• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.4 no.3
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• pp.170-179
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• 1999

The SUS (Signal, Underwater Sound)-OAT experiment was carried out in the Ulleung Basin of the East Sea on 3 June 1997. The SUS-OAT system consisted of aircraft deployed shots as sources and a vertical line array (VLA) tethered by a receiver ship was used to survey a large area where a mesoscale warm eddy appears frequently. The experiment was carried out such that explosive charges set to detonate at 800 ft depth were dropped in a rectangular ($120{\times}120$ km). Sources were a rapidly deployable SUS charge (MK 61 MOD 0), and receiver is a fixed VLA, 90 m in length (150-240 m in receiver depth), composed of 10 elements equally spaced. The reference ray paths are computed by range-dependent acoustic model in canonical ocean based on the historical data. The singular value decomposition (SVD) method is used to obtain the horizontal perturbation of the temperature fields. Horizontal distributions of temperature fields at 150 m and 200 m depth show a weak warm eddy observed by AXBT and the inversely estimated temperature shows similar patterns in terms of the location of the warm eddy. In conclusion, the SUS-OAT experiment has been successful to estimate the position of warm eddy and its temperature field in the East Sea of Korea.

• Journal of radiological science and technology
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• v.39 no.3
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• pp.369-376
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• 2016

Positron Emission Tomography(PET) is nuclear medical tests which is a combination of several compounds with a radioactive isotope that can be injected into body to quantitatively measure the metabolic rate (in the body). Especially, Phenomena that increase (sing) glucose metabolism in cancer tissue using the $^{18}F$-FDG (Fluorodeoxyglucose) is utilized widely in cancer diagnosis. And then, Numerous studies have been reported that incidence seems high availability even in the modern diagnosis of dementia and Parkinson's (disease) in brain disease. When using a dynamic PET iamge including the time information in the static information that is provided for the diagnosis many can increase the accuracy of diagnosis. For this reason, clinical researchers getting great attention but, it is the lack of tools to conduct research. And, it interfered complex mathematical algorithm and programming skills for activation of research. In this study, in order to easy to use and enable research dPET, we developed the software based graphic user interface(GUI). In the future, by many clinical researcher using DIA-Tool is expected to be of great help to dPET research.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.177-185
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• 2019

Ground roll is a surface wave which is usually observed in the land seismic data. It is one of the typical coherent noise. During the reflection data processing, ground roll is removed because it is considered as noise. This removal process often causes the loss of reflection signals if the ground roll overlaps reflection signals. In this study, we look over Karhunen-Loeve Transform (KLT) and analyze its effects to suppress the ground roll appropriately while reducing the reflection loss. Numerical tests in homogeneous elastic media show that the ground roll has been properly rejected. However, the field data application reveals that there is no significant suppression of ground roll when compared to band-pass filtering. This can be considered that it is hard to calculate horizontally aligned gathers in the field data because the ground roll contains a wide range of frequency bands. On the contrary, the result of singular value decomposition (SVD) filtering shows that the ground roll has been significantly reduced. It is thought that the SVD filtering performs better in the ground roll suppression than KLT because it is easy to calculate the horizontally aligned gathers in the SVD filtering.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.5
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• pp.227-234
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• 2018

Researches regarding measurement and control of the dynamic behavior of liquid such as sloshing have been actively on undertaken in various engineering fields. Liquid vibration is being measured in the study of tuned liquid dampers(TLDs), which attenuates wind motion of buildings even in building structures. To overcome the limitations of existing wave height measurement sensors, a method of measuring liquid vibration in a TLD using a laser Doppler vibrometer(LDV) and galvanometer scanner is proposed in this paper: the principle of measuring speed and displacement is discussed; a system of multi-point measurement with a single point of LDV according to the operating principles of the galvanometer scanner is established. 4-point liquid vibration on the TLD is measured, and the time domain data of each point is compared with the conventional video sensing data. It was confirmed that the waveform is transformed into the traveling wave and the standing wave. In addition, the data with measurement delay are cross-correlated to perform singular value decomposition. The natural frequencies and mode shapes are compared using theoretical and video sensing results.

