In this paper, a high-precision three-dimensional (3-D) near-field (NF) localization method is proposed under an underdetermined case based on a symmetric enhanced nested array (SENA). Firstly, the symmetry of the arr...
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The demand for electricity is increasing exponentially day by day,especially with the arrival of electric *** the smart community neighborhood project,electricity should be produced at the household or community level...
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The demand for electricity is increasing exponentially day by day,especially with the arrival of electric *** the smart community neighborhood project,electricity should be produced at the household or community level and sold or bought according to the *** the actors can produce,sell,and buy according to the demands,thus the name *** solutions can contribute to this in several ways,such as machine learning for analyzing the household data for customer demand and peak hours for the usage of electricity,blockchain as a trustworthy platform for selling or buying,data hub,and ensuring data security and privacy of ***:Token for controlled computation is a framework that allows users to analyze the data without moving the data from the data owner's *** also ensures the data security and privacy of the ***,in this article,we will show the importance of the TOTEM architecture in the EnergiX project and how the extended version of TOTEM can be efficiently merged with the demands of the current and similar projects.
In this work, a weight profile design is presented for efficient Ising solver system based on a Hopfield neural network (HNN) using 32×32 memristor crossbar array. It utilizes device noise in the probabilistic de...
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Rotor angle stability(RAS)prediction is critically essential for maintaining normal operation of the interconnected synchronous machines in power *** wide deployment of phasor measurement units(PMUs)promotes the devel...
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Rotor angle stability(RAS)prediction is critically essential for maintaining normal operation of the interconnected synchronous machines in power *** wide deployment of phasor measurement units(PMUs)promotes the development of data-driven methods for RAS *** paper proposes a temporal and topological embedding deep neural network(TTEDNN)model to accurately and efficiently predict RAS by extracting the temporal and topological features from the PMU *** grid-informed adjacency matrix incorporates the structural and electrical parameter information of the power *** the small-signal RAS with disturbance under initial operating conditions and the transient RAS with short circuits on transmission lines are *** studies of the IEEE 39-bus and IEEE 300-bus power systems are used to test the performance,scalability,and robustness against measurement uncertainties of the TTEDNN *** show that the TTEDNN model performs best among existing deep learning ***,the superior transfer learning ability from small-signal RAS conditions to transient RAS conditions has been proved.
We propose a principal component analysis (PCA)-based approach to quantify (the node dissimilarity index, NDI) the extent of dissimilarity among nodes in a network with respect to values incurred for a suite of node-l...
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Recent advancements in computing speed and capacity of Artificial Intelligence (AI) algorithms have reached a saturation level in performance due to the continuous application of Moore's law which resulted in the ...
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In this paper, a novel algorithm had been proposed to improve the efficiency performance of the wind energy conversion system (WECS) to reach the maximum possible captured power under fast varying wind speed. The perm...
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In this paper, contactless monitoring and classification of human activities and sleeping postures in bed using radio signals is presented. The major contribution of this work is the development of a contactless monit...
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Quantile regression (QR) is a powerful tool for estimating one or more conditional quantiles of a target variable Y given explanatory features X.A limitation of QR is that it is only defined for scalar target variable...
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Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision *** methods of diagnosing and treating the disease are time-consuming and ***,machine learning and deep transfer learning(DTL)tec...
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Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision *** methods of diagnosing and treating the disease are time-consuming and ***,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic *** advanced techniques offer higher accuracy and *** Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease ***,these technological advancements hold great potential for improving the management of diabetic *** study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these *** robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its *** outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance *** study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of *** manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.
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