A quick neural network for computer vision of gray images

This paper presents a comparison between the traditional image processing method and the area vector concept as well as the new technique of artificial neural networks. Freeman chain coding is considered in the study, and the principle of segmentation may be based and implemented for further investigations resulting from the proposed work. The pattern recognition concept is analyzed and defined through the sigmoid function and the determination of the threshold of a gray image for an object. The block schemes for the given protocols are summarized in a single scheme for illustration and comparison purposes. The synthetic pictures are generated and investigated regarding the dependence of computer vision on the contents of the artificial neural network. The normalization technique is included to eliminate noise and zooming problems. The minimum computational time for image processing with the generated pictures is also determined. The rate of deflection in the computational time is recommended for sensing the minimum computational time according to the variation of the number of hidden units in the hidden layer. A three-layer neural network has been used. The study of gray binary imaging for color pictures is illustrated to save computational time and effort.     

Spontaneous Formation of Liquid Crystals in Ultralarge Graphene Oxide Dispersions

A novel process is developed to synthesize graphene oxide sheets with an ultralarge size based on a solution‐phase method involving pre‐exfoliation of graphite flakes. Spontaneous formation of lyotropic nematic liquid crystals is identified upon the addition of the ultralarge graphene oxide sheets in water above a critical concentration of about 0.1 wt%. It is the lowest filler content ever reported for the formation of liquid crystals from any colloid, arising mainly from the ultrahigh aspect ratio of the graphene oxide sheets of over 30 000. It is proposed that the self‐assembled brick‐like graphene oxide nanostructure can be applied in many areas, such as energy‐storage devices and nanocomposites with a high degree of orientation.     

Analytical solution of three-dimensional Navier–Stokes equations for the flow near an infinite rotating disk

In this letter, we will consider variational iteration method (VIM) and Padé approximant, for finding analytical solutions of three-dimensional viscous flow near an infinite rotating disk. The solutions is compared with the numerical (fourth-order Runge–Kutta) solution. The results illustrate that VIM–Padé is an appropriate method in solving the systems of nonlinear equations. It is predicted that VIM–Padé can have wide application in engineering problems (especially for boundary-layer and natural convection problems).     

Neumann-like integrable models

A countable class of integrable dynamical systems, with four-dimensional phase space and conserved quantities in involution (Hn,In)$(H_n,I_n)$ are exhibited. For n=1$n=1$ we recover Neumann system on T^∗S²$T^{\ast }{S}^2$. All these systems are also integrable at the quantum level.     

Nonlinear Mechanical Response of Polymer Matrix Composites: A Review

Abstract

The present article provides a review on the nonlinear mechanical behavior of polymer matrix composites (PMCs). Initially, essential mechanisms driving the nonlinear response of PMCs under different loading conditions are discussed. Rate-dependence, tension-compression asymmetry, viscous behavior, unloading characteristics, interaction between stress components and effects of environmental factors on mechanical properties are briefly reviewed. This is followed by a review of major approaches and constitutive models for predicting stress–strain behavior of PMCs. Following an increasing degree of complexity, models are categorized into four major classes: nonlinear elasticity models, elastic-plastic models, elastic-plastic-viscous models and Damage-Plasticity models. The vast number of existing models is mainly due to the anisotropy and inhomogeneity of PMCs. In brief, this review focuses on informing the reader of major frameworks, rather than addressing all the models in detail.     

Supercontinuum generation with femtosecond optical pulse compression in silicon photonic crystal fibers at 2500 nm

In this paper, femtosecond optical pulses compression and supercontinuum generation in a triangular silicon photonic crystal fiber at 2500 nm are investigated. A region of large minimum anomalous group velocity dispersion, negligible higher order dispersions and unique nonlinearity of silicon are used to demonstrate compression of 100 fs initial input optical pulses to 2.5 fs and ultra-broadband supercontinuum generation with very low input pulse energy over short distances of the fiber.     

Analysis of multistage amplifiers with hybrid cascode feedforward compensation using a modified model for load impedance

Hybrid cascode feedforward compensation (HCFC) is an effective technique to stabilize nano-scale three-stage amplifiers driving ultra-large load capacitors. It divides the compensation capacitance and shares it between two high-speed local feedback loops embedded within the amplifier core. In this article, a systematic approach to analyze the transfer function and to evaluate the pole expressions of nano-scale HCFC amplifiers is presented. For the first time, the equivalent output impedance is successfully modeled to approximate the complicated transfer function of the HCFC amplifier without the need for lengthy pencil-and-paper calculations. An HCFC amplifier is designed and simulated in 90-nm CMOS technology, to verify the effectiveness of the new analytic approach. The simulated transfer function of the amplifier is almost identical to a calculated transfer function derived based on the new model.     

A novel algorithm to study the impact of the mismatch on analog building blocks: a case study in basic 35 nm CMOS amplifiers

In this paper, the context of modeling of the impact of mismatch and statistical variations on analogue circuit building blocks is emphasized. The aim is to develop a new algorithm which predicts the statistical behavior of important parameters of an amplifier including output resistance, voltage gain and trans-conductance. The relative error of standard deviation of statistical parameters will remain less than 5% compared with the most accurate Monte-Carlo (MC) simulations using atomistic library model-cards. In comparison with other models which are based on the normal distribution of parameters, the proposed model does not need this limiting presumption. On the other hand, the proposed algorithm is more efficient compared with time consuming MC atomistic simulations.     

Synthesis and characterization of PEGylated iron and graphene oxide magnetic composite for curcumin delivery

Nowadays, nanostructures have been given significant attention in medical and biological fields. Among these nanostructures, graphene oxide (GO) has been widely used in drug delivery systems, because of its unique properties, and the ability to connect to other nanostructures such as magnetic nanoparticles (NPs) as well as polymers by its functional groups. In this research, first, GO was prepared by exfoliating graphite according to the modified Hummer’s method, and then the Fe₃O₄ NPs were synthesized by a simple co-precipitation method on GO nanosheets. In the next step, with the help of the ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide coupling reagents, the polyethylene glycol (PEG) polymer was bonded to the GO-Fe₃O₄ nanocomposite. Finally, anti-cancer drug, curcumin (Cur) was loaded onto the nanocomposite and the Cur loading ratio was measured at about 8%. The samples were evaluated using Fourier transform-infrared, differential scanning calorimtery, vibrating-sample magnetometry, atomic force microscopy and dynamic light scattering techniques. The results show that the prepared nanocomposite is an appropriate candidate for biomedical applications.     

Modeling and active control of chatter vibrations of piezoelectric stacked machining arm in micro-turning process

Self-excited vibrations known as chatter are considered as the most detrimental issue in micro-turning processes. Occurring unpredictably, they adversely affect the tool life, productivity rate and surface quality of the machining processes. In this paper, a novel machining arm is modeled as a piezoelectric stacked rod which is subjected to a chatter force in the orthogonal micro-turning process. Due to the fact that machining processes are affected by various sources of uncertainties, H_∞ robust control approach is used to suppress the chatter vibrations of the machining arm in the presence of tool wear and dynamic model parameter variations. Also, input control force of the system is provided by exciting the input voltage of piezoelectric layers of the rod. In order to be certain that the designed controller succeeds in suppressing vibrations of the effective structural modes, behavior of the first three modes of vibrations are considered in the final response of the machining arm. In the following, performance of the robust H_∞ controller is compared with a modified PID controller. Simulation results show that the H_∞ controller improves the robustness and performance of the system against uncertainties. The PID controller extends the stability region of the sharp tool and fails to achieve this purpose for the worn tool although its performance is acceptable in suppressing chatter vibrations.