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.203-209
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• 2006

The aim of this study is to investigate the feasibility of ex vivo MR diffusion tensor imaging technique in order to observe the diffusion-contrast characteristics of human gastric tissues. On normal and pathologic gastric tissues, which have been fixed in a polycarbonate plastic tube filled with 10% formalin solution, laboratory made 3D diffusion tensor Turbo FLASH pulse sequence was used to obtain high resolution MR images with voxel size of $0.5{\times}0.5{\times}0.5mm^3\;using\;64{\times}32{\times}32mm^3$ field of view in conjunction with an acquisition matrix of $128{\times}64{\times}64$. Diffusion weighted- gradient pulses were employed with b values of 0 and $600s/mm^2$ in 6 orientations. The sequence was implemented on a clinical 3.0-T MRI scanner(Siemens, Erlangen, Germany) with a home-made quadrature-typed birdcage Tx/Rx rf coil for small specimen. Diffusion tensor values in each pixel were calculated using linear algebra and singular value decomposition(SVD) algorithm. Apparent diffusion coefficient(ADC) and fractional anisotropy(FA) map were also obtained from diffusion tensor data to compare pixel intensities between normal and abnormal gastric tissues. The processing software was developed by authors using Visual C++(Microsoft, WA, U.S.A.) and mathematical/statistical library of GNUwin32(Free Software Foundation). This study shows that 3D diffusion tensor Turbo FLASH sequence is useful to resolve fine micro-structures of gastric tissue and both ADC and FA values in normal gastric tissue are higher than those in abnormal tissue. Authors expect that this study also represents another possibility of gastric carcinoma detection by visualizing diffusion characteristics of proton spins in the gastric tissues.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1109-1119
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• 2009

WLAN(Wireless Local Area Network) standard is currently developing with increased wireless internet demand. Though existing IEEE 802.11e demonstrates that data rates exceed 54Mbps with assuring QoS(Quality of Service), wireless internet users can't be satisfied with real communication system. After IEEE 802.11e system, Study trends of IEEE 802.11n show two aspects, enhanced system throughput using aggregation among packets in MAC (Medium Access Control) layer, and better data rates adapting MIMO(Multiple-Input Multiple-Output) in PHY(Physical) layer. But, no one demonstrates IEEE 802.11n system performance results considering MAC and PHY connection. Therefore, this paper adapts MIMO in PHY layer for IEEE 802.11n system based on A-MPDU(Aggregation-MAC Protocol Data Unit) method in MAC layer considering MAC and PHY connection. SVD(Singular Value Decomposition) method with WLAN MIMO TGn Channel is used to analyze MIMO. Consequently, Simulation results show enhanced throughput and data rates compared to existing system. Also, We use Ns-2(Network Simulator-2) considering MAC and PHY connection for reality.

• Journal of Platform Technology
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• v.9 no.3
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• pp.52-62
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• 2021

Quality control is critical at manufacturing sites and is key to predicting the risk of quality defect before manufacturing. However, the reliability of manual quality control methods is affected by human and physical limitations because manufacturing processes vary across industries. These limitations become particularly obvious in domain areas with numerous manufacturing processes, such as the manufacture of major nuclear equipment. This study proposed a novel method for predicting the risk of quality defects by using natural language processing and machine learning. In this study, production data collected over 6 years at a factory that manufactures main equipment that is installed in nuclear power plants were used. In the preprocessing stage of text data, a mapping method was applied to the word dictionary so that domain knowledge could be appropriately reflected, and a hybrid algorithm, which combined n-gram, Term Frequency-Inverse Document Frequency, and Singular Value Decomposition, was constructed for sentence vectorization. Next, in the experiment to classify the risky processes resulting in poor quality, k-fold cross-validation was applied to categorize cases from Unigram to cumulative Trigram. Furthermore, for achieving objective experimental results, Naive Bayes and Support Vector Machine were used as classification algorithms and the maximum accuracy and F1-score of 0.7685 and 0.8641, respectively, were achieved. Thus, the proposed method is effective. The performance of the proposed method were compared and with votes of field engineers, and the results revealed that the proposed method outperformed field engineers. Thus, the method can be implemented for quality control at manufacturing sites.