• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.213-221
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• 2007

This paper showed how to analysis the object-based classification for wildfire fuel type map using Hyperion hyperspectral remote sensing data acquired in April, 2002 and compared the results of the object-based classification with the results of the pixel-based classification. Our methodological approach for wildfire fuel type map firstly processed correcting abnormal pixels and atypical bands and also calibrating atmospheric noise for enhanced image quality. Fuel type map is characterized by the results of the spectral mixture analysis(SMA). Object-based approach was based on segment-based endmember selection, while pixel-based method used standard SMA. To validate and compare, we used true-color high resolution orthoimagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.229-235
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• 2011

Traffic noise pollution is a growing problem that highly affects the health of people in urban areas. In order to implement effective measures against traffic noise the noise mapping about its distribution is imperative. Urban traffic noise maps will help to establish the existing baseline so that we will be able to look for the effective way to control the noise. They will also let us see in an understandable and visual way how noise spreads from roads into residential areas. In this paper we considered three development types between roads and residential areas, and applied the interpolation of ArcGIS for noise attenuation with distance from the roads to find the noise level at the parcels positions in residential areas, and then generated the noise map using the interpolated results. Therefore we present results that the traffic noise level within residential areas exceed the national noise standard and also can estimate the noise level of individual parcels. These results can be used for traffic noise control planning or assessment of officially assessed land price in near future.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.709-712
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• 1987

In this paper, a mathematical model for the purpose of QRS detection is considered in the case of the occurrence of nonoverlapping pulse-shaped waveforms corrupted with white noise. The number of waveforms, the arrival times, amplitudes, and widths of QRS complexes are regarded as random variables. The joint MAP estimation of all the unknown quantities consists of linear filtering followed by an optimization procedure. Because of time-consuming, the optimization procedure is modified so that a threshold test is obtained. The model formulation with nonoverlapping waveforms leads to a standard procedure covering a segment before as well as after an accepted event. Adaptivity of the detector is gained by utilizing past signal properties in determining threshold for QRS detection.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.642-649
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• 2012

This paper deals with a copper die casting induction motor which has several advantages of motor performance. The developed motor is used as spindle motor in machining center. The dynamic characteristic analysis of rotor is dealt with for precision machining. The critical speed of rotor considering rotation and gyroscopic effect should be above operating speed, 18,000 rpm, and have a 201 % sufficient separation margin. Also, the 3-D unbalance vibration response analysis is performed and enabled the prediction of the expected vibration amplitude by unbalance in high speed. The unbalance vibration responses of each position on the rotor are satisfied with allowable vibration displacement of API 611 standard according to balancing G grade(G 0.4, G 2.5, G 6.3). Copper die casting high speed induction motor is successfully developed and verified by experiment.

• Progress in Medical Physics
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• v.10 no.3
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• pp.125-131
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• 1999

T$_1$/T$_2$ weighted images are being used to give the characteristic contrast among the various tissues and the norma;/abnormal tissues. Abnormalities in tissues, in general, accompany the biochemical changes and eventually structural ones in which results in the change in T$_1$ and T$_2$ relaxation times of water protons. It has been suggested that the mapping of T$_1$/T$_2$ values may serve as a possible tool for the quantitative evaluation of the degree of abnormality. On reconstructing T$_1$/T$_2$ maps(or any other MR parametric map), only corresponding variables are to be varied, such as TE for T$_2$, TI or TR for T$_1$ and b-factor for diffusion images. But often the receiver gain is taken for the optimal usage of A/D converter, so that the set of the image data has different receiver gain. It must be corrected before any attempt to reconstruct the maps. Here we developed method of correcting receiver gain variation effect, using the standard deviation of noise on individual image. The resultant T$_1$ and T$_2$ values were very comparable to the other reported values.

• ETRI Journal
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• v.36 no.5
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• pp.752-760
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• 2014

This paper proposes a conditional replenishment algorithm (CRA) to improve the visual quality (where spatial resolutions of the left and right views are mismatched) of a hybrid stereoscopic 3DTV that is based on the ATSC-M/H standard. So as to generate an enhanced view, the CRA is to choose the better substitute among a disparity-compensated view with high quality and a simply interpolated view. The CRA generates a disparity map that includes modes and disparity vectors as additional information. It also employs a quad-tree structure with variable block size by considering the spatial correlation of disparity vectors. In addition, it takes advantage of the disparity map used in a previous frame to keep the amount of additional information as small as possible. The simulation results show that the proposed CRA can successfully improve the peak signal-to-noise ratio of a poor-quality view and consequently have a positive effect on the subjective quality of the resulting 3D view.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3121-3143
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• 2019

Segmentation plays an important role in the field of image processing and computer vision. Intuitionistic fuzzy C-means (IFCM) clustering algorithm emerged as an effective technique for image segmentation in recent years. However, standard fuzzy C-means (FCM) and IFCM algorithms are sensitive to noise and initial cluster centers, and they ignore the spatial relationship of pixels. In view of these shortcomings, an improved algorithm based on IFCM is proposed in this paper. Firstly, we propose a modified non-membership function to generate intuitionistic fuzzy set and a method of determining initial clustering centers based on grayscale features, they highlight the effect of uncertainty in intuitionistic fuzzy set and improve the robustness to noise. Secondly, an improved nonlinear kernel function is proposed to map data into kernel space to measure the distance between data and the cluster centers more accurately. Thirdly, the local spatial-gray information measure is introduced, which considers membership degree, gray features and spatial position information at the same time. Finally, we propose a new measure of intuitionistic fuzzy entropy, it takes into account fuzziness and intuition of intuitionistic fuzzy set. The experimental results show that compared with other IFCM based algorithms, the proposed algorithm has better segmentation and clustering performance.

• Journal of KSNVE
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• v.7 no.3
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• pp.439-447
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• 1997

In this study, the dynamic instabilities of a nonlinear elastic system subjected to follower forces are investigated. The two-degree-of-freedom double pendulum model with nonlinear geometry, cubic spring, and linear viscous damping is used for the study. The constant, the initial impact forces acting at the end of the model are considered. The chaotic nature of the system is identified using the standard methods, such as time histories, power density spectrum, and Poincare maps. The responses are chaotic and unpredictable due to the sensitivity to initial conditions. The sensitivities to parameters, such as geometric initial imperfections, magnitude of follower force, direction control constant, and viscous damping, etc., are analysed. Dynamic buckling loads are computed for various parameters, where the loads are changed drastically for the small change of parameters.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.5
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• pp.11-20
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• 2002

Based on regularization principles, we propose a new dequantization scheme on DCT-based transform coding for reducing of blocking artifacts and minimizing the quantization error. The conventional image dequantization is simply to multiply the received quantized DCT coefficients by the quantization matrix. Therefore, for each DCT coefficients, we premise that the quantization noise is as large as half quantizer step size (in DCT domain). Our approach is based on basic constraint that quantization error is bounded to ${\pm}$(quantizer spacing/2) and at least there are not high frequency components corresponding to discontinuities across block boundaries of the images. Through regularization, our proposed dequantization scheme, sharply reduces blocking artifacts in decoded images. Our proposed algorithm guarantees that the dequantization process will map the quantized DCT coefficients will be evaluated against the standard JPEG, MPEG-1 and H.263 (with Annex J deblocking filter) decoding process. The experimental results will show visual improvements as well as numerical improvements in terms of the peak-signal-to-noise ratio (PSNR) and the blockiness measure (BM) to be defined.