The Nigella Sativa seeds were utilized for the environment-friendly zinc oxide nanoparticles(ZnO NPs),as evident by the observation of a white *** analytical techniques,such as XRD,FTIR,UV–vis,SEM,and EDX,were utiliz...
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The Nigella Sativa seeds were utilized for the environment-friendly zinc oxide nanoparticles(ZnO NPs),as evident by the observation of a white *** analytical techniques,such as XRD,FTIR,UV–vis,SEM,and EDX,were utilized to describe the specimen's structural,optical,and electrical *** analysis was used to confirm that the ZnO NPs were *** absorbance peak at 401 nm was observed in the UV–vis,indicating that the ZnO NPs have a 2.91 eV *** groups are present in ZnO NPs,as seen by the FTIR *** nanoparticles'spherical form and average size of 37.9 nm were confirmed by the SEM *** analysis confirmed the composition of the nanoparticles,with zinc accounting for 73.17%and oxygen for 26.83%.ZnO NPs demonstrated excellent electrical conductivity because of their higher surface-to-volume ***,the synthesis of ZnO NPs exhibited effective degradation of methylene blue *** results point to potential applications in several domains,including electronics,biomedical devices,industry,and agriculture,and they call for immediate follow-up research.
The number of Distributed Green Cloud Datacenters (DGCDs) is globally increasing. Such DGCDs deploy different types of renewable sources to generate clean energy and save money. They are located in different regions d...
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This article focuses on inferring a general class of hidden Markov models (HMMs) using data acquired from experts. Expert-acquired data contain decisions/actions made by humans/users for various objectives, such as na...
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The IEEE 802.1Qbv (80.21Qbv) standard is designed for traffic requiring deterministic and bounded latencies through strict periodic time synchronization, as specified by IEEE 802.1AS standard. However, internal clock ...
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The increasing complexity of optical communication systems and networks necessitates advanced methodologies for extracting valuable insights from vast and heterogeneous datasets. Machine learning (ML) and deep learnin...
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The increasing complexity of optical communication systems and networks necessitates advanced methodologies for extracting valuable insights from vast and heterogeneous datasets. Machine learning (ML) and deep learning (DL) have emerged as pivotal tools in this domain, revolutionizing data analysis and enabling automated self-configuration in optical communication systems. Their adoption is fueled by the growing intricacy of systems and links, driven by numerous adjustable and interdependent parameters. This complexity is particularly evident in areas such as coherent transceivers, advanced digital signal processing, optical performance monitoring, cross-layer network optimizations, and nonlinearity compensation. While ML and DL offer immense potential, their application in optical communications is still in its early stages, with significant opportunities remaining unexplored. Many algorithms have yet to be fully deployed in practical settings, underscoring the emerging nature of this research area. This paper presents a comprehensive survey of ML and DL applications across optical fiber communication (OFC), optical wireless communication (OWC), and optical communication networking (OCN), highlighting the challenges, current advancements, and future potential of these approaches. To address the identified gaps, this survey evaluates and compares ML and DL algorithms in terms of their performance, complexity, objectives, input data, metrics, and applications in optical communication. Specific emphasis is placed on identifying how these algorithms enhance system performance and optimization. Furthermore, the advantages and limitations of existing methods are analyzed, offering a clear perspective on the role of ML and DL in this domain. The survey also includes updated visual representations and domain-specific examples to elucidate the practical applications of ML and DL in OFC, OWC, and OCN. It concludes by discussing the open challenges, proposing potential soluti
This paper presents a performance evaluation of the Ordered Reliability Bits Guessing Random Additive Noise Decoding (ORBGRAND) decoder in the context of underwater acoustic communications. Utilizing an underwater aco...
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Wireless communications are particularly vulnerable to eavesdropping attacks due to their broadcast nature. To effectively deal with eavesdroppers, existing security techniques usually require accurate channel state i...
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Person re-identification (ReID) aims to identify pedestrian images with the same identity across non-overlapping camera views. Intra-camera supervised person re-identification (ICS-ReID) is a new paradigm that trains ...
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Chaos theory has been widespread in use in various applications like secure communication and chaotic synchronization. A chaotic system is characterized by bounded and unpredictable trajectory, sensitivity to initial ...
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In the PoS blockchain landscape, the challenge of achieving full decentralization is often hindered by a disproportionate concentration of staked tokens among a few validators. This study analyses this challenge by fi...
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