• Journal of Ocean Engineering and Technology
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• v.23 no.3
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• pp.1-5
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• 2009

It is necessary to develop an efficient optimization technique to optimize engineering structures that have given design spaces, discrete design values, and several design goals. In this study, an optimum algorithm based on the genetic algorithm was applied to the multi-object problem to obtain an optimum solution that simultaneously minimizes the structural weight and construction cost of panel blocks in ship structures. The cost model was used in this study, which includes the cost of adjusting the weld-induced deformation and applying the deformation control methods, in addition to the cost of the material and the welding cost usually included in the normal cost model. By using the proposed cost model, more realistic optimum design results can be expected.

• Korean Journal of Plant Taxonomy
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• v.37 no.4
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• pp.323-333
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• 2007

The degree to which parallel evolution utilizes the same genetic mechanisms indicates the degree to which developmental processes constrain or channel phenotypic evolution. A transgenetic strategy was used to elucidate the role of one floral meristem identity gene, LEAFY (LFY), in the evolution of rosette flowering, a plant architecture that has evolved in parallel in several lineages of the mustard family, Brassicaceae. The LFY genes from three rosette flowering species were cloned and introduced into a species with the ancestral architecture, and results indicated that changes at the LFY locus contributed to the evolution of rosette flowering in two of the three lineages, but that in each lineage a different set of genetic partners was involved. Also, LFY was shown to play a role in the evolution of flower size. Transgenetic strategy may be useful in the study of plant morphological evolution and parallelism.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1187-1188
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• 2008

An area of research called evolvable hardware has recently emerged which combines aspects of evolutionary computation with hardware design and synthesis. Evolvable hardware (EHW) is hardware that can change its own circuit structure by genetic learning to achieve maximum adaptation to the environment. In conventional EHW, the learning is executed by software on a computer. In this paper, we have studied and surveyed a gate-level evolvable hardware chip, by integrating both GA hardware and reconfigurable hardware within a single LSI chip. The chip consists of genetic algorithm(GA) hardware, reconfigurable hardware logic, and the control logic. In this paper, we describe the architecture, functions of the chip.

• Journal of Korean Association for Spatial Structures
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• v.13 no.3
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• pp.91-98
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• 2013

A multi-input single-output (MISO) semi-active control systems were studied by many researchers. For more improved vibration control performance, a structure requires more than one control device. In this paper, multi-input multi-output (MIMO) semi-active fuzzy controller has been proposed for vibration control of seismically excited small-scale buildings. The MIMO fuzzy controller was optimized by multi-objective genetic algorithm. For numerical simulation, five-story example building structure is used and two MR dampers are employed. For comparison purpose, a clipped-optimal control strategy based on acceleration feedback is employed for controlling MR dampers to reduce structural responses due to seismic loads. Numerical simulation results show that the MIMO fuzzy control algorithm can provide superior control performance to the clipped-optimal control algorithm.

• Advances in Computational Design
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• v.2 no.3
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• pp.241-256
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• 2017

This paper introduces the process for Multi-objective Optimization Framework (MOF) which mediates multiple conflicting design targets. Even though the extensive researches have shown the benefits of optimization in engineering and design disciplines, most optimizations have been limited to the performance-related targets or the single-objective optimization which seek optimum solution within one design parameter. In design practice, however, designers should consider the multiple parameters whose resultant purposes are conflicting. The MOF is a BIM-integrated and simulation-based parametric workflow capable of optimizing the configuration of building components by using performance and non-performance driven measure to satisfy requirements including build programs, climate-based daylighting, occupant's experience, construction cost and etc. The MOF will generate, evaluate all different possible configurations within the predefined each parameter, present the most optimized set of solution, and then feed BIM environment to minimize data loss across software platform. This paper illustrates how Multi-objective optimization methodology can be utilized in design practice by integrating advanced simulation, optimization algorithm and BIM.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.7
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• pp.938-943
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• 2016

Development of body hair is an important physiological and cellular process that leads to better adaption in tropical environments for dairy cattle. Various studies suggested a major gene and, more recently, associated genes for hairy locus in dairy cattle. Main aim of this study was to i) employ a variant of the discordant sib pair model, in which half sibs from the same sires are randomly sampled using their affection statues, ii) use various single marker regression approaches, and iii) use whole genome regression approaches to dissect genetic architecture of the hairy gene in the cattle. Whole and single genome regression approaches detected strong genomic signals from Chromosome 23. Although there is a major gene effect on hairy phenotype sourced from chromosome 23: whole genome regression approach also suggested polygenic component related with other parts of the genome. Such a result could not be obtained by any of the single marker approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

• Nuclear Engineering and Technology
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• v.49 no.8
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• pp.1696-1710
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• 2017

An improved Reactor Regulating System (RRS) logic architecture, which is combined with genetic algorithm (GA), is implemented in this work. It is devised to provide an optimal solution to the current RRS. The current system works desirably and has contributed to safe and stable nuclear power plant operation. However, during the ascent and descent section of the reactor power, the RRS output reveals a relatively high steady-state error, and the output also carries a considerable level of overshoot. In an attempt to consolidate conservatism and minimize the error, this work proposes to apply GA to RRS and suggests reconfiguring the system. Prior to the use of GA, reverse engineering is implemented to build a Simulink-based RRS model. Reengineering is followed to produce a newly configured RRS to generate an output that has a reduced steady-state error and diminished overshoot level. A full-scope APR1400 simulator is used to examine the dynamic behaviors of RRS and to build the RRS Simulink model.

• Genomics & Informatics
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• v.12 no.4
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• pp.136-144
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• 2014

Besides single-nucleotide variants in the human genome, large-scale genomic variants, such as copy number variations (CNVs), are being increasingly discovered as a genetic source of human diversity and the pathogenic factors of diseases. Recent experimental findings have shed light on the links between different genome architectures and CNV mutagenesis. In this review, we summarize various genomic features and discuss their contributions to CNV formation. Genomic repeats, including both low-copy and high-copy repeats, play important roles in CNV instability, which was initially known as DNA recombination events. Furthermore, it has been found that human genomic repeats can also induce DNA replication errors and consequently result in CNV mutations. Some recent studies showed that DNA replication timing, which reflects the high-order information of genomic organization, is involved in human CNV mutations. Our review highlights that genome architecture, from DNA sequence to high-order genomic organization, is an important molecular factor in CNV mutagenesis and human genomic instability.

• Korean Institute of Interior Design Journal
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• v.15 no.1 s.54
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• pp.30-38
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• 2006

The new aspect of contemporary architectural design is the computer simulation of morphogenesis and evolution of the organic body. Morphogenesis and evolution is the kind of emergence that is the process of complex pattern formation from simpler rules in complex system. The development comprises the sequence of pattern formation, differentiation, morphogenesis, growth. This study analyzes the application methodology of various biomorphism in contemporary architecture. The methods of generative application by computation in architecture are self-organization, differentiation, growth algorithm via MoSS. And the methods of evolution by computation are genetic algorithm, multi-parameter in environments, phylogenetic cross-over, competing as natural selection, mutation+external constraints, generative algorithm+genetic algorithm via Genr8.