• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.255-258
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• 2001

This paper is implementation of cellular automata neural network system which is a living creatures' brain using evolving hardware concept. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogeny of natural living things. The proposed system developes each cell's state in neural network by CA. And it regards code of CA rule as individual of genetic algorithm, and evolved by genetic algorithm. In this paper we implement this system using evolving hardware concept Evolving hardware is reconfigurable hardware whose configuration is under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system is verified by applying it to time-series prediction.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.255-262
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• 1998

The neural network can roughly be classified as the specialized control, indirect control and general schemes. Neural network is adopted for MPPT of solar array. And back propagation algorithm also is used to train neural network controller. We investigate the possibilities of $P_{max}$ control using the neural networks, and then we also examine about operating the solar cell at an optimal voltage comprise of temperature compensated voltage with boost converter. Proposed boost converter of MPPT system is studied by simulation and is implemented by using a microprocessor(80c196kc) which controls duty ratio of the boost converter.

• Molecules and Cells
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• v.41 no.5
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• pp.373-380
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• 2018

Synapses and neural circuits form with exquisite specificity during brain development to allow the precise and appropriate flow of neural information. Although this property of synapses and neural circuits has been extensively investigated for more than a century, molecular mechanisms underlying this property are only recently being unveiled. Recent studies highlight several classes of cell-surface proteins as organizing hubs in building structural and functional architectures of specific synapses and neural circuits. In the present minireview, we discuss recent findings on various synapse organizers that confer the distinct properties of specific synapse types and neural circuit architectures in mammalian brains, with a particular focus on the hippocampus and cerebellum.

• 대한생식의학회:학술대회논문집
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• 2002.05a
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• pp.74.2-75
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• 2002

• 대한생식의학회:학술대회논문집
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• 2002.05a
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• pp.91.2-92
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• 2002

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.1-10
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• 2005

In this paper, 150W photovoltaic system using neural network tracker is proposed, the system designed as the normal line of the solar cell always runs parallel the ray of the sun. This design can minimize the cosine loss of the system output results of solar cell are sensitive to the change of weather and insolation condition don't react rapidly to parameter condition change such as system circumstance and deterioration. To achieve precise operation of photovoltaic tracker system using method of intelligent control, Neural Network is used in the design of the photovoltaic tracker system drive. The control performance of this system drive influenced by the environment parameter such as weather condition and motor parameter variations. we used synchronous motor in this tracker and the experimental results show that the fixing system shows 10,159[Wh] and tracking system shows 12,360[Wh] electricity.

• Molecules and Cells
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• v.38 no.9
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• pp.806-813
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• 2015

Gaucher disease (GD) is an autosomal recessive lysosomal storage disorder caused by mutations in the glucocerebrosidase gene (GBA), which encodes the lysosomal enzyme glucosylceramidase (GCase). Deficiency in GCase leads to characteristic visceral pathology and lethal neurological manifestations in some patients. Investigations into neurogenesis have suggested that neurodegenerative disorders, such as GD, could be overcome or at least ameliorated by the generation of new neurons. Bone marrowderived mesenchymal stem cells (BM-MSCs) are potential candidates for use in the treatment of neurodegenerative disorders because of their ability to promote neurogenesis. Our objective was to examine the mechanism of neurogenesis by BM-MSCs in GD. We found that neural stem cells (NSCs) derived from a neuronopathic GD model exhibited decreased ability for self-renewal and neuronal differentiation. Co-culture of GBA-deficient NSCs with BM-MSCs resulted in an enhanced capacity for self-renewal, and an increased ability for differentiation into neurons or oligodendrocytes. Enhanced proliferation and neuronal differentiation of GBA-deficient NSCs was associated with elevated release of macrophage colony-stimulating factor (M-CSF) from BM-MSCs. Our findings suggest that soluble M-CSF derived from BM-MSCs can modulate GBA-deficient NSCs, resulting in their improved proliferation and neuronal differentiation.

• BMB Reports
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• v.29 no.3
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• pp.200-204
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• 1996

Nerve growth factor (NGF) is literally known to promote neural differentiation and survival in several peripheral and central neurons. Thus, it is Widely believed that NGF may serve as a therapeutic agent for many types of neuronal diseases. One of the mechanisms suggested to explain the protective role of NGF is that the trophic factor can prevent the increase of intracellular calcium ions which might be responsible for neural death. To examine whether or not the calcium hypothesis works even under pathological conditions, we applied NGF to cultures deprived of glucose. Surprisingly, what was observed here is that NGF rather promoted cell death under a glucose-deprived condition. What we call the NGF paradox phenomenon occurred in a calcium concentration-dependent manner, indirectly suggesting that NGF might increase intracellular calcium ions in cells deprived of glucose. This suggestion is further supported by the fact that nifedipine, a well-known L-type calcium channel blocker, could block the cell death potentiated by NGF. Here it is still premature to propose the complete mechanism underlying the NGF paradox phenomenon. However, this study certainly indicates that NGF as a therapeutic agent for neuronal diseases should be carefully considered before use.

• Journal of Biomedical Engineering Research
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• v.2 no.1
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• pp.47-54
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• 1981

This paper deals with a new approach to the modelling of neural interactions in the cerebellar cortex to construct a general purpose electronic simulation model. Since physiological data show that cerebellar neural activity changes in an approximately pulse manner in response to pulse stimulation, the differences in timing between excitation and inhibition of cerebellar cells will be treated as pure time delays and the transfer functions of the cells will be presented by pure gains. The parameters to be discussed in this paper are the coupling coefficients between a cell and its several inputs, the magnitude of a coupling coefficient which is presented as a measure of how much influnce a particular has on its target cell. And also this paper has been proposed that the cerrbellum engaged in improving the overall performance of the motor control system, i.e., the cerebellum is a compensator.