• Journal of Ginseng Research
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• 제47권2호
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• pp.228-236
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• 2023

Background: QiShen YiQi pills (QSYQ) is a Traditional Chinese Medicine (TCM) formula, which has a significant effect on the treatment of patients with myocardial infarction (MI) in clinical practice. However, the molecular mechanism of QSYQ regulation pyroptosis after MI is still not fully known. Hence, this study was designed to reveal the mechanism of the active ingredient in QSYQ. Methods: Integrated approach of network pharmacology and molecular docking, were conducted to screen active components and corresponding common target genes of QSYQ in intervening pyroptosis after MI. Subsequently, STRING and Cytoscape were applied to construct a PPI network, and obtain candidate active compounds. Molecular docking was performed to verify the binding ability of candidate components to pyroptosis proteins and oxygen-glucose deprivation (OGD) induced cardiomyocytes injuries were applied to explore the protective effect and mechanism of the candidate drug. Results: Two drug-likeness compounds were preliminarily selected, and the binding capacity between Ginsenoside Rh2 (Rh2) and key target High Mobility Group Box 1 (HMGB1)was validated in the form of hydrogen bonding. 2 μM Rh2 prevented OGD-induced H9c2 death and reduced IL-18 and IL-1β levels, possibly by decreasing the activation of the NLRP3 inflammasome, inhibiting the expression of p12-caspase1, and attenuating the level of pyroptosis executive protein GSDMD-N. Conclusions: We propose that Rh2 of QSYQ can protect myocardial cells partially by ameliorating pyroptosis, which seems to have a new insight regarding the therapeutic potential for MI.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 추계학술발표논문집 (하)
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• pp.1427-1430
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• 2001

액티브 네트워크는 기존의 패킷 교환 네트워크와 달리 네트워크 중간 노드에서 사용자의 요구나 서비스 특성에 따라 패킷을 처리할 수 있는 차세대 네트워크 구조이다. 기존의 네트워크 문제점을 개선하고 네트워크에 지능을 부여한다는 측면에서 새로운 접근 방식이지만 아직 해결해야 할 많은 논지를 가지고 있다. 본 논문은 액티브 네트워크와 기존의 네트워크 공존문제를 해결, 관리하기 위한 SNMP 확장에 관한 모델을 제시하고, SNMP 기반의 네트워크와 비교 분석하기로 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.72-75
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• 2000

This paper presents a simulation study on the description of the motion and the control of an active catheter actuator with multi-link structure actuated by Shape Memory Alloy(SMA). The model of an active catheter adopted in this paper has 3 links, and the individual links are composed of 3 micro coils of SMA for the omni-directional motion. In order to analyze the motions of multi-link structure, 3-dimensional kinematics description is presented. Also, the motion control of the end point of an active catheter using simple Neural Network is shown based on GUI(Graphic User Interface) system.

• Journal of Power Electronics
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• 제16권5호
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• pp.1716-1724
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• 2016

This paper proposes both an active-switched quasi-Z-source inverter (AS-qZSI) and an extended active-switched qZSI (EAS-qZSI), which are based on the classic qZSI. The proposed AS-qZSI adds only one active switch and one diode to the classic qZSI for increasing the voltage boost capability. Compared with other topologies based on the switched-inductor/capacitor qZSI, the proposed AS-qZSI requires fewer passive components in the impedance network under the same boost capability. Additionally, the proposed EAS-qZSI is designed by adding one inductor and three diodes to the AS-qZSI, which offers enhanced boost capability and lower voltage stress across the switches. The performances of the two proposed topologies are verified by simulation and experimental results obtained from a prototype with a 32-bit DSP built in a laboratory.

