• 대한전자공학회논문지SP
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• 제48권2호
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• pp.96-101
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• 2011

소실점이란 실제 공간의 평행한 선들이 영상 내에 투영되면서 한곳에 모이는 점이다. 본 논문에서는 이러한 소실점의 특성을 이용한 실시간 소실점 검출 알고리즘을 제안한다. 기존의 소실점 검출 방법은 1) 복잡한 계산이 요구되거나 2) 알고리즘에 따라 소실점을 검출할 수 있는 영상이 제한되어 있다. 제안하는 방법은 블록 기반의 HOG(Histogram of Oriented Gradient)를 구하여 영상의 구조적 특성을 이용하는 것으로 영상 내에 존재하는 소실점을 실시간으로 검출한다. 먼저 영상의 블록 단위로 HOG 기술자를 구한 뒤, 제안하는 동적 프로그래밍(dynamic programing)을 이용하여 소실점의 위치를 예측한다. 본 논문에서는 다양한 영상에 대한 실험을 통해 제안하는 알고리즘이 효율적인 소실점 검출 방법임을 보이고자 한다.

• 한국식품과학회지
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• 제52권3호
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• pp.296-303
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• 2020

Hop-resistant lactic acid bacteria (LAB) are well-known, major beer-spoilage bacteria. The hop-gradient agar containing ethanol (c-HGA+E) method has been used to examine hop-resistance of beer-spoilage LAB. However, the selection of beer-spoilage bacteria by the c-HGA+E method is either too selective or too inclusive. Furthermore, it is accompanied by a complicated experimental procedure, high-cost and time. To overcome these disadvantages, the modified hop-gradient agar with ethanol (m-HGA+E) method was developed. The most remarkable modifications were the shape of the petri dish and the inoculation method for bacteria. The efficiency and validation of the m-HGA+E approach were proven by the formation of colonies at different hop concentrations in the bottom layer, co-culture with the bacteriocin producer and by PCR detection of hop-resistant genes. This study demonstrated that m-HGA+E is a rapid, economical, and easy method to monitor potential hop-resistant beer-spoilage LAB during the beer brewing process.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.515-518
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• 1998

This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.

• 한국동물생명공학회지
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• 제35권1호
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• pp.58-64
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• 2020

This present study was conducted to investigate protective effect of discontinuous Percoll gradient containing alpha-linolenic acid (ALA) before freezing process on viability, acrosome damage, mitochondrial activity, and oxidative stress of frozen-thawed boar spermatozoa. The separation of spermatozoa by discontinuous Percoll gradient was performed by different concentration of Percoll solution (45/90%) containing ALA combined with bovine serum albumin (BSA), and collected sperm in each Percoll layer was cryopreserved. To evaluate viability, acrosome damage, mitochondrial activity, and reactive oxygen species (ROS) level of frozen-thawed sperm, flow cytometry was used. Morphological abnormalities were observed under light microscope. In results, viability of sperm from 90% Percoll layer was higher than control and 45% Percoll group (p < 0.05). Separated sperm in 90% Percoll layer had lower acrosome damage and morphological abnormalities than control as well as viability, whereas 45% Percoll group was higher (p < 0.05). Similar with acrosome damage and abnormalities, mitochondrial activity was slightly enhanced and the population of live sperm with high ROS level was decreased by 90% Percoll separation, however, there was no significant difference. Supplementation of 3 ng/mL ALA into Percoll solution increased sperm viability and decreased population of live sperm with high ROS compared to control (p < 0.05). In conclusion, discontinuous Percoll gradient before freezing process could improve efficiency of cryopreservation of boar sperm through selection of sperm with high freezing resistance, and supplement of ALA during Percoll gradient might contribute suppression of ROS generation via stabilizing of plasma membrane during cryopreservation.

