• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.527-537
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• 2004

Consequence-Based Engineering (CBE) is a new paradigm proposed by the Mid-America Earthquake Center (MAE) to guide evaluation and rehabilitation of building structures and networks in areas of low probability - high consequence earthquakes such as the central region of the U.S. The principal objective of CBE is to minimize consequences by prescribing appropriate intervention procedures for a broad range of structures and systems, in consultation with key decision makers. One possible intervention option for rehabilitating unreinforced masonry (URM) buildings, widely used for essential facilities in Mid-America, is passive energy dissipation (PED). After the CBE process is described, its application in the rehabilitation of vulnerable URM building construction in Mid-America is illustrated through the use of PED devices attached to flexible timber floor diaphragms. It is shown that PED's can be applied to URM buildings in situations where floor diaphragm flexibility can be controlled to reduce both out-of-plane and in-plane wall responses and damage. Reductions as high as 48% in roof displacement and acceleration can be achieved as demonstrated in studies reported below.

• Archives of Plastic Surgery
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• v.51 no.3
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• pp.275-283
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• 2024

Background Shortage of speech and language therapists results in lack of speech services. The aims of this study were to find the effectiveness of a combination speech therapy model at Level IV: General speech and language pathologist (GSLP) and Level V: Specific speech and language pathologist (SSLP) in reduction of the number of articulation errors and promotion the quality of life (QoL) for children with cleft palate with or without cleft lip (CP ± L). Methods Fifteen children with CP ± L, aged 4 years 1 month to 10 years 9 months (median = 76 months; minimum:maximum = 49:129 months) were enrolled in this study. Pre- and post-assessment included oral peripheral examination; articulation tests via Articulation Screening Test, Thai Universal Parameters of Speech Outcomes for People with Cleft Palate, Hearing Evaluation, The World Health Organization Quality of Life Brief_Thai (WHOQOL-BRIEF-THAI) version questionnaire for QoL were performed. Speech therapy included a 3-day intensive speech camp by SSLP, five 30-minute speech therapy sessions by a GSLP, and five 1-day follow-up speech camps by SSLP that provided four 45-minute speech therapy sessions for each child. Results Post-articulation revealed statistically significant reduction of the numbers of articulation errors at word, sentence, and screening levels (median difference [MD] = 3, 95% confidence interval [CI] = 2-5; MD = 6, 95% CI = 4.5-8; MD = 2.25, 95% CI = 1.5-3, respectively) and improvement of QoL. Conclusion A speech task force consisting of a combination of Level IV: GSLP and Level V: SSLP could significantly reduce the number of articulation errors and promote QoL.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.185-194
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• 2008

There is increased soil erosion potential at highland agricultural crop fields because of its topographic characteristics and site-specific agricultural management practices performed at these areas. The agricultural upland fields are usually located at the sloping areas, resulting in higher soil loss, pesticides, and nutrients in case of torrential rainfall events or typhoon, such as 2002 Rusa and 2003 MaeMi. At the highland agricultural fields, the soil reconditioning have been performed every year to decrease damage by continuous cropping and pests. Also it has been done to increase crop productivity and soil fertility. The increased amounts of soil used for soil reconditioning are increasing over the years, causing significant impacts on water quality at the receiving water bodies. In this study, the field investigation was done to check soil reconditioning status for potato, carrot, and cabbage at the Doam-dam watershed. With these data obtained from the field investigation, the Soil and Water Assesment Tool (SWAT) model was used to simulate the soil loss reduction with environment-friendly and agronomically enough soil reconditioning. The average soil reconditioning depth for potato was 34.3 cm, 48.3 cm for carrot, and 31.2 cm for cabbage at the Doam-dam watershed. These data were used for SWAT model runs. Before the SWAT simulation, the SWAT ArcView GIS Patch, developed by the Kangwon National University, was applied because of proper simulation of soil erosion and sediment yield at the sloping watershed, such as the Doam-dam watershed. With this patch applied, the Coefficient of Determination ($R^2$) value was 0.85 and the Nash-Sutcliffe Model Efficiency (EI) was 0.75 for flow calibration. The $R^2$ value was 0.87 and the EI was 0.85 for flow validation. For sediment simulation, the $R^2$ value was 0.91 and the EI was 0.70, indicating the SWAT model predicts the soil erosion processes and sediment yield at the Doam-dam watershed. With the calibrated and validated SWAT for the Doam-dam watershed, the soil erosion reduction was investigated for potato, carrot, and cabbage. For potato, around 19.3 cm of soil were over applied to the agricultural field, causing 146% of more soil erosion rate, approximately 33.3 cm, causing 146% of more soil erosion for carrot, and approximately 16.2 cm, causing 44% of more soil erosion. The results obtained in this study showed that excessive soil reconditioning are performed at the highland agricultural fields, causing severe muddy water issues and water quality degradation at the Doam-water watershed. The results can be used to develop soil reconditioning standard policy for various crops at the highland agricultural fields, without causing problems agronomically and environmentally.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.345-354
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• 2005

