• Structural Engineering and Mechanics
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• v.89 no.3
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• pp.225-238
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• 2024

In this paper, a quasi-3D hyperbolic shear deformation theory for the bending responses of a functionally graded (FG) porous micro-beam is based on a modified couple stress theory requiring only one material length scale parameter that can capture the size influence. The model proposed accounts for both shear and normal deformation effects through an illustrative variation of all displacements across the thickness and satisfies the zero traction boundary conditions on the top and bottom surfaces of the micro-beam. The effective material properties of the functionally graded micro-beam are assumed to vary in the thickness direction and are estimated using the homogenization method of power law distribution, which is modified to approximate the porous material properties with even and uneven distributions of porosity phases. The equilibrium equations are obtained using the virtual work principle and solved using Navier's technique. The validity of the derived formulation is established by comparing it with the ones available in the literature. Numerical examples are presented to investigate the influences of the power law index, material length scale parameter, beam thickness, and shear and normal deformation effects on the mechanical characteristics of the FG micro-beam. The results demonstrate that the inclusion of the size effects increases the microbeams stiffness, which consequently leads to a reduction in deflections. In contrast, the shear and normal deformation effects are just the opposite.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.77-82
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• 2024

The test set of machine learning consists of the remaining data that did not participate as training data. It is quantitative division and it is setting aside a certain amount of data which has the same effect as random selection. However from a software testing perspective, test cases sufficient to catch errors are selected as a test set rather than a random selection. This is called the adequacy of the test case, and the higher the adequacy, the better the test case is selected. We want to examine whether the test cases used in machine learning are sufficient from this perspective by comparing them with the equivalence split method of software testing. If higher sufficiency is guaranteed when applying a software test design technique, that is, equivalence splitting, high effectiveness can be achieved with a small number of test sets. This reduces the size of the test set, thereby increasing the size of the training data set and ultimately securing more data to learn. It can be expected that more sophisticated models can be built with larger training data sets.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.2
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• pp.175-184
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• 2012

In the present study, the effects of feeding different forage sources on the growth performance, meat production and meat quality of Hanwoo steers were evaluated using meta-analysis. In total 5 studies that were performed and published in the domestic journals in Korea were employed for the analysis. The results from nutritionally better quality roughage-based steers and rice straw-based steers in each study were assigned as a treatment and a control, respectively, and the mean difference between the treatment and the control was used for the evaluation of effect size. The summary effect was calculated using random effect model. As results, in growth performance, positive effects were found in feed intake, daily weight gain, final body weight and feed efficiency. The significant effect was found only in daily weight gain (p<0.05). In meat production, carcass weight, Longissimus dorsi area, yield index showed positive effect and negative effect was detected in back fat thickness. The significant effect in meat production was found in carcass weight and Longissimus dorsi area (p<0.05). In meat quality, positive effects were represented in marbling score and fat color. Meat color showed little effect. The significance for effects was not observed in the analysis of meat quality. In conclusion, feeding good quality forages to ruminants plays an important role in Korean beef cattle industry and hence further researches are necessary to improve the efficiency of forage utilization in Hanwoo cattle.

• Journal of Korea Technology Innovation Society
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• v.10 no.3
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• pp.431-457
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• 2007

