Floating car data augmentation based on infrastructure sensors and neural networks

The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.

Flow and fracture behaviour of FV535 steel at different triaxialities, strain rates and temperatures

The new generation jet engines operate at highly demanding working conditions. Such conditions need very precise design which implies an exhaustive study of the engine materials and behaviour in their extreme working conditions. With this purpose, this work intends to describe a numerically-based calibration of the widely-used Johnson–Cook fracture model, as well as its validation through high temperature ballistic impact tests. To do so, a widely-used turbine casing material is studied. This material is the Firth Vickers 535 martensitic stainless steel. Quasi-static tensile tests at various temperatures in a universal testing machine, as well as dynamic tests in a Split Hopkinson Pressure Bar, are carried out at different triaxialities. Using ABAQUS/Standard and LS-DYNA numerical codes, experimental data are matched. This method allows the researcher to obtain critical data of equivalent plastic strain and triaxility, which allows for more precise calibration of the Johnson–Cook fracture model. Such enhancement allows study of the fracture behaviour of the material across its usage temperature range.

Towards an unsupervised speaking style voice building framework: multi-style speaker diarization

Current text-to-speech systems are developed using studio-recorded speech in a neutral style or based on acted emotions. However, the proliferation of media sharing sites would allow developing a new generation of speech-based systems which could cope with spontaneous and styled speech. This paper proposes an architecture to deal with realistic recordings and carries out some experiments on unsupervised speaker diarization. In order to maximize the speaker purity of the clusters while keeping a high speaker coverage, the paper evaluates the F-measure of a diarization module, achieving high scores (>85%) especially when the clusters are longer than 30 seconds, even for the more spontaneous and expressive styles (such as talk shows or sports).

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

Steady-state thermal analysis of an innovative receiver for linear Fresnel reflectors

The study of the performance of an innovative receiver for linear Fresnel reflectors is carried out in this paper, and the results are analyzed with a physics perspective of the process. The receiver consists of a bundle of tubes parallel to the mirror arrays, resulting on a smaller cross section for the same receiver width as the number of tubes increases, due to the diminution of their diameter. This implies higher heat carrier fluid speeds, and thus, a more effective heat transfer process, although it conveys higher pumping power as well. Mass flow is optimized for different tubes diameters, different impinging radiation intensities and different fluid inlet temperatures. It is found that the best receiver design, namely the tubes diameter that maximizes the exergetic efficiency for given working conditions, is similar for the cases studied. There is a range of tubes diameters that imply similar efficiencies, which can drive to capital cost reduction thanks to the flexibility of design. In addition, the length of the receiver is also optimized, and it is observed that the optimal length is similar for the working conditions considered. As a result of this study, it is found that this innovative receiver provides an optimum design for the whole day, even though impinging radiation intensity varies notably. Thermal features of this type of receiver could be the base of a new generation of concentrated solar power plants with a great potential for cost reduction, because of the simplicity of the system and the lower weigh of the components, plus the flexibility of using the receiver tubes for different streams of the heat carrier fluid.

Outline of Europe-Japan collaborative research on concentrator photovoltaics

The Europe-Japan Collaborative Research Project on Concentrator Photovoltaics (CPV) has been initiated under support by the EC (European Commission) and NEDO (New Energy and Industrial Technology Development Organization) since June 2011. This is project (NGCPV Project; a New Generation of Concentrator PhotoVoltaic cells, modules and systems) is aiming to accelerate the move to very high efficiency and lower cost CPV technologies and to enhance widespread deployment of CPV systems. 7 organizations such as UPM, FhG-ISE Imperial College, BSQ, CEA-INES, ENEA, and PSE in Europe and 9 organizations such as TTI, Univ. Tokyo, AIST, Sharp Co. Daido Steel Co., Kobe Univ., Miyazaki Univ., Asahi Kasei Co., and Takano Co. participate in this project. The targets of this project are 1) to develop world-record efficiency CPV cells of more than 45%, 2) to develop world-record efficiency CPV modules of 35%, 3) to establish standard measurements of CPV cells and modules, 4) to install 50kW CPV system in Spain, to carry out field test of CPV system and to manage power generation of CPV systems, and 5) to develop high-efficiency and low-cost new materials and structure cells such as III-V-N, III-V-on-Si tandem, quantum dots and wells. This paper presents outline of this project and most recent results such as world record efficiency (37.9% under 1-sun) cell and high-efficiency (43.5% under 240-306 suns) concentrator cell with inverted epitaxial grown InGaP/GaAs/InGaAs 3-junction solar cells.

Accurate Parabolic Navier-Stokes solutions of the supersonic flow around and elliptic cone

Flows of relevance to new generation aerospace vehicles exist, which are weakly dependent on the streamwise direction and strongly dependent on the other two spatial directions, such as the flow around the (flattened) nose of the vehicle and the associated elliptic cone model. Exploiting these characteristics, a parabolic integration of the Navier-Stokes equations is more appropriate than solution of the full equations, resulting in the so-called Parabolic Navier-Stokes (PNS). This approach not only is the best candidate, in terms of computational efficiency and accuracy, for the computation of steady base flows with the appointed properties, but also permits performing instability analysis and laminar-turbulent transition studies a-posteriori to the base flow computation. This is to be contrasted with the alternative approach of using order-of-magnitude more expensive spatial Direct Numerical Simulations (DNS) for the description of the transition process. The PNS equations used here have been formulated for an arbitrary coordinate transformation and the spatial discretization is performed using a novel stable high-order finite-difference-based numerical scheme, ensuring the recovery of highly accurate solutions using modest computing resources. For verification purposes, the boundary layer solution around a circular cone at zero angle of attack is compared in the incompressible limit with theoretical profiles. Also, the recovered shock wave angle at supersonic conditions is compared with theoretical predictions in the same circular-base cone geometry. Finally, the entire flow field, including shock position and compressible boundary layer around a 2:1 elliptic cone is recovered at Mach numbers 3 and 4

