• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.407-418
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• 2018

The frequency and risk of disasters are increasing due to environmental and social factors. In order to respond effectively to disasters that occur unexpectedly, it is very important to quickly obtain up-to-date information about target area. It is possible to intuitively judge the situation about the area through the image-map generated at high speed, so that it can cope with disaster quickly and effectively. In this study, we propose an image-map generation and visualization system from UAV images for real-time disaster monitoring. The proposed system consists of aerial segment and ground segment. In the aerial segment, the UAV system acquires the sensory data from digital camera and GPS/IMU sensor. Communication module transmits it to the ground server in real time. In the ground segment, the transmitted sensor data are processed to generate image-maps and the image-maps are visualized on the geo-portal. We conducted experiment to check the accuracy of the image-map using the system. Check points were obtained through ground survey in the data acquisition area. When calculating the difference between adjacent image maps, the relative accuracy was 1.58 m. We confirmed the absolute accuracy of the image map for the position measured from the individual image map. It is confirmed that the map is matched to the existing map with an absolute accuracy of 0.75 m. We confirmed the processing time of each step until the visualization of the image-map. When the image-map was generated with GSD 10 cm, it took 1.67 seconds to visualize. It is expected that the proposed system can be applied to real - time monitoring for disaster response.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.47-53
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• 2004

The paper shows that the combination of the hardware, NI PCI 6110E board and the software, Fourier and continuous wavelet transform(CWT) can be used to implement for extracting the important features of the real-time signal. The results confirmed that CWT produces the fast computation enough for the application of the real-time signal processing except the negligible time delay. In denoising case, because of the lack of translation invariance of wavelet basis, traditional wavelet thresholding leads to pseudo-Gibbs phenomena in the vicinity of discontinuities of signal. In this paper, in order to reduce the pseudo-Gibbs phenomena, wavelet coefficients are threshold and reconstruction algorithm is implement through shift-invariant gibbs free denoising algorithm based on wavelet transform footprint. The proposed algorithm can potentially be extended to more general signals like piecewise smooth signals and represents an effective solution to problems like signal denoising.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.137-144
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• 2019

Testing maturity is critical to the system under development with lack of experience and skills in the acquisition of the weapon systems. Defects have a huge impact on important system operations. Sharing real-time information will lead to rapid command and mission capability in submarine. DDS(Data Distribution System) is a very important information sharing system and interface between various manufacturers or data formats. In this paper, we analyze data distribution characteristics of distributed data system to group data-specific systems and proposes a test case-generation method using path search of postorder and preorder which is a tree traversal in path testing method. The proposed method reduces 73.7.% testing resource compare to existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.877-889
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• 2006

This paper introduces a simple but effective method for recognizing vehicle models corresponding to each maker by information and images for moving vehicles. The proposed approach is implemented by combination of the breadth detection mechanism using the vehicle's pressure, exact height detection by a laser scanning, and license plate recognition for classifying specific vehicles. The implemented system is therefore capable of robust classification with real-time vehicle's moving images and established sensors. Simulation results using the proposed method on synthetic data as well as real world images demonstrate that proposed method can maintain an excellent recognition rate for moving vehicle models because of image acquisition by 2-D CCD and various image processing algorithms.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.61-76
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• 2018

Everything is coming into the world of network where modern people are living. The Internet of Things that attach sensors to objects allows real-time data transfer to and from the network. Mobile devices, essential for modern humans, play an important role in keeping all traces of everyday life in real time. Through the social network services, information acquisition activities and communication activities are left in a huge network in real time. From the business point of view, customer needs analysis begins with SNS data. In this research, we want to build an automatic collection system of SNS contents of web environment in real time using Python. We want to help customers' needs analysis through the typical data collection system of Instagram, Twitter, and YouTube, which has a large number of users worldwide. It is stored in database through the exploitation process and NLP process by using the virtual web browser in the Python web server environment. According to the results of this study, we want to conduct service through the site, the desired data is automatically collected by the search function and the netizen's response can be confirmed in real time. Through time series data analysis. Also, since the search was performed within 5 seconds of the execution result, the advantage of the proposed algorithm is confirmed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.341-349
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• 2003

A real time interactive controller (spectrometer) for magnetic resonance imaging (MRI) system has been developed using high speed digital signal processors (DSP). The controller generates radio frequency (rf) waveforms and audio frequency gradient waveforms and controls multiple receivers for data acquisition. By employing DSPs having high computational power (e.g., TMS320C670l) real time generation of complicated gradient waveforms and interactive control of selection planes are possible, which are important features in real-time imaging of moving organs, e.g., cardiac imaging. The spectrometer was successfully implemented at a 1.5 Tesla whole body MRI system for clinical application. Performance of the spectrometer is verified by various experiments including high- speed imaging such as fast spin echo (FSE) and echo planar imaging (EPI). These high-speed imaging techniques reduce measurement time, however, usually intensify artifact if there is any systematic phase error or jitter in the synchronization between the transmitter, receiver, and gradients.

