Abstract
Digital circuits exposed to environments with high levels of radiation, such as those found in High Energy Physics experiments, are prone to Single Event Upsets. These upsets impact the reliability of the circuit. In order to mitigate the effects of the upsets, several well-known techniques for use with register transfer level (RTL) circuit descriptions have been proposed over the years. They typically have a large impact on circuit size and power consumption. Therefore, they are often applied only to the more critical modules of the system. Additionally, the manual implementation of those techniques has a significant cost in terms of time and design effort, involving both RTL changes and tailoring of the synthesis flow to avoid optimizing away the additional hardware. This paper describes an automated workflow that reduces the time for implementing SEU mitigation techniques, avoids the errors caused by manual alteration of the RTL descriptions, and enables the designer to explore different alternatives quickly. The paper describes the application of the workflow to three digital circuits and discusses the data obtained from the implementation of the different mitigation techniques.

Abstract
This work reports a variable attenuator/waveplate based on thermo-optic (TO) effect induced on a waveguide patterned by direct UV-laser writing on films of organic-inorganic di-ureasil hybrids. The waveguide temperature was tuned inducing phase retardation between the transverse electric (TE) and transverse magnetic (TM) modes, resulting in a controllable waveplate. Furthermore, the waveguide TO actuation allows obtaining a variable optical attenuator. The relevant properties, such as attenuation, polarization dependence of the thermal actuation and power consumption will be presented in the NIR (1550 nm). The required electrical power and temperature variation to attain the optical signal extinction and the retardation phase of pi/2 were estimated.

Abstract

Abstract
A growth of the market share of private label brands has been observed in developed countries. This growth was initially confirmed for food and drugstore categories, but it quickly expanded to new product categories, particularly technology products. This study focus on a specific technology segment - the private label brands in smartphones, due to the growth observed in its demand, in recent years. In this context, we analyzed and studied the smartphone market and consumer, and examine the factors influencing purchase intention of private label smartphones. The literature review on private label technological products proved to be scarce, which raised a challenge in exploring the main differences among factors influencing purchase intention for this specific product category. In this study, through the development and application of an analytical model, we test a set of variables that resulted from the literature review, which could potentially influence the purchase intention of smartphones. We applied a questionnaire to a study population, and recorded 339 valid answers. The results were estimated in accordance with the Structural Equation Model. Our analysis highlights the importance given to technology by consumers, as well as price and quality. This study also revealed the importance of private label brands in a market which has as yet been underexplored.

Abstract
A notion of generalized regular expressions for a large class of systems modeled as coalgebras, and an analog of Kleene's theorem and Kleene algebra, were recently proposed by a subset of the authors of this paper. Examples of the systems covered include infinite streams, deterministic automata, Mealy machines and labeled transition systems. In this paper, we present a novel algorithm to decide whether two expressions are bisimilar or not. The procedure is implemented in the automatic theorem prover CIRC, by reducing coinduction to an entailment relation between an algebraic specification and an appropriate set of equations. We illustrate the generality of the tool with three examples: infinite streams of real numbers, Mealy machines and labeled transition systems.

Abstract
Disturbance Management is a major issue in process industries like the pulp and paper (P&P) industry. In this paper, a case study in an integrated P&P mill is examined. Production plans for the whole mill need not only to be optimized concerning company's indicators, but also to be robust so that disturbances can be avoided. We present a simulation-optimization approach that generates plans, correctly weighting their quality (regarding various indicators) and robustness. A discrete-event simulation model replicates the dynamics of implementation and adaptation of production plans in practice. The simulation model gives then feedback to optimization, in order to enhance the analytical model, which is thus able to generate robust plans. © IFAC.