• Korean Journal of Plant Tissue Culture
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• v.26 no.3
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• pp.163-169
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• 1999

This study was conducted to produce herbicide resistant plants by transferring phosphinothricin acetyltransferase (PAT) gene into Populus alba $\times$ Populus glandulosa No .3 using Agrobacterium tumefaciens MP 90/PAT. Leaf segments from in vitro grown shoots of hybrid poplar No. 3 were soaked in a AB medium containing Agrobacterium tumefaciens MP 90/PAT for 10 min and cocultivated for 2 days on MS medium containing 1.0 mg/L 2,4-D and 0.2mg/L kinetin (CIM). Putative transformed calli could be selected after cocultivation of leaf segments on CIM supplemented with 50mg/L kanamycin and 500mg/L cefotaxime for 3 weeks. The selected calli were cultured on CIM supplemented with 50 mg/L kanamycin and 500 mg/L cefotaxime for 5~8 weeks before transfer to WPM containing 1.0mg/L zeatin, 0.1mg/L BAP, 50 mg/L kanamycin and 500mg/L cefotaxime for shoot regeneration. Shoots were regenerated from the callus after 4 week cultivation, and the regenerants were grown on the same medium for 7~l0 weeks. The plants rooted on 1/2 WPM containing 0.2 mg/L IBA and 50 mg/L kanamycin. To confirm the gene insertion into plants, GUS activity was detected by histochemical assay in the transformed plants. Finally, the presence of both NPT II and PAT genes from the transgenic plants were confirmed by PCR amplification with the gene specific primers and subsequent PCR-Southern blot with DIG-labeled PAT gene probe. After acclimatization in pots for 4 weeks, the plants were sprayed by 3 mL/L of Basta to test resistance to the herbicide. The transgenic plants remained green, whereas all the control plants died after one week.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.105-112
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• 2018

To determine the position of receiver, the GPS (Global Positioning System) uses position information of satellites and pseudo ranges based on signals. These are reflected by surrounding structures and multipath errors occur. This paper proposes a method for multipath error reduction using digital images to enhance the accuracy. The goal of the study is to calculate the shielding environment of receiver using image processing and apply it to GPS positioning. The proposed method, firstly, performs a preprocessing to reduce the effect of noise on images. Next, it uses hough transform to detect the outline of building roofs and determines mask angles and permissible azimuth range. Then, it classifies the satellites according to the condition using the image processing results. Finally, base on point positioning, it computes the receiver position by applying a weight model that assigns different weights to the classified satellites. We confirmed that the RMSE (Root Mean Square Error) was reduced by 2.29m in the horizontal direction and by 15.62m in the vertical direction. This paper showed the potential for the hybrid of GPS positioning and image processing technology.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.102-109
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• 2008

In this paper, the robust hybrid modulation type classifier which use both HOS and WT key features and can recognize 10 digitally modulated signals without a priori information in multipath fading channel conditions is proposed. The proposed classifier developed using data taken field measurements in various propagation model (i,e., rural area, small town and urban area) for real world scenarios. The 9 channel data are used for supervised training and the 6 channel data are used for testing among total 15 channel data(i.e., holdout-like method). The Proposed classifier is based on HOS key features because they are relatively robust to signal distortion in AWGN and multipath environments, and combined WT key features for classifying MQAM(M=16, 64, 256) signals which are difficult to classify without equalization scheme such as AMA(Alphabet Matched Algorithm) or MMA(Multi-modulus Algorithm. To investigate the performance of proposed classifier, these selected key features are applied in SVM(Support Vector Machine) which is known to having good capability of classifying because of mapping input space to hyperspace for margin maximization. The Pcc(Probability of correct classification) of the proposed classifier shows higher than those of classifiers using only HOS or WT key features in both training channels and testing channels. Especially, the Pccs of MQAM 3re almost perfect in various SNR levels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.544-561
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• 2002

In this paper, we propose a new hybrid type of the routing protocol (Virtual Cluster-based Routing Protocol: VCRP) for mobile ad-hoc networks, based on a virtual cluster, which is defined as a narrow-sense network to exchange the basic information related to the routing among the adjacent nodes. This particular approach combines advantage of proactive routing protocol (PRP), which immediately provides the route collecting the network-wide topological and metric information, with that of reactive routing protocol, which relies on the route query packet to collect the route information on its way to the destination without exchanging any information between nodes. Furthermore, it also provides the back-up route as a byproduct, along with the optimal route, which leads to the VCBRP (Virtual Cluster-based Routing Protocol with Backup Route) establishing the alternative route immediately after a network topology is changed due to degradation of link quality and terminal mobility, Our simulation studies have shown that the proposed routing protocols are robust against dynamics of network topology while improving the performances of packet transfer delay, link failure ratio, and throughput over those of the existing routing protocols without much compromising the control overhead efficiency.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.3
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• pp.265-269
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• 2021

