• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.7
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• pp.41-47
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• 2014

The on-line partial discharge (PD) in stator windings of air-cooled gas turbine (GT) generator (119.2MVA, 13.8kV) is measured and analyzed in this paper. This generator was designed by global vacuum pressure impregnation (VPI). The generator failed two times at top bar (16T) of phase B in the stator slot. Six epoxy-mica capacitors were installed in three phases of GT generator. On-line PD test was performed on GT generator using turbine generator analyzer (TGA). TGA showed that the normalized quantity number (NQN) and the PD magnitude($Q_m$) were high in phase B. Internal discharges were generated in phases A, B and C. The trend analysis of NQN and $Q_m$ value are obtained in order to monitor the insulation condition in GT generator stator windings. Phases A and C were in good condition. But phase B had deteriorated significantly

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.655-655
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• 2002

Spatial distribution of phytoplankton pigment concentration (PPC) and sea surface temperature (SST) around the East Korean Warm Current (EKWC) was described, using both ocean color images and advanced very high resolution radiometer (AVHRR) images. Water mass in this region can be classified into five categories in the horizontal profile of PPC and SST, nLw(normalized water-leaving radiance) images: (1) coastal cold water region associated with concentrations of dissolved organic material or yellow colored substances and suspended sediments, (2) cold water region of thermal frontal occurred by a combination of phytoplankton absorption and suspended materials, (3) warm water overlay region by the phytoplankton absorption than the suspended materials; (4) warm water region occurred by the low phytoplankton absorption, and (5) offshore region occurred by the high phytoplankton absorption. In particular, the highest PPC area appeared in the ocean color and SST images with a band shaped distribution of the thermal front and ocean color front region, which is located the coastal cold waters along western thermal front of the warm streamer of the EKWC.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.965-967
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• 2003

Information on forest volume, forest coverage and biomass are important for developing global perspectives about CO$_{2}$ concentration changes. Forest biomass cannot be directly measured from space yet, but remotely sensed greenness can be used to estimate biomass on decadal and longer time scales in regions of distinct seasonality, as in the north. Hence, in this research, numerical methods were used to estimate forest biomass in higher northern regions. A regression model linking Normalized Difference Vegetation Index(NDVI), to forest biomass extracted from SPOT/4 VEGETATION data and PAL 8km data in regional and continental area (N40-N70) respectively. Statistical tests indicated that the regression model can be used to represent the changes of forest biomass carbon pools and sinks at high latitude regions over years 1982-2000. This study suggests that the implementation of estimation of biomass based on 8-km resolution NOAA/AVHRR PAL and SPOT-4/VEGETATION data could be detected over a range of land cover change processes of interest for global biomass change studies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.493-504
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• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.486-491
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• 2008

The spray characteristics and drop size measurements have been experimentally studied in liquid jets injected into subsonic crossflow. With water as fuel injection velocity, injection angle and atomizer internal flows were varied to provide of jet operation conditions. The injector internal flow was classified as three modes such as a non-cavitation flow, cavitation, and hydraulic flip flows. Pulsed Shadowgraph Photography measurement was used to determine the spatial distribution of the spray droplet diameter in a subsonic crossflow of air. And this study also obtains the SMD(Sauter Mean Diameters) distribution by using PLLIF(Planar Liquid Laser Induced Fluorescence) technique. The objectives of this research are getting a droplet distribution and drop size measurement of each condition and compare with the other flows effect. As the result, This research have been showed the droplet size were spatially dependent on air-stream velocity, fuel injection velocity, injection angle effects and normalized distance from the injector exit length.(x/d, y/d)There are also different droplet size characteristics between cavitation, hydraulic flip and the non-cavitation flows.

• Progress in Superconductivity
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• v.3 no.1
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• pp.36-40
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• 2001

We have studied vortex dynamics in$ Bi_2$$Sr_2$$CaCu_2$O$_{8}$single crystals of unirradiated and irradiated samples by using 100 $\times$ $100\mu\textrm{m}^2$Hall sensor. Doses equivalent magnetic fields are 20 G, 100 G and 1 kG. In the magnetization measurement, a second magnetization peak (SMP) was observed in unirradiated, 20 G dose and 100 G dose samples in contrast to 1 kG dose sample. In the unirradiated sample, the SMP was observed in the range of 18 K ~ 35 K and the amplitude of the SMP decreased with increasing temperature. With increase of the irradiation dose, temperature region and sharpness of the SMP were reduced. In the magnetic relaxation measurement, we observed that the normalized relaxation rate S decreased with increasing the irradiation dose. Our results suggest that the vortex dynamics is not greatly affected by low-density columnar defects.s.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2057-2062
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• 2024

