Empirical model generation techniques for planar microwave components using electromagnetic linear regression models

Accurate and efficient empirical model generation techniques of microwave devices, for a large range of geometric and material parameters opportunely chosen, are presented. The empirical models are based on multiple linear regression approach, which compensates the error between an initial inaccurate empirical model and an electromagnetic (EM) full-wave solver (or measurement data). The aim of these techniques is to generate accurate empirical models, which are computationally very efficient with respect to any EM technique. These simple models could be integrated in a toolbox of any commercially available computed-aided design tools for RF/microwave circuits. Comparisons with artificial neural networks and linear-regression-based models are listed and discussed for the dispersion of a microstrip transmission line propagating the quasi-TEM mode and a microwave tunable phase shifter propagating the even mode.     

A secure energy-efficient m-banking application for mobile devices

Mobile banking is one of the emerging services in telecommunications due to the explosive increase in the number of mobile customers around the world. Solutions for mobile banking are varied, ranging from the use of Wireless Transport Layer Security, Security Socket Layer, or application-layer based options. Whereas security at the transport layer is a good choice for e-banking, using it in a mobile device presents several disadvantages such as high energy consumption. In this work, we present a secure energy-efficient m-banking solution for mobile devices. We propose an application-layer protocol whose message formats and message exchanges are designed to reduce time processing, bandwidth use, and energy consumption. Through experimentation, we demonstrate that our secure solution reduces power and energy consumption in more than 30% compared to a secure web-access from the mobile device.     

Architectural synthesis of high-level analogue VHDL-AMSdescriptions using netlist extraction from parse trees

A technique of translating high-level analogue dynamic system behavioural models from VHDL-AMS parse trees into circuit-level netlists is described. The primary application of this work is automatic synthesis of general analogue dynamic systems with feedback. The technique is demonstrated with a practical example of Lorenz`s chaos system synthesis