• Journal of Digital Convergence
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• v.15 no.2
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• pp.173-181
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• 2017

In this paper, we have studied tracking as a training stage of considering the position and the scale of a person given its previous position, scale, as well as next and forward image fraction. Unlike other learning methods, CNN is thereby learning combines both time and spatial features from the image for the two consecutive frames. We introduce multiple path ways in CNN to better fuse local and global information. A creative shift-variant CNN architecture is designed so as to alleviate the drift problem when the distracting objects are similar to the target in cluttered environment. Furthermore, we employ CNNs to estimate the scale through the accurate localization of some key points. These techniques are object-independent so that the proposed method can be applied to track other types of object. The capability of the tracker of handling complex situations is demonstrated in many testing sequences. The accuracy of the SVM classifier using the features learnt by the CNN is equivalent to the accuracy of the CNN. This fact confirms the importance of automatically optimized features. However, the computation time for the classification of a person using the convolutional neural network classifier is less than approximately 1/40 of the SVM computation time, regardless of the type of the used features.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.571-586
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• 2014

Moderate Resolution Imaging Spectroradiometer (MODIS) provides air temperature (Tair) and dew point temperature (Tdew) profiles at a spatial resolution of 5 km. New Collection 6 (C006) MODIS07_L2 atmospheric profile product has been produced since 2012. The Collection 6 algorithm has several modifications from the previous Collection 5 (C005) algorithm. This study evaluated reliabilities of two alternative datasets of surface-level Tair and Tdew derived from C005 and C006 Aqua MODIS07_L2 (MYD07_L2) products using ground measured temperatures from 77 National Weather Stations (NWS). Saturated and actual vapor pressures were calculated using MYD07_L2 Tair and Tdew. The C006 Tair showed lower mean error (ME, -0.76 K) and root mean square error (RMSE, 3.34 K) than the C005 Tair (ME = -1.89 K, RMSE = 4.06 K). In contrasts, ME and RMSE of C006 Tdew were higher than those (ME = -0.39 K, RMSE = 5.65 K) of C005 product. Application of ambient lapse rate for Tair showed appreciable improvements of estimation accuracy for both of C005 and C006, though this modification slightly increased errors in C006 Tdew. The C006 products provided better estimation of vapor pressure datasets than the C005-derived vapor pressure. Our results indicate that, except for Tdew, C006 MYD07_L2 product showed better reliability for the region of South Korea than the C005 products.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.79-89
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• 2005

Groundwater level changes in coastal aquifers occur due to oceanic tides, where the properties of oceanic tides can be applied to estimate hyadraulic parameters. Hydraulic parameters of coastal aquifers located in eastern part of Jeju island were estimated using the tidal response technique. Groundwater level data from a saltwater intrusion monitoring well system was used which showed tidal effects from 3 to 5 km. The hydraulic gradient was assessed by utilizing the filtering method from 71 consecutive hourly water-level observations. Calculated hydraulic diffusivity ranged from 2.94${\times}10^7m^2d^{-1}$ to 4.36${\times}10^7m^2d^{-1}$ . The hydraulic gradient of the coastal aquifer area was found to be ~$10^{-4}$, whereas the gradient of the area between wells Handong-1 and 2 was found to be ~$10^{-6}$, which is very low comparatively. Analysis of groundwater monitoring data showed that groundwater levels are periodically higher near coastal areas compared to that of inner land areas due to oceanic tide influences. When assessing groundwater flow direction in coastal aquifers it is important to consider tidal fluctuation.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Convergence Security Journal
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• v.21 no.1
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• pp.191-200
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• 2021

Artificial intelligence technology is developing in an environment where a lot of data is produced due to the development of computing technology, a cloud environment that can store data, and the spread of personal mobile phones. Among these artificial intelligence technologies, the deep neural network provides excellent performance in image recognition and image classification. There have been many studies on image detection for forest fires and fire prevention using such a deep neural network, but studies on detection of cigarette smoking were insufficient. Meanwhile, military units are establishing surveillance systems for various facilities through CCTV, and it is necessary to detect smoking near ammunition stores or non-smoking areas to prevent fires and explosions. In this paper, by reflecting experimentally optimized numerical values such as activation function and learning rate, we did the detection of smoking pictures and non-smoking pictures in two cases. As experimental data, data was constructed by crawling using pictures of smoking and non-smoking published on the Internet, and a machine learning library was used. As a result of the experiment, when the learning rate is 0.004 and the optimization algorithm Adam is used, it can be seen that the accuracy of 93% and F1-score of 94% are obtained.

