• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.426-430
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• 1994

The assessment of exposure is an important component of the risk assessment process. Exposure information is used in risk assessment in at least two ways: 1) in the identification of hazards and the epidemiologic research investigating exposure-response relationships and 2) in the development of population exposure estimates. In both of these cases, the value of a chemical risk assessment is enhanced by improvements in the quality of exposure assessments. The optimum exposure assessment is the direct measurement of population exposure; however, such measurements are rarely available. Recent developments in methods for exposure assessment allow estimates to be made that are valid representations of actual exposure. The use of these exposure estimates to classify exposures correctly enhances the likelihood that causal associations between exposure and response will be correctly identified and that population risks will be accurately assessed.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.2
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• pp.50-58
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• 1998

Genetic Algorithm (GA) consists of selection, reproduction, crossover and mutation processes and many parameters including population size, generation number, the probability of crossover (Pc) and the probability of mutation (Pm). Determining values of the parameters is found critical in the whole optimization process and a sensitivity analysis with them seems mandatory. This paper tries to demonstrate such importance of sensitivity analysis of GA using an example water supply tunnel network of the New York City. For optimization of the network with GA, Pc and Pm vary from 0.5 to 0.9 by an increment of 0.1 and from 0.01 to 0.05 by an increment of 0.01, respectively, while fixing both the population size and the generation number to 100. This sensitivity analysis results in an optimum design of 22.3879 million dollars at the values of 0.8 and 0.01 for Pc and Pm, respectively. In addition, the probability of recombination (Pr) is introduced to check its applicability in the GA optimization of water distribution network. When Pr is 0.05 with the same values of Pc and Pm as above, the optimum design costs 20.9077 million dollars. This is lower than the cost of 22.3879 million dollars for the case of not using Pr by 6.6%. These results indicate that conducting a sensitivity analysis with parameter values and using Pr are useful in the optimization of WDN.

• Fisheries and Aquatic Sciences
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• v.3 no.3_4
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• pp.222-227
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• 2000

Fabrea salina living at salt pond is an interesting ciliate in the research of photobiology and live food for aquaculture. This study was carried out to understand the natural habitat of F. salina at salt pond, which would be a basic biological knowledge for the indoor mass culture of this ciliate. In this research, the water quality as temperature, salinity, dissolved oxygen, and chlorophyll-a was examined with the population density of the ciliate at salt pond. The highest population density of F. salina occurred at 109 ppt and $31^{\circ}C$with 2,390 inds./L in August, and the distribution of the ciliate was positively correlated with salinity, temperature, and chlorophyll­a. Even though F. salina is a very euryharine ciliate, it did not occur at the salinity below 47 ppt in this study. Its reason is able to be explained with the occurrence of many predators as small fish and food competitors as zooplankton living at low salinity of salt pont. While F. salina occurred with Anemia at the same habitat using the same food source, the optimum salinity for the ciliate was a little higher than that of Anemia, and the optimum temperature for the former was a little lower than that of the later. This should be a reason for that these two species have different ecological nich at the same habitat using the same food source.

• Korea journal of population studies
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• v.27 no.1
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• pp.171-201
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• 2004

Modern sciences in the West are deeply rooted in the Greek and Roman cultural heritage. Consequently, the academic achievements accomplished by the scholars of the Arabs including Persian world, the profound thoughts developed in the Indian subcontinent, and the excellent works made by the East Asian scholars have mostly been neglected in the past. This paper attempts to compare the thoughts and theories on population developed by the Western scholars with those of East Asian scolars, in chronological order, ancient, mediaeval, and modern period before Malthus. The thesis that excessive population growth may reduce output per worker, depress levels of living for the masses and engender strife is of great antiquity. In fact, overpopulation in East Asia, especially in China, goes back to very ancient times, most Confucian scholars maintained the notion of a numerical balance between population and environment. They also looked for means to check the increase in numbers. The foundations of a theory of optimum population level, fully developed in the twentieth century, can be found in their writings. Although early population thoughts in China had not advanced far in the analysis of the significance of population size and growth, it had taken only a few steps forward. At some times and to some observers, populousness appeared desirable; at other times and to other observers, it seemed all too evident that the number of people could become too great. These viewpoints foreshowed some of the later developments. The early population literatures reviewed here seem to consist of a number of quite isolated contributions. In fact, however, there may have been a greater continuity of thought than now appears, for many of the contributions may have been lost and there are many gaps in the record. An intensive review on comparing two works, those of Malthus' and Hong, Liang-chi's, are presented in this paper. Only five years before Malthus published his famous work, An Essay on the Principle of Population, Hong published his theories on population. Some of them, Hong insisted, are very similar to the Malthusian concepts of geometrical increase, natural and artificial checks of population. Despite the excellent works in the ancient period, this paper concludes with an investigation of the reasons why modem achievements in scientific areas in the East Asia have been far behind that of the West.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.324-333
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• 2013

The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.177-183
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• 2008

