• Journal of Mechanical Science and Technology
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• v.16 no.1
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• pp.60-74
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• 2002

In this study, normal, log-normal, triangular, uniform. Weibull, Erlang and unit beta probability density functions are tried to represent the behaviour of frequency distributions of workpiece dimensions collected from various manufacturing firms. Among the distribution functions, the unit beta distribution function is found to be the best fit using the chi-square test of fit. An attempt is made for the adoption of the unit beta model to x-bar charts of quality control in manufacturing. In this direction, upper and lower control limits (UCL and LCL) of x-bar control charts of dimension measurements are estimated for the beta model, and the observed differences between the beta and normal model control limits are discussed for the measurement sets.

• Journal of the Korean Wood Science and Technology
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• v.28 no.4
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• pp.51-55
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• 2000

The woodceramics which are new porous carbon materials were obtained by carbonizing from thinned small log of Aomori HIBA (Thujopsis dolabrata S. et. Z. var. hondae M.) impregnated with phenol resin in a vacuum furnace. During the carbonization process, the resin changes into glassy carbon, which has superior property. The resin impregnation rate and bending strength depend on the types of board and density. In this paper, the manufacturing method of woodceramics made from thinned small logs of Aomori HIBA was introduced and some properties were examined.

• Journal of the Korean Wood Science and Technology
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• v.28 no.4
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• pp.56-60
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• 2000

A new porous carbon material "woodceramics" was developed by carbonizing wood or woody materials impregnated with thermosetting resin. Steamed board and non-steamed board were made from thinned small log of Aomori Hiba (Thujopsis dolabrata S. et. Z. var. hondae M.). They were impregnated with phenol resin and sintered in a vacuum furnace at $650^{\circ}C$. In this paper, the manufacturing method of woodceramics and changes of dimension, weight and compressive strength were investigated. The changes of dimension, weight and compressive strength depend on the types of board and density.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2011.10a
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• pp.43-47
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• 2011

In woody waste separated from municipal solid waste, medium density fiberboard was major contributors with particleboard, paper, plywood and log, with different composition based on collected period. In chemical compositional analysis of woody waste, it was similar to softwood based on carbohydrate composition analysis. Based on the carbohydrate composition, saccharified solution from MWW could be good resource for biorefinery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.868-873
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• 2008

In this paper, we analyze the burst error performance of LDPC codes on perpendicular magnetic recording(PMR) channel. When burst error is generated on PMR channel, we use channel state information(CSI) to set the LLR information of channel detector zero. We consider the rate 0.94 LDPC codes and use SOVA as channel detector with low complexity.

• ETRI Journal
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• v.33 no.6
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• pp.949-952
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• 2011

In this letter, a simplified suboptimum receiver based on soft-limiting for the detection of binary antipodal signals in non-Gaussian noise modeled as a generalized normal-Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman-Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL-plus-Gaussian distribution.

• ETRI Journal
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• v.36 no.4
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• pp.591-598
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• 2014

This paper proposes a new min-sum algorithm for low-density parity-check decoding. In this paper, we first define the negative and positive effects of the received signal-to-noise ratio (SNR) in the min-sum decoding algorithm. To improve the performance of error correction by considering the negative and positive effects of the received SNR, the proposed algorithm applies adaptive scaling factors not only to extrinsic information but also to a received log-likelihood ratio. We also propose a combined variable and check node architecture to realize the proposed algorithm with low complexity. The simulation results show that the proposed algorithm achieves up to 0.4 dB coding gain with low complexity compared to existing min-sum-based algorithms.

• MALSORI
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• no.60
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• pp.109-123
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• 2006

Since computing the log-likelihood of Gaussian mixture density is a major computational burden for the speech recognizer based on the continuous HMM, several techniques have been proposed to reduce the number of mixtures to be used for recognition. In this paper, we propose a modified Bucket Box Intersection (BBI) algorithm, in which two relative thresholds are employed: one is the relative threshold in the conventional BBI algorithm and the other is used to reduce the number of the Gaussian boxes which are intersected by the hyperplanes at the boxes' edges. The experimental results show that the proposed algorithm reduces the number of Gaussian mixtures by 12.92% during the recognition phase with negligible performance degradation compared to the conventional BBI algorithm.

• The Korean Journal of Food And Nutrition
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• v.8 no.1
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• pp.1-5
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• 1995

ATPase was the most available phosphatase in culture broth of 5. coli P90C. To measure the stable phosphatase activity it was necessary to react nth reaction reagent over 30 min and then we can get stable optical density at 410 m. Transfer time from preculture to main culture for the production of $\beta$-glactosidase was good after 3 hrs cultivation. Phosphatase activity was highest at log phase in main culture and as the cell begins to make $\beta$-galactosidase phosphatase activity begins to decrease.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.473-481
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• 2008

This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.