• Journal of Food Hygiene and Safety
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• v.6 no.1
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• pp.1-12
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• 1991

Fischer 344 rats aged six weeks were diYided into four groups and group 1, 2, and 3 of rats were given an intraperitoneal injection of diethylnitrosamine at 200 mg/kg body weight and group 4 was given saline alone. Two weeks after beginning of the experiment, group 1 and 2 of rats were begun to feed on diets containing 0.02% 2-acetylaminofluorene as a promoter for four weeks. Three weeks after beginning of the experiment, all groups were performed partial hepatectomy. During the last two weeks, group 1 and 3 of rats were received subcutaneously 3 consecutive weekly doses of iron dextran at 0.125 ml/100 g body weight. Subcutaneous injection of iron dextran resulted in hepatic siderosis in group 1 and 3 of rats. Pre neoplastic nodules were identified histopathologically by two markers, resistance to exogenous iron accumulation and glutathione S-transeferase placental form (GST-P) activity, while early carcinogen induced foci were hardly resistant to iron accumulation and though a few lesions were identified, it could hardly be distincted from normal hepatocytes of surroundings. However, GST-P positive nodules as well as foci were clearly distincted from normal hepatic cells of surroundings. In the quantitative analysis of carcinogen-induced nodules and foci, more lesions were detected by immunohistochemical method for GST-P than by prussian blue staining for resistant to iron accumulation. It is concluded that immunohistochemical marker for GST-P is more sensitive and reliable than iron-resistance marker, and that iron-resistance is not useful marker for early detection of carcinogen-induced hepatic lesions.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.329-352
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• 2005

Long term observations of full-disk Lyman-o irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the $Lyman-{\alpha}$ irradiance. Previous full disk $Lyman-{\alpha}$ images of the sun have been very interesting and useful scientifically, but have been only five-minute 'snapshots' obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-o intensity. The $Lyman-{\alpha}$ Imaging Solar Telescope(LIST) can provide a unique opportunity for the study of the sun in the $Lyman-{\alpha}$ region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project And these can be utilized to build a high resolution photometric detectors for military and commercial purposes. It is also believed that we will be able to apply several acquired techniques for the development of the Korean satellite projects in the future.

• Pediatric Infection and Vaccine
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• v.16 no.2
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• pp.131-141
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• 2009

Purpose : In February 2007, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) skin and soft tissue infections occurred in two newborns in the neonatal unit of Sahmyook Seoul Hospital. We performed this study to investigate the characteristics of MRSA nasal carriage among neonatal unit staffs and the effective infection control measures. Methods : Nasal swab specimens were obtained from the neonatal unit staff for the presence of MRSA. MRSA-colonized staffs were offered decolonization therapy with oral trimethoprim-sulfamethoxazole or 2% mupirocin ointment. Every 2-4months after decolonizaton, repeat nasal swab specimens were obtained. Also, samples from the neonatal unit environment and room air were collected. Results : Successful decolonization was achieved in 92% of the cases in 2 weeks after decolonization therapy, but most of the staffs were recolonized after several months. The nature of antibiotic susceptibility was changed from multi-drugsusceptible to multi-drug-resistant. The most frequently contaminated objects were dressing carts, computer keyboards, bassinets and washbowls. In environmental cultures using the settle microbe count method, the colony counts were decreased significantly at the last study period compared with the first study period in the neonatal room, breastfeeding room, service room, and dressing room (P <0.05). Conclusion : Effective control of sustained MRSA transmission within an institution may require prompt identification, treatment, and monitoring of colonized and/or infected staffs. However, nasal decolonization therapy may induce multi-drugresistant MRSA infection and had no effect on decreasing the MRSA nasal carriage rate in our study. Other factors might be more important, such as improving staff education, increasing hand hygiene practices, and environmental sterilization for controlling MRSA infections.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.