• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.550-555
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• 2018

International Maritime Organization (IMO) is one of the most effective organizations in evolving international law for the protection and conservation of the marine environment. The IMO, MARPOL(Marine Pollution) 73/78 contains six Annexes that provide an overarching framework for the objectives of the international marine pollution. Annex IV was regulated by 64 th resolution in 2012 to control sea pollution from sewage. In 2014 large-scale wastewater treatment and nutrient removal device was developed with a grant from the Ministry of Oceans and Fisheries. A combined new process of Sequence Batch Reactor (SBR) and Membrane Bioreactor(MBR) was developed to overcome the pollution caused by shipboard sewage. In the present study, shipboard sewage wastewater was treated by mixing and aeration cycle in the newly developed SBR process. Furthermore, during analysis by NGS technique(Macrogen Co., Ltd.), dominant species of bacteria were found in the aeration tank of the Bench-scale wastewater treatment facility. Bacteroidetes and Gammaproteobacteria accounted for 27.1 % of the aerobicbacteria and 16.8 % of the anaerobicbacteria, respectively. Microorganisms play a vital role in shipboard wastewater treatment. A further detailed study is required to understand the precise role of the microorganisms in the wastewater treatment.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.403-410
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• 2020

In addition to the research on noise removal and super-resolution using the data restoration (Output result) function of Autoencoder, research on the performance improvement of clustering using the dimension reduction function of autoencoder are actively being conducted. The clustering function and data restoration function using Autoencoder have common points that both improve performance through the same learning. Based on these characteristics, this study conducted an experiment to see if the autoencoder model designed to have excellent data recovery performance is superior in clustering performance. Skip connection technique was used to design autoencoder with excellent data recovery performance. The output result performance and clustering performance of both autoencoder model with Skip connection and model without Skip connection were shown as graph and visual extract. The output result performance was increased, but the clustering performance was decreased. This result indicates that the neural network models such as autoencoders are not sure that each layer has learned the characteristics of the data well if the output result is good. Lastly, the performance degradation of clustering was compensated by using both latent code and skip connection. This study is a prior study to solve the Hanja Unicode problem by clustering.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.4
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• pp.41-50
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• 2022

Recently, research on carbon adsorbents has been active as an interest in improving the environment such as indoor and outdoor air quality. Considering that causative substances deteriorate the air quality are basically volatile organic compounds, it is important to improve the hydrophobicity of the carbon materials for better removal efficiency. This study presents a method for improving hydrophobicity of carbon and a measurement of the hydrophobicity. Generally, methods of improving the hydrophobicity of carbon materials are heat treatment, acid/alkali treatment, coating and immersion with hydrophobic materials. However, it collapses the pore structure and reduces the adsorption capacity. Therefore, this study briefly introduce not only the general method for improving carbon materials' hydrophobicity but also the method for converting the precursor of the material is briefly introduced. Futhermore, this study introduces a analytical technique used to determine hydrophobic modification or not, and aims to enhance the understanding of carbon materials.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.973-979
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• 2020

This study aims to objectively and quantitatively determine the social emotion of empathy by collecting pupillary response. 52 subjects (26 men and 26 women) voluntarily participated in the experiment. After the measurement of the reference of 30 seconds, the experiment was divided into the task of imitation and spontaneously self-expression. The two subjects were interacted through facial expressions, and the pupil images were recorded. The pupil data was processed through binarization and circular edge detection algorithm, and outlier detection and removal technique was used to reject eye-blinking. The pupil size according to the empathy was confirmed for statistical significance with test of normality and independent sample t-test. Statistical analysis results, the pupil size was significantly different between empathy (M ± SD = 0.050 ± 1.817)) and non-empathy (M ± SD = 1.659 ± 1.514) condition (t(92) = -4.629, p = 0.000). The rule of empathy according to the pupil size was defined through discriminant analysis, and the rule was verified (Estimation accuracy: 75%) new 12 subjects (6 men and 6 women, mean age ± SD = 22.84 ± 1.57 years). The method proposed in this study is non-contact camera technology and is expected to be utilized in various virtual reality with smart glasses.

