Abstract Physical activity (PA) is known to be a risk factor for obesity and chronic diseases such as diabetes metabolic syndrome. Few attempts have been made pattern the time of physical while incorporating intensity duration in order determine relationship this multi-faceted behavior with health. In paper, we explore distance-based approach clustering daily series estimate temporal patterns among U.S. adults (ages 20-65) from National Health Nutrition Examination Survey 2003-2006 (NHANES)....

The aims of this study are to (1) create clusters joint temporal patterns diet and physical activity (PA), (2) determine the association these with health status indicators including body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total blood pressure outcomes obesity, Type 2 Diabetes (T2DM) metabolic syndrome (MS) in U.S. adults 20–65 years. A random day PA from accelerometry data first 24 hour...

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Data-driven temporal dietary patterning (TDP) methods were previously developed. The objectives to create data-driven patterns and assess concurrent validity of energy time cut-offs describing the TDPs by determining their relationships BMI waist circumference (WC). first day 24-h recall timing amounts for 17,915 U.S. adults National Health Nutrition Examination Survey 2007−2016 used clusters representing four using dynamic warping kernel k-means clustering algorithm. Energy extracted from...

This study conducted an in-depth analysis of the momentum shift phenomenon during men's singles matches at 2023 Wimbledon Open, with aim quantifying changes and their impact on match outcomes through a comprehensive data framework that incorporates multivariate statistical methods such as BP neural networks, principal component (PCA), entropy weighting analysis, linear regression. The model, after sensitivity quantification player rankings, is capable predicting shifts providing athletes...

Abstract Stochastic resonance (SR) for weak fault detection stands as a significant constructive methodology leveraging noise in nonlinear information systems processing. In virtue of the SR technique conjunction with coupled non-saturated systems, an exponential unsaturated bistable stochastic (EUBSR) model is developed to enhance output levels. By integrating monostable system (ESR) and (UBSR) through coupling coefficients, this offers broader spectrum characteristics. The performance...

Multiple instance learning(MIL) has shown superior performance in the classification of whole-slide images(WSIs). The implementation multiple learning for WSI typically involves two components, i.e., a feature extractor, which is used to extract features from patches, and an MIL aggregator, responsible generating patch features, also contributing final WSIs. aggregators often employs specific module. To ensure interactive optimization extractor existing state-of-the-art methods select...

Computed tomography is a widely used imaging modality with applications ranging from medical to material analysis. One major challenge arises the lack of scanning information at certain angles, leading distorted CT images artifacts. This results in an ill-posed problem known as Limited Angle Tomography (LACT) reconstruction problem. To address this problem, we propose Residual Null-Space Diffusion Stochastic Differential Equations (RN-SDEs), which are variant diffusion models that...

Abstract Both diet and physical activity are associated with obesity chronic diseases such as diabetes metabolic syndrome. Early efforts in connecting dietary behaviors to generate patterns rarely considered the use of time. In this paper, we propose a distance-based cluster analysis approach find joint temporal among U.S. adults ages 20-65. Dynamic Time Warping (DTW) generalized multi-dimensions is combined commonly used clustering methods unbiased partitioning National Health Nutrition...

This dissertation considers the stability issue for generalized neural networks (GNNs) subject to mixed delays. Firstly, an appropriate Lyapunov-Krasovskii functionals (LKF) is constructed by containing two new delay-product-type (DPT) terms, augmented terms and double integral terms. Then, cooperate with established LKF effectively, improved finite-interval quadratic polynomial inequality utilized handle function negative-determination. As a consequence, less conservative condition...

The integration of time with dietary patterns throughout a day, or temporal (TDP), have been linked quality but links to health outcomes are unknown. TDP were created the objective examine their association status indicators including body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total blood pressure, and chronic diseases obesity, diabetes, metabolic syndrome in US adults 20–65 years. first-day...

Integration of time to physical activity (PA) patterns is novel and may be linked health. Temporal PA integrating were created determine their association with health indicators: body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total blood pressure, chronic diseases obesity, diabetes, metabolic syndrome in US adults 20–65 years. Objectively measured accelerometry data collected from the National...

Given a large matrix containing independent data entries, we consider the problem of detecting submatrix inside that contains larger-than-usual values. Different from previous literature, do not have exact information about dimension potential elevated submatrix. We propose Bonferroni type testing procedure based on permutation tests, and show our proposed test loses no first-order asymptotic power compared to tests with full knowledge In order speed up calculation during test, an...

With the development of social media sites, user credit grading, which served as an important and fashionable problem, has attracted substantial attention from a slew developers operators mobile applications. In particular, multi-grades aimed to achieve (1) anomaly detection risk early warning (2) personalized information service recommendation for privileged users. The above two goals still remained up-to-date challenges. To these ends, in this article, we propose novel regression-based...