Epigenetic modifications, like N6methyladenine (6 mA), regulate genetic configuration and impact the cellular tasks. Recognizing the dissemination of 6mA sites within the rice genome is required for deciphering its in...
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This study investigates using machine learning (ML), the Internet of Things (IoT), and cloud computing to predict cardiovascular diseases. Integrating these advanced technologies in healthcare enables the collection, ...
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The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feat...
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The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrat...
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The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrates how advanced machine learning and specialized deep learning techniques can significantly enhance darknet traffic analysis to strengthen *** diverse classifiers such as random forest and naïve Bayes with a novel spiking neural network architecture provides a robust foundation for identifying concealed *** on the CIC-Darknet2020 dataset establishes state-of-the-art results with 98%accuracy from the random forest model and 84.31%accuracy from the spiking neural *** pioneering application of artificial intelligence advances the frontiers in analyzing the complex characteristics and behaviours of darknet *** proposed techniques lay the groundwork for improved threat intelligence,real-time monitoring,and resilient cyber defense systems against the evolving landscape of cyber threats.
This paper explores the advancements in human motion-tracking technology within the past three years, analyzing research that presents novel methods for capturing and analyzing human movement. We examine the methodolo...
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The increasing prevalence of smishing (SMS phishing) attacks on mobile devices poses significant security risks, particularly for Android users. Traditional spam detection techniques often fail to accurately distingui...
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ISBN:
(纸本)9791188428137
The increasing prevalence of smishing (SMS phishing) attacks on mobile devices poses significant security risks, particularly for Android users. Traditional spam detection techniques often fail to accurately distinguish between legitimate and malicious messages due to the complexity and contextual nature of smishing. In this paper, we propose an AI-driven smishing detection approach using TinyBERT for feature extraction and Aquila Optimization (AO) to optimize a deep learning model. With AO-tuned hyperparameters, the proposed model achieved an accuracy of 96.81%, outperforming standard models like GRU, LSTM, and SVM. Our approach offers a robust, efficient solution for Android smishing detection. Copyright 2025 Global IT research Institute (GIRI). All rights reserved.
Mathematical modeling in the study of dynamic processes in biomedicine is currently widely used. The use of mathematical statistics and formal logic methods in the analysis of complex biomedical processes is especiall...
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— In recent years, time series prediction has become a highly interesting topic in various applied areas, including clinical time series analysis. Hospitals and other clinical healthcare systems collect Electronic He...
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The Harmony Search (HS) algorithm has been used in many applications, including engineering, excavation, epidemiology, object recognition, stock price prediction, genetic analysis, and structural design optimization, ...
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With the rapid increase in cloud services and the increasing shift toward them, balancing the cloud load has become a critical research issue. The increasing demand from customers for technology services worldwide is ...
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