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have a priori knowledge about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper presents the motion detection algorithm that can run robustly about recusive motion. The motion detection compares and analyzes two frames each other, motion of whether happened judge. Through experiments, we show significant improvements in the reduction of the computational time in terms of the number of search steps without much quality degradation in the predicted image.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.203-212
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• 2002

This study was conducted to remove the urban heat island effects embedded in the interpolated surfaces of daily minimum temperature in the Korean Peninsula. Fifty six standard weather stations are usually used to generate the gridded temperature surface in South Korea. Since most of the weather stations are located in heavily populated and urbanized areas, the observed minimum temperature data are contaminated with the so-called urban heat island effect. Without an appropriate correction, temperature estimates over rural area or forests might deviate significantly from the actual values. We simulated the spatial pattern of population distribution within any single population reporting district (city or country) by allocating the reported population to the "urban" pixels of a land cover map with a 30 by 30 m spacing. By using this "digital population model" (DPM), we can simulate the horizontal diffusion of urban effect, which is not possible with the spatially discontinuous nature of the population statistics fer each city or county. The temperature estimation error from the existing interpolation scheme, which considers both the distance and the altitude effects, was regressed to the DPMs smoothed at 5 different scales, i.e., the radial extent of 0.5, 1.5, 2.5, 3.5 and 5.0 km. Optimum regression models were used in conjunction with the distance-altitude interpolation to predict monthly normals of daily minimum temperature in South Korea far 1971-2000 period. Cross validation showed around 50% reduction in terms of RMSE and MAE over all months compared with those by the conventional method.conventional method.

• Biomolecules & Therapeutics
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• v.30 no.3
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• pp.238-245
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• 2022

Previous reports have demonstrated that genetic mechanisms greatly mediate responses to drugs of abuse, including methamphetamine (METH). The circadian gene Period 2 (Per2) has been previously associated with differential responses towards METH in mice. While the behavioral consequences of eliminating Per2 have been illustrated previously, Per2 overexpression has not yet been comprehensively described; although, Per2-overexpressing (Per2 OE) mice previously showed reduced sensitivity towards METH-induced addiction-like behaviors. To further elucidate this distinct behavior of Per2 OE mice to METH, we identified possible candidate biomarkers by determining striatal differentially expressed genes (DEGs) in both drug-naïve and METH-treated Per2 OE mice relative to wild-type (WT), through RNA sequencing. Of the several DEGs in drug naïve Per2 OE mice, we identified six genes that were altered after repeated METH treatment in WT mice, but not in Per2 OE mice. These results, validated by quantitative real-time polymerase chain reaction, could suggest that the identified DEGs might underlie the previously reported weaker METH-induced responses of Per2 OE mice compared to WT. Gene network analysis also revealed that Asic3, Hba-a1, and Rnf17 are possibly associated with Per2 through physical interactions and predicted correlations, and might potentially participate in addiction. Inhibiting the functional protein of Asic3 prior to METH administration resulted in the partial reduction of METH-induced conditioned place preference in WT mice, supporting a possible involvement of Asic3 in METH-induced reward. Although encouraging further investigations, our findings suggest that these DEGs, including Asic3, may play significant roles in the lower sensitivity of Per2 OE mice to METH.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.29-39
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• 2023

