• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Economic Analysis
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• v.27 no.4
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• pp.1-42
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• 2021

The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

• Clean Technology
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• v.16 no.2
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• pp.103-116
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• 2010

It has been reported that the LCD panel market in the FPD industry is become growing and its panel size and production capacity are increasing, and its manufacturing technique is improved every year. FPD manufacturing process requires high cleanliness in its overall process. Especially, FPD cleaning process which accounts for 30~40% of total manufacturing process is very important in its technological and productivity aspects. It is difficult to remove residual liquid-crystal in the fine gap after liquid-crystal injection process in the cell. In this study, aqueous cleaning agents with excellent cleaning, rinsing, and penetrating abilities, but minimum ion content for LCD panel were formulated through mixing glycol ether-type and glycol dimethyl ether-type solvents and nonionic surfactants which are widely used as raw materials for alternative cleaning agents because of environmental regulation at home and abroad. And the formulated cleaning agents were applied to clean FPD liquid crystal after its injection in the cell. Physical properties, cleaning efficiencies, and rinsabilities of the formulated cleaning agents with different combination ratios of solvents, surfactants and additives were measured. As experimental results, the formulated cleaning agents showed higher wetting indices and cloud point than the traditional commercial cleaning agent. And it was found that cleaning efficiencies of the formulated cleaning agents were influenced by the structure of main solvents in them and the types of liquid crystal as soil for cleaning. The best cleaning agents among the formulated cleaning agents showed similar cleaning efficiencies and better rinsabilities compared to the conventional cleaning agent.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.16-24
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• 2023

Accidents are greatly reduced through projects to improve frequent traffic accidents. These results show that safety facilities play a big role. Traffic accidents are caused by various causes and various environmental factors, and it is difficult to achieve improvement effects by installing one safety facility or facilities without standards. Therefore, this study analyzed the improvement effect of each accident type by combining the two safety facilities, and suggested a method of predicting the combination of safety facilities suitable for a specific point, including environmental factors such as road type, road type, and traffic. The prediction was carried out by selecting an XGBoost technique that creates one strong prediction model by combining prediction models that can be simple classification. Through this, safety facilities that have had positive effects through improvement projects and safety facilities to be installed at points in need of improvement were derived, and safety facilities effect analysis and prediction methods for future installation points were presented.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• Korean Journal of Environmental Agriculture
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• v.42 no.2
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• pp.112-120
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• 2023

Methane (CH₄) and nitrous oxide (N₂O) are significant contributors to greenhouse gas (GHG) emissions from rice fields. Mid-summer drainage is a commonly practiced water management technique that reduces CH₄ emissions from rice fields. Slow-release fertilizers gradually release nutrients over an extended period and have been shown to reduce N₂O emissions. However, the combined effect of slow-release fertilizer and water management on GHG emissions remains unclear. This study compared GHG emissions from a rice paddy subjected to mid-summer drainage for 10 days (control) with that of a rice paddy subjected to prolonged mid-summer drainage for 20 days combined with slow-release fertilizer (W+S). Gas sampling was conducted weekly using a closed chamber method. During the rice cultivation period, cumulative CH₄ and N₂O emissions were reduced by 12.3% and 16.2%, respectively, in the W+S treatment compared to the control. Moreover, the W+S treatment exhibited a 1.9% increase in grain yield compared to the control. Under experimental conditions, slow-release fertilizers, in combination with prolonged mid-summer drainage, proved to be the optimal approach for achieving high crop yield while reducing GHG emissions. This represents an effective strategy to mitigate GHG emissions from rice paddy fields.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.63-74
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• 2008

Site response analyses were performed based on equivalent linear technique using the local geologic and dynamic site characteristics, which include soil profiles, shear wave velocity profiles and depth to bedrock for 125 sites collected in Korean Peninsula. From the results of site response analyses, 2-parameters site classification system based on the combination of mean shear wave velocity of soil and depth to bedrock was newly recommended for regions of shallow bedrock depth in Korea. First, as the borders of bedrock depth (H) for site classification were determined as 10m and 20m, the soil sites were divided into 3 classes as $H_1$, $H_2$ and $H_3$ sites. And then, the 3 site classes were subdivided into 7 classes based on the mean shear wave velocity of soil ($V_{s,soil}$). The feasibility of new site classification system was verified and the representative site coefficients ($F_a$ and $F_v$) and design response spectrum were suggested by analyzing uniform trend and dispersion of site coefficients for each site class. The suggested site coefficients and the regression curves present the nonlinear characteristics of soils according to the change of rock outcrop acceleration with uniform trend effectively. From the comparison between the mean values of response spectrum which was acquired from the site response analysis and the suggested design response spectrum, there was a little difference in some of site classes and it was verified to adjust the integration interval to make it more suitable for the site condition in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.775-784
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• 2023

