• Korean Journal Plant Pathology
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• v.11 no.1
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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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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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.

• Journal of the Korean Society of Visualization
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• v.15 no.2
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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.

• Asia pacific journal of information systems
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• v.20 no.2
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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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2002.05a
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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.

• Journal of Sensor Science and Technology
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• v.24 no.1
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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%.

• Proceedings of the KIEE Conference
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• 1988.07a
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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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.

• Journal of KIISE
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• v.44 no.12
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• pp.1313-1318
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• 2017

Aggregating local features in a single vector is a fundamental problem in an image search. In this process, the image search process can be speeded up if binary features which are extracted almost two order of magnitude faster than gradient-based features are utilized. However, in order to utilize the binary features in an image search, it is necessary to study the techniques for clustering binary features to generate binary visual words. This investigation is necessary because traditional clustering techniques for gradient-based features are not compatible with binary features. To this end, this paper studies the techniques for clustering binary features for the purpose of generating binary visual words. Through experiments, we analyze the trade-off between the accuracy and computational efficiency of an image search using binary features, and we then compare the proposed techniques. This research is expected to be applied to mobile applications, real-time applications, and web scale applications that require a fast image search.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.75-85
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• 2010

This paper presents a robust 3D model hashing based on object feature vector for 3D content authentication. The proposed 3D model hashing selects the feature objects with highest area in a 3D model with various objects and groups the distances of the normalized vertices in the feature objects. Then we permute groups in each objects by using a permutation key and generate the final binary hash through the binary process with the group coefficients and a random key. Therefore, the hash robustness can be improved by the group coefficient from the distance distribution of vertices in each object group and th hash uniqueness can be improved by the binary process with a permutation key and a random key. From experimental results, we verified that the proposed hashing has both the robustness against various mesh and geometric editing and the uniqueness.