• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.2
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• pp.1-16
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• 1995

This study was carried out to suggest method which can be used to improve competitive power of theme parks. The characteristics of Hybrid Conjoint Analysis were described and its usefulness for identification of specific types of service theme parks have to provide was tested "Lotte World, " "Seoul land," and "farmland" were selected as study areas, and .7 attributes with 3 levels were utilized for analyses. Master design with 81 profiles was constructed to meet the requirement of ′Compromise Plan 1,′and data was collected by in-personal interviews on the study areas. Respondents were grouped by cluster analysis, and their characteristics were analyzed by discriminant analysis. Then, part-worth of each attribute . was estimated by stagewise estimation model Calibrated model of each group did not show part-worths of attributes clearly because both main effects and 2-way interaction effects were included in the models. Therefore, calibrated models′ coefficients were used to calculate utilities of all possible combinations of attributes levels. The results showed that managers of theme parks have several options for providing a new service: the combination of attribute levels with the highest utility is they however, they can choose the other combinations with next highest utlities is they can not afford it. Several suggestions were described to cope with the problems when Hybrid Conjoint Analysis is applied to landscape architectural study.

• Journal of Plant Biotechnology
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• v.44 no.3
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• pp.208-219
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• 2017

Heterosis or hybrid vigor describes a phenomenon that superior phenotypes compared to the two parents are observed in the heterozygous $F_1$-hybrid plants. Identification and characterization of heterosis-related genes (HRGs) will facilitate hybrid breeding in crops. To identify HRGs in Brassica rapa, we analyzed transcriptome profiling using a Br300K microarray in non-heading Chinese cabbage at three developmental stages. A large number of genes were differentially expressed in $F_1$ hybrids and non-additive expression was prominent. Genes that are expressed specifically for $F_1$ hybrid at all three stages were Brassica-specific uncharacterized genes and several defense-related genes. Expression of several photosynthesis- and stress-related genes were also $F_1$ hybrid-specific. Thirteen NBS-LRR class genes showed high and specific expression in $F_1$ hybrid Shulu: some of them were characterized as defense genes in Arabidopsis, but most have not been. Further characterization of these defense-related genes in Brassica species and its application will be helpful for understanding the role of defense responses in heterosis. In addition, results obtained in this study will be valuable to develop molecular markers for heterosis and disease resistance in B. rapa.

• Journal of Life Science
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• v.23 no.11
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• pp.1311-1316
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• 2013

Heterogeneous nuclear ribonucleoprotein L (hnRNP L) is a major pre-mRNA binding protein and it is an abundant nuclear protein that shuttles between the nucleus and the cytoplasm. hnRNP L is known to be related to many cellular processes, including chromatin modification, pre-mRNA splicing, mRNA export of intronless genes, internal ribosomal entry site (IRES)-mediated translation, mRNA stability, and spermatogenesis. In order to identify the cellular proteins interacting with hnRNP L, this study performed a yeast two-hybrid screening, using a human liver cDNA library. The study identified insulin-like growth factor binding protein-4 (IGFBP-4) as a novel interaction partner of hnRNP L in the human liver. It then discovered, for the first time, that hnRNP L interacts specifically with IGFBP-4 in a yeast two-hybrid system. The authenticity of this two-hybrid interaction of hnRNP L and IGFBP-4 was confirmed by an in vitro pull-down assay.

• Proceedings of the Ginseng society Conference
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• 2002.10a
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• pp.467-476
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• 2002

