• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.561-568
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• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.251-263
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• 2022

This paper presents an idea of ScanSAR image formation. For image formation of ScanSAR that utilizes the burst mode for raw signal acquisition, most conventional single burst methods essentially require a step of azimuth stitching which contributes to radiometric and phase distortions to some extent. Time-domain cross correlation could replace SPECAN which is most popularly used for ScanSAR processing. The core idea of the proposed method is that it is possible to relieve the necessity of azimuth stitching by an extension of Doppler bandwidth of the reference function to the burst cycle period. Performance of the proposed method was evaluated by applying it to the raw signals acquired by a spaceborne SAR system, and results satisfied all image quality requirements including 3 dB width, peak-to-sidelobe ratio (PSLR), compression ratio,speckle noise, etc. Image quality of ScanSAR is inferior to that of Stripmap in all aspects. However, it is also possible to improve the quality of ScanSAR image competitive to that of Stripmap if focused on a certain parameter while reduced qualities of other parameters. Thus, it is necessary for a ScanSAR processor to offer a great degree of flexibility complying with different requirements for different applications and techniques.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.319-325
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• 2022

The Study In order to obtain a sharpness Image from Skull PA axial projection (Haas) in a head axial X-ray Examination, this study changed the posture angle using Skull Phantom and evaluated the image subjectively to 5 radiologists who worked in the Department of Imaging at University Hospital. In the prone position, the head was lowered 4 cm from the back of the head, entered 25° toward the head, and the image evaluation score was high with 20 points, such as the back bone, dorsum sellae projected in the large hole, and posterior clinoid process. In addition, the score significance was verified, and the Cronbach Alpha value was evaluated to have good reliability of 0.789. As a result of calculating the signal-to-noise ratio (SNR) by setting the region of interest (ROI) of the image, it was the highest at 5.957 for 25° incident at the back of the head and 6.430 for 30° incident at the back of the head. As a result of the study, in order to obtain a sharp image of the back of the head bone, dorsum sellae, and posterior clinoid process when shooting in the axial direction after the head, it is filmed by tilting 25° toward the head from 4 cm below the back of the head. In order to obtain a sharp image of rock pyramid symmetry, petrous ridge, sagittal suture, and lambdoid suture, it is thought that it will be helpful for clinical use if you shoot it 8cm down from the back of the head and tilt it 30° toward the head.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.446-460
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• 2022

In this paper, we propose an algorithm to improve target detection rate degradation due to direct blast in a bi-static sonar systems with high duty cycle using an adaptive filters. It is very important to suppress the direct blast in the aforementioned sonar systems because it has a fatal effect on the actual system operation. In this paper, the performance was evaluated by applying the Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms to the simulation and sea experimental data. The beam signals of the target and direct blast bearings were used as the input and desired signals, respectively. By optimizing the difference between the two signals, the direct blast is removed and only the target signal is remained. As a result of evaluating the results of the matched filter in the simulation, it was confirmed that the direct blast was removed to the noise level in both Linear Frequency Modultated (LFM) and Generalized Sinusoidal Frequency Modulated (GSFM), and in the case of GSFM, the target sidelobe decreased by more than 20 dB, thereby improving performance. In the sea experiment, it was confirmed that the LFM reduced the level of the transmitted direct wave by 10 dB, the GSFM reduced the level of the transmitted direct wave by about 4 dB, and the side lobe of the target decreased by about 4 dB, thereby improving the performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1517-1524
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• 2022

In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.871-877
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• 2022

This study was conducted to improve the problems of exposure dose and image reading applied to patients due to the incorrect use of AEC during chest radiography. Images were acquired by dividing the case where AEC was used as the test condition and the case where AEC was not used. As a result of the study, the dose was reduced by 1.17% in 110 kVp without AEC than with AEC, 17.2% decrease at 100 kVp, 30.19% decrease at 90 kVp, and 46.45% decrease at 80 kVp. There was a significant difference in the statistical values according to the tube voltage change in the lung, trachea, and heart SNR average values with AEC and without AEC 110 kVp, but the difference in image quality was insignificant in actual images. When AEC was not applied at the same tube voltage, the dose could be reduced by 17.2% while maintaining the image quality similar to that of with AEC at 100 kVp without AEC. Therefore, rather than relying on AE conditions during chest radiographic examination, it is considered that the conditions should be considered for the examination while lowering the dose by selecting an appropriate tube voltage.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.77-90
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• 2022

This study seeks to develop a stretch sensor for measuring the wrist movements of people using fishing lures. In order to confirm wrist movement, a stretch sensor was attached to the wrist band, and measurements of the dorsiflexion, plantar flexion, and fishing landing motion were measured using a scale to gauge factor, tensile strength, and elongation recovery rate. A conductive sensor using CNT dispersion was developed and applied to the E-band under the same conditions. A total of 15 sensors of the same size and five types of impregnation once, twice, and three times each were used to measure the gauge factor using UTM. The sensor that was impregnated twice had the best gauge rate, and the prototypes were manufactured with three sensors with high gauge rates and tensile strength. The results of the operation test conducted by connecting to the Arduino showed that Sample 1, which had the highest tensile strength and gauge factor, had a stable graph wavelength in three operations. Samples 2 and 3 showed stable wavelengths in the dorsiflexion and the plantar flexion; however, signal noise appeared in the fishing landing motion. This showed stable wavelengths in the two motions, but the wavelengths of the graphs differ depending on the tensile strength and gauge factor in the fishing landing motion. As a result, it was possible to identify the conditions necessary for manufacturing a stretch sensor for measuring wrist movement. This study will contribute to the development of smart wearable products for lure fishing.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.145-148
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• 2023

Open-loop Octonion space-time block code for 4 transmit antenna system is considered and random phases are applied to 4 transmit antennas for physical layer security. When an illegal hacker estimates the random phases of 1 through 4 transmit antennas with maximum likelihood (ML), this letter analyzes the bit error rate (BER) performances versus signal-to-noise ratio (SNR). And the Octonion code in the literature[1] does not have full orthogonality so, this letter employs the perfect orthogonal Octonion code. When the hacker knows that the random phases are 2-PSK constellations and he should estimate all the 4 random phases, the hacking is impossible until 100dB. When the hacker possibly know that some of the random phases, bit error rate goes down to 10^-3 so, the transmit message could be hacked.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.403-411
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• 2023

Functional ultrasound imaging, such as elasticity imaging and micro-blood flow Doppler imaging, enhances diagnostic capability by providing useful mechanical and functional information about tissues. However, the implementation of functional ultrasound imaging poses limitations such as the storage of vast amounts of data in Radio Frequency (RF) data acquisition and processing. In this paper, we propose a sub-Nyquist approach that reduces the amount of acquired axial samples for efficient shear-wave elasticity imaging. The proposed method acquires data at a sampling rate one-third lower than the conventional Nyquist sampling rate and tracks shear-wave signals through RF signals reconstructed using band-pass filtering-based interpolation. In this approach, the RF signal is assumed to have a fractional bandwidth of 67 %. To validate the approach, we reconstruct the shear-wave velocity images using shear-wave tracking data obtained by conventional and proposed approaches, and compare the group velocity, contrast-to-noise ratio, and structural similarity index measurement. We qualitatively and quantitatively demonstrate the potential of sub-Nyquist sampling-based shear-wave elasticity imaging, indicating that our approach could be practically useful in three-dimensional shear-wave elasticity imaging, where a massive amount of ultrasound data is required.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.