This study explores the integration of Raman optical amplifiers in a Wavelength Division Multiplexing Passive Optical Network (WDM-PON) system to enhance high-speed data transmission. Traditional amplifiers like Erbiu...
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The Industrial Internet of Things (IIoT) involves the real-time gathering of information from physical devices and technologies for improved perception and management. To ensure information transmission security, an e...
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The emergence of blockchain technology is transforming various aspects, including electronic voting (e-voting) systems, which have become increasingly important due to the need for transparency, accessibility, and sec...
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Integrating deep learning methods into metaheuristic algorithms has gained attention for addressing design-related issues and enhancing performance. The primary objective is to improve solution quality and convergence...
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The specification of experiments expressed as Complex Analytics Workflows is a complex task that involves many decision-making steps with various degrees of complexity. The use of the context, the expert knowledge, an...
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This paper proposes a new ecosystem vision designed to measure and incentivize citizen and corporate engagement in environmental stewardship through circular economy (CE). The ecosystem uses a gamified platform where ...
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In the world of cryptocurrencies, there is the possibility of participating in numerous processes in which some kind of reward is obtained, most often in the form of cryptocurrency. This paper investigates the possibi...
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A collaborative system that includes mobile devices (MDs), edge nodes (ENs), and the cloud is needed where ENs at the network edge can run offloaded tasks of MDs with limited resources and energy for timely processing...
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The phenomenon of atmospheric haze arises due to the scattering of light by minute particles suspended in the atmosphere. This optical effect gives rise to visual degradation in images and videos. The degradation is p...
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The phenomenon of atmospheric haze arises due to the scattering of light by minute particles suspended in the atmosphere. This optical effect gives rise to visual degradation in images and videos. The degradation is primarily influenced by two key factors: atmospheric attenuation and scattered light. Scattered light causes an image to be veiled in a whitish veil, while attenuation diminishes the image inherent contrast. Efforts to enhance image and video quality necessitate the development of dehazing techniques capable of mitigating the adverse impact of haze. This scholarly endeavor presents a comprehensive survey of recent advancements in the domain of dehazing techniques, encompassing both conventional methodologies and those founded on machine learning principles. Traditional dehazing techniques leverage a haze model to deduce a dehazed rendition of an image or frame. In contrast, learning-based techniques employ sophisticated mechanisms such as Convolutional Neural Networks (CNNs) and different deep Generative Adversarial Networks (GANs) to create models that can discern dehazed representations by learning intricate parameters like transmission maps, atmospheric light conditions, or their combined effects. Furthermore, some learning-based approaches facilitate the direct generation of dehazed outputs from hazy inputs by assimilating the non-linear mapping between the two. This review study delves into a comprehensive examination of datasets utilized within learning-based dehazing methodologies, elucidating their characteristics and relevance. Furthermore, a systematic exposition of the merits and demerits inherent in distinct dehazing techniques is presented. The discourse culminates in the synthesis of the primary quandaries and challenges confronted by prevailing dehazing techniques. The assessment of dehazed image and frame quality is facilitated through the application of rigorous evaluation metrics, a discussion of which is incorporated. To provide empiri
In today’s digital age, the Internet is pivotal in bringing both convenience and security concerns. Individuals are vulnerable to unauthorized access and manipulation of their information by potential attackers. A no...
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