• Journal of Plant Biotechnology
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• v.35 no.4
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• pp.275-280
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• 2008

One of the limitation for Agrobacterium-mediated transformation via organogenesis from cotyledon explants routinely in cucumber is the production of chimeric plants. To overcome the limitation, Agrobacterium-mediated transformation system via somatic embryogenesis from hypocotyl explants of cucumber (c.v., Eunsung) on the selection medium with paromomycin as antibiotics was developed. The hypocotyl explants were inoculated with Agrobacterium tumefaciens strain EHA101 carrying binary vector pPTN290; then were subsequently cultured on the following media: co-cultivation medium for 2 days, selection medium for $5{\times}14$ days, and regeneration medium. The T-DNA of the vector (pPTN290) carried two cassettes, Ubi promoter-gus gene as reporter and 35S promoter-nptll gene conferring resistance to paromomycin as selectable agent. The confirmation of stable transformation and the efficiency of transformation was based on the resistance to paromomycin indicated by the growth of putative transgenic calli on selection medium amended with 100mg/L paromomycin, and GUS gene expression. Forty eight clones (5.2%) with GUS gene expressed of 56 callus clones with resistance to paromomycin were independently obtained from 928 explants inoculated. Of 48 clones, transgenic plants were only regenerated from 5 clones (0.5%) at low frequency. The histochemical GUS assay in the transgenic seeds ($T_1$) also revealed that the gus gene was successfully integrated and segregated into each genome of transgenic cucumber.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.525-535
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• 2018

If the frequency of a particular class is excessively higher than the frequency of other classes in the classification problem, data imbalance problems occur, which make machine learning distorted. Corporate bankruptcy prediction often suffers from data imbalance problems since the ratio of insolvent companies is generally very low, whereas the ratio of solvent companies is very high. To mitigate these problems, it is required to apply a proper sampling technique. Until now, oversampling techniques which adjust the class distribution of a data set by sampling minor class with replacement have popularly been used. However, they are a risk of overfitting. Under this background, this study proposes ROSE(Random Over Sampling Examples) technique which is proposed by Menardi and Torelli in 2014 for the effective corporate bankruptcy prediction. The ROSE technique creates new learning samples by synthesizing the samples for learning, so it leads to better prediction accuracy of the classifiers while avoiding the risk of overfitting. Specifically, our study proposes to combine the ROSE method with SVM(support vector machine), which is known as the best binary classifier. We applied the proposed method to a real-world bankruptcy prediction case of a Korean major bank, and compared its performance with other sampling techniques. Experimental results showed that ROSE contributed to the improvement of the prediction accuracy of SVM in bankruptcy prediction compared to other techniques, with statistical significance. These results shed a light on the fact that ROSE can be a good alternative for resolving data imbalance problems of the prediction problems in social science area other than bankruptcy prediction.

• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.174-185
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• 2010

Full-length cDNAs are essential for the correct annotation of genomic sequences and for the functional analysis of genes and their products. To elucidate the functions of a large population of Chinese cabbage (Brassica rapa) genes and to search efficiently for agriculturally useful genes, we have been taking advantage of the full-length cDNA Over-eXpresser (FOX) gene hunting system. With oligo dT column it purify the each mRNA from the flower organs, leaf and stem tissue. And about 120,000 cDNAs from the library were transformed into $\lambda$-pFLCIII-F vector. Of which 115,000 cDNAs from the library were transformed into T-DNA binary vector, pBigs for transformation study. We used normalized full-length cDNA and introduced each cDNA into Arabidopsis by in planta transformation. Full-length Chinese cabbage cDNAs were expressed independently under the CaMV 35S promoter in Arabidopsis. Selfed seeds were harvested from transgenic Arabidopsis. We had selected 2,500 transgenic plants by hygromycin antibiotic tolerant test, and obtained a number of transgenic mutants. Each transgenic Arabidopsis was investigated in morphological changes, fertility and leaf colour. As a result, 285 possible morphological mutants were identified. Introduced cDNA was isolated by PCR amplification of the genomic DNA from the transgenic mutants. Sequencing result and BLAST analysis showed that most of the introduced cDNA were complete cDNAs and functional genes. Also, we examined the effect of Bromelain on enhancing resistance to soft rot in transgenic Chinese cabbage 'Osome'. The bromelain gene identified from FOX hunting system was transformed into Chinese cabbage using Agrobacterium methods. Transformants were screened by PCR, then RT-PCR and real time PCR were performed to analyze gene expression of cysteine protease in the T1 and T2 generations. The anti-bacterial activity of bromelain was tested in Chinese cabbages infected with soft rot bacteria. The results showed that the over-expressed bromelain gene from pineapple conferred enhanced resistance to soft rot in Chinese cabbage.

