• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.421-424
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• 2003

This paper proposes the generalized predictive control(GPC) method of chaotic systems using a self-recurrent wavelet neural network(SRWNN). The reposed SRWNN, a modified model of a wavelet neural network(WNN), has the attractive ability such as dynamic attractor, information storage for later use. Unlike a WNN, since the SRWNN has the mother wavelet layer which is composed of self-feedback neurons, mother wavelet nodes of the SRWNN can store the past information of the network. Thus the SRWNN can be used as a good tool for predicting the dynamic property of nonlinear dynamic systems. In our method, the gradient-descent(GD) method is used to train the SRWNN structure. Finally, the effectiveness and feasibility of the SRWNN based GPC is demonstrated with applications to a chaotic system.

• Applied Microscopy
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• 제41권4호
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• pp.249-255
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• 2011

신경세포는 생존 및 정상적인 기능을 위하여 다량의 에너지를 소비하므로, 미토콘드리아의 기능이 매우 중요하다. 미토콘드리아는 신경세포 내에서 신경돌기를 따라 이동하기도 하고, 세포내 여러 상황에 따라 접합과 절단을 반복하면서 그 분포와 형태가 역동적으로 변화한다. 역동적인 미토콘드리아의 형태 변화는 주로 GTPase 단백질인 Dynamin-related protein-1 (Drp1)에 의한 절단에 의해 조절되는 것으로 알려져 있다. 그러나, 중추신경계 신경세포에서의 미토콘드리아 분포 및 형태 변화 조절에 대해서는 비교적 연구가 미흡한 실정이다. 이 연구의 저자들은 미토콘드리아에 선택적으로 표적화되는 DsRed-mito 플라스미드를 일차 배양한 대뇌겉질 신경세포에 유전자 도입하여, 가지돌기 및 축삭에 분포하는 미토콘드리아의 길이와 역동성을 분석하였다. 흥미롭게도, 축삭 말단 부위에 분포하는 미토콘드리아의 길이가 세포체 근처의 축삭에 분포하는 미토콘드리아에 비하여 유의미하게 짧았다. 또한 Drp1 단백질이 가지돌기와 축삭에 다량 분포하며, 형광현미경하에서 이뤄진 실시간 촬영을 통해 축삭내에서 미토콘드리아의 절단이 활발하게 나타나는 것을 관찰하였다. 이를 통해, 축삭 말단 미토콘드리아의 길이 감소는 축삭 내 분포하는 Drp1 단백질의 활성에 의한 것으로 생각할 수 있었다. 위 가설을 검증하기 위하여, Drp1의 우성음성돌연변이 단백질을 신경세포에 유전자 도입하여 내재적 Drp1의 활성을 억제한 결과, 축삭 내 미토콘드리아 길이의 유의미한 증가가 관찰되었다. 이러한 결과들을 종합할 때, 대뇌겉질 신경세포에서 미토콘드리아의 절단은 축삭 내에서 지엽적으로도 진행되며, 이에 의하여 축삭내 위치에 따른 미토콘드리아의 길이 변화가 조절되는 것으로 생각되었다.

• 융합신호처리학회논문지
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• 제5권1호
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• pp.32-39
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• 2004

생체 뉴론은 일반적으로 지속적 또는 과도적인 카오틱 특성을 가지고 있다. 생체 뉴론의 카오틱 반응에 대한 분석적인 해석은 아직까지 이루어지지 않고 있다. 동적 카오틱 반응에 대한 카오틱 뉴런의 과도 카오틱 특성은 지역 수렴 문제를 극복하는데 도움이 되지만 일반적으로 지속적인 카오틱 응답은 최적화 문제에 악영향을 미치게 되므로 초기 카오틱 특성은 사라져야 한다. 패턴 인식, 확인, 예측, 그리고 제어에 사용되는 대부분의 신경회로망 응용에 있어서 필요한 최적화 문제를 해결하기 위해서는 뉴론은 한 개의 안정적인 고정점을 가지고 있어야 한다. 본 논문에서는 동적 카오틱 뉴런의 동적 특성과 카오틱 응답을 발생시키는 조건을 분석하고, 카오틱 뉴런의 수렴조건을 제안하였다.

• Molecules and Cells
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• 제45권11호
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• pp.855-867
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• 2022

For proper function of proteins, their subcellular localization needs to be monitored and regulated in response to the changes in cellular demands. In this regard, dysregulation in the nucleocytoplasmic transport (NCT) of proteins is closely associated with the pathogenesis of various neurodegenerative diseases. However, it remains unclear whether there exists an intrinsic regulatory pathway(s) that controls NCT of proteins either in a commonly shared manner or in a target-selectively different manner. To dissect between these possibilities, in the current study, we investigated the molecular mechanism regulating NCT of truncated ataxin-3 (ATXN3) proteins of which genetic mutation leads to a type of polyglutamine (polyQ) diseases, in comparison with that of TDP-43. In Drosophila dendritic arborization (da) neurons, we observed dynamic changes in the subcellular localization of truncated ATXN3 proteins between the nucleus and the cytosol during development. Moreover, ectopic neuronal toxicity was induced by truncated ATXN3 proteins upon their nuclear accumulation. Consistent with a previous study showing intracellular calcium-dependent NCT of TDP-43, NCT of ATXN3 was also regulated by intracellular calcium level and involves Importin α3 (Imp α3). Interestingly, NCT of ATXN3, but not TDP-43, was primarily mediated by CBP. We further showed that acetyltransferase activity of CBP is important for NCT of ATXN3, which may acetylate Imp α3 to regulate NCT of ATXN3. These findings demonstrate that CBP-dependent acetylation of Imp α3 is crucial for intracellular calcium-dependent NCT of ATXN3 proteins, different from that of TDP-43, in Drosophila neurons.

