Geomorphic Flood Area is a plugin used to classify flood-prone areas using a linear binary classifier method based on Geomorphic Flood Index. However, key determinant data in this classification are geographic data li...
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Deep reinforcement learning agents have achieved unprecedented results when learning to generalize from unstructured data. However, the “black-box” nature of the trained DRL agents makes it difficult to ensure that ...
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Blood Glucose Monitoring levels are essential to the treatment of diabetes and must be done continuously. Patients often don't comply with conventional glucose monitoring techniques since they cause discomfort and...
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Intelligent Reflective Surfaces (IRSs) enable controlling the radio propagation environment to enhance wireless communications and are particularly relevant for vehicle-to-everything (V2X) applications. This paper exp...
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Gender detection and age estimation have emerged as active and vital research areas, finding widespread applications in diverse fields such as biometrics, social networks, targeted advertising, access control, human-c...
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We present a new graph neural network, the Attention-based Parametric-Kernel augmented Graph Neural Network (APKGNN), developed for node classification tasks. Despite extensive work on modeling multi-faceted relations...
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Active Visual Exploration (AVE) optimizes the utilization of robotic resources in real-world scenarios by sequentially selecting the most informative observations. However, modern methods require a high computational ...
The Internet ofMedical Things(IoMT)is mainly concernedwith the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically,whereas machine learning approaches enable th...
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The Internet ofMedical Things(IoMT)is mainly concernedwith the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically,whereas machine learning approaches enable these smart systems to make informed ***,broadcasting is used for the transmission of frames,whereas congestion,energy efficiency,and excessive load are among the common issues associated with existing *** this paper,a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames,especially with the minimum possible communication overheads in the IoMT *** this purpose,the proposed scheme utilises a well-known technique,i.e.,Kruskal’s algorithm,to find an optimal path from source to destination wearable ***,other evaluation metrics are used to find a reliable and shortest possible communication path between the two interested *** from that,every device is bound to hold a supplementary path,preferably a second optimised path,for situations where the current communication path is no longer available,either due to device failure or heavy ***,the machine learning approach helps enable these devices to update their routing tables simultaneously,and an optimal path could be replaced if a better one is *** proposed mechanism has been tested using a smart environment developed for the healthcare domain using IoMT *** results show that the proposed machine learning-oriented approach performs better than existing approaches where the proposed scheme has achieved the minimum possible ratios,i.e.,17%and 23%,in terms of end to end delay and packet losses,***,the proposed scheme has achieved an approximately 21%improvement in the average throughput compared to the existing schemes.
Alzheimer's disease(AD)is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function,but the etiology of AD is still *** the explosive growth of electronic health data,the...
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Alzheimer's disease(AD)is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function,but the etiology of AD is still *** the explosive growth of electronic health data,the application of artificial inteligence(Al)in the healthcare setting provides excellent potential for exploring etiology and personalized treatment approaches,and improving the disease's diagnostic and prognostic *** paper first briefly introduces Al technologies and applications in medicine,and then presents a comprehensive review of Al in *** simple,it includes etiology discovery based on genetic data,computer-aided diagnosis(CAD),computer-aided prognosis(CAP)of AD using multi-modality data(genetic,neuroimaging and linguistic data),and pharmacological or non-pharmacological approaches for treating ***,some popular publicly available AD datasets are introduced,which are important for advancing Al technologies in AD ***,core research challenges and future research directions are discussed.
We consider the problem of control allocation for weakly redundant systems subject to actuator faults. In particular, the design of a suitable allocator will be devised with the aim of compensating for the fault effec...
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