In this study, an analysis of medical waste generation characteristics was conducted, differentiating between ordinary situation and the outbreaks of massive infectious diseases. During ordinary situation, prediction models for medical waste quantities by type, general medical waste(G-MW), hazardous medical waste(H-MW), infectious medical waste(I-MW), were established through regression analysis, with all significance values (p) being <0.0001, indicating statistical significance. The determination coefficient(R2) values for prediction models of each category were analyzed as follows : I-MW(R2=0.9943) > G-MW(R2=0.9817) > H-MW(R2=0.9310). Additionally, factors such as GDP(G-MW), the number of medical institutions (H-MW), and the elderly population ratio(I-MW), utilized as influencing factors and consistent with previous literature, showed high correlations. The total MW generation, evaluated by combining each model, had an MAE of 2,615 and RMSE of 3,353. This indicated accuracy levels similar to the medical waste models of H-MW(2,491, 2,890) and I-MW(2,291, 3,267). Due to limitations in accurately estimating the quantity of medical waste during the rapid and outbreaks of massive infectious diseases, the generation unit of I-MW was derived to analyze its characteristics. During the early unstable stage of infectious disease outbreaks, the generation unit was 8.74 kg/capita·day, 2.69 kg/capita·day during the stable stage, and an average of 0.08 kg/capita·day during the reduction stage. Correlation analysis between generation unit of I-MW and lethality rates showed +0.99 in the unstable stage, +0.52 in the stable stage, and +0.96 in the reduction period, demonstrating a very high positive correlation of +0.95 or higher throughout the entire outbreaks of massive infectious diseases. The results derived from this study are expected to play a useful role in establishing an effective medical waste management system in the field of health care.

• Korean Journal of Digital Imaging in Medicine
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• v.13 no.2
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• pp.63-69
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• 2011

Table strapis patient fixture for securing the patient movements and falls. if it designed to measure the abdominal circumference and used as an indicator of dose selection at CT scan. it will prevent the overexposure of dose without degradation of image quality and efficiently manage dose of each type of body to technician to deal with CT. First, in order to compare the dose used in CT image and qualitative characteristics. reference image is obtained by examining the abdominal phantom in same conditions with the hospital 120 kVp, 200 mAs, D-Dom (Dynamic Dose Of Modulation). SNR, PSNR, RMSE, MAE, CTDIvol of CT images are compared with reference image. for comparing with reference image, the image that Umbilicus level image of Abdomen CT is stored in the PACS were used. For comparison, the top 12 o'clock portion of the air drawn from the same ROI was measured. CTDIvol, mAs, etc. In order to analyze the characteristics of the image, by measuring the length of the umbilicus circumference, pattern of the dose was analyzed. by using the analyzed perimeter and dose information, To be identified visually, fixed band that scale marked were produced. Use them, If the length of circumference of less than 60 cm 100 mAs, Case of 61~80 cm 120 mAs, Case of 80~100 cm 150 mAs, more than 100 cm 200 mAs, dose selection based on the perimeter, the image was applied. by compare analyzed with the Reference Image, image quality was assessed. by compare with existing tests that equally 200 mAs applied, How much was confirmed that the dose reduction. 1. Depending on the Abdominal circumference, the average PSNR(dB) of the image that differently dose applied was 45.794. 2. Comparing with existing test. the dose of scan that adjusted the mAs depending on the circumference was decreased about 40%. SNR and PSNR of the image that obtained by adjusting the standard mAs based on dose modulation were not much different. Therefore, By choosing a low mAs. dose reduction can be obtained. and the dose selection method that measured Abdominal circumference using a fixed band can protect the overexposure and uniformly apply dose of each type of body to technician to deal with CT.

• 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.