Clostridium tended to decrease. This suggests that ingestion of the Bacillus fermented beverage ENM has an effect on the proliferation of intestinal bacteria.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.3
• /
• pp.77-84
• /
• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.