• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.35-48
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• 2015

It is frequently found in daily life that people who experience good luck as lottery winners try to improve their background (e.g., home, car) but it has not been empirically validated why they do that. Present research attempts to explore the prediction that people who experience good luck expand the scope of attention to background and those who undergo bad luck shrink the scope of attention to adjacent objects. Findings from Experiment 1a indicate that participants who experienced good luck (won the rock-paper-scissors game) paid more attention to background and performed worse in the "find the hidden picture" (below FHP) task while those who underwent bad luck (lost the rock-paper-scissors game) paid more attention to objects, leading to better performance in the FHP task. It is also found in Experiment 1a that, if people washed their hands after experiencing good or bad luck, the opposite result occurred. Experiment 1b confirmed that the rock-paper-scissor game manipulated good and bad luck successfully and did not influence self-control. Experiment 2 shows that people who strongly believe in good luck performed poorly in FHP task while those who do not believe in good luck performed well in FHP task. Overall, three experiments support the proposed research hypotheses. Implications of the study findings for cognitive psychology and related fields including consumer and sports psychology are discussed.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.693-702
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• 2019

Deep learning has gained popularity for the classification and prediction task. Neural network layers become deeper as more data becomes available. Saturation is the phenomenon that the gradient of an activation function gets closer to 0 and can happen when the value of weight is too big. Increased importance has been placed on the issue of saturation which limits the ability of weight to learn. To resolve this problem, Glorot and Bengio (Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 249-256, 2010) claimed that efficient neural network training is possible when data flows variously between layers. They argued that variance over the output of each layer and variance over input of each layer are equal. They proposed a method of initialization that the variance of the output of each layer and the variance of the input should be the same. In this paper, we propose a new method of establishing initialization by adopting truncated normal distribution and truncated cauchy distribution. We decide where to truncate the distribution while adapting the initialization method by Glorot and Bengio (2010). Variances are made over output and input equal that are then accomplished by setting variances equal to the variance of truncated distribution. It manipulates the distribution so that the initial values of weights would not grow so large and with values that simultaneously get close to zero. To compare the performance of our proposed method with existing methods, we conducted experiments on MNIST and CIFAR-10 data using DNN and CNN. Our proposed method outperformed existing methods in terms of accuracy.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Journal of the Korean Wood Science and Technology
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• v.38 no.3
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• pp.170-177
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• 2010

Finite element numerical analysis was conducted with using the knot data which has a strong influence on the prediction of capacity for the structural wood member. Wood is a orthotropic property unlike other structural materials, so orthotropic property was applied. Knot was modelled as a cylinder shape, cone shape, and cubic shape. Compressive test was carried out to investigate the failure types and to calculate ultimate strengths for the wood members. Numerical model which can reflect the member size, number of knot, location of knot, size of knot was created and analyzed. By the numerical analysis using the ultimate compressive strength, numerical stress distribution types of each specimen was compared to real failure types for the test specimen. Cylinder shape modelling might be most reasonable, according to the necessary time for the analysis, the difficulty of element meshing, and the similarity of stress transfer around knot. Moreover, according to the stress and deformation distribution for the numerical analysis, failures or cracks of real specimen were developed in the vicinity of stress concentrated section and most transformed section. Based on the those results, numerical analysis could be utilized as a useful method to analyze the performance of bending member and tensile member, if only orthotropic property and knot modelling were properly applied.

• Journal of the Korea Concrete Institute
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• v.15 no.2
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• pp.280-287
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• 2003

To evaluate the practical application of oyster shells(OS) as construction materials, an experimental study was performed. More specifically, the long-term mechanical properties and durability of concrete blended with oyster shells were investigated. Test results indicate that long-term strength of concrete blended with 10% oyster shells is almost identical to that of normal concrete. However, the long-term strength of concrete blended with 20% oyster shells is appreciably lower than that of normal concrete. Thereby, concrete with higher oyster shell blend has the possibility of negatively influencing the concrete long-term strength. Elastic modulus of concrete blended with crushed oyster shells decreases as the blending mixture rate increases. Namely, the modulus is reduced to approximately 10∼15% when oyster shells are blended up to 20% as the fine aggregate. The drying shrinkage strain increases with an increasing crushed oyster shells substitution rate. In addition, the existing model code of drying shrinkage and creep do not coincide with the test results of this study. An adequate prediction equation needs to be developed. The utilization of oyster shells as the fine aggregate in concrete has an insignificant effect on fleering and thawing resistance, carbonation and chemical attack of concrete. However, water permeability is considerably improved.

• Journal of the Korea Concrete Institute
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• v.25 no.6
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• pp.631-639
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• 2013

Non-linear finite element analysis for newly developed precast concrete details for beam-to-column connection which can be used in moderate seismic region was carried out in this study. Developed precast system is based on composite structure and which have steel tube in column and steel plate in beam. Improving cracking strength of joint under reversed cyclic loading, joint area was casted with ECC (Engineering Cementitious Composites). Since this newly developed precast system have complex sectional properties and newly developed material, new analysis method should be developed. Using embedded elements and models of non-linear finite element analysis program ABAQUS previously tested specimens were successfully analyzed. Analysis results show comparatively accurate and conservative prediction. Using finite element model, effect of axial load magnitude and flexural strength ratio were investigated. Developed connection have optimized performance under axial load of 10~20% of compressive strength of column. Plastic hinge was successfully developed with flexural strength ratio greater than 1.2.

