• Parasites, Hosts and Diseases
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• 제49권4호
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• pp.349-356
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• 2011

The existence of symbiotic relationships between Acanthamoeba and a variety of bacteria is well-documented. However, the ability of Acanthamoeba interacting with host bacterial pathogens has gained particular attention. Here, to understand the interactions of Escherichia coli K1 and E. coli K5 strains with Acanthamoeba castellanii trophozoites and cysts, association assay, invasion assay, survival assay, and the measurement of bacterial numbers from cysts were performed, and nonpathogenic E. coli K12 was also applied. The association ratio of E. coli K1 with A. castellanii was 4.3 cfu per amoeba for 1 hr but E. coli K5 with A. castellanii was 1 cfu per amoeba for 1 hr. By invasion and survival assays, E. coli K5 was recovered less than E. coli K1 but still alive inside A. castellanii. E. coli K1 and K5 survived and multiplied intracellularly in A. castellanii. The survival assay was performed under a favourable condition for 22 hr and 43 hr with the encystment of A. castellanii. Under the favourable condition for the transformation of trophozoites into cysts, E. coli K5 multiplied significantly. Moreover, the pathogenic potential of E. coli K1 from A. castellanii cysts exhibited no changes as compared with E. coli K1 from A. castellanii trophozoites. E. coli K5 was multiplied in A. castellanii trophozoites and survived in A. castellanii cysts. Therefore, this study suggests that E. coli K5 can use A. castellanii as a reservoir host or a vector for the bacterial transmission.

• 한국화재소방학회논문지
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• 제30권6호
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• pp.92-98
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• 2016

본 논문은 Charge-Coupled Device (CCD) 카메라를 이용한 열화상의 실시간 추정과 화재경보에 대하여 논한 것으로 각도 및 위치에 따른 특징점 분석과 동일 형상의 벡터 성분 좌표점 설정에 따른 이미지 융합이 잘 되었다. 영상을 Display하는 픽셀의 데이터 값은 0~255, 센서 출력값은 0~5,000로 하여 정확성이 높았다. 시험결과 시험체로부터 500 m, 1000 m, 1500 m 거리에서 화염에 의한 시험체의 작동시간은 각각 7초, 26초, 62초 소요 되었고 화면이미지 생성이 효과적으로 이루어졌다. 화재 발생 진단은 주의/경보/화재의 3단계로 프로그램하여 Alarm의 순차적 동작과 SNS 전송이 이루어졌다. 비화재보시험을 위해 백열등, 형광등에 대해 시험하였으나 모두 비화재보를 발생하지 않았다. 시간대별 화염의 변화영상과 진행방향 및 확산속도의 분석은 화재진행상황 예측이나 열화상 실시간 추정과 경보로 비화재보 감소가 가능함을 확인하였다.

• 대한소아치과학회지
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• 제28권3호
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• pp.496-503
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• 2001

골격성 II급 1류 부정교합을 가지는 아동에서 상악골의 과도한 성장은 흔히 전후방적 요소 뿐 아니라 수직적 요소도 가지고 있는데, 그 이유는 상악골이 전하방으로 성장, 이동할 경우 하악골이 후하방 회전하기 때문이며, 하악골의 성장이 전방으로 이루어지는 것을 방해하게 된다. 따라서 이 경우 치료목표는 하악골이 더욱 돌출 되어 상악골과 정상적인 관계를 가지도록 성장하는 동안 상악골의 성장을 억제하는 것이며, 이를 위해 구외력을 적용하는 것이 현명한 방법으로 보고되고 있다. 조선대학교 소아치과에 내원한 골격성 II급 1류 부정교합 환자에서 C II activator와 headgear를 이용한 구외력을 적용후 양호한 결과를 얻었기에 보고하는 바이다.

• Genomics & Informatics
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• 제4권4호
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• pp.161-166
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• 2006

The establishment of DNA microarray technology has enabled high-throughput analysis and molecular profiling of various types of cancers. By using the gene expression data from microarray analysis we are able to investigate diagnostic applications at the molecular level. The most important step in the application of microarray technology to cancer diagnostics is the selection of specific markers from gene expression profiles. In order to select markers of Immortalization and transformation we used c-myc and $H-ras^{V12}$ oncogene-transfected NIH3T3 cells as our model system. We have identified 8751 differentially expressed genes in the immortalization/transformation model by multivariate permutation F-test (95% confidence, FDR<0.01). Using the support vector machine algorithm, we selected 13 discriminative genes which could be used to predict immortalization and transformation with perfect accuracy. We assayed $H-ras^{V12}$-transfected 'transformed' cells to validate our immortalization/transformation dassification system. The selected molecular markers generated valuable additional information for tumor diagnosis, prognosis and therapy development.

