A compact model for multiterminal bipolar devices used in smartpower applications

Complex technologies merging low-voltage bipolar devices and vertical current-flow power transistor allow more smart functions at low chip cost but pose problems during the design phase because there is no way to predict the influence of the high-voltage transistor over the control components by using standard bipolar junction transistor (BJT) models. In fact the large inductive load usually present in high-voltage power transistors applications forces both negative substrate voltage and spurious currents that can induce positive feedback among parasitic devices, downgrading the performance of a single device and so of the whole circuit. In this work we introduce a model for the five-terminal bipolar devices used in smart power applications. The model accounts for all main static and dynamic parasitic effects and gives results in very good agreement with experimental data on both simple devices and complex integrated circuits currently implemented in commercial products for microprocessor based engine management systems (EMS's)     

Two-Way Protocol with Imperfect Devices

The security of a deterministic quantum scheme for communication, namely the LM05 [1], is studied in presence of a lossy channel under the assumption of imperfect generation and detection of single photons. It is shown that the scheme allows for a rate of distillable secure bits higher than that pertaining to BB84 [2]. We report on a first implementation of LM05 with weak pulses.     

Techniques for the mechanical characterisation of civil structures

Broadly speaking, structural defects include all those changes affecting a structure so that its behaviour is no longer in keeping with its intended use characteristics or differs from the behaviour it was originally designed for. In recent years, damage recognition and location methods, relying on the measurement of parameters that are indicative of a structure's mechanical behaviour, have benefitted from the introduction of innovative approaches, which make it possible to process and correlate an unprecedented wealth of measurble data. The aim of this work is to illustrate the basic problems associated with the different methods used for structural identification (parametric and non-parametric, linear and non-linear, with known and unknown inputs, etc.) and to report on some interesting applications for civil structural diagnosis.     

Fast support vector machines for convolution tree kernels

Feature engineering is one of the most complex aspects of system design in machine learning. Fortunately, kernel methods provide the designer with formidable tools to tackle such complexity. Among others, tree kernels (TKs) have been successfully applied for representing structured data in diverse domains, ranging from bioinformatics and data mining to natural language processing. One drawback of such methods is that learning with them typically requires a large number of kernel computations (quadratic in the number of training examples) between training examples. However, in practice substructures often repeat in the data which makes it possible to avoid a large number of redundant kernel evaluations. In this paper, we propose the use of Directed Acyclic Graphs (DAGs) to compactly represent trees in the training algorithm of Support Vector Machines. In particular, we use DAGs for each iteration of the cutting plane algorithm (CPA) to encode the model composed by a set of trees. This enables DAG kernels to efficiently evaluate TKs between the current model and a given training tree. Consequently, the amount of total computation is reduced by avoiding redundant evaluations over shared substructures. We provide theory and algorithms to formally characterize the above idea, which we tested on several datasets. The empirical results confirm the benefits of the approach in terms of significant speedups over previous state-of-the-art methods. In addition, we propose an alternative sampling strategy within the CPA to address the class-imbalance problem, which coupled with fast learning methods provides a viable TK learning framework for a large class of real-world applications.     

Characterisation of mortar morphology in thin sections by digital image processing

A digital imaging approach was applied to investigate mortar morphology in thin sections; in particular, the binder/aggregate ratio and the grading curve of five mortar bars were attained by digital image processing (DIP), using the Image Pro Plus 4.1 software package. The imaging procedure employed image segmentation, to extract mortar aggregate, and image filtering, to fix grain boundaries. The results show that digital image processing may be considered as an alternative method to mechanical sieving for the characterisation of mortar morphology, as it appears to be quicker and more accurate than the traditional method. However, digital image processing exhibits limits, which are discussed in the text.     

