• 미생물학회지
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• 제55권2호
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• pp.164-166
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• 2019

이 연구에서는 Microbacterium aurum KACC $15219^T$ (=IFO $15204^T$ = DSM $8600^T$)의 완전한 유전체 서열이 해독되었다. 하나의 원형 염색체는 3.42 Mbp였으며 G+C 함량이 69.9%였다. 해당 염색체 염기서열을 주석화한 결과, 총 3,096개의 유전자 서열이 발견되었다. 16종 이상의 탄소원을 분해하는 것으로 알려진 M. aurum KACC $15219^T$에는 방향족 아미노산 합성 기질인 quinic acid를 비롯한 다양한 탄소원의 이용과 관련된 유전자가 존재하였다. M. aurum KACC $15219^T$의 유전체 정보는 이 미생물에 대한 이해를 높이고 산업적인 이용을 위한 기반이 될 것이다.

• 대한피부과학회지
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• 제56권10호
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• pp.631-635
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• 2018

Microvenular hemangioma (MVH) is a rare acquired benign vascular neoplasm, which presents commonly as a solitary purple-to-red nodule or plaque measuring approximately 10 mm in diameter. MVH occurs primarily on the extremities or the trunk. Most lesions are solitary, and multiple lesions are rare. Histopathological features of MVH include numerous, scattered, thin and irregularly branching small vessels in the dermis and endothelial cells without atypia. Owing to similarities in clinical morphology and histopathological features, MVH may often be indistinguishable from the early patch stage of Kaposi sarcoma. Immunohistochemical (IHC) analysis helps differentiate between the 2 diseases. The results of IHC tests in patients with MVH show positive staining for CD31 and smooth muscle actin and typically, negative staining for the human herpes virus 8 antigen. We report a rare case of multiple MVH clinically mimicking the early patch stage of Kaposi sarcoma in a 63-year-old woman who presented with a 3-year history of slowly growing, compressible, soft, bluish-purple macules and plaques on the trunk and right arm.

• 센서학회지
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• 제28권3호
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• pp.157-163
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• 2019

The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.

• 대한치과의사협회지
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• 제57권1호
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• pp.8-17
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• 2018

Purpose : The purpose of this study was to survey the present status of the regional oral health centers for the disabled. Material and methods : Face to face interviews with oral healthcare professionals in eight regional oral health centers and literature reviews were conducted among eight regional oral health centers for the disabled during 2, July to 30, August 2017. Results : It is necessary to establish more regional oral health centers for the disabled in area where the number of disabled person as percentage of whole region population is high. Also, all the centers appeared a lack of professional manpower including dentist, dental hygienist and anesthesiologist, equipment and facilities for the demands of patients and their guardians. It is essential for the government to improve the support system to regional oral health centers for the disabled. Conclusions : This study can be used as a reference for the countermeasure to make a new policy and activate the accessibility of dental care services in the public for the disabled.

• 한국음향학회지
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• 제40권1호
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• pp.10-17
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• 2021

심벌 트랜스듀서는 Class V flextensional 트랜스듀서의 소형화된 버전으로서 크기에 비해 낮은 공진 주파수와 고출력 특성을 가진다. 하지만, 높은 품질계수와 낮은 에너지 변환 효율성 때문에 단일보다는 배열형으로 많이 사용된다. 배열형으로 사용하면 구성 트랜스듀서들 간의 상호작용으로 인해 단일 트랜스듀서에 비해 주파수 특성에 많은 변화가 나타난다. 본 연구에서는 이러한 성질을 이용하여 심벌 어레이가 광대역 특성을 가지게 하는 패턴을 설계하였다. 특정 중심 주파수를 가지는 세 개의 심벌 트랜스듀서를 먼저 설계하였고, 설계된 심벌 트랜스듀서들로 3 × 3 평면 배열을 구성할 수 있는 모든 패턴을 찾았다. 그 후, 이들 패턴들의 주파수 특성을 분석하고, 그 결과를 바탕으로 높은 비대역폭을 구현하기 위해 가장 효과적인 배열 패턴을 도출하였다. 도출된 배열 패턴은 기준 모델에 비해 비대역폭이 최대 24.9 % 개선되었다.

• Journal of Korean Academy of Oral Health
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• 제41권1호
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• pp.16-21
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• 2017

Objectives: Dental caries and periodontitis are major oral bacterial infections associated with dental plaque. Infection and inflammation play a role in carcinogenesis, and a significant link has been found between some highly prevalent oral and dental diseases and some types of cancer. Therefore, the aim of this study was to evaluate the relationship between cancer and oral health among Korean adults. Methods: Data from the 6th Korea National Health and Nutrition Examination Survey were used to analyze the incidence of cancer according to oral health. Demographic and socioeconomic statuses and oral behavior of the participants was analyzed using complex chi-square tests. Logistic regression was used to analyze the relationship between a high DMFT index and cancer by calculating the 95% confidence intervals. Results: In total, 6,450 case-control subjects were included. Significant difference was observed in the DMFT index, but not in periodontal diseases, between the cases and controls. The odds ratio for cancer was 1.80 (95% confidence interval: 1.18 to 2.73) in the high-risk group. However, no significant difference was observed after adjusting for age, education level, and income. Conclusions: The results provide potential evidence of a significant association between cancer and oral disease.

