Intelligent agents (IAs) are highly autonomous software applications designed for performing tasks in a broad spectrum of virtual environments by circulating freely around them, possibly in numerous copies, and taking...
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The banking sector is widely acknowledged for its intrinsic unpredictability and susceptibility to risk. Bank loans have emerged as one of the most recent services offered over the past several decades. Banks typicall...
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In this study, we review the fundamentals of IoT architecture and we thoroughly present the communication protocols that have been invented especially for IoT technology. Moreover, we analyze security threats, and gen...
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The high demand for data rates in the fifth generation (5G) and beyond of wireless communication can be met by the Non-Orthogonal Multiple Access (NOMA) approach in the millimeter-wave (mmWave) frequency band. Joint p...
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Indoor air quality (IAQ) is an important yet often overlooked aspect of public health, with poor IAQ contributing to a significant number of diverse health problems worldwide. Existing air quality standards have faile...
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Statistical models, enhanced by deep learning techniques, have become pivotal in various predictive tasks, including financial forecasting. This paper addresses the challenge of predicting cryptocurrency prices, utili...
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This research aims to develop an expert system for initial diagnoses of skin diseases in cats using the Decision Tree method. It assists cat owners in identifying skin diseases based on observed symptoms. Data from ex...
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Lip-reading is a process of interpreting speech by visually analysing lip *** research in this area has shifted from simple word recognition to lip-reading sentences in the *** paper attempts to use phonemes as a clas...
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Lip-reading is a process of interpreting speech by visually analysing lip *** research in this area has shifted from simple word recognition to lip-reading sentences in the *** paper attempts to use phonemes as a classification schema for lip-reading sentences to explore an alternative schema and to enhance system *** classification schemas have been investigated,including characterbased and visemes-based *** visual front-end model of the system consists of a Spatial-Temporal(3D)convolution followed by a 2D *** utilise multi-headed attention for phoneme recognition *** the language model,a Recurrent Neural Network is *** performance of the proposed system has been testified with the BBC Lip Reading Sentences 2(LRS2)benchmark *** with the state-of-the-art approaches in lip-reading sentences,the proposed system has demonstrated an improved performance by a 10%lower word error rate on average under varying illumination ratios.
Additive manufacturing, mainly 3D printing, has emerged as a transformative technology with widespread applications across various industries. Despite its advancements, filament brittleness remains a significant chall...
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Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacit...
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Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.
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