• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.8
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• pp.630-640
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• 2003

As tunnel ventilation has recently been playing a major role in the tunnel construction and maintenance, longitudinal ventilation systems with jet fans have been utilized a great deal because they are economical and effective. However, due to the length of tunnels and heavy traffic, it is hard to take the field measurements. In this study, therefore, the computer simulation and the model experiment of producing a wind tunnel were carried out simultaneously and the results were compared. The ultimate objective of this research was to interpret the air flow pattern inside the tunnel with a jet-fan was set up, and to offer the useful data for jet-fan installation and operation. The experiment was carried out with varying the jet-fan diameters, location of installation, the discharge velocity. Result showed that as the initial static pressure came up with the negative pressure, the tunnel air flowed into the inside of tunnel from outside due to the entrainment-effect and the backflow-phenomenon by separation-effect was observed in the lower half part of the tunnel. As the jet-fan was getting closer to the tunnel wall, the entrainment-effect caused by the interaction with the wall was increased; however, the mixing distance and irregular flow section became longer, and also the air pressure loss generated by wall friction was large.

• Journal of Interdisciplinary Genomics
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• v.3 no.1
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• pp.21-24
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• 2021

Purpose: Activating mutations of the calcium-sensing receptor (CASR) are a rare genetic disorder, and result in autosomal dominant hypocalcemia with hypercalciuria (ADHH). ADHH exhibited varying degrees of hypocalcemia. In this study, we report the clinical and molecular characteristics of activating variants in CASR patients diagnosed in Korea. Methods: This study included three patients with activating variants of CASR confirmed by biochemical and molecular analysis of CASR. Clinical and biochemical findings were reviewed chart retrospectively. Mutation analysis of CASR was performed by Sanger sequencing. Results: Subject 1 showed severe symptoms from the neonatal period and had difficulty in controlling the medications that were administered. Subject 2 was identified as having a novel variant of CASR with hypocalcemia and a low parathyroid hormone that were found in the neonatal period. During a course without medication, hypocalcemia occurred suddenly around 2 years of age. Subject 3 was diagnosed with hypoparathyroidism with hypocalcemic seizures starting from the neonatal period. About 4 years without taking medication with any symptom. However, at 10 years old revisited by repetitive hypocalcemic seizure events. Subject 1 and 3, were heterozygous for c.2474A>T (p.Y825F), c.2395G>A (p.E799K) located in the transmembrane domain (TMD) of CASR. Subject 2 was heterozygous for c.403A>C (S430L) located in the extracellular domain (ECD) of CASR. Conclusion: We reported 3 patients who have activating CASR variant with different onset and severity of symptoms. In the future, further study is needed to determine how the protein level according to the location of the mutation of CASR affects the degree of symptoms.

• Journal of Aerospace System Engineering
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• v.12 no.6
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• pp.9-16
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• 2018

This paper describes how to find out the optimum position of the reaction wheel assembly (RWA) to minimize image quality degradation through the integrated system jitter prediction combining the micro-vibration test with finite element analysis considering optical coefficients. Micro-vibration generated from RWA that is widely used for satellite maneuver, is one of key factors that degrades the quality of satellite image. Due to varying vibration characteristics of each RWA, its accommodation position may affect image quality even though the same company manufactured them. To resolve this issue, an integrated system jitter prediction is conducted with all possible RWA accommodation location, and finally we determine optimal RWA position from the analysis results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.24-34
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• 2019

In this research, a practical deep learning framework to differentiate the lesions and nodules in breast acquired with ultrasound imaging has been proposed. 7408 ultrasound breast images of 5151 patient cases were collected. All cases were biopsy proven and lesions were semi-automatically segmented. To compensate for the shift caused in the segmentation, the boundaries of each lesion were drawn using Fully Convolutional Networks(FCN) segmentation method based on the radiologist's specified point. The data set consists of 4254 benign and 3154 malignant lesions. In 7408 ultrasound breast images, the number of training images is 6579, and the number of test images is 829. The margin between the boundary of each lesion and the boundary of the image itself varied for training image augmentation. The training images were augmented by varying the margin between the boundary of each lesion and the boundary of the image itself. The images were processed through histogram equalization, image cropping, and margin augmentation. The networks trained on the data with augmentation and the data without augmentation all had AUC over 0.95. The network exhibited about 90% accuracy, 0.86 sensitivity and 0.95 specificity. Although the proposed framework still requires to point to the location of the target ROI with the help of radiologists, the result of the suggested framework showed promising results. It supports human radiologist to give successful performance and helps to create a fluent diagnostic workflow that meets the fundamental purpose of CADx.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.33-46
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• 2021