• 한국재료학회지
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• 제31권7호
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• pp.420-426
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• 2021

Graphene, a new material with various advantageous properties, has been actively used in various fields in recent years. Applications of graphene oxide are increasing in combination with other materials due to the different properties of graphene oxide, depending on the number of single and multiple layers of graphene. In this study, single-layer graphene oxide and multi-layer graphene oxide are spray coated on polystyrene, and the physicochemical properties of the coated surfaces are characterized using SEM, Raman spectroscopy, AFM, UV-Vis spectrophotometry, and contact angle measurements. In single-layer graphene oxide, particles of 20 ㎛ are observed, whereas a 2D peak is less often observed, and the difference in surface height increases according to the amount of graphene oxide. Adhesion increases with an increase in graphene oxide up to 0.375 mg, but decreases at 0.75 mg. In multi-layer graphene oxide, particles of 5 ㎛ are observed, as well as a 2D peak. According to the amount of graphene oxide, the height difference of the surface increases and the adhesive strength decreases. Both materials are hydrophilic, but single-layer graphene oxide has a hydrophilicity higher than that of multi-layer graphene oxide. We believe that multi-layer graphene oxide and single-layer graphene oxide can be implemented based on the characteristics that make them suitable for application.

• 한국염색가공학회지
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• 제33권2호
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• pp.79-86
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• 2021

This study investigated the effect of a pigment (C. I. Pigment Red 122) addition on mechanical properties of the epoxy resin, diglycidyl ether of bisphenol F (DGEBF) and G640 curing agent. The K/S value, thermal properties, tensile properties, and fracture toughness of the prepared epoxy samples were evaluated. When the pigment was added to the DGEBF/G640 epoxy system, the color of the epoxy resin changed to red from transparent and yellowish color, and the K/S value in the red region increased as the pigment content increased. When the pigment content was increased up to 0.1 phr, the tensile strength was improved up to 21.8 %, whereas the pigment content was over 0.1 phr, the tensile strength decreased. The fracture toughness was improves up to 23.1 % until the amount of pigment added was up to 0.2 phr, and then decreased when the amount of the pigment added was more than 0.2 phr. This attributed to the aggregation of the pigments in the epoxy resin when the amount of the pigment added was more than 0.2 phr. Therefore, the coloration of the epoxy resin with an organic pigment must be carried out very carefully because the coloration of epoxy resin affects its mechanical properties.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.143-149
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• 2021

In order to predict and prevent the disease of the abdominal aorta, which is the largest artery in the human body and the most common aneurysm, the normal arterial blood flow operation should be considered. To this end, we are trying to solve problems that may arise in the future by executing FSI based on the data obtained from 4D flow MRI. However, to match the similarity between the 4D flow MRI flow and the FSI flow, correlation was used in previous papers, but the correlation did not show the degree of agreement. Therefore, in this paper, we analyzed the correlation between the 4D flow MRI flow velocity of the human abdominal aorta and the two-way FSI flow velocity in which the three physical properties used for the aortic FSI were added to the CT abdominal aorta 3D model and the interclass correlation coefficient. As a result, the physical property M2 showed the highest similarity in correlation and intraclass correlation coefficient, and this property is intended to be helpful in the future study of the abdominal aortic two-way FSI flow rate.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.167-174
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• 2021

The purpose of this study is to classify TIFF images, PNG images, and JPEG images using deep learning, and to compare the accuracy by verifying the classification performance. The TIFF, PNG, and JPEG images converted from chest X-ray DICOM images were applied to five deep neural network models performed in image recognition and classification to compare classification performance. The data consisted of a total of 4,000 X-ray images, which were converted from DICOM images into 16-bit TIFF images and 8-bit PNG and JPEG images. The learning models are CNN models - VGG16, ResNet50, InceptionV3, DenseNet121, and EfficientNetB0. The accuracy of the five convolutional neural network models of TIFF images is 99.86%, 99.86%, 99.99%, 100%, and 99.89%. The accuracy of PNG images is 99.88%, 100%, 99.97%, 99.87%, and 100%. The accuracy of JPEG images is 100%, 100%, 99.96%, 99.89%, and 100%. Validation of classification performance using test data showed 100% in accuracy, precision, recall and F1 score. Our classification results show that when DICOM images are converted to TIFF, PNG, and JPEG images and learned through preprocessing, the learning works well in all formats. In medical imaging research using deep learning, the classification performance is not affected by converting DICOM images into any format.