• International Journal of Naval Architecture and Ocean Engineering
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• v.1 no.2
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• pp.95-100
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• 2009

As ships become larger, thicker and higher tensile steel plate are used in shipyard. Though special chemical compositions are required for high-tensile steels, recently they are made by the TMCP (Thermo-Mechanical control process) methodology. The increased Yield / Tensile strength of TMCP steels compared to the normalized steel of same composition are induced by suppressing the formation of Ferrite and Pearlite in favor of strong and tough Bainite while being transformed from Austenite. But this Bainite phase could be vanished by another additional thermal cycle like welding and heating. As thermal deformations are deeply related by yield stress of material, the study for prediction of plate deformation by heating should niflect the principle of TMCP steels. The present study is related to the development of an algorithm which could calculate inherent strain. In this algorithm, not only the mechanical principles of thermal deformations, but also the initial portion of Bainite is considered when calculating inherent strain. Distortion analysis results by these values showed good agreements with experimental results for normalized steels and TMCP steels during welding and heating. This algorithm has also been used to create an inherent strain database of steels in Class rule.

• Geophysics and Geophysical Exploration
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• v.15 no.2
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• pp.66-74
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• 2012

This paper presents development of a three-dimensional marine controlled-source electromagnetic (mCSEM) modeling algorithm and its application to a salt and reservoir model to examine detectability of mCSEM for a reservoir under complex subsurface structures. The algorithm is based on the finite difference method, and employs the secondary field formulation for an accurate and fast calculation of modeling responses. The algorithm is verified for a two-layer model by comparing solutions not only with analytic solutions but also with those from other 3D modeling algorithm. We calculate and analyze electric and magnetic fields and their normalized responses for a salt and reservoir model due to three sources located at boundaries between a salt, a reservoir, and background. Numbers and positions of resistive anomalies are informed by normalized responses for three sources, and types of resistive anomalies can be informed when there is a priori information about a salt by seismic exploration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.876-884
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• 2014

A hardware design of LDPC decoder which is based on the improved normalized min-sum(INMS) decoding algorithm is described in this paper. The designed LDPC decoder supports 19 block lengths(576~2304) and 6 code rates(1/2, 2/3A, 2/3B, 3/4A, 3/4B, 5/6) of IEEE 802.16e mobile WiMAX standard and 3 block lengths(648, 1296, 1944) and 4 code rates(1/2, 2/3, 3/4, 5/6) of IEEE 802.11n WLAN standard. The decoding function unit(DFU) which is a main arithmetic block is implemented using sign-magnitude(SM) arithmetic and INMS decoding algorithm to optimize hardware complexity and decoding performance. The LDPC decoder synthesized using a 0.18-${\mu}m$ CMOS cell library with 100 MHz clock has 284,409 gates and RAM of 62,976 bits, and it is verified by FPGA implementation. The estimated performance depending on code rate and block length is about 82~218 Mbps at 100 MHz@1.8V.

• Korean Journal of Optics and Photonics
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• v.20 no.1
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• pp.16-22
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• 2009

We propose a method to convert a two-dimensional movie to a three-dimensional movie using normalized cut and optical flow. In this paper, we segment an image of a two-dimensional movie to objects first, and then estimate the depth of each object. Normalized cut is one of the image segmentation algorithms. For improving speed and accuracy of normalized cut, we used a watershed algorithm and a weight function using optical flow. We estimate the depth of objects which are segmented by improved normalized cut using optical flow. Ordinal depth is estimated by the change of the segmented object label in an occluded region which is the difference of absolute values of optical flow. For compensating ordinal depth, we generate the relational depth which is the absolute value of optical flow as motion parallax. A final depth map is determined by multiplying ordinal depth by relational depth, then dividing by average optical flow. In this research, we propose the two-dimensional/three-dimensional movie conversion method which is applicable to all three-dimensional display devices and all two-dimensional movie formats. We present experimental results using sample two-dimensional movies.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.395-432
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• 2021

