• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.11-22
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• 2023

A radiating elements fault diagnosis method with simplified radiation pattern measurement procedure was presented for planar active phased array antenna system. For presenting the mentioned method, the technique for linear approximation based on the radiation characteristics of a planar array configuration and a technique for solving a unique solution problem that occur in process of diagnosing a fault in a radiating elements were presented. Based on the presented method and a genetic algorithm, experimental simulations were performed for radiating element defect diagnosis according to various planar active phased array antenna configurations. As a result, it was confirmed that the presented radiating element fault diagnosis method can be smoothly applied to planar active phased antennas having various configurations.

• Journal of Educational Research in Mathematics
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• v.13 no.3
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• pp.351-364
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• 2003

by A.C. Clairaut is the first geometry textbook based on the historico-genetic principle against the logico-deduction method of Euclid's This paper aims to recognize Clairaut's historico-genetic principle by inquiring into this book and to search for its applications to school mathematics. For this purpose, we induce the following five characteristics that result from his principle and give some suggestions for school geometry in relation to these characteristics respectively : 1. The appearance of geometry is due to the necessity. 2. He approaches to the geometry through solving real-world problems.- the application of mathematics 3. He adopts natural methods for beginners.-the harmony of intuition and logic 4. He makes beginners to grasp the principles. 5. The activity principle is embodied. In addition, we analyze the two useful propositions that may prove these characteristics properly.

• 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.

• Interdisciplinary Bio Central
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• v.6 no.4
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• pp.2.1-2.7
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• 2014

Sexual dimorphism in intelligence suggests that this phenotype is a sexually selected trait. This view is supported by an overrepresentation (compared to the autosomal genome) of genes affecting cognition on the X chromosome. The aim of this study is to test the hypothesis that sexual selection can explain sex and country-level differences in performance on tests of fluid intelligence. Nationally representative samples from N = 44 countries were obtained from the Programme for International Student Assessment (PISA) Creative Problem Solving (CPS), which evaluates the core of intelligence, that is novel problem solving ability. Sexual selection has the double effect of increasing the prevalence of a favored phenotype and reducing genetic variation in sexually selected traits. Matching these predictions from evolutionary theory, the average country fluid intelligence is positively correlated to sexual dimorphism after partialling out per capita GDP and the latter in turn is inversely correlated to variance in intelligence scores within populations. Males have a higher variance than females but there is a negative correlation between male-female difference in variance and sexual dimorphism in intelligence, suggesting that selection reduces variance more in the selected sex. Average country male height is negatively correlated to sexual dimorphism in intelligence, a fact that supports the notion of a trade-off between physical and intellectual competition in the context of access to females. The results of this study, if replicated, imply that genome-wide association studies of cognition may benefit from a focus on sex chromosomes, which so far have been neglected. Another implication of this study is that intelligence has continued to evolve after different human populations migrated out of Africa and possibly up to the 19th century, as suggested by the substantial variability in sex differences even between neighbouring countries.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.233-238
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• 2003

Living creatures maintain their variety through speciation, which helps them to have more fitness for an environment. So evolutionary algorithm based on biological evolution must maintain variety in order to adapt to its environment. In this paper, we utilize the concept of speciation. Each individual of population creates their offsprings using mutation, and next generation consists of them. Each individual explores search space determined by mutation. Useful search space is extended by differentiation, then population explorers whole search space very effectively. If evolvable hardware evolves through mutation, it is useful way to explorer search space because of less varying inner structure. We verify the effectiveness of the proposed method by applying it to two optimization problems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.396-398
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• 2003

This paper presents the scheme for load model based dispersed generation system (DGs) installation and operation in unbalanced distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The main idea of solving fuzzy nonlinear goal programming is to transform the original objective function and constraints into the equivalent multiple objective functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithms. The method proposed was applied to IEEE 13 bus test systems to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2339-2341
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• 1998

This paper is concerned with an energy optimization for the walking of IWR biped robot. The movement of balancing joints are determined by ZMP(Zero Moment Point) and dynamic properties caused by motion of a swing leg. Therefore, ZMP positions have an important role in walking and guarnateeing the stability of a robot. A genetic algorithm is utilized for solving this problem and finding ZMP with a minimum energy at each sampling time during the walk. In this study, we performed an energy optimization with desired ZMP trajectories and motion of balancing joints.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.70-77
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• 2000

This paper proposes a method of solving a unit commitment problem using tabu search (TS) which is heuristic algorithm. Ts is a local search method that starts from any initial solution and attempts to determine a better solution using memory structures. In this paper, to reduce the computation time for finding the optimal solution, changing tabu list size as intensification strategy and path relinking method as diversification strategy are proposed. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with priority list, genetic algorithm(GA), and hybrid GA.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2122-2125
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• 2008

Because the reheating furnace consumes a large amount of energy to heat up the slabs, it is very important to find an optimal temperature patterns in the furnace for energy saving as well as uniform target temperature at the exit of the furnace. In this study, the temperature profiles in the slab are determined by solving the transient one-dimensional heat conduction equation in conjunction with boundary conditions with total heat exchange factors. The optimal temperature patterns are obtained to minimize the fuel consumption with satisfying the predetermined constraint conditions. The design optimization is performed by using a genetic algorithm and the optimal results are validated with results obtained from the PIDO tool, called as P.I.A.n.O.