• 대한수학회논문집
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• 제18권2호
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• pp.375-383
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• 2003

Under some conditions on an array of rowwise independent random variables, Hu et at. (1998) obtained a complete convergence result for law of large numbers with rate {a$\_$n/, n $\geq$ 1} which is bounded away from zero. We investigate the general situation for rate {a$\_$n/, n $\geq$ 1) under similar conditions.

• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.29-39
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• 2019

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

• 한국산업정보학회논문지
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• 제23권3호
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• pp.131-142
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• 2018

Since income growth rate and poverty level are related, there is a possibility that the poverty rate may converge in the long run steady state as well. If the poverty rate converges, then for this study the state that begins with the high poverty rate would have a higher poverty reduction rate. To examine the convergence of poverty rate among the US states, this study uses two times series methodologies. First, in order to prevent the power loss from ignoring the structural break when testing for a unit root in a single time series, this study employs the newly developed panel LM unit root tests with level and trend shifts. The results of unit root tests of the log of poverty rate without allowing for structural breaks show that twenty six states reject the null hypothesis of unit root test for the ADF test, twenty five states for the LM test, and thirty five states for the RALS-LM test. The result of unit root tests that allow one structural break shows that the null hypothesis of a unit root test is rejected for twenty two states with the LM test, and thirty three states with the RALS-LM test. This supports poverty rates are converging among US states.

• 터널과지하공간
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• 제13권2호
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• pp.108-116
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• 2003

백악기 경상계 안산암과 불국사 화강암류가 주로 분포하는 지반에서 시공된 터널의 내공변위 계측자료를 분석하였다. 터널 주변 암반을 RMR법에 의한 다섯 가지 암반등급으로 구분하고 각 등급에 포함된 계측자료들을 통계처리하여 암반등급별 내공변위의 회귀분석을 실시하였다. 연구 결과. 로그함수보다는 지수함수의 상관계수 가 더 크며, 연약한 암반등급일수록 내공변위의 크기와 표준편차가 크게 나타났다. 또한, 최종내공변위에 대한 최대변위속도 및 초기내공변위의 관계를 도출하였으며, 이 중에서 최종내공변위와 최대변위속도의 상관계수는 0.87로 나타나 이들은 비교적 높은 상관성을 가지는 것으로 확인되었다

• 한국공작기계학회논문집
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• 제12권3호
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• pp.82-88
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• 2003

SGA(Single Genetic Algorithm) is a heuristic global optimization method based on the natural characteristics and uses many populations and stochastic rules. Therefore SGA needs many function evaluations and takes much time for convergence. In order to solve the demerits of SGA, ${\mu}GA$(Micro-Genetic Algorithm) has recently been developed. In this study, ${\mu}GA$ which have small populations and fast convergence rate, was applied to structural optimization with discrete or integer variables such as 3, 10 and 25 bar trusses. The optimized results of ${\mu}GA$ were compared with those of SGA. Solutions of ${\mu}GA$ for structural optimization were very similar or superior to those of SGA, and faster convergence rate was obtained. From the results of examples, it is found that ${\mu}GA$ is a suitable and very efficient optimization algorithm for structural design.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.9-14
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• 2003

SGA (Single Genetic Algorithm) is a heuristic global optimization method based on the natural characteristics and uses many populations and stochastic rules. Therefore SGA needs many function evaluations and takes much time for convergence. In order to solve the demerits of SGA, $\mu$GA(Micro-Genetic Algorithm) has recently been developed. In this study, $\mu$GA which have small populations and fast convergence rate, was applied to structural optimization with discrete or integer variables such as 3, 10 and 25 bar trusses. The optimized results of $\mu$GA were compared with those of SGA. Solutions of $\mu$GA for structural optimization were very similar or superior to those of SGA, and faster convergence rate was obtained. From the results of examples, it is found that $\mu$GA is a suitable and very efficient optimization algorithm for structural design.

• Journal of Welding and Joining
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• 제35권3호
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• pp.28-34
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• 2017

The authors derived the criteria on the process parameters of laser depositions with metal powers(SUS316L & IN718) by evaluating the surface and cross-section properties of the deposition layers. The surface characteristics of the deposition layer are investigated through optical microscopy by controlling the process parameters of laser output, powder feeding rate and gas feeding rate. The cross-section characteristics were also analyzed after polishing and chemical etching process. As the gas feeding rate increased, the amount of powder loss increased and the difference in the dilution ratio and heat affected zone depending on laser outputs was observed. In addition, the powder feeding rate used in the experiment did not interfere with the energy absorption of the base material.

• 대한수학회지
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• 제43권4호
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• pp.815-828
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• 2006

Let {$V_{nk},\;k\;{\geq}\;1,\;{\geq}\;1$} be an array of rowwise independent random elements which are stochastically dominated by a random variable X with $E\|X\|^{\frac{\alpha}{\gamma}+{\theta}}log^{\rho}(\|X\|)\;<\;{\infty}$ for some ${\rho}\;>\;0,\;{\alpha}\;>\;0,\;{\gamma}\;>\;0,\;{\theta}\;>\;0$ such that ${\theta}+{\alpha}/{\gamma}<2$. Let {$a_{nk},k{\geq}1,n{\geq}1$) be an array of suitable constants. A complete convergence result is obtained for the weighted sums of the form $\sum{^\infty_k_=_1}\;a_{nk}V_{nk}$.

• International journal of advanced smart convergence
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• 제6권4호
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• pp.67-72
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• 2017

Deep learning neural network becomes very popular nowadays due to the reason that it can learn a very complex dataset such as the image dataset. Although deep learning neural network can produce high accuracy on the image dataset, it needs a lot of time to reach the convergence stage. To solve the issue, we have proposed a scaling method to improve the neural network to achieve the convergence stage in a shorter time than the original method. From the result, we can observe that our algorithm has higher performance than the other previous work.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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• pp.189-192
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• 2000

A fuzzy controller for the evaluation of the quantization parameters in the H.263 coder has been introduced. We adopted a Mamdani fuzzy controller with centroid defuzzification. The inputs are variance, entropy, current motion vector and previous motion vector. This results is obtained a effective rate control technique using fuzzy Quantization.