• Journal of The Korean Association For Science Education
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• v.31 no.3
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• pp.440-454
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• 2011

This study proposes a new instructional strategy and corresponding materials designed from various alternative frameworks to help students understand evolution as a biologically acceptable theory. Biology teachers have normally taught the evolutionary mechanism by means of comparing Lamarckism with natural selection. In this study, a new instructional strategy in which the Lamarckian explanation is first excluded because Lamarckism is known to be subsumed in a learner's cognitive structure as a strong preconception of evolution is suggested for teaching evolution. After mutation theory is introduced, Darwinism including natural selection is explained separately during the next class hour. Corresponding instructional materials that aid student understanding of the evolutionary mechanism were developed using recently published articles on human genetic traits as scientific evolutionary evidence instead of the traditional evolutionary subject matter, giraffe neck. Evolutionary evidence from human genetic traits allows students to exclude anthropocentric thoughts effectively and raise concern for the phenomenon of evolution positively. The administered instructional strategy and materials in this research improved student conception, concern, and belief of evolution and it is believed that they helped students understand the evolutionary mechanism effectively.

• Journal of Power Electronics
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• v.13 no.5
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• pp.877-883
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• 2013

This paper discussed a transformer-less shunt static synchronous compensator (STATCOM) with consideration of the following aspects: fast compensation of the reactive power, harmonic cancelation and reducing the unbalancing of the 3-phase source side currents. The STATCOM control algorithm is based on the theory of instantaneous reactive power (P-Q theory). A self charging technique is proposed to regulate the dc capacitor voltage at a desired level with the use of a PI controller. In order to regulate the DC link voltage, an off-line Genetic Algorithm (GA) is used to tune the coefficients of the PI controller. This algorithm arranged these coefficients while considering the importance of three factors in the DC link voltage response: overshoot, settling time and rising time. For this investigation, the entire system including the STATCOM, network, harmonics and unbalancing load are simulated in MATLAB/SIMULINK. After that, a 35KVA STATCOM laboratory setup test including two parallel converter modules is designed and the control algorithm is executed on a TMS320F2812 controller platform.

• Composites Research
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• v.20 no.1
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• pp.1-7
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• 2007

This study presents a methodology for optimization of static characteristics of golf club shafts. Stacking sequence for the optimal composite shaft performance is searched. A new objective function is defined for the simultaneous optimization of flexural and torsional stiffnesses. Classical lamination theory is used for the static analysis. As the optimization tool, genetic algorithm is applied with the stacking sequence as design. variables. With the optimal stacking sequence, dynamic characteristics of the shaft is also studied.

• Journal of Ship and Ocean Technology
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• v.5 no.3
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• pp.14-26
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• 2001

The shape of an industrial product has to be determined within the constrained conditions of keeping firmly many kinds of functional and performance requirements. On the other hand, the configuration of artistic work would be created desirably using the sense of aesthetics, even if conflicting slightly with these requirements. The development of a methodology for an aesthetic design founded on human sensitivity is becoming highly desirable in recent years. In this paper, a method of measuring beauty quantitatively for an artistic evaluation if proposed using the aesthetic cognitive theory and the optimum configuration could be found by a search using the genetic algorithm. Furthermore, an expression of optimum ship appearance can be gained as graphics.

• Korean Institute of Interior Design Journal
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• v.14 no.3 s.50
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• pp.64-72
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• 2005

The purpose of this study is to propose a topological design principles and to analyze the space of digital architecture applying topological invariant expressive characteristics. As this study is based on topology as a science of true world's pattern, we intented to explain the concepts and provide some methods of low-level and hyperspace topological invariant Properties. Four major aspects are discussed. Those are connection theory, boundary concept, homotopy group, knot Pattern theory as topological invariant properties. Then we intented to make understand topological characteristics of the Algorithms, luring machine, cellular automata, string theory, membrane, DNA and supramolecular chemistry. In fine, the topological invariant properties of the digital architecture as genetic algorithms based on self-organization and heterogeneous networks of interacting actors can be analyzed and used as a critical tool. Therefore topology can be provided endless possibilities for architecture, designers and scientists intended in expressing the more complex and organic patterns of nature as life.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.4 s.346
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• pp.58-66
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• 2006

This paper proposes an FSS(Frequency Selective Surface) design system that automatically derives design parameters minimally specified by engineers. The proposed system derives optimal design parameters through theory of electromagnetic scattering on FSS, database implemented from real data obtained from practically manufactured FSS, and GA(Genetic Algorithm) for optimizing design parameters. The system, at the first step, searches the best matching FSS within preconstructed DB with given characteristics specified by operators, and then sets initial genes from the searched FSS parameters. GA iterates the optimization process until the system finds the FSS design parameters that matches the characteristics specified by operators. The theory for the electromagnetic scattering on FSS is verified by comparing the simulation results with real data obtained by measuring system composed of horn antenna and receiver. The process for manufacturing the FSS is also included in the paper.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.2
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• pp.64-74
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• 2004

In order to accelerate the rate of consolidation settlement, to reduce settlement, and to increase bearing capacity for soft ground under quay wall, sand compaction pile method (SCP) has widely been applied. Improved ground is composite ground which is consisted of the sand pile-surrounding clayey soil. As caisson and upper structures are installed on SCP composite ground, the settlement is compositively occurred by elastic compression of sand compaction piles and also consolidation of the surrounding clay ground. In this study, the combined settlement model is proposed to predict the settlement of SCP composite ground in basis of elastic theory for sand compaction pile and consolidation theory for marine soft clay. Optimization technique was performed based on back-analysis so that real coded genetic algorithm was applied to estimate the parameters of the proposed settlement model. Case analysis was carried out for a domestic SCP composite ground to examine the applicability of the proposed prediction technique.

• Journal of the korean academy of Pediatric Dentistry
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• v.40 no.3
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• pp.203-208
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• 2013

Although the first case of supernumerary teeth had been documented almost 20 centuries ago, the etiology of supernumerary teeth still remains unclear. The prevalence of supernumerary teeth in the general Asian population is between 2.7% and 3.4%. The pathogenesis of supernumerary teeth has been attributed to phylogenetic reversion(atavism), splitting of the tooth bud(dichotomy theory), locally induced hyperactivity of the dental lamina and a combination of genetic and environmental factors(unified etiologic explanation). This report describes 3 cases of monozygotic twins with mesiodens who visited the pediatric dental clinic of Kyungpook national university hospital, and this is significant to support genetic factors involoved in the development of supernumerary teeth.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1479-1494
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• 2015

Since the Markowitz's mean-variance framework for portfolio analysis, the topic of portfolio optimization has been an important topic in finance. Traditional approaches focus on maximizing the expected return of the portfolio while minimizing its variance, assuming that risky asset returns are normally distributed. The normality assumption however has widely been criticized as actual stock price distributions exhibit much heavier tails as well as asymmetry. To this extent, in this paper we employ the genetic algorithm to find the optimal portfolio under the Value-at-Risk (VaR) constraint, where the tail of risky assets are modeled with the generalized Pareto distribution (GPD), the standard distribution for exceedances in extreme value theory. An empirical study using Korean stock prices shows that the performance of the proposed method is efficient and better than alternative methods.