• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.491-498
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• 2012

Recently, many papers have been proposed in order to improve the OFDM system performance in T-DMB DOCR (Digital On Channel Repeater), by using removing the feedback signal so that the transmitter power can be increased or by using the equalizer to remove ICI. Despite these efforts, however, signal quality at the receiving terminal has not been improved because of constellation smearing in T-DMB DOCR. In this paper, in order to suppress constellation smearing, we propose an effective equalizer algorithm that can improve system performance. We perform adaptive channel estimation and non-coherent decision directed noise cancellation method that can estimate the channel subsequently during data symbols period in the frequency domain. So we can obtain better quality of the signal at the receiving terminal. In order to secure QoS(Quality of Service) required in T-DMB handsets, we evaluate SNR and BER in T-DMB DOCR(Digital On Channel Repeater) and verified by simulation. In this simulation results, this system is satisfied the performance of BER=$10^{-5}$ at less than SNR=14 dB at the receiver after compensation of phase noise -18 dBc.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.3
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• pp.60-66
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• 2012

This paper aims to constitute a feedback vibration control system using wireless sensor networks and experiment it on a model structure to verify its effectiveness. For the purpose, we set up a feedback vibration control system composed of a wireless input/output(I/O) sensor node based on bluetooth, a home-made shear type MR damper, a shaker which generates a constant size of sine wave, and a simple beam model structure. The vibration control experiment was performed by shaking the 1/4 point of beam with a shaker. At the moment of shaking, we controled the vibration with MR damper which was placed vertically on the center of beam. Simultaneously, by acquiring acceleration response at the 2/4 point of beam, we evaluated the effectiveness of control capability. The control command was set to send a voltage signal to MR damper when the acceleration response, acquired from the wireless I/O sensor node placed at the center of beam, was more than a certain amount. Although the realtime feedback vibration control system constituted in this paper is effective only within a limited command system, it has been proven that the system was able to effectively decrease the vibration of structure by generating a control command aimed for realtime purpose. The system also showed a possibility to be used as a structural response control system adapting a variety of semi-active control algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.166-174
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• 2013

QRS detection of ECG is the most popular and easy way to detect cardiac-disease. But it is difficult to analyze the ECG signal because of various noise types. The important problem in recording ECG signal is a baseline wandering, which is occurred by rhythm of respiration and muscle contraction attaching to an electrode. Particularly, in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, baseline wander removing method based on morphological filter for efficient QRS detection method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. The signal distortion ratio of the proposed method is compared with other filtering method. Also, R wave detection is evaluated by using MIT-BIH arrhythmia database. Experiment result show that proposed method removes baseline wanders effectively without significant morphological distortion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4021-4030
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• 2015

Pulse wave is the physiological responses through the autonomic nervous system such as ECG. It is relatively convenient because it can measure the signal just by applying a sensor on a finger. So, it can be usefully employed in the field of U-Healthcare. The objects of this study are acquiring the PPG (Photoplethysmography) one of the way of measuring the pulse waves in non-invasive way using the CMOS image sensor on a smartphone camera, developing the portable system judging stressful or not, and confirming the applicability in the field of u-Healthcare. PPG was acquired by using image data from smartphone camera without separate sensors and analyzed. Also, with that image signal data, HRV (Heart Rate Variability) and stress index were offered users by just using smartphone without separate host equipment. In addition, the reliability and accuracy of acquired data were improved by developing additional hardware device. From these experiments, we can confirm that measuring heart rate through the PPG, and the stress index for analysis the stress degree using the image of a smartphone camera are possible. In this study, we used a smartphone camera, not commercialized product or standardized sensor, so it has low resolution than those of using commercialized external sensor. However, despite this disadvantage, it can be usefully employed as the u-Healthcare device because it can obtain the promising data by developing additional external device for improvement reliability of result and optimization algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.359-364
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• 2011

