Investigation of thermoelastic damping in rectangular microplate resonator using modified couple stress theory

Thermoelastic damping is a significant energy lost mechanism at room temperature in micro-scale resonators. Prediction of thermoelastic damping (TED) is crucial in the design of high quality MEMS resonators. In this study the governing equations of motion and the thermal couple equation of a microplate with an arbitrary rectangular shape are derived using the modified version of the couple stress theory. Analytical expressions are presented for calculating the quality factor (QF) of TED in a rectangular microplate considering the plane stress and plane strain conditions. As a case study, a rectangular microplate resonator is considered with material property of gold that has a considerably high value of length-scale parameter in comparison with silicon and the effect of the length-scale parameter on the QF of TED is discussed in detail. The relation between QF and temperature increment for microplates with clamped boundary conditions based on plane stress and plane strain models are studied and results obtained by considering classical and modified couple stress theory (MCST) are compared. The effect of thickness of the plate on the rigidity ratio is studied and the critical thickness which is an important design parameter is obtained using the MCST for three boundary conditions. Variations of TED versus the plate thickness for various boundary conditions according to the classical and the modified couple stress theories are investigated.     

A Study on Kinematics and Workspace Determination of a General 6-<Emphasis Type="Underline">P</Emphasis> US Robot

This paper proposes the novel adaptive neural network (ADNN) compliant force/position control algorithm applied to a highly nonlinear serial pneumatic artificial muscle (PAM) robot as to improve its compliant force/position output performance. Based on the new adaptive neural ADNN model which is dynamically identified to adapt well all nonlinear features of the 2-axes serial PAM robot, a new hybrid adaptive neural ADNN-PID controller was initiatively implemented for compliant force/position controlling the serial PAM robot system used as an elbow and wrist rehabilitation robot which is subjected to not only the internal coupled-effects interactions but also the external end-effecter contact force variations (from 10[N] up to critical value 30[N]). The experiment results have proved the feasibility of the new control approach compared with the optimal PID control approach. The novel proposed hybrid adaptive neural ADNN-PID compliant force/position controller successfully guides the upper limb of subject to follow the linear and circular trajectories under different variable end-effecter contact force levels.     

A lossless data hiding scheme for medical images using a hybrid solution based on IBRW error histogram computation and quartered interpolation with greedy weights

In the digital world, watermarking technology is a solution for data hiding and completely essential for management and secure communications of digital data propagated over the internet-based platforms. Reversible watermarking is a quality-aware type of watermarking which has been applied in managing digital contents such as digital images, texts, audios and videos. Reversible watermarking is also known as lossless watermarking due to its preservation of all details of host and hidden data. One of the important uses of this kind of watermarking is to manage medical data regarding DICOM images. In the recent years, a new type of reversible watermarking technology entitled interpolation-based reversible watermarking has been introduced, and we are going to enhance it for DICOM images by using a hybrid approach based on computing error histogram and by applying an image interpolation with greedy weights (adaptive weighting). In practice, simulation results clearly show better performance of the proposed scheme compared to the previous techniques using interpolation-based reversible watermarking on different DICOM images.

     

Minimum positive influence dominating set and its application in influence maximization: a learning automata approach

In recent years, with the rapid development of online social networks, an enormous amount of information has been generated and diffused by human interactions through online social networks. The availability of information diffused by users of online social networks has facilitated the investigation of information diffusion and influence maximization. In this paper, we focus on the influence maximization problem in social networks, which refers to the identification of a small subset of target nodes for maximizing the spread of influence under a given diffusion model. We first propose a learning automaton-based algorithm for solving the minimum positive influence dominating set (MPIDS) problem, and then use the MPIDS for influence maximization in online social networks. We also prove that by proper choice of the parameters of the algorithm, the probability of finding the MPIDS can be made as close to unity as possible. Experimental simulations on real and synthetic networks confirm the superiority of the algorithm for finding the MPIDS Experimental results also show that finding initial target seeds for influence maximization using the MPIDS outperforms well-known existing algorithms.     

