rt is well known that glycosaminoglycans are 01' fllndamental importance to the processes 01' morphogenesis and cytodifferentiati on dllring the teeth development , With HlD-TCH-SP(High - iron diamine-thiocarbohydrazide-silvel protcinntc) , s lllfatcd glycosaminoglycans such as chondroitin sulfate and heparan slllfate have been localized a t the III trastrllctural level i n a wide variety of tlssues The pmpose of this stlldy were to examine slllfated glycosaminoglycan at llltrastrllctllral level fo 1' the phase of morphogenesis and cytodifferentiation of hllma n fetal tooth germs, and to detect the protein expression of slllfated glycosaminoglycan by immunoslot blot Human tooth gerll1s fl'Oll1 the a lveolar bone of twenty still born fetuses we1'e fixed in a mixtllre of 2% gllltaraldehyde/1% forma ldehyde, The 미 t 1'athin sections were stained witb HID-TCH-SP and were treated with 0, 05% solution of t esticular hyaluronidase to identify the histochemical properties 01' tbe HID-TCH-SP stain deposits , For semi quantitative protein assay , immllnoslot blot was done Sulfated glycocongugated deposits were localized in DEJ, peri tubular dentin , and mantle dentin matrix‘ enamel prism sheath , interrod area , and enamel matnx Heparan sll l띠 te deposits i n DEJ resisted to testicular hyalllronidase treatment prior to HID-TCH-SP staining, Immunoslot blot s howed that• chondroitin sulfate was detected higher in enamel and dentin extract, while heparan sulfate was relatively expressed in enamel and dentin extract, but rarely expressed in enamel or dentin extract It suggest ecl that chonclroi tin and hepa ran slllfate woulcl play an important role in the formation of DEJ, while chondroitin sulfate would in the clevelopll1ent of enamel prism sheath, enamel matrix, and mantle 01' peritublllar clentin of human fetal tooth germs,

본 연구에서는 경계 요소법을 이용하여 2차원 비등방성 탄성체의 손상 규명을 수행한다. 경계에서의 적분항만을 포함하는 본 수치모델은 1차원으로 줄게된다. 이러한 장점은 특히 균열 역학과 같은 문제에 있어서 중요한 의미를 갖는다. 또한 일정 영역을 분할하는 기법을 피함으로서 수치해석 과정을 간편하고 효율적으로 수행할수 있기 때문에 역문제 해결에 있어서 장점을 갖는다. 본 연구에서는 기존의 등방성 재료에 대한 비파괴 추정기법을 복합신소재와 같은 비등방성 재료로 이루어진 탄성체의 해석에 대하여 확장한다. 먼저 경계요소법에 의한 수치모델의 타당성을 기존의 문헌과 비교 검증하며, 서로 다른 특성을 보이는 비등방성 형식의 변화에 따라 실제 측정시 발생하는 노이즈 영향을 분석한다. 수치예제는 적층 형태 및 하중조건에 대하여 수행하며, 결함 추정에 미치는 적층 형태의 영향을 시험한다.

PSC 보의 비파괴 손상검색을 위한 고유진동수 이용 손상추정법과 모드형상 이용 손상추정법을 제시하였다. 먼저, 고유진동수의 변화를 사용하여 손상의 위치를 예측하는 알고리즘과 고유진동수 1차 섭동 이론에 근거하여 균열크기를 예측하는 알고리즘을 요약하였다 다음으로, 모드형상의 변화로부터 모드민감도의 변화를 감지하고 이를 통해 손상의 위치와 크기를 추정하는 손상지수 알고리즘을 요약하였다. PSC 보의 유한요소모델을 사용하는 수치실험을 통해 고유 진동수 이용 손상추정법과 모드형상 이용 손상추정 법의 정확성을 검증하였다. 분석결과 두 방법 모두 실험 대상 구조에 도입된 균열의 위치를 정확하게 예측하였으며 균열의 크기를 비교적 근사하게 예측하였다.

