• Korean Journal of Applied Biomechanics
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• v.18 no.2
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• pp.59-64
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• 2008

D. W. KANG, J. S. CHOI, and G. R. TACK, A Study on Real-Time Sports Activity Classification & Monitoring Using a Tri-axial Accelerometer. Korean Jouranl of Sport Biomechanics, Vol. 18, No. 2, pp. 59-64, 2008. This study was conducted to study the real-time sports activity classification and monitoring using single waist mounted tri-axial accelerometer. This monitoring system detects events of sports activities such as walking, running, cycling, transitions between movements, resting and emergency event of falls. Accelerometer module was developed small and easily attachable on waist using wireless communication system which does not constrain sports activities. The sensor signal was transferred to PC and each movement pattern was classified using the developed algorithm in real-time environment. To evaluate proposed algorithm, experiment was performed with several sports activities such as walking, running, cycling movement for 100sec each and falls, transition movements(sit to stand, lie to stand, stand to sit, lie to sit, stand to lie and sit to lie) for 20 times each with 5 healthy subjects. The results showed that successful detection rate of the system for all activities was 95.4%. In this study, through sports activity monitoring. it was possible to classify accurate sports activities and to notify emergency event such as falls. For further study, the accurate energy consumption algorithm for each sports activity is under development.

• Composites Research
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• v.18 no.4
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• pp.1-7
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• 2005

In-situ structural health monitoring of filament wound pressure tanks were conducted during water-pressurizing test using embedded fiber Bragg grating (FBG) sensors. We need to monitor inner strains during working in order to verify the health condition of pressure tanks more accurately because finite element analyses on filament wound pressure tanks usually show large differences between inner and outer strains. Fiber optic sensors, especially FBG sensors can be easily embedded into the composite structures contrary to conventional electric strain gages (ESGs). In addition, many FBG sensors can be multiplexed in single optical fiber using wavelength division multiplexing (WDM) techniques. We fabricated a standard testing and evaluation bottle (STEB) with embedded FBG sensors and performed a water-pressurizing test. In order to increase the survivability of embedded FBG sensors, we suggested a revised fabrication process for embedding FBG sensors into a filament wound pressure tank, which includes a new protecting technique of sensor heads, the grating parts. From the experimental results, it was demonstrated that FBG sensors can be successfully adapted to filament wound pressure tanks for their structural health monitoring by embedding.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.127-136
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• 2009

This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.681-688
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• 2005

This study investigates an existing steel plate girder railroad bridge after superstructure rehabilitation to monitor static and dynamic responses using Fiber Bragg Grating (FBG) sensors. This paper also presents an experimental technique to estimate the vertical deflection of the bridge using FBG sensors. Seven FBG sensors are multiplexed in a single optical fiber and installed in parallel pairs along the length of the bridge, with one set at the top flange and the other at the bottom flange. In addition to FBG sensors, a conventional electric strain gauge and anLVDT are installed at the mid-span of the bridge for comparison. A test train consisting of one locomotive is placed at the center of the bridge to produce the maximum static effect. The train is also made to pass over the bridge at different speeds ranging from 10 km/h to 90 km/h to monitor the dynamic response of the bridge. This study demonstrates that the measured strains using the FBG sensor compared well with the readings from the electric strain gauge. The results show that the proposed instrumentation technique is capable of estimating the vertical deflection of the bridge for various loading conditions, which is crucial in structural health monitoring. Several dynamic characteristics of the bridge were also identified.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.47-59
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• 2014