Entropy generation analysis and heatline visualization of free convection in nanofluid (KKL model-based)-filled cavity including internal active fins using lattice Boltzmann method

Two-dimensional natural convection and entropy generation in a square cavity filled with CuO–water nanofluid is performed. The lattice Boltzmann method is employed to solve the problem numerically. The influences of different Rayleigh numbers $\left(10^3<Ra<10^6\right)$ and solid volume fractions $\left(0<\phi <0.05\right)$ on the fluid flow, heat transfer and total/local entropy generation are presented comprehensively. Also, the heatline visualization is employed to identify the heat energy flow. To predict the thermo-physical properties, dynamic viscosity and thermal conductivity, of CuO–water nanofluid, the KKL model is applied to consider the effect of Brownian motion on nanofluid properties. It is concluded that the configurations of active fins have pronounced effect on the fluid flow, heat transfer and entropy generation. Furthermore, the Nusselt number has direct relationship with Rayleigh number and solid volume fraction, and the entropy generation has direct and reverse relationships with Rayleigh number and solid volume fraction, respectively.     

A Priority-Based MAC Protocol for Energy Consumption and Delay Guaranteed in Wireless Body Area Networks

Wireless Personal Communications - Wireless body area networks (WBANs) consist of tiny sensors that placed around or implant in the human body. These nodes can permanently monitor the health of...     

A content recognizability measure for image quality assessment considering the high frequency attenuating distortions

Multimedia Tools and Applications - The existing image quality assessment (IQA) techniques try to estimate image distortions regardless of their destructive effects on image contents. Analyzing the...     

Decomposition based Multi Objective Evolutionary Algorithms for Design of Large-Scale Water Distribution Networks

In last two decades, multiobjective evolutionary algorithms (MOEAs) have shown their merit for solving different optimization problems within the context of water resources and environmental engineering. MOEAs mainly use the concept of Pareto dominance for obtaining the trade-off solutions considering different criteria. A new alternative method for solving multiobjective problems is multiobjective evolutionary algorithm based on decomposition (MOEA/D) which uses scalarizing the objective functions. In this paper, decomposition strategies are developed for the large-scale water distribution network (WDN) design problems by integrating the concepts of harmony search (HS) and genetic algorithm (GA) within the MOEA/D framework. The proposed algorithms are then compared with two well-known non-dominance based MOEAs: NSGA2 and SPEA2 across four different WDN design problems. Experimental results show that MOEA/D outperform the Pareto dominance methods in terms of both non-domination and diversity criteria. MOEA/D-HS in particular could provide very high quality solutions with a uniform distribution along the Pareto front preserving the diversity and dominating the solutions of the other algorithms. It suggests that decomposition based multiobjective evolutionary algorithms are very promising in dealing with complicated large-scale WDN design problems.     

A model‐based framework for automatic generation of a pattern language verifier

Design patterns solve recurring design problems. One of the best practices, to solve a whole problem in a specific context, is to apply patterns in the form of a collection of related patterns, ie, a pattern language (PL). However, with the rapid growth of the number of patterns and their interrelationships in PLs and because manual verification of the applied PLs is a tedious and error‐prone task, when designing in PL‐based fashion, there is a need for tool support to verify the applied PLs. In our previous work, aimed at automating the development process of PL verification tools, a PL formalism was presented. This paper, based on the presented formalism, describes a framework called Pattern Language Verifier Generator (PLVGen) that automatically generates a pattern language verifier (PLV) for any given PL assuming its constituent patterns are represented in the Unified Modeling Language (UML). Using a modelware approach, two metamodels named pattern language specification language (PLSL) and pattern specification language (PSL) are developed to model the given PL and its patterns, respectively. By getting the models of a PL and its patterns, PLVGen automatically generates an epsilon validation language (EVL) module representing the expected PLV. By launching PLV, the applied PL on a UML model will be verified. To evaluate the applicability of PLVGen in practice, we automatically generated three PLVs. The statistics regarding the generated PLVs, as case studies, illustrate the scalability of PLVGen. Compared with similar tools, the generated PLVs are more portable, transparent, and free of ambiguities.