• International Journal of Fluid Machinery and Systems
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• 제2권1호
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• pp.1-12
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• 2009

Surrogate modeling is applied to a compressor blade shape optimization to modify its stacking line and thickness to enhance adiabatic efficiency and total pressure ratio. Six design variables are defined by parametric curves and three objectives; efficiency, total pressure and a combined objective of efficiency and total pressure are considered to enhance the performance of compressor blade. Latin hypercube sampling of design of experiments is used to generate 55 designs within design space constituted by the lower and upper limits of variables. Optimum designs are found by formulating a PRESS (predicted error sum of squares) based averaging (PBA) surrogate model with the help of a gradient based optimization algorithm. The optimum designs using the current variables show that, to optimize the performance of turbomachinery blade, the adiabatic efficiency objective is improved substantially while total pressure ratio objective is increased a very small amount. The multi-objective optimization shows that the efficiency can be increased with the less compensation of total pressure reduction or both objectives can be increased simultaneously.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3139-3143
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• 2007

The objective of this paper was to investigate the mixing characteristics of an three-stage inline coagulant mixing system experimentally. Wastewater samples of pH 8.5 and initial turbidity 1,000NTU were taken from a site of tunneling work. At the constant dosage, 0.36mL/L, of polymer as coagulant aids, the coagulation efficiency with the dosage of PAC as coagulant was about 4${\sim}$6% at 10 minutes after sampling. In the case of 2 different velocity gradient conditions, the efficiency of turbidity removal was increased about 6.5${\sim}$8% with increasing the dosage of coagulant while, the efficiency was increased about 20${\sim}$21.5% with increasing the dosage of coagulant aids. The efficiency of turbidity removal with the settling time after sampling was about 90% after 1 minute, and the efficiency was about 95% after 5 minutes.

• 한국미생물·생명공학회지
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• 제28권3호
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• pp.185-187
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• 2000

Instead of using binary HPLC pump which is usually used for the generation of solvent gradient for the analysis of amino acid an isocratic HPLC pump and conventional gra-dient maker were demonstrated to perform such analysis withmuch lower expenses and similar efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• 천문학회보
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• 제37권1호
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• pp.39.1-39.1
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• 2012

Nuclear rings in barred galaxies are sites of active star formation (SF). We investigate SF and its feedback effects occurring in barred galaxies, for the first time, using high-resolution grid-based hydrodynamic simulations. The gaseous medium is assumed to be infinitesimally thin, isothermal, and unmagnetized. The SF recipes include a density threshold corresponding to the Jeans condition, a SF efficiency of 1%, and momentum feedback via Type II supernova events together with stellar-wind mass loss. To investigate various environments, we vary the gas sound speed as well as the efficiency of momentum injection in the in-plane direction. We find that when the sound speed is small, the surface density of a ring becomes largely independent of the azimuthal angle, resulting in star-forming regions distributed over the whole length of the ring. When the sound speed is large, on the other hand, the ring achieves the largest density at the contact points between the dust lanes and the ring where SF occurs preferentially, leading to a clear age gradient of star clusters in the azimuthal direction. Since rings shrink with time, a radial age gradient of star clusters naturally develop regardless of sound speed, consistent with observations. SF persists over 200 Myr, with an average rate of ${\sim}1.3M_{\odot}/yr$ similar to observed values. Rings gradually become hostile to SF as they lose gas into stars and turbulent motions dominate.

• Steel and Composite Structures
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• 제37권2호
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• pp.193-209
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• 2020

In this paper, the efficiency of five Machine Learning (ML) methods consisting of Deep Learning (DL), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and Gradient Tree Booting (GTB) for regression and classification of the Ultimate Load Factor (ULF) of nonlinear inelastic steel frames is compared. For this purpose, a two-story, a six-story, and a twenty-story space frame are considered. An advanced nonlinear inelastic analysis is carried out for the steel frames to generate datasets for the training of the considered ML methods. In each dataset, the input variables are the geometric features of W-sections and the output variable is the ULF of the frame. The comparison between the five ML methods is made in terms of the mean-squared-error (MSE) for the regression models and the accuracy for the classification models, respectively. Moreover, the ULF distribution curve is calculated for each frame and the strength failure probability is estimated. It is found that the GTB method has the best efficiency in both regression and classification of ULF regardless of the number of training samples and the space frames considered.