Among photon counting detector (PCD)-based technologies, the K-edge subtraction (KES) method has a very high material decomposition efficiency. Yet, since the increase in noise in the X-ray image to which the KES method is applied is inevitable, research on image quality improvement is essential. Here, we modeled a block-matching and 3D filtering (BM3D) algorithm and applied it to PCD-based X-ray images with the improved KES (IKES) method. For PCD modeling, Monte Carlo simulation was used, and a phantom composed of iodine substances with different concentrations was designed. The IKES method was modeled by adding a log term to KES, and the X-ray image used for subtraction was obtained by applying the 3.0 keV range based on the K-edge region of iodine. As a result, the IKES image using the BM3D algorithm showed the lowest normalized noise power spectrum value. In addition, we confirmed that the contrast-to-noise ratio and no-reference-based evaluation results when the BM3D algorithm was applied to the IKES image were improved by 29.36 % and 20.56 %, respectively, compared to the noisy image. In conclusion, we demonstrated that the IKES imaging technique using a PCD-based detector and the BM3D algorithm fusion technique were very efficient for X-ray imaging.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.29-42
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• 2016

Remote sensing allows acquisition of information across a large area without contacting objects, and has thus been rapidly developed by application to different areas. Thus, with the development of remote sensing, satellites are able to rapidly advance in terms of their image resolution. As a result, satellites that use remote sensing have been applied to conduct research across many areas of the world. However, while research on remote sensing is being implemented across various areas, research on data processing is presently insufficient; that is, as satellite resources are further developed, data processing continues to lag behind. Accordingly, this paper discusses plans to maximize the performance of satellite image processing by utilizing the CUDA(Compute Unified Device Architecture) Library of NVIDIA, a parallel processing technique. The discussion in this paper proceeds as follows. First, standard KOMPSAT(Korea Multi-Purpose Satellite) images of various sizes are subdivided into five types. NDVI(Normalized Difference Vegetation Index) is implemented to the subdivided images. Next, ArcMap and the two techniques, each based on CPU or GPU, are used to implement NDVI. The histograms of each image are then compared after each implementation to analyze the different processing speeds when using CPU and GPU. The results indicate that both the CPU version and GPU version images are equal with the ArcMap images, and after the histogram comparison, the NDVI code was correctly implemented. In terms of the processing speed, GPU showed 5 times faster results than CPU. Accordingly, this research shows that a parallel processing technique using CUDA Library can enhance the data processing speed of satellites images, and that this data processing benefits from multiple advanced remote sensing techniques as compared to a simple pixel computation like NDVI.

• Radiation Oncology Journal
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• v.17 no.2
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• pp.136-140
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• 1999

Purpose : Prostate specific antigen (PSA) is a useful tumor marker, which is widely used as a diagnostic index and predictor of both treatment and follow-up result in prostate cancer. A prospective analysis was carried out to obtain the period of PSA normalization and the half life of PSA and to analyze the factors influencing the period of PSA normalization. The PSA level was checked before and serially after radical radiotherapy. Materials and Method : Twen쇼 patients with clinically localized prostate cancer who underwent radical external beam radiotherapy were enrolled in this study. Accrual period was from April 1993 to May 1998. Median follow-up period was 20 months. Radiotherapy was given to whole pelvis followed by a boost to prostate. Dose range for the whole pelvis was from 45 Gy to 50 Gy and boost dose to prostate, from 14 Gy to 20 Gy. The post-irradiation PSA normal value was under 3.0 ng/ml. The physical examination and serum PSA level evaluation were performed at 3 month interval in the first one year, and then at every 4 to 6 months. Results : PSA value was normalized in nineteen patients (95%) within 12 months. The mean period of PSA normalization was 5.3 (${\pm}$2.7) months. The half life of PSA Of the nonfailing patients was 2.1 (${\pm}$0.9) month. The nadir PSA level Of the nonfailing Patients waS 0.8 (${\pm}$0.5) ng/ml. The period of PSA normalization had the positive correlation with pretreatment PSA level (R$^{2}$=0.468). The nadir PSA level had no definite positive correlation with the pretreatment PSA level (R$^{2}$=0.075). The half life of serum PSA level also had no definite correlation with pretreatment PSA level (R$^{2}$=0.029). Conclusion :The PSA level was mostly normalized within 8 months (85%). If it has not normalized within 12 months, we should consider the residual disease in prostate or distant metastasis. In 2 patients, the PSA level increased 6 months or 20 months before clinical disease was detected. So the serum PSA level can be used as early diagnostic indicator of treatment failure.