• 한국정보통신학회논문지
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• 제6권5호
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• pp.667-675
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• 2002

본 논문에서는 신경망을 이용한 새로운 비선형 능동소음제어 시스템(ANC； active noise control system) 을 제안하였다. 제안한 시스템에서는 2개의 다층신경망을 사용하여 제어기와 2차 경로의 모델을 구성하였으며, 특히 기존의 비선형 ANC와는 달리 2차 경로의 모델링이 온라인으로 수행되기 때문에 2차경로가 시변 시스템인 경우에도 적용이 가능하다. 제안한 방범을 비선형 시변 시스템에 대해서 모의 실험한 결과 좋은 소음감소 효과를 보여주었다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 춘계학술발표대회
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• pp.105-108
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• 2014

기업에서 사용하는 시스템에서는 대량의 데이터를 실시간으로 처리해야 하며 또한 시스템 장애로 인한 생산 중단이 발생하지 않도록 하기 위해 서버 이중화 구성에 많은 투자를 하고 있다. 장애를 최소화하기 위해 서버 구성을 Active-Standby 구조로 이중화를 구성하여 사용하고 있으며, 이로 인해 시스템에 대한 많은 비용을 투자하고 있다. 서버 부하 감소 및 서버 가용성 향상을 통한 투자 비용을 절감하기 위해 서버 분산 처리에 대한 방법이 나오고 있다. 그러나 Network 스위치나 라우터 등의 Hardware 적인 분산 시스템을 이용한 방법으로는 특정한 데이터만을 분산하여 처리할 수 없고 Hardware 의 투자 비용 또한 증가하게 된다. 또한 서버의 Active-Standby 구성에서 Standby 서버는 Active 서버의 문제 발생시에만 이용하게 됨으로 인해 서버의 가용성이 떨어지는 불합리가 발생함으로 인해 이를 개선하기 위한 연구를 통해 Active-Active 구성을 통해 서버의 가용성을 확보하고자 한다. 본 논문에서는 서버 가용성 향상을 위한 방법으로 DQ(Distributed Queue)를 이용하여 응용프로그램에서의 데이터 분산을 통한 응용프로그램에서의 부하를 분산하여 서버 내 리소스를 최대한 활용하면서 응용프로그램에서의 부하를 감소화할 수 있는 방법을 검증하고자 한다.

• Journal of Advanced Marine Engineering and Technology
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• 제32권8호
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• pp.1263-1268
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• 2008

In this paper, the low noise power amplifier for GaAs FET ATF-10136 is designed and fabricated with active bias circuit and self bias circuit. To supply most suitable voltage and current, active bias circuit is designed. Active biasing offers the advantage that variations in the pinch-off voltage($V_p$) and saturated drain current($I_{DSS}$) will not necessitate a change in either the source or drain resistor value for a given bias condition. The active bias network automatically sets a gate-source voltage($V_{gs}$) for the desired drain voltage and drain current. Using resistive decoupling circuits, a signal at low frequency is dissipated by a resistor. This design method increases the stability of the LNA, suitable for input stage matching and gate source bias. The LNA is fabricated on FR-4 substrate with active and self bias circuit, and integrated in aluminum housing. As a results, the characteristics of the active and self bias circuit LNA implemented more than 13 dB and 14 dB in gain, lower than 1 dB and 1.1 dB in noise figure, 1.7 and 1.8 input VSWR at normalized frequency $1.4{\sim}1.6$, respectively.

• ETRI Journal
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• 제30권2호
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• pp.194-204
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• 2008

The online collection of coarse-grained traffic information, such as the total number of flows, is gaining in importance due to a wide range of applications, such as congestion control and network security. In this paper, we focus on an active queue management scheme called SRED since it estimates the number of active flows and uses the quantity to indicate the level of congestion. However, SRED has several limitations, such as instability in estimating the number of active flows and underestimation of active flows in the presence of non-responsive traffic. We present a Markov model to examine the capability of SRED in estimating the number of flows. We show how the SRED cache hit rate can be used to quantify the number of active flows. We then propose a modified SRED scheme, called hash-based two-level caching (HaTCh), which uses hashing and a two-level caching mechanism to accurately estimate the number of active flows under various workloads. Simulation results indicate that the proposed scheme provides a more accurate estimation of the number of active flows than SRED, stabilizes the estimation with respect to workload fluctuations, and prevents performance degradation by efficiently isolating non-responsive flows.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2000년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2000
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• pp.509-514
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• 2000

A structural control algorithm using CMAC(Cerebellar Model Articulation Controller) neural network is proposed Learning rule for CMAC is derived based on cost function. Learning convergence of CMAC is compared with MLNN(Multilayer Neural Network). Numerical examples are shown to verify the proposed control algorithm. Examples show that CMAC can be applicable to structural control with fast learning speed.