Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, they have computational and h...
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This paper proposes microgrid reconfiguration based on ring topology to achieve fault-tolerant space microgrids required for long-term space exploration and human presence. Different failure modes of the power electro...
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Agricultural productivity has a critical role in maintaining economies, especially in nations where a significant proportion of the population is engaged in farming. Plant diseases are a serious risk to agricultural p...
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Brain medical image classification is an essential procedure in computer-Aided Diagnosis(CAD)*** methods depend specifically on the local or global *** fusion methods have also been developed,most of which are problem...
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Brain medical image classification is an essential procedure in computer-Aided Diagnosis(CAD)*** methods depend specifically on the local or global *** fusion methods have also been developed,most of which are problem-distinct and have shown to be highly favorable in medical ***,intensity-specific images are not *** recent deep learning methods ensure an efficient means to design an end-to-end model that produces final classification accuracy with brain medical images,compromising *** solve these classification problems,in this paper,Histogram and Time-frequency Differential Deep(HTF-DD)method for medical image classification using Brain Magnetic Resonance Image(MRI)is *** construction of the proposed method involves the following ***,a deep Convolutional Neural Network(CNN)is trained as a pooled feature mapping in a supervised manner and the result that it obtains are standardized intensified pre-processed features for ***,a set of time-frequency features are extracted based on time signal and frequency signal of medical images to obtain time-frequency ***,an efficient model that is based on Differential Deep Learning is designed for obtaining different *** proposed model is evaluated using National Biomedical Imaging Archive(NBIA)images and validation of computational time,computational overhead and classification accuracy for varied Brain MRI has been done.
Epicyclic Bevel Gear Trains (EBGTs) play a vital role in providing highly efficient solutions for power transmissions between shafts in various engineering applications, such as wind turbines and jet airplane engines....
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A disruptive radio communication paradigm is proposed, where the dynamic channel reconfiguration capability of the emerging fluid antennas (FA) and hybrid reflecting intelligent surfaces (RIS) technologies is exploite...
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Wind turbine blades are subjected to a variety of loads, including aerodynamic and gravitational loads. These loads produce aerodynamic strain and vibration in the blades, resulting in rotor blade damage and a reducti...
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Digital twin technology, leveraging sensor data to replicate physical systems, offers a potent means to validate equipment dynamics and control strategies. This paper presents an advanced Hardware-in-the-Loop setup co...
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Data encryption which is associated with cryptography is necessary to prevent the compromise of Personally Identifying. Multi-level security is ensured by combining the Huffman code with certain cryptographic techniqu...
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This paper advances temporal reasoning within dynamically changing high-dimensional noisy observations, focusing on a latent space that characterizes the nonlinear dynamics of objects in their environment. We introduc...
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