• Korean Journal of Cognitive Science
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• v.7 no.3
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• pp.37-60
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• 1996

From the biopsychological point of view,learning could be defined as the processes to transfer the information that we obtain from environment to the neural circuits in the brain.In the studies to determine the biological substrates of learning and memory,there was a remarkable effort to identify neural circuits related with a specific type of learning and to describe the mechanixm of neural plasticity of learning and memory,under the assumption that the memory orinformation may be stored as a modificationof neural synapes in the central nerviys system.On the other hand,there was a different kind of tendency to analyze the mechanism of interactions between neural substrates involved in learning and memory,under the assumption that a specific information may be represented in the patterns of comples neural network of the central nervous system.The present review,in the former position.focused on the research methods and the chracteristics and finding of the investigations employing animal model systems to indentify the essential site of engram for learning and memory.Specifically,the review presents major advances in ourunderstanding of the memory trace circuit for a specific type of learning,with the use of animal model system,the detemination of the critical lodi of neuaral plastic chabges In learing abd memory,and the neurophysiological an biocemical mechanixms of the neural modifia by learint.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2C
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• pp.81-88
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• 2006

This study performed field and laboratory tests for poor subsoils taken in six regions of the country and determined undrain shear strength. Su values and preconsolidation pressure are predicted using Back Propagation neural network (BPNN) and the application of BPNN is verified. The result of BPNN shows that correlation coefficient between test and neural network result is over 0.9, which means high correlativity. Especially the neural network uses only 6 parameters such as natural water content, void ratio, specific gravity, rate of passing 200th sieve, liquid limits and plasticity index among various affecting factors to estimate value and the correlation coefficent is 0.93. The conclusions obtained in this paper are from the tests performed for poor subsoils taken in the several regions of the country. If there were more test results, the prediction and influence of various soil properties could be effectively performed by neural network.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.6
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• pp.356-362
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• 2019

Scutellaria baicalensis (SB) has widely used in the treatment for various brain diseases in the field of Oriental medicine. Biofermantation of SB can make major chemical constituents of SB to pass blood-brain barrier easily and to have more potent anti-oxidant ability. There is a little information about the contribution of fermented SB (FSB) to the formation or maintenance of the neural plasticity in the hippocampus. The purpose of this study was to evaluate effects of FSB extract on hydrogen peroxide (H₂O₂) - induced impairments of the induction and maintenance of long-term potentiation (LTP), an electrophysiological marker for the neural plasticity in the hippocampus. From hippocampal slices of rats, the field excitatory postsynaptic potentials (fEPSPs) were evoked by the electrical stimulation to the Schaffer collaterals - commissural fibers in the CA1 areas and LTP by theta-burst stimulation by using 64 - channels in vitro multi-extracellular recording system. In order to induce oxidative stress to hippocampal slices two different concentrations (200, 400 μM) of H₂O₂ were given to the perfused aCSF before and after the LTP induction, respectively. The ethanol extract of FBS with concentration of 25 ㎍/ml, 50 ㎍/ml was diluted in perfused aCSF that had 200 μM H₂O₂, respectively. Oxidative stress by the treatment of H₂O₂ resulted in decrease of the induction rate of LTP in the CA1 area with a dose - dependent manner. However, the ethanol extract of FSB prevented the reduction of the induction rate of LTP caused by H₂O₂ - induced oxidative stress with a dose - dependent manner. These results may support a potential application of FSB to ameliorate impairments of hippocampal dependent neural plasticity or memory caused by oxidative stress.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.59-65
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• 2022

Rodent model for chronic cerebral hypoperfusion caused by bilateral carotid artery occlusion (BCAO) show clinically relevant evidences for vascular dementia and impairments of synaptic plasticity in the hippocampus. The purpose of this study was to evaluate effect of fermented garlic (F-Garlic) extract with NO metabolites on cognitive behaviors, synaptic plasticity, and molecular events in the hippocampus following BCAO. Adult male Sprague-Dawley rats were randomly divided three experimental groups into: control+water; BCAO+water; BCAO+F-Garlic. Animals were treated with oral administration of F-Garlic in tap water as a drinking water after surgery for 4 weeks. On passive avoidance test and Y-maze test, BCAO+water showed a significant decrease in step-through latency and spontaneous alteration, indicating deficit of hippocampal memory formation but the treatment of F-Garlic significantly increased these cognitive behaviors. In control+water, a robust increase in the amplitude of evoked field excitatory postsynaptic potentials was observed by theta burst stimulation to hippocampal neural circuit indicating formation of long-term potentiation (LTP) in the hippocampal CA1. BCAO+water showed a highly significant deficit in LTP induction 4 weeks after BCAO. On other hand, daily oral administration of F-Garlic extract caused the marked preservation of LTP induction. Moreover, parvalbumin was markedly reduced in the CA1, especially, in the stratum radiatum of BCAO+water. In contrast, BCAO+F-Garlic mitigate a significantly reduction of the parvalbumin. In summary, these results suggest that daily oral administration of F-Garlic extract can ameliorate cognitive memory deficit through the preservation of synaptic plasticity and interneurons integrity in the hippocampus in rodent model of chronic cerebral hypoperfusion.

