• 산업경영시스템학회지
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• 제1권1호
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• pp.37-44
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• 1978

The purpose of this study is to search for an efficient application method in solving delay-phenomenon problems which influence upon total production cost through case study. The method of this study is an experimental study based on cutting time data in lead cutting operations from "Lead Cutting Machine (Stripper)" and its service rate data from a large electronic products company which utilizes conveyor line system for the products "Car Stereo" The procedure of this experimental study is as follows; 1) Using loading(Man-Hour) analysis technique j,1 order to analyse and evaluate Production capacity, efficiency, operation and idle rate assembly charge, waiting and service cost -when its are controlled by stripper operator(server) 2) Establishing adequate waiting time model of finite population caused by the interference of 4 stripper machine which is drawn from mathematical statistics testing, that is, goodness of fit test in the waiting and service rate and to search for optimal solution by utilizing the above mentioned model The experimental result was that amount to 8,546,618won Per year was brought down, that is, by optimum point, it shows a decrease as compared with Present point. The major limitation of this experimental study is that the Queue in the Finite Population, so to speak. it comes from the interference of 4 stripper machine dealt with this case were limited only on the Car Stereo conveyor line. Further study of application of this application method to the areas such as material handling, personnel management marketing and transportation management is strong1y recommended.trong1y recommended.

• Journal of Microbiology and Biotechnology
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• 제26권5호
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• pp.946-952
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• 2016

The eglS gene in Bacillus amyloliquefaciens encodes an endo-β-1,4-glucanase that belongs to glycosyl hydrolase family 5. In this study, a disruption mutant of gene eglS was constructed to examine its role in bacterial adaptation in plants. The mutant TB2_k, eglS gene inactivated bacterial strain, was remarkably impaired in extracellular cellulase activity. When inoculated on Brassica campestris, the TB2_k population was reduced by more than 60% compared with the wild-type strain in the root, stem, and leaf tissues. Overexpression of eglS in the wild-type strain increased the bacteria population in the plant tissues. Further studies revealed that the transcription level of eglS was correlated with bacterial population. These data demonstrate that endo-β-1,4-glucanase of B. amyloliquefaciens is required for its optimal endophytic colonization.

• 환경영향평가
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• 제19권5호
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• pp.483-495
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• 2010

The passenger pigeon (Ectopistes migratorius) was a species of pigeon that was once the most common bird in North America. According to some ornithologists, the number of passenger pigeons is estimated as many as five to six billions at the time when the first Europeans arrived there. But this species became extinct in 1914. There were a multiplicity of causes in the extinction; first, the extension of telegraph lines and railroads into the Middle West of the USA beginning in 1850s, second, the loss of vast feeding, nesting, and roosting sites of the passenger pigeon due to the massive deforestation, third, the rapid population growth of the USA during nineteen century, fourth, the commercial exploitation of the species, and finally, the infirm and weak protective efforts. Some important lessons can be learned from the extinction of the passenger pigeon. First, it shows how much critical the public interest is for a successful conservational movement. Second, it illustrates the need for strong laws and practices in the protection of an endangered species from going extinct. Third, the fate of the passenger pigeon proves a very important principle in conservational biology. That is, for each species (bird or other animal) there is a minimum population to sustain the species. Ecologists generally believe that the extinction of the passenger pigeon was due to the loss of their numbers below the minimum owing to overexploitation.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.169-183
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• 2009

The simplicity and wide application of Greenberg et al. (1971) prompts to propose a set of alternative estimators of population total for multi-character surveys that elicit simultaneous information on many. sensitive study variables. The proposed estimators take into account the already known rough value of the correlation coefficient between Y(the characteristic under study) and p(the measure of size). These estimators are biased, but it is expected that the extent of bias will be smaller, since the proposed estimators are suitable for situations in between those optimum for the usual estimators and the estimators based on multi-characters for no correlation. The relative efficiency of the proposed estimators has been studied under a super population model through empirical study. It has been found through simulation study that a choice of an unrelated variable in the Greenberg et al. (1971) model could be made based on its correlation with the auxiliary variable used at estimation stage in multi-character surveys.