In terms of flood management, it is necessary to analyze quantitative rainfall and runoff from a spatial and temporal perspective and to analyze runoff for heavy rainfall events that are concentrated within a short period of time. The simulation and analysis results of rainfall-runoff models vary depending on the type and input data. In particular, rainfall data is an important factor, so calculating areal mean rainfall is very important. In this study, the areal mean rainfall of the Samcheok Osipcheon(Riv.) watersheds located in the mountainous terrain was calculated using the Arithmetic Mean Method, Thiessen's Weighting Method, and the Isohyetal Method, and the rainfall-runoff results were compared by applying the distributional model S-RAT and the lumped model HEC-HMS. The results of the temporal transferability study showed that the combination of the distributional model and the Isohyetal Method had the best statistical performance with MAE of 64.62 m³/s, RMSE of 82.47 m³/s, and R² and NSE of 0.9383 and 0.8547, respectively. It is considered that this study was properly analyzed because the peak flood volume occurrence time of the observed and simulated flows is within 1 hour. Therefore, the results of this study can be used for frequency analysis in the future, which can be used to improve the accuracy of simulating peak flood volume and peak flood occurrence time in mountainous watersheds with steep slopes.

• Information Systems Review
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• v.25 no.1
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• pp.129-143
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• 2023

In the era of big data, the field of artificial intelligence is showing remarkable growth, and in particular, the image classification learning methods by deep learning are becoming an important area. Various studies have been actively conducted to further improve the performance of CNNs, which have been widely used in image classification, among which a representative method is the Convolutional Recurrent Neural Network (CRNN) algorithm. The CRNN algorithm consists of a combination of CNN for image classification and RNNs for recognizing time series elements. However, since the inputs used in the RNN area of CRNN are the flatten values extracted by applying the convolution and pooling technique to the image, pixel values in the same phase in the image appear in different order. And this makes it difficult to properly learn the sequence of arrangements in the image intended by the RNN. Therefore, this study aims to improve image classification performance by proposing a novel hybrid method of CNN and RNN applying the concepts of encoder and decoder. In this study, the effectiveness of the new hybrid method was verified through various experiments. This study has academic implications in that it broadens the applicability of encoder and decoder concepts, and the proposed method has advantages in terms of model learning time and infrastructure construction costs as it does not significantly increase complexity compared to conventional hybrid methods. In addition, this study has practical implications in that it presents the possibility of improving the quality of services provided in various fields that require accurate image classification.

• Journal of Yeungnam Medical Science
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• v.16 no.2
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• pp.347-356
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• 1999

Background: Exit site/tunnel infection causes considerable morbidity and technique failure in CAPD patients. We presently use a unique revision method for the treatment of refractory ESI/TI in CAPD patients and mupirocin prophylaxis for high risk patients. Materials and Methods: We reviewed 139 CAPD patients about the ESI/TI from October 1993 to February 1999 at Yeungnam University Hospital. At the beginning of the ESI. we usually started medications with rifampicin and ciprofloxacin and then changed the antibiotics according to the sensitivity test. If the ESI had persisted and there were TI symptoms (purulent discharge, abscess lesion around exit site). we performed catheter revision(external cuff shaving, disinfection around tunnel and new exit site on opposit direction) with a combination of proper antibiotics. We applied local mupirocin ointment at the exit site three times per week to the 34 patients who had the risk of ESI starting from October 1998. Results: The total follow-up was 2401 patient months(pt. mon). ESI occurred on 105 occasions in 36 out of 139 patients, and peritonitis occurred on 112 occasions in 67 out of 139 patients. The total number of incidences of ESI and peritonitis was 1 per 23.0 pt. mon and 1 per 2l.6 pt.mon. The most common organism responsible for ESI was Staphylococcus aureus (26 of 54 isolated cases, 48%), followed by the Methicillin resistant S. aureus(MRSA) (13 cases, 24%). Seven patients(5: MRSA. 2: Pseudomonas) had to be treated with a revision to control infection. Three patients experienced ESI relapse after revision. One of them improved with antibiotics, while another needed a second revision and the remaining required catheter removal due to persistent MRSA infection with re-insertion at the same time. But, there was no more ESI in these 3 patients who were received management to relapse (The mean duration: 14.0 months). The rates of ESI were significantly reduced after using mupirocin than before(1 per 12.7 vs 34.0 pt.mon, P<0.01). Conclusions: In summary, revision technique can be regarded as an effective method for refractory ESI/TI before catheter removal. Also local mupirocin ointment can play a significant role in the prevention of ESI.