• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.3
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• pp.193-210
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• 1991

For the deckhouse or superstructure, attention is directed to the reduction of vibration from a human susceptibility point of view. The two basic requirements for obtaining a low vibration level in the accommodation are to ensure that excitation forces from propeller and/or main engine are small and to avoid resonance excitation of the hull and superstructure. In recent years increased attention has been directed towards the problems of vibration and noise in deckhouse, which have caused major problems with regard to the environmental quality in the living quarters for crews. Accordingly, in this paper, the characteristic of the vibration of deckhouse of fishing boat, of which the length/height ratio is also relatively high, are studied systematically with regard to the shape and modelling of deckhouse based on finite element method of 1-dimensional, 2-dimensional and 3-dimensional model. This study is divided into 4-part. 1st part is the global deckhouse vibration, 2nd part is the local deckhouse vibration, 3rd part consists of the estimation for stiffness of foundational support and 4th part is the application to TUNA LONG LINER of 416 ton class. For the global vibration analysis, the severity of the vibration depends on the longitudinal shear and bending stiffness of the deckhouse, on the vertical deckhouse support(fore, aft and sides). However, even if the design is technically sound, vibration problems may arise due to vertical or longitudinal hull girder or afterbody resonances. Author applied the method of this study to the analysis of, deep-sea fishing vessel of G.T. 416 ton class with relatively low height and long deckhouse, and investigated the vibrational characteristic of the fishing vessel with earlier structural feature. According to this investigation, the vibration, response of above vessel was confirmed of which main hull and deckhouse behave as one body. It is at the bottom of vibrational trouble which a accommodation part of the fishing vessel is raised, that is the local vibration for side wall, fore-aft wall and deck plate of deckhouse rather than thief fect of fore-aft vibration of deckhouse for above fishing vessel. and the resonance of main hull, deckhouse and driving system such as the main engine, propeller in exciting source is mainly brought up as the trouble.

• Applied Chemistry for Engineering
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• v.23 no.1
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• pp.35-41
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• 2012

This paper proposes a new methodology for the real-time on-line quality monitoring of biofuel processes through the integration of infrared spectroscopy and chemometrics. A method of Partial Least Squares (PLS) in Chemometrics is employed for quantitative analysis of key components in bioethanol products. After a number of preprocessing methods and variable importance in projection (VIP) are used, Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed method allows us to economically forecast the concentration of multiple impurities encountered with the production of bioethanol. The proposed system is also accurate enough ($R^2$ > 0.99) to replace the laboratory analysis.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.248-257
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• 2002

Clustering is a method for grouping objects with similar properties into a same cluster. SVD(Singular Value Decomposition) is known as an efficient preprocessing method for clustering because of dimension reduction and noise elimination for a high dimensional and sparse data set like E-Commerce data set. However, it is hard to evaluate the worth of original attributes because of information loss of a converted data set by SVD. This research proposes a cluster feature selection method, called ENTROPY-SVD, to find important attributes for each cluster based on entropy weighting and SVD. Using SVD, one can take advantage of the latent structures in the association of attributes with similar objects and, using entropy weighting one can find highly dense attributes for each cluster. This paper also proposes a model-based collaborative filtering recommendation system with ENTROPY-SVD, called CFS-CF and evaluates its efficiency and utilization.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.189-196
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• 2010

In this paper, we proposed the adaptive local sigma filter reducing noises generated by an image sensor. The small noises generated by the image sensor are amplified by increased an analog gain and an exposure time of the image sensor together with information. And the goal of this work was the system design that is reduce the these amplified noises. Edge data are extracted by Flatness Index Map algorithm. We made the threshold adaptively changeable by the luminance average in this algorithm that extracts the edge data not in high luminance, but just low luminance. The Local Sigma Filter performed only about the edge pixel that were extracted by Flatness Index Map algorithm. To verify the performance of the designed filter, we made the Window test program. The hardware was designed with HDL language. We verified the hardware performance of Local Sigma Filter system using FPGA Demonstration board and HD image sensor, $1280{\times}720$ image size and 30 frames per second.

• Applied Microscopy
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• v.42 no.2
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• pp.105-109
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• 2012

Electron tomography (ET) of biological specimens is performed from a series of images obtained over a range of tilt angles in a transmission electron microscope. When using the high voltage electron microscope (HVEM), various noises appear in EM images acquired from thick sections by high voltage electron beam. In order to obtain an adequate result in electron tomograms that allow visualization of rather complex and mega-cellular structure such as brain tissue, it is necessary to remove the noise in each original tilt images of thick section. Using band-pass filtering of original tilt images, the filtered images are obtained and used to assemble a reconstructed tomogram. The qualified 3D tomogram from filtered images results in a considerable reduction of the noises compared to conventional tomogram. In conclusion, this study suggests that band-pass filtering is effective to improve the brightness and intensity of HVEM produced tomograms acquired from micron-thick sections of biological specimens.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.213-221
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• 2004

A new method for design of two-channel finite-impulse response(FIR) quadrature mirror-image filter(QMF) banks with low reconstruction delay using weighting function is proposed. The weighting function used in this paper is calculated from the previous updated filter coefficients vector which is adjusted from iteration to iteration in the design of QMF banks. In this paper, passband and stopband edge frequency are used in design of QMF banks with low delay characteristic in time domain instead of specific frequency interval where the artifacts occur in conventional design method. The investigation of specific frequency interval where artifacts occur can not be required by using passband and stopband edge frequency. Some comparisons of performance are made with other existing design method to demonstrate the proposed method for QMF bank design. and it was observed that the proposed method using the weighted function and passband and stopband edge frequency improves the peak reconstruction error by 0.001 [dB], the peak-to-peak passband ripple by 0.003[dB], SNR with a white noise by 7[dB] and SNR with a step input by 32[dB], but with a reduction of the computational efficiency because of updating the weighting function over the conventional method in Ref [11].

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.157-164
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• 2015

The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

• Journal of the Korean Magnetics Society
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• v.20 no.2
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• pp.61-67
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• 2010

As a high energy permanent magnet is commonly applied to motors so that small motors have high power capacities, it is also necessary to reduce a cogging torque which causes a noise and vibration in permanent magnet motors. The patterns of cogging torque in permanent magnet motors depend on the magnetic field distributions, so it is possible to reduce a cogging torque by designing a core shapes optimally. But it is known that an optimum design algorithm for reduction of cogging torques is too complicated and the process to get an optimized core shape is time consuming task. In this paper, new simplified core shapes are suggested to reduce a design parameters so that the core shapes to reduce a cogging torques could be obtained with simple computations. The result shows that the cogging torques of permanent magnet motors with this simplified core shapes could be reduced effectively without any loss of average torques.

• Smart Structures and Systems
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• v.6 no.9
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• pp.1057-1077
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• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.675-682
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• 2014

Prostate is only an organ of men. To diagnose the disease of the prostate, generally transrectal ultrasound(TRUS) images are used. Detecting its boundary is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Support Vector Machine(SVM) is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing. Gabor filter bank for extraction of rotation-invariant texture features has been implemented. SVM for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted. A number of experiments are conducted to validate this method and results shows that the proposed algorithm extracted the prostate boundary with less than 10% relative to boundary provided manually by doctors.