• 한국인구학
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• 제29권1호
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• pp.209-239
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• 2006

본 연구는 총부양비를 최소화하는 적정인구성장률을 인구학적 부양비와 경제적 부양비로 나누어 계산하구 그것이 무엇을 의미하가를 연구하는 것이 목적이다. 이 연구를 위하여 연구모형을 제시하고, 합계출산율과 적정인구성장률의 관계를 명시하며, 그것이 궁극적으로 적정인구 규모에 어떤 의미를 갖는가를 탐색한다. 인구학적 부양비를 최소화하는 인구성장률은 $-0.03%{\sim}0.15%$의 범위에 있으며, 그것은 합계 출산율로는 $2.1{\sim}2.2$명에 해당한다. 경제적 부양비를 최소화하는 인구성장률은 유년층과 노년층의 상대적 개인 소비비중에 따라 인구성장률과 그것이 함의하는 합계출산율은 달라진다. 예컨대, $u_1:u_3=2:1$일 때 적정인구성장률은 $-1.17{\sim}-0.93%$, 그것이 함의하는 합계출산율은 $1.5{\sim}1.6$명이다. 한편 유년층 대비 노년층의 상대적 소비비중이 증가하는 경우에는 적정인구성장율이 높아져야 한다. 예컨대 $u_1:u_2=1:1.2$일 때 적정인구성장률은 $0.42{\sim}0.45%$이고, 그것이 함의하는 합계출산율은 $2.3{\sim}2.4$명이다. 본 연구에서 적정인구추계를 위한 기초 여론조사에 따라 진행된 상대적 소비비중을 계산한 결과에 따르면, 유년층과 노년층의 상대적 개인 소비비중은 $u_1:u_2=1.25:1$이며, 이에 따른 현재의 상황에서 한국의 적정출산율은 $1.9{\sim}2.0$명 수준으로, 이에 해당하는 적정인구성장률은 대략 약간의 네거티브 성장을 하는 경우라고 할 수 있을 것이다.

• Journal of Biosystems Engineering
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• 제22권3호
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• pp.343-350
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• 1997

In farm management, many factors should be considered to select optimum farm machinery Some factors such as fm size can be quantified, but other factors such as working experience can not be. Futhermore, as several factors are missed and assumptions are made for the selection using conventional computer programs, the result is sometimes questionable. This problem can be solved using artificial intelligent techniques such as expert system. In this study, an expert system was developed to select optimum machinery by considering available working days, machinery to on, farming environments, labor cost, population, etc. It also took into account the characteristics of machinery, turning radius, easiness of operation, subsidy, loan to purchase, asset. farmers age, Rest Metabolic Rate, and working experience, etc. Expertise and experience of human experts were utilized to develop the expert system. The developed expert system was evaluated by the human experts and others, and it was proved to be practically useful fir farmers.

• Structural Monitoring and Maintenance
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• 제1권4호
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• 응용통계연구
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• 제25권3호
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• pp.447-456
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• 2012

For a sensitive survey in which the population is comprised of several clusters with a quantitative attribute, we present an additive quantitative randomized response model by cluster sampling that adapts a two-stage cluster sampling instead of a simple random sample based on Himmelfarb-Edgell's additive quantitative attribute model and Gjestvang-Singh's one. We also derive optimum values for the number of 1st stage clusters and the optimum values of observation units in a 2nd stage cluster under the condition of minimizing the variance given constant cost. We can see that Himmelfarb-Edgell's model is more efficient than Gjestvang-Singh's model under the condition of cluster sampling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.952-955
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• 1996

It is difficult to determine the feeding rate of coagulant in water treatment process, due to nonlinearity, multivariables and slow response characteristics etc. To deal with this difficulty, the fusion of genetic algorithms and fuzzy inference system was used in determining of feeding rate of coagulant. The genetic algorithms are excellently robust in complex operation problems, since it uses randomized operators and searches for the best chromosome without auxiliary information from a population consists of codings of parameter set. To apply this algorithms, we made the look up table and membership function from the actual operation data of water treatment process. We determined optimum dosages of coagulant (PAC, LAS etc.) by the fuzzy operation, and compared it with the feeding rate of the actual operation data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.4-101
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• 2001

Evolutionary algorithm has been receiving a remarkable attention due to the model-free and population-based parallel search attributes and much successful results are coming out. However, there are some problems in most of the evolutionary algorithms. The critical one is that it takes much time or large generations to search the global optimum in case of the objective function with multimodality. Another problem is that it usually cannot search all the local optima because it pays great attention to the search of the global optimum. In addition, if the objective function has several global optima, it may be very difficult to search all the global optima due to the global characteristics of the selection methods. To cope with these problems, at first we propose a preprocessing process, grid-filtering algorithm(GFA), and propose a new distributed evolutionary ...