• Bulletin of the Korean Chemical Society
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• v.32 no.spc8
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• pp.3063-3073
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• 2011

The synthesis and biological evaluation of 1-heteroarylmethyl 1,4-diazepane derivatives as potential T-type calcium channel blockers is described. In this study, we have identified the compound 21i exhibiting the most potent T-type calcium channel blocking activity with $IC_{50}$ value of 0.20 ${\mu}M$, which is superior to that of mibefradil.

• The Korean Journal of Pain
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• v.9 no.2
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• pp.423-425
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• 1996

Tic convulsif is a syndrome restricted to paroxysmal dysfunction of the fifth and seventh cranial nerves. It occurs predominantly in women over the age of 50 years and is usually associated with an ectatic vertebrobasilar artery - less frequently an arteriovenous malformation or cholesteatoma - which compresses the trigeminal and facial nerve roots in the postetior fossa. In rare instances this syndrome may be caused by brain tumor. Because of the high incidence of posterior fossa lesions in painful tic convulsif, a complete neurological evaluation including computerised transaxial tomography should be performed in every case. We experienced a case of trigeminal neuralgia(mandibular division)and contralateral hemifacial spasm.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.285-290
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• 2020

Neuro-feedback is a technology that can identify your brain state and you can intentionally change your brain state. People with attention deficit and hyperactivity disorder need this technology but existing neuro-feedback training has a problem, which is not interesting and maintains a static state for a long time. In this paper, we proposed and implemented a neuro-feedback game that combines neuro-feedback and gun-shooting games to enhance concentration training. The neuro-feedback game has been implemented with the design of EEG measurement system, game controller and gamesoft. We hope that this study will be useful for people suffering from attention deficit and hyperactivity disorder.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.201-208
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• 2005

Neuro-Fuzzy modeling approach is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system consists of friction pendulum systems (FPS) and a magnetorheological (MR) damper. Fuzzy model of the M damper is trained by ANFIS using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses or experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.534-536
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• 2003

It is important to classily fault types and discriminate fault section by any detecting technique for combined transmission lines. This paper proposes the technique to classify the fault types and fault section using neuro-fuzzy systems. Neuro-fuzzy systems are composed of two parts to perform different works. First, neuro-fuzzy system for fault type classification is performed with approximation coefficient of currents obtained by wavelet transform. Another neuro-fuzzy system discriminates the fault section between overhead and underground with detail coefficients of voltage and current. In this paper, neuro-fuzzy system shows the excellent results for classification of fault types and discrimination of fault section.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.722-730
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• 2003

Current differential relay is commonly used to protect power transformer. However, current differential relay will be tripod by judging like internal fault during inrush occurring in transformer. To resolve such problem, this paper proposes a new protective relaying algorithm using Neuro-Fuzzy Inference. A variety of transformer transition states are simulated by BCTRAN and HYSDT of EMTP. Primary phase voltage and differential current are obtained from simulation. The target data which are used in Neuro-Fuzzy algorithm are obtained from transformed primary voltage and current. Then, these are trained by Neuro-Fuzzy algorithm. The trained Neuro-Fuzzy algorithm correctly distinguishes whether internal fault occurs or not, within 1/2 cycle after fault. Accordingly, it is evaluated that the proposed algorithm has good relaying characteristics.

• Computers and Concrete
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• v.27 no.5
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• pp.489-512
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• 2021

In this study, two powerful techniques, namely particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were selected and combined with a pre-developed ANN model aiming at improving its performance prediction of the compressive strength of concrete modified with fly ash. To achieve this study's aims, a comprehensive database with 379 data samples was collected from the available literature. The output of the database is the compressive strength (CS) of concrete samples, which are influenced by 9 parameters as model inputs, namely those related to mix composition. The modeling steps related to ICA-ANN (or neuro-imperialism) and PSO-ANN (or neuro-swarm) were conducted through the use of several parametric studies to design the most influential parameters on these hybrid models. A comparison of the CS values predicted by hybrid intelligence techniques with the experimental CS values confirmed that the neuro-swarm model could provide a higher degree of accuracy than another proposed hybrid model (i.e., neuro-imperialism). The train and test correlation coefficient values of (0.9042 and 0.9137) and (0.8383 and 0.8777) for neuro-swarm and neuro-imperialism models, respectively revealed that although both techniques are capable enough in prediction tasks, the developed neuro-swarm model can be considered as a better alternative technique in mapping the concrete strength behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.52-63
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• 1995

A neuro-fuzzy algorithm is presented for nuclear reactor power control in a pressurized water reactor. Automatic reacotr power control is complicated by the use of control rods because of highly nonlinear dynamics in the axial power shape. Thus, manual shaped controls are usually employed even for the limited capability during the power maneuvers. In an attempt to achieve automatic shape control, a neuro-fuzzy approach is considered because fuzzy algorithms are good at various aspects of operator's knowledge representation while neural networks are efficinet structures capable of learning from experience and adaptation to a changing nuclear core state. In the proposed neuro-fuzzy control scheme, the rule base is formulated based ona multi-input multi-output system and the dynamic back-propagation is used for learning. The neuro-fuzzy powere control algorithm has been tested using simulation fesponses of a Korean standard pressurized water reactor. The results illustrate that the proposed control algorithm would be a parctical strategy for automatic nuclear reactor power control.

• Knowledge Management Research
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• v.9 no.4
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• pp.143-156
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• 2008

The main purpose of this study is to suggest a way that how government innovation ecosystem can be successfully managed by applying neuro-cybernetics approach. Innovation ecosystem is not a rare phenomenon around us. Especially national innovation managed by government relies on heavily innovation ecosystem. Unfortunately discussions of successful management of this ecosystem are rare. This study strongly urged necessity of such management by observing the case of introduction of CDMA mobile communication technology in Korea. Neuro-cybernetics was suggested as one alternative approach for the such management.

• Knowledge Management Research
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• v.1 no.1
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• pp.65-80
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• 2000

The main purpose of this study is to answer a question that how a company can be a learning organization producing useful knowledge by applying neuro-cybernetics approach. This approach borrows its working principles from the human body systems. The current study urges that the principles can be applied to build a learning organization. System 1 to 5, the core parts of neuro-cybernetics, are explained. And it is explored that how these systems can be designed for a company to be a learning organization. Limitations of the current study are discussed at the end of the paper.