• School Mathematics
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• v.5 no.4
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• pp.421-440
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• 2003

It is difficult for the learner to understand completely the ratio concept which forms a basis of proportional reasoning. And proportional reasoning is, on the one hand, the capstone of children's elementary school arithmetic and, the other hand, it is the cornerstone of all that is to follow. But school mathematics has centered on the teachings of algorithm without dealing with its essence and meaning. The purpose of this study is to analyze the essence of ratio concept from multidimensional viewpoint. In addition, this study will show the direction for improvement of ratio concept. For this purpose, I tried to analyze the historical development of ratio concept. Most mathematicians today consider ratio as fraction and, in effect, identify ratios with what mathematicians called the denominations of ratios. But Euclid did not. In line with Euclid's theory, ratio should not have been represented in the same way as fraction, and proportion should not have been represented as equation, but in line with the other's theory they might be. The two theories of ratios were running alongside each other, but the differences between them were not always clearly stated. Ratio can be interpreted as a function of an ordered pair of numbers or magnitude values. A ratio is a numerical expression of how much there is of one quantity in relation to another quantity. So ratio can be interpreted as a binary vector which differentiates between the absolute aspect of a vector -its size- and the comparative aspect-its slope. Analysis on ratio concept shows that its basic structure implies 'proportionality' and it is formalized through transmission from the understanding of the invariance of internal ratio to the understanding of constancy of external ratio. In the study, a fittingness(or comparison) and a covariation were examined as the intuitive origins of proportion and proportional reasoning. These form the basis of the protoquantitative knowledge. The development of sequences of proportional reasoning was examined. The first attempts at quantifying the relationships are usually additive reasoning. Additive reasoning appears as a precursor to proportional reasoning. Preproportions are followed by logical proportions which refer to the understanding of the logical relationships between the four terms of a proportion. Even though developmental psychologists often speak of proportional reasoning as though it were a global ability, other psychologists insist that the evolution of proportional reasoning is characterized by a gradual increase in local competence.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• Korean Journal of Plant Tissue Culture
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• v.25 no.3
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• pp.147-152
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• 1998

AL1-gene, necessary for the replication of the genome of a gemini virus TGMV, was inserted in the opposite direction to the promoter CaMV35S resulting in the construction of a plant transformation binary vector pAR35-2. The vector pAR35-2 contains the chimeric gene cassette involving the duplicated promoter CaMV35S, opposite direction of AL1-gene fusioned with hygromycin resistant gene, and the gene cassette of the neomycin phosphotransferase II gene. The plasmid was transferred to tobacco and tomato plants by leaf disk infection via Agrobacterium. The transgenic plants were selected and grown on the MS-agar medium containing kanamycin and hygromycin. The shoots induced from the calli were regenerated to the whole transgenic plants. The antisense AL1-gene was detected in the genomic DNA isolated from the leaves by using the PCR mediated Southern blot analysis. The expression of the antisense AL1-gene was also observed using the RT-PCR mediated Southern blot analysis. The observation of chloroplasts in guard cell pair indicated that the transgenic tomato plants were diploid.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.359-366
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• 2021

A number of construction companies in Korea invest considerable human and financial resources to construct a system for managing apartment defect data and for categorizing repair tasks. Thus, this study proposes machine learning models to automatically classify defect complaint text-data into one of the sub categories of 'finishing work' (i.e., one of the defect repair tasks). In the proposed models, we employed two word representation methods (Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF)) and two machine learning classifiers (Support Vector Machine, Random Forest). In particular, we conducted both binary- and multi- classification tasks to classify 9 sub categories of finishing work: home appliance installation work, paperwork, painting work, plastering work, interior masonry work, plaster finishing work, indoor furniture installation work, kitchen facility installation work, and tiling work. The machine learning classifiers using the TF-IDF representation method and Random Forest classification achieved more than 90% accuracy, precision, recall, and F1 score. We shed light on the possibility of constructing automated defect classification systems based on the proposed machine learning models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.83-97
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• 2021

Wireless sensors that make up the Wireless Sensor Network generally have extremely limited power and resources. The wireless sensor enters the sleep state at a certain interval to conserve power. The Sleep deflation attack is a deadly attack that consumes power by preventing wireless sensors from entering the sleep state, but there is no clear countermeasure. Thus, in this paper, using clustering-based binary search tree structure, the Sleep deprivation attack detection model is proposed. The model proposed in this paper utilizes one of the characteristics of both attack sensor nodes and normal sensor nodes which were classified using machine learning. The characteristics used for detection were determined using Long Short-Term Memory, Decision Tree, Support Vector Machine, and K-Nearest Neighbor. Thresholds for judging attack sensor nodes were then learned by applying the SVM. The determined features were used in the proposed algorithm to calculate the values for attack detection, and the threshold for determining the calculated values was derived by applying SVM.Through experiments, the detection model proposed showed a detection rate of 94% when 35% of the total sensor nodes were attack sensor nodes and improvement of up to 26% in power retention.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• Journal of Microbiology and Biotechnology
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• v.10 no.3
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• pp.415-418
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• 2000

Productivity of a rice plant is greatly influenced by salt stress. One of the ways to achieve tolerance to salinity is to transfer genes encoding protective enzymes from other organisms, such as microorganisms. The bacterial gene, mtlD, which encodes mannitol-1-phosphate dehydrogenase (Mtl-DH), was introduced to the cytosol of a rice plant by an imbibition technique to overproduce mannitol. The germination and survival rate of the imbibed rice seeds were markedly increased by transferring the mtlD gene when it was delivered in either a pBIN19 or pBmin binary vector. When a polymerase chain reaction was performed with the genomic DNAs of the imbibed rice leaves as a template and with mtlD-specific primers, several lines were shown to contain an exogenous mtlD DNA. However, a reverse transcription (RT)-PCR analysis revealed that not all of them showed an expression of this foreign gene. This paper demonstrates that the growth and germination of rice plants transiently transformed with the bacterial gene, mtlD, are enhanced and these enhancements may have resulted from the experssion of the mtlD gene. The imbibition method empolyed in this study fulfills the requirements for testing the function of such a putative gene in vivo prior to the production of a stable transgenic plant.