• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.57-61
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• 2014

This study measured the stream data from the several sensors, and stores the database in MapReduce framework environment, and it aims to design system with the small performance and cluster analysis error rate through the KMSVM algorithm. Through the KM-SVM algorithm, the cluster analysis effective data was used for U-health system. In the results of experiment by using 2003 data sets obtained from 52 test subjects, the k-NN algorithm showed 79.29% cluster analysis accuracy, K-means algorithm showed 87.15 cluster analysis accuracy, and SVM algorithm showed 83.72%, KM-SVM showed 90.72%. As a result, the process speed and cluster analysis effective ratio of KM-SVM algorithm was better.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.970-976
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• 2004

In this paper, we analyze channel estimation algorithms in a RAKE receiver with MRC. There are 3 popular channel estimation algorithms, which are WMSA(Weighted Multi-Slot Averaging) algorithm, EGE(Equal Gain Estimation) algorithm, SSE(Symbol-to-Symbol Estimation) algorithm. We analyze asynchronous IMT-2000(3GPP) which employ 3 different channel estimation algorithms by HP-ADS(Advanced Design System) simulation tool. We used lakes fading channel model for the analysis. from simulation results, we could observe that the performance of WMSA algorithm is better than others in low Doppler effect(3Km/h). However, in the case of high Doppler effect(120km1h), the EGE algorithm is more efficient. In this case the simple estimator with EGE algorithm seems to be more useful.

• Korean Journal of Optics and Photonics
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• v.10 no.5
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• pp.405-412
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• 1999

We propose an effective algorithm, which can predict the detailed behavior of the intensity-modulated high speed optical signal after propagating through an optical fiber. The alogrithm is based on the SSF (Split Step Fourier) Method, however, the step size is automatically calibrated in each calculation step to reduce the number of calculations within given round-off error bound. Applying the algorithm to the 2.5 Gbps 100 km transmission and 10 Gbps 40 km transmission simulations, we achieved the calculation time reduction by maximum 1/120 and 1/56 of the calculation time by using the SSF fixed step algorithm previously known. The root-mean-square of the round-off error was kept within -30 dB compared to the signal level throughout the calculation.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.1-8
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• 2012

Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 33 participants(15 males and 18 females) that performed walking and running on treadmill at 2 ~ 11 km/h speeds(each stage increase 1km/h). Algorithm for energy expenditure of physical activities were implemented with $VO_2$ consumption and SVM correlation between the data. Algorithm consists of three kinds and hip, wrist, waist and hip can be used to apply.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.4
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• pp.163-170
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• 2005

This paper deals with an improved fault location algorithm with compensation ground capacitance through distributed parameter for a long parallel T/L. For the purpose of fault locating algorithm non-influenced by source impedance and fault resistance, the loop method was used in the system modeling analysis. This algorithm uses a positive and negative sequence of the fault current for high accuracy of fault locating calculation. Power system model of 160km and 300km long parallel T/L was simulated using EMTP software. To evaluate of the proposed algorithm, we used the several different cases 64 sampled data per cycle. The test results show that the proposed algorithm was minimized the error factor and speed of fault location estimation.

• Geophysics and Geophysical Exploration
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• v.18 no.1
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• pp.1-8
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• 2015

To estimate the shear-wave velocity (${\nu}_s$ beneath the OTVZ seismic station on Ngauruhoe volcano in New Zealand, we calculated receiver functions (RFs) using 127 teleseismic data ($Mw{\geq}5.5$) with high signal-to-noise ratios recorded during November 11, 2011 to September 11, 2013. The genetic inversion algorithms was applied to 21 RFs calculated by the iterative time-domain deconvolution method. In the 1-D ${\nu}_s$ model derived by the inversion, the Moho is observed at a 14 km depth, marked by a ${\nu}_s$ transition from 3.7 km/s to 4.7 km/s. The average ${\nu}_s$ of the overlying crust is 3.4 km/s, and the average ${\nu}_s$ of a greater than 9-km thick low-velocity layer (LVL) in the lower crust is 3.1 km/s. The LVL becomes thinner with increasing distance from the station. Another LVL thicker than 10 km with ${\nu}_s$ less than 4.3 km/s is found in the upper mantle. Those LVLs in the lower crust and the upper mantle and the relatively thin crust might be related to the magma activity caused by the subducting Pacific plate.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.63-77
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• 2023

This study applies reinforcement learning to effectively operate expressway hard shoulder running (HSR). An HSR algorithm was developed, and its effectiveness was evaluated using the VISSIM microscopic simulation program. The simulation evaluated two aspects: mobility and safety. The DQN-based HSR algorithm found speed improvement of up to 26 km/h. Compared to the current method, the difference in the number of conflicts was not significant. Considering the results, a DQN-based HSR operation has a clear effect, and it is necessary to consider adjusting the current operational criteria.

• Atmosphere
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• v.17 no.2
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• pp.125-133
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• 2007

Cloud amount calculation algorithm was developed using MTSAT-1R satellite data. The cloud amount is retrieved at 5 km ${\times}$ 5 km over the Korean Peninsula and adjacent sea area. The algorithm consists of three steps that are cloud detection, cloud type classification, and cloud amount calculation. At the first step, dynamic thresholds method was applied for detecting cloud pixels. For using objective thresholds in the algorithm, sensitivity test was performed for TBB and Albedo variation with temporal and spatial change. Detected cloud cover was classified into 3 cloud types (low-level cloud, cirrus or uncertain cloud, and cumulonimbus type high-level cloud) in second step. Finally, cloud amount was calculated by the integration method of the steradian angle of each cloud pixel over $3^{\circ}$ elevation. Calculated cloud amount was compared with measured cloud amount with eye at surface observatory for the validation. Bias, RMSE, and correlation coefficient were 0.4, 1.8, and 0.8, respectively. Validation results indicated that calculated cloud amount was a little higher than measured cloud amount but correlation was considerably high. Since calculated cloud amount has 5km ${\times}$ 5km resolution over Korean Peninsula and adjacent sea area, the satellite-driven cloud amount could show the possibility which overcomes the temporal and spatial limitation of measured cloud amount with eye at surface observatory.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.103-111
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• 2011

The research has increased the role of physical activity in promoting health and preventing chronic disease. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). COUNT method has been proven through experiments of validity Freedson, Hendelman, Leenders, Yngve was implemented by applying the SVM method. A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activity protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks. Customized estimating algorithm for energy expenditure of physical activities were implemented with COUNT and SVM correlation between the data.