• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.251-258
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• 2023

It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.277-285
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• 2023

In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.77-85
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• 2009

This paper describes the findings obtained from a research project aimed at investigating, via 1 g laboratory model tests, the ground movements caused by multiple side-by-side (sbs) tunnel construction in clay. The ground movements above a second tunnel showed different trends from those observed above a first tunnel. These trends include an increase in the overall volume loss, and a widening of the settlement troughs on the near limb of the trough accompanied by a shift of the maximum settlement towards existing tunnel. This would suggest that the use of simple predictive methods of adopting a Gaussian curve for analysing the ground settlements associated with twin (sbs) tunnel construction is not appropriate. Therefore the current paper adopts a method that modifies the Gaussian curve approach in order to improve the predictions. This paper comments on the parameter selection involved with adopting this new method to apply it to full-scale field situations, and also discusses its limitations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.149-154
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• 2022

Due to high power capabilities and high linearity of GaN devices, GaN Low-Noise Amplifiers (LNAs) without a limiter can be implemented in order to improve noise figure and reduce chip area in radar receivers. In this paper, a GaN LNA is presented for Ka-band radar receivers. The designed LNA was realized in a 150-nm GaN HEMT process and measurement results show that the voltage gain of >23 dB and the noise figure of <6.5 dB including packaging loss in the target frequency range. Under the high-power stress test, measured gain and noise figure of the GaN LNA is degraded after the first stress test, but no more degradation is observed under multiple stress tests. Through post-stress noise and s-parameter measurements, we verified that the GaN LNA is resilient to pulsed input power of ~40 dBm.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.357-363
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• 2023

In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.

• Steel and Composite Structures
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• v.48 no.1
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• pp.27-41
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• 2023

Under the long-term effect of corrosive environment, many cold-formed steel (CFS) structures have serious corrosion problems. Corrosion leads to the change of surface morphology and the loss of section thickness, which results in the change of instability mode and failure mechanism of CFS structure. This paper mainly investigates the elastic local buckling behavior of corroded CFS columns. The surface morphology scanning test was carried out for eight CFS columns accelerated corrosion by the outdoor periodic spray test. The thin shell finite element (FE) eigen-buckling analysis was also carried out to reveal the influence of corrosion surface characteristics, corrosion depth, corrosion location and corrosion area on the elastic local buckling behaviour of the plates with four simply supported edges. The accuracy of the proposed formulas for calculating the elastic local buckling stress of the corroded plates and columns was assessed through extensive parameter studies. The results indicated that for the plates considering corrosion surface characteristics, the maximum deformation area of local buckling was located at the plates with the minimum average section area. For the plates with localized corrosion, the main buckling shape of the plates changed from one half-wave to two half-wave with the increase in corrosion area length. The elastic local buckling stress decreased gradually with the increase in corrosion area width and length. In addition, the elastic local buckling stress decreased slowly when corrosion area thickness was relatively large, and then tends to accelerate with the reduction in corrosion area thickness. The distance from the corrosion area to the transverse and longitudinal centerline of the plate had little effect on the elastic local buckling stress. Finally, the calculation formula of the elastic local buckling stress of the corroded plates and CFS columns was proposed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.369-377
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• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Clinical Endoscopy
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• v.57 no.4
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• pp.446-453
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• 2024

With increasing global life expectancy, the significance of geriatric assessment parameters has increased. Sarcopenia is a crucial assessment parameter and is defined as the age-related loss of muscle mass and strength. Sarcopenia is widely acknowledged as a risk factor for postoperative complications in diverse advanced malignancies and has a detrimental effect on the long-term prognosis. While most studies have primarily concentrated on the correlation between sarcopenia and advanced cancer, more recent investigations have focused on the relationship between sarcopenia and early-stage cancer. Endoscopic submucosal dissection (ESD), which is less invasive than surgical intervention, is extensively employed in the management of early-stage cancer, although it is associated with complications such as bleeding and perforation. In recent years, several reports have revealed the adverse consequences of sarcopenia in patients with early-stage cancer undergoing ESD. This literature review briefly summarizes the recent studies on the association between sarcopenia and ESD.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• Korean Journal of Environmental Agriculture
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• v.25 no.4
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• pp.306-315
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• 2006

Two different experiments, adsorption/desorption and runoff by rainfall simulation of four pesticides, such as alachlor, ethalfluralin, ethoprophos and pendimethalin were undertaken their runoff and erosion losses from sloped land and to assess the influence of their properties and environmental factors on them. The mobility of four pesticides and which phase they were transported by were examined in adsorption study, and the influence of rainfall pattern and sloping degree on the pesticide losses were evaluated in simulated rainfall study. Freundlich adsorption parameters (K) by the adsorption and desorption methods were 1.2 and 2.2 for ethoprophos, 1.5 and 2.6 for alachlor, respectively. And adsorption distribution coefficients (Kd) by the adsorption and desorption methods were 56 and 94 for ethalfluralin, and 104 and 189 for pendimethalin, respectively. K or Kd values of pesticides by the desorption method which were desorbed from the soil after thoroughly mixing, were higher than these ones by the adsorption method which pesticides dissolved in water were adsorbed to the soil. Another parameter (1/n), representing the linearity of adsorption, in Freundlich equation for the pesticides tested ranged from 0.96 to 1.02 by the desorption method and from 0.87 to 1.02 by the adsorption method. Therefore, the desorption method was more independent from pesticide concentration in soil solution than the adsorption method. By Soil Survey and Land Research Center (SSLRC)'s classification for pesticide mobility, alachlor and ethoprophos were classified into moderately mobile $(75{\leq}Koc<500)$, and ethalfluralin and pendimethalin were included to non-mobile class (Koc > 4000). Runoff and erosion loss of pesticides by three rainfall scenarios were from 1.0 to 6.4% and from 0.3 to 1.2% for alachlor, from 1.0 to 2.5% and from 1.7 to 10.1% for ethalfluralin, from 1.3 to 2.9% and from 3.9 to 10.8% for pendimethalin, and from 0.6 to 2.7% and from 0.1 % 0.3% for ethoprophos, respectively. Distribution of pesticides in soil profile were investigated after the simulated rainfall study. Alachlor and ethoprophos were leached to from 10 to 15 cm of soil layer, but ethalfluralin and pendimethalin were mostly remained at the top 5 cm of soil profile. The losses of the pesticides at 30% of sloping degree were from 0.2 to 1.9 times higher than those at 10%. The difference of their runoff loss was related with their concentration in runoff water while the difference of their erosion loss must be closely related with the quantity of soil eroded.