Discrete-time rate-dependent hysteresis modeling and parameter identification of piezoelectric actuators

A discrete-time-modified Bouc–Wen model is proposed to describe the non-symmetrical and rate-dependent hysteresis of piezoelectric actuators for micro-vibration control applications. The modified model combines a non-symmetrical Bouc–Wen model and a frequency-dependent dynamic module. A series of experiments are conducted to characterize the rate-dependent hysteresis of piezoelectric stack actuators under sinusoidal excitations at a range of 1 to 20 Hz. The experimental results verify the validity of the modified model. The modified Bouc–Wen model increases the complexity of Bouc–Wen hysteresis nonlinear differential equation, which brings difficulties to parameter identification. To identify the parameters of Bouc–Wen model, an improved hybrid differential evolution and Jaya (DE-Jaya) algorithm is introduced with a hybrid mutant operator and Jaya operator that tried to balance between convergence speed and solution accuracy. The improved algorithm is tested on benchmark functions and compared with other optimizations to prove its effectiveness. The comparison results show that hybrid DE-Jaya algorithm has better performance in convergence speed and solution accuracy. The identified discrete-time-modified Bouc–Wen model is used as the secondary path in a filtered-x variable step-size affine projection algorithm (FXVSSAPA), and experimental verifications are done on a micro-vibration control platform. The experimental results show that the FXVSSAPA algorithm can converge to the steady-state error faster and verify the effectiveness of the proposed discrete-time-modified Bouc–Wen model.

A new severity classification of lower limb secondary lymphedema based on lymphatic pathway defects in an indocyanine green fluorescent lymphography study

Most protocols for lymphatic imaging of the lower limb conventionally inject tracer materials only into the interdigital space; however, recent studies indicate that there are four independent lymphatic vessel groups (anteromedial, anterolateral, posteromedial, and posterolateral) in the lower limb. Thus, three additional injection sites are needed for lymphatic imaging of the entire lower limb. We aimed to validate a multiple injection designed protocol and demonstrate its clinical benefits. Overall, 206 lower limbs undergoing indocyanine green fluorescent lymphography with the new injection protocol were registered retrospectively. To assess the influence of predictor variables on the degree of severity, multivariable logistic regression models were used with individual known risk factors. Using a generalized linear model, the area under the curve (AUC) of the conventional clinical model, comprising known severity risk factors, was compared with that of the modified model that included defects in the posterolateral and posteromedial groups. Multivariable logistic regression models showed a significant difference for the posteromedial and posterolateral groups. The AUC of the modified model was significantly improved compared to that of the conventional clinical model. Finding defects in the posteromedial and posterolateral groups is a significant criterion for judging lymphedema severity and introducing a new lymphedema severity classification.

A Simplified Tantalum Oxide Memristor Model, Parameters Estimation and Application in Memory Crossbars

In this paper, an improved and simplified modification of a tantalum oxide memristor model is presented. The proposed model is applied and analyzed in hybrid and passive memory crossbars in LTSPICE environment and is based on the standard Ta2O5 memristor model proposed by Hewlett–Packard. The discussed modified model has several main enhancements—inclusion of a simplified window function, improvement of its effectiveness by the use of a simple expression for the i–v relationship, and replacement of the classical Heaviside step function with a differentiable and flat step-like function. The optimal values of coefficients of the tantalum oxide memristor model are derived by comparison of experimental current–voltage relationships and by using a procedure for parameter estimation. A simplified LTSPICE library model, correspondent to the analyzed tantalum oxide memristor, is created in accordance with the considered mathematical model. The improved and altered Ta2O5 memristor model is tested and simulated in hybrid and passive memory crossbars for a state near to a hard-switching operation. After a comparison of several of the best existing memristor models, the main pros of the proposed memristor model are highlighted—its improved implementation, better operating rate, and good switching properties.

Propagation and Transformation of Vortexes in Linear and Nonlinear Radio-Photon Systems

The article is devoted to issues related to the propagation and transformation of vortexes in the optical range of frequency. Within the framework of the traditional and modified model of slowly varying envelope approximation (SVEA), the process of converting vortex beams of the optical domain into vortex beams of the terahertz radio range based on nonlinear generation of a difference frequency in a medium with a second-order susceptibility is considered. The modified SVEA splits a slowly varying amplitude into two factors, which makes it possible to more accurately describe the three-wave mixing process. The theoretical substantiation of the rule of vortex beams topological charges conversion is given—the topological charge of the output radio-vortex beam is equal to the difference between the topological charges of the input optical vortex beams. A numerical simulation model of the processes under consideration has been implemented and analyzed.

Can Popular High-Intensity Interval Training (HIIT) Models Lead to Impossible Training Sessions?

High-Intensity Interval Training (HIIT) is a time-efficient training method suggested to improve health and fitness for the clinical population, healthy subjects, and athletes. Many parameters can impact the difficulty of HIIT sessions. This study aims to highlight and explain, through logical deductions, some limitations of the Skiba and Coggan models, widely used to prescribe HIIT sessions in cycling. We simulated 6198 different HIIT training sessions leading to exhaustion, according to the Skiba and Coggan-Modified (modification of the Coggan model with the introduction of an exhaustion criterion) models, for three fictitious athlete profiles (Time-Trialist, All-Rounder, Sprinter). The simulation revealed impossible sessions (i.e., requiring athletes to surpass their maximal power output over the exercise interval duration), characterized by a few short exercise intervals, performed in the severe and extreme intensity domains, alternating with long recovery bouts. The fraction of impossible sessions depends on the athlete profile and ranges between 4.4 and 22.9% for the Skiba model and 0.6 and 3.2% for the Coggan-Modified model. For practitioners using these HIIT models, this study highlights the importance of understanding these models’ inherent limitations and mathematical assumptions to draw adequate conclusions from their use to prescribe HIIT sessions.

Using Direct Numerical Simulation of Pore-Level Events to Improve Pore-Network Models for Prediction of Residual Trapping of CO2

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO2, it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO2. While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO2-brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO2 obtained from core flow experiments and direct numerical simulation.

Process Corresponding Implications Associated with a Conclusive Model-Fit Current-Voltage Characteristic Curves

NFinFET transistors with various fin widths (110 nm, 115 nm, and 120 nm) are put into measurements, and the data are collected. By using the modified model, the measure data is fitted. Several parameters in the formula of modified model are determined to make both the measured data and the fitting data almost as close as possible. Those parameters are listed and analyzed, including kN (proportional to channel width and gate oxide capacitor, and inversely proportional to the channel length) λ (the inverse of Early Voltage), and sometimes Vth (Threshold Voltage). By kN, the appropriate process control can be high lighted, the corresponding channel concentration can be calculated and thus many implicit physical quantities may be exploited.

Multipurpose Watermarking Approach for Copyright and Integrity of Steganographic Autoencoder Models

With the great achievements of deep learning technology, neural network models have emerged as a new type of intellectual property. Neural network models’ design and training require considerable computational resources and time. Watermarking is a potential solution for achieving copyright protection and integrity of neural network models without excessively compromising the models’ accuracy and stability. In this work, we develop a multipurpose watermarking method for securing the copyright and integrity of a steganographic autoencoder referred to as “HiDDen.” This autoencoder model is used to hide different kinds of watermark messages in digital images. Copyright information is embedded with imperceptibly modified model parameters, and integrity is verified by embedding the Hash value generated from the model parameters. Experimental results show that the proposed multipurpose watermarking method can reliably identify copyright ownership and localize tampered parts of the model parameters. Furthermore, the accuracy and robustness of the autoencoder model are perfectly preserved.