The main purpose of this study is to analyze the determinants of innovation in the medium core firms that belong to components and materials industry. For this purpose, we introduce the Schumpeterian hypothesis as a theoretical background at first. According to the Schumpeterian hypothesis, large firms in concentrated markets are likely to have more innovative activities. That means, firm site and market structure are the main determinant of innovation. Then, we propose other economic factors that have been considered to have effects on firms' innovative activities in previous studies. Those factors are export, profit, growth rate, R&D expenditure and capital intensity. In order to analyze the determinants of innovation, we estimate whether firm size, market structure, export, profit, growth rate, R&D expenditure and capital intensity affect to the possibility of creating innovation in medium core firms. In order to do this, our study uses survey data from 'Korean Innovation Survey(2005)' conducted by STEPI as well as utilizes the probit model as an analytical method. According to the empirical results, firm size has a positive relationship with innovative activities of medium core firms but market concentration does not. We find the negative correlation between market concentration and innovative activities in this study. Thus, was have to say that we do not fully support the Schumpeterian hypothesis in this case. Among other variables, profit and R&D expenditure are estimated to have positive relationship with innovative activities, while export and capital intensity are estimated to have negative relationship with innovative activities. In case of growth rate, we do not find any significant relationship with innovative activities. In conclusion, larger firm size, higher market competition, more access to the financial market and additional R&D investment would facilitate innovative activities of medium core firms. However, we have to review the relationship between export and innovative activities that has been estimated in this study. While the estimated effect of export on innovative activities can be explained by the own characteristics of medium core firms that produce and supply capital goods to final manufacturer, we have address this issue in the future.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.853-862
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• 2017

In this study, we analyse the determinants of the youth employment rate of public agencies and local public enterprises. On the other hand the youth employment rate contains information of the youth employment rate and the size of the youth employment. We use pooled tobit model and panel tobit model since dependent variable is a censored form observed only in a certain area. The results of the analysis are summarized as follows. First, the panel tobit model is more statistically significant as compared to the combined tobit model. Second, the youth employment rate is more statistically significantly higher in 2014 and 2015 than in 2011. Third, the youth employment rate in public enterprises is more statistically significantly higher than that in local public agencies. Finally, the higher the average wage is, the lower the youth employment ratio is.

• Composites Research
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• v.15 no.4
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• pp.23-31
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• 2002

The two dimensional size effect of specimen gauge section ($length{\;}{\times}{\;}width$) was investigated on the compressive behavior of a T300/924 $\textrm{[}45/-45/0/90\textrm{]}_{3s}$, carbon fiber-epoxy laminate. A modified ICSTM compression test fixture was used together with an anti-buckling device to test 3mm thick specimens with a $30mm{\;}{\times}{\;}30mm,{\;}50mm{\;}{\times}{\;}50mm,{\;}70mm{\;}{\times}{\;}70mm{\;}and{\;}90mm{\;}{\times}{\;}90mm$ gauge length by width section. In all cases failure was sudden and occurred mainly within the gauge length. Post failure examination suggests that $0^{\circ}$ fiber microbuckling is the critical damage mechanism that causes final failure. This is the matrix dominated failure mode and its triggering depends very much on initial fiber waviness. It is suggested that manufacturing process and quality may play a significant role in determining the compressive strength. When the anti-buckling device was used on specimens, it was showed that the compressive strength with the device was slightly greater than that without the device due to surface friction between the specimen and the device by pretoque in bolts of the device. In the analysis result on influence of the anti-buckling device using the finite element method, it was found that the compressive strength with the anti-buckling device by loaded bolts was about 7% higher than actual compressive strength. Additionally, compressive tests on specimen with an open hole were performed. The local stress concentration arising from the hole dominates the strength of the laminate rather than the stresses in the bulk of the material. It is observed that the remote failure stress decreases with increasing hole size and specimen width but is generally well above the value one might predict from the elastic stress concentration factor. This suggests that the material is not ideally brittle and some stress relief occurs around the hole. X-ray radiography reveals that damage in the form of fiber microbuckling and delamination initiates at the edge of the hole at approximately 80% of the failure load and extends stably under increasing load before becoming unstable at a critical length of 2-3mm (depends on specimen geometry). This damage growth and failure are analysed by a linear cohesive zone model. Using the independently measured laminate parameters of unnotched compressive strength and in-plane fracture toughness the model predicts successfully the notched strength as a function of hole size and width.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.32-49
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• 1998

