• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.31-39
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• 2009

Purpose : This study proposes the keyhole method in order to improve the time resolution of the proton resonance frequency(PRF) MR temperature monitoring technique. The values of Root Mean Square (RMS) error of measured temperature value and Signal-to-Noise Ratio(SNR) obtained from the keyhole and full phase encoded temperature images were compared. Materials and Methods : The PRF method combined with GRE sequence was used to get MR temperature images using a clinical 1.5T MR scanner. It was conducted on the tissue-mimic 2% agarose gel phantom and swine's hock tissue. A MR compatible coaxial slot antenna driven by microwave power generator at 2.45GHz was used to heat the object in the magnetic bore for 5 minutes followed by a sequential acquisition of MR raw data during 10 minutes of cooling period. The acquired raw data were transferred to PC after then the keyhole images were reconstructed by taking the central part of K-space data with 128, 64, 32 and 16 phase encoding lines while the remaining peripheral parts were taken from the 1st reference raw data. The RMS errors were compared with the 256 full encoded self-reference temperature image while the SNR values were compared with the zero filling images. Results : As phase encoding number at the center part on the keyhole temperature images decreased to 128, 64, 32 and 16, the RMS errors of the measured temperature increased to 0.538, 0.712, 0.768 and 0.845$^{\circ}C$, meanwhile SNR values were maintained as the phase encoding number of keyhole part is reduced. Conclusion : This study shows that the keyhole technique is successfully applied to temperature monitoring procedure to increases the temporal resolution by standardizing the matrix size, thus maintained the SNR values. In future, it is expected to implement the MR real time thermal imaging using keyhole method which is able to reduce the scan time with minimal thermal variations.

• Particle and aerosol research
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• v.13 no.3
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• pp.105-110
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• 2017

Real-time measurements of fine particles from stack emission gases are necessary due to the needs of continuous environmental monitoring of PM10 and PM2.5. The porous tube dilutor using hot and cold dilutions was developed to measure fine particles without condensable particles from highly humid emission gases and compared to the commercialized ejector-type dilutor. Particle size distributions were measured at the emission gases from a diesel engine and a coal-fired boiler. The porous tube dilutor could successfully measure the accumulation mode particles including relatively large particles more than $3{\mu}m$ without nuclei particles, while the ejector dilutor detected some condensable particles and could not detect large particles. The porous tube dilutor could successfully remove the already condensed water droplet particles generated by a humidifier in a $30m^3$ chamber.

• Korean Journal of Food Science and Technology
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• v.49 no.2
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• pp.123-131
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• 2017

Norovirus causes frequent epidemic viral gastroenteritis in Korea. The team for the control of noroviral foodborne outbreaks (NOROTECL) executed a project to trace the cause of norovirus contamination in agricultural products and environmental samples to reduce norovirus outbreaks in Korea. Between January and November in 2015, the contaminations by norovirus and indicator microorganisms such as coliforms, Escherichia coil and male specific coliphage (MSC) were examined in 80 agricultural products, 80 soil samples, 78 human feces samples, 3 animal feces samples, 80 agricultural water samples and 80 river water samples. Semi-nested PCR and DNA sequencing revealed 18 genogroup I and 3 genogroup II noroviruses in a total of 18 samples. These noroviruses were validated by real-time (RT)-PCR analysis. For indicator microorganisms, coliform and E. coli were respectively detected in agricultural products (68, 1%), soils (88, 7%), human feces (44, 12.8%), animal feces (67, 67%), agricultural waters (74, 30%) and river waters (96, 51%). The MSC results revealed 14 positive samples.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.527-534
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• 2017

The purpose of this study is to develop unmanned equipment that can automatically move to the desired point and measure water quality at the correct depth. For this purpose, we constructed a water sampling lift and water sampling container, an unmanned vessel equipped with a VRS-GPS, an acoustic echo sounder, and a water quality sensor. Also, we developed an automatic navigation algorithm and program, an automatic water sampling program, and a water quality map generation program. As a result of the experiment in the detention pond, the unmanned vessel sailed along the planned route with an accuracy of about 93% within the error range of 3m. In addition, the water quality sensor installed in the lift was able to acquire the water quality of the target area in real time and transmit it to the server via wireless Internet, and it was possible to monitor the water quality of each site in real time. Through field experiments, the water sampling lift was able to control the desired length with an accuracy of about 94%. The stretch length accuracy experiment of the water sampling lift was impossible to measure directly in the water, so it was replaced land-based experiment. We also found some unstable problems due to the weight of the water sampling lift and the weight of the air compressor to operate the water container. Except these two problems, we accomplished purpose of this study. An automated water quality measurement method using an unmanned vessel can be used to measure the quality of water in a difficult to access area and to secure the safety of the worker.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3135-3140
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• 2010

