• 제목/요약/키워드: binary vector

검색결과 370건 처리시간 0.028초

오이 모자이크 바이러스 위성RNA의 cDNA가 도입된 형질전환 담배의 육성 (Transgenic Tobacco Plants Introduced with cDNA of Cucumber Mosaic Virus Satellite RNA)

  • 이상용;홍은주;최장경
    • 한국식물병리학회지
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    • 제11권1호
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    • pp.80-86
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    • 1995
  • The cDNA of CMV-As satellite RNA was introduced into tobacco plants (Nicotiana tabacum cv. Samsun NN) using a binary Ti plasmid vector system of Agrobacterium tumefaciens. The cDNA of satellite RNA introduced into tobacco plants was detected by polymerase chain reaction (PCR) and molecular hybridization analyses. Symptom development was distinctly suppressed in the transgenic tobacco plants when inoculated with CMV-Co. CMV concentration in the transgenic tobacco plants was decreased to 1/40 of non-transgenic tobacco plants. The kanamycin resistance gene of the transgenic tobacco plants was also detected in the progeny.

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이진분열 알고리즘에 기반한 계층적 구조의 시공간 영상 분할 (Spatio-Temporal Image Segmentation Using Hierarchical Structure Based on Binary Split Algorithm)

  • 박영식;송근원;정의윤;한규필;하영호
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1997년도 학술대회
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    • pp.145-149
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    • 1997
  • In this paper, a hierarchical spatio-temporal image segmentation method based on binary split algorithm is proposed. Intensity and displacement vector at each pixel are used for image segmentation. The displacement vectors between two image frames which skip over one or several frames can be approximated by accumulating of the velocity vectors calculated from optical flow between two successive frames when the time interval between the two image frames is short enough or the motion is slow. The pixels whose displacement vector and intensity are ambiguous are precisely decided by the modified watershed algorithm using the proposed priority measure. In the experiment, the region of moving object is precisely segmented.

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증발하는 이성분혼합물 액적의 유동장 해석 (Investigation of Internal Flow Fields of Evaporating of Binary Mixture Droplets)

  • 김형수
    • 한국가시화정보학회지
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    • 제15권2호
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    • pp.21-25
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    • 2017
  • If a liquid droplet evaporates on a solid substrate, when it completely dries, it leaves a peculiar pattern, which depends on the composition of the liquid. Not only a single component liquid but also complex liquids are studied for a different purpose. In particular, a binary mixture droplet has been widely studied and used for an ink-jet printing technology. In this study, we focus on investigating to visualize the internal flow field of an ethanol-water mixture by varying a concentration ratio between two liquids. We measure the in-plane velocity vector fields and vorticities. We believe that this fundamental study about the internal flow field provides a basic idea to understand the dried pattern of the binary mixture droplet.

Customer Level Classification Model Using Ordinal Multiclass Support Vector Machines

  • Kim, Kyoung-Jae;Ahn, Hyun-Chul
    • Asia pacific journal of information systems
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    • 제20권2호
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    • pp.23-37
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    • 2010
  • Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.

인체 모유 단백질 및 영양 성분 강화 고부가가치 기능성 쌀 생산 벼 품종 개발 전략 (Development Strategy for functional rice improved with human lactoferrin and enhancement of nutrient compounds)

  • 임성렬;이진형;이효연;서석철
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2002년도 춘계 학술대회지
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    • pp.48-50
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    • 2002
  • A strategy for development of a functional rice in proved with human lactoferrin and enhancement of nutrient compounds was planned. For the purposes we have cloned and characterized a human lactoferrin cDNA from human mammary gland cDNA library A endosperm storage vacuole targeting sequence and the cDNA fragment was linked to endosperm specific glutelin promoter. The fusion gene fragment was inserted into a binary vector containing MAR gene. In addition a new ${\beta}$-galactosidase gene from Bifidobacterium of human was used as a reporter gene in the vector system, Rice plants showing a high concentration of amino acids in the endosperm cells were developed by using a biochemical mutation and bred for the transformation with the binary vector system Finally we have established a transformation method for the rice endosperm cells.

