• Journal of Forest and Environmental Science
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• v.36 no.4
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• pp.259-266
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• 2020

Poplar trees from the Salicaceae family over the years have been utilized for various reasons which include prevention of deforestation as well as phytoremediation. This study aims to determine the optimal pre-treatment and soil conditions required for propagation of poplar cuttings for increased initial adaptability and survival rate. Five poplar clones (Hanan, 110, 107, DN-34, 52-225) were selected for IBA, soil composition treatments on propagation. IBA pre-treatment of cuttings were utilized 0, 10, and 100 mg l-1 concentrations. Soil compositions were amended with TKS-2+perlite 2:1 (v:v) and sandy clay loam mixed with artificial soil. According to the greenhouse results 10 mg l-1 of IBA showed a significant increase in plant height whereas 100 mg l-1 inhibited plant growth except in clone 110. Soil composition severely affected root growth and hence overall growth of the clones. Sandy clay loam soil had poor to stunted growth compared to TKS-2+perlite.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.354-366
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• 2020

This work mainly focuses on determination of the fully plastic J-integral solutions for welded center cracked plates subjected to remote tension loading. Detailed three-dimensional elasticeplastic Finite Element Analyses (FEA) were implemented to compute the fully plastic J-integral along the crack front for a wide range of crack geometries, material properties and weld strength mismatch ratios for 900 cases. According to the database generated from FEA, Back-propagation Neural Network (BPNN) model was proposed to predict the values and distributions of fully plastic J-integral along crack front based on the variables used in FEA. The determination coefficient R2 is greater than 0.99, indicating the robustness and goodness of fit of the developed BPNN model. The network model can accurately and efficiently predict the elastic-plastic J-integral for weld centerline crack, which can be used to perform fracture analyses and safety assessment for welded center cracked plates with varying strength mismatch conditions under uniaxial loading.

• Current Optics and Photonics
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• v.6 no.5
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• pp.479-488
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• 2022

To account for the internal thermal effects of solid-state lasers, a method using a back propagation (BP) neural network integrated with a particle swarm optimization (PSO) algorithm is developed, which is a new wavefront distortion correction technique. In particular, by using a slab laser model, a series of fiber pumped sources are employed to form a controlled array to pump the gain medium, allowing the internal temperature field of the gain medium to be designed by altering the power of each pump source. Furthermore, the BP artificial neural network is employed to construct a nonlinear mapping relationship between the power matrix of the pump array and the thermally induced wavefront aberration. Lastly, the suppression of thermally induced wavefront distortion can be achieved by changing the power matrix of the pump array and obtaining the optimal pump light intensity distribution combined using the PSO algorithm. The minimal beam quality β can be obtained by optimally distributing the pumping light. Compared with the method of designing uniform pumping light into the gain medium, the theoretically computed single pass beam quality β value is optimized from 5.34 to 1.28. In this numerical analysis, experiments are conducted to validate the relationship between the thermally generated wavefront and certain pumping light distributions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.389-398
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• 2006

The present study compositely applied the self-organizing map (SOM), which is a kind of artificial neural networks (ANNs), and the back propagation algorithm (BPA) for the rainfall-runoff prediction model taking account of the irregular variation of the spatiotemporal distribution of rainfall. To solve the problems from the previous studies on ANNs, such as the overestimation of low flow during the dry season, the underestimation of runoff during the flood season and the persistence phenomenon, in which the predicted values continuously represent the preceding runoffs, we introduced SOM theory for the preprocessing in the prediction model. The theory is known that it has the pattern classification ability. The method proposed in the present research initially includes the classification of the rainfall-runoff relationship using SOM and the construction of the respective models according to the classification by SOM. The individually constructed models used the data corresponding to the respectively classified patterns for the runoff prediction. Consequently, the method proposed in the present study resulted in the better prediction ability of runoff than that of the past research using the usual application of ANNs and, in addition, there were no such problems of the under/over-estimation of runoff and the persistence.

