• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.166-174
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• 1999

On-line efficiency optimization control of an induction motor drive using neural network is important from the v viewpoints of energy saving and controlling a nonlinear system whose charact81istics are not fully known. This paper p presents a neural networklongleftarrowbased on-line efficiency optimization control for an induction motor drive, which adopts an optimal slip an밍J.lar frequency control. In the proposed scheme, a neuro-controller provides minimal loss operating point i in the whole range of the measured input power. Both simulation and experimental results show that a considerable e energy saving is achieved compared with the conventional constant vlf ratio operation.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.4
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• pp.49-60
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• 1996

The objective of this paper is to develop an adaptive learning method for fuzzy hypercubes using a neural network. An intelligent control system is proposed by exploiting only the merits of a fuzzy logic controller and a neural network, assuming that we can modify in real time the consequential parts of the rulebase with adaptive learning, and that initial fuzzy control rules are established in a temporarily stable region. We choose the structure of fuzzy hypercubes for the fuzzy controller, and utilize the Perceptron learning rule in order to upda1.e the fuzzy control ru1c:s on-line with the output errors. As a result, the effectiveness and the robustness of this intelligent controller are shown with application of the proposed adaptive fuzzy-neuro controller to control of the cart-pole system.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.254-259
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• 1998

A new design methology is proposed to identify the structure and parameters of fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN(Fuzzy Polynomial Neural Networks) algorithm uses PNN(Polynomial Neural networks) structure and a fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on consequence of fuzzy rules with a polynomial equations such as linear, quadratic and cubic equation. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. In this paper, we will consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• Journal of Korean Critical Care Nursing
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• v.14 no.1
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• pp.50-62
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• 2021

Purpose : This study examined the effects of an integrated management program on physical function, cognitive function, and depression in patients with subacute stroke. Methods : A nonequivalent control group design was adopted. The participants were assigned to either the experimental group (n=20) or control group (n=23). The experimental group received an 8-week integrated management program and standard rehabilitation service (i.e., physical therapy and occupational therapy), while the control group received the standard rehabilitation service only. Physical function was measured as gait speed and balance ability using the Berg Balance Scale (BBS). Cognitive function was measured with neuro-behavioral cognitive status examination (NCSE), and depression was measured using the Beck Depression Inventory-II (BDI-II). Repeated measure ANOVA was used to determine changes in physical function, cognitive function, and depression over 8-weeks. Results : The interaction between group and time was significant, indicating that the experimental group showed improvement in gait speed, balance ability, cognitive function (linguistic ability, linguistic memory, reasoning), and a decrease in depression compared to the control group. Conclusion : These results indicate that the integrated management program developed herein was beneficial in restoring physical function, cognitive function, and depression in subacute stroke patients.

• Journal of Pharmaceutical Investigation
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• v.41 no.1
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• pp.31-36
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• 2011

$5HT_{2C}$ receptor among fourteen 5-HT subtypes plays important roles in several disorders such as depression, anxiety, epilepsy, schizophrenia and sleep disorders. The purpose of the study is to investigate pharmacokinetic parameters and bioavailability of a newly synthesized selective agonist of $5-HT_{2C}$ receptor, KOPC-20010 (KP10) in rats after intravenous and oral administration for the development of therapeutic anti-obesity agents. KP10 was administered orally (40 mg/kg) or intravenously (20 mg/kg), blood was collected via a catheter, and analyzed by GC/MSD. The calibration curve of KP10 in plasma and urine showed high linearity ($r^2$ >0.999). The retention times of KP10 in plasma and urine were 8.7 and 9.7 min, respectively. After oral administration of 40 mg/kg, pharmacokinetic parameters were calculated as follows; $C_{max}$ value was $1242.9{\pm}1195.5$ ng/mL at $1.1{\pm}0.6$ hr ($T_{max}$). $AUC_{0->24hr}$ and $AUC_{0>{\infty}}$ were $8034.2{\pm}960.7$ and $10464.1{\pm}681.5\;ng{\cdot}hr/mL$, respectively. The terminal half-life was $21.9{\pm}7.6$ hr. $AUC_{0->24hr}$ and $AUC_{0>{\infty}}$ were $4292.4{\pm}523.0$ and $6111.2{\pm}756.2\;ng{\cdot}hr/mL$, respectively, after 20 mg/kg of intravenous administration. The terminal half-life after intravenous administration was $25.1{\pm}9.4$ hr. Bioavailability of KP10 was determined to 86%. The excretion amount into the urine within 48 hr was approximately 4.7 to 6.7% of the dose administered. These data may be beneficial to the anti-obesity drug development of KP10.