The particle swarm optimization(PSO) has been shown to converge rapidly during the initial stages of a global search, but around global optimum, the search process becomes very slow. On the other hand, the genetic algorithm is very sensitive to the initial population. In fact, the random nature of the GA operators makes the algorithm sensitive to initial population. This dependence to the initial population is in such a manner that the algorithm may not converge if the initial population is not well selected. In this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient and can find the optimal solution more accurately and with less computational time. Optimal location of SVC using this hybrid PSO-GA algorithm is found. We have also found the optimal place of SVC using GA and PSO separately and have compared the results. It has been shown that the new algorithm is more effective and efficient. An IEEE 68 bus test system is used for simulation.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1369-1377
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• 2020

Objective: The main objectives of the present study were to assess the genetic diversity, population structure and to appraise the efficiency of ongoing selective breeding program in the closed nucleus herd of Nellore sheep through pedigree analysis. Methods: Information utilized in the study was collected from the pedigree records of Livestock Research Station, Palamaner during the period from 1989 to 2016. Genealogical parameters like generation interval, pedigree completeness, inbreeding level, average relatedness among the animals and genetic conservation index were estimated based on gene origin probabilities. Lambs born during 2012 and 2016 were considered as reference population. Two animal models either with the use of F_i or ΔF_i as linear co-variables were evaluated to know the effects of inbreeding on the growth traits of Nellore sheep. Results: Average generation interval and realized effective population size for the reference cohort were estimated as 3.38±0.10 and 91.56±1.58, respectively and the average inbreeding coefficient for reference population was 3.32%. Similarly, the effective number of founders, ancestors and founder genome equivalent of the reference population were observed as 47, 37, and 22.48, respectively. Fifty per cent of the genetic variability was explained by 14 influential ancestors in the reference cohort. The ratio f_e/f_a obtained in the study was 1.21, which is an indicator of bottlenecks in the population. The number of equivalent generations obtained in the study was 4.23 and this estimate suggested the fair depth of the pedigree. Conclusion: Study suggested that the population had decent levels of genetic diversity and a non-significant influence of inbreeding coefficient on growth traits of Nellore lambs. However, small portion of genetic diversity was lost due to a disproportionate contribution of founders and bottlenecks. Hence, breeding strategies which improve the genetic gain, widens the selection process and with optimum levels of inbreeding are recommended for the herd.

• Journal of Animal Environmental Science
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• v.1 no.1
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• pp.65-75
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• 1995

This experiment was carried out to the effects of population density and C/N ratios of feed on the growth, reproductive effciency and cast producation of the earthworm(Eisenia foetida). The population densities of 50, 100, 150, 200 and 250 individuals of the earthworm fed with different C/N ratios of 25, 35, 45 and 55 cow manures were studied in rearing box($6,400cm^3$), and at the fertility stage during a period of 60 days. The results were summarized as follows; The survial rate(SR), increasing rate(IR), reproductive efficiency(RE) and cast production of the earthworms showed highest values in C/N ratio of 25. These results may indicate that C/N ratio of 25 is a very favourable feed for the growth of the earthworms. The survial rate(SR) indicated significant positive correlation with reproductive efficiency(RE) in different C/N ratios of feeds. The survial rate(SR) showed highest values in population densities of $50{\sim}100$ worms/$6,400cm^3(64.0{\sim}128.0cm^3/worm$). On the contrary, increasing rate(IR) tended to decreased with the increased population densities. The survival rate(SR) indicated significant negative correlation with reproductive efficiency(RE) in different population densities of the earthworms. The cast production estimated were $31.6mg{\sim}67.4mg/day/worm$ grown in optimum population densities($50{\sim}100\;worms/6,400cm^3$). The earthworm casting are an excellent soil conditioning material or organic fertilizer sources with a high chemical composition and their physical properties.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6276-6281
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• 2014

Genetic Algorithms (GAs) are efficient methods for search and optimization problems. On the other hand, there are some problems associated with the premature convergence to local optima of the multimodal function, which has multi peaks. The problem is related to the lack of genetic diversity of the population to cover the search spaces sufficiently. A sharing and crowding method were introduced. This paper proposed strategies to improve the convergence speed and the convergence to the global optimum for solving the multimodal optimization function. These strategies included the random generated sub-population that were well-distributed and spread widely through search spaces. The results of the simulation verified the effects of the proposed method.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.2
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• pp.178-182
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• 2011

Generally in order to reduce the steel weight of stiffened plate, stiffener spaces tend to be narrow and the plate gets thin. However, it will involve more fabrication cost because it can lead to the increase of welding length and the number of structural members. In the yard, the design which is able to reduce the total fabrication cost is needed, although it requires more steel weight. The purpose of this study is to find optimum stiffener spaces to minimize the fabrication cost for the cargo tank of LPG Carriers. Global optimization methods such as ES(Evolution Strategy) and GA(Genetic Algorithm) are introduced to find a global optimum solution and the sum of steel material cost and labor cost is selected as main objective function. Convergence degree of both methods in according to the size of searching population is examined and an efficient size is investigated. In order to verify the necessity of the optimum design based on the cost, minimum weight design and minimum cost design are carried out.