• Food Science and Biotechnology
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• 제17권3호
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• pp.508-513
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• 2008

Erythromycin has been used to treat Streptococosis, Edwardsiel1osis, Vibriosis, Bacterial enteritis in the cultured fish. In this study, a rapid and effective erythromycin analysis method with new sample treatment protocol and liquid chromatography/tandem mass spectrometry (LC/MS/MS) system for fish products was developed. For the erythromycin extraction from fish muscle, the solvent mixture composed of 0.2% meta-phosphoric acid and methanol (6:4) showed good recovery rate, and the optimum extraction solvent volume was 20 mL. Erythromycin detection using LC/MS/MS were carried out under electro spray ionization (ESI) positive condition and erythromycin mass value 576.2 and 157.9. And the detection limit of the established method was 0.005 mg/kg in fish products. The recovery rate of the developed method applied to the fish species were as following, olive flounder, $87.6{\pm}5.0%$; black rockfish, $87.2{\pm}6.4%$; eel, $85.2{\pm}4.8%$; and rainbow trout, $86.0{\pm}6.2%$. In the established method in this study, the correlation of coefficient values ($R^2$) of erythromycin calibration curve (n=11) was 0.9998.

• 대한전자공학회논문지SD
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• 제43권12호
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• pp.33-39
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• 2006

나노 스케일 벌크 MOSFET의 RF 비선형 특성을 넓은 bias영역에 걸쳐 정확히 예측하기 위하여 내된 비선형 요소들을 가진 엠피리컬 비선형 모델이 새롭게 구축되었다. 먼저, 나노 스케일 벌크 MOSFET에 적합한 파라미터 추출방법을 사용하여 측정된 S-파라미터로부터 bias 종속 내부 파라미터 곡선을 추출하였다. 그 후에 비선형 캐패시턴스 및 전류원 방정식들은 추출된 bias 종속 곡선들과 3차원 fitting함으로서 엠피리컬하게 구하여졌다. 이와 같이 모델된 S-파라미터는 60nm MOSFET의 측정치와 20GHz 까지 아주 잘 일치하였으며, 이는 엠피리컬 나노 MOSFET 모델의 정확도를 증명한다

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.979-982
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• 2005

This paper is to be pre-processing that decides the text recognizability and quality contained in natural image. Differentiated with the existing studies, In this paper, it suggests the application of partially unified color models, Coiflet Wavelet and text extraction algorithm that uses the closed curve edge features of LoG (laplacian of gaussian)operator. The text image included in natural image such as signboard has the same hue, saturation and value, and there is a certain thickness as for their feature. Each color element is restructured into closed area by LoG operator, the 2nd differential operator. The text area is contracted by Hough Transform, logical AND-OR operator of each color model and Minimum-Distance classifier. This paper targets natural image into which text area is added regardless of the size and resolution of the image, and it is confirmed to have more excellent performance than other algorithms with many restrictions.

• 한국농공학회논문집
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• 제49권5호
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• pp.81-90
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• 2007

Watershed topographical information is required in hydrologic analysis, supporting efficient hydrologic model operation and managing water resources. Watershed topographical data extraction systems based on desktop GIS are abundant these days placing burdens for spatial data processing on users. This paper describes development of a Web-based Geographic Information Systems that can delineate the Geum River sub-basins and extract watershed topographical data in real time. Through this system, users can obtain a watershed boundary by selecting outlet location and then extracting topographical data including watershed area, boundary length, average altitude, slope distribution about the elevation range with Web browsers. Moreover, the system provides watershed hydrological data including land use, soil types, soil drainage conditions, and NRCS(Natural Resources Conservation Service) curve number for hydrologic model operation through grid overlay technique. The system operability was evaluated with the hydrological data of WAMIS(Water Management Information System) with the government operation Web site as reference data.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1230-1242
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• 1993

In a case of mushroom (Lentinus Edodes L.) , visual features are crucial for grading and the quantitative evaluation of the growth state. The extracted quantitative visual features can be used as a performance index for the drying process control or used for the automatic sorting and grading task. First, primary external features of the front and back sides of mushroom were analyzed. And computer vision based algorithm were developed for the extraction and measurement of those features. An automatic thresholding algorithm , which is the combined type of the window extension and maximum depth finding was developed. Freeman's chain coding was modified by gradually expanding the mask size from 3X3 to 9X9 to preserve the boundary connectivity. According to the side of mushroom determined from the automatic recognition algorithm size thickness, overall shape, and skin texture such as pattern, color (lightness) ,membrane state, and crack were quantified and measured. A portion of t e stalk was also identified and automatically removed , while reconstructing a new boundary using the Overhauser curve formulation . Algorithms applied and developed were coded using MS_C language Ver, 6.0, PC VISION Plus library functions, and VGA graphic function as a menu driven way.