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.509-519
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• 2018

This study was investigated the anti-oxidant property and neuro-protective effect of Cirsium japonicum var. maackii (CJM) against oxidative stress in hydrogen peroxide ($H_2O_2$)-induced C6 glial cells. We measured the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical, hydroxyl radical (${\cdot}OH$), and superoxide ($O_2{^-}$) radical scavenging activities of an ethanol extract and four fractions [n-Butanol, ethyl acetate (EtOAc), $CHCl_3$, and n-Hexane] from CJM. The results of this study show that the extract and all fractions from CJM had a dose-dependent DPPH radical scavenging activity. In particular, the EtOAc fraction exhibited the strongest scavenging effect with 88.23% at a concentration of $500{\mu}g/mL$. In addition, the EtOAc fraction from CJM also effectively scavenged ${\cdot}OH$ radicals and $O_2{^-}$ radicals, compared to other extract and fractions. In C6 glial cells, $H_2O_2$ markedly decreased the cell viability as well as increased lactate dehydrogenase (LDH) release and reactive oxygen species (ROS) production. However, the EtOAc fraction of CJM attenuated the cellular damage from the oxidative stress by elevating the cell viability and inhibiting the LDH release and ROS over-production compared with the $H_2O_2$-treated control group. Our findings indicate that the EtOAc fraction from CJM has antioxidant effect and neuro-protective effect against oxidative stress, suggesting that it can be used as a natural antioxidant and therapeutic agent for the prevention of neurodegenerative disorders.

• IMMUNE NETWORK
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• v.5 no.1
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• pp.45-49
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• 2005

Background: Inflammation in the brain has known to be associated with the development of a various neurological diseases. The hallmark of neuro-inflammation is the activation of microglia, brain macrophage. Pro-inflammatory compounds including nitric oxide (NO) are the main cause of neuro-degenerative disease such as Alzheimer's disease (AD) which is resulted in cell death. Among those pro-inflammatory compounds, NO contributes to the cell death by directly or indirectly. Methods: In the study, we examined whether ursodeoxycholic acid (UDCA), a non-toxic hydrophilic bile acid, inhibits the NO production by a direct method using Griess reagent and by RT-PCR in the gene expression of inducible nitric oxide synthase (iNOS). In signal transduction, we also examined the NF-${\kappa}B$ (p65/p50), IKK, and I ${\kappa}B$, which are associated with the expression of iNOS gene using western blots. Results: In the present study, we found that UDCA effectively inhibited NO production in BV-2 microglial cell, and NF-${\kappa}B$ activation was reduced by suppressing IKK gene expression and by increasing the I${\kappa}B$ in cytosol comparing those to the positive control LPS. Conclusion: Taken together, these data suggested that UDCA may playa crucial role in inhibiting the NO production and the results imply that UDCA suppresses a cue signal of the microglial activation via stimulators, such as ${\beta}$-amyloid peptides which are known to stimulate microglia in AD pathogenesis.

• Journal of Korean Neurosurgical Society
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• v.54 no.3
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• pp.175-182
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• 2013

Objective : Intracavitary injection of beta-emitting radiation source for control of cystic tumors has been tried with a benefit of localized internal radiation. The authors treated cystic brain tumor patients with Holmium-166-chitosan complex (Ho-166-chico), composed of a beta-emitting radionuclide Holmium-166 and biodegradable chit polymer, and evaluated the safety and effective measurement for response. Methods : Twenty-two patients with recurrent cystic brain tumor and/or located in a deep or eloquent area were enrolled in this pilot study. The cyst volume and wall thickness were determined on CT or MRI to assess radiological response. The activity of Ho-166-chico injected via Ommaya reservoir was prescribed to be 10-25 Gy to the cyst wall in a depth of 4 mm. Results : There was neither complications related to systemic absorption nor leakage of Ho-166-chico in all 22 patients. But, two cases of oculomotor paresis were observed in patients with recurrent craniopharyngioma. Radiological response was seen in 14 of 20 available follow-up images (70%). Seven patients of 'evident' radiological response experienced more than 25% decrease of both cyst volume and wall thickness. Another 7 patients with 'suggestive' response showed decrease of cyst volume without definitive change of the wall thickness or vice versa. All patients with benign tumors or low grade gliomas experienced symptomatic improvement. Conclusion : Ho-166-chico intracavitary radiation therapy for cystic tumor is a safe method of palliation without serious complications. The determination of both minimal effective dosage and time interval of repeated injection through phase 1 trial could improve the results in the future.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.2
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• pp.111-118
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• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality, Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FLC(fuzzy logic control), The parameters of input membership functions and those of consequence functions in FLC were tuned through the method of learning by backpropagation algorithm, Bead geometry could he reasoned from welding current, arc voltage, travel speed on FLC using the results learned by neural networks. On the developed inference system of bead geometry using neuo-fuzzy algorithm, the inference error percent of bead width was within ${\pm}4%$, that of bead height was within ${\pm}3%$, and that of penetration was within ${\pm}8%$, Neural networks came into effect to find the parameters of input membership functions and those of consequence in FLC. Therefore the inference system of welding quality expects to be developed through proposed algorithm.