Transient analysis of diffusion least‐mean squares adaptive networks with noisy channels

In this paper, we study the effect of noisy channels on the transient performance of diffusion adaptive network with least‐mean squares (LMS) learning rule. We first drive the update equation of diffusion LMS which incorporates the effects of noisy channels. Then, using the framework of fundamental weighted energy conservation relation, we derive closed‐form expressions for learning curves in terms of mean‐square deviation and excess mean‐square error. We also find the mean and mean‐square stability bounds of step‐size for diffusion LMS with noisy channels. We show that although noisy channels affect the performance of the diffusion LMS network, the stability bounds of the step‐size are the same form as in the ideal channels case. The derived closed‐form expressions are shown to provide a good match with values found by simulation. Copyright © 2011 John Wiley & Sons, Ltd.     

Model-based design verification for embedded systems through SVOCL: an OCL extension for SystemVerilog

Model Based System Engineering (MBSE) is a renowned approach in the context of embedded systems development. It is frequently used to deal with the structural and behavioral aspects of system design. However, the verification of system design is generally performed in isolation. It is particularly true in the context of assertion based verification. Consequently, there is a huge gap between system design and its verification that seriously effects the productivity and time-to market objectives. Therefore, in this research, we target to reduce this gap by exploiting the features of MBSE and SystemVerilog assertions (SVA’s). This article introduces a novel MBSE approach to model the design verification aspects of embedded systems, along with the system design (structural and behavioral aspects). We propose SystemVerilog in Object Constraint Language (SVOCL), an OCL temporal extension for SystemVerilog, to represent the design verification requirements by means of SVA’s. As a part of research, SVOCL transformation engine has been developed to generate SVA’s code in order to automate the design verification of embedded systems. The application of SVOCL has been validated through four case studies.     

Interactive Instruction in Bayesian Inference

An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions at significantly improved rates. Nonetheless, in novel interactivity conditions, performance was lowered suggesting that more interaction can add more difficulty for participants. Overall, a leap forward in accuracy was found, with more than twice the participant accuracy of previous work. This indicates that an instructional approach to improving human performance in Bayesian inference is a promising direction.     

Automating the sizing of transistors in CMOS gates for low‐power and high‐noise margin operation

This paper presents an automatic method for sizing the transistors in CMOS gates. The method utilizes a feedback control system to efficiently optimize the transistor sizes in small and large fan‐in gates, with the primary goal of enhancing noise robustness (as characterized by the static noise margin). The gates retain their robustness under threshold‐voltage variations over a range of supply voltages. The optimized gates not only expend reduced power and energy, but also take up less area than the conventional ones. These multi‐faceted gains, however, do incur some performance loss. Copyright © 2014 John Wiley & Sons, Ltd.     

Synthesis,Characterization, and Investigation of Inhibitor Release of the Anticorrosion Sol–Gel Hybrid Nanocomposite Coatings

Protection of Metals and Physical Chemistry of Surfaces - Corrosion protective coatings were developed on 1050 aluminum alloy through the sol–gel process using...     

Evaluation of alumina reinforced oil fly ash composites prepared by spark plasma sintering

The thermomechanical behavior of micro/nano-alumina (Al₂O₃) ceramics reinforced with 1-5 wt.% of acid-treated oil fly ash (OFA) was investigated. Composites were sintered using spark plasma sintering (SPS) technique at a temperature of 1400°C by applying a constant uniaxial pressure of 50 MPa. It was evaluated that the fracture toughness of micro- and nanosized composites improved in contrast with the monolithic alumina. Highest fracture toughness value of 4.85 MPam^1/2 was measured for the nanosized composite reinforced with 5 wt.% OFA. The thermal conductivity of the composites (nano-/microsized) decreased with the increase in temperature. However, the addition of OFA (1-5 wt.%) in nanosized alumina enhanced the thermal conductivity at an evaluated temperature. Furthermore, a minimum thermal expansion value of 6.17 ppm*K⁻¹ was measured for nanosized Al₂O₃/5 wt.% OFA composite. Microstructural characterization of Al₂O₃-OFA composites was done by x-ray diffraction and Raman spectroscopy. Oil fly ash particles were seen to be well dispersed within the alumina matrix. Moreover, the comparative analysis of the nano-/microsized Al₂O₃/OFA composites shows that the mechanical and thermal properties were improved in nanosized alumina composites.     

Investigation of miscibility and phase structure of a novel blend of poly(lactic acid) (PLA)/acrylic rubber (ACM) and its nanocomposite with nanosilica

In this work, a novel polymer blend containing poly(lactic acid) (PLA) as a biocompatible and biodegradable thermoplastic and acrylic rubber (ACM) is prepared and the miscibility and phase structure of the blend and its nanocomposite (PLA/ACM/nanosilica) are investigated through theoretical and experimental methods. To predict the phase diagram of the blend, a compressible regular solution model was employed, in which an upper critical solution temperature was observed. The model predicted that PLA/ACM blends are immiscible over the whole composition range at temperatures below 260 °C. Performing scanning force microscopy on the blend showed phase separated structures for the blends containing different amounts of the PLA and ACM. This was in accordance with the results of dynamic mechanical analysis, which revealed two distinct glass transition temperatures for the studied blends. The effect of nanometer sized silica particle on morphology and rheological properties of these blends was also investigated. Scanning force microscopy results showed much reduction of droplet size in the blends containing 2 wt % nanosilica. This was attributed to the suppression effect of nanosilica on the droplets coalescences. Rheological measurements confirmed the interaction of both components with the silica nanofiller. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45499.     

Shape sensitivity analysis of composites in contact using the boundary element method

This paper presents the application of the boundary element method to the shape sensitivity analysis of two-dimensional composite structures in contact. A directly differentiated form of boundary integral equation with respect to geometric design variables is used to calculate shape design sensitivities for anisotropic materials with frictionless contact. The selected design variables are the coordinates of the boundary points either in the contact or non-contact area. Three example problems with anisotropic material properties are presented to validate the applications of this formulation.