• 제목/요약/키워드: window bag

검색결과 6건 처리시간 0.021초

포도에서 봉지의 종류, 처리시기 및 식물성오일 처리가 열과와 탄저병 발생에 미치는 영향 (Effects of Treatment of Bag Kinds, Bagging Time and Plant Oils on Fruit Cracking and Bitter Rot in Grapevines)

  • 문병우;이영철;남기웅;김정주
    • 생물환경조절학회지
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    • 제17권2호
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    • pp.143-149
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    • 2008
  • 포도에서 봉지 종류, 봉지 처리시기 및 식물성 오일처리에 따른 열과와 병 발생 및 과실 품질에 미치는 영향을 조사하였다. 봉지 종류별 열과 및 탄저병 경감효과는 '캠벨얼리'에서 열과 발생은 큰 차이를 인정할 수 없으나, 탄저병 발생은 무대처리를 제외한 모든 처리에서 감소하였다. '조생 캠벨얼리'에서 열과 및 탄저병 발생은 무대처리를 제외한 관행봉지, 창문봉지, 칼슘함유봉지 처리에서 감소하였다 '캠벨얼리'에서 모두 7월 5일 이전의 봉지처리에서, '거봉'에서는 각각 6월 29일과 7월 6일이전의 봉지처리 모두에서 현저하게 줄었다. 식물성오일 처리는 '조생 캠벨얼리'에서 열과 및 탄저병 발생률을 현저히 줄 일수 있었고 '캠벨얼리'에서는 과피의 칼슘함량을 증가시켰다. 봉지종류별 과실품질 중 가용성고형물은 창문봉지 처리에서 많이 감소되었으며 칼슘함유봉지 처리에서는 Hunter b값이 떨어졌다. 따라서 칼슘함유봉지 및 식물성오일 처리는 열과 경감효과가 있는 것으로 판단되었다.

L0 Norm 기반의 LE(Local Effect) 연산자를 이용한 디지털 이미지 위변조 검출 기술 개발 (Development of Digital Image Forgery Detection Method Utilizing LE(Local Effect) Operator based on L0 Norm)

  • 최용수
    • 한국소프트웨어감정평가학회 논문지
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    • 제16권2호
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    • pp.153-162
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    • 2020
  • 디지털 이미지 위조 탐지는 디지털 포렌식 분야에서 매우 중요한 분야 중 하나이다. 기술의 발전을 통해 위조된 이미지가 자연스럽게 바뀜에 따라 이미지 위조를 감지하기 어렵게 만들었다. 본 논문에서는 디지털 이미지에서 복사 붙여넣기 위조에 대한 수동적 위조 검출을 이용한다. 또한, L0 Norm 기반 LE 연산자를 사용해 복사 붙여넣기 위조를 검출함과 동시에 기존에 존재하던 L2, L1 Norm 기반 LE 연산자를 이용한 위조 검출 정확도를 비교하였다. 제안한 하삼각 윈도우를 적용하고 L2, L1 및 L0 Norm 기반 LE 연산자를 통해 BAG 불일치를 검출하고 위조 검출률을 측정하였다. 검출률의 비교에서 제안한 하삼각 윈도우는 기존의 윈도우 필터보다 BAG 불일치 검출에 강인함을 볼 수 있었다. 또한, 하삼각 윈도우를 쓰는 경우 L2, L1, L0 Norm LE 연산으로 갈수록 이미지 위조 검출의 성능이 점점 높게 측정되었다.

대동맥중격결손증[수술치험 1예] (Aorticopulmonary Window: one case report)

  • 최영호
    • Journal of Chest Surgery
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    • 제14권3호
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    • pp.302-306
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    • 1981
  • Aorticopulmonary window is a rare anomaly among congenital heart disease. Various terms have been suggested including A-P window, A-P fenestration, fistula, aorticseptal defect etc. The defect lies usually between the left side of the ascending aorta and right wall of the pulmonary artery just anterior to the origin of the right main pulmonary artery. We have experienced one case of aorticopulmonary septal defect which was diagnosed as V5D with pulmonary hypertension in 1 4/12 year old, 7.2 Kg, male patient. Operation was done under the hypothermic cardiopulmonary bypass using 5t. Thomas cardioplegic solution. Vertical right ventriculotomy over the anterior wall of RVOT revealed no defect in the ventricular septum, and incision was extended up to the main pulmonary artery to find the source of massive regurgitation of blood through MPA. Finger tip compression of the aorticopulmanary window was replaced with Foley bag catheter balloon, and the $7{\times}10$ mm aorticoseptal defect located 15mm above the pulmonic valve was sutured continuously wih 3-0 nylon suture during azygos flow of cardiopulmonary cannula which was located distal to the window resulted massive air pumping systemically, and temporary reversal of pumping was tried to minimize cerebral air embolism. Remained procedure was done as usual, and pump off was smooth and uneventful. Postoperatively, patient was attacked frequent opistotonic seizure with no recovery sign mentally and p.hysically. Vital signs were gradually worsen with peripheral cyanosis and oliguria, and cardiac activity was arrested 1485 minutes after operation. Autopsy was performed to find the sutured window and massive edema of the brain.

