To solve the large resource overhead and risk problems of traditional encryption and decryption technologies. This paper presents a secure computing scheme of 8T1C structure based on charge accumulation and dissipatio...
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In the digital era, the rapid dissemination of false information has emerged as a formidable challenge, undermining the credibility of online platforms and posing a threat to informed public discourse. Addressing this...
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Cardiovascular disease continue to pose a major threat to the lives and health of humans across the world. How to achieve portable and high-precision detection has become a research hotspot in preventing cardiovascula...
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In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basi...
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In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.
The paper aims to assist in a more accurate classification of crimes provided by North Macedonia's Ministry of Internal Affairs using machine learning techniques. By means of natural language processing, data is t...
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Agriculture is evolving towards more sustainable practices thanks to the integration of the machine learning and Internet of Things, which addresses many of the issues related to agricultural production and leads to i...
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Current spatiotemporal learning methods for complex data exploit the graph structure as an inductive bias to restrict the function space and improve data and computation efficiency. However, these methods work princip...
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The placement of virtual machines in cloud data centers faces the challenge of multiple optimization goals. For example, the benefits of cloud providers are to reduce the cost of cloud resources and energy consumption...
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The 'free' business model prevails in mobile apps available through the major channels, hinting at the possibility that users 'pay' for the use of the mobile apps by sharing their private data with the...
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In this paper, a multiband miniaturized crescent-shaped patch antenna with circular slots is presented for ultra-wideband applications. The proposed antenna is constructed on a Flame Retardant 4 (FR-4) dielectric subs...
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