Results 121 to 130 of about 10,821 (279)

Bioinspired Flexible and Stretchable Coil Structure from Ti3C2Tx MXene/AgNPs‐Functionalized Piezoelectric Nanofibers for Enhanced Energy Harvesting

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Ti3C2Tx MXene and Ag nanoparticles are embedded into piezoelectric nanofibers to form a stretchable, self‐powered coil that converts mechanical deformation into electrical energy. The device enables controllable power output during stretching and release while maintaining a compact and lightweight architecture, making it suitable for miniaturized ...
Fatemeh Mokhtari   +6 more
wiley   +1 more source

A generalized attention deficit disorder chaotic model with Soboleva hyperbolic tangent functions [PDF]

open access: yes
This work studies the problem of modeling Attention Deficit Disorder (ADD) using a previously reported one dimensional map, but by replacing its two hyperbolic tangent activation functions, with Soboleva hyperbolic tangent ones.
Lawnik, Marcin   +9 more
core   +1 more source

Eight-Scale Image Contrast Enhancement Based on Adaptive Inverse Hyperbolic Tangent Algorithm [PDF]

open access: yes, 2014
The Eight-Scale parameter adjustment is a natural extension of Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm. It has long been known that the Human Vision System (HVS) heavily depends on detail and edge in the understanding and perception of ...
Chi-Yuan Lin   +3 more
core   +1 more source

A New AILC for a Class of Nonlinearly Parameterized Systems with Unknown Delays and Input Dead-Zone

open access: yesJournal of Applied Mathematics, 2014
This paper presents an adaptive iterative learning control (AILC) scheme for a class of nonlinear systems with unknown time-varying delays and unknown input dead-zone. A novel nonlinear form of deadzone nonlinearity is presented.
Jian-ming Wei, Yun-an Hu, Mei-mei Sun
doaj   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen   +1 more
wiley   +1 more source

Additional Smoothing Transition Autoregressive Models [PDF]

open access: yes
In this paper we present, propose and examine additional membership functions. There is no reason why more functions cannot be proposed. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions.
Giovanis, Eleftherios
core   +1 more source

Parametrized Half-Hyperbolic Tangent Function-Activated Complex-Valued Neural Network Approximation [PDF]

open access: yes
In this paper, we create a family of neural network (NN) operators employing a parametrized and deformed half-hyperbolic tangent function as an activation function and a density function produced by the same activation function. Moreover, we consider the
Seda Karateke   +3 more
core   +1 more source

Sensitivity Analysis of Velocity in Tangent Hyperbolic Fluid Flow Over a Stretching Sheet Under Magnetic Field Influence

open access: yesEngineering Reports
This study presents a numerical sensitivity investigation of the velocity behavior of a tangent hyperbolic fluid over a stretching sheet embedded in a porous medium under slip conditions. The governing equations describing the flow are transformed into a
S. E. Ghasemi
doaj   +1 more source

Seismic Fragility of Gravity and Semi‐Gravity Retaining Walls and Its Impact on the Functionality Loss of Road Infrastructures

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Retaining walls are key geotechnical components of road infrastructure, whose seismic performance directly affects the resilience of transportation networks. Despite their importance, seismic fragility models for retaining walls available in the literature refer only to specific case studies.
Amendola C., Conti R., de Silva F.
wiley   +1 more source

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