The study uses department of the sensitivity and fuzzy reasoning, one of artificial intelligence algorithms, so that develop LED lighting system based on fuzzy reasoning for systematical control of the LED color temperature. In the area of sensitivity engineering, by considering the relation between color and emotion expressed as an adjective word, the corresponding sensitivity word can be determined, By taking into consideration the relation between the brain wave measured from the human brain and the color temperature, the preferred lesson subject can be determined. From the decision of the sensitivity word and the lesson subject, we adjust the color temperature of RGB (Red, Green, Blue) LED. In addition, by using the information of the latitude and the longitude from GPS(Global Positioning System), we can calculate the on-line moving altitude of sun. By using the sensor information of both temperature and humidity, we can calculate the discomfort index. By considering the altitude of sun as well as the value of the discomfort index, the illumination of W(white) LED and the color temperature of RGB LED can be determined. The (LED) sensitivity lighting control system is bulit up by considering the sensitivity word, the lesson subject, the altitude of sun, and the discomfort index The developed sensitivity lighting control system leads to more suitable atmosphere and also the enhancement of the efficiency of lesson subjects as well as business affairs.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.141-146
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• 2019

Economic analysis predicts that the drone market will grow, and the growth of the toy and hobby drone market is expected to gradually expand. Drone expectations are rising due to the net economic function of drone market growth, but accidents due to improper management and operations are also increasing. The difference in toy drone performance is incomparably small compared to industrial drone performance, but the ordinary buyer can not know whether the difference can cause an accident during use. The toy drones used in this study were obtained from KC and CE certification, and 20 kinds of drones were used. The flight time ranged from a minimum of 3 minutes to a maximum of 12 minutes, and the control distance ranged from a minimum of 20m to a maximum of 380m. Therefore, it is necessary to secure product safety through sampling inspection of the radio wave output of toy drones, and it is also necessary to mount an algorithm that automatically lowers the altitude or hover when exceeding the limit flight distance. For future research, we will build data to establish toy drone safety standards through a altitude testing and impact testing of toy drone.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.89-97
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• 2021

Fault detection in seismic data is well suited to the application of machine learning algorithms. Accordingly, various machine learning techniques are being developed. In recent studies, machine learning models, which utilize synthetic data, are the particular focus when training with deep learning. The use of synthetic training data has many advantages; Securing massive data for training becomes easy and generating exact fault labels is possible with the help of synthetic training data. To interpret real data with the model trained by synthetic data, the synthetic data used for training should be geologically realistic. In this study, we introduce a method to generate realistic synthetic seismic data. Initially, reflectivity models are generated to include realistic fault structures, and then, a one-way wave equation is applied to efficiently generate seismic stack sections. Next, a migration algorithm is used to remove diffraction artifacts and random noise is added to mimic actual field data. A convolutional neural network model based on the U-Net structure is used to verify the generated synthetic data set. From the results of the experiment, we confirm that realistic synthetic data effectively creates a deep learning model that can be applied to field data.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.52-67
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• 2020

Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.

• Explosives and Blasting
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• v.39 no.2
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• pp.1-14
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• 2021

Recently, with the development of high-performance processing devices such as GPGPU, a three-dimensional dynamic analysis technique that can replace expensive rock material impact tests has been actively developed in the defense and aerospace fields. Experimentally observing or measuring fracture processes occurring in rocks subjected to high impact loads, such as blasting and earth penetration of small-diameter missiles, are difficult due to the inhomogeneity and opacity of rock materials. In this study, a three-dimensional dynamic fracture process analysis technique (3D-DFPA) was developed to simulate the fracture behavior of rocks due to impact. In order to improve the operation speed, an algorithm capable of GPGPU operation was developed for explicit analysis and contact element search. To verify the proposed dynamic fracture process analysis technique, the dynamic fracture toughness tests of the Straight Notched Disk Bending (SNDB) limestone samples were simulated and the propagation of the reflection and transmission of the stress waves at the rock-impact bar interfaces and the fracture process of the rock samples were compared. The dynamic load tests for the SNDB sample applied a Pulse Shape controlled Split Hopkinson presure bar (PS-SHPB) that can control the waveform of the incident stress wave, the stress state, and the fracture process of the rock models were analyzed with experimental results.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.