In competitive physical sports such as boxing, analytics on a boxer's efficiency, particularly the number and kind of punches delivered, offer information and feedback commonly utilized for performance and coachin...
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The demand for more efficient and reliable elevator monitoring systems has increased due to security and safety issues in high-mobility buildings. This paper proposes a microservice architecture for an elevator monito...
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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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Electroencephalogram (EEG) recordings of children are often used to study the underlying neural basis of causal factors of reading disorders and dyslexia. However, the inter-subject variability in EEG and the unconstr...
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We derive new bounds for the condition number of kernel matrices, which we then use to enhance existing non-asymptotic test error bounds for kernel ridgeless regression (KRR) in the overparameterized regime for a fixe...
We derive new bounds for the condition number of kernel matrices, which we then use to enhance existing non-asymptotic test error bounds for kernel ridgeless regression (KRR) in the overparameterized regime for a fixed input dimension. For kernels with polynomial spectral decay, we recover the bound from previous work; for exponential decay, our bound is non-trivial and novel. Our contribution is two-fold: (i) we rigorously prove the phenomena of tempered overfitting and catastrophic overfitting under the sub-Gaussian design assumption, closing an existing gap in the literature; (ii) we identify that the independence of the features plays an important role in guaranteeing tempered overfitting, raising concerns about approximating KRR generalization using the Gaussian design assumption in previous literature.
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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This paper aims to determine the better technique for kidney stone detection between K-Nearest Neighbor (KNN) and Convolutional Neural Networks (CNNs). As well known, the presence of kidney stones is an important topi...
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The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using...
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The rapid advancements in distributed generation technologies,the widespread adoption of distributed energy resources,and the integration of 5G technology have spurred sharing economy businesses within the electricity...
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The rapid advancements in distributed generation technologies,the widespread adoption of distributed energy resources,and the integration of 5G technology have spurred sharing economy businesses within the electricity *** technologies such as blockchain,5G connectivity,and Internet of Things(IoT)devices have facilitated peer-to-peer distribution and real-time response to fluctuations in supply and ***,sharing electricity within a smart community presents numerous challenges,including intricate design considerations,equitable allocation,and accurate forecasting due to the lack of well-organized temporal *** address these challenges,this proposed system is focused on sharing extra electricity within the smart *** working of the proposed system is composed of five main *** phase 1,we develop a model to forecast the energy consumption of the appliances using the Long Short-Term Memory(LSTM)integrated with the attention *** phase 2,based on the predicted energy consumption,we designed a smart scheduler with attention-induced Genetic Algorithm(GA)to schedule the appliances to reduce energy *** phase 3,a dynamic Feed-in Tariff(dFIT)algorithm makes real-time tariff adjustments using LSTM for demand prediction and SHapley Additive exPlanations(SHAP)values to improve model *** phase 4,the energy saved from solar systems and smart scheduling is shared with the community ***,in phase 5,SDP security ensures the integrity and confidentiality of shared energy *** evaluate the performance of energy sharing and scheduling for houses with and without solar support,we simulated the above phases using data obtained from the energy consumption of 17 household appliances in our IoT ***,the simulation results show that the proposed scheme reduces energy consumption and ensures secure and efficient distribution with peers,promoting a more sustainable energy management and res
Residential racial and economic segregation has been linked to significant disparities in health outcomes, including increased risks for major causes of death. Although the Index of Concentration at the Extremes (ICE)...
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