For estimation of regional myocardial blood flow with O-15 water PET, a few modifications considering partial volume effect based on single compartment model have been proposed. In this study, we attempted to quantify the degree of heterogeneity and to show the effect of tissue flow heterogeneity on partition coefficient(${\lambda}$) and to find the relation between perfusable tissue index(PTI) and ${\lambda}$ by computer simulation using two modified models. We simulated tissue curves for the regions with homogeneous and heterogeneous blood flow over a various flow range(0.2-4.0ml/g/min). Simulated heterogeneous tissue composed of 4 subregions of the same or different size of block which have different homogeneous flow and different degree of slope of distribution of blood flow. We measured the index representing heterogeneity of distribution of blood flow for each heterogeneous tissue by the constitution heterogeneity(CH). For model I, we assumed that tissue recovery coefficient ($F_{MME}$) was the product of partial volume effect($F_{MMF}$) and PTI. Using model I, PTI, flow, and $F_{MM}$ were estimated. For model II, we assumed that partition coefficient was another variable which could represent tissue characteristics of heterogeneity of flow distribution. Using model II, PTI, flow and ${\lambda}$ were estimated. For the simulated tissue with homogeneous flow, both models gave exactly the same estimates, of three parameters. For the simulated tissue with heterogeneous flow distribution, in model I, flow and $F_{MM}$ were correctly estimated as CH was increased moderately. In model II, flow and ${\lambda}$ were decreased curvi-linearly as CH was increased. The degree of underestimation of ${\lambda}$ obtained using model II, was correlated with CH. The degree of underestimation of flow was dependent on the degree of underestimation of ${\lambda}$. PTI was somewhat overestimated and did not change according to CH. We conclude that estimated ${\lambda}$ reflect the degree of tissue heterogeneity of flow distribution. We could use the degree of underestimation of ${\lambda}$ to find the characteristic heterogeneity of tissue flow and use ${\lambda}$ to recover the underestimated flow.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.297-303
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• 2014

The effect of solar irradiance has been used to estimate daily maximum temperature, which make it possible to reduce the error inherent to lapse-rate based elevation difference correction in mountainous terrain. Still, recent observations indicated that the effect of solar radiation would need correction for estimation of daily maximum temperature. It was attempted to examine what would cause the variability of solar irradiance effect in determination of daily maximum temperature under natural field conditions and to suggest improved methods for estimation of the temperature distribution over mountainous regions. Temperature at 1500 and the wind speed for 1100 to 1500 were obtained at 10 validation sites with various topographical features including slope and aspect within a mountainous $50km^2$ catchment for 2012-2013. Lapse-rate corrected temperature estimates on clear days were compared with these observations, which would represent the differential irradiance effect among sloped surfaces. Results indicated a negative correlation between the mean wind speed and the estimation error. A simple scheme was derived from relationship between wind speed and estimation error for daily temperature to correct the effect of solar radiation. This scheme was incorporated into an existing model to estimate daily maximum temperature based on the effect of solar radiation. At 10 validation sites on clear days, estimates of 1500 LST temperature with and without the correction scheme were compared. It was found that a substantial improvement was achieved when the correction scheme was applied in terms of bias correction as well as error size reduction at all sites.

• Structural Engineering and Mechanics
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• v.2 no.4
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• pp.359-367
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• 1994

The stability behaviour of symmetrically laminated rectangular composite plates with loaded ends clamped and unloaded edges simply-supported, and subjected to uniform in-plane compression is investigated. A numerical and experimental investigation is presented in this contribution. The stacking sequence of the laminated glass/epoxy composite plates is symmetric about the middle surface and consists of 8-ply [0, 90, +45, -45]s lamination. Numerical predictions were obtained through the use of the finite element method. The above plates were modelled with 8-noded isoparametric layered shell elements. The effect of the input parameters such as the degree and forms of prescribed initial imperfection and the incremental step size required for incremental loading, on the convergence of the solution is thoroughly examined. Experimental results are presented for 10 test panels. All test panels were made from glass/epoxy unidirectional prepregs and have aspect ratio of 5.088. The laminate thicknesses were found to vary from 1.054 mm to 1.066 mm. Comparison of experimental data with predicted results show good correlation and give confidence in the finite element model.