Gender bias has been extensively studied in both the educational field and the Natural Language Processing (NLP) field, the former using human coding to identify patterns associated with and causes of gender bias in t...
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The use of high-penetration solar photovoltaics (PV) to transmission networks is complicated by voltage rise. Infractions of voltage occur when voltage levels surpass the permitted limits. Several solutions have been ...
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Preventing mechanical faults in motors is often impossible, early detection of air gap eccentricity faults in induction motors is critical in preventing damage to the machine. Therefore, designing a reliable, effectiv...
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Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault *** paper proposes a unified approach for isolation of mult...
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Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault *** paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical *** and sensor fault isolation are accomplished in two independent modules,that monitor the system and are able to isolate the potential faulty actuator(s)or sensor(s).For the sensor fault isolation(SFI)case,a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s).For the actuator fault isolation(AFI)case,a second module is designed,which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s)and,based on a reasoning decision logic and suitably designed AFI thresholds,the faulty actuator(s)set can be *** effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.
Unmanned aerial vehicles(UAVs)technology is rapidly advancing,offering innovative solutions for various industries,including the critical task of oil and gas pipeline ***,the limited flight time of conventional UAVs p...
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Unmanned aerial vehicles(UAVs)technology is rapidly advancing,offering innovative solutions for various industries,including the critical task of oil and gas pipeline ***,the limited flight time of conventional UAVs presents a significant challenge to comprehensive and continuous monitoring,which is crucial for maintaining the integrity of pipeline *** review paper evaluates methods for extending UAV flight endurance,focusing on their potential application in pipeline *** an extensive literature review,this study identifies the latest advancements in UAV technology,evaluates their effectiveness,and highlights the existing gaps in achieving prolonged flight *** techniques,including artificial intelligence(AI),machine learning(ML),and deep learning(DL),are reviewed for their roles in pipeline ***,DL algorithms like You Only Look Once(YOLO)are explored for autonomous flight in UAV-based inspections,real-time defect detection,such as cracks,corrosion,and leaks,enhancing reliability and accuracy.A vital aspect of this research is the proposed deployment of a hybrid drone design combining lighter-than-air(LTA)and heavier-than-air(HTA)principles,achieving a balance of endurance and *** vehicles utilize buoyancy to reduce energy consumption,thereby extending flight *** paper details the methodology for designing LTA vehicles,presenting an analysis of design parameters that align with the requirements for effective pipeline *** ongoing work is currently at Technology Readiness Level(TRL)4,where key components have been validated in laboratory conditions,with fabrication and flight testing planned for the next *** design analysis indicates that LTA configurations could offer significant advantages in flight endurance compared to traditional UAV *** findings lay the groundwork for future fabrication and testing phases,which will be critical
Power quality has become more important due to the increasing expansion of special consumers, increasing demand, and its effect on network voltage. The role of converters with AC output is effective in improving power...
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The main challenges of designing an antenna for modern wireless communication represented size reduction and mutual coupling. In this paper, a four-element multiple-input multiple-output (MIMO) ultra-wideband (UWB) an...
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This study focuses on the development of an electrical demand forecasting model using machine learning techniques, specifically Long Short-Term Memory (LSTM) and eXtreme Gradient Boosting (XGBoost). The objective is t...
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We propose a method that sequentially acquires features and selects a classifier for label assignment in data instances of related variables. The objective is to accurately infer the values of such variables (labels),...
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