• Progress in Superconductivity
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• 제10권2호
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• pp.69-73
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• 2009

For extraction of the self-energy from the angle resolved photoemission spectroscopy(ARPES) experiments for the cuprate superconductors, the momentum distribution curve(MDC) analysis is commonly used. There are two requirements for this method to work: the self-energy is momentum independent and the bare electron dispersion is known. Assuming that the first condition is satisfied in the cuprates, we checked the effects of the bare dispersion on the extracted self-energy. For this, we first generated the ARPES intensity using the tight-binding band of the B2212 by solving the Eliashberg equation. We then extracted the self-energy from the theoretically generated ARPES intensity using the linear and quadratic dispersions. By choosing the bare dispersion such that the Kramer-Kronig relation is best satisfied between the real and imaginary parts of the extracted self-energy, we confirmed that the quadratic dispersion is better for the bare electron band for Bi2212. The self-energy can be reasonably extracted from the ARPES experiments using the MDC analysis.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.909-915
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• 2008

Recently, the interests in the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration, and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with an autonomous travelling function to cope with unexpected terrains and obstacles. This means that they should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents a method for extracting terrain information, that is, slope and roughness from elevation maps as a prior step of traversability analysis. Slope is extracted using the curve fitting based on the least squares method and roughness using three metrics and their weighted average. The effectiveness of the proposed method is verified on both a fractal map and the world model map of a real terrain.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1293-1308
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• 2020

In fine-tuning-based transfer learning, the size of the dataset may affect learning accuracy. When a dataset scale is small, fine-tuning-based transfer-learning methods use high computing costs, similar to a large-scale dataset. We propose a mid-level feature extractor that retrains only the mid-level convolutional layers, resulting in increased efficiency and reduced computing costs. This mid-level feature extractor is likely to provide an effective alternative in training a small-scale medical image dataset. The performance of the mid-level feature extractor is compared with the performance of low- and high-level feature extractors, as well as the fine-tuning method. First, the mid-level feature extractor takes a shorter time to converge than other methods do. Second, it shows good accuracy in validation loss evaluation. Third, it obtains an area under the ROC curve (AUC) of 0.87 in an untrained test dataset that is very different from the training dataset. Fourth, it extracts more clear feature maps about shape and part of the chest in the X-ray than fine-tuning method.

• 대한의용생체공학회:의공학회지
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• 제44권5호
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• pp.354-361
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• 2023

Most of spinal diseases are diagnosed based on the subjective judgment of a specialist, so numerous studies have been conducted to find objectivity by automating the diagnosis process using deep learning. In this paper, we propose a method that combines segmentation and feature extraction, which are frequently used techniques for diagnosing spinal diseases. Four models, U-Net, U-Net++, DeepLabv3+, and M-Net were trained and compared using 1000 X-ray images, and key-points were derived using Douglas-Peucker algorithms. For evaluation, Dice Similarity Coefficient(DSC), Intersection over Union(IoU), precision, recall, and area under precision-recall curve evaluation metrics were used and U-Net++ showed the best performance in all metrics with an average DSC of 0.9724. For the average Euclidean distance between estimated key-points and ground truth, U-Net was the best, followed by U-Net++. However the difference in average distance was about 0.1 pixels, which is not significant. The results suggest that it is possible to extract key-points based on segmentation and that it can be used to accurately diagnose various spinal diseases, including spondylolisthesis, with consistent criteria.

• 한국산업정보학회논문지
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• 제12권5호
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• pp.39-46
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• 2007

최근 유비쿼터스 환경에서 개인 인증을 위한 연구가 활발하게 진행되고 있다. 그 중에서 걸음걸이 인식은 원거리에서 사람의 물리적인 특성을 이용하여 개인을 인증하는데 효과적인 방법이다. 본 논문에서는 걸음걸이 인식을 위해 평균 이동 알고리즘(mean shift algorithm)과 geodesic 활성 윤곽선 모델(active contour models) 기반의 사람 외형 추출 및 추적 시스템을 제안한다. 활성 윤곽선 모델은 움직이고, 변화하기 쉬운 물체를 다루는데 효과적이다. 그러나 활성 윤곽선 모델의 성능은 초기 커브에 의존적인 한계를 가지고 있다. 이 문제를 극복하기 위해 전형적인 geodesic 활성 윤곽선 모델에 평균 이동 알고리즘을 결합한다. 기본 개념은 진화시키기 전에 level set 방법을 사용하여 초기 커브를 사람 영역에 위치시키고, 그 영역을 충분히 둘러싸도록 크기를 조정한 후에 커브를 진화시킨다. 이러한 방법은 움직임이 큰 물체를 다루거나 진화 횟수를 줄이기 위해 효과적이다. 제안된 시스템은 사람 영역 검출 모듈과 사람 외형 추적모듈로 구성된다. 사람 영역 검출 모듈에서는 배경영상 제거(background subtraction)와 모폴로지 연산(morphologic operation)으로 사람의 실루엣을 검출한다. 이때, 사람의 외형은 평균 이동 알고리즘과 geodesic 활성 윤곽선 모델에 의해 정확하게 검출된다. 실험 결과에서 제안된 방법이 걸음걸이 인식(gait recognition)을 위해 사람의 외형을 효과적으로 정확하게 추출하고 추적됨을 보여준다.