• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.7-17
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• 2007

An analysis and design theory of an aperture-coupled cavity-fed back-to-back microstrip directional coupler is presented for the efficient and optimized design. For this purpose, an equivalent network is developed, and simple but accurate calculations of circuit element values are described. Design equations of the coupler are derived based on the equivalent circuit. In order to determine various structural design parameters, the evolutionary hybrid optimization method based on the genetic algorithm and Nelder-Mead method is invoked. As a validation check of the proposed theory and optimized design method, a 10 dB directional coupler was designed and fabricated. The measured coupling was 10.3 dB at 3 GHz, and the return loss and isolation were 31.8 dB and 30.5 dB, respectively. The directional coupler also showed very good quadrature phase characteristics. Good agreements between the measured and the design specifications fully validate the proposed network analysis and design procedure.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.717-722
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• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.62-70
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• 2021

2020 was a year in which the world spent in disorder due to the pandemic of Coronavirus infection-19(COVID-19). The pandemic was at the beginning of a turning point in history. For examples, the Black Death(Pest) that destroyed the feudal system of medieval Europe in the 14th century, smallpox that led to the destruction of the Inca Empire by Spain in the 17th century, and the Spanish flu that ended World War I early. The great transformation that will come after COVID-19 is presented from various fields and perspectives, but the understanding and direction of the transformation is ambiguous. This study attempts to derive and to analyze core terms based on a network of the future of globalization after COVID-19. Four Networks related to globalization, anti-globalization, and globalization and digitalization after COVID-19 were established respectively. A network integrating four networks was also constructed. The core terms were extracted from the hub nodes, the stress centrality, and the simplified network to which the K-core algorithm was applied. After COVID-19, the changes in globalization were analyzed from the extracted core terms. This study is thought to be meaningful to propose a method of deriving and analyzing core terms based on a network in understanding social changes after COVID-19.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.43-56
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• 2005

In the existing broadcasting environment, it is not easy to serve the bi-directional service between a broadcasting server and a TV audience. In the uni-directional broadcasting environments, almost TV programs are scheduled depending on the viewers' popular watching time, and the advertisement contents in these TV programs are mainly arranged by the popularity and the ages of the audience. The audiences make an effort to sort and select their favorite programs. However, the advertisement programs which support the TV program the audience want are not served to the appropriate audiences efficiently. This randomly provided advertisement contents can occur to the audiences' indifference and avoidance. In this paper, we propose the target advertisement service for the appropriate distribution of the advertisement contents. The proposed target advertisement service estimates the audience's profile without any issuing the private information and provides the target-advertised contents by using his/her estimated profile. For the experimental results, we used the real audiences' TV usage history such as the ages, fonder and time of the programs from AC Neilson Korea. And we show the accuracy of the proposed target advertisement service algorithm. NDS (Normalized Distance Sum) and the Vector correlation method, and implementation of our target advertisement service system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.3 s.106
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• pp.249-258
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• 2006

In this letter, we propose a novel printed helix antenna for RFID reader in UHF band. The printed strip line of the antenna is first wound up outside a polygonal shaped layer and then the winding continues on an inner layer to control the overall gain and the radiation pattern. In addition, the winding pitch angles on each layer have either negative or positive values resulting in the broad CP bandwidth. The detail structure of the antenna was optimized using Pareto genetic algorithm(GA), so as to obtain excellent performances for RFID reader antennas. The optimized two-layered polygonal helix was fabricated on the cardboard of a flexible substrate and the performances were measured and compared with the simulations. The fabricated antenna was made up of copper tape which can adhere to a flexible cardboard and had 21.4 % matching bandwidth, 31.9 % CP bandwidth, readable range of $5.5m^2$ with kr=3.2. Also based on the current distribution of the strip line of the antenna and sensitivity of the antenna bents points, we confirmed that the antenna has the quarter-wave transformer near the feed for the broad matching bandwidth and radiates the traveling wave for the broad CP bandwidth using the bent strip line.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.157-165
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• 2006

The change of external/internal factors of the cell rquires specific biological functions to maintain life. Such functions encourage particular genes to jnteract/regulate each other in multiple ways. Accordingly, we applied a linear decomposition model IFSA, which derives hidden variables, called the 'expression mode' that corresponds to the functions. To interpret gene interaction/regulation, we used a cross-correlation method given an expression mode. Linear decomposition models such as principal component analysis (PCA) and independent component analysis (ICA) were shown to be useful in analyzing high dimensional DNA microarray data, compared to clustering methods. These methods assume that gene expression is controlled by a linear combination of uncorrelated/indepdendent latent variables. However these methods have some difficulty in grouping similar patterns which are slightly time-delayed or asymmetric since only exactly matched Patterns are considered. In order to overcome this, we employ the (IFSA) method of [1] to locate phase- and shut-invariant features. Membership scoring functions play an important role to classify genes since linear decomposition models basically aim at data reduction not but at grouping data. We address a new function essential to the IFSA method. In this paper we stress that IFSA is useful in grouping functionally-related genes in the presence of time-shift and expression phase variance. Ultimately, we propose a new approach to investigate the multiple interaction information of genes.