• Journal of Korean Society of Water Science and Technology
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• v.26 no.6
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• pp.99-107
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• 2018

This research has developed a high temperature steam cleaning technology using a ceramic membrane with durability against temperature and pressure conditions. In steam cleaning, steam of $120^{\circ}C$ is injected into the ceramic membrane to induce pyrolysis by the endothermic reaction to remove fouling from the membrane. The water quality of raw water was adjusted to turbidity 10, 25 NTU and DOC 2.5 mg/L, and the membrane was uniformly fouled by constant pressure operation at 100, 200, and 300 kPa. Physical backwashing was performed with water and air at a pressure of 500 kPa and steam at $120^{\circ}C$ was injected for 0 to 5 minutes. As the turbidity concentration and the operating pressure increased, the flux decreased by 0.7 to 14.4%. It is confirmed that 10.7 to 53.8% recovery is possible than physical cleaning at the injection of steam for 3 minutes, so it is considered that the steam cleaning of the ceramic membrane is effective. Compared with CEB after NaOCl (300 mg/L) filtration at 25 NTU and 300 kPa of turbidity, the steam cleaning result for 3 minutes was similar to 46.7% of CEB for 3 hours. It has been confirmed that steam cleaning is suitable for a ceramic membrane having excellent heat resistance against high temperature. It was considered to have better cleaning efficiency as compared with general physical backwashing.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.386-391
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• 2022

This study is about a technique for obtaining collagen by extracting fat by treating collagen-containing liposuction effluent in the presence of supercritical fluid. Using a supercritical solvent, a collagen extract could be obtained from animal-derived fat in a short time (about 6 hours), and about 2-3% of collagen by mass compared to the raw material could be obtained. The presence of collagen in the extract obtained by supercritical extraction was confirmed by SDS-PAGE, and it was confirmed that it was type 1 collagen having a relatively large molecular weight. In addition, the growth factors of IGF-1, bFGF, VEGF and NGF were analyzed to find out which growth factors were present in the collagen obtained by supercritical extraction, and it was found that these growth factors were contained in the extract. There was no significant difference in DNA content per mg of sample before and after supercritical treatment. Further in-depth studies are likely to be needed on decellularization technology using the supercritical process. In conclusion, the extracellular matrix obtained through the solvent extraction process using a supercritical fluid contains growth factors above a certain amount even after decellularization and removal of fat, so that it was found that not only biocompatibility is greatly increased, but also tissue regeneration can be rapidly induced.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.379-385
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• 2023

With the recent development of digital dentistry, fully digitalized methods for fabricating dentures, using intraoral scans and computer-aided design/computer-aided manufacturing (CAD-CAM), are getting popular. Digital methods have the advantage of simplifying the fabrication process in the clinic and laboratory, supplementing digital data. This case report shows a fully digital fabrication method for interim removable dentures in a patient with anterior tooth loss in which implant placement is impossible or delayed. Interim removable dentures were fabricated using two methods. One method is printing tooth and base parts separately and combining, and the other method is printing the whole denture at one time and coloring on the base part. Afterward, dentures were delivered and adaptation was evaluated using the triple scan technique. The extracted site was scanned intraorally (first scan) and the interim removable denture was digitally scanned both intraorally (second scan) and, after removal extraorally (Third scan). In both method, denture adaptation was shown favorable. We report this case report as both the patient and the operator were satisfied with a simplified process using a fully digital method in the clinic.

• The korean journal of orthodontics
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• v.54 no.2
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• pp.79-88
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• 2024

Objective: Alveolar bone loss is a common adverse effect of intrusion treatment. Mandibular incisors are prone to dehiscence and fenestrations as they suffer from thinner alveolar bone thickness. Methods: Thirty skeletal class II patients treated with mandibular intrusion arch therapy were included in this study. Lateral cephalograms and cone-beam computed tomography images were taken before treatment (T1) and immediately after intrusion arch removal (T2) to evaluate the tooth displacement and the alveolar bone changes. Pearson's and Spearman's correlation was used to identify risk factors of alveolar bone loss during the intrusion treatment. Results: Deep overbite was successfully corrected (P < 0.05), accompanied by mandibular incisor proclination (P < 0.05). There were no statistically significant change in the true incisor intrusion (P > 0.05). The labial and lingual vertical alveolar bone levels showed a significant decrease (P < 0.05). The alveolar bone is thinning in the labial crestal area and lingual apical area (P < 0.05); accompanied by thickening in the labial apical area (P < 0.05). Proclined incisors, non-extraction treatment, and increased A point-nasion-B point (ANB) degree were positively correlated with alveolar bone loss. Conclusions: While the mandibular intrusion arch effectively corrected the deep overbite, it did cause some unwanted incisor labial tipping/flaring. During the intrusion treatment, the alveolar bone underwent corresponding changes, which was thinning in the labial crestal area and thickening in the labial apical area vice versa. And increased axis change of incisors, non-extraction treatment, and increased ANB were identified as risk factors for alveolar bone loss in patients with mandibular intrusion therapy.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.