• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.483-493
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• 2021

Urban overcrowding has created an explosive supply and demand for high-rise buildings. High-rise buildings are contributing to enhancing the image of the city by serving as focal points, but due to the stack effect, malfunction of elevator doors, difficulties in opening and closing the doors and windows of the outer wall, smoke and odors spreading to the upper floors, noise, energy loss, fire and pollutants have been causing various unexpected problems such as rapid spread of fire. This study classified high-rise buildings according to their vertical zoning, analyzed the causes of and solutions to the stack effect, and derived design and construction methods. Through the initial plan to block the outside air and securing airtightness through precise construction, we sought ways to secure the airtightness inside and outside the building by actively blocking the airflow from the lower floors. In addition, the facility solution can be a measure to reduce the specific phenomena caused by the stack effect, but it should only be applied to the minimum extent because the potential for secondary damage is high. This study emphasized the need for systematic stack effect management by suggesting design and construction measures for each vertical zoning of the causes and countermeasures of the stack effect. It is expected that this study will be helpful not only for design and construction, but also for building maintenance.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Korean Journal of Radiology
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• v.22 no.4
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• pp.624-633
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• 2021

Objective: To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters. Materials and Methods: A phantom, simulating the L2-4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings. Results: The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30-150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0-44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used. Conclusion: Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1764-1776
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• 2021

Objective: This study aimed to validate a deep learning-based fully automatic calcium scoring (coronary artery calcium [CAC]_auto) system using previously published cardiac computed tomography (CT) cohort data with the manually segmented coronary calcium scoring (CAC_hand) system as the reference standard. Materials and Methods: We developed the CAC_auto system using 100 co-registered, non-enhanced and contrast-enhanced CT scans. For the validation of the CAC_auto system, three previously published CT cohorts (n = 2985) were chosen to represent different clinical scenarios (i.e., 2647 asymptomatic, 220 symptomatic, 118 valve disease) and four CT models. The performance of the CAC_auto system in detecting coronary calcium was determined. The reliability of the system in measuring the Agatston score as compared with CAC_hand was also evaluated per vessel and per patient using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. The agreement between CAC_auto and CAC_hand based on the cardiovascular risk stratification categories (Agatston score: 0, 1-10, 11-100, 101-400, > 400) was evaluated. Results: In 2985 patients, 6218 coronary calcium lesions were identified using CAC_hand. The per-lesion sensitivity and false-positive rate of the CAC_auto system in detecting coronary calcium were 93.3% (5800 of 6218) and 0.11 false-positive lesions per patient, respectively. The CAC_auto system, in measuring the Agatston score, yielded ICCs of 0.99 for all the vessels (left main 0.91, left anterior descending 0.99, left circumflex 0.96, right coronary 0.99). The limits of agreement between CAC_auto and CAC_hand were 1.6 ± 52.2. The linearly weighted kappa value for the Agatston score categorization was 0.94. The main causes of false-positive results were image noise (29.1%, 97/333 lesions), aortic wall calcification (25.5%, 85/333 lesions), and pericardial calcification (24.3%, 81/333 lesions). Conclusion: The atlas-based CAC_auto empowered by deep learning provided accurate calcium score measurement as compared with manual method and risk category classification, which could potentially streamline CAC imaging workflows.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Investigative Magnetic Resonance Imaging
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• v.17 no.2
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• pp.110-122
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• 2013

Purpose : To compare the image quality and ligament traceability in ankle images obtained using Volume Isotropic Turbo Spin Echo Acquisition (VISTA) MRI with and without fat suppression. Materials and Methods: The signal-to-noise ratios (SNRs) in images from a phantom and from the ankle of a volunteer were compared. Ten ankles from 10 non-symptomatic volunteers were imaged for comparisons of contrast ratio (CR) and ligament traceability. All examinations were performed using VISTA sequences with and without fat suppression on a 3T MRI scanner. The SNRs were obtained from images with subjects and without subjects (noise-only). Contrast ratios from images of the 10 ankles were acquired between fluid and tendon (F-T), F-cartilage (C), F-ligament (L), fat (f)-T, f-C and f-L. Two musculoskeletal radiologists independently scored the traceability of 7 ligaments, in sagittal, axial and coronal images respectively, based on a 4-point scale (1 as not traceable through 4 as clearly traceable). The Wilcoxon signed-rank test was used to compare the CR. Fisher's exact test and Pearson's chi-squared test were used to compare the ligament traceability. Results: The SNRs did not differ significantly between the two sequences except in bone marrow. VISTA SPAIR showed the higher CR only in F-T (p = 0.04), whereas VISTA showed higher CR in f-T (p = 0.005), f-C (p = 0.005) and f-L (p = 0.005). The calcaneofibular ligament traceability with VISTA was superior to that obtained with VISTA SPAIR (p < 0.05) in all planes. Conclusion: VISTA showed significant superiority to VISTA SPAIR in tracing CFL due to the superior CR between fat and ligament.

