• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.96-110
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• 2017

Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.4
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• pp.257-268
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• 2012

The EFDC model with find grid resolution system connecting the Gyeong-Gi bay and Han River estuary was constructed to study on spring-neap variability of net volume transport at each channel of the Han River estuary. The simulation time of numerical model is 124 days from May to August, 2009 with freshwater discharge at Han, Imjin and Yeseong River. The calibration and verification of model results was confirmed using harmonic components of water level and tidal current. The net volume transport was calculated during 30 days with normal freshwater conditions at Seokmo channel and Yeomha channel around Ganghwado. The ebbing net volume transport of 44% and 56% is drained into Gyeong-Gi bay through Yeomha and Seokmo channel, respectively. The ebbing net volume transport nearby Seodo at Yeomha channel convergence flooding net volume transport at Incheon harbor, and drain (westward direction) through channel of tidal flat between Ganghwado and Yeongjongdo to the Gyeong-Gi bay. The averaged net volume transport during 4 tidal cycles was compared to variation of spring-neap periods of the Yeomha channel. The convergence position is moved up- and down-ward according to spring-neap variability. The movement of the convergence zone is appeared because 1) increasing of discharged rate tidal flat channel between Ganghwado and Yeongjongdo at the spring period, 2) The growth of barotropic forcing with downward direction at the spring tide, and 3) The strength of the baroclinic pressure gradient is greater than spring with mixing processes.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.459-467
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• 2016

LISFLOOD-FP model in which channel flows are resolved separately from the floodplain flows using either a kinematic or diffusive wave approximation has been used to analyze flooding behavior on the lower Mankyung River influenced by backwater. A calibration and validation process was applied using the previous flood events to assess the model performance. Sensitivity analysis was conducted for main calibrated parameters, such as Manning roughness coefficient and downstream boundary condition. Also, we examined the effect of warm-up for the initial conditions. The results show that the computed hydrograph is in good agreement with measured data on the study reach, even though it was a hydrologic kinematic wave model. The sensitive analysis show that the difference between the computed results may be greater depending on the used calibrated parameters and that the sufficient calibration/validation process against various flood events is necessary. If the flood inundation simulation is performed using the validated model, it is expected to be able to contribute about river planning and policy decision-making for flood damage reduction.

• Progress in Medical Physics
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• v.27 no.1
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• pp.37-45
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• 2016

In proton therapy, in vivo proton beam range verification is very important to deliver conformal dose to the target volume and minimize unnecessary dose to normal tissue. For this purpose, a multi-slit prompt-gamma camera module made of 24 scintillation detectors and 24-channel signal processing system is under development. In the present study, we have developed and tested a dual-mode signal processing system, which can operate in the energy calibration mode and the fast data acquisition mode, to process the signals from the 24 scintillation detectors. As a result of performance test, using the energy calibration mode, we were able to perform energy calibration for the 24 scintillation detectors at the same time and determine the discrimination levels for the detector channels. Further, using the fast data acquisition mode, we were able to measure a prompt-gamma distribution induced by a 45 MeV proton beam. The measured prompt gamma distribution was found similar to the proton dose distribution at the distal fall-off region, and the estimated beam range was $17.13{\pm}0.76mm$, which is close to the proton beam range of 16.15 mm measured by an EBT film.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.7
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• pp.449-458
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• 2014

In the context-aware services, localization is an important technical element. Due to the easy to use and low cost, it was widely enabled with RF properties such as RSSI. However, RSSI is known to be not appropriated for indoor localization, because it tends to show big variance in time and is greatly effected with the multipath. This paper proposes a distance estimation process and its constituted methods for indoor localization, by making use of the other WLAN's RF property, CSI(Channel State Information). Firstly we define a comprehensive localization process, and suggest a calibration algorithm of environment factors in the path loss propagation model. Then, by implementing them with a commercial WLAN module, an the proposed process and methods are evaluated in terms of usefulness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.512-515
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• 2010

SIGINT(SIGnal INTelligence) includes several parameters intercepted by measurement and analysis of the RF(Radio frequency) signal from free space. One of the important parameters is frequency information. Expecially, in order to perform instantaneous frequency measurement of Radar and Missile seeker's RF signals, we use dedicated RF modules as a DFD(Digital Frequency Discriminator) to provide frequency information by measurement of the relative phase difference between signals via intended RF delay lines. It must measure and provide realtime based frequency information on short pulsed RF signal up to 100 nSec or less. This document proposes Ultra wideband DFD consisted of a RF input section of Wideband 4 channel RF delay line and correlator, a digital processing section to measure and provide frequency information from I/Q signal, and a frequency calibration section. Also, it will show design suitability based on test results measured under test condition of very short input pulse signals.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.172-172
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• 2023

The use of low-cost IoT sensors for flow measurement in open channels has gained significant attention due to their potential to provide continuous and real-time data at a low cost. However, the accuracy and reliability of these sensors in real-world scenarios are not well understood. This study aims to compare the performance of low-cost IoT sensors in the laboratory and real-world conditions to evaluate their accuracy and reliability. Firstly, a low-cost IoT sensor was integrated with an IoT platform to acquire real-time flow rate data. The IoT sensors were calibrated in the laboratory environment to optimize their accuracy, including different types of low-cost IoT sensors (HC-SR04 ultrasonic sensor & YF-S201 sensor) using an open channel prototype. After calibration, the IoT sensors were then applied to a real-world case study in the Dorim-cheon stream, where they were compared to traditional flow measurement methods to evaluate their accuracy.The results showed that the low-cost IoT sensors provided accurate and reliable flow rate data under laboratory conditions, with an error range of less than 5%. However, when applied to the real-world case study, the accuracy of the IoT sensors decreased, which could be attributed to several factors such as the effects of water turbulence, sensor drift, and environmental factors. Overall, this study highlights the potential of low-cost IoT sensors for flow measurement in open channels and provides insights into their limitations and challenges in real-world scenarios.

• Water Engineering Research
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• v.2 no.2
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• pp.113-121
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• 2001

The objective of this study is to develop a prediction mode for a flood forecasting system in the downstream of the Nakdong river basin. Ranging from the gauging station at Jindong to the Nakdong estuary barrage, the hydraulic flood routing model(DWOPER) based on the Saint Venant equation was calibrated by comparing the calculated river stage with the observed river stages using four different flood events recorded. The upstream boundary condition was specified by the measured river stage data at Jindong station and the downstream boundary condition was given according to the tide level data observed at he Nakdong estuary barrage. The lateral inflow from tributaries were estimated by the rainfall-runoff model. In the calibration process, the optimum roughness coefficients for proper functions of channel reach and discharge were determined by minimizing the sum of the differences between the observed and the computed stage. In addition, the forecasting lead time on the basis of each gauging station was determined by a numerical simulation technique. Also, we suggested a model structure for a real-time flood forecasting system and tested it on the basis of past flood events. The testing results of the developed system showed close agreement between the forecasted and observed stages. Therefore, it is expected that the flood forecasting system we developed can improve the accuracy of flood forecasting on the Nakdong river.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.106-116
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• 2012

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.