The integration of electric vehicles (EVs) into the smart grid has introduced new challenges and opportunities for optimizing power and energy management. This paper presents a simple method using a decision-tree to e...
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Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power *** power ...
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Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power *** power systems’behaviors during cascading failures is of great importance to comprehend how failures originate and propagate,as well as to develop effective preventive and mitigative control *** intricate mechanism of cascading failures,characterized by multi-timescale dynamics,presents exceptional challenges for their *** paper provides a comprehensive review of simulation models for cascading failures,providing a systematic categorization and a comparison of these *** challenges and potential research directions for the future are also discussed.
Ferroelectric field-effect transistors (FeFETs) are a promising emerging non-volatile memory, but the impact of manufacturing imperfections on these devices has yet to be studied comprehensively. We extend a previous ...
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Flexible neuromorphic computing systems have emerged as a promising candidate for next-generation edge computing systems, especially for the development of lightweight, low-power spiking neural network (SNN) systems. ...
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Modern data mining methods have demonstrated effectiveness in comprehending and predicting materials *** essential component in the process of materials discovery is to know which material(s)will possess desirable ***...
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Modern data mining methods have demonstrated effectiveness in comprehending and predicting materials *** essential component in the process of materials discovery is to know which material(s)will possess desirable *** many materials properties,performing experiments and density functional theory computations are costly and ***,it is challenging to build accurate predictive models for such properties using conventional data mining methods due to the small amount of available *** we present a framework for materials property prediction tasks using structure information that leverages graph neural network-based architecture along with deep-transfer-learning techniques to drastically improve the model’s predictive ability on diverse materials(3D/2D,inorganic/organic,computational/experimental)*** evaluated the proposed framework in cross-property and cross-materials class scenarios using 115 datasets to find that transfer learning models outperform the models trained from scratch in 104 cases,i.e.,≈90%,with additional benefits in performance for extrapolation *** believe the proposed framework can be widely useful in accelerating materials discovery in materials science.
Magnetoinductive Waveguides (MIWs) consist of coupled electrically small resonant elements that support the propagation of magnetoinductive waves. By exciting current on an element, a magnetic field is formed, leading...
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For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition *** to magnetic saturation,existing methods require nonlinear saturation model and measurements from mu...
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For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition *** to magnetic saturation,existing methods require nonlinear saturation model and measurements from multiple load/current conditions,and the estimation is relying on the accuracy of saturation model and other machine parameters in the *** harmonic produced by harmonic currents is inductance-dependent,and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance *** estimation models are built based on either the magnitude or phase angle,and the inductances can be from d-axis voltage and the magnitude or phase angle,in which the filter influence in harmonic extraction is considered to ensure the estimation *** inductances can be estimated from the measurements under one load condition,which is free of saturation ***,the inductance estimation is robust to the change of other machine *** proposed approach can effectively improve estimation accuracy especially under the condition with low current *** and comparisons are conducted on a test PMSM to validate the proposed approach.
A novel approach defined by the artificial neural network (ANN) model trained by the improved Gauss-Newton in conjunction with a simulated annealing technique is used to control a step-up converter. To elucidate the s...
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We propose a family of second-order resonance-based sinusoidal oscillators with electronically tunable frequencies. Each oscillator is comprised of two amplifiers, surrounded by four impedances which must be a single ...
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The study examined various filtering methods applied to ECG signals;the MIT-BIH Arrhythmia dataset included two channels to reduce noise and artifacts while maintaining critical waveform characteristics. Initial filte...
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