• Journal of The Korean Association For Science Education
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• v.44 no.5
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• pp.531-545
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• 2024

The purpose of this study was to develop instructional programs aimed at enhancing middle school students' understanding of evolutionary concepts using a step-by-step writing strategies and an applicable evaluation rubric for evolutionary concepts. To achieve this, a step-by-step writing instructional model (PEECE) was devised as a method for scientific writing, and essential evolutionary core concepts were selected considering the middle school curriculum's coverage of biological evolution. Six evolutionary core concepts-variation, inheritance of variation, differential survival and reproduction, microevolution, and macroevolution-were chosen, with each serving as the focus of a lesson in a four-lesson program following the PEECE lesson model. The program was implemented with 16 students in a co-curricular middle school class. Pre- and post-lesson evolutionary concept checklists were administered to diagnose and compare the level of evolutionary concept understanding. Additionally, students' writing materials for each evolutionary core concept were collected, scored using an evolutionary concept evaluation rubric, and thoroughly analyzed. The results indicated that the step-by-step writing strategy effectively enhanced understanding of the six evolutionary core concepts and reduced cognitive biases and misconceptions about evolution. Contrasted with the optional evolution concept test, the descriptive writing activity provided a more tangible insight into students' scientific concepts, biases, and misconceptions, facilitating teachers' assessment of understanding and feedback provision. Moreover, the jointly developed evaluation rubric offered specific scoring criteria, enabling objective assessment without subjective influence, allowing analysis and scoring of students' writing materials across evaluation areas for collecting fundamental data.

• Korean Journal of Child Studies
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• v.26 no.5
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• pp.185-204
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• 2005

This paper demonstrated how application of evolutionary knowledge to developmental perspectives enhances understanding of human ontogeny. Evolutionary Developmental Psychology (EDP) explains human behavior through evolutionary principles and focuses on ontogeny rather than phylogeny. In this paper, the authors review concepts of evolution, adaptations, and the processes of evolution from EDP perspectives. The definition and basic assumptions of EDP are introduced, followed by explanations of how evolution happens in ontogeny by looking at developmental systems approaches, concepts of ontogenetic and deferred adaptations, evolution of childhood, and brain plasticity. Possible pathways of evolution in ontogeny are also discussed. Finally, some research methodology for applying EDP to child development is suggested with specific hypotheses and studies.

• Biomolecules & Therapeutics
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• v.25 no.1
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• pp.57-68
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• 2017

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.567-578
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• 2022

In this study, we examine whether the description of the elementary science curriculum guide, the concept of evolution, and the beliefs of teachers affect the teaching practice in classes related to adaptation of elementary school teachers. First, we examined the alternative concept among the sentences described in the bio-adaptation-related unit of the 2009 Elementary Science Curriculum Teacher's Guide and identified the effects of this description on the teaching practice of elementary school teachers. Next, six elementary school teachers were classified according to the results of the evolutionary concept test paper and the evolutionary belief test paper, and based on the class recording data and interview data, whether there is a difference in teaching execution. As a result, it was confirmed that there were a total of 18 descriptions corresponding to the concept of evolutionary alternatives in the analysis of instruction descriptions, and that these descriptions influenced elementary school teachers' adaptation concepts and teaching practice. Next, the group with high and low levels of evolution differ in the areas of "recognition of importance in the unit, distinction between adaptation concepts in the general sense and adaptation concepts in the biological sense, errors in the class," and "recognition of evolutionary education needs in the elementary curriculum." This study is meaningful in that it qualitatively confirms the research on the evolution concept of elementary school teachers, which has been approached quantitatively, and in-depth, confirms how the description, evolution concepts, and evolutionary beliefs affect elementary school teachers' biological adaptation concepts.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.1
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• pp.95-110
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• 1998

Evolutionary Algorithms (EAs) are population-based optimization methods based on the principle of Darwinian natural selection. The representative methodology in EAs is genetic algorithm (GA) proposed by J. H. Holland, and the theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the meaning of these foundational concepts, simple genetic algorithm (SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithm. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. And predator-prey co-evolution and symbiotic co-evolution, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. And the experimental results show a co-evolutionary algorithm works well in optimization problems even though in deceptive functions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.107-110
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• 2000

In this paper, we propose a method of constructing neural networks using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series.

• Journal of Global Scholars of Marketing Science
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• v.7
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• pp.71-103
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• 2001

Marketing practice varies among firms. However, the prescriptive literature emphasises a universal view of practice, a 'one size fits all' view. This paper addresses the issue of explaining diversity in marketing practice in competitive space and in time. Diversity in competitive space reflects the existence of different routes to high performance. Diversity in time reflects some combination of change in the individual firm and change in a population of firms. In the former case, diversity is shaped by organisational change; in the latter by the disbandment and founding of firms in the population. In so far as diversity is the norm, the manner in which practice will be shaped by evolutionary processes is considered. Fnally, the role of the academy as one of the forces driving the evolutionary process is discussed. Miles and Snow's (1978, 1986) work is taken as a main point of departure in the search for explanation and ecological and evolutionary concepts are drawn on for support and to suggest an explanation for the nature of diversity over time.

• International Journal of Fluid Machinery and Systems
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• v.10 no.3
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• pp.264-273
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• 2017

In order to be able to predict the maximum Annual Energy Production (AEP) for tidal power plants, an AEP optimization tool based on Evolutionary Algorithms was developed by ANDRITZ HYDRO. This tool can simulate all operating modes of the units (bi-directional turbine, pump and sluicing mode) and provide the optimal plant operation that maximizes the AEP to the control system. For the Swansea Bay Tidal Power Plant, the AEP optimization evaluated all different hydraulic and operating concepts and defined the optimal concept that led to a significant AEP increase. A comparison between the optimal plant operation provided by the AEP optimization and the full load operating strategy is presented in the paper, highlighting the advantage of the method in providing the maximum AEP.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.224-227
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• 2000

In this Paper, we prepose a method of constructing neural networks using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series, Sun spot data and KOSPI data.

• World Technopolis Review
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• v.3 no.2
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• pp.66-77
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• 2014

This paper aims at exploring a conceptual framework of analyzing the evolutionary processes of regional economies by reconciling the notion of regional resilience and the concepts prevailing in the disciplines of evolutionary economics and geography. The resilience framework appears to offer a promising outlet with which combination of the seemingly contradictory conceptions is made possible. It can address why some regions manage to adapt to external shocks, renew themselves, or lock out themselves, while others are more locked in decline. In addition, it can also explain how the spatial organization of economic production, distribution, and consumption is transformed over time. Then, regional economic resilience, together with its accompanying vehicle of panarchy, emerges as a workable framework of explaining regional differentiation in regional economic performance and trajectories. Despite the risk of being a fuzzy concept, the resilience conception can be properly operationalized to provide policy principles of regional economic innovation adjusted to region-specific contexts.