A study was carried out to establish a detection method for irradiated black and white pepper. Samples were packed in polyethylene bags and irradiated with 2.5, 5, 7.5, 10 and 15 kGy using a Co-60 irradiator. The samples were suspended in water, and alkalized with sodium hydroxide solution. Apparent viscosity was determined after heat gelatinization using a Brookfield DV-III rotation viscometer at 30 with 30, 60, 90, 120, 150, 180, and 210 rpm. Means and standard deviations of the viscosities of all samples decreased by increasing the stirring speeds. The viscosities increased in all samples by increasing the concentration. Regression expressions and coefficients of viscosity which decreased with increasing irradiation dose of 10% and 13% black pepper, and 7% and 10% white pepper were 0.9531 (y=-131.29x+1,769.0), 0.9725 (y=-351.33x+4,036.0), 0.9731 (y=2,208.0e^(-0.3546x)), and 0.9959 (y=5,116.0e^(0.2887x)), respectively, at 120 rpm. This trend was similar for all stirring speeds. These results suggest that the detection of irradiated black and white pepper at various doses is possible by the viscometric method.

구조물의 손상추정법은 정적방법과 동적방법으로 나눌 수 있다. 정적방법은 정적하중과 정적변위의 관계를 이용하여 구조물의 손상위치와 손상정도를 추정하는 방법으로 동적방법에 비해 수식이 간단하나, 정적하중과 정적변위의 관계만을 사용하여 구조물의 손상을 추정하므로 정적변위에 대한 오차에 매우 민감하다. 동적방법은 구조물의 고유한 진동특성을 나타내는 고유진동수와 진동모우드를 구하여 구조물의 손상을 추정하는 방법으로, 정적방법에 비해 동일한 측점에서 많은 양의 시간기록자료를 계측할 수 는 있으나, 신뢰성이 높은 많은 수의 고유진동수와 진동모우드를 구하기가 어렵다. 본 연구에서는 구조물의 정적변위, 고유진동수와 진동모우드에 대한 민감도행렬을 사용하여 구조물의 정적 및 동적특성을 동시에 고려할 수 있는 구조물의 손상추정법을 제시하였다. 제시한 방법은 구조물의 손상 전.후의 정적변위와 진동모우드의 변화량을 부등구속조건식으로한 최적화기법을 사용하므로, 제한된 계측절점과 오차를 고려할 수 있으며 정적변위와 모우드 민감도행렬이외의 다양한 구조적 특성에 대한 민감도를 구속조건식으로 사용할 수 있다. 트러스구조물에 대한 모의 수치예제를 통한 제안한 방법의 정확성과 효율성을 수치적으로 검증하였다.

A screening method has been developed for detecting sulfamethazine(SMZ) contamination of meat or feeds by using horseradish pero×idase (HRP) labeled protein A (Prot A-HRP)and an indirect competitive enzyme-linked immunosorbent assay(ELISA). The assay is based on competitive binding of guinea pig anti-SMZ with SMZ in sample and SMZ-gelatin con$lt;jugate(SMZ.GEL) followed by the uptake of prot A-HR,P onto polystyrene microwell plate coated with SMZ.GEL. Percent binding B/Bo × 100) was calculated from the absorbance in the absence (BO) and presence (B) of SMZ. By the sandard curve prepared by plotting log(SMZ) vs percent binding of each lmown reference solution, the detection limit was 1.0 ppb or leas. Cross reaction with sulfadimethoxine, sulfaguaniding, sulfamerazine, sulfamthoaypyridazine, sulfanilamide, aulfisomidine and aulfisoxazole were not observed. But sulfamerazine crosareacted in the test. The EC-50 value (concentration causing 50% inhibition of color development compared with blank) of sulfamerazine was 2.0 ppm. Further quality control will make the ELISA system ideal for the detection of SMZ in meat or feeds.