• The Korean Journal of Physiology and Pharmacology
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• 제3권4호
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• pp.365-373
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• 1999

Somatostatin (SOM) is one of the major neuropeptides in dorsal root ganglion cells, but its role in spinal nociceptive process has not been well known. In present study we aimed to investigate the effect of SOM on the response of dorsal horn neurons to the various types of peripheral nociceptive stimuli in anesthetized cats. Using carbon-filament microelectrode, the single cell activities of wide dynamic range neurons were recorded from the lumbosacral enlargement after noxious mechanical (squeeze), thermal (radiant heat lamp) and cold (dry ice) stimulation to the receptive field. Sciatic nerve was stimulated electrically to evoke $A\;{\delta}-$ and C-nociceptive responses. SOM analogue, octreotide $(10\;{\mu}g/kg),$ was applied intravenously and the results were compared with those of morphine (2 mg/kg, MOR). Systemic SOM decreased the cellular responses to the noxious heat and the mechanical stimulation, but increased those to the cold stimulation. In the responses to the electric stimuli of sciatic nerve, $A\;{\delta}-nociceptive$ response was increased by SOM, while C-nociceptive response was decreased. On the other hand, MOR inhibited the dorsal horn cell responses to all the noxious stimuli. From the above results, it is concluded that SOM suppresses the transmission of nociceptive heat and mechanical stimuli, especially via C-fiber, while it facilitates those of nociceptive cold stimuli via $A\;{\delta}-fiber$.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 춘계학술대회 논문집
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• pp.125-130
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• 1997

In this paper, it is presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C3x is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, andsuitable for implementation of robust control.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1231-1238
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• 1999

This paper presents an approach for the optimal heating load Identification using Diagonal Recurrent Neural Networks(DRNN). In this paper, the DRNN captures the dynamic nature of a system and since it is not fully connected, training is much faster than a fully connected recurrent neural network. The architecture of DRNN is a modified model of the fully connected recurrent neural network with one hidden layer. The hidden layer is comprised of self-recurrent neurons, each feeding its output only into itself. In this study, A dynamic backpropagation (DBP) with delta-bar-delta learning method is used to train an optimal heating load identifier. Delta-bar-delta learning method is an empirical method to adapt the learning rate gradually during the training period in order to improve accuracy in a short time. The simulation results based on experimental data show that the proposed model is superior to the other methods in most cases, in regard of not only learning speed but also identification accuracy.

• 한국지능시스템학회논문지
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• 제7권5호
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• pp.60-66
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• 1997

This paper presents a fuzzy inference-based reinforcement learning algorithm of dynamci recurrent neural networks, which is very similar to the psychological learning method of higher animals. By useing the fuzzy inference technique the linguistic and concetional expressions have an effect on the controller's action indirectly, which is shown in human's behavior. The intervlas of fuzzy membership functions are found optimally by genetic algorithms. And using recurrent neural networks composed of dynamic neurons as action-generation networks, past state as well as current state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying it to the inverted pendulum control problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.939-942
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• 1996

This paper presents a stable learning algorithm for diagonal recurrent neural network(DRNN). DRNN is applied to a problem of controlling nonlinear dynamical systems. A architecture of DRNN is a modified model of the Recurrent Neural Network(RNN) with one hidden layer, and the hidden layer is comprised of self-recurrent neurons. DRNN has considerably fewer weights than RNN. Since there is no interlinks amongs in the hidden layer. DRNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. To guarantee convergence and for faster learning, an adaptive learning rate is developed by using Lyapunov function. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed algorithm is demonstrated by computer simulation.

• 생명과학회지
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• 제16권6호
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• pp.955-959
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• 2006

단백질의 serine 및 threonine 잔기에 O-linked N-acetylglucosamine (O-GlcNAc)의 수식은 핵단백질과 세포질 단백질의 주요 조절인자로 부각되고 있다. 본 연구에서는 GlcNAc를 인산화시켜 GlcNAc 6-phosphate로 만드는 GlcNAc kinase (NAGK, EC2.7.1.59)의 세포내 표현을 면역화학적 방법으로 조사하였다. 배양한 해미신경세포에서 NAGK는 가지돌기를 따라 점박이(punctae)를 형성하였으며, 이 점박이들은 caveolin-1 혹은 flotillin 항체에도 염색이 되었다. 이들은 각각 caveolac와 lipid raft의 표지단백질이기 때문에 본 연구결과는 NAGK가 세포막의 이러한 특수 미세부분(microdomain)에 존재함을 의미하며, 이 미세부분에서 아직 알려지지 않은 어떤 기능을 할 것을 시사한다.