• Title/Summary/Keyword: binary vector

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Genetic Transformation of Panax ginseng with Herbicide Resistant Gene (제초제 저항성 유전자에 의한 인삼의 형질전환)

  • 양계진
    • Korean Journal of Plant Tissue Culture
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    • v.28 no.6
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    • pp.353-357
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    • 2001
  • Transformation of ginseng plants was achieved by biolistic system with cotyledon explants and callus using phosphinothricin acetyl-transferase (PAT) gene resisting to a herbicide of Bialaphos. The binary vector for transformation was constructed with disarmed Ti-plasmid and with double 355 promoter. The introduced NPT II and PAT genes of the transgenic ginseng plants were successfully identified by the PCR, and the survival test on the medium with basta. The transgenic ginseng plants were propagated using repetitive secondary embryogenesis. The transgenic ginseng plantlets had normal structures of roots and shoots, and dormant buds for new year sprouting. We transferred the transgenic plants to greenhouse and observed the continuing growth until a new year.

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A Study on Identification of Track Irregularity of High Speed Railway Track Using an SVM (SVM을 이용한 고속철도 궤도틀림 식별에 관한 연구)

  • Kim, Ki-Dong;Hwang, Soon-Hyun
    • Journal of Industrial Technology
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    • v.33 no.A
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    • pp.31-39
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    • 2013
  • There are two methods to make a distinction of deterioration of high-speed railway track. One is that an administrator checks for each attribute value of track induction data represented in graph and determines whether maintenance is needed or not. The other is that an administrator checks for monthly trend of attribute value of the corresponding section and determines whether maintenance is needed or not. But these methods have a weak point that it takes longer times to make decisions as the amount of track induction data increases. As a field of artificial intelligence, the method that a computer makes a distinction of deterioration of high-speed railway track automatically is based on machine learning. Types of machine learning algorism are classified into four type: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. This research uses supervised learning that analogizes a separating function form training data. The method suggested in this research uses SVM classifier which is a main type of supervised learning and shows higher efficiency binary classification problem. and it grasps the difference between two groups of data and makes a distinction of deterioration of high-speed railway track.

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Stress Detection and Classification of Laying Hens by Sound Analysis

  • Lee, Jonguk;Noh, Byeongjoon;Jang, Suin;Park, Daihee;Chung, Yongwha;Chang, Hong-Hee
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.4
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    • pp.592-598
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    • 2015
  • Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.

Direct Regeneration of Transgenic Buckwheat from Hypocotyl Segment by Agrobacterium-mediated Transformation

  • Kim, Hyun-Soon;Kang, Hyeon-Jung;Lee, Young-Tae;Lee, Seung-Yeob;Ko, Jeong-Ae;Rha, Eui-Shik
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.5
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    • pp.375-379
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    • 2001
  • Transgenic plants from hypocotyl segments of buckwheat were produced with the Agrobacterium strain LBA4404 harboring the binary vector pBI121 containing chimeric genes of neomycin phosphotransferase II (npt II) and $\beta$-glucuronidase (gus). Two weeks after co-cultivation with Agrobacterium, most of the hypocotyl segments gradually became brown and died on the selection medium containing 100mg/$\ell$ of kanamycin. Plants regenerated from the hypocotyl explants grown on selection medium were GUS-positive in the leaf, stem and vascular tissues by histochemical assay, and varied in gus activity (440-2568 pmol, 4-MU/mg protein) by fluorimetry. The plants showing GUS activity were confirmed of containing GUS and NPT-II genes by polymerase chain reaction (PCR). Within 3 months, transgenic buckwheat plants were able to obtained from the hypocotyl segments.

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Efficiency of transformation mediated by Agrobacterium tumefaciens using vacuum infiltration in rice (Oryza sativa L.)

  • Safitri, Fika Ayu;Ubaidillah, Mohammad;Kim, Kyung-Min
    • Journal of Plant Biotechnology
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    • v.43 no.1
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    • pp.66-75
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    • 2016
  • Agrobacterium-mediated gene transfer has recently been developed to improve rice transformation. In this study, 3 different transformation methods were tested including soaking, co-cultivation, and vacuum infiltration. Agrobacterium tumefaciens GV3101 harboring the binary vector pGreen:: LeGSNOR was used in this experiment. This study aimed to identify the most appropriate method for transferring LeGSNOR into rice. Vacuum infiltration of the embryonic calli for 5 min in Ilpum resulted in high transformation efficiency based on confirmation by PCR, RT-PCR, and qRT-PCR analyses. In conclusion, we described the development of an efficient transformation protocol for the stable integration of foreign genes into rice; furthermore, the study results confirmed that PCR is suitable for efficient detection of the integrated gene. The vacuum infiltration system is a potentially useful tool for future studies focusing on transferring important genes into rice seed calli, and may help reduce time and effort.