• 전자공학회논문지 IE
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• v.43 no.3
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• pp.41-48
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• 2006

In this paper, we propose a new active queue management (AQM) scheme by utilizing the predictability of the Internet traffic. The proposed scheme predicts future traffic input rate by using the auto-regressive (AR) time series model and determines the future congestion level by comparing the predicted input rate with the service rate. If the congestion is expected, the packet drop probability is dynamically adjusted to avoid the anticipated congestion level. Unlike the previous AQM schemes which use the queue length variation as the congestion measure, the proposed scheme uses the variation of the traffic input rate as the congestion measure. By predicting the network congestion level, the proposed scheme can adapt more rapidly to the changing network condition and stabilize the average queue length and its variation even if the traffic input level varies widely. Through ns-2 simulation study in varying network environments, we compare the performance among RED, Adaptive RED (ARED), REM, Predicted AQM (PAQM) and the proposed scheme in terms of average queue length and packet drop rate, and show that the proposed scheme is more adaptive to the varying network conditions and has shorter response time.

• Journal of IKEEE
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• v.22 no.3
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• pp.829-835
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• 2018

Recently, studies have been actively conducted to reduce spare power that is unnecessarily generated or wasted in existing power systems and to improve energy use efficiency. In this study, smart meter, which is one of the element technologies of smart grid, is implemented to improve the efficiency of energy use by controlling power of electric devices, and predicting trends of energy usage based on deep learning. We propose and develop an algorithm that controls the power of the electric devices by comparing the predicted power consumption with the real-time power consumption. To verify the performance of the proposed smart meter based on the deep running, we constructed the actual power consumption environment and obtained the power usage data in real time, and predicted the power consumption based on the deep learning model. We confirmed that the unnecessary power consumption can be reduced and the energy use efficiency increases through the proposed deep learning-based smart meter.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.15
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• pp.6449-6453
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• 2014

Background: Prior studies showed a relationship between serum albumin and the albumin to globulin ratio with different types of cancer. We aimed to evaluate the predictive value of the albumin-globulin ratio (AGR) for survival of patients with lung adenocarcinoma. Materials and Methods: This retrospective study included 240 lung adenocarcinoma patients. Biochemical parameters before chemotherapy were collected and survival status was obtained from the hospital registry. The AGR was calculated using the equation AGR=albumin/(total protein-albumin) and ranked from lowest to highest, the total number of patients being divided into three equal tertiles according to the AGR values. Furthermore, AGR was divided into two groups (low and high tertiles) for ROC curve analysis. Cox model analysis was used to evaluate the prognostic value of AGR and AGR tertiles. Results: The mean survival time for each tertile was: for the $1^{st}$ 9.8 months (95%CI:7.765-11.848), $2^{nd}$ 15.4 months (95%CI:12.685-18.186), and $3^{rd}$ 19.9 months (95%CI:16.495-23.455) (p<0.001). Kaplan-Meier curves showed significantly higher survival rates with the third and high tertiles of AGR in comparison with the first and low tertiles, respectively. At multivariate analysis low levels of albumin and AGR, low tertile of AGR and high performance status remained an independent predictors of mortality. Conclusions: Low AGR was a significant predictor of long-term mortality in patients with lung adenocarcinoma. Serum albumin measurement and calculation of AGR are easily accessible and cheap to use for predicting mortality in patients with lung adenocarcinoma.

• Composites Research
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• v.23 no.4
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• pp.44-51
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• 2010

Recently, to solve the problems associated with the neutralization and corrosion of reinforced concrete compression members, the structural configurations such as CFFT (Concrete Filled GFRP Tube) and RCFFT (Reinforced Concrete Filled GFRR Tube) have been developed and applied to main members of civil engineering structure. These members can increase structural performance in terms of structural stability, ductility as well as chemical resistance compared with conventional concrete structural members. Many researches in numerous institutions to predict the load carrying capacity of the concrete compression member strengthened with FRP materials have been conducted and they have been suggested an equation for the prediction of the load carrying capacity of the members. Through the review of the research results, it was found that their results are similar each other. Moreover, it was also found that the results are not directly applicable to our specimens since the results are largely depended upon the member configurations. Also, since the accurate design criteria for the RC members strengthened with FRP such as RCFFT have not been established properly, relevant theoretical and experimental investigations must be conducted for the application to the practical structures. In this study, structural behavior of RCFFT was evaluated through compressive and quasi-static flexural tests in order to formulate design criteria for the structural design. In addition, the RCFFT members were also investigated to examine their confinement effect and the equations capable of estimating the compressive ultimate strength and flexural stiffness of the RCFFT members were proposed.