• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.59-68
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• 2009

This paper addresses a hybrid multi-focus image fusion scheme using the recent curvelet transform constructions. Hybridization is obtained by combining the MS fusion rule with a novel "copy" method. The proposed scheme use MS rule to fuse the m most significant terms in spectrum of an image at each decomposition level. The scheme is dubbed in this work as m-term fusion in adherence to its use of the MSC (most significant coefficients) in the transform set at any given scale, orientation, and translation. We applied the edge-sensitive objective quality measure proposed by Xydeas and Petrovic to evaluate the method. Experimental results show that the proposed scheme is a potential alternative to the redundant, shift-invariant Dual-Tree Complex Wavelet transforms. In particular, it was confirmed that a 50% m-term fusion produces outputs with no visible quality degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1328-1336
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• 2012

Compared to terrestrial RF communications, underwater acoustic communications have several limitations such as limited bandwidth, high level of fading effects, and a large underwater propagation delay. In this paper, in order to tackle those limitations of underwater communications and to make it possible to form a large underwater monitoring systems, we propose a hierarchical underwater network architecture, which consists of underwater sensors, clusterheads, underwater/surface sink nodes, autonomous underwater vehicles (AUVs). In the proposed architecture, for the maximization of packet delivery ratio and the minimization of underwater sensor's energy consumption, a hybrid routing protocol is used. More specifically, cluster members use Tree based routing to transmit sensing data to clusterheads. AUVs on optimal trajectory movements collect the aggregated data from clusterhead and finally forward the data to the sink node. Also, in order to minimize the maximum travel distance of AUVs, an Integer Linear Programming based algorithm is employed. Performance analysis through simulations shows that the proposed architecture can achieve a higher data delivery ratio and lower energy consumption than existing routing schemes such as gradient based routing and geographical forwarding. Start after striking space key 2 times.

• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• Journal of Korean Society of Forest Science
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• v.87 no.1
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• pp.50-56
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• 1998

Thirty-six $F_3$ hybrid poplar (Populus trichocarpa${\times}$P. deltoides) clones were fumigated with ozone to select for ozone sensitive and resistant clones. Fumigation was applied for 6 to 8 hours each day for approximately 3 months at ozone concentrations of 90 to 115 ppb using by open-top chambers. Height, diameter, number of leaves, total biomass, biomass components, root/shoot ratios, leaf drop and stomatal response were investigated. In summary, ozone generally reduced height, diameter, number of leaves, total biomass, and root/shoot ratios. Ozone stress induced leaf drop and foliar senescence in trees. This study showed very low relationship between total biomass and stomatal conductance. Increased plant resistant to ozone is not always correlated with stomatal behaviour. Probably, characterization of biochemical and other physiological responses to ozone exposure can provide a better understanding of tree response to ozone environment.

• Macromolecular Research
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• v.15 no.2
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• pp.95-99
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• 2007

The most recent developments in two areas: (a) synthesis of inorganic particles with control over size and shape by polymer additives, and (b) synthesis of inorganic-polymer hybrid materials by bulk polymerization of blends of monomers with nanosized crystals are reviewed. The precipitations of inorganics, such as zinc oxide or calcium carbonate, in presence and under the control of bishydrophilic block or comb copolymers, are relevant to the field of Biomineralization. The application of surface modified latex particles, used as controlling agents, and the formation of hybrid crystals in which the latex is embedded in otherwise perfect crystals, are discussed. The formation of nano sized spheres of amorphous calcium carbonate, stabilized by surfactant-like polymers, is also discussed. Another method for the preparation of nanosized inorganic functional particles is the controlled pyrolysis of metal salt complexes of poly(acrylic acid), as demonstrated by the syntheses of lithium cobalt oxide and zinc/magnesium oxide. Bulk polymerization of methyl methacrylate blends, with for example, nanosized zinc oxide, revealed that the mechanisms of tree radical polymerization respond to the presence of these particles. The termination by radical-radical interaction and the gel effect are suppressed in favor of degenerative transfer, resulting in a polymer with enhanced thermal stability. The optical properties of the resulting polymer-particle blends are addressed based on the basic discussion of the miscibility of polymers and nanosized particles.

• Korean Journal of Breeding Science
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• v.40 no.3
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• pp.250-257
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• 2008

Knowledge of genetic diversity and of the genetic relationships among elite breeding materials has had a significant impact on the improvement of crops. In maize, this information is particularly useful in i) planning crosses for hybrid and line development, ii) in assigning lines to heterotic groups and iii) in plant variety protection. We have used the SSR technique to study the genetic diversity and genetic relationships among 76 Korean waxy corn accessions, representing a diverse collection from throughout Korea. Assessment of genetic diversity among members of this group was conducted using 30 microsatellite markers. Among these 30 microsatellite markers, we identified a total of 127 alleles (with an average of 4.2 and a range of between 2 and 9 alleles per locus). Gene diversity at these 30 microsatellite loci varied from 0.125 to 0.795 with an average of 0.507. The cluster tree generated with the described microsatellite markers recognized two major groups with 36.5% genetic similarity. Group I includes 63 inbred lines, with similarity coefficients of between 0.365 and 0.99. Group II includes 13 inbred lines, with similarity coefficients of between 0.45 and 0.85. The present study indicates that the 30 microsatellite loci chosen for this analysis are effective molecular markers for the assessment of genetic diversity and genetic relationships between Korean waxy corn accessions. Specifically, this study's assessment of genetic diversity and relationships between a set of 76 Korean waxy corn inbred lines will be helpful for such activities as planning crosses for hybrid and line development and association mapping analyses of maize breeding programs in Korea.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.99-109
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• 2019

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. For example DEA is good at estimating "relative" efficiency of a DMU(Decision Making Unit), it only tells us how well we are doing compared with our peers but not compared with a "theoretical maximum." Thus, in order to measure efficiency of a new DMU, we have to develop entirely new DEA with the data of previously used DMUs. Also we cannot predict the efficiency level of the new DMU without another DEA analysis. We aim to show that DEA can be used to evaluate the efficiency of ports and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with C5.0. We can generate classification rules C5.0 in order to classify any new Port without perturbing previously existing evaluation structures by proposed methodology.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.6
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• pp.258-263
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• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• Horticultural Science & Technology
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• v.28 no.4
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• pp.711-714
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• 2010

A new cultivar 'Daemang' ($Hibiscus$ hybrid 'Daemang') originated from the interspecific cross between $Hibiscus$ $sinosyriacus$ 'Seobong' and $Hibiscus$ $syriacus$ 'Namwon' to improve the flower quality in 2001. 'Daemang' was preliminarily selected as 'R-143' in 2003 for its stable flower quality with long red eye spot and named in 2006. The tree habit shows vigorous growth and is upright, so it can be used as a specimen tree or street tree. Characteristic tests such as leaf shape, leaf size, flower characteristics, flowering, and capsule size were conducted from 2004 to 2006. The characteristics succeed after grafting. 'Daemang' had pink color flower with red eye spot. The width of flower is 15.2 cm. Petal length and width are 8.0 cm and 6.4 cm, respectively. Leaves are 9.49 cm long and 8.72 cm wide. After the plant characteristics evaluation for 3 years (2004~2006), it was registered as a variety 'Daemang' in 2008.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.