The Vision Transformer (ViT) model serves as a powerful model to capture and comprehend global information, particularly when trained on extensive datasets. Conversely, the Convolutional Neural Network (CNN) model is ...
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The growing risk of cyber-attacks and information vulnerability has become a major problem in today's dynamic digital environment. The necessity for strong security solutions is more critical than ever due to the ...
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Convolutional neural networks (CNNs) have shown very appealing performance for many computer vision applications. The training of CNNs is generally performed using stochastic gradient descent (SGD)-based optimization ...
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The rapid expansion of Internet of Things (IoT) devices in smart homes has significantly improved the quality of life, offering enhanced convenience, automation, and energy efficiency. However, this proliferation of c...
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The system delves into the important topic of agricultural market pricing, with a specific emphasis on the ever-changing realm of vegetable supply and prices. Stabilizing the supply and prices of vegetables becomes an...
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In this paper, we propose a novel infrastructure-dependent ramp-metering control for the recently proposed METANET with service station (METANET-s) model, i.e., a second-order macroscopic traffic model that, compared ...
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Cutting-edge healthcare structures generate and technique a large sort of statistics from a couple of assets. The effective analysis and usage of this facts is vital for decision makers in healthcare, in particular wh...
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Tunneling ionization, a fascinating quantum phenomenon, has played the key role in the development of attosecond physics. Upon absorption of a few tens of photons, tunneling ionization creates ions in different excite...
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Tunneling ionization, a fascinating quantum phenomenon, has played the key role in the development of attosecond physics. Upon absorption of a few tens of photons, tunneling ionization creates ions in different excited states and even enables the formation of population inversion between ionic states. However, the underlying physics is still being debated. Here, we demonstrate a significant enhancement in the efficiency of multiphoton excitation when ionization of neutral molecules and resonant excitation of ions coexist in strong laser fields. It facilitates the dramatic increase in population inversion and lasing radiation in N2+ around 1000 nm pump wavelength. Utilizing the ionization-coupling theory, we discover that the synergistic interplay between tunneling ionization and multiphoton excitation enables the ionic coherence to be maximized by phase locking of the periodically created ionic dipoles and consistently maintain an optimal phase for the follow-up photoexcitation. This Letter provides new insights into the photoexcitation mechanism of ions in strong laser fields and opens up a route for optimizing ionic lasing radiations.
A chronic stroke affects hand mobility limiting the normal functioning of the finger joints. The voluntary tasks with a repetitive motion can identify the limitation in the range of motion (ROM) to enhance the hand fu...
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Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity,mortality,and *** there is a consensus that d...
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Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity,mortality,and *** there is a consensus that dementia is a multifactorial disorder,which portrays changes in the brain of the affected individual as early as 15 years before its onset,prediction models that aim at its early detection and risk identification should consider these *** study aims at presenting a novel method for ten years prediction of dementia using on multifactorial data,which comprised 75 *** are two automated diagnostic systems developed that use genetic algorithms for feature selection,while artificial neural network and deep neural network are used for dementia *** proposed model based on genetic algorithm and deep neural network had achieved the best accuracy of 93.36%,sensitivity of 93.15%,specificity of 91.59%,MCC of 0.4788,and performed superior to other 11 machine learning techniques which were presented in the past for dementia *** identified best predictors were:age,past smoking habit,history of infarct,depression,hip fracture,single leg standing test with right leg,score in the physical component summary and history of TIA/*** identification of risk factors is imperative in the dementia research as an effort to prevent or delay its onset.
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