Robust image watermarking scheme using bit-plane of hadamard coefficients

Multimedia Tools and Applications - Nowadays, due to widespread usage of the Internet, digital contents are distributed quickly and inexpensively throughout the world. Watermarking techniques can...     

High-blocking-voltage UMOSFETs with reformed electric field distribution

A high-performance vertical GaN metal–oxide–semiconductor field-effect transistor (MOSFET) with a U-shaped gate (UMOSFET) and high blocking voltage is proposed. The main concept behind this work is to reform the electric field distribution to achieve high blocking voltage. The proposed structure includes p-regions in the drift region, which we call reformed electric field (REF) regions. Simulations using the two-dimensional SILVACO simulator reveal the optimum doping concentration, and width and height of the REF regions to achieve the maximum depletion region at the breakdown voltage in the drift region. Also, the electric field distribution in the REF-UMOSFET is reformed by producing additional peaks, which decreases the common peaks under the gate trench. We discuss herein the impact of the height, width, and doping concentration of the REF regions on the ON-resistance (R_ON) and blocking voltage. The blocking voltage, specific ON-resistance, and figure of merit \( \left( {{\text{FOM}} = \frac{{V_{{{\text{BR}}}}^{2} }}{{R_{{{\text{ON}}}} }}} \right) \) are 1140 V, 0.587 mΩ cm² (V_GS = 15 V, V_DS = 1 V), and 2.214 GW/cm², respectively. The blocking voltage and FOM are increased by about 72 % and 171 % in comparison with a conventional UMOSFET (C-UMOSFET).     

A review on the micro- and nanoporous polymeric foams: Preparation and properties

A great number of studies on new synthetic materials have been focused on the preparation of different porous polymers. This review explains the principles and techniques of polymeric foam formation and their features followed by an overview of papers on polymeric porous materials. Physical blowing agent, phase separation, leaching, etching, and thermal decomposition are the main techniques for foam formation that are briefly described. This discussion covers different polymeric foams with various morphologies, pore sizes, and properties. These polymeric foams can be applied for various purposes, including tissue engineering, membranes in separation process, electrical and thermal insulators, packaging, and scaffolds.     

Controlled Preparation and Characterization of Nigella Sativa Electrospun Pad for Controlled Release

Silicon - Nigella sativa (NS) oil is an anti-inflammatory agent in the traditional medicine. In the present study, novel electrospun mats contained NS oil/polyacrylonitrile as a sustained release...     

Multiscale modeling of elastic properties of cortical bone

We model cortical bone as a composite material with hierarchical structure. At a nanostructural level, bone is composed of cross-linked collagen molecules, containing water and non-collagenous proteins in their gaps, reinforced with hydroxyapatite-like nanocrystals. Such a nanocomposite structure represents a mineralized collagen fibril, which serves as a primary building block of bone. At a sub-microstructural level (few microns), the mineralized collagen fibrils are embedded in an extrafibrillar hydroxyapatite matrix to form a single lamella, which also contains the lacunar cavities. At a microstructural level (hundreds of microns) one can distinguish two lamellar structures in the mature cortical bone: osteons, made of concentric layers of lamellae surrounding long hollow Haversian canals, and interstitial lamellae made of remnants of old osteons. At a mesostructural level (several millimeters), the cortical bone is represented by a random collection of osteons and resorption cavities in the interstitial lamellae. A macrostructural level is the whole bone level containing both the cortical (compact) and trabecular (spongy) bone types. In this paper, we predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, spanning from the nanostructural to mesostructural levels, using micromechanics methods and composite materials laminate theories. The results obtained at a lower scale serve as inputs for the modeling at a higher scale. The predictions are in good agreement with the experimental data reported in literature.     

Comparative study of mechanical-electrical-thermal responses of pouch,cylindrical, and prismatic lithium-ion cells under mechanical abuse

In the study, mechanical abuse tests mainly in the form of indentation were performed on the cylindrical cell, pouch cell, and prismatic cell. The mechanical force-displacement response, open circuit voltage (OCV), and temperature distribution were recorded and compared. In spherical head indentation tests of the pouch and prismatic cell and lateral indentation of the cylindrical cell, the peak force is strongly correlated with OCV drop and local temperature increase. However, in flat-end cylinder indentation tests, the internal mechanical damage is progressively developed, and the OCV drop and the temperature increase occur before the peak force. The fracture surfaces of the post-mortem samples were examined to investigate the correlation between fracture patterns and internal short circuit (ISC) behaviors (OCV and temperature distribution). Two distinct fracture patterns were observed that the in-plane fracture induced by biaxial stretching and inter-layers’ fracture induced by shearing. A strong correlation is observed between the number of shear fractures and OCV drop. An increase in the number of inter-layers’ fractures increases the rate of OCV drop. Additionally, the fracture patterns influence the ISC area and location, thereby affecting the heat generation and conduction as well as the temperature distribution.     

Hybrid binary arithmetic optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical data

Gene expression data play a significant role in the development of effective cancer diagnosis and prognosis techniques. However, many redundant, noisy, and irrelevant genes (features) are present in the data, which negatively affect the predictive accuracy of diagnosis and increase the computational burden. To overcome these challenges, a new hybrid filter/wrapper gene selection method, called mRMR-BAOAC-SA, is put forward in this article. The suggested method uses Minimum Redundancy Maximum Relevance (mRMR) as a first-stage filter to pick top-ranked genes. Then, Simulated Annealing (SA) and a crossover operator are introduced into Binary Arithmetic Optimization Algorithm (BAOA) to propose a novel hybrid wrapper feature selection method that aims to discover the smallest set of informative genes for classification purposes. BAOAC-SA is an enhanced version of the BAOA in which SA and crossover are used to help the algorithm in escaping local optima and enhancing its global search capabilities. The proposed method was evaluated on 10 well-known microarray datasets, and its results were compared to other current state-of-the-art gene selection methods. The experimental results show that the proposed approach has a better performance compared to the existing methods in terms of classification accuracy and the minimum number of selected genes.

     

Stability domains of the delay and PID coefficients for general time-delay systems

Time delays are encountered in many physical systems, and they usually threaten the stability and performance of closed-loop systems. The problem of determining all stabilising proportional-integral-derivative (PID) controllers for systems with perturbed delays is less investigated in the literature. In this study, the Rekasius substitution is employed to transform the system parameters to a new space. Then, the singular frequency (SF) method is revised for the Rekasius transformed system. A novel technique is presented to compute the ranges of time delay for which stable PID controller exists. This stability range cannot be readily computed from the previous methods. Finally, it is shown that similar to the original SF method, finite numbers of singular frequencies are sufficient to compute the stable regions in the space of time delay and controller coefficients.     

Speaker independent feature selection for speech emotion recognition: A multi-task approach

Nowadays, automatic speech emotion recognition has numerous applications. One of the important steps of these systems is the feature selection step. Because it is not known which acoustic features of person’s speech are related to speech emotion, much effort has been made to introduce several acoustic features. However, since employing all of these features will lower the learning efficiency of classifiers, it is necessary to select some features. Moreover, when there are several speakers, choosing speaker-independent features is required. For this reason, the present paper attempts to select features which are not only related to the emotion of speech, but are also speaker-independent. For this purpose, the current study proposes a multi-task approach which selects the proper speaker-independent features for each pair of classes. The selected features are then given to the classifier. Finally, the outputs of the classifiers are appropriately combined to achieve an output of a multi-class problem. Simulation results reveal that the proposed approach outperforms other methods and offers higher efficiency in terms of detection accuracy and runtime.

     

Correction to: Automatic COVID-19 detection mechanisms and approaches from medical images: a systematic review

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