This paper presents a framework to support the development of three-dimensional virtual scenarios for an operator training simulator for electrical systems. Given the need to represent a variety of scenarios of intere...
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作者:
Butola, RajatLi, YimingKola, Sekhar ReddyNational Yang Ming Chiao Tung University
Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation
The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan
In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SP...
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In this paper, three structures were developed and analyzed, these configurations are based on three-leg ac/dc/ac converters operating as a universal active power filter (UAPF) also known as unified power quality cond...
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This paper presents a topology based on three-leg ac-dc-ac converters for active power filter (APF) applications. The proposed configuration is appropriate for voltage sag/swell compensation, reactive power compensati...
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Two new algorithms to compute the direct and the inverse discrete wavelet transform of continuous streams of data are discussed in this paper. The algorithms are optimized to be used in uniprocessor systems, presentin...
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Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process *** accurate monitoring and controlling...
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Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process *** accurate monitoring and controlling of the process can improve production yield and *** purpose of this paper is to propose a real-time optimization(RTO)using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the ***/methodology/approach-The integration of the esterification process optimization using self-optimization(SO)was developed with classification process was combined with necessary condition optimum(NCO)as gradient adaptive selection,supported with laboratory scaled medium wavelength infrared(mid-IR)sensors,and measured the proposed optimization system indicator in the batch *** Process Modeling and Notation(BPMN 2.0)was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual ***,Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine(SVM)classification and Arduino microcontroller for ***-This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent,lower error measurement with percentage error 1.11 percent,reduced the process duration up to 22 minutes,with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210℃ which was more efficient,as it consumed less *** limitations/implications-In this research the authors just have an experiment for the esterification process using glycerol,but as a development concept of RTO,it would be possible to apply for another chemical reaction or *** implications-This research introduces new development of an RTO approach to optimal con
The human visual system employs a mechanism of visual attention, which selects only part of the incoming information for further processing. Through this mechanism, the brain avoids overloading its limited cognitive c...
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In this paper we introduce a class of granular evolving system modeling approach within the framework of interval analysis. Our aim is to present an interval-based learning algorithm which develops both, granular and ...
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In this paper we introduce an adaptive fuzzy neural network framework for classification of data stream using a partially supervised learning algorithm. The framework consists of an evolving granular neural network ca...
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Image retargeting has seen many applications in areas such as content adaptation for small displays and thumbnailing for image database browsing. Most retargeting methods, however, are too expensive computationally to...
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