• Progress in Medical Physics
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• v.21 no.1
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• pp.1-8
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• 2010

In this study, we evaluated the dose response of MAGAT (Methacrylic Acid Gelatin gel and THPC) normoxic polymer gel dosimeters based on the X-ray CT scanner. To perform this study, we determined the proper ratio of the gel composition and acquired X-ray scan parameters. MAGAT gel dosimeters were manufactured using MAA (MethacrylicAcid) and gelatin of various concentration, irradiated up to 20 Gy. We obtained the 20 CT images from the irradiated gel dosimeters by using on a Phillips Brilliance Big Bore CT scanner with the various scan parameters. This CT images were used to determine the $N_{CT}$-dose response, dose sensitivity and dose resolution As an amount of MAA and gelatin were increase, the slope and intercept were increase in each MAGAT gel dosimeter with various concentration of the $N_{CT}$-dose response curve. The dose sensitivity was $0.38{\pm}0.08$ to $0.859{\pm}0.1$ and increased were amount of the MAA was increased or the gelatin was decreased. However, the change of gelatin concentration was very small compare to MAA. The Dose resolution ($D_{\Delta}^{95%}$) varies considerably from 2.6 to 6 Gy, dependent on dose resolution and CT image noise. The slope and dose sensitivity was almost ident verywith the variation of the tube voltage, tube current and slice thickness in the dose response curve, but the noise (standard deviation of averamalg CT number) was decreased when the tube voltage, tube current and slice thickness are increase. The optimal MAGAT polymer gel dosimeter based on the CT were evaluated to determine the CT imaging scan parameters of the maximum tube voltage, tube current and slice thickness (commonly used in clinical) using the composition ratio of a 9% MAA, 8% gelatin and 83% water. This study could get proper composition ratio and scan parameter evaluating dose response of MAGAT normoxic polymer gel dosimeter using CT scanner.

• Journal of the Korean Geophysical Society
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• v.3 no.1
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• pp.57-66
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• 2000

The location and geometry of the Ulsan Fault play important roles in interpreting tectonic evolution of the southeastern part of the Korean Peninsula. Dipole-dipole electrical resistivity surveys and seismic refraction surveys were carried out in the Yaksoo area, Ulsan in order to measure the thickness of the alluvium covering the Ulsan Fault and to find associated fracture zones and possibly the location of its major fault plane. The collected data were analyzed and interpreted. Some results reported previously by others were also used in this interpretation. No low resistivity anomalies were found in the cross-sectional resistivity image of the survey line located in the east of the Dong River. In contrast, well-developed continuous low resistivity anomalies were detected in the west of the Dong River. This strongly suggests that the major fault plane of the Ulsan Fault is located under or in the west part of the Dong River. Two refraction boundaries corresponding to the underground water level and the bottom of the alluvium were found by refraction surveys carried out on the limited part of the east survey line. The thickness of the alluvium was found to be about 30 m. Small faults in the basement rock identified by reflection surveys were not detected by both resistivity and refraction seismic surveys. This might be explained by assuming that low resistivity anomaly is more closely related to the clay contents than the water contents. On the other hand, it may be resulted by the limited resolution of the resistivity and refraction surveys. Detailed study is required to clarify the reason. Resistivity survey is frequently considered to be a good exploration method to detect subsurface faults. However, it appears to be less useful than reflection seismic survey in this work. In dipole-dipole resistivity survey, the number of separation should be increased to survey deeper subsurface with the same resolution. However, signal to noise ratio decreases as the number of separation increases. In this survey area, the signal to noise ratio of up to sixteen separations was good enough based on the statistical properties of measurements.