Although millimeter wave (mmWave) mesh networks provide large bandwidth to deliver IoT packets, link failure caused by non-light-of-sight (NLoS) condition degrades network reliability. With the assistance of software ...
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Price comparison websites (PCWs) have become integral to the online shopping experience, enabling consumers to make informed decisions by comparing prices, features, and reviews from multiple retailers. These platform...
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Predicting energy consumption has become crucial to creating a sustainable and intelligent environment. With the aid of forecasts of future demand, the distribution and production of energy can be optimized to meet th...
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Recent advancements in machine learning (ML) have significantly enhanced the accuracy and efficiency of diagnosing dermatological diseases, surpassing conventional methods. This paper presents a detailed exploration o...
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The metaverse represents a groundbreaking concept for the next generation of the Internet and social forms. It maps both the real world and the virtual world into a unified digital space, creating a parallel universe ...
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With the ever-rising risk of phishing attacks, which capitalize on vulnerable human behavior in the contemporary digital space, requires new cybersecurity methods. This literary work contributes to the solution by nov...
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With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant c...
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With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant challenges to information *** techniques embed hidden information into speech streams,making detection increasingly difficult,particularly under conditions of low embedding rates and short speech *** steganalysis methods often struggle to balance detection accuracy and computational efficiency due to their limited ability to effectively capture both temporal and spatial features of speech *** address these challenges,this paper proposes an Efficient Sliding Window Analysis Network(E-SWAN),a novel deep learning model specifically designed for real-time speech steganalysis.E-SWAN integrates two core modules:the LSTM Temporal Feature Miner(LTFM)and the Convolutional Key Feature Miner(CKFM).LTFM captures long-range temporal dependencies using Long Short-Term Memory networks,while CKFM identifies local spatial variations caused by steganographic embedding through convolutional *** modules operate within a sliding window framework,enabling efficient extraction of temporal and spatial *** results on the Chinese CNV and PMS datasets demonstrate the superior performance of *** conditions of a ten-second sample duration and an embedding rate of 10%,E-SWAN achieves a detection accuracy of 62.09%on the PMS dataset,surpassing existing methods by 4.57%,and an accuracy of 82.28%on the CNV dataset,outperforming state-of-the-art methods by 7.29%.These findings validate the robustness and efficiency of E-SWAN under low embedding rates and short durations,offering a promising solution for real-time VoIP *** work provides significant contributions to enhancing information security in digital communications.
Circular dichroism has extensive applications in fields such as ultra-sensitive biosensing and wavefront manipulation within chiral structures. However, traditional terahertz chiral structures face challenges in effec...
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Digital microfluidic biochips (DMFBs) can effectively reduce the cost of biochemical analysis and improve experimental efficiency, as they are easy to carry, use fewer reagent samples and have high precision. Paper-ba...
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This paper gives deeper insight into the range of recent approaches developed and reported in the literature specifically for monophonic acoustic event classification (AEC), polyphonic acoustic event detection (AED) a...
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