• Korean Journal of Plant Resources
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• v.6 no.2
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• pp.171-179
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• 1993

This study was conducted to investigate the effect of growth regulators and medium composition on the growth of each stage in apical meristem culture for mass propagation of Zanthoxylum piperitum var. inerme Makino. The source material, shoot tip segments were taken from three-years old graft trees. Apical meristems were cultured in vitro on basal MS, GD, WS, half strength MS(1/2MS) and half strength GD(1/2GD) media supplemented with various concentrations for growth regulators(BA, IBA) and inorganic nutrients. The results summarized are as follows: 1. In culture establishment stage, ratio of culture establishment was 96.7% and the best resuit was obtained using MS medium supplemented with 1.0mg/l BA and 0.2mg/l IBA. 2. In shoot multitication stage, both shoot multiplication and growth were achieved in average 5.6cm. These results were obtained on in MS medium supplemented with 1.0mg/l BA and 0.2mg/l IBA. 3. In roothing stage, phloroglucinol(PG) acted as IBA synergist in root initiation. The most faverable combinations for root development was half-strength MS medium supplemented with 162mg/l PG and 0.2mg/l IBA, and ratio of rooting was 58.0%. 4. In Vitro formed plantlets were transplanted to paper pots in greenhouse with 85% of relative humidity. 96% of survival rate was obtained from artificial soil mix having same volume of sand, vermiculite, peat, and soil.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.6
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• pp.953-962
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• 1987

Domestic dissimilar structural steels, SM 45 C and SUS304 were friction welded under optimal welding condition and the micro-artificial holes were drilled at SM 45 C base metal, SM 45 C HAZ, welded zone, SUS 304 HAZ, and SUS 304 base metal for fatigue behavior tests. In this study, the fatigue limit and the behavior of micro-crack propagation, crack propagation rate, and its dependency on stress intensity factor under the low stress level and high stress level of bending stress have been investigated. The results obtained are as follows. (1) The fatgiue strength of the portion of SM45C B.M., SM45C HAZ, welded zune, SUS304 HAZ and SUS304 B.M. on notched friction welded specimens are 20 kgf/mm$^{2}$, 32 kgf/mm$^{2}$, 27kgf/mm$^{2}$, 29kgf/mm$^{2}$, and 29kgf/mm$^{2}$, respectively. (2) The fatigue strength of welded zone of unnotched and notched specimens are 32.5kgf/mm$^{2}$, and 27kgf/mm$^{2}$, respectively. (3) Micro-crack initiation in the welded zone, HAZ, and each base metals occurrs simultaneously in front and rear of micro-hole tips in the view of the rotational directions. (4) Fatigue crack propagates more slowly in the welded zone than in another protions of specimen, regardless of the magnitude of the stress level. (5) Fatigue crack propagation rates were plotted as a function of stress intensity range. The value of m in the equation da/dN=C(.DELTA.K)$^{m}$ was found to range from 2.09-2.55 in this study.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.77-82
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• 2005

This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

• Journal of Forest and Environmental Science
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• v.37 no.4
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• pp.323-330
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• 2021

Zygotic embryo culture was performed to propagate evergreen oak, Quercus myrsinifolia, which has recalcitrant seeds and is difficult to propagate by cuttings. Zygotic embryos appeared in WPM medium after 14 days, and after 56 days, they developed into complete plants with cotyledons and roots. The medium suitable for zygotic embryo culture was 1/4 WPM medium, showing a shoot growth of 2.43 cm and root growth of 8.7 cm after 8 weeks of culture. As a result of investigating the effect of GA₃ on the growth of plants germinated from zygotic embryos through GA₃ treatment, the best growth was shown in 0.5 mg/l GA₃ treatment. The in vitro rooting and growth of IBA-treated zygotic embryo-derived plants were good in the 0.5 mg/l IBA treatment and rooting and shoot growth were not observed at higher concentrations. And the callus induction rate also increased as the concentration of IBA increased. Plants grown in vitro were transferred to a plastic pot containing artificial soil and acclimatized in a greenhouse for about 4 weeks, resulting in more than 90% survival. As a result of this study, the zygotic embryo culture method was confirmed to be effective for mass propagation of Q. myrsinifolia. The results of this study are expected to contribute significantly to the mass propagation of elite Q. myrsinifolia.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.639-645
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• 2006

FRP (Fiber Reinforced Polymer) is an excellent new constructional material in resistibility to corrosion, high intensity, resistibility to fatigue, and plasticity. FBG (Fiber Bragg Grating) sensor is widely used at present as a smart sensor due to lots of advantages such as electric resistance, small-sized material, and high durability. However, with insufficiency of measuring displacement, FBG sensor is used only as a sensor measuring physical properties like strain or temperature. In this study, FRP and FBG sensors are to be hybridized, which could lead to the development of a smart FRP rod. Moreover, developing the estimated model for deflection with neural network method, with the data measured through FBG sensor, could make conquest of a disadvantage of FBG sensor - uniquely used for sensing strain. Artificial neural network is MLP (Multi-layer perceptron), trained within error rate of 0.001. Nonlinear object function and back-propagation algorithm is applied to training and this model is verified with the measured axial displacement through UTM and the estimated numerical values.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.