• 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.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1527-1534
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• 2016

Online voltage stability monitoring using real-time measurements is one of the most important tasks in a smart grid system to maintain the grid stability. Loading margin is a good indicator for assessing the voltage stability level. This paper presents an Extreme Learning Machine (ELM) approach for estimation of voltage stability level under credible contingencies using real-time measurements from Phasor Measurement Units (PMUs). PMUs enable a much higher data sampling rate and provide synchronized measurements of real-time phasors of voltages and currents. Depth First (DF) algorithm is used for optimally placing the PMUs. To make the ELM approach applicable for a large scale power system problem, Mutual information (MI)-based feature selection is proposed to achieve the dimensionality reduction. MI-based feature selection reduces the number of network input features which reduces the network training time and improves the generalization capability. Voltage magnitudes and phase angles received from PMUs are fed as inputs to the ELM model. IEEE 30-bus test system is considered for demonstrating the effectiveness of the proposed methodology for estimating the voltage stability level under various loading conditions considering single line contingencies. Simulation results validate the suitability of the technique for fast and accurate online voltage stability assessment using PMU data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1759-1764
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• 2005

Human Adaptive Mechatronics(HAM) is a new concept which was proposed in our university's research project sponsored by Japanese Ministry of Education, Sports, Culture, Science and Technology(MEXT), and is defined as "intelligent mechanical systems that adapt themselves to the user's skill under various environments, assist to improve the user's skill, and assist the human-machine system to achieve best performance". In this paper, the concept and key-items of HAM are mentioned. And the control strategy to realize a HAM human-machine system is explained in the case of physical-interface system, i.e. haptic system. The proposed assist-control of a force-feedback type haptic system includes online estimation of a operator's control characteristics, and a `force assist' function implemented as a change in the support ratio according to the identified skill level. We developed a HAM-haptic device test system, executed evaluation experiments with this apparatus, and analyzed the measured data. It was confirmed that the operator's skill could be estimated and that operator's performance was enhanced by the assist-control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• Journal of Power Electronics
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• 제12권6호
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• pp.1003-1010
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• 2012

Recent power electronics and variable-frequency motor drive technologies have been applied to air conditioners to improve efficiency and power density. However, the mechanical vibrations and acoustic noise resulting from the compressor still remain as a serious problem. This paper presents the development and implementation of an online disturbance state-filter for the suppression of multiple unknown and time-varying vibrations of air conditioning systems. The proposed design has a form of the state-filter based on a Luenburger-style closed-loop speed observer. An active vibration decoupling strategy with an estimated disturbance is provided, which manipulates a motor torque command. Since the proposed estimation does not require any additional transducers or hardware for obtaining real-time information upon disturbances, it is suitable for retrofitting industrial air conditioners.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.127-134
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• 2021

This study aims to determine the role of innovative capabilities as a mediator in analyzing entrepreneurial marketing's effect on sustainable competitive advantage in food and beverage micro-, small-, and medium- enterprises (MSMEs). Data was obtained from a food and beverage store manager in Tangerang City, comprising 119 samples. Furthermore, the G⁎Power, a tool used to calculate statistical power analysis for various t-tests, F tests, χ2 tests, z tests, and several exact tests, was used to determine the number of research samples, the α error probability of 5%, and 3 variables. The data collection method used questionnaires with Likert Scale 1-5 to indicate strongly disagree to strongly agree. To analyze data, we used Path Analysis supported by SmartPLS statistics software. Path analysis is a form of multiple regression statistical analysis that is used to evaluate causal models by examining the relationships between a dependent variable and two or more independent variables. It aims to provide estimates of the magnitude and significance of hypothesized causal connections between sets of variables. The data processing process took place in two stages, namely the estimation model testing with validity and reliability, and the structural model testing to decide the impact or correlation between variables utilizing the t-test. The result showed a positive and significant effect of entrepreneurial marketing to innovative capability and competitive advantage through the innovative capability of MSMEs.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권3호
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• pp.272-275
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• 2014

An improved fuzzy Kalman filtering speed estimation scheme was proposed by means of measuring stator side voltage and current value based on vector control state equation of induction motor. The designed fuzzy adaptive controller conducted recursive online correction of measurement noise covariance matrix by monitoring the ratio of theory residuals and actual residuals to make it approach real noise level gradually, allowing the filter to perform optimal estimation to improve estimation accuracy of EKF. Meanwhile, co-simulation scheme based on MATLAB and Ansoft was proposed in order to improve simulation accuracy. Field-circuit coupling problems of induction motor under the action of vector control were solved and the parameter optimization accuracy was improved dramatically. The simulation and experimental results show that this algorithm has a strong ability to inhibit the random measurement noise. It is able to estimate motor speed accurately, and has superior static and dynamic characteristics.

• 전기전자학회논문지
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• 제22권3호
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• pp.754-758
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• 2018

전력계통에서 해석 하는 방법종류로 정적해석과 동적해석 그리고 온라인 해석과 오프라인 해석으로 나뉜다. 기존의 계통 해석하는 방법으로는 오프라인 정적해석을 이용하며 PSS/E에서도 정적해석을 주로 사용한다. 하지만 우리가 사용하고 있는 실제 계통에서는 실시간으로 값이 변한다. 정확한 해석을 하기 위해 실시간으로 해석이 가능한 온라인 해석과 동적해석이 요구되며 이에 따라 EMS(Energy Management System)에 대한 중요도가 높아지고 있다. 본 논문에서는 다양한 EMS시스템 중에서도 실시간으로 취득 점으로부터 데이터를 받아와 해석 할 수 있는 정적 온라인 해석인 상태추정을 다룰 것이다. 오늘날 DC부하, DC배전망, 신재생에너지 등 다양한 분야에서 DC계통이 확산되고 있다. 이처럼 DC계통에 많은 관심과 이목이 집중되고 있다. 본 논문에서는 DC계통에 접목시킬 수 있는 상태추정에 대한 해석과 사례연구를 통한 사용가능성에 대해 연구하였다.