A 5 kWh composite flywheel rotor was designed and manufactured, and its spin test was performed to monitor strain distribution and burst speed. Strain distribution in radial and circumferential directions of the rotor were measured using a wireless telemetry system based on bluetooth technology for real-time strain measurement. The strains was compared with pre-calculated design values to verify the initial rotor design. We noticed the rotor failed at 19,499 rpm in the spin test, 11 % lower than the predicted burst speed of 22,000 rpm. Failure occurred at the hub which connects the shaft and the composite rotor. The performance of the composite rotor was confirmed in a general sense, and the danger of unexpected failure of composite rotor during high-speed spinning was also demonstrated in this paper. Special attention should be paid to not only composite rotor but also hub when designing a flywheel energy storage system. The telemetry system needs to be further developed, especially enduring the high centrifugal forces, and can be used in a real time monitoring system for the flywheel energy storage system.

• Journal of the Korean Vacuum Society
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• v.16 no.2
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• pp.145-152
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• 2007

The evolution dynamics of nanoscale Ge islands on both Si (001) and (113) surfaces is explored using ultraviolet photoelectron emission microscopy (UV-PEEM). Real-time monitoring of the in-situ growth of the Ge island structures can allow us to study the variation of the size, the shape and the density of the nanostructures. For Ge depositions greater than ${\sim}4$ monolayer (ML) with a growth rate of ${\sim}0.4\;ML/min$ at temperatures of $450-550^{\circ}C$, we observed island nucleation on both surfaces indicating the transition from strained layer to island structure. During continuous deposition the circular islands grew larger via ripening processes. AFM measurements showed that the islands grown on Si (001) were dome-shaped while the islands on Si (113) were multiple-side faceted with flat tops of (113)-orientation. In contrast, for Ge deposition with a lower growth rate of ${\sim}0.15\;ML/min$ on Si(113), we observed the shape transition from circular into elongated island structures. The elongated islands grew longer along the [$33\bar{2}$] during continuous Ge deposition. The shape evolution of the islands is discussed in terms of strain relaxation and kinetic effects.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.9-17
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• 2013

Geospatial information data came recently in use to build the location-based service in various fields. These data were shown via a 2-D map in the past but now can be viewed as a 3-D map due to the dramatic evolution of IT technology, thus improving efficiency and raising practicality to a greater extent by providing a more realistic visualization of the field. In addition, many previous GIS applications have been provided under desktop environment, limiting access from remote sites and reducing its approachability for less experienced users. The latest trend offers service with web-based environment, providing efficient sharing of data to all users, both unknown and specific internal users. Therefore, real-time information sensors that have been installed on steep slopes are to be integrated with 3-D geospatial information in this study. It is also to be developed with web-based environment to improve usage and access. There are three steps taken to establish this system: firstly, a 3-D GIS database and 3-D terrain with higher resolution aerial photos and DEM (Digital Elevation Model) have been built; secondly, a system architecture was proposed to integrate real-time sensor information data with 3D Web-based GIS; thirdly, the system has been constructed for Gangwon Province as a test bed to verify the applicability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.886-895
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• 2005

As the networked media technology have been grown in recent, there have been many research works to deliver high-quality video such as HDV and HDTV over the Internet. To realize high-quality media service over the Internet, however, the network adaptive streaming scheme is required to adopt to the dynamic fluctuation of underlying networks. In this paper, we design and implement the network-adaptive HD(high definition) MPEG-2 streaming system employing the frame-based prioritized packetization. Delivered video is inputted from the JVC HDV camera to the streaming sewer in real-time. It has a bit-rate of 19.2 Mbps and is multiplexed to the MPEG-2 TS (MPEG-2 MP@HL). For the monitoring of network status, the packet loss rate and the average jitter are measured by using parsing of RTP packet header in the streaming client and they are sent to the streaming server periodically The network adaptation manager in the streaming server estimates the current network status from feedback packets and adaptively adjusts the sending rate by frame dropping. For this, we propose the real-time parsing and the frame-based prioritized packetization of the TS packet. The proposed system is implemented in software and evaluated over the LAN testbed. The experimental results show that the proposed system can enhance the end-to-end QoS of HD video streaming over the best-effort network.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.159-166
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• 2016

In this paper, an active object tracking system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-embedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18% on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.