• The Korean Journal of Physiology and Pharmacology
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• v.19 no.2
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• pp.177-181
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• 2015

The subfornical organ (SFO) is one of circumventricular organs characterized by the lack of a normal blood brain barrier. The SFO neurons are exposed to circulating glutamate ($60{\sim}100{\mu}M$), which may cause excitotoxicity in the central nervous system. However, it remains unclear how SFO neurons are protected from excitotoxicity caused by circulating glutamate. In this study, we compared the glutamate-induced whole cell currents in SFO neurons to those in hippocampal CA1 neurons using the patch clamp technique in brain slice. Glutamate ($100{\mu}M$) induced an inward current in both SFO and hippocampal CA1 neurons. The density of glutamate-induced current in SFO neurons was significantly smaller than that in hippocampal CA1 neurons (0.55 vs. 2.07 pA/pF, p<0.05). To further identify the subtype of the glutamate receptors involved, the whole cell currents induced by selective agonists were then compared. The current densities induced by AMPA (0.45 pA/pF) and kainate (0.83 pA/pF), non-NMDA glutamate receptor agonists in SFO neurons were also smaller than those in hippocampal CA1 neurons (2.44 pA/pF for AMPA, p<0.05; 2.34 pA/pF for kainate, p< 0.05). However, the current density by NMDA in SFO neurons was not significantly different from that of hippocampal CA1 neurons (1.58 vs. 1.47 pA/pF, p>0.05). These results demonstrate that glutamate-mediated action through non-NMDA glutamate receptors in SFO neurons is smaller than that of hippocampal CA1 neurons, suggesting a possible protection mechanism from excitotoxicity by circulating glutamate in SFO neurons.

• Journal of the Korean Society of Food Science and Nutrition
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• v.30 no.3
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• pp.403-409
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• 2001

A novel strain of SFO41 producing a large amount of cholesterol oxidase as an extracellular enzyme isolate from Korean salt fermented foods. The strain was identified as Bacillus megaterium based on morphological, cultural and physiological characteristics. Experiments were carried out to optimized the condition of cholesterol oxidase production using B. megaterium SFO41. B. megaterium SFO41 was shown to give the maximum yield of cholesterol oxidase in the medium containing 2.0% glucose, 0.5% yeast extract. 0.03% $MgSO_4{\cdot}7H_2O,\;0.02%\;K_2HPO_4,\;0.2%\;NH_4NO_3$ and 0.2% cholesterol. The optimum culture conditions, temperature, initial pH and agitation speed were $30^{\circ}C$, 7.0 and 150 rpm, respectively. The enzyme production reached a maximum level at 24 hr of cultivation (2.37 U).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.1-6
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• 2014

Recently, orthogonal frequency-division multiplexing(OFDM), with clusters of subcarriers allocated to different subscribers(often referred to as OFDMA), has gained much attention for its ability in enabling multiple-access wireless multimedia communications. In such systems, carrier frequency offsets (CFOs) can destroy the orthogonality among subcarriers. And the mismatch in sampling frequencies between transmitter and receiver can lead to serious degradation due to the loss of orthogonality between the subcarriers. As a result, multiuser interference (MUI) along with significant performance degradation can be induced. In this paper, we present a scheme to compensate for the SFOs and CFOs at the base station of an OFDMA system. A novel sampling frequency offset estimation algorithm is proposed, which is based on the repetition of a symbol at the communication start-up. Then, circular convolutions are employed to generate the interference after the discrete Fourier transform processing, which is then removed from the original received signal to increase the signal to interference power ratio(SIR). Simulation result shows that the proposed scheme can improve system performance.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.6
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• pp.531-536
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• 2002

This paper investigates the problem of the speed controller of conventional speed sensorless stator flux-oriented(SFO) induction motor drive, and proposes a robust speed controller to solve the conventional problem. In the proposed method, a robust speed controller for speed sensorless SFO system Is designed by taking advantage of disturbance torque observer and using feedforward.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.73-81
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• 2012

In this paper, we propose a high-speed synchronization method for Digital Radio Mondiale (DRM) receivers. In order to satisfy the high-speed synchronization requirement of DRM receivers, the proposed method eliminate the initial sampling frequency synchronization process in conventional synchronization methods. In the proposed method, sampling frequency tracking is performed after integer frequency synchronization and frame synchronization. Different correlation algorithms are applied to detect the first frame of the Orthogonal Frequency Division Multiplexing (OFDM) demodulation symbol with sampling frequency offset (SFO). A frame detection algorithm that is robust to SFO is selected based on the performance analysis and simulation. Simulation results show that the proposed method reduces the time spent for initial sampling frequency synchronization even if SFO is present in the DRM signal. In addition, it is verify that inter-cell differential correlation used between reference cells is roubst to the effect of initial SFO.