This study was conducted to provide primary data through analysis of zoysia grass genetic resources to develop grass cultivars with beneficial novel properties. Zoysia grass (Zoysia. spp) is native to Korea, and is mainly propagated through stolons. However, since seed coat treatment technology was developed, the breeding of sexually reproductive grass variants has become possible, necessitating characterization of the floret appearance rate in the secured zoysia grass genetic resource before developing sexually reproductive cultivars. In this experiment, 549 grass lines were examined, revealing that florets appear in only 43 lines (7.81%). Survival rates after transplantation, and stolon generation rates displayed a significant positive correlation (Rho = 0.44). Survival rates after transfer, and rates of stolon production displayed very low correlations with floret appearance (Rho = -0.11 and Rho = -0.06). No significant results were obtained in 43 lines that displayed >20% floret appearance. To breed sexually reproductive grass variants, it is thus necessary to secure more genetic resources, considering the low rate of floret appearance. Finding traits that predict floret appearance at an early stage is also required.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.805-813
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• 2018

The research was conducted with the purpose of providing effective safety and quality control system for assistive products for handicapped those are used extensively. Assistive products couldn't be classified independently due to collision with the act of medical device and lack in legal basis. The issues about safety and quality have been solved by other legal frames on a case by case basis. We couldn't find any abroad case of independent safety and quality control policy. For the practical solution, this article suggested hybrid classification system mixed with existing policies. Each classified branches are allocated to the appropriate policy of safety and quality control so those are ease of understanding and prospect. And also a delicacy process was suggested not to leave off any assistive products. Through these suggests of the improvement it is expected that blind areas of safety and quality control for assistive products for handicapped could be solved and identity of assistive products could be established to provide product safety for handicapped and boost relevant industries.

• Composites Research
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• v.34 no.1
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• pp.35-46
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• 2021

This paper aims to reduce weight by replacing the reinforcements of the B-pillar used in vehicles with CFRP(Carbon Fiber Reinforced Plastics) and GFRP(Glass Fiber Reinforced Plastics) from the existing steel materials. For this, it is necessary to secure structural stability that can replace the existing B-pillar while reducing the weight. Existing B-pillar are composed of steel reinforcements of various shapes, including a steel outer. Among these steel reinforcements, two steel reinforcements are to be replaced with composite materials. Each steel reinforcement is manufactured separately and bonded to the B-pillar outer by welding. However, the composite reinforcements presented in this paper are manufactured at once through compression and injection processes using patch-type CFRP and rib-structured GFRP. CFRP is attached to the high-strength part of the B-pillar to resist side loads, and the GFRP ribs are designed to resist torsion and side loads through a topology optimization technique. Through structural analysis, the designed composite B-pillar was compared with the existing B-pillar, and the weight reduction ratio was calculated.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.498-509
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• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• Korea Science and Art Forum
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• v.25
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• pp.463-475
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• 2016

As the transition to the digital age in the late 20th century, the intrinsic value of the craft, the emotional values of human, has been noticed as an alternative to overcome the adverse effects of the modernism of the industrial age. To introduce experimental tries which convergence of contemporary technologies and elements of traditional craft, and to inspire artists and present the new possibility of creation to them who want to take advantage of craft emotion as the elements of creation is the purpose of this study in the current digital technology age. First, the meaning and value of craft in modern times and digital media and hybrid creation environments are theoretically investigated based on previous studies and literature. Second, design cases produced by combining digital technology as a tool and craft elements are classified for substantial understanding of the design. Thirdly, identify the design characteristics presented through case studies and suggest the new possibility of creation. The results of the study are as follows. Reject typical types highlight the functional role and try free express conversion, e.g. form, material, texture, making process etc. Extracts the various elements that can be applied and search combining ways, because the convergence of digital technology and the craft is sufficient to activate the human emotion. Interaction between the craft and the digital medium is made actively. Craft accepts digital form, the craft appeared again as the contents of the digital. the traditional and digital method appropriately fused and utilized depending on the situation in process.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.