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서포트벡터머신을 이용한 충격전 낙상방향 판별 (Determination of Fall Direction Before Impact Using Support Vector Machine)

  • 이정근
    • 센서학회지
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    • 제24권1호
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    • pp.47-53
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    • 2015
  • Fall-related injuries in elderly people are a major health care problem. This paper introduces determination of fall direction before impact using support vector machine (SVM). Once a falling phase is detected, dynamic characteristic parameters measured by the accelerometer and gyroscope and then processed by a Kalman filter are used in the SVM to determine the fall directions, i.e., forward (F), backward (B), rightward (R), and leftward (L). This paper compares the determination sensitivities according to the selected parameters for the SVM (velocities, tilt angles, vs. accelerations) and sensor attachment locations (waist vs. chest) with regards to the binary classification (i.e., F vs. B and R vs. L) and the multi-class classification (i.e., F, B, R, vs. L). Based on the velocity of waist which was superior to other parameters, the SVM in the binary case achieved 100% sensitivities for both F vs. B and R vs. L, while the SVM in the multi-class case achieved the sensitivities of F 93.8%, B 91.3%, R 62.3%, and L 63.6%.

이진화상 잡음제거 연산자에 관한 연구 (Implementation of the noise eliminating operators of binary image)

  • 홍희경;조동섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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    • pp.636-639
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    • 1988
  • This paper suggests the operation performing the noise elimination of binary image. The image is read by the scanner. And operand is selected according to the size of input image. Through the Dilation and Erosion, elementary vector operation with selected operand, the noise of input image is eliminated.

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Cross-architecture Binary Function Similarity Detection based on Composite Feature Model

  • Xiaonan Li;Guimin Zhang;Qingbao Li;Ping Zhang;Zhifeng Chen;Jinjin Liu;Shudan Yue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권8호
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    • pp.2101-2123
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    • 2023
  • Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

고속 이미지 검색을 위한 2진 시각 단어 생성 기법 (Binary Visual Word Generation Techniques for A Fast Image Search)

  • 이수원
    • 정보과학회 논문지
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    • 제44권12호
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    • pp.1313-1318
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    • 2017
  • 다수의 지역 특징들을 취합하여 하나의 벡터로 표현하는 것은 이미지 검색의 핵심 기술이다. 이 과정에서 경사도 기반 특징에 비해 수십 배 빠르게 추출되는 2진 특징이 활용된다면 이미지 검색의 고속화가 가능하다. 이를 위해서는 2진 특징들을 군집하여 2진 시각 단어를 생성하는 기법에 대한 연구가 선행되어야 한다. 기존의 경사도 기반 특징들을 군집하는 전통적인 방식으로는 2진 특징들을 군집할 수 없기 때문이다. 이를 위해 본 논문은 2진 특징들을 군집하여 2진 시각 단어를 생성하는 기법들에 대해 연구한다. 실험을 통해 2진 특징의 활용이 이미지 검색에 미치는 정확도와 연산효율 사이의 상충관계에 대해 분석한 후, 제안한 기법들을 비교한다. 본 연구는 고속 이미지 검색을 필요로 하는 모바일 응용, 리얼 타임 응용, 웹 스케일 응용 등에 활용될 것으로 기대된다.

객체별 특징 벡터 기반 3D 콘텐츠 모델 해싱 (3D Content Model Hashing Based on Object Feature Vector)

  • 이석환;권기룡
    • 전자공학회논문지CI
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    • 제47권6호
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    • pp.75-85
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    • 2010
  • 본 논문에서는 3D 콘텐츠 인증을 위한 객체별 특징 벡터 기반 강인한 3D 모델 해싱을 제안한다. 제안한 3D 모델 해싱에서는 다양한 객체들로 구성된 3D 모델에서 높은 면적을 가지는 특징 객체내의 꼭지점 거리들을 그룹화한다. 그리고 각 그룹들을 치환한 다음, 그룹 계수, 랜덤 변수 키와 이진화 과정에 의하여 최종 해쉬를 생성한다. 이 때 해쉬의 강인성은 객체 그룹별 꼭지점 거리 분포를 그룹 계수에 의하여 향상되고, 해쉬의 유일성은 그룹 계수를 치환 키 및 랜덤변수 키 기반의 이진화 과정에 의하여 향상된다. 실험 결과로부터 제안한 해싱이 다양한 메쉬 공격 및 기하학 공격에 대한 해쉬의 강인성과 유일성을 확인하였다.