• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.42-50
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• 1997

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.282-295
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• 2013

In order to communicate with a ground station, the tracking profile design problem for a directional antenna system is considered. Because the motions of the gimbal angles in the antenna system affect the image quality, the main object is to minimize the motion of the gimbal angles during the satellite's imaging phase. For this goal, parameter optimization problems in the imaging and maneuver phases are formulated separately in the body-frame, and solved sequentially. Also, several mechanical constraints, such as the limitation of the gimbal angle and rate, are considered in the problems. The tracking profiles of the gimbal angles in the maneuver phases are designed with N-th order polynomials, to continuously connect the tracking profiles between two imaging phases. The results confirm that if the vector trace of the desired antenna-pointing vector is within the antenna's beam-width angle, motions of the gimbal angles are not required in the corresponding imaging phase. Also, through numerical examples, it is shown that motion of the gimbal angles in the imaging phase can be minimized by the proposed design process.

• Laser Solutions
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• v.10 no.1
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• pp.11-17
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• 2007

We presented the proper laser processing conditions for the capillary line marking, which could be applied for the fabrication of injection needles. With changing the parameters such as lamp current, duty cycle and beam amplification factor of beam expander, we evaluated the processing performance considering amount of dross, processing efficiency and processed linewidth in the sample. We could carry out the proper line marking at the condition of 70% lamp current, duty cycle of 7-10% and 6-times amplification of beam diameter. To perform efficient line processing, the utilization of duty cycle of 12% at 80% lamp current was also preferred.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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• pp.109-122
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• 2023

In this study, we consider the application of the bifocusing method (BFM) for identifying the locations and shapes of small anomalies from scattering parameter data when the exact values of background permittivity and conductivity are unknown. To this end, an imaging function using numerical focusing operator is introduced and its mathematical structure is revealed by establishing a relationship with an infinite series of Bessel functions, antenna arrangements, and anomaly properties. On the basis of the revealed structure, we demonstrate why inaccurate location and size of anomalies were retrieved via the BFM. Some simulation results are illustrated using synthetic data polluted by random noise to support the theoretical result.

• The Journal of the Acoustical Society of Korea
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• v.9 no.2
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• pp.73-81
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• 1990

• Korean Journal of Optics and Photonics
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• v.4 no.1
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• pp.28-35
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• 1993

In the case of an imaging system affected by aberrations which are not precisely known, the effect of aberrations can be minimized and near-diffraction-limited images can be restored by introducing artificial random phase fluctuations in the exit pupil of the imaging system and using bispectral speckle imaging. In order to determine the optimum value of the correlation length for Gaussian random phase model, computer simulation is performed for 50 image frames of a point object in the presence of defocus, spherical aberration, coma, astigmatism of 1 wave, respectively. In terms of the criterion of performance, the FWHM of the point spread function, normalized peak intensity, MTF and visual inspection of the restored object are employed. The optimum value for the rms difference $\sigma$ of aberration on the exit pupil in the interval of Fried parameter ${\Upsilon}_0$ is given by 0.27-0.53 wave for spherical aberration, and 0.24-0.36 wave for defocus and astigmatism, respectively. It is found that the bispectral speckle imaging technique does not give good results in the case of coma.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.157-175
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• 2000

A synthetic aperture radar (SAR) system is able to provide all-weather, day-and- night superior imaging capability of the earth surface, and thus is extremely useful in surveillance for both civil and military applications. In this paper, the X-band high resolution spaceborne SAR system design is demonstrated with the key design performance for a given mission and system requirements characterized by the small satellite system. The SAR multi-mode imaging technique is presented with a critical parameter assessment, and the standard mode results are analyzed in terms of the image quality performances. In line with the system requirement X-band SAR payload and ground reception/processing subsystems are designed and the major design results are presented with the key performance characteristics. This small satellite SAR system shows the wide range of imaging capability with high resolution, and proves to be an effective surveillance systems in the light weight, high performance and cost-effective points of view.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.177-183
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• 2011

Hidden Markov random eld(HMRF) is one of the most common model for image segmentation which is an important preprocessing in many imaging devices. The HMRF has unknown hyper-parameters on Markov random field to be estimated in segmenting testing images. However, in practice, due to computational complexity, it is often assumed to be a fixed constant. In this paper, we numerically show that the segmentation results very depending on the fixed hyper-parameter, and, if the parameter is misspecified, they further depend on the choice of the class-labelling algorithm. In contrast, the HMRF with estimated hyper-parameter provides consistent segmentation results regardless of the choice of class labelling and the estimation method. Thus, we recommend practitioners estimate the hyper-parameter even though it is computationally complex.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.2
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• pp.112-120
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• 2016

The nonlinearity parameter is frequently measured as a sensitive indicator in damaged material characterization or tissue harmonic imaging. Several previous studies have employed the plane wave solution, and ignored the effects of beam diffraction when measuring the non-linearity parameter ${\beta}$. This paper presents a multi-Gaussian beam approach to explicitly derive diffraction corrections for fundamental and second harmonics under quasilinear and paraxial approximation. Their effects on the nonlinearity parameter estimation demonstrate complicated dependence of ${\beta}$ on the transmitter-receiver geometries, frequency, and propagation distance. The diffraction effects on the non-linearity parameter estimation are important even in the nearfield region. Experiments are performed to show that improved ${\beta}$ values can be obtained by considering the diffraction effects.