MdMADS2 - transgenic chrysanthemum (Dendranthema grandiflorum (Ramat.) Kitamura) showing the reduction of the days to flowering

  • Han, Bong-Hee;Lee, Su-Young;Choi, Seong-Youl
    • Journal of Plant Biotechnology
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    • v.36 no.4
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    • pp.366-372
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    • 2009
  • This study was conducted to develop new lines expressing the characteristic of early flowering by introducing MdMADS2 gene in chrysanthemum (Dendranthema grandiflorum (Ramat.) Kitamura) ‘Zinba'. Transformation of chrysanthemum was conducted by Agrobacterium tumefaciens LBA4404 harboring the binary vector containing MdMADS2 controlled by double CaMV 35S promoters. Ninety three shoots were regenerated from 1,463 leaf segment explants cultured on the first selection medium (MS basal salts + 1.0 mg/L BA + 0.5 mg/L IAA + 10 mg/L kanamycin + 400 mg/L cefotaxime, pH 5.8) after co-cultivation, and 20 out of the 93 shoots rooted on the second selection medium containing 20 mg/L kanamycin and 400 mg/L cefotaxime. Many escapes (98.6%) were removed on the selection stage for rooting. Nineteen lines were confirmed as transgenic plant with transgene by PCR analysis. Six transgenic plants flowered 2-11 days earlier than non-transgenic plant without big change of phenotype, and especially, 3 (Mo-7, Mo-11, Mo-17) out of 6 transgenic lines showed a significant reduction in days to flowering compared to non-transgenic plant. Introduction and expression of MdMADS2 gene in them were confirmed by Southern and real-time PCR analyses, respectively.

An Optimized CLBP Descriptor Based on a Scalable Block Size for Texture Classification

  • Li, Jianjun;Fan, Susu;Wang, Zhihui;Li, Haojie;Chang, Chin-Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.288-301
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    • 2017
  • In this paper, we propose an optimized algorithm for texture classification by computing a completed modeling of the local binary pattern (CLBP) instead of the traditional LBP of a scalable block size in an image. First, we show that the CLBP descriptor is a better representative than LBP by extracting more information from an image. Second, the CLBP features of scalable block size of an image has an adaptive capability in representing both gross and detailed features of an image and thus it is suitable for image texture classification. This paper successfully implements a machine learning scheme by applying the CLBP features of a scalable size to the Support Vector Machine (SVM) classifier. The proposed scheme has been evaluated on Outex and CUReT databases, and the evaluation result shows that the proposed approach achieves an improved recognition rate compared to the previous research results.

Novel Method for Face Recognition using Laplacian of Gaussian Mask with Local Contour Pattern

  • Jeon, Tae-jun;Jang, Kyeong-uk;Lee, Seung-ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5605-5623
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    • 2016
  • We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

Implement of Realtime Character Recognition System for Numeric Region of Sportscast (스포츠 중계 화면 내 숫자영역에 대한 실시간 문자인식 시스템 구현)

  • 성시훈;전우성
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.5-8
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    • 2001
  • We propose a realtime numeric caption recognition algorithm that automatically recognizes the numeric caption generated by computer graphics (CG) and displays the modified caption using the recognized resource only when a valuable numeric caption appears in the aimed specific region of the live sportscast scene produced by other broadcasting stations. We extract the mesh feature from the enhanced binary image as a feature vector after acquiring the sports broadcast scenes using a frame grabber in realtime and then recover the valuable resource from just a numeric image by perceiving the character using the neural network. Finally, the result is verified by the knowledge-based rule set designed for more stable and reliable output and is displayed on a screen as the converted CC caption serving our purpose. At present, we have actually provided the realtime automatic mile-to-kilometer caption conversion system taking up our algorithm f3r the regular Major League Baseball (MLB) program being broadcasted live throughout Korea over our nationwide network. This caption conversion system is able to automatically convert the caption in mile universally used in the United States into that in kilometer in realtime, which is familiar to almost Koreans, and makes us get a favorable criticism from the TV audience.

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Transformation of a Filamentous Fungus Cryphonectria parasitica Using Agrobacterium tumefaciens

  • Park, Seung-Moon;Kim, Dae-Hyuk
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.9 no.3
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    • pp.217-222
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    • 2004
  • As Agrobacterium tumefaciens, which has long been used to transform plants, is known to transfer T-DNA to budding yeast, Saccharomyces cerevisiae, a variety of fungi were subjected to the A. tumefaciens-mediated transformation to improve their transformation frequency and feasibility. The A. tumefaciens-mediated transformation of chestnut blight fungus, Cryphonectria parasitica, is performed in this study as the first example of transformation of a hardwood fungal pathogen. The transfer of the binary vector pBIN9-Hg, containing the bacterial hygromycin B phosphotransferase gene under the control of the Aspergillus nidulans trpC promoter and terminator, as a selectable marker, led to the selection of more than 1,000 stable, hygromycin B-resistant transformants per 1${\times}$10$\^$6/ conidia of C. parasitica. The putative transformants appeared to be mitotically stable. The transformation efficiency appears to depend on the bacterial strain, age of the bacteria cell culture and ratio of fungal spores to bacterial cells. PCR and Southern blot analysis indicated that the marker gene was inserted at different chromosomal sites. Moreover, three transformants out of ten showed more than two hybridizing bands, suggesting more than two copies of the inserted marker gene are not uncommon.