Due to its potential uses in a number of industries, including healthcare, security, and entertainment, human aberrant activity identification has attracted a lot of interest lately. Real-time detection and classifica...
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Alzheimer's Disease is a progressive neurodegenerative condition distinguished by a steady deterioration in cognitive abilities. Given the empirical inquiries conducted, it is imperative to take age into account a...
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The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** the...
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The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** these devices are constrained in numerous aspects,it leaves network designers and administrators with no choice but to deploy them with minimal or no security at *** have seen distributed denial-ofservice attacks being raised using such devices during the infamous Mirai botnet attack in *** we propose a lightweight authentication protocol to provide proper access to such *** have considered several aspects while designing our authentication protocol,such as scalability,movement,user registration,device registration,*** define the architecture we used a three-layered model consisting of cloud,fog,and edge *** have also proposed several pre-existing cipher suites based on post-quantum cryptography for evaluation and *** also provide a fail-safe mechanism for a situation where an authenticating server might fail,and the deployed IoT devices can self-organize to keep providing services with no human *** find that our protocol works the fastest when using ring learning with *** prove the safety of our authentication protocol using the automated validation of Internet security protocols and applications *** conclusion,we propose a safe,hybrid,and fast authentication protocol for authenticating IoT devices in a fog computing environment.
This study introduces a novel method for recognizing human actions through the semantic segmentation of images. The aim is to enhance action-motion dynamics by directing attention toward regions crucial for action rec...
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This study introduces a novel method for recognizing human actions through the semantic segmentation of images. The aim is to enhance action-motion dynamics by directing attention toward regions crucial for action recognition. The proposed approach utilizes a SegNet model with an incorporated attention mechanism and modified bidirectional gated recurrent unit (BiGRU) backbone. The process begins with the generation of binary masks for each frame in a video dataset, achieved through a combination of grayscale conversion, Gaussian blurring, and adaptive thresholding. The emphasis on crucial regions for action recognition and capturing temporal variations is heightened through the application of the frame-ranking method. In our experiments, we observed that the proposed method significantly enhances the dynamics of the action-motion representation. The SegNet architecture was designed for semantic segmentation tasks and features an encoder-decoder architecture. In this structure, the model performs hierarchical feature extraction from the input image via the encoder, whereas the decoder focuses on reconstructing the segmented output. Attention is paid to the encoded feature maps, augmenting the model's capability to capture dependencies over extensive spatial ranges. A bidirectional GRU layer is employed to capture the sequential dependencies in the concatenated feature maps. The integration of the SegNet model with the attention mechanism and a BiGRU backbone, featuring an encoder-decoder architecture for feature extraction, classification, and segmentation, demonstrated superior performance in capturing nuanced spatiotemporal features. The proposed method demonstrated an accuracy of 98.52% for UCF101 and 84.25% for HMDB51. The findings reveal that the model achieves state-of-the-art results in human action recognition tasks, outperforming the existing methods in terms of accuracy. The combination of semantic segmentation and BiGRU-based temporal modeling proved effec
The secure authentication of user data is crucial in various sectors, including digital banking, medical applications and e-governance, especially for images. Secure communication protects against data tampering and f...
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Vehicular Ad Hoc Networks (VANETs) are important for intelligent transportation systems, permitting vehicles to communicate with one another and nearby infrastructure in order to enhance road safety, traffic managemen...
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A multi-secret image sharing (MSIS) scheme facilitates the secure distribution of multiple images among a group of participants. Several MSIS schemes have been proposed with a (n, n) structure that encodes secret...
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Detecting malicious URLs by employing the Random Forest algorithm alongside URL parsing techniques. The dataset comprises URLs categorized into phishing, benign, and defacement classes. By parsing these URLs, various ...
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Cyber-Physical Systems (CPS) combine physical and computational elements to produce intelligent systems communicating with their surroundings. By integrating digital and physical processes, CPS provides increased func...
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The early diagnosis of lung diseases, including pneumonia, tuberculosis (TB), asthma, fibrosis, and COVID-19 is critical for effective treatment and management. With the emergence of COVID-19, distinguishing between p...
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