SmartK: Smart cards in operating systems at kernel level

A smart card is a tamper-resistant miniature computer that performs some basic computations on input a secret information. So far, smart cards have been widely used for securing many digital transactions (e.g., pay television, ATM machines).We focus on the implementation of operating system security services leveraging on smart cards. This very challenging feature allows one to personalize some functionalities of the operating system by simply changing a smart card. Current solutions for integrating smart card features in operating system services require at least a partial execution of some of the operating system functionalities at “user level”. Unfortunately, system functionalities built on top of components lying at both kernel and user levels may negatively affect the overall system security, due to the introduction of multiple points of failure.In this work, we present the design and implementation of SmartK: a framework that integrates features of smart cards uniquely in the Linux kernel. In order to validate our approach, we propose a host of enhancements to the Linux operating system built on top of SmartK: 1) in-kernel clients' authentication with Kerberos; 2) execution of trusted code; 3) key management in secure network filesystems.In particular, we present an experimental Linux OS distribution (SalSA), which addresses the security issues related to downloading packages and to updating an operating system through the Internet.     

Solvent vapor treatment controls surface wettability in PMMA femtosecond-laser-ablated microchannels

A solvent vapor treatment was applied to femtosecond-laser-ablated microchannels in PMMA to selectively restore the original hydrophilic wetting behavior of the pristine surface. The hydrophobic surface of the microchannels from the submicron porosity induced by ablation becomes smoother and more transparent after the treatment. This simple and low-cost method, together with suitable masking, can produce wettability patterns that may be exploited to develop passive microfluidic elements such as valves and mixers.     

Analysis of the gate current as a suitable indicator for FET degradation under nonlinear dynamic regime

Electron device degradation, although not directly accounted for, represents a key issue in microwave circuit design. This is especially true when the particular applications involved (e.g., satellite, military, consumer) do not allow or strongly discourage any kind of maintenance. As a matter of fact, in order to account for device degradation in circuit design, a suitable electron device model is needed which is able to predict the performance degradation as a function of the actual electrical regime involved in the device operation. Such a kind of model is not available in literature. In this paper, quantitative results are provided for device degradation indicators which correlate DC and RF stress experiments. These results can be considered an important step toward the definition of a nonlinear model accounting for device degradation.     

Three-dimensional effects induced by FRP-from-masonry delamination

In this study, delamination of a perfectly-adherent FRP reinforcement from a masonry pillar is investigated by means of a fully three-dimensional finite element model. It is shown that the width of the FRP reinforcement governs the propagation of damage through the brick bulk starting from the anchorage of the strip, and influences significantly the overall response in terms of peak strength, ductility and fracture energy. The resulting failure mechanisms are specified. A critical comparison with formulae provided by Italian design code is also provided, for which mechanically-based improvements are suggested, taking into account three-dimensional effects.     

Minimum Hellinger distance based inference for scalar skew-normal and skew-t distributions

The skew-normal is a parametric model that extends the normal family by the addition of a shape parameter to account for skewness. As well, the skew-t distribution is generated by a perturbation of symmetry of the basic Student’s t density. These families share some nice properties. In particular, they allow a continuous variation through different degrees of asymmetry and, in the case of the skew-t, tail thickness, but still retain relevant features of the perturbed symmetric densities. In both models, a problem occurs in the estimation of the skewness parameter: for small and moderate sample sizes, the maximum likelihood method gives rise to an infinite estimate with positive probability, even when the sample skewness is not too large. To get around this phenomenon, we consider the minimum Hellinger distance estimation technique as an alternative to maximum likelihood. The method always leads to a finite estimate of the shape parameter. Furthermore, the procedure is asymptotically efficient under the assumed model and allows for testing hypothesis and setting confidence regions in a standard fashion.     

(Computer) Vision without Sight

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs of the VI population and which of these needs might be addressed by computer vision. This article reviews the types of assistive technology application areas that have already been developed for VI, and the possible roles that computer vision can play in facilitating these applications. We discuss how appropriate user interfaces are designed to translate the output of computer vision algorithms into information that the user can quickly and safely act upon, and how system-level characteristics affect the overall usability of an assistive technology. Finally, we conclude by highlighting a few novel and intriguing areas of application of computer vision to assistive technology.     

Molds and Resists Studies for Nanoimprint Lithography of Electrodes in Low-Voltage Polymer Thin-Film Transistors

A low-cost patterning of electrodes was investigated looking forward to replacing conventional photolithography for the processing of low-operating voltage polymeric thin-film transistors. Hard silicon, etched by sulfur hexafluoride and oxygen gas mixture, and flexible polydimethylsiloxane imprinting molds were studied through atomic force microscopy (AFM) and field emission gun scanning electron microscopy. The higher the concentration of oxygen in reactive ion etching, the lower the etch rate, sidewall angle, and surface roughness. A concentration around 30 % at 100 mTorr, 65 W and 70 sccm was demonstrated as adequate for submicrometric channels, presenting a reduced etch rate of 176 nm/min. Imprinting with positive photoresist AZ1518 was compared to negative SU-8 2002 by optical microscopy and AFM. Conformal results were obtained only with the last resist by hot embossing at 120 °C and 1 kgf/cm² for 2 min, followed by a 10 min post-baking at 100 °C. The patterning procedure was applied to define gold source and drain electrodes on oxide-covered substrates to produce bottom-gate bottom-contact transistors. Poly(3-hexylthiophene) (P3HT) devices were processed on high-κ titanium oxynitride (TiO _x N _y ) deposited by radiofrequency magnetron sputtering over indium tin oxide-covered glass to achieve low-voltage operation. Hole mobility on micrometric imprinted channels may approach amorphous silicon (～0.01 cm²/V s) and, since these devices operated at less than 5 V, they are not only suitable for electronic applications but also as sensors in aqueous media.     

Artifact removal in magnetoencephalogram background activity with independent component analysis

The aim of this study was to assess whether independent component analysis (ICA) could be valuable to remove power line noise, cardiac, and ocular artifacts from magnetoencephalogram (MEG) background activity. The MEGs were recorded from 11 subjects with a 148-channel whole-head magnetometer. We used a statistical criterion to estimate the number of independent components. Then, a robust ICA algorithm decomposed the MEG epochs and several methods were applied to detect those artifacts. The whole process had been previously tested on synthetic data. We found that the line noise components could be easily detected by their frequency spectrum. In addition, the ocular artifacts could be identified by their frequency characteristics and scalp topography. Moreover, the cardiac artifact was better recognized by its skewness value than by its kurtosis one. Finally, the MEG signals were compared before and after artifact rejection to evaluate our method.