Deep neural networks have succeeded in learning balanced and imbalanced data in the field of pneumonia diagnosis. However, both require separate model designs in their respective domains. The pneumonia recognition met...
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Based on a comparative analysis of the Long Short-Term Memory(LSTM)and Gated Recurrent Unit(GRU)networks,we optimize the structure of the GRU network and propose a new modulation recognition method based on feature ex...
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Based on a comparative analysis of the Long Short-Term Memory(LSTM)and Gated Recurrent Unit(GRU)networks,we optimize the structure of the GRU network and propose a new modulation recognition method based on feature extraction and a deep learning ***-order cumulant,Signal-to-Noise Ratio(SNR),instantaneous feature,and the cyclic spectrum of signals are extracted firstly,and then input into the Convolutional Neural Network(CNN)and the parallel network of GRU for *** modulation modes of communication signals are recognized *** results show that the proposed method can achieve high recognition rate at low SNR.
In this article, an event-based neuroadaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network...
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Recently,wireless sensor networks(WSNs)find their applicability in several real-time applications such as disaster management,military,surveillance,healthcare,*** utilization of WSNs in the disaster monitoring process...
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Recently,wireless sensor networks(WSNs)find their applicability in several real-time applications such as disaster management,military,surveillance,healthcare,*** utilization of WSNs in the disaster monitoring process has gained significant attention among research communities and ***-time monitoring of disaster areas using WSN is a challenging process due to the energy-limited sensor ***,the clustering process can be utilized to improve the energy utilization of the nodes and thereby improve the overall functioning of the *** this aspect,this study proposes a novel Lens-Oppositional Wild Goose Optimization based Energy Aware Clustering(LOWGO-EAC)scheme for WSN-assisted real-time disaster *** major intention of the LOWGO-EAC scheme is to perform effective data collection and transmission processes in disaster *** achieve this,the LOWGOEAC technique derives a novel LOWGO algorithm by the integration of the lens oppositional-based learning(LOBL)concept with the traditional WGO algorithm to improve the convergence *** addition,the LOWGO-EAC technique derives a fitness function involving three input parameters like residual energy(RE),distance to the base station(BS)(DBS),and node degree(ND).The proposed LOWGO-EAC technique can accomplish improved energy efficiency and lifetime of WSNs in real-time disaster management *** experimental validation of the LOWGO-EAC model is carried out and the comparative study reported the enhanced performance of the LOWGO-EAC model over the recent approaches.
The management of plastic waste in our ecosystem represents a significant environmental issue, necessitating effective sorting and categorization to facilitate efficient recycling practices. This study introduces a me...
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The rapid advancement of beyond fifth-generation (B5G) networks has opened a new era of high throughput demands, necessitating novel access schemes to overcome the associated challenges. Non-orthogonal multiple access...
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The lexicon is an essential component in the hybrid automatic speech recognition (ASR) system. However, a high-quality lexicon requires significant efforts from the linguistic experts and is difficult to obtain, espec...
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This paper proposes an advanced system for automated insurance claims processing, integrating Natural Language Processing (NLP) and blockchain technology. Unlike existing systems that rely on rule-based automation and...
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A Living being or an organism that is about to vanish from this world will come under the category of Endangered *** Explanation for their state vary from time to time but few important reasons are loss of habitat and...
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Consumer segmentation is essential for accurate targeting and successful marketing efforts in today’s competitive business environment. Modern marketing groups individuals by interests and attributes. Segmentation dr...
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