• 대한수의학회지
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• 제40권1호
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• pp.86-93
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• 2000

Paratuberculosis (Johne's disease), a chronic enteritis produced by Mycobacterium paratuberculosis, affects a large proportion of ruminants in all continents and causes important economic losses. The identification of well-characterized and species-specific components of M paratuberculosis would provide the means to improve the specificity and sensitivity of immunodiagnostic assays for Johne's disease. The aims of this study were to express the recombinant C-terminal of 34kDa protein (rC34P) of M paratuberculosis in E coli and to investigate the effectiveness of this protein in detecting antibodies to the native protein in sera from paratuberculosis infected cattle. The C-terminal of the gene encoding the 34kDa protein was amplified by polymerase chain reaction from the chromosomal DNA of M paratuberculosis (ATCC 19698) and cloned into vector pGEX-4T-2. Then, cloned plasmid was transformed into E coli DH5${\alpha}$ and the rC34P was overexpressed. The rC34P was purified by affinity chromatography and gel filtration. The rC34P was examined antigenicity by Western blot. The rC34P was reactive with culture positive bovine serum and hyperimmune rabbit anti-M paratuberculosis serum but was not reactive with culture negative bovine serum and tuberculin positive bovine serum in Western blot. In conclusion, the rC34P produced in this study is expected as a useful candidate for antigen in serological diagnosis of Johne's disease.

• 한국정보통신학회논문지
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• 제13권10호
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• pp.2163-2170
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• 2009

흉부 컴퓨터단층영상에서의 얻어진 폐 영상은 볼륨과 형태 등의 정량적인 정보들로서 진단과 수술 계획 등에 있어서 필연적 정보를 제공한다. 일반적인 영상분할은 이미지를 구성 요소영역이나 목적물에 따라 나누는 방법이다. 그러나 재분할을 하는 단계에서 최종영상은 에너지 최소화를 해결하는 정도에 의존하며, 분할은 응용대상의 관심 영역에서 객체나 물체의 경계에서 정지하게 된다. 가변형 능동모델은 컴퓨터 비젼, 영상처리 분야에서 광범위하게 사용되고 있다. 또한 영역 분할은 현재까지 많은 연구가 되고 있으며, Xu에 의해서 GVF라는 새로운 형태의 외부힘이 제안되고 있다. 본 논문에서 제안하는 알고리듬은 흉부 컴퓨터단층영상에서 실질을 자동 분할하기 위해서 에너지 최소화 방법을 사용하고, 영역분할을 위해 개선된 가변형 능동모델을 제안한다. 알고리듬은 정확한 영역분할을 위해서 기존 방법과 다른 개선된 외부힘을 정의하는 것이다. 임상의 실험은 흉부 컴퓨터단층영상에서 진단에 필요로 하는 폐 실질의 분할이 성공적인 결과를 나타내었다.

• 대한의용생체공학회:의공학회지
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• 제40권2호
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• 대한의생명과학회지
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• 제25권1호
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Parasites, Hosts and Diseases
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• 제56권6호
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• pp.559-565
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• 2018

The identification and characterization of pathogenic and zoonotic tick-borne diseases like granulocytic anaplasmosis are essential for developing effective control programs. The differential diagnosis of pathogenic Anaplasma phagocytophilum and non-pathogenic A. phagocytophilum-like Anaplasma spp. is important for implementing effective treatment from control programs. The objective of the present study was to investigate the prevalence of Anaplasma spp. in horses in Korea by nucleotide sequencing and restriction enzyme fragment length polymorphism assay. Of the 627 horses included in the study, only 1 (0.2%) was infected with A. phagocytophilum. Co-infection with A. phagocytophilumlike Anaplasma spp. was not detected in the study. The 16S rRNA sequence of A. phagocytophilum was similar (99.5-100%) to A. phagocytophilum 16S rRNA isolated from horses in other countries. PCR adapted to amplify A. phagocytophilum groEL and msp2 genes failed to generate amplicons, suggesting genetic diversity in these genes. This study is the first molecular detection of A. phagocytophilum in horses in Korea. Human granulocytic anaplasmosis and animal infection of A. phagocytophilum have been reported in Korea recently. Because of vector tick distribution, global warming, and the increase of the horse industry, horses should be considered as a potential reservoir for A. phagocytophilum, and cross infectivity should be evaluated even though a low prevalence of infection was detected in this study. Furthermore, continuous surveillance and effective control measures for A. phagocytophilum should be established to prevent disease distribution and possible transmission to humans.

• 해양환경안전학회지
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• 제27권7호
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• pp.1088-1097
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• 2021

기계 장비의 진동 데이터는 필연적으로 노이즈를 포함하고 있다. 이러한 노이즈는 기계 장비의 유지보수를 진행하는데 악영향을 끼친다. 그에 따라 데이터의 노이즈를 얼마나 효과적으로 제거해주냐에 따라 학습 모델의 성능을 좌우한다. 본 논문에서는 시계열 데이터를 전처리 함에 있어 특성추출 과정을 포함하지 않는 Denoising Auto Encoder 기법을 활용하여 데이터의 노이즈를 제거했다. 또한 기계 신호 처리에 널리 사용되는 Wavelet Transform과 성능 비교를 진행했다. 성능비교는 고장 탐지율을 계산하여 진행했으며 보다 정확한 비교를 위해 분류 성능 평가기준 중 하나인 F-1 Score를 계산하여 성능 비교를 진행했다. 고장을 탐지하는 과정에서는 One-Class SVM 기법을 활용하여 고장 데이터를 탐지했다. 성능 비교 결과 고장 진단율과 오차율 측면에서 Denoising Auto Encoder 기법이 Wavelet Transform 기법에 비해 보다 좋은 성능을 나타냈다.