A large number of individual ginseng plants have been selected in the farmer's fields to develop new ginseng varieties with desirable traits since 1970s. Among them, Hwangsukjong with green stem and yellow berry was selected as a ginseng germplasm. The phenotype of Hwangsukjong is quite different from Jakyungjong that has violet stem and red berry and has been cultivated in most of ginseng fields. Therefore, Hwangsukjong was crossed with Jakyungjong to clarify the inheritance of stem color and then the characteristics of $F_1\;and\;F_2$ hybrids were investigated. $F_1$ hybrid plants were similar to Jakyungjong in most of aerial part characters and showed hybrid vigor in fresh weight of root and weight of 100 seeds. In $F_2$ generation, the stem color was segregated in a ratio of 3 violet to 1 green. From this result, it was elucidated that violet color was controlled by single dominant gene. In another experiment, DNA was extracted from parents (Jakyungjong and Hwangsukjong) and $F_1$ hybrid. For each primer evaluated, multiple band profile was produced comprising from one to five major bands plus a varying number of minor bands and amplified bands were detected among most primers. In case of UBC primer number 13, 17, 30, 31, and 43, band patterns of parents and $F_1$ hybrid were very similar, but the others were not. Especially, in {\sharp}1$, {\sharp}4$, and {\sharp}33$, specific band was produced in Hwangsukjong and $F_1$ hybrid while in {\sharp}6$, another specific band was produced in Jakyungjong and $F_1$ hybrid. Therefore, $F_1$ hybrid had all specific bands at these primers. So, these selective markers could be used for identification of characteristics of $F_2$ hybrids

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.178-185
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• 2005

This paper presents a new music identification method using probabilistic and dynamic characteristics of melody. The propo3ed method uses pitch and MFCC parameters as feature vectors for the characteristics of music notes and represents melody pattern by pitch histogram and temporal sequence of codeword indices. We also propose a new pattern matching method for the hybrid method. We have tested the proposed algorithm in small (drama OST) and broad (1.005 popular songs) search spaces. The experimental results on search areas of OST and 1,005 popular songs showed better performance of the proposed method over conventional methods. We achieved the performance improvement of average $9.9\%$ and $10.2\%$ in error reduction rate on each search area.

• Smart Structures and Systems
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• v.25 no.5
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.91-97
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• 2011

In this paper we present an approach to the structure identification based on genetic algorithm and to the parameter identification by hybrid learning method in neuro-fuzzy-genetic hybrid system in order to predicate the Mackey-Glass Chaotic time series. In this scheme the basic idea consists of two steps. One is the construction of a fuzzy rule base for the partitioned input space via genetic algorithm, the other is the corresponding parameters of the fuzzy control rules adapted by the backpropagation algorithm. In an attempt to test the performance the proposed system, three patterns, x(t-3), x(t-6) and x(t-9), was prepared according to time interval. It was through lots of simulation proved that the initial small error of learning owed to the good structural identification via genetic algorithm. The performance was showed in Table 2.

• The Korea Journal of Herbology
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• v.34 no.5
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• pp.1-12
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• 2019

Objectives : The consumption of licorice is large in Korea, but domestic production is insufficient due to the lack of adaptability. This study aimed to provide a morphological basis for adding interspecific hybrid licorice with improved adaptability to pharmacopoeia. Methods : This study was to establish identification criteria for the original plants, external and internal morphology of the authentic herbal medicines (Glycyrrhiza uralensis, G. glabra and G. inflata), market products and artificially interspecific hybrid forms of licorice. For this purpose, previous studies were investigated and visual and histological observations were carried out. We focused on the internal morphology by microscopic observation for securing objectivity. Finally, we proposed the identification keys for precise classification of each part. Results : 1) Original plant : Licorice species in the compendium were distinguished by the number of leaflets, presence of hair on the fruit, curvature and swelling of the fruit. 2) External morphology : Licorice species were distinguished by degree of powderiness, tearing gap, radial structure in the cross section and existence of protrusion of outer epidermis. 3) Internal morphology : Licorice species were distinguished by the degree of development of phloem fiber bundle, development of obliterated sieve, whether the secondary medullary ray are branched. In the case of interspecific hybrids, the characteristics of both species used for hybridization were mixed in all observation methods. Conclusions : These results suggest that the interspecific crossbred licorice is suitable for the pharmacopoeial standard. Therefore, it can be applied as a herbal medicine through additional supplementary study.

• ETRI Journal
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• v.30 no.5
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.