• Smart Structures and Systems
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• v.30 no.4
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• pp.421-432
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• 2022

Regarding the high significance of correct pan evaporation modeling, this study introduces two novel neuro-metaheuristic approaches to improve the accuracy of prediction for this parameter. Vortex search algorithms (VSA), sunflower optimization (SFO), and stochastic fractal search (SFS) are integrated with a multilayer perceptron neural network to create the VSA-MLPNN, SFO-MLPNN, and SFS-MLPNN hybrids. The climate data of Arcata-Eureka station (operated by the US environmental protection agency) belonging to the years 1986-1989 and the year 1990 are used for training and testing the models, respectively. Trying different configurations revealed that the best performance of the VSA, SFO, and SFS is obtained for the population size of 400, 300, and 100, respectively. The results were compared with a conventionally trained MLPNN to examine the effect of the metaheuristic algorithms. Overall, all four models presented a very reliable simulation. However, the SFS-MLPNN (mean absolute error, MAE = 0.0997 and Pearson correlation coefficient, R_P = 0.9957) was the most accurate model, followed by the VSA-MLPNN (MAE = 0.1058 and R_P = 0.9945), conventional MLPNN (MAE = 0.1062 and R_P = 0.9944), and SFO-MLPNN (MAE = 0.1305 and R_P = 0.9914). The findings indicated that employing the VSA and SFS results in improving the accuracy of the neural network in the prediction of pan evaporation. Hence, the suggested models are recommended for future practical applications.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.175-178
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• 2002

In a conventional speed sensorless Stator Flux Oriented(SFO) induction machine drive system, the estimated speed is delayed in transients by the use of a low pass filter(LPF). To prevent extreme overshoot caused by this delay, PI controller gains should be small, which consequently is greatly affected by disturbance torque. In this paper, by taking advantage of disturbance torque observer and feedforward control, robust speed controller is designed for speed sensorless SFO system. The proposed method is verified by the simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1860-1875
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• 2013

In this paper, we present a comparative performance evaluation of the sampling frequency synchronization method that eliminates the initial sampling frequency offset (SFO) to reduce the overall synchronization time in Digital Radio Mondiale (DRM) receivers. To satisfy the advanced synchronization performance requirements of DRM receivers, we introduce the conventional DRM synchronization method (Method 1) and another method (Method 2), which does not perform the initial sampling frequency synchronization in the conventional synchronization method (both methods are mentioned later in this paper). To demonstrate the effectiveness of the performance evaluation, analytical expressions for frame detection are derived and simulations are provided. Based on the simulations and numerical analysis, our result shows that Method 2, with a negligible performance loss, is robust to the effects of the initial sampling frequency synchronization even if SFO is present in the DRM signal. In addition, we verify that the inter-cell differential correlation used between reference cells is robust to the effect of the initial SFO.

• Steel and Composite Structures
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• v.45 no.2
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• pp.281-291
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• 2022

Surmounting complexities in analyzing the mechanical parameters of concrete entails selecting an appropriate methodology. This study integrates a novel metaheuristic technique, namely satin bowerbird optimizer (SBO) with artificial neural network (ANN) for predicting uniaxial compressive strength (UCS) of concrete. For this purpose, the created hybrid is trained and tested using a relatively large dataset collected from the published literature. Three other new algorithms, namely Henry gas solubility optimization (HGSO), sunflower optimization (SFO), and vortex search algorithm (VSA) are also used as benchmarks. After attaining a proper population size for all algorithms, the Utilizing various accuracy indicators, it was shown that the proposed ANN-SBO not only can excellently analyze the UCS behavior, but also outperforms all three benchmark hybrids (i.e., ANN-HGSO, ANN-SFO, and ANN-VSA). In the prediction phase, the correlation indices of 0.87394, 0.87936, 0.95329, and 0.95663, as well as mean absolute percentage errors of 15.9719, 15.3845, 9.4970, and 8.0629%, calculated for the ANN-HGSO, ANN-SFO, ANN-VSA, and ANN-SBO, respectively, manifested the best prediction performance for the proposed model. Also, the ANN-VSA achieved reliable results as well. In short, the ANN-SBO can be used by engineers as an efficient non-destructive method for predicting the UCS of concrete.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.829-833
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• 2001

In a conventional speed sensorless stator flux­oriented (SFO) induction machine drive system, the estimated speed is delayed in transients by the use of a low pass filter. This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of the estimated speed in the field weakening region. In addition, this paper proposes a method to estimate exactly speed by using Kalman filter. The proposed method is verified by simulation and experiment with a 5-hp induction motor drive.