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기본간호학 실습교육에 있어 표준화 환자를 이용한 학습방법의 효과 (The Effectiveness of Standardized Patient Managed Instruction for a Fundamental Nursing Course)

  • 유문숙
    • 한국간호교육학회지
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    • 제7권1호
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    • pp.94-112
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    • 2001
  • The main purpose of this study was to investigate the effectiveness of a standardized patients managed instruction program for a fundamentals of nursing. The standardized patients managed instruction was evaluated by using a quasi-experimental, nonequivalent control group posttest design with two separate classes of sophomore students attending fundamentals of nursing classes at one baccaleureate nursing school in Korea. Control group was taught by traditional lecture/model instruction and experimental group was taught by standardized patient managed instruction. Data were collected from December, 1999 to July, 2000 using checklist developed by researcher on following areas; clinical nursing performance, communication skills, and learning motivation. There were 36 students in the experimental group and 40 students in the control group. Data analysis was done using SPSS WINDOW. The results were summarized as follows ; 1. Clinical nursing performances were evaluated by change position, back care and hot bag apply. The total score was statistically significant higher in the experimental group than the control group(t=3.325, p=.000). Thus hypothesis 1 was supported. 2. Communication skill was evaluated by professional attitude and ability to explain to patients. There was a statistically significant difference between the experimental group and the control group (t=4.232, p=.000). Thus hypothesis 2 was supported. 3. Learning motivation was evaluated by self-reported questionnaires. There was statistically a significant difference between the experimental group and the control group(t=3.024, p=.004). Thus hypothesis 3 was supported. In conclusion, this study suggests that standardized patients managed instruction is an effective learning method to nursing students. By utilizing a standardized patient managed instruction, learning can proceed in a more relaxed environment and reduce the risks to patients because student inexperience are avoided. It is recommended to develop more standardized patients cases for wider areas of nursing educational and evaluate the program with more students using logitudinal method.

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광 삼각법 측정 알고리즘을 이용한 자동차 도어 간격 측정 및 보정에 관한 연구 (A study on measurement and compensation of automobile door gap using optical triangulation algorithm)

  • 강동성;이정우;고강호;김태민;박규백;박정래;김지훈;최두선;임동욱
    • Design & Manufacturing
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    • 제14권1호
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    • pp.8-14
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    • 2020
  • In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

CNN을 적용한 한국어 상품평 감성분석: 형태소 임베딩을 중심으로 (Sentiment Analysis of Korean Reviews Using CNN: Focusing on Morpheme Embedding)

  • 박현정;송민채;신경식
    • 지능정보연구
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    • 제24권2호
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    • pp.59-83
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    • 2018
  • 고객과 대중의 니즈를 파악하기 위한 감성분석의 중요성이 커지면서 최근 영어 텍스트를 대상으로 다양한 딥러닝 모델들이 소개되고 있다. 본 연구는 영어와 한국어의 언어적인 차이에 주목하여 딥러닝 모델을 한국어 상품평 텍스트의 감성분석에 적용할 때 부딪히게 되는 기본적인 이슈들에 대하여 실증적으로 살펴본다. 즉, 딥러닝 모델의 입력으로 사용되는 단어 벡터(word vector)를 형태소 수준에서 도출하고, 여러 형태소 벡터(morpheme vector) 도출 대안에 따라 감성분석의 정확도가 어떻게 달라지는지를 비정태적(non-static) CNN(Convolutional Neural Network) 모델을 사용하여 검증한다. 형태소 벡터 도출 대안은 CBOW(Continuous Bag-Of-Words)를 기본적으로 적용하고, 입력 데이터의 종류, 문장 분리와 맞춤법 및 띄어쓰기 교정, 품사 선택, 품사 태그 부착, 고려 형태소의 최소 빈도수 등과 같은 기준에 따라 달라진다. 형태소 벡터 도출 시, 문법 준수도가 낮더라도 감성분석 대상과 같은 도메인의 텍스트를 사용하고, 문장 분리 외에 맞춤법 및 띄어쓰기 전처리를 하며, 분석불능 범주를 포함한 모든 품사를 고려할 때 감성분석의 분류 정확도가 향상되는 결과를 얻었다. 동음이의어 비율이 높은 한국어 특성 때문에 고려한 품사 태그 부착 방안과 포함할 형태소에 대한 최소 빈도수 기준은 뚜렷한 영향이 없는 것으로 나타났다.