• 제목/요약/키워드: Algorism

검색결과 225건 처리시간 0.032초

Practical Algorisms for PCR-RFLP-Based Genotyping of Echinococcus granulosus Sensu Lato

  • Kim, Hye-Jin;Yong, Tae-Soon;Shin, Myeong Heon;Lee, Kyu-Jae;Park, Gab-Man;Suvonkulov, Uktamjon;Kovalenko, Dmitriy;Yu, Hak Sun
    • Parasites, Hosts and Diseases
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    • 제55권6호
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    • pp.679-684
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    • 2017
  • Echinococcus granulosus sensu lato (s.l.) is a causative agent of cystic echinococcosis or cystic hydatid disease in humans and domestic and wild animals. The disease is a serious health problem in countries associated with poverty and poor hygiene practices, particularly in livestock raising. We introduced a practical algorism for genotyping the parasite, which may be useful to many developing countries. To evaluate the efficiency of the algorism, we genotyped 3 unknown strains isolated from human patients. We found that unknowns 1 and 3 were included in G1, G2, and G3 genotypes group and unknown 2 was included in G4 genotype (Echinococcus equinus) according to the algorisms. We confirmed these results by sequencing the 3 unknown isolates cox1 and nad1 PCR products. In conclusion, these new algorisms are very fast genotype identification tools that are suitable for evaluating E. granulosus s.l. isolated from livestock or livestock holders, particularly in developing countries.

Near infrared spectroscopy for classification of apples using K-mean neural network algorism

  • Muramatsu, Masahiro;Takefuji, Yoshiyasu;Kawano, Sumio
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1131-1131
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    • 2001
  • To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

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배경분리 방법에 의한 이동 물체 검출에서 개선된 색정보 정규화 기법에 관한 연구 (A Study on the Revised Method using Normalized RGB Features in the Moving Object Detection by Background Subtraction)

  • 박종범
    • 한국ITS학회 논문지
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    • 제12권6호
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    • pp.108-115
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    • 2013
  • 영상취득 장치를 이용한 지능화된 감시 장치의 개발 기술 또한 발전하고 있다. 이 분야의 기술 영역은 감시하고 있는 장소에 어떤 사람이나 물체를 탐지하는 전경 분리 기술과 사람이나 물체의 이동 경로를 파악하는 추적 기술로 나뉜다. 본 논문에서는 이동체를 탐지하는 기술로서 잡음이나 조도의 변화에 비교적 안정적인 엔진개발을 위한 개선된 알고리즘을 제안한다. 논문의 제안 알고리즘은 사람이나, 동물, 또는 비교적 저속 운행 중인 차량 등의 탐지에 적합한 모델로서, 조도의 변화나 잡음에 안정적이면서 실시간 처리가 가능한 방법을 고안하는 데 주안점을 두고 있다.

시간 지도에 관한 초등수학교과서 비교 연구 - 한국, 싱가포르, 일본을 중심으로 - (A Study on Textbooks of South Korea, Singapore, and Japan Focused on the Teaching of the Time)

  • 조영미;임선혜
    • 한국초등수학교육학회지
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    • 제14권2호
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    • pp.421-440
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    • 2010
  • 본 연구에서는 시간 지도 개선에 관한 시사점을 찾고자 한국, 싱가포르, 일본의 초등학교 수학교과서를 비교 분석하였다. 연구 결과에 따르면, 우리나라는 두 나라에 비해 시간의 덧셈과 뺄셈의 사칙 계산과 그 알고리즘이 강조되고 있었다. 또한 두 나라에 비해 시간 지도 요소 항목이 많이 편이었으며, 소재와 시계 모형에 있어서도 유사한 것들이 반복 사용되고 있었다. 마지막으로 시간의 흐름이 적게 반영되어 있었다.

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GIS를 활용한 해양환경관리에 관한 연구 I - LDI 알고리즘 적용을 위한 보간법에 관한 연구 - (A Study on the GIS for The Sea Environmental Management I - Focus on the Study of A Interpolation on The Application of LDI Algorism -)

  • 이형민;박기학
    • 환경영향평가
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    • 제15권6호
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    • pp.443-452
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    • 2006
  • Today, satellite remote sensing (RS) and geographic information systems (GIS) plays an important role as an advanced science and technology. This study was developed a Line Density Algorithm which was clarify and describe the thermal front by using NOAA SST (sea surface temperature) and GIS spatial analysis for systemic and effective management of fish raising industry and sea environmental pollution by land reclamation program. Before this, a study about a interpolation method was carry out which was very important for estimate the hidden value between a special point. For this study Inverse Distance Weighted interpolation, Spline interpolation, Kriging interpolation methods were choose and SST data from 2001 to 2004 in spring (March, April, May) were analyzed. According to the study Kriging interpolation method was the very adaptive method from a practical point of view and excellent in description and precision then others. Finally, the result of this study will be use for develope the Line Density Index Algorism.

교사의 수학에 대한 신념이 수업 방법과 학생의 문제해결 수행에 미치는 영향 (The Effects of Teacher's Beliefs about Mathematics on the Method of Class and the Performance of Problem Solving)

  • 김시년
    • 한국수학교육학회지시리즈C:초등수학교육
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    • 제3권1호
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    • pp.79-88
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    • 1999
  • This paper shows how the social tradition and belief of korea on education affects teachers and students and learning. 1 Interview with teacher. During surveying this teacher's class, we knowed that the teacher have accentuated algorism loaming and preparation fur external examination in math class. Teacher's beliefs about mathematics have a strong effect on the method of class and the performance of problem solving 2. Interview with students and short test. 1) Students usually had fine ability of calculation for number. But Many pupils didn't know the meaning of the operations. 2) The most of pupils are good at routine math problem solving but when the question whose the condition don't meet was given, they experienced difficulties.3.Korean sociocultural specialty on education: The korean place high emphasis on education and think of education as the means of success. This emphasis can be traced to the Confucian view. 1) tradition on examination culture. 2) the traditional convention of the learning method. Korean sociocultural specialty on education play role of strengthen role learning and algorism class. The important things to education reformation are getting a balance between practice and understanding. we should make changes not only in national dimension but also in math class.

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다중코어 GPU를 위한 병렬처리 보간 알고리즘 구현 (Implementation of Parallel Processing Interpolation Algorithm for Multicore GPU)

  • 이광엽;김치용
    • 전기전자학회논문지
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    • 제16권4호
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    • pp.304-309
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    • 2012
  • 최근 디스플레이의 해상도가 높아짐에 따라 그래픽 하드웨어가 처리해야할 데이터량과 연산량이 증가 하고 있다. 특히 레스터라이저의 데이터 처리량이 크게 증가 하고 있다. 본 논문은 높은 해상도의 많은 데이터를 빠르게 처리하기 위하여 레스터라이저를 병렬로 설계 하였다. 본 논문은 레스터라이저의 병렬화를 용이하게 하기 위하여 기존 보간 단계에서 사용하는 Bilinear 알고리즘[1] 대신 삼각형의 무게중심 좌표와 넓이를 이용하는 알고리즘을 사용하였다. 설계한 레스터라이저를 FPGA 환경에서 구현하여 기존 레스터라이저와 비교 검증 하였다. 기존 레스터라이저와 비교 결과 성능이 약 50퍼센트 상승 하였다.