• Nuclear Engineering and Technology
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• v.20 no.2
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• pp.88-104
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• 1988

The FUel Rod Analysis(FURA) code is developed using two-dimensional finite element methods for axisymmetric and plane stress analysis of fuel rod. It predicts the thermal and mechanical behavior of fuel rod during normal and load follow operations. To evaluate the exact temperature distribution and the inner gas pressure, the radial deformation of pellet and clad, the fission gas release are considered over the full-length of fuel rod. The thermal element equation is derived using Galerkin's techniques. The displacement element equation is derived using the principle of virtual works. The mechanical analysis can accommodate various components of strain: elastic, plastic, creep and thermal strain as well as strain due to swelling, relocation and densification. The 4-node quadratic isoparametric elements are adopted, and the geometric model is confined to a half-pellet-height region with the assumption that pellet-pellet interaction is symmetrical. The pellet cracking and crack healing, pellet-cladding interaction are modelled. The Newton-Raphson iteration with an implicit algorithm is applied to perform the analysis of non-linear material behavior accurately and stably. The pellet and cladding model has been compared with both analytical solutions and experimental results. The observed and predicted results are in good agreement. The general behavior of fuel rod is calculated by axisymmetric system and the cladding behavior against radial crack is used by plane stress system. The sensitivity of strain aging of PWR fuel cladding tube due to load following is evaluated in terms of linear power, load cycle frequency and amplitude.

• Radiation Oncology Journal
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• v.4 no.2
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• pp.89-97
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• 1986

Using as assay for jejunal crypt stem cell survival, dose-response curves for the reproductive capacity of crypt stem cells of mouse jejunum exposed to multifractionated gamma-ray irradiation (single, 2, 3, 4, 5, 8, 10, 12, and 16 fractions) were analyzed and single-dose survival curve of these cells was constructed. The following conclusion were drawn: 1) Survival curves for higher numbers of dose fractions were displaced to higher dose, and characterized by increasingly shallower slopes. 2) The single-dose survival curve had broad shoulder, Dq=460 cGy, remaining near-exponential over initial dose range 0 to 300 cGy, with initial slope 1Do=474 cGy. 3) At fractionated dose En the range of 180 to 450 cGy, the average recovered dose per fraction interval was approximately $50\%$ of the dose per fraction. 4) The value of $\alpha/\beta$ ratio by using of linear regression analysis for the reciprocal dose plots was 8.3 Gy which lied in the range of 6-14 Gy for early-reacting tissues. 5) The linear-quadratic model for dose-response formula offers valid approximations for at 1 doses to be used in radiotherapy, only two parameters to be determined, and considerable convenience in practical applications.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.25-58
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• 2017

This study aimed to identify self-worth and self-deprecation trajectories and their associated factors among Korean adolescents. For these purposes, we used latent growth curve modeling involving 2,350 students who participated in the Korea Children and Youth Panel Survey in 2010, 2012, 2014, and 2015. Major findings are as follows: 1) Adolescents' self-worth and self-deprecation increased with time, but the speed gradually changed to a quadratic function model; and 2) the types of predictors affecting self-worth and self-deprecation were different. Specifically, the factors that affected only self-worth were adolescents' relationship with teachers and household income, and the factors that affected only self-deprecation were presence of disease and parental over interference. Factors affecting both self-worth and self-deprecation were child's sex, parental affection, peer trust, and peer alienation. These results suggest that independent intervention is needed for self-worth and self-deprecation. Furthermore, the results can be an important basis for establishing a more focused intervention strategy when intervening in self-worth and self-deprecation in adolescents.

• Journal of Korea Trade
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• v.26 no.5
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• pp.23-38
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• 2022

Purpose - This research intends to find out whether R&D cost stickiness shows differentiated aspects depending on exports in Korea. A cost behavior that indicates a lower rate of costs decrease when sales decrease than the rate of costs increase when sales increase is called cost stickiness. This sticky cost behavior is caused by considering the adjusting costs. This study aims to empirically verify that R&D cost stickiness is greater in export firms than in non-export firms. We also investigate the effect of exports on R&D cost stickiness is nonlinear. Design/methodology - We obtain data for the analysis from Kis-Value and TS2000 from 2012 to 2020. This study tests for R&D cost stickiness of exports using the cost stickiness model developed by Anderson et al. (2003) that is used in a lot of prior literature. To explore the nonlinear behavior of R&D cost stickiness we include a quadratic term of exports in our model. Findings - The results of our analysis are as follows. First, we observed that R&D costs of export firms are more sticky than that of non-export firms. Our result indicated that export firms are less likely to reduce R&D costs in decreasing sales periods in preparation for future sales recovery. Second, our empirical evidence shows that export firms view R&D costs much favorably. However, we hypothesize that the effect of export intensity on R&D costs may not necessarily be linear. Our result shows the effect of exports intensity on R&D stickiness is thus nonlinear, forming a reverse U-shaped curve. When export intensity exceeds a certain threshold, the growth rate of R&D costs appears to be viewed negatively. Firms with relatively high export intensity do not support R&D costs, viewing them as taking away firms' resources from other more productive costs. On the contrary, those with export intensity under the threshold view R&D costs as beneficial and therefore promote further R&D costs when revenue decreases. Originality/value - The results of this research can contribute academically to the expansion of empirical research on R&D cost stickiness. R&D cost stickiness varies by industry. As a result of our research, the managers of export firms recognize the importance of R&D to lead innovation. We expected that this research contributes to further studies on R&D costs and cost stickiness. Second, this research has implications from a business perspectives. Our findings of export firms' R&D stickiness suggest that export firms' managers should consider keeping the stickiness of R&D when revenue decreases because it is essential for exporting firms to maintain their R&D stickiness to secure long-term competitiveness. R&D stickiness can be used on a practical basis to emphasize the need for continuous investment in exporting firms' R&D activities.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.366-376
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• 2023

