Nowadays, weather image classification is very important, it can help many sectors, such as daily weather forecasting, disaster control, agriculture, aviation, etc. Deep learning has emerged as an effective method for...
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In the general max–min fair allocation problem, there are m players and n indivisible resources, each player has his/her own utilities for the resources, and the goal is to find an assignment that maximizes the minim...
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Aircraft electrification has received increasing attention due to the significant benefits, such as low carbon emissions, high energy efficiency, low operation cost, and reduced acoustic noise. Limitations on both the...
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We investigate the use of the Neighborhood-based Bridge Node Centrality (NBNC) tuple to choose nodes for preferential vaccination so that such vaccinated nodes could provide herd immunity and reduce the spreading rate...
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Vehicle suspension systems play a pivotal role in ensuring both comfort and safety during driving by maintaining stability and handling. Recent advancements in reinforcement learning (RL) for control design offer adap...
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Various sciences have always considered the maximum use of limited resources and planning to optimize their use. Parking in urban spaces is regarded as a finite resource. This paper investigates the idea of introducin...
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Phasor Measurement Units(PMUs)provide Global Positioning System(GPS)time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid *** synchroniz...
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Phasor Measurement Units(PMUs)provide Global Positioning System(GPS)time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid *** synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition.A PMU device is a crucial part of the power equipment in terms of the cost and operative point of ***,such ongoing development and improvement to PMUs’principal work are essential to the network operators to enhance the grid quality and the operating *** paper introduces a proposed method that led to lowcost and less complex techniques to optimize the performance of PMU using Second-Order Kalman *** is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access *** MATLAB model has been created to implement the proposed method in the presence of Gaussian and *** results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing *** results were tested usingMean Square Error(MSE).The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into thePMUstructure to clarify the significance of the proposed new PMU.
The demand for electricity is increasing exponentially day by day,especially with the arrival of electric *** the smart community neighborhood project,electricity should be produced at the household or community level...
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The demand for electricity is increasing exponentially day by day,especially with the arrival of electric *** the smart community neighborhood project,electricity should be produced at the household or community level and sold or bought according to the *** the actors can produce,sell,and buy according to the demands,thus the name *** solutions can contribute to this in several ways,such as machine learning for analyzing the household data for customer demand and peak hours for the usage of electricity,blockchain as a trustworthy platform for selling or buying,data hub,and ensuring data security and privacy of ***:Token for controlled computation is a framework that allows users to analyze the data without moving the data from the data owner's *** also ensures the data security and privacy of the ***,in this article,we will show the importance of the TOTEM architecture in the EnergiX project and how the extended version of TOTEM can be efficiently merged with the demands of the current and similar projects.
The Internet of Things (IoT) has become in demand nowadays as many embedded devices are connected to the internet to collect a vast amount of data for processing. A substantial amount of this data between IoT devices ...
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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
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