The rollout of 5G systems has prompted standards bodies to begin the 6G system design process. The increased complexity of 6G networks will increase the time, money, and effort needed for implementation and administra...
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The Fake news is becoming more and more common due to the significant changes made to the information distribution landscape by the rapid advancement of technology. Misinformation can spread quickly in this environmen...
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Position sensitive device(PSD)sensor is a vital optical element that is mainly used in tracking systems for visible light communication(VLC).Recently,a new reconfigurable PSD architecture *** proposed architecture mak...
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Position sensitive device(PSD)sensor is a vital optical element that is mainly used in tracking systems for visible light communication(VLC).Recently,a new reconfigurable PSD architecture *** proposed architecture makes the PSD perform more functions by modifying its *** the PSD is mainly formed of an array of *** primary concept involves employing transistors to alternate between the operating modes of the photodiodes(photoconductive and photovoltaic).Additionally,alternating among output pins can be done based on the required *** paper presents the mathematical modeling and simulation of a reconfigurable-multifunctional optical sensor which can perform energy harvesting and data acquisition,as well as positioning,which is not available in the traditional *** using the MATLAB software tool was achieved to demonstrate the *** simulation results confirmed the validity of the mathematical modeling and proved that the modified sensor architecture,as depicted by the equations,accurately describes its *** proposed sensor is expected to extend the battery's lifecycle,reduce its physical size,and increase the integration and functionality of the *** presented sensor might be used in free space optical(FSO)communication like cube satellites or even in underwater wireless optical communication(UWOC).
Phase noise measurement of Phase Locked Loop (PLL) in automated test equipment (ATE) is expensive and time-consuming. Indirect phase noise measurement relies on a few correlated low-cost measurements called signatures...
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Mode division multiplexing (MDM) technology represents a significant advancement in high-capacity optical data transmission in photonics integrated circuits (PICs). Among the critical components in MDM architecture ar...
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Automated speaker recognition has recently emerged as a hot and demanding area of study. In this work, we provide a new approach to speaker detection and verification that makes use of attention mechanisms in conjunct...
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Automated speaker recognition has recently emerged as a hot and demanding area of study. In this work, we provide a new approach to speaker detection and verification that makes use of attention mechanisms in conjunction with deep multidimensional acoustic feature acquisition. This approach is based on several deep convolutional neural networks (CNN). In order to get deep, segment-level speaker-specific characteristics from the source speech signal, the suggested method first creates three separate audio components for multi-CNNs: one for training with an unprocessed waveform in one dimension, one for training with a time–frequency Mel-spectrogram in two dimensions, and one for training with dynamic time–space features. The utterance-level analysis outcomes are generated by applying global average pooling to the segment-level outputs acquired from 1D, 2D, and 3D CNN models. Finally, for speaker identification, an attention-based approach skillfully combines features from the three streams to incorporate various outcomes from utterance-level categorization. The extracted deep multimodal speaker properties are demonstrated to be mutually beneficial, allowing for their integration in an attention-based fusion network to yield substantially enhanced performance. In order to test the suggested scheme, we used a number of conventional and real-time audio datasets. The suggested attention-based multi-dimensional fused-feature convolutional neural network (AMDF-CNN) reduces the speaker misclassification error rate by 2.52% when tested against baseline approaches, according to the experimental results. With an impressive identification rate of 97.59%, the AMDF-CNN speaker identification model performed well in the experiments. All the while, we put the model through its paces under different kinds of noise to see how reliable it is. Experimental results show that the suggested strategy outperforms state-of-the-art schemes with a reliability of more than 85%. Relevance of the
The Internet of Things (IoT), which enables seamless connectivity and effective data exchange between physical items and digital systems, has completely changed the way we interact with our surroundings. This study ev...
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Signal detection in massive multiple-input multiple-output(m-MIMO)is a challenging task due to high computational ***,the minimum mean square error(MMSE)method is a popular signal detection,however it involves matrix ...
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Signal detection in massive multiple-input multiple-output(m-MIMO)is a challenging task due to high computational ***,the minimum mean square error(MMSE)method is a popular signal detection,however it involves matrix inversion with complexity of cubic ***,several linear signal detection methods were developed such as Gauss-Seidel,successive over relaxation,Jacobi method,and Richardson methods to provide a trade-off between performance and *** methods are developed for flat fading scenario,however in practice,the channel is frequency selective rather flat *** this paper,we have proposed an efficient signal detection technique based on iterative parallel multistage detection with decision statistics combiner(IPMD-DSC)for uplink m-MIMO-orthogonal frequency division multiplexing(mMIMO-OFDM)system over frequency selective ***,the proposed method is compared with several convention methods with respect to bit error rate(BER)and *** results demonstrate that the proposed method outperforms the MMSE method with lower complexity.
This research work presents the realization of a decisive, substantial, and wideband infinite impulse response-type fractional order digital differentiator (FODD) adopting a new nature-influenced meta-heuristic optimi...
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Electronic auctions(e-auctions)remove the physical limitations of traditional auctions and bring this mechanism to the general ***,most e-auction schemes involve a trusted auctioneer,which is not always credible in **...
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Electronic auctions(e-auctions)remove the physical limitations of traditional auctions and bring this mechanism to the general ***,most e-auction schemes involve a trusted auctioneer,which is not always credible in *** studies have applied cryptography tools to solve this problem by distributing trust,but they ignore the existence of *** this paper,a blockchain-based Privacy-Preserving and Collusion-Resistant scheme(PPCR)for double auctions is proposed by employing both cryptography and blockchain technology,which is the first decentralized and collusion-resistant double auction scheme that guarantees bidder anonymity and bid privacy.A two-server-based auction framework is designed to support off-chain allocation with privacy preservation and on-chain dispute resolution for collusion resistance.A Dispute Resolution agreement(DR)is provided to the auctioneer to prove that they have conducted the auction correctly and the result is fair and *** addition,a Concise Dispute Resolution protocol(CDR)is designed to handle situations where the number of accused winners is small,significantly reducing the computation cost of dispute *** experimental results confirm that PPCR can indeed achieve efficient collusion resistance and verifiability of auction results with low on-chain and off-chain computational overhead.
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