This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.613-623
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• 2011

This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with $R^2$ 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with $R^2$ 0.66 and 0.73, respectively. Their performance showed the 'Approximate Prediction' with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.6
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• pp.642-652
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• 2008

The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.

• Korean Journal of Veterinary Research
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• v.41 no.2
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• pp.203-210
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• 2001

Here, we compared the effectiveness of 50 MeV($p{\to}RBe^+$) cyclotron fast neutrons versus $^{60}Co$ ${\gamma}$-rays by the apoptotic fragment frequency in both rat peripheral lymphocytes and crypt cells to check a radiobiological endpoint. The incidence of apoptotic cell death was increased in all irradiated groups, and radiation at all doses trigger rapid changes in both crypt cells and peripheral lymphocytes. These data suggest that apoptosis may play an important role in homeostasis of damaged radiosensitive target organ by removing damaged cells. The curve of dose-effect relationship for these data of apoptotic fragments frequencies was $y=0.3+(6.512{\pm}0.279)D(r^2=0.975)$ after neutrons, while $y=0.3+(4.435{\pm}0.473)D+(-1.300{\pm}0.551)D^2(r^2=0.988)$ after ${\gamma}$-rays. In addition, $y=3.5+(118.410{\pm}10.325)D+(-33.548{\pm}12.023)D^2(r^2=0.992)$ after ${\gamma}$-rays in rat lymphocytes. A significant dose-response relationship was found between the frequency of apoptotic cell and dose. These data show a trend towards increase of the numbers of apoptotic cells with increasing dose. Dose-response curves for high and low linear energy transfer (LET) radiation modalities in these studies were different. The relative biological effectiveness (RBE) value for crypt cells was 1.919. In addition, there were significant peaks on apoptosis induction at 4 and 6h after irradiation, and the morphological findings of the irradiated groups were typical apoptotic fragments in crypt cells that were hardly observed in the control group. Thus, apoptosis induction in both crypt cells and peripheral lymphocytes could be a useful endpoint of rat model for studying screening test and microdosimetic indicator to evaluate the biological effects of radiation-induced cell damage.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.7
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• pp.915-921
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• 2001

IGF-I is involved in the regulation of growth and differentiation in mammals, but its role as a modulator of growth and metabolism in poultry is poorly understood. And, no studies have so far been reported for the comparison between serum IGF-I concentration and body growth in the egg type or the dual purposes (meat and egg type) chicken including the Korean Native Ogol Chicken (KNOC). Therefore, in order to improve the body growth and meat production of the KNOC, this study was conducted for the identification of the polymorphism of IGF-I gene and for its possible association with both body weight and IGF-I concentration. The RFLP patterns for IGF-I gene were identified by the PstI restriction enzyme. The frequencies of +/+, +/-, and -/- genotype were 16.9%, 51.7%, and 31.4%, respectively. Any statistical significance was not observed in all variations except for sex variation (p<0.01) by covariate quadratic model. The significant effect of the IGF-I genotype on body weight by sex indicates that there are different physiological characteristics in gender. Although the body weights of male KNOCs in most ages were not significant, there was a tendency of KNOCs with +/+ IGF-I genotype to be heavier than those with any other genotypes. But all IGF-I genotypes in female did not influence on body weight. The ANOYA revealed no significant effects of IGF-I genotypes on serum IGF-I concentration but sex effect was highly significant on the IGF-I concentration at 20 and 40 weeks (p<0.01). Although the +/+ genotype, in gender, tended to express a higher IGF-I concentration than the other genotypes at all ages in males, a statistical difference among the genotypes was not found except for 60 weeks (p<0.05). Furthermore, since body weight and IGF-I genotypes are associated, it is possible to improve KNOC to a meat type breed if a continuous selection can be made for the body weight and/or IGF-I traits.