After the Gyeongju earthquake, which was the largest in the history of measuring instruments in Korea in 2016, and after the Pohang earthquake, where the pillars of pallet structures were destroyed in 2017, the seismic design standards for all domestic facilities have been revised and supplemented. In particular, during the investigation of the Pohang Earthquake damage cases, liquefaction damage that occurs mainly in countries with strong earthquakes such as the United States, Japan, and New Zealand was found, so studies are being conducted in depth to improve seismic design standards. In this study, the liquefaction potential assessment in the recently revised seismic design standard for port and harbor was reviewed, and an applicability review was conducted focusing on the newly cited liquefaction potential index (LPI). At this time, by varying the thickness and location of the sandy soil where liquefaction can occur, the LPIs for various cases were calculated and compared. Also, 22 LPI values in the practical port area were compared and reviewed along with performance of the liquefaction assessment based on the site response analysis using the boring-hole data of the actual 22 port sites.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.629-638
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• 2023

This study introduces an innovative approach to monitor the whereabouts of workers within indoor construction settings. While traditional modalities such as GPS and NTRIP have demonstrated efficacy for outdoor localizations, their precision dwindles in indoor environments. In response, this research advocates for the adoption of Aruco markers. Leveraging computer vision technology, these markers facilitate the quantification of the distance between a worker and the marker, subsequently pinpointing the worker's instantaneous location with heightened accuracy. The methodology's efficacy was rigorously evaluated in a real-world construction scenario. Parameters including system stability, the influence of lighting conditions, the extremity of measurable distances, and the breadth of recognition angles were methodically appraised. System stability was ascertained by maneuvering the camera at a uniform velocity, gauging its marker recognition prowess. The impact of varying luminosity on marker discernibility was scrutinized by modulating the ambient lighting. Furthermore, the camera's spatial movement ascertained both the upper threshold of distance until marker recognition waned and the maximal angle at which markers remained discernible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1497-1503
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• 2020

Inflammatory myofibroblastic tumors (IMTs) are rare. They are characterized by myofibroblastic spindle cell proliferation with a varying degree of inflammatory cell infiltration. IMT can occur in any anatomic location but has been reported in the lung, mesentery, and omentum, mainly in children or young adults. It rarely occurs in the pancreas and is often difficult to distinguish from other tumors, including some malignant ones. Therefore, it can be challenging to make a radiological diagnosis of IMT. Here, we present a case of IMT that occurred in the pancreas head of a middle-aged female. The patient's ultrasonography, computed tomography, and magnetic resonance imaging findings are presented along with a review of the literature.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.265-273
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• 2023

To effectively and safely manage the radiation exposure to nuclear power plant (NPP) workers in accidents, major overseas NPP operators such as the United States, Germany, and France have developed and applied realistic 3D model radiation dose assessment software for workers. Continuous research and development have recently been conducted, such as performing NPP accident management using 3D-VR based on As Low As Reasonably Achievable (ALARA) planning tool. In line with this global trend, it is also required to secure technology to manage radiation exposure of workers in Korea efficiently. Therefore, in this paper, it is described the application method and assessment results of radiation exposure scenarios for workers in response to accidents assessment technology, which is one of the fundamental technologies for constructing a realistic platform to be utilized for radiation exposure prediction, diagnosis, management, and training simulations following accidents. First, the post-accident sampling after the Loss of Coolant Accident(LOCA) was selected as the accident and response scenario, and the assessment area related to this work was established. Subsequently, the structures within the assessment area were modeled using MCNP, and the radiation source of the equipment was inputted. Based on this, the radiation dose distribution in the assessment area was assessed. Afterward, considering the three principles of external radiation protection (time, distance, and shielding) detailed work scenarios were developed by varying the number of workers, the presence or absence of a shield, and the location of the shield. The radiation exposure doses received by workers were compared and analyzed for each scenario, and based on the results, the optimal accident response scenario was derived. The results of this study plan to be utilized as a fundamental technology to ensure the safety of workers through simulations targeting various reactor types and accident response scenarios in the future. Furthermore, it is expected to secure the possibility of developing a data-based ALARA decision support system for predicting radiation exposure dose at NPP sites.