Recycled poly(ethylene terephthalate) and its short glass fibres composites: effects of hygrothermal aging on the thermo-mechanical behaviour

This paper reports on the effects of hygrothermal aging at 70 °C in water and at 80% relative humidity, on the thermo-mechanical properties, molar mass and microstructure of recycled poly(ethylene terephthalate) (rPET) and its short glass fibres composites.For all the investigated materials, the elastic mechanical properties (tensile and storage moduli) determined at low strain levels resulted practically unaffected by hygrothermal aging under the selected conditions. On the other hand, a marked reduction of the tensile strength and apparent fracture toughness has been observed for rPET matrix and its composites during hygrothermal aging, more markedly for materials immersed in water than for those aged at 80% RH. Both properties resulted to be related on the molar mass of the rPET matrix, that decreased during hygrothermal aging as a consequence of the hydrolysis process.The materials glass transition, evaluated as the temperature of the loss factor peak, increased during hygrothermal aging due to the progressively restricted mobility of the amorphous phase caused by a concurrent crystallinity increase. This crystallization process (chemicrystallization) is favoured by temperature, by the plasticizing effect of water and by the reduction of molar mass.Consistently with the mechanical measurements, the morphology of fracture surfaces exposed to hygrothermal aging in water revealed a reduction of plastic deformation of the rPET matrix and a weakening of the fibre-matrix interface for rPET composites.     

EXPERIMENTAL STUDIES OF NUCLEATION PHENOMENA WITHIN THERMAL BOUNDARY LAYERS—INFLUENCE ON CHEMICAL VAPOR DEPOSITION RATE PROCESSES

In carrying out partial vapor condensations using actively cooled surfaces it is known that 'mist' formation can occur within thermal boundary layers (Rosner and Epstein, 1968), dramatically modifying total deposition fluxes. Using a combination of flash-evaporation (Rosner and Liang, 1986) and laser probing techniques, we report new experimental results on binary alkali salt (K₂SO₄ + Na₂SO₄) deposition from combustion gases showing that the deposition rate of potassium sulfate first increases with the addition of sodium sulfate until the concentration of Na₂SO₄ reaches a (target surface temperature dependent) 'threshold' value. Further increases in the concentration of Na₂SO₄ dramatically decrease the total deposition rate of K₂SO₄, implying that potassium sulfate-containing microdroplets are formed within the thermal boundary layer, which, despite their thermophoretic drift toward the target, are not collected as effectively as the 'parent' K₂SO₄-vapor species. Laser light scattering measurements clearly reveal that suspended particles exist near the deposition surface under these conditions. Our experimental results on mass transfer rate and light scattering are consistent with those predicted using laminar boundary layer theory (Castillo and Rosner, 1989b) coupling both binary salt vapor deposition with particle vapor scavenging and deposition. Comparisons of our observed mist onset conditions (implying critical supersaturations near unity) with those expected using homogeneous nucleation theory suggest that the binary alkali sulfate mist nucleation mechanism is, instead, heterogeneous, even in our relatively 'clean' combustion products. Because of the; well-known vapor pressure reduction phenomenon associated here with the formation of non-ideal solutions, binary systems are shown to provide convenient 'vehicles' to investigate BL mist formation onset conditions and CVD-rate consequences without requiring the more extreme surface coolings characteristic of unary condensible vapor systems. An understanding of this dramatic phenomenon, obtained via such laboratory experiments and calculations, will allow its inclusion in future deposition rate calculations of engineering importance.     

What Borromini Might Have Known About Ovals. Ruler and Compass Constructions

This paper is about drawing ovals using a given number of certain parameters. New constructions are displayed, including the case when the symmetry axes are not given. Many of these constructions make use of a recent conjecture by Ragazzo, for which a Euclidean proof is found, thus suggesting it might have been known at the time Borromini chose the ovals for the dome of San Carlo alle Quattro Fontane. A geometric proof of the same conjecture—as well as constructions—in the more general case of eggs and polycentric curves is the subject of the first part of this same research (Mazzotti, a Euclidean approach to eggs and polycentric curves, 2014).     

Robust consensus for uncertain multi‐agent systems with discrete‐time dynamics

This paper investigates robust consensus for multi‐agent systems with discrete‐time dynamics affected by uncertainty. In particular, the paper considers multi‐agent systems with single and double integrators, where the weighted adjacency matrix is a polynomial function of uncertain parameters constrained into a semialgebraic set. Firstly, necessary and sufficient conditions are provided for robust consensus based on the existence of a Lyapunov function polynomially dependent on the uncertainty. In particular, an upper bound on the degree required for achieving necessity is provided. Secondly, a necessary and sufficient condition is provided for robust consensus with single integrator and nonnegative weighted adjacency matrices based on the zeros of a polynomial. Lastly, it is shown how these conditions can be investigated through convex programming by exploiting linear matrix inequalities and sums of squares of polynomials. Some numerical examples illustrate the proposed results. Copyright © 2013 John Wiley & Sons, Ltd.