• Transactions on Electrical and Electronic Materials
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• v.14 no.2
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• pp.71-77
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• 2013

Advanced semiconductor manufacturing technology requires methods to maximize tool efficiency and improve product quality by reducing process variability. Real-time plasma process monitoring and diagnosis have become crucial for fault detection and classification (FDC) and advanced process control (APC). Additional sensors may increase the accuracy of detection of process anomalies, and optical monitoring methods are non-invasive. In this paper, we propose the use of a chromatic data acquisition system for real-time in-situ plasma process monitoring called the Plasma Eyes Chromatic System (PECS). The proposed system was initially tested in a six-inch research tool, and it was then further evaluated for its potential to detect process anomalies in an eight-inch production tool for etching blanket oxide films. Chromatic representation of the PECS output shows a clear correlation with small changes in process parameters, such as RF power, pressure, and gas flow. We also present how the PECS may be adapted as an in-situ plasma arc detector. The proposed system can provide useful indications of a faulty process in a timely and non-invasive manner for successful run-to-run (R2R) control and FDC.

• Journal of Yeungnam Medical Science
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• v.18 no.1
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• pp.39-50
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• 2001

Background: Power spectrum analysis method is a powerful noninvasive tool for quantifying autonomic nervous system activity. In this paper, we developed a data acquistion system for estimating the activity of the autonomic nervous system by the analysis of heart rate and respiratory rate variability using power spectrum analysis. Materials and methods: For the detection of QRS peak and measurement of respiratory rate from patient's ECG, we used low-pass filter and impedence method respectively. This system adopt an isolated power for patient's safety. In this system, two output signals can be obtained: R-R interval heart rate) and respiration rate time series. Experimental ranges are 30-240 BPM for ECG and 15-80 BPM for respiration. Results: The system can acquire two signals accurately both in the experimental test using simulator and in real clinical setting. Conclusion: The system developed in this paper is efficient for the acquisition of heart rate and respiration signals. This system will play a role in research area for improving our understanding of the pathophysiologic involvement of the autonomic nervous system in various disease states.

• Journal of the Korean earth science society
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• v.34 no.6
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• pp.588-601
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• 2013

In geophysics and geophysical exploration fields, we can use information about inclination and azimuth in various ways. These include borehole deviation logging for inversion process, real-time data acquisition system, geophysical monitoring system, and so on. This type of information is also necessarily used in the directional drilling of shale gas fields. We thus need to develop a subminiature, low-powered, multi-functional inclination and azimuth measurement system for geophysical exploration fields. In this paper, to develop real-time measurement system, we adopt the high performance low power Micro Control Unit (made with state-of-the-art Complementary Metal Oxide Semiconductor technology) and newly released Micro Electro Mechanical Systems Attitude Heading Reference System sensors. We present test results on the development of a multifunctional real-time inclination and azimuth measurement system. The developed system has an ultra-slim body so as to be installed in 42mm sonde. Also, this system allows us to acquire data in real-time and to easily expand its application by synchronizing with a depth encoder or Differential Global Positioning System.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.4
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• pp.428-432
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• 2014

Rotating machines are an integral part of large electrical power machinery in most of the industries. Any degradation or outages in the rotating electric machinery can result in significant losses in productivity. It is critical to monitor the equipment for any degradation's so that it can serve as an early warning for adequate maintenance activities and repair. Prior research and field studies have indicated that the rotating machines have a particular type of signal structure during the initial start-up transient. A machine performance can be studied based on the effect of degradation in signal parameters. In this paper a data-acquisition system and the FFT algorithm has been design and model using the MATLAB and Simulink. The implementation had been carried out on the TMS320 DSP Processor and various testing and verification of the machine performance had been carried out. The results show good agreement with expected results for both simulated and real-time data. The real-time data from AC water pumps which have rotating motors built-in were collected and analysed. The FFT algorithm provides frequency response and based on this frequency response performance of the machine had been measured.The FFT algorithm provides only approximation about the machine performances.