• Journal of Power Electronics
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• v.10 no.1
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• pp.21-26
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• 2010

The most important feature of the one-cycle control method is its excellent ability in line disturbance rejection. However, when it is used as a controller in dc-dc converters, it has an undesirable transient response. The voltage overshoot at the transient time, which usually exists in one-cycle controlled converters, is unwanted in many applications and it is sometimes hazardous. In this paper, it is shown that the combination of a one-cycle controller with a current mode controller, can improve the transient response and consequently the overshoot can be controlled. Therefore, the combined controller has the excellent line disturbance rejection of a one-cycle controller and the output current limiting capability of current mode controllers. Because in this scheme a one-cycle controller is the master controller, the problem of instability of current mode control, will not happen. By simulation and a practical prototype, the capability of the method is shown.

• MALSORI
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• no.53
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• pp.103-118
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• 2005

The performance of speech recognition system is degraded by mismatch between training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE) was introduced to overcome environmental mismatch using stereo data. In this paper, we propose several methods to improve the conventional SPLICE and evaluate them in the Aurora2 task. We generalize SPLICE to compensate for covariance matrix as well as mean vector in the feature space, and thereby yielding the error rate reduction of 48.93%. We also employ the weighted sum of correction vectors using posterior probabilities of all Gaussians, and the error rate reduction of 48.62% is achieved. With the combination of the above two methods, the error rate is reduced by 49.61% from the Aurora2 baseline system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3322-3337
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• 2018

Sleep mode detection is a significant power management and green computing feature. However, it is difficult for televisions and smart TVs to detect deactivation events because we can use these devices without the assistance of an input device. In this paper, we propose a robust method for smart TVs to detect deactivation events based on a visual combination of face and motion detection. The results of experiments conducted indicate that the proposed method significantly reduces incorrect face detection and human absence by means of motion detection. The results also show that the proposed method is robust and effective for smart TVs to reduce power consumption.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.653-668
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• 2011

This paper presents a new hybrid method for solving nonlinear complementarity problems with $P_0$-functions. It can be regarded as a combination of smoothing trust region method with ODE-based method and line search technique. A feature of the proposed method is that at each iteration, a linear system is only solved once to obtain a trial step, thus avoiding solving a trust region subproblem. Another is that when a trial step is not accepted, the method does not resolve the linear system but generates an iterative point whose step-length is defined by a line search. Under some conditions, the method is proven to be globally and superlinearly convergent. Preliminary numerical results indicate that the proposed method is promising.

• Speech Sciences
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• v.11 no.2
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• pp.247-257
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• 2004

There has been many research efforts to overcome the problems of speech recognition in the noisy conditions. Among them, the model-based compensation methods such as the parallel model combination (PMC) and vector Taylor series (VTS) have been found to perform efficiently compared with the previous speech enhancement methods or the feature-based approaches. In this paper, a data-driven model compensation approach that adapts the HMM(hidden Markv model) parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional model-based methods such as the PMC, the statistics necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared with the PMC for the noisy speech recognition.

• Journal of Microbiology and Biotechnology
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• v.19 no.11
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• pp.1301-1305
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• 2009

The evolution of living organisms occurs via a combination of highly complicated processes that involve modification of various features such as appearance, metabolism and sensing systems. To understand the evolution of life, it is necessary to understand how each biological feature has been optimized in response to new environmental conditions and interrelated with other features through evolution. To accomplish this, we constructed contents-based trees for a two-component system (TCS) and metabolic network to determine how the environmental communication mechanism and the intracellular metabolism have evolved, respectively. We then conducted a comparative analysis of the two trees using ARACNE to evaluate the evolutionary and functional relationship between TCS and metabolism. The results showed that such integrated analysis can give new insight into the study of bacterial evolution.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.311-311
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• 2000

We propose a DP-based formulation for matching line patterns by defining a robust and stable geometric representation that is based on the conceptual organizations. Usually, the endpoint proximity and collinearity of image lines, as two main conceptual organization groups, are useful cues to match the model shape in the scene. As the endpoint proximity, we detect junctions from image lines. We then search for junction groups by using geometric constraint between the junctions. A junction chain similar to the model chain is searched in the scene, based on a local comparison. A Dynamic Programming-based search algorithm reduces the time complexity for the search of the model chain in the scene. Our system can find a reasonable matching, although there exist severely distorted objects in the scene. We demonstrate the feasibility of the DP-based matching method using both synthetic and real images.

• Transactions of Materials Processing
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• v.13 no.2
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• pp.160-167
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• 2004

In order to theoretically analyze the creep behavior of high Cr steel at $600^{\circ}C$, a unified elasto-viscoplastic constitutive model based on the consideration of dislocation density is proposed. A combination of a kinetic equation describing the mechanical response of a material at a given microstructure in terms of dislocation glide and evolution equations for internal variables characterizing the microstructure provides the constitutive equations of the model. Microstructural features of the material such as the grain size and spacing between second phase particles are directly implemented in the constitutive equations. The internal variables are associated with the total dislocation density in a simple model. The model has a modular structure and can be adjusted to describe a creep behavior using the material parameters obtained from uniaxial tensile tests.

• Journal of Information Technology Services
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• v.7 no.2
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• pp.59-75
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• 2008

Despite our extensive understanding on the Internet business and widely understood first-mover advantage. it is not clearly answered yet whether an internet firm can enjoy the first-mover advantage in the new environment of the Internet. This is mainly because the Internet marketplace itself has a complex combination of various business models, ranging from a simple channel-extension to a whole new business model. Based on new theoretical development on the first-mover advantage, we empirically test whether being an early mover in the Internet environment materially affects firm performance, using clickstream data from Korea where broadband Internet installation is ranked as top among OECD countries. Our results show the effectiveness of first-mover advantage on the web does not exist, regardless of its business model and competitive environment. This result expands our understandings on the e-business, not to mention of the real feature of first-mover advantage.