Developement of simulation tools for the analysis of variability in advanced semiconductor electron devices

The progressive down-scaling has been the driving force behind the integrated circuit (IC) industry for several decades, continuously delivering higher component densities and greater chip functionality, while reducing the cost per function from one CMOS technology generation to the next. Moore’s law boosts IC industry profits by constantly releasing high-quality and inexpensive electronic applications into the market using new technologies. From the 1 m gate lengths of the eighties to the 35 nm gate lengths of contemporary 22 nm technology, the industry successfully achieved its scaling goals, not only miniaturizing devices but also improving device performance

Can Telematics Improve Driving Style? The Use of Behavioural Data in Motor Insurance

The use of behavioural data in insurance is loaded with promises and unresolved issues. This paper explores the related opportunities and challenges analysing the use of telematics data in third-party liability motor insurance. Behavioural data are used not only to refine the risk profile of policyholders, but also to implement innovative coaching strategies, feeding back to the drivers the aggregated information obtained from the data. The purpose is to encourage an improvement in their driving style. Our research explores the effectiveness of coaching on the basis of an empirical investigation of the dataset of a company selling telematics motor insurance policies. The results of our quantitative analysis show that this effectiveness crucially depends on the propensity of policyholders to engage with the telematics app. We observe engagement as an additional kind of behaviour, producing second-order behavioural data that can also be recorded and strategically used by insurance companies. The conclusions discuss potential advantages and risks connected with this extended interpretation of behavioural data.Comment: Paper sent for publication on a journal. This is a preliminary version, updated versions will be uploade

The EcoThermo project: key and innovative aspects

In this paper we present the most innovative aspects of the EC-FP7 EcoThermo project. The main aim of the project consists on innovating the technique of heat cost allocation in buildings with a centralized heating system, overcoming the heat cost allocator drawbacks for reliability, measurement reproducibility and traceability and contexts of applications. Given the complexity of the project, we will focus on its main aspects, such as the use of a virtual sensor to estimate the radiators heating power, the design of electronic valves fitted out with an energy harvesting system and the original wireless communication protocol

Parameters Estimation of Hydraulic Circuit Head Losses for Virtual Sensor Design

This paper presents the procedure used to design a so-called virtual sensor (VS) that is able to estimate fluid flow rates (FRs) in the elements of a complex hydraulic closed network, only knowing the total FR imposed by the circulator pump and the open/closed state of the valves that section off each subnet. The VS is based on a mathematical model representing the relationship between FR and head loss (HL). An identification procedure is developed to estimate the numerical values of the parameters of the FR/HL relationship. Once the mathematical model is completely known, in terms of its topological representation and the numerical values of all the model parameters, a flow-solver algorithm is used to estimate the FR in each branch of the hydraulic circuit. The importance of such a mathematical device is evidenced by the necessity to compute the heating power, directly depending on the hydraulic FR, that each single heating body releases, in order to give a new solution going beyond the current technologies to many problems, such as, for example, the optimization of the central heat generator efficiency or the fair cost allocation in the management of old centralized heating plants. The good results obtained from different tests, carried on a reference mock-up, are presented to prove the reliability and the efficiency of the proposed approach

Optimal Scheduling of Distributed Energy Storage Systems by Means of ACO Algorithm

Energy Storage is the best candidate to improve renewable energy penetration and moderate the intermittent generation problems supporting the match between energy demand and production. This paper addresses the optimal storage operations scheduling based on load and renewable production forecast. Stored energy is controlled to minimize the energy input from the grid and maximizing the revenue from selling renewable energy. This work proposes an optimal scheduling solution based on the Ant Colony Optimization (ACO) algorithm enabling the battery to respond to external signals, e.g. the energy price or on the basis of energy trades. This feature is highly demanded in scenarios with a high share of intermittent renewable energy sources. Four different ACO implementations, customized with respect to the specific problem, are compared. The developed algorithms have been tested by using real load consumption data along a week

A Green's function approach to the analysis of non volatile memory device variability as a function of individual trap position

This paper is aimed at exploring efficient approaches for the simulation of Random Telegraph Noise (RTN) in variability analysis of advanced floating gate non-volatile memories. RTN is traced back to randomly occupied localized traps located close to the Si/SiO2interface. While the effect of traps has been investigated previously by means of time-consuming Monte Carlo simulations, in this work we try to exploit an efficient Green Function based analysis, akin to the one implemented in Synopsys SDevice for Random Doping Fluctuations (RDF)