Results 151 to 160 of about 426,383 (324)
Energy Science &Engineering, EarlyView.This study develops a framework for predicting flow cessation in ultra‐deep wells, featuring a crude oil property correction model accounting for ultrahigh pressure/temperature effects, a revised liquid holdup model with field‐fitted coefficients, and an integrated pressure drop model coupled with nodal analysis to link reservoir inflow and wellbore ...
Lirong Gao +4 more
wiley +1 more source
Matrix Commutators Over an Algebraically Closed Field [PDF]
, 1975 P. M. Gibson
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Energy Science &Engineering, EarlyView.ABSTRACT PCMs store thermal energy during phase transitions without temperature changes, making them valuable for various thermal applications. When direct PCM use isn't practical, researchers have developed encapsulation methods as an alternative approach.
Mohammed Azeez Alomari +4 more
wiley +1 more source
Berichtigung zu der Arbeit: On Algebraic Curves over Real Closed Fields [PDF]
, 1977 Manfred Knebusch
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Novel Approach for Power Management‐Based NPC STATCOM for Grid‐Connected Photovoltaic Battery System
Energy Science &Engineering, EarlyView.ABSTRACT The development of power quality control systems and methods is a credible step for the modernization of the power grid. In this context, this paper presents novel approaches for the control of power quality and voltage of the power grid using power converters connected to photovoltaic battery systems.
Kamel Sayahi +3 more
wiley +1 more source
Energy Science &Engineering, EarlyView.For output power, light intensity has the highest correlation, indicating that light intensity is the most sensitive factor affecting the output power of PV cells, and its changes have the most significant impact on output power. The change in temperature will lead to changes in the concentration and mobility of carrier inside the battery, which will ...
Biying Zhou, Peng Zhang
wiley +1 more source
A General Approach to Dropout in Quantum Neural Networks
Advanced Quantum Technologies, EarlyView., 2023 Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala +3 more
wiley +1 more source
Small solutions of congruences over algebraic number fields [PDF]
, 1987 Todd Cochrane
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DeepSeek in Education: Exploring the Transformative Potential of AI‐Driven Educational Intelligence
Future in Educational Research, EarlyView.ABSTRACT The integration of artificial intelligence into education remains challenged by issues of scalability, interpretability, and multimodal adaptability. DeepSeek's AI‐driven educational tools show potential to improve educational applications through advances in reasoning efficiency, lightweight deployment, and multimodal fusion.
Jian Liao, Fan Sun, Yajie Liu, Yuli Hu
wiley +1 more source
Benefits of Open Quantum Systems for Quantum Machine Learning
Advanced Quantum Technologies, EarlyView., 2023 Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio +2 more
wiley +1 more source