• Molecules and Cells
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• v.39 no.10
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• pp.715-721
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• 2016

Plants have become physiologically adapted to a seasonally shifting environment by evolving many sensory mechanisms. Seasonal flowering is a good example of adaptation to local environmental demands and is crucial for maximizing reproductive fitness. Photoperiod and temperature are major environmental stimuli that control flowering through expression of a floral inducer, FLOWERING LOCUS T (FT) protein. Recent discoveries made using the model plant Arabidopsis thaliana have shown that the functions of photoreceptors are essential for the timing of FT gene induction, via modulation of the transcriptional activator CONSTANS (CO) at transcriptional and post-translational levels in response to seasonal variations. The activation of FT transcription by the fine-tuned CO protein enables plants to switch from vegetative growth to flowering under inductive environmental conditions. The present review briefly summarizes our current understanding of the molecular mechanisms by which the information of environmental stimuli is sensed and transduced to trigger FT induction in leaves.

• Geotechnical Engineering
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• v.8 no.4
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• pp.51-66
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• 1992

As the scale of public works get recently larger and diversified. the construction of retain- ing walls is required for the effective use of land. In the design of the retaining wall, the reliability and fitness of the retaining wall itself are regarded prudently although there is a tendency to ignore the importance of backfill. In this study, the experiments under various conditions such as repetition-continuity-load, roller-press load, and working space of backfill, are carried out using a model retaining wall similar to the real system. The experimental roes tilts are interpreted theoretically, Using a computer program, the experimental results are analyzed and compared with other theoretical wonts.

• Journal of Technologic Dentistry
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• v.38 no.3
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• pp.185-191
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• 2016

Purpose: The purpose of this study were to evaluate the quality of dental prostheses printed by 3-dimensional printing system. Methods: Mater model was prepared and ten study models were fabricated. Ten single crowns were printed by 3D-printing system(Resin group) and another ten single crowns using casting method were manufactured(Metal group). The marginal adaptation of single crowns were measured using by silicone replica technique. Silicone replicas were sectioned four times. The marginal adaptations were evaluated using by digital microscope. Statistical analyses were performed with Mann-Whitney test(${\alpha}=0.05$). Results: $Mean{\pm}standard$ deviations of all marginal adaptations were $92.1(20.0){\mu}m$ for Metal group and $69.7(12.3){\mu}m$ for Resin group. Two groups were no statistically significant differences(p>0.05). Conclusion: Marginal adaptation of single crowns printed by 3D-printing system were ranged within the clinical recommendation.

• Bulletin of the Korean Chemical Society
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• v.27 no.2
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• pp.266-272
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• 2006

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.81-84
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• 1998

Genetic Algorithms (GAs) are stochastic algorithms whose search methods model some natural phenomena. The procedure of GAs may be divided into two sub-procedures : Operation and Selection. Chromosomes can produce new offspring by means of operation, and the fitter chromosomes can produce more offspring than the less fit ones by means of selection. However, operation which is executed randomly and has some limits to its execution can not guarantee to produce fitter chromosomes. Thus, we propose a method which gives a directional information to the genetic operator by reinforcement learning. It can be achived by using neural networks to apply reinforcement learning to the genetic operator. We use the amount of fitness change which can be considered as reinforcement signal to calcualte the error terms for the output units. Then the weights are updated using backpropagtion algorithm. The performance improvement of GAs using reinforcement learning can be measured by applying the pr posed method to GA-hard problem.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1146-1150
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, initial values are determined by the Switched Reluctance Motor of system and Ziegler-Nichols method. After deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the neural network and multiple regression model method in characteristic of output, and has extent of applying without limit of initial parameters.

• Korean Journal of Child Studies
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• v.27 no.3
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• pp.271-284
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• 2006

In order to define their relative influence, this study analyzed causal relationships between academic achievement of elementary school students and such related variables as self-esteem and the psychological and economic environment of the home, including clarification of other significant variables affecting academic achievement. Participants were a sample of 485 5th grade students from 8 elementary schools in Busan. Correlation, analysis of covariance structure modeling, and model-fitness tests were applied to the data. Results indicated that the psychological environment of the home has the most significant influence on the academic achievement of children, and the economic environment of the home and self-esteem have relatively low or indirect influence.

• Bulletin of the Korean Chemical Society
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• v.27 no.11
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• pp.1741-1746
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• 2006

3D-QSARs on the neuroblocking activities by 1-(6-chloro-3-pyridylmethyl)-2-nitroiminoimidazolidine analogues as agonist at the nicotinic acetylcholine receptor (nAChR) were studied quantitatively using CoMFA and CoMSIA methodologies. The statistical results of CoMFA (A5: $r^2\;_{cv.}\;=\;0.707\;&\;r^2\;_{ncv.}$= 0.986) and CoMSIA model (A3: $r^2\;_{cv.}$ = 0.715 & $r^2\;_{ncv.}$ = 0.961) showed the best predictability and fitness for neuroblocking activity based on the cross-validated value and non-cross validated value. The steric and H-bond acceptor nature of a compound were essential for high activity. The study on 3D-QSARs between substrate molecules and their neuroblocking activities appears to be an useful approach for designing better neuroblocking drug development.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.420-426
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• 1998

Evolutionary algorithms are probabilistic optimization algorithms based on the model of natural evolution. Recently the efforts to improve the performance of evolutionary algorithms have been made extensively. In this paper, we introduce the research for improving the convergence rate and search faculty of evolution algorithms by using reinforcement learning. After providing an introduction to evolution algorithms and reinforcement learning, we present adaptive genetic algorithms, reinforcement genetic programming, and reinforcement evolution strategies which are combined with reinforcement learning. Adaptive genetic algorithms generate mutation probabilities of each locus by interacting with the environment according to reinforcement learning. Reinforcement genetic programming executes crossover and mutation operations based on reinforcement and inhibition mechanism of reinforcement learning. Reinforcement evolution strategies use the variances of fitness occurred by mutation to make the reinforcement signals which estimate and control the step length.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.275-280
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• 2009

A Genetic Algorithm (GA) is a kind of search techniques used to find exact or approximate solutions to optimization and searching problems. This paper discusses the design of a genetic algorithm-based intelligent parking system. This is a search strategy based on the model of evolution to solve the problem of parking systems. A genetic algorithm for an optimal solution is used to find a series of optimal angles of the moving vehicle at a parking space autonomously. This algorithm makes the planning simpler and the movement more effective. At last we present some simulation results.