Groundwater recharge rates vary widely by location and with time. They are difficult to measure directly and are thus often estimated using simulations. This study employed frequency and regression analysis and a classification and regression tree (CART) algorithm in a machine learning method to estimate groundwater recharge. CART algorithms are considered for the distribution of precipitation by subbasin (PCP), geomorphological data, indices of the relationship between vegetation and landuse, and soil type. The considered geomorphological data were digital elevaion model (DEM), surface slope (SLOP), surface aspect (ASPT), and indices were the perpendicular vegetation index (PVI), normalized difference vegetation index (NDVI), normalized difference tillage index (NDTI), normalized difference residue index (NDRI). The spatio-temperal distribution of groundwater recharge in the SWAT-MOD-FLOW program, was classified as group 4, run in R, sampled for random and a model trained its groundwater recharge was predicted by CART condidering modified PVI, NDVI, NDTI, NDRI, PCP, and geomorphological data. To assess inter-rater reliability for group 4 groundwater recharge, the Kappa coefficient and overall accuracy and confusion matrix using K-fold cross-validation were calculated. The model obtained a Kappa coefficient of 0.3-0.6 and an overall accuracy of 0.5-0.7, indicating that the proposed model for estimating groundwater recharge with respect to soil type and vegetation cover is quite reliable.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.49-57
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• 1994

An efficient approach for the computationtion of the optimum convergence factor is proposed for the LMS algorithm applied to a transversal FIR structure in this study. The approach automatically leads to an optimum step size algorithm at each weight in every iteration that results in a dramatic reduction in terms of convergence time. The algorithm is evaluated in system identification application where two alternative computer simulations are considered for time-invariant and time-varying system cases. The results show that the proposed algorithm needs not appropriate convergence factor and has better performance than AGC(Automatic Gain Control) algorithm and Karni algorithm, which require the convergence factors controlled arbitrarily in computer simulation for time-invariant system and time-varying systems. Also, itis shown that the proposed algorithm has the excellent adaptability campared with NLMS(Normalized LMS) algorithm and RLS (Recursive least Square) algorithm for time-varying circumstances.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.484-490
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• 2012

In this paper, we design a digitally pre-distorted RF power amplifier operating in 900 MHz band. The linearity of RF power amplifier is improved by employing the digital pre-distortion(DPD) based on affine projection(AP) algorithm, where the look-up table(LUT) method is used with non-linear indexing. The proposed DPD with AP algorithm is compared with that with normalized least mean square(NLMS) algorithm, applied to the RF power amplifier. A commercial power amplifier module is used for verification of the proposed algorithm which shows improvement of adjacent channel leakage ratio(ACLR) by about 21 dB.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.108-115
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• 1994

Most pattern classifiers have been designed based on the ML (Maximum Likelihood) training algorithm which is simple and relatively powerful. The ML training is an efficient algorithm to individually estimate the model parameters of each class under the assumption that all class models in a classifier are statistically independent. That assumption, however, is not valid in many real situations, which degrades the performance of the classifier. In this paper, we propose a minimum-error-rate training algorithm based on the MAP (Maximum a Posteriori) approach. The algorithm regards the normalized outputs of the classifier as estimates of the a posteriori probability, and tries to maximize those estimates. According to Bayes decision theory, the proposed algorithm satisfies the condition of minimum-error-rate classificatin. We apply this algorithm to NPM (Neural Prediction Model) for speech recognition, and derive new disrminative training algorithms. Experimental results on ten Korean digits recognition have shown the reduction of 37.5% of the number of recognition errors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2349-2354
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• 1996

Convergence analysis on Godard's quartic (GQ) algorithm used forblind equalization is accomplished in this paper. The first main result is an explanation of the lacal behavior of the GQ algorithm around the global minimum point of the average performance functio, from which we can determine the adaptation gain. It is show that the normalized adaptation gain of the GQ algorithm should be smaller than that of the decision directed (DD) algorithm. In addition, it is observed that the GQ algorithm converges faster than the DD equalization algorithm.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.423-426
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• 2003

Adaptive algorithm used in Acoustic Echo Canceller (AEC) needs fast convergence algorithm when reference signal is colored speech signal. Set-Membership Affine Projection (SMAP) algorithm is derived from the constraint, which is the minimum value adaptive filter coefficient error. In this paper, we test the characteristic about noise of the SMAP algorithm and proposed modified version of SMAP algorithm fur using at AEC. As the projection order increase, the convergence characteristic of the SMAP algorithm is improved where no noise space. But if the noise uncorrelated with input signal exists, the AEC shows bad performance. In this paper, we propose normalized version of adaptive constants using estimated error signal for robust to noise and show the good performance through AEC simulation.