Results 71 to 80 of about 160,280 (251)
Prediction of body image dissatisfaction in university students by multivariate statistical methods
Acta Scientiarum. Health Sciences, 2019 Overweight and obesity are responsible for significant costs of the Brazil’s public health system and can modify the self-perception of the body image, attitudes, cognitions and thoughts.
Vinícius Rodrigues Arruda Pinto +2 more
doaj +1 more source
CHARACTERIZATIONS OF MULTINOMIAL AND NEGATIVE MULTINOMIAL MIXTURES BY REGRESSION
Australian Journal of Statistics, 1984 SummaryCharacterizations are given for mixtures of multinomial and negative multinomial distributions with respect to their index parameter. Several well known multivariate discrete distributions are used as illustrative examples.
openaire +3 more sources
Printed 2.5D‐Microstructures with Material‐Specific Functionalization for Tunable Biosensing
Advanced Materials Technologies, EarlyView.The 2.5D‐MiSENSE platform integrates a microstructured biosensor with an in‐line milking pipeline to enable real‐time detection of mastitis biomarkers during active milk flow. The system uses a 2.5D microengineered surface and patterned electrodes to enhance milk–sensor interaction.
Matin Ataei Kachouei +2 more
wiley +1 more source
Application of Multinomial Logistic Regression to Model the Impact of Rainfall Genesis on the Performance of Storm Overflows: Case Study [PDF]
, 2022 Bartosz Szeląg +7 more
openalex +1 more source
Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
Approximate Sparse Multinomial Logistic Regression for Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 We propose a new learning rule for sparse multinomial logistic regression (SMLR). The new rule is the generalization of the one proposed in the pioneering work by Krishnapuram et al. In our proposed method, the parameters of SMLR are iteratively estimated from log-posterior by using some approximations.
openaire +3 more sources
Advanced Optical Materials, Volume 13, Issue 8, March 13, 2025.The tripodal terpyridine‐1,3,5‐benzene tricarboxamide (BTA) ligand 1 is employed in the self‐assembly formation of novel luminescent materials using a range of lanthanide ions. In the polar protic solution, the results from the photophysical measurements are assessed using nonlinear regression analysis, while the functional material properties of the ...
Jason M. Delente +6 more
wiley +1 more source
Süleyman Demirel Üniversitesi Fen-Edebiyat Fakültesi Fen Dergisi, 2010 : Multinomial logistic (ML) and multinomial conditional logistic (MCL) regression models are used for modeling the relationships between a polytomous response variable and a set of explanatory variables.
Yüksel ÜNVAN, Gamze ÖZEL
doaj
Advanced Robotics Research, EarlyView.Embedded flexible sensing technologies advance underwater soft robotics, yet most systems still suffer from hysteresis and limited perceptiveness. Instead, vision‐based tactile sensors provide reliable and rapid feedback essential for complex underwater tasks.
Qiyi Zhang +5 more
wiley +1 more source
Dirichlet-Multinomial Regression [PDF]
In this paper we provide a Random-Utility based derivation of the Dirichlet-Multinomial regression and posit it as a convenient alternative for dealing with overdispersed multinomial data.
Paulo Guimaraes, Richard Lindrooth
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