• Environmental Analysis Health and Toxicology
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• v.14 no.4
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• pp.203-216
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• 1999

This paper describes a set of multi-pathway models for estimating health risk to lead. The models link concentrations of an environmental contaminant (lead) in air, water and food to human exposure through inhalation, ingestion, and dietary routes. Exposure is used as the foundation for predicting risk of health detriment within the population. The process of estimating exposure using often limited data and extrapolating to a large diverse population requires many assumption, inferences, and simplification. This paper is divided into four section. The first section provides lead contaminant levels on obtaining environmental concentration of air, tap water, and foods. The second section provides a discussion of exposure parameters and uncertainty associated predicting human health risk of contaminants. The third and fourth section illustrate lifetime average daily exposure (LADE) and excess cancer risk (ECR) based on exposure parameters. The relationship between concentration of lead in an environmental medium and human exposure is determined with pathway exposure factors (PEFs). The calculation of LADE and ECR is carried out using Monte-Carlo simulation with probability density function of exposure parameters. Examination of the result reveals that, for lead exposure, ingestion (food) is the dominant route of exposure rather than inhalation (air), and ingestion (tap eater).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.9-15
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• 2001

This paper describes a new method of Genetic Algorithms for Adaptive Fuzzy Control System. Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied to a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method.

• The Journal of the Acoustical Society of Korea
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• v.24 no.6
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• pp.309-316
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• 2005

This paper Presents the geoacoustic inversion with Parallel Multi-Population Genetic Algorithm (PMPGA). This method is the modified form of simple genetic algorithm (SGA), which is devised for complementing the defects of simple genetic algorithm. The light bulb source and vertical line array (VLA) receiver are used for geoacoustic inversion. The results of this study show the geoacoustic Parameters can be estimated by PMPGA and the proposed algorithm is 1.7 times as fast as serial one on an average.

• The Journal of Information Technology
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• v.5 no.4
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• pp.73-79
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• 2002

In this paper, I will propose the Niche-Meta Genetic Algorithm that has a multi-mutation operator for design of fuzzy controller. The gene in the proposed algorithm is formed by several parameters that represent the crossover rate, mutation rate and input-output membership functions. The optimization of fuzzy membership function is performed with local search on sub-population and the optimal structure is constructed with global search on total-population. The multi-mutation is selected under basis of the result of local evolution. A simulation for 2 D.O.F wheeled-mobile robot is showed to prove the efficiency of the proposed algorithm

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2119-2136
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• 2024

The rapid progress of social media allows more people to express their feelings and opinions online. Many data on social media contains people's emotional information, which can be used for people's psychological analysis and emotional calculation. This research is based on the simplified psychological scale algorithm of multi-theory integration. It aims to accurately analyze people's psychological emotion. According to the comparative analysis of algorithm performance, the results show that the highest recall rate of the algorithm in this study is 95%, while the highest recall rate of the item response theory algorithm and the social network analysis algorithm is 68% and 87%. The acceleration ratio and data volume of the research algorithm are analyzed. The results show that when 400,000 data are calculated in the Hadoop cluster and there are 8 nodes, the maximum acceleration ratio is 40%. When the data volume is 8GB, the maximum scale ratio of 8 nodes is 43%. Finally, we carried out an empirical analysis on the model that compute the population's psychological and emotional conditions. During the analysis, the psychological simplification scale algorithm was adopted and multiple theories were taken into account. Then, we collected negative comments and expressions about Japan's discharge of radioactive water in microblog and compared them with the trend derived by the model. The results were consistent. Therefore, this research model has achieved good results in the emotion classification of microblog comments.

• Korean Journal of Child Studies
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• v.30 no.6
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• pp.85-97
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• 2009

Korean society has been facing many challenges and promises resulting from the rapid population shifts into multi-cultural and multi-ethnic family composition. Government strived to respond to the impending demands and needs of Korean cultural families, in terms of marriage and birth, caring and educating children, and labor and work. This paper overviews the current state of Korean multicultural trends and facts in terms of family, marriage, children, and work. It also overarches major issues of multicultural studies of family relations and child development. By wrapping the facts and issues in current discourse and studies, pragmatic policy points were provided and condensed into some suggestions for the policy-making and program implementation.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.125-129
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• 2008

A new genetic algorithm for the solution of a multi-tasking problem is presented in this paper. The approach introduces innovative genetic operation that guides the genetic algorithm more directly towards better quality of the population. A wide variety of standard genetic parameters are explored, and results allow the comparison of performance for cases both with and without the new operator. The proposed algorithm improves the convergence speed by reducing the number of generations required to identify a near-optimal solution, significantly reducing the convergence time in each instance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.573-576
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• 2006

This paper deals with multi-objective optimization problem of finding a set of well-distributed solutions close to the true Pareto optimal solutions. In this paper, we present a two-leveled symbiotic evolutionary algorithm to efficiently solve the problem. Most of the existing multi-objective evolutionary algorithms (MOEAs) operate one population that consists of individuals representing the complete solution to the problem. The proposed algorithm maintains several populations, each of which represents a partial solution to the entire problem, and has a structure with two levels. The parallel search and the structure are intended to improve the capability of searching diverse and good solutions. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The experimental results confirm the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.3
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• pp.17-24
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• 1997

Broad-band RAM's (Radar absorbing materials) are designed by multi-layered lossy dielectrics. The depth, the relative permittivity and the loss tangent of each layer are optimized in order to meet the required reflective power over the specified frequency range using a genetic algorithm. The reflection coefficients are calculated by the continued fraction method. A new population model of the partial initialization method during iterations is applied for the multi-modal functions to enhance the performance of the genetic algorithm. The optimal RAN's are designed by setting the relative permittivity and the loss tangent of the dielectrics as a funtion of the frequency over 5~20GHz.