Volcanic ash (VA) can be estimated by remote sensing sensors through their spectral signatures determined by the inherent optical property (IOP) including complex refractive index and the scattering properties. Until now, a very limited range of VA refractive indices has been reported and the VA from each volcanic eruption has a different composition. To improve the robustness of VA remote sensing, there is a need to understanding of VA - radiation interactions. In this study, we calculated extinction coefficient, scattering phase function, asymmetry factor, and single scattering albedo which show different values between andesite and pumice. Then, IOPs were used to analyze the relationship between theoretical remote sensed radiation calculated by radiative transfer model under various aerosol optical thickness (${\tau}$) and sun-sensor geometries and characteristics of VA. It was found that the mean rate of change of radiance at top of atmosphere versus ${\tau}$ is six times larger than in radiance values at 0.55 ${\mu}m$. At the surface, positive correlation dominates when ${\tau}$ <1, but negative correlation dominates when ${\tau}$ >1. However, radiance differences between andesite and pumice at 11 ${\mu}m$ are very small. These differences between two VA types are expressed as the polynomial regression functions and that increase as VA optical thickness increases. Finally, these results would allow VA to be better characterized by remote sensing sensors.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.316-322
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• 2009

This paper presents a preliminary study to monitor the lateral behavior of pile foundation using multiplexed fiber Bragg grating(FBG) sensors. In the Preliminary study, an 1.7 meter long cantilever beam with the shape of square hollow box was fabricated and tested under the static loading. Four FBG sensors were multiplexed in a single optical fiber and installed into the top and bottom of the cantilever beam. The strains are directly measured from FBG sensors followed by curvature calculations based on the plane section assumption. Vertical deflections are then estimated using the regression analyses based on the geometric relationships. It has been found that excellent correlation with conventional sensing system was observed. The success of the test encourages the use of the FBG sensing system as a monitoring system for pile foundations. However, further consideration should be given in the case of the sensor malfunction for the practical purpose.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.260-260
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• 2013

Multiferroic materials have attracted much attention due to their fascinating fundamental physical properties and technological applications in magnetic/ferroelectric data-storage systems, quantum electromagnets, spintronics, and sensor devices. Among single-phase multiferroic materials, $BiFeO_3 $ is a typical multiferroic material with a room temperature magnetoelectric coupling in view of high magnetic-and ferroelectric-ordering temperatures (Neel temperature $T_N$~647 K and Curie temperature $T_C$~1,103 K). Rare-earth ion substitution at the Bi sties is very interesting, which induces suppressed volatility of Bi ion and improved ferroelectric properties. At the same time, Fe-site substitution with magnetic ions is also attracting, and the enhanced ferromagnetism was reported. In this study, $Bi_{1-x}Dy_xFe_{0.95}Co_{0.05}O_3$ (x=0, 0.05 and 0.1) bulk ceramic compounds were prepared by solid-state reaction and rapid sintering. High-purity $Bi_2O_3$, $Dy_2O_3$, $Fe_2O_3$ and $Co_3O_4$ powders with the stoichiometric proportions were mixed, and calcined at $500^{\circ}C$ or 24 h to produce $Bi_{1-x}Dy_xFe_{0.95}Co_{0.05}O_3$. The samples were immediately put into an oven, which was heated up to $800^{\circ}C$ nd sintered in air for 30 min. The crystalline structure of samples was investigated at room temperature by using a Rigaku Miniflex powder diffractometer. The field-dependent magnetization measurements were performed with a vibrating-sample magnetometer. The electric polarization was measured at room temperature by using a standard ferroelectric tester (RT66B, Radiant Technologies).

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.64-69
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• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.149-158
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• 2017

Fine temporal and spatial resolution of image data are necessary to monitor the phenology of vegetation. However, there is no single sensor provides fine temporal and spatial resolution. For solve this limitation, researches on spatiotemporal data fusion methods are being conducted. Among them, FSDAF (Flexible spatiotemporal data fusion) can fuse each band in high accuracy.In thisstudy, we applied MODIS NDVI and Landsat NDVI to enhance time resolution of NDVI based on FSDAF algorithm. Then we proposed the possibility of utilization in vegetation phenology monitoring. As a result of FSDAF method, the predicted NDVI from January to December well reflect the seasonal characteristics of broadleaf forest, evergreen forest and farmland. The RMSE values between predicted NDVI and actual NDVI (Landsat NDVI) of August and October were 0.049 and 0.085, and the correlation coefficients were 0.765 and 0.642 respectively. Spatiotemporal data fusion method is a pixel-based fusion technique that can be applied to variousspatial resolution images, and expected to be applied to various vegetation-related studies.