• Korean Journal of Acupuncture
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• v.35 no.4
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• pp.187-202
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• 2018

Objectives : Non-invasive transcranial electrical stimulation is one of therapeutic interventions to change in neural excitability of the cortex. Transcranial electro-acupuncture (TEA) can modulate brain functions through changes in cortical excitability as a model of non-invasive transcranial electrical stimulation. Some composites of fermented Scutellaria baicalenis (FSB) can activate intercellular signaling pathways for activation of brain-derived neurotrophic factor that is critical for formation of neural plasticity in stroke patients. This study was aimed at evaluation of combinatory treatment of TEA and FSB on behavior recovery and cortical neural excitability in rodent focal stroke model. Methods : Focal ischemic stroke was induced by photothrombotic injury to the motor cortex of adult rats. Application of TEA with 20 Hz and $200{\mu}A$ in combination with daily oral treatment of FBS was given to stroke animals for 3 weeks. Motor recovery was evaluated by rotating bean test and ladder working test. Electrical activity of cortical pyramidal neurons of stroke model was evaluated by using multi-channel extracellular recording technique and thallium autometallography. Results : Compared with control stroke group who did not receive any treatment, Combination of TEA and FSB treatment resulted in more rapid recovery of forelimb movement following focal stroke. This combination treatment also elicited increase in spontaneous firing rate of putative pyramidal neurons. Furthermore expression of metabolic marker for neural excitability was upregulated in peri-infract area under thallium autometallography. Conclusions : These results suggest that combination treatment of TEA and FSB can be a possible remedy for motor recovery in focal stroke.

• Transactions of Materials Processing
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• v.19 no.1
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• pp.5-10
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• 2010

The current understanding for phase/grain boundary sliding and low-temperature/high-strain rate superplasticity of two-phase titanium alloys is summarized. The quantitative analysis on boundary sliding revealed increased sliding resistance on the order of ${\alpha}/{\beta}\;\ll\;{\alpha}/{\alpha}\;{\approx}\;{\beta}/{\beta}$ boundary, hence, led to the conclusion that approximately 50% alpha(or beta) volume fraction and/or grain refinement is beneficial for obtaining large superplastic elongation at low temperature and/or high strain rate. To predict the temperature for 50% alpha volume in various alpha/beta Ti, artificial neural network was applied. Finally, much enhanced superplasticity was achieved through grain refinement utilizing dynamic globularization.

• Transactions of Materials Processing
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• v.7 no.2
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• pp.127-138
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• 1998

Process design of multi-step wire drawing process, conducted by means of finite element analysis and ANN(Artificial Neural Network) has been considered. The investigated problem involves the ade-quate selection of the drawing die angle and the correspondent reduction rate in the condition of desired initial and final diameter. Combinations of the process parameters which are used in finite ele-ment simulation are selected by using the orthogonal array. Also the orthogonal array. Also the orthogonal array and the results of finite element simulation which are related to the process energy are used as train data of ANN. In this study it is shown that the application of new technique using ANN and Othogonal array table to the process design of metal forming process is useful method.

• Transactions of Materials Processing
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• v.11 no.4
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• pp.341-348
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• 2002

For the light guide plate of the TFT-LCD, there have been increasing demands for higher brightness, thin and light-weight design, and lower power consumption. To meet these demands, a micro-prism-type frontlight that integrates a prismatic sheet and a light-guiding plate has been developed. In this paper, the influences of processing conditions on the brightness were studied lot the injection molding of the light guide plate. Based on the experiment with an actual mold, the design of experiments and the neural network theory were used lot choosing the optimal processing parameters to increase the brightness and the uniformity. The verification experiment also showed that the brightness and the uniformity were increased dramatically with the chosen processing conditions.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.223-240
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• 1998

The purpose of this paper is to develop the pattern recognition system with a 'Robust' concept to be applicable to flexible manufacture automation in practice. The 'Robust' concept has four meanings as follows. First, pattern recognition is performed invariantly in case the object to be recognized is translated, scaled, and rotated. Second, it must have strong resistance against noise. Third, the completely learned system is adjusted flexibly regardless of new objects being added. Finally, it has to recognize objects fast. To develop the proposed system, contouring, spectral analysis and Fuzzy ART neural network are used in this study. Contouring and spectral analysis are used in preprocessing stage, and Fuzzy ART is used in object classification stage. Fuzzy ART is an unsupervised neural network for solving the stability-plasticity dilemma.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2525-2527
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• 2004

This paper classify using Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter $\rho$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter setting criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one. And this paper goal is the input pattern cognition and classification using neural network.