Results 101 to 110 of about 116,475 (314)

Micropillar‐Engineered Hybrid Adhesive Patch for Surface‐Conformable and Directional Adhesion

open access: yesAdvanced Materials Technologies, EarlyView.
This work presents a surface‐conformable hybrid adhesive integrating height‐optimized hexagonal micropillars with open‐rectangular cuts. The micropillars enhance rough‐surface contact and microscale crack arrest, while the cuts guide and reverse interfacial cracks for strong and directional adhesion. The multiscale architecture achieves robust pull‐off
Seongjin Park   +4 more
wiley   +1 more source

Improved Almost-Orthogonal Neural Network for Nonlinear System Identification with Application to Anti-Lock Braking Systems

open access: yesApplied Sciences
Accurate modelling of nonlinear dynamical systems remains a fundamental challenge in control engineering, particularly in applications characterized by strong nonlinearities, uncertainty, and varying operating conditions such as anti-lock braking systems
Staniša Perić   +5 more
doaj   +1 more source

Quasi Score is more efficient than Corrected Score in a general nonlinear measurement error model [PDF]

open access: yes, 2005
We compare two consistent estimators of the parameter vector beta of a general exponential family measurement error model with respect to their relative efficiency.
Kukush, Alexander   +5 more
core   +1 more source

A Pressure Microsensor Made of Parylene‐C for Use as Medical Implant

open access: yesAdvanced Materials Technologies, EarlyView.
A monolithic parylene‐C pressure sensor with gold strain gauges provides 6.2 μV$\mu{\rm V}$·mmHg$\cdot{\rm mmHg}$−1$^{-1}$ sensitivity. The morphology of a sputtered thin film strain sensor is granular/columnar, which results in a high gauge factor of 7.5. Thermal bonding and parylene‐C coating create a hermetic cavity.
Ann‐Kathrin Klein   +2 more
wiley   +1 more source

General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1)

open access: yes
High breakdown-point regression estimators protect against large errors and data con- tamination. We generalize the concept of trimming used by many of these robust estima- tors, such as the least trimmed squares and maximum trimmed likelihood, and ...
Cizek, P.
core  

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov   +3 more
wiley   +1 more source

General Linear Models: An Integrated Approach to Statistics [PDF]

open access: yesTutorials in Quantitative Methods for Psychology, 2008
Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks.
Andrew Faulkner, Sylvain Chartier
doaj  

General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models

open access: yes
High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which unifies and ...
Cizek, P.
core  

Agar‐Based Optical Sensing System With a Phosphorescent Grid Pattern for Measuring Stress Distributions of Root Growth Using the Sampling Moiré Method

open access: yesAdvanced Materials Technologies, EarlyView.
This paper presents an agar medium with a phosphorescent grid pattern that measures the stress distribution generated by growing plant roots. Using phosphorescence, the system optically separates the grid pattern from the root and extracts the grid deformation.
Gakuto Kagawa, Hidetoshi Takahashi
wiley   +1 more source

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