In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven t...
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In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.
Researchers are investigating deep learning techniques with their automatic feature learning capabilities for automated rice disease recognition from images. The current study has developed an ensamble model exploring...
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We aim to effectively solve and improvise the Meta Meme Challenge for the binary classification of hateful memes detection on a multimodal dataset launched by Meta. This problem has its challenges in terms of individu...
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Stock market forecasting is one of the most exciting areas of time series forecasting both for the industry and academia. Stock market is a complex, non-linear and non-stationary system with many governing factors and...
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Social media users articulate their opinions on a broad spectrum of subjects and share their experiences through posts comprising multiple modes of expression, leading to a notable surge in such multimodal content on ...
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Internet of Things (IoT) devices are often directly authenticated by the gateways within the network. In complex and large systems, IoT devices may be connected to the gateway through another device in the network. In...
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Recent advancements in satellite technologies have resulted in the emergence of Remote Sensing (RS) images. Hence, the primary imperative research domain is designing a precise retrieval model for retrieving the most ...
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In this paper, we introduce the Maximum Distance Sublattice Problem (MDSP). We observed that the problem of solving an instance of the Closest Vector Problem (CVP) in a lattice L is the same as solving an instance of ...
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Waterborne pathogens pose a lifelong threat, necessitating advanced disinfection systemswith state-of-the-art materials. Laser-Induced Graphene (LIG), a 3-dimensional form ofgraphene, is a widely known electrode mater...
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Waterborne pathogens pose a lifelong threat, necessitating advanced disinfection systemswith state-of-the-art materials. Laser-Induced Graphene (LIG), a 3-dimensional form ofgraphene, is a widely known electrode material for its electrically-induced antimicrobialproperties. However, LIG surfaces exhibit antimicrobial properties exclusively in the presenceof electricity. In this work, copper-doped LIG (Cu-LIG) composite electrodes and filterswere developed with enhanced antimicrobial properties in single-step laser scribing. Thework emphasizes the optimization of copper doping with LIG for both electrical and nonelectrical-based disinfection. The copper doping was optimized to a minimal concentration(∼1%) just to enhance the electrochemical properties of LIG. Furthermore, the excess additionof copper was helpful towards non-electricity-based treatment without significantleaching. The prepared surfaces were tested in both electrodes and filter configuration andshowed excellent antibacterial and antiviral activity against mixed bacterial culture and amodel enteric virus, MS2 bacteriophage. On the application of 2.5 V with Cu-LIG electrodes,6-log removal of bacteria and virus was achieved. Furthermore, the membrane-based electroconductivefilters were tested in a flow-through configuration and demonstrated 6-logremoval at 2.5 V with a flux of ∼ 500 (L·m^(2))/h with both bacteria and viruses at minimumenergy expense. Additionally, reactive oxygen species scavenging and hydrogen peroxidegeneration experiments have confirmed the role of electrical effects and indirect oxidationon the inactivation mechanism. The prepared Cu-LIG composite surfaces showed potentialfor environmental remediation applications.
Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can ha...
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Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).
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