Edge degree-of-sharpness and free-stream turbulence scale effects on the aerodynamics of a bridge deck

This paper discusses the sensitivity of the aerodynamic behavior of a trapezoidal-shaped bridge deck cross-section to its lower corner degree-of-sharpness and to the incoming flow turbulence integral length scale in conjunction with low turbulence intensity. Since these features are hard to set and measure in experimental facilities, the aerodynamic behavior of the body has been investigated through the computational simulation of the flow around it. The results are given in term of force coefficients, Strouhal number, pressure distribution along its surface, and the mean and instantaneous flow patterns. Dramatic changes in the force coefficients and Strouhal number occur following small changes in the parameter values. These changes have been found to be due to significant modifications in the topological structure of the flow. Special emphasis has been given to the analysis of the separation and reattachment points, the recirculation bubble length, the vortex shedding mechanisms and the wake structures. On the basis of the results, four aerodynamic regimes have been pointed out in analogy with the well-known individual Re number regimes. Some of these regimes have also been recognized on the deck section with the considered sharpest and smoothest lower edge treatments, i.e. for the highest and lowest degrees-of-sharpness.     

Planar mirrors for image-based robot localization and 3-D reconstruction

Planar catadioptric vision sensors consist of a pinhole camera observing a scene being reflected on two (or more) planar mirrors. These systems have recently received an increasing attention because, unlike stereo cameras, can capture two views of the same scene without the need of hardware multi-camera synchronization and calibration. In this paper we explore the original scenario in which a robot manipulator, equipped with a pinhole camera on its end-effector, observes an unknown 3-D scene both directly and reflected through multiple mirrors. We present new multiple-view properties for this scenario and, based on these theoretical results, we present new image-based camera localization and new 3-D scene reconstruction algorithms. Extensive simulation and real-data experiments illustrate the theory and show the effectiveness of the proposed designs.     

Robust and objective decomposition and mapping of bifurcating vessels

Computational modeling of human arteries has been broadly employed to investigate the relationships between geometry, hemodynamics and vascular disease. Recent developments in modeling techniques have made it possible to perform such analyses on realistic geometries acquired noninvasively and, thus, have opened up the possibility to extend the investigation to populations of subjects. However, for this to be feasible, novel methods for the comparison of the data obtained from large numbers of realistic models in the presence of anatomic variability must be developed. In this paper, we present an automatic technique for the objective comparison of distributions of geometric and hemodynamic quantities over the surface of bifurcating vessels. The method is based on centerlines and consists of robustly decomposing the surface into its constituent branches and mapping each branch onto a template parametric plane. The application of the technique to realistic data demonstrates how similar results are obtained over similar geometries, allowing for proper model-to-model comparison. Thanks to the computational and differential geometry criteria adopted, the method does not depend on user-defined parameters or user interaction, it is flexible with respect to the bifurcation geometry and it is readily extendible to more complex configurations of interconnecting vessels.     

Digital Median Filters

Several DSP algorithms need to remove high-frequency or impulsive noise while preserving edges, e.g., in speech and image processing applications: median filtering has been proved to be more effective for achieving this goal than other filtering techniques. Efficient architectural implementation for real-time applications involves a careful VLSI design, which takes into account modularity, regularity, adaptability, scalability, throughput, circuit complexity and fault tolerance. Four new architectural approaches are presented and evaluated in this paper to deal with different application and implementation constraints. They are: the serial-input polarizing median filter, the floating median filter, the pipelined polarizing median filter and the pipelined sorting median filter. The 1st and the 2nd architectures are based on majority voting, while the 3rd and the 4th ones are based on sorting techniques. All of them are designed so as to exhibit high scalability and to be easily pipelined for higher working frequencies.     

A 1.0-mW, 71-dB SNDR,fourth-order ΣΔ interface circuit for MEMS microphones

In this paper an integrated interface circuit for condenser MEMS microphones is presented. It consists of an input buffer followed by a multi-bit (12-levels), analog, second-order ΣΔ modulator and a fully-digital, single-bit, fourth-order ΣΔ modulator, thus providing a single-bit output signal with fourth order noise shaping, compatible with standard audio chipsets. The circuit, supplied with 3.3 V, exhibits a current consumption of 215 μA for the analog part and 95 μA for the digital part. The measured signal-to-noise and distortion ratio (SNDR) is 71 dB, with an input signal amplitude as large as −1.8 dB with respect to full-scale, obtained thanks to the use of a feed-forward architecture in the analog ΣΔ modulator, which relaxes the voltage swing requirements of the operational amplifiers. The test chip, fabricated in a 0.35-μm CMOS process, occupies an area of 3 mm², including pads.     

A novel batch-based group key management protocol applied to the Internet of Things

Many applications for ad hoc networks are based on a point-to-multipoint (multicast) communication paradigm, where a single source sends common data to many receivers, or, inversely, on a multipoint-to-point communication paradigm, where multiple sources send data to a single receiver. In such scenarios, communication can be secured by adopting a common secret key, denoted as “group key”, shared by multiple communication endpoints. In this work, we propose a novel centralized approach to efficiently distribute and manage a group key in generic ad hoc networks and Internet of Things, while reducing the computational overhead and network traffic due to group membership changes caused by users’ joins and leaves. In particular, the proposed protocol takes advantage of two possible leave strategies: (i) at a pre-determined time selected when the user joins the group or (ii) at an unpredictable time, as in the case of membership revocation. The proposed protocol is applied to two following relevant scenarios: (i) secure data aggregation in Internet of Things (IoT) and (ii) Vehicle-to-Vehicle (V2V) communications in Vehicular Ad hoc Networks (VANETs).     

Estimation of M-wave scale factor during sustained contractions at high stimulation rate

In this paper, we propose a time-domain index to assess M-wave widening during high-frequency stimulation, as an objective parameter for quantifying muscle fatigue. At high stimulation frequencies, signal truncation, due to the delivery of the electrical stimulus before the M-wave generated by the previous stimulus extinguishes, biases the spectral frequency variables usually computed to estimate M-wave widening. Thus, we propose an estimator of the scale factor between two truncated M-waves. The estimator is derived from the Scale Transforms of the two signals, with an efficient implementation that avoids limits of resolution. The method was tested on both simulated and experimental signals. The simulations showed that the proposed technique is significantly less affected by signal truncation than previous approaches. The experimental recordings were collected from 11 subjects at stimulation frequencies of 20, 40, and 60 Hz. The scale factor estimation assessed M-wave widening in the three conditions, differentiating between the different rates of change of signal widening. The method proved to be significantly superior to M-wave spectral analysis. The technique can be applied to investigate myoelectric manifestations of muscle fatigue at stimulation rates that could not be analyzed in the past and, thus, opens new perspectives in the evaluation of electrical stimulation for training and rehabilitation protocols.