• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.95-105
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• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.779-784
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• 2008

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3E
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• pp.126-131
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• 2002

Ultrasonic measurements are made in egg white to study the properties of the solution of the natural protein. The high-Q ultrasonic resonator method is used to get the ultrasonic absorption spectra over the range 0.2-10 ㎒ at 20℃. It is proportional to the 1.25th power of the frequency. The gelation process caused by heat is studied from the change in the velocity and the absorption. at 3 ㎒ using the pulse echo overlap technique over the range of 10-80℃. The absorption decreases with increasing temperature up to 60℃ where it turns up sharply and rapidly increases thereafter. The strong absorption in the gel region is described by the interaction between the solution and the network structure made of protein. Very slow variation in time elapse is observed after the temperature is quickly raised. It would be a real-time observation of the network building process and the characteristic time for the process is shown to be 400 min. A hysteresis phenomenon with respect to the temperature is observed. This phenomenon is associated with the memorizing effect of the network structure of protein of the gel.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.485-494
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• 2005

It is very important to analyze the correlation between discharge and water quality. The observation of discharge and water quality are effective at same point as well as same time for real time management. But no less significant is the fact that there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. In this case, it need to observe accurate discharge data, and to develop forecasting program or system using real time data. In this paper, discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and compared with discharge using WMS(Watershed Modeling System) model. WMS shows better results when peak discharge is small and hydrograph is smooth. Forecasted discharge of neural network model have achieved the highest overall accuracy of specific discharge and WMS. Neural network model forecast change of discharge well on unrecored station.

• Journal of Astronomy and Space Sciences
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• v.27 no.2
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• pp.107-116
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• 2010

We developed the playback control software for a high-speed playback system which is a component of the Korea-Japan Joint VLBI Correlator (KJJVC). The Mark5B system, which is a recorder and playback system used in the Korean VLBI Network (KVN), has two kinds of operation mode. That is to say, the station unit (SU) mode, which is for the present Mark4 system, and the VSI mode, which is for the new VLBI standard interface (VSI) system. The software for SU is already developed and widely used in the Mark4 type VLBI system, but the software for VSI has only been developed for recording. The new VLBI system is designed with a VSI interface for compatibility between different systems. Therefore, the playback control software development of the VSI mode is needed for KVN. In this work, we developed the playback control software of the Mark5B VSI mode. The developed playback control software consists of an application part for data playing back, a data input/output part for the VSI board, a module for the StreamStor RAID board, and a user interface part, including an observation time control part. To verify the performance of developed playback control software, the playback and correlation experiments were performed using the real observation data in Mark5B system and KJJVC. To check the observation time control, the data playback experiment was performed between the Mark5B and Raw VLBI Data Buffer (RVDB) systems. Through the experimental results, we confirmed the performance of developed playback control software in the Mark5B VSI mode.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.280-288
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• 2009

In this paper, we developed new time information recording module of VSI (VLBI Standard Interface) format by analyzing the Mark5B recorder control and operation software with 1Gbps speed, which is able to record the weak signal of space radio source, through the Korean VLBI Network (KVN). The control and operation software of high-speed recorder consists of 2 kinds of software, which is that it can operate RAID control board by controlling large capacity HDD drive and the network control and operation. Especially, core software in high-speed recorder is able to output the results after performing and analyzing the input command. Through the analysis of control and operation software, new time information recording module, which is needed to process the observed data for correlation, is developed. New developed time information recording module can record the time information together after checking the interrupt of 1PPS(Pulse Per Second) input signal when the observed data will be recorded. To verify the normal operation of the developed time information recording module, we performed the real observation test and confirmed the effectiveness of developed software through analyzing the recorded observation data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.654-659
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• 2018

In this study, continuous long-term observation is implemented with an ocean radar. Ocean radar conducts remote observation (combined) with ground-based radars, which enable a series of simultaneous observations of an extensive range of the coast with high frequency. An ocean radar for continuous long-term observation is operated at Samcheok on the east coast of Korea. Samcheok experienced tsunami damage in recent years and is the location of a nuclear power plant. In order to examine the reliability of the ocean radar, a pressure-type wave gauge, ultrasonic wave gauge, and ocean buoy are installed for the purpose of data comparison and verification. The ocean radar used in this study is an array-type HF-RADAR named WERA (WavE RAdar). The analysis of the data obtained from continuous long-term observations showed that the radar observations were in agreement with more than 90% of the wave data collected within a 25 km range from the center of two sites. Less than 1% of the entire observation data was unmeasured by the time series analysis. As a result of comparing the radar data with the direct observations made by the wave gauge, it was inferred that the RMS deviation is less than 20cm and the correlation coefficient was in the range of 0.84 ~ 0.87. Moreover, supported by such observations, a comprehensive monitoring system is being developed to provide the public with real-time reports on waves and currents via the internet.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1184-1188
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• 2005

The impacts of turbidity flow induced by summer rainfall events on water supply, aquatic ecosystems, and socioeconomics are significant and major concerns in most of reservoirs operations. As a decision support tool, the real-time turbidity flow monitoring and modeling system RTMMS is under development using a laterally integrated two-dimensional (2D) hydrodynamic and water quality model. The objectives of this paper is to present the preliminary field observation results on the characteristics of rainfall-induced turbidity flows and their density flow regimes, and the model performance in replicating the fate and transport of turbidity plume in a reservoir. The rainfall-induced turbidity flows caused significant drop of river water temperature by 5 to $10^{\circ}C$ and resulted in density differences of 1.2 to $2.6kg/m^3$ between inflow water and ambient reservoir water, which consequently led development of density flows such as plunge flow and interflow in the reservoir. The 2D model was set up for the reservoir. and applied to simulate the temperature stratification, density flow regimes, and temporal and spatial turbidity distributions during flood season of 2004 After intensive refinements on grid resolutions , the model showed efficient and satisfactory performance in simulating the observed reservoir thermal stratification and turbidity profiles that all are essentially required to enhance the performance of RTMMS.