Interleaved multi-cell isolated three-phase PWM rectifier system for aircraft applications

Recently there has been an important increase in electric equipment, as well as, electric power demand in aircrafts applications. This prompts to the necessity of efficient, reliable, and low-weight converters, especially rectifiers from 115VAC to 270VDC because these voltages are used in power distribution. In order to obtain a high efficiency, in aircraft application where the derating in semiconductors is high, normally several semiconductors are used in parallel to decrease the conduction losses. However, this is in conflict with high reliability. To match both goals of high efficiency and reliability, this work proposes an interleaved multi-cell rectifier system, employing several converter cells in parallel instead of parallel-connected semiconductors. In this work a 10kW multi-cell isolated rectifier system has been designed where each cell is composed of a buck type rectifier and a full bridge DC-DC converter. The implemented system exhibits 91% of efficiency, high power density (10kW/10kg), low THD (2.5%), and n−1 fault tolerance which complies, with military aircraft standards.

Generation of an UWB monocycle employing cross-phase modulation in a SOA-MZ interferometer

In the present article, an innovative approach for generation of an UWB monocycle is proposed and experimentally demonstrated. The proposed design features the combination of an interferometric device (SOA-Mach Zehnder interferometer) with an optical processor unit. The fusion of such components permits to generate, combine and customize UWB pulses. An optical pulse is used as pump signal and two optical carriers represent and the optical input of the system. The selection of a specific wavelength and therefore of a particular port provides the possibility of modifying the systems output pulse polarity. The capacity of transmitting several data sequence has been also evidenced.

A comparative analysis of road financing approaches in Europe and the United States

• The viability of the present system of road funding has in recent years been widely questioned, for it has proved insufficient to support spending programs at their current levels. • Some transfers from the general fund have been needed since 2008 to keep the HTF solvent. • Fuel taxes, the primary source for funding roads in the US, have not kept pace with inflation for years. • A wide variety of measures to increase revenue has been presented: raising fuel taxes, extending toll highways, implementing a VMT fee, etc.

A novel FPGA-based evolvable hardware system based on multiple processing arrays

In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications.

Classical segmentation methods on novel MR imaging: a study of brain tissue segmentation of MP2RAGE vs MPRAGE

MP2RAGE has proven to be a bias-free MR acquisition with excellent contrast between grey and white matter. We investigated the ability of three state-of-the-art algorithms to automatically extract white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) from MPRAGE and MP2RAGE images: unified Segmentation (S) in SPM82 , its extension New Segment (NS), and an in-house Expectation-Maximization Markov Random Field tissue classification3 (EM-MRF) with Graph Cut (GC) optimization4 . Our goal is to quantify the differences between MPRAGE and MP2RAGE-based brain tissue probability maps.

Mechanical Degradation of Tungsten Alloys at Extreme Temperatures in Vacuum and Oxidation Atmospheres

Mechanical degradation of tungsten alloys at extreme temperatures in vacuum and oxidation atmospheres.

FK concentrator outdoor measurements

The FK is a two-stage optical concentrator for CPV, composed by a Fresnel lens working as POE and a refractive element working as SOE. Both elements perform Köhler integration, for uniform irradiance purposes. The FK has demonstrated that compares very well with other Fresnel-based concentrator optics. Recent on-sun measurements carried out on an FK mono-module prototype have already shown outstanding results, achieving electrical efficiencies over 34%. Further optimization of optical design together with application of AR coating on SOE will predictably lead to efficiencies over 35%.

A combined algorithm for analyzing structural controllability and observability of complex networks

In this paper a combined algorithm for analyzing structural controllability and observability of complex networks is presented. The algorithm addresses the two fundamental properties to guarantee structural controllability of a system: the absence of dilations and the accessibility of all nodes. The first problem is reformulated as a Maximum Matching search and it is addressed via the Hopcroft- Karp algorithm; the second problem is solved via a new wiring algorithm. Both algorithms can be combined to efficiently determine the number of required controllers and observers as well as the new required connections in order to guarantee controllability and observability in real complex networks. An application to a Twitter social network with over 100,000 nodes illustrates the proposed algorithms.

Dam seepage analysis based on artificial neural networks: the hysteresis phenomenon

Seepage flow measurement is an important behavior indicator when providing information about dam performance. The main objective of this study is to analyze seepage by means of an artificial neural network model. The model is trained and validated with data measured at a case study. The dam behavior towards different water level changes is reproduced by the model and a hysteresis phenomenon detected and studied. Artificial neural network models are shown to be a powerful tool for predicting and understanding seepage phenomenon.

Adaptive spatio-temporal filter for low-cost camera depth maps

In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise.

High-quality real-time temporal segmentation tool for video editing software

The increasing use of video editing software has resulted in a necessity for faster and more efficient editing tools. Here, we propose a lightweight high-quality video indexing tool that is suitable for video editing software.

Low-cost efficient interactive whiteboard

In this paper we present a low-cost efficient Interactive Whiteboard that, by fusing depth and video information provided by a low-cost depth camera, is able to detect and track user movements.

Region-dependent vehicle classification using PCA features

Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) is proposed that addresses the main limitations of existing methods. Namely, in contrast to classical approaches which train a single classifier regardless of the relative position of the candidate (thus ignoring valuable pose information), a region-dependent analysis is performed by considering four different areas. In addition, a study on the evolution of the classification performance according to the dimensionality of the principal subspace is carried out using PCA features within a SVM-based classification scheme. Indeed, the experiments performed on a publicly available database prove that PCA dimensionality requirements are region-dependent. Hence, in this work, the optimal configuration is adapted to each of them, rendering very good vehicle verification results.

Accurate depth-color scene modeling for 3D contents generation with low cost depth cameras

In this paper, we present a depth-color scene modeling strategy for indoors 3D contents generation. It combines depth and visual information provided by a low-cost active depth camera to improve the accuracy of the acquired depth maps considering the different dynamic nature of the scene elements. Accurate depth and color models of the scene background are iteratively built, and used to detect moving elements in the scene. The acquired depth data is continuously processed with an innovative joint-bilateral filter that efficiently combines depth and visual information thanks to the analysis of an edge-uncertainty map and the detected foreground regions. The main advantages of the proposed approach are: removing depth maps spatial noise and temporal random fluctuations; refining depth data at object boundaries, generating iteratively a robust depth and color background model and an accurate moving object silhouette.

Adaptive protection scheme for MVC-encoded stereoscopic video streaming in IP-based networks

We present an adaptive unequal error protection (UEP) strategy built on the 1-D interleaved parity Application Layer Forward Error Correction (AL-FEC) code for protecting the transmission of stereoscopic 3D video content encoded with Multiview Video Coding (MVC) through IP-based networks. Our scheme targets the minimization of quality degradation produced by packet losses during video transmission in time-sensitive application scenarios. To that end, based on a novel packet-level distortion model, it selects in real time the most suitable packets within each Group of Pictures (GOP) to be protected and the most convenient FEC technique parameters, i.e., the size of the FEC generator matrix. In order to make these decisions, it considers the relevance of the packet, the behavior of the channel, and the available bitrate for protection purposes. Simulation results validate both the distortion model introduced to estimate the importance of packets and the optimization of the FEC technique parameter values.