In this work, a guard array termination structure using hydrogen plasma technology (H-GAT) was proposed for multi-kV AlGaN/GaN heterojunction Schottky barrier diodes. A highest breakdown voltage (BV) of 9.5 kV, a spec...
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Electroencephalography is a technique used to evaluate and record the brain's electrical activity. It is used mostly for medical purposes, to identify various brain disorders like epilepsy, tumors, and others, but...
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CRISPR-Cas9 is significantly potential and versatile gene-editing treatment for neurodegenerative disorders. The CRISPR-Cas9 system incorporates a single guide RNA (sgRNA) and Cas9 nuclease, which helps system to bind...
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With the advancement of artificial intelligence,the dominance of deep learning(DL)models over ordinary machine learning(ML)algorithms has become a reality in recent years due to its capability of handling complex patt...
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With the advancement of artificial intelligence,the dominance of deep learning(DL)models over ordinary machine learning(ML)algorithms has become a reality in recent years due to its capability of handling complex pattern recognition without manual feature *** the growing demands for power savings,building energy loss reduction could benefit from DL *** buildings/rooms with the varying number of occupants,heating,ventilation,and air conditioning(HVAC)systems are often found in operations without much *** reduce the building’s energy loss,accurate occupancy detection/prediction(ODP)results could be used to control the proper operations of ***,ODP is a challenging issue due to multiple reasons,such as improper selection/deployment of sensors,inefficient learning algorithms for pattern recognition,varying room conditions,*** overcome the above challenges,we propose a DL-based framework,i.e.,Deep Weighted Fusion Learning(DWFL),to detect and predict occupancy counts with optimal multi-sensor fusion *** fuses the extracted features from multiple types of sensors with the priority/weight assignment to each *** weight assignment considers different room conditions and the pros/cons of each type of *** evaluate DWFL model in terms of occupancy prediction accuracy,we have set up an experimental testbed with low-cost cameras,carbon dioxide(CO_(2)),and passive infrared(PIR)*** the recently proposed occupancy detection models,DeepFusion utilized deep learning model on heterogeneous sensor data and achieved 88%accuracy in occupancy count estimation(Xue et al.,2019).Another deep learning-based model MI-PIR achieved 91%accuracy on raw analog data from PIR sensors(Andrews et al.,2020).Our research outcome is 94%.Therefore,the experiment results show that our DWFL scheme outperforms the state-of-the-art ODP methods by 3%.
Autism Spectrum Disorders (ASD) describe a heterogeneous set of conditions classified as neurodevelopmental disorders. Although the mechanisms underlying ASD are not yet fully understood, more recent literature focuse...
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In this paper,we study the robustness property of policy optimization(particularly Gauss-Newton gradient descent algorithm which is equivalent to the policy iteration in reinforcement learning)subject to noise at each...
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In this paper,we study the robustness property of policy optimization(particularly Gauss-Newton gradient descent algorithm which is equivalent to the policy iteration in reinforcement learning)subject to noise at each *** invoking the concept of input-to-state stability and utilizing Lyapunov's direct method,it is shown that,if the noise is sufficiently small,the policy iteration algorithm converges to a small neighborhood of the optimal solution even in the presence of noise at each *** expressions of the upperbound on the noise and the size of the neighborhood to which the policies ultimately converge are *** on Willems'fundamental lemma,a learning-based policy iteration algorithm is *** persistent excitation condition can be readily guaranteed by checking the rank of the Hankel matrix related to an exploration *** robustness of the learning-based policy iteration to measurement noise and unknown system disturbances is theoretically demonstrated by the input-to-state stability of the policy *** numerical simulations are conducted to demonstrate the efficacy of the proposed method.
The dynamic range of radar receiver chains is a critical concern in practical scenarios due to the significant variation in power levels between backscattered signals from desired targets and surrounding clutter. High...
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This study explores the challenges of frequency insta-bility in isolated island power systems predominantly powered by fluctuating renewable sources like solar panels and wind turbines. These non-interconnected island...
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The study address the challenge of forecasting per unit energy prices in a microgrid environment consisting of solar and hydro power resources under multi-seasonal *** deep learning techniques such as LSTM,GRU and ESN...
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