This paper is a study on data augmentation for small dataset by using deep learning. In case of training a deep learning model for recognition and classification of non-mainstream objects, there is a limit to obtaining a large amount of training data. Therefore, this paper proposes a data augmentation method using perspective transform and image synthesis. In addition, it is necessary to save the object area for all training data to detect the object area. Thus, we devised a way to augment the data and save object regions at the same time. To verify the performance of the augmented data using the proposed method, an experiment was conducted to compare classification accuracy with the augmented data by the traditional method, and transfer learning was used in model learning. As experimental results, the model trained using the proposed method showed higher accuracy than the model trained using the traditional method.

The damage detection method of blade systems largely depends on the personal ability of an inspector using a camera. Thus, this paper proposes a deep learning-based detection method that can rapidly and reliably identify and evaluate the damages on the blades.

상수도관의 파열은 과도한 압력, 노후화, 온도변화나 지진 등에 의한 지반이동에 의해 발생한다. 상수도관 파열이 대규모 단수, 싱크홀 등과 같은 더 심각한 피해 이어지지 않도록 신속하게 탐지 및 대응하는 것이 중요하다. 본 연구에서는 상수도관 파열 탐지를 위해 개선 Western Electric Company (WECO) 방법을 개발하였다. 개선 WECO 방법은 통계적공정관리기법 중 하나인 기존 WECO 방법에 임계치 조정자(w)를 추가하여 대상 네트워크에 적합한 이상탐지 의사결정을 할 수 있도록 했다. 개발된 개선 WECO 방법을 미국 텍사스 오스틴 관망에 적용 및 검증하였다. 상수도관 파열 발생 시 측정한 비정상데이터와 수요량 변동만 고려한 정상데이터를 이용하여 기존 및 개선 WECO 방법을 비교하였다. 최적 임계치 조정자 w값을 결정하기 위해 민감도 분석을 수행하였으며, 다양한 계측시간 간격 데이터(dt = 5, 10, 15분 등)의 영향도 분석하였다. 각 경우 별 탐지 성능은 탐지확률, 오경보확률, 평균탐지시간을 계산하여 비교하였다. 본 연구에서는 도출된 결과를 바탕으로 WECO 방법을 실제 상수도관 파열 탐지에 적용하기 위한 가이드라인을 제공한다.

Background : A soil-borne pathogenic fungus, Ilyonectria radicicola (Cylindrocarpon destructans) species complex causing ginseng root rot is the major pathogen on ginseng. DNA extraction from soil is necessary to confirm the presence of ginseng root rot pathogen, I. radicicola. Methods and Results : In order to the increase the detection sensitivity of pathogens present in the soil, the existing soil DNA extraction method was modified to inctease the efficiency of the PCR reaction and to increase the amount of soil samples that can be analyed once by 500 times. For increase the DNA concentration, phenol : chloroform : isoamylalcohol (25 : 24 : 1) were used instead of chloroform : isoamylalcohol (24 : 1), and the sensitivity of PCR was increased by using purification kit. Conclusion : The modified DNA extraction method can detect ginseng root rot pathogen (I. radicicola) with DNA extraction and purification higher than the conventional method.

In this paper, we propose a new collision detection algorithm for human-robot collaboration. We use an IMU sensor located at the tip of the manipulator and the kinematic behavior of the manipulator to detect the unexpected collision between the robotic manipulator and environment. Unlike other method, the developed algorithm uses only the kinematic relationship between the manipulator joint and the end effector. Therefore, the collision estimation signal is not affected by the error of the dynamics model. The proposed collision detection algorithm detects the collision by comparing the estimated acceleration of the end effector derived from the position, velocity and acceleration trajectories of the robot joints with the actual acceleration measured by the sensor. In simulation, we compare the performance of our method with the conventional Residual Observer (ROB). Our method is less sensitive to the load variation because of the independency on the dynamic modeling of the manipulator.

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.