• Economic and Environmental Geology
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• v.31 no.2
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• pp.141-147
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• 1998

Earth tide observations were taken at AMIST observatory in Seoul by LaCoste-Romberg ET gravimeter from September 2 to 16, 1997 for determining the gravimetric factor ($\delta$) and analyzing the tidal components. Meter drifts were corrected by regression and then denoised by threshholding wavelet, a data processing tool. The mean value of $\delta$ is 1.2 and the mean phase lag of & ($M_2$, $S_2$) and & $K_1$, $O_1$) is $0.07{\pm}0.03^{\circ}$ and $0.08{\pm}0.07^{\circ}$ by analyzing the observed earth tides. For yielding measurements of gravity accurate to about 0.01 mgal, the Earth tide observations are required by ET meter. The tidal variations are due to the planet's distance and zenith angle. With the exception of Earth-Moon and Earth-Sun mechanism, the possible causes of tidal variations are tectonical, meterological and hydrological perturbations. The long period and broad observations are required for determining the state of art gravimetric factor in Korea.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.11
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• pp.89-95
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• 2015

As a solution of improving the energy efficiency in power system, Low Voltage DC (LVDC) distribution systems different from conventional ones have been constantly researched. As in conventional AC distribution system, LVDC distribution system can suffer from High Impedance Fault (HIF) which may cause a failure of protective relay due to relatively low change in magnitude of fault current. In order to solve the problem, a scheme for detecting HIFs is presented in this paper. Closing Opening Difference Operation (CODO) based on Mathematical Morphology (MM), one of the MM-based filters, is utilized to make fault signals discriminable. To verify performance of the scheme, a simple LVDC distribution system is modeled by using ElectroMagnetic Transient Program (EMTP) software. Computer simulations according to various conditions are performed and comparison studies with a scheme using Wavelet Transform (WT) in an aspect of simulation time are also conducted.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.71-79
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• 2015

Recently, new Low Voltage DC (LVDC) power distribution systems have been constantly researched as uses of DC in end-user equipment are increased. As in conventional AC distribution system, High Impedance Fault (HIF) which may cause a failure of protective relay can occur in LVDC distribution system as well. It, however, is hard to be detected since change in magnitude of current due to the fault is too small to detect the fault by the protective relay using overcurrent element. In order to solve the problem, this paper presents an algorithm for detecting HIF using accumulated energy in LVDC distribution system. Wavelet Singular Value Decomposition (WSVD) is used to extract abnormal high frequency components from fault current and accumulated energy of high frequency components is considered as the element to detect the fault. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed algorithm using ElectroMagnetic Transient Program (EMTP) software. Simulation results considering various conditions show that the proposed algorithm can be utilized to effectively detect HIF.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.5
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• pp.777-782
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• 2002

This study will offer multimodal recognition instead of an existing monomodal bioinfomatics by using facial multi-feature to improve the accuracy of recognition and to consider the convenience of user . Each bioinfomatics vector can be found by the following ways. For a face, the feature is calculated by principal component analysis with wavelet multiresolution. For a lip, a filter is used to find out an equation to calculate the edges of the lips first. Then by using a thinning image and least square method, an equation factor can be drawn. A feature found out the facial parameter distance ratio. We've sorted backpropagation neural network and experimented with the inputs used above. Based on the experimental results we discuss the advantage and efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.565-568
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• 2006

In the luminance and chrominance signal, luminance signal creates gray images, and is capable of making each color component compatible with monochrome system. And color components of luminance and chrominance signals are useful to encode or convert the signal because they have low correlation. Each color signal has low correlation statistically, but they are not independent of one another. Therefore, this paper proposes the watermark inserting algorithm for luminance and chrominance signal in the domain of frequency founded on wavelet, considering the interdependent characteristics of color components. Therefore, it can guarantee the robustness and invisible of digital watermark.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.23-26
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• 2005

This paper describes the algorithm for deciding the status of the operating machines in the power plants. It is very important to decide whether the status of the operating machines is good or not in the industry to protect the accidents of machines and improve the operation efficiency of the plants. There are two steps to analyze the status of the running machines. First, we extract the features from the input original data. Second, we classify those features into normal/abnormal condition of the machines using the wavelet transform and the input RMS vector through the K-means algorithm. In this paper we developed the algorithm to detect the fault operation using the K-means method from the sound of the operating machines.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.191-204
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• 2018

To combat the adverse impact imposed by illumination variation in the face recognition process, an effective and feasible algorithm is proposed in this paper. Firstly, an enhanced local texture feature is presented by applying the central symmetric encode principle on the fused component images acquired from the wavelet decomposition. Then the proposed local texture features are combined with Deep Belief Network (DBN) to gain robust deep features of face images under severe illumination conditions. Abundant experiments with different test schemes are conducted on both CMU-PIE and Extended Yale-B databases which contain face images under various illumination condition. Compared with the DBN, LBP combined with DBN and CSLBP combined with DBN, our proposed method achieves the most satisfying recognition rate regardless of the database used, the test scheme adopted or the illumination condition encountered, especially for the face recognition under severe illumination variation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.805-810
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• 2011

This paper deals with the method and algorithm used to find fault locations in gas insulated transmission line. The method uses UHF sensors and digital oscilloscope to detect discharge signals emitted to the outside through insulating spacer in the event of breakdown inside GIL. UHF sensors are the external type and installed at outside of insulating spacers of GIL. And we used wavelet signal processing to analyze the discharge signals and confirm the exact fault location findings in the GIL test line. This method can overcome demerit of TDR(Time Domain Reflectometer) method having been applied to detect fault location for conventional underground transmission lines, and Ground Fault Sensors used in conventional GIS systems. TDR method requires high level of specialty and experience in analyzing the measured signals. Ground fault sensors are installed inside GIL and can be destroyed by high transient voltage. This paper's method can simplify the fault location process and minimize the damage of sensors. In addition, this method can estimate the fault location only by the time difference when discharge signals are arrived to detecting sensors at the ends of GIL sections without reasons of breakdown. To test the performance of our method, we installed sensors at the ends of test line of GIL(84m) and sensed discharge signals occurred in GIL, energized with AC voltage generator up to 700kV.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1246-1248
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• 2003

Internal wave with a soliton-like, large amplitudes within several kilometers, is frequently observed in the sea surface caused by tidal rectification due to sill or rough topographic changes. Internal waves can perturb current and density field, initiate bottom sediment re -suspension and mix nutrients to photic zone. Previous studies indicate that the appearance of internal wave in the Lombok Strait have been detected in SAR image data. This paper studies effect of internal wave in the Lombok Strait to chlorophyll distribution in the surrounded areas using SeaWiFS and ERS SAR images data during 1996-2001 periods. The preliminary result concludes that the internal waves presumably affect phytoplankton distribution spreading southeastward in the coast off Bali Island. The distribution of phytoplankton at southern coastline off Bali Island when internal wave occurred is elongated and distributed further to westward (from 8.8$^{\circ}$ to 10.7$^{\circ}$LS) than the area when internal wave did not occur on August 2000 (from 9.25$^{\circ}$ to 10.25$^{\circ}$LS) as shown in figure 3. It shown that the surface phytoplankton concentration near coastal area, i.e. from 8.8$^{\circ}$ to 9.25$^{\circ}$ LS, increased when internal wave is occurred.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.177-185
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• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.