Efectos de la aplicación de fertilizantes de nueva generación en la dehesa toledana: producción, diversidad y composición florística de pastos herbáceos

Fertilization can be an interesting treatment to improve the different productions of the dehesa and to improve tree vigor. In order to evaluate the effect of different fertilizers of new generation on herbaceous pasture diversity and species composition, in this work we analyzed the effect of three treatments: control (natural pastures), fertization with 36 UF of P2O5 of a complex NPK and low content of N, and natural phosphates. Fertilization was applied in autumn of 2009, 2010 and 2011 and we analized herbaceous pastures composition and yield in springs of 2010, 2011 and 2012 (one control per year). The best results of production were obtained with the NPK application; also, pasture specific richness and diversity improved with the fertilization in years of average regime of precipitation.

Speed-independent gait identification for mobile devices

Due to the intensive use of mobile phones for diferent purposes, these devices usually contain condential information which must not be accessed by another person apart from the owner of the device. Furthermore, the new generation phones commonly incorporate an accelerometer which may be used to capture the acceleration signals produced as a result of owner s gait. Nowadays, gait identication in basis of acceleration signals is being considered as a new biometric technique which allows blocking the device when another person is carrying it. Although distance based approaches as Euclidean distance or dynamic time warping have been applied to solve this identication problem, they show di±culties when dealing with gaits at diferent speeds. For this reason, in this paper, a method to extract an average template from instances of the gait at diferent velocities is presented. This method has been tested with the gait signals of 34 subjects while walking at diferent motion speeds (slow, normal and fast) and it has shown to improve the performance of Euclidean distance and classical dynamic time warping.

Information reconciliation for Quantum Key Distribution

Secret-key agreement, a well-known problem in cryptography, allows two parties holding correlated sequences to agree on a secret key communicating over a public channel. It is usually divided into three different procedures: advantage distillation, information reconciliation and privacy amplification. The efficiency of each one of these procedures is needed if a positive key rate is to be attained from the legitimate parties? correlated sequences. Quantum key distribution (QKD) allows the two parties to obtain correlated sequences, provided that they have access to an authenticated channel. The new generation of QKD devices is able to work at higher speeds and in noisier or more absorbing environments. This exposes the weaknesses of current information reconciliation protocols, a key component to their performance. Here we present a new protocol based in low-density parity-check (LDPC) codes that presents the advantages of low interactivity, rate adaptability and high efficiency,characteristics that make it highly suitable for next generation QKD devices.

Routines in precision agriculture technology: an action research study

A crop management and precision agriculture software application facilitates the flow of information between disparate software/equipment and the network of individuals that work with them. A new generation of farmers are using precision technology to help them more efficiently manage their roplands. By measuring precisely the way their fields reflect and emit energy at visible and infrared wavelengths, precision farmers can monitor a wide range of variables that affect their crops,such as soil moisture, surface temperature, photosynthetic activity, and weed or pest infestations. Over thirty years have passed since Nelson and Winter put the concept of routines firmly at the center of the analysis of organizational and economic change. Taken as the central unit of analysis, routines would help understand energy and agriculture economy evolution.

Costes y opciones técnicas para la implantación de las próximas tecnologías de generación eléctrica sostenible

En este proyecto hemos realizado un análisis sobre la sostenibilidad de las tecnologías de generación más representativas desde un punto de vista sostenible. El objetivo de este proyecto es valorar cuantitativamente la sostenibilidad utilizando para ello los tres pilares de la sostenibilidad, para ello nos hemos apoyado en estudios sobre impactos medioambientales, seguridad en el suministro y costes de generación. Todo esto nos ha llevado a la conclusión de que aunque no existe una tecnología que satisfaga todas las necesidades, las nuevas tecnologías de generación, como las renovables, ganan en competitividad si añadimos un punto de vista sostenible. ABSTRACT In this paper, we have done an analysis about the sustainability of the power generation technologies most representative form a sustainable point of view. The objective of this paper is to evaluate quantitatively the sustainability using for this the three pillars of sustainability, for this we have relied on studies about environmental impacts, security supply and generation costs. All this led us to the conclusion that although there is no technology that satisfies all the necessities, the new generation technologies, such as the renewable, gains in competitiveness if we add a sustainable point of view.

Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.

Multiscale-fiber-reinforced thermoplastic composites incorporating carbon nanotubes: A review

This article reviews recent literature on hierarchical thermoplastic-based composites that simultaneously incorporate carbon nanotubes (CNTs) and conventional microscale fibers, and discusses the structure?property relationships of the resulting hybrids. The mixing of multiple and multiscale constituents enables the preparation of materials with new or improved properties due to synergistic effects. By exploiting the outstanding mechanical, thermal and electrical properties of CNTs, a new generation of multifunctional high-performance composites suitable for a wide variety of applications can be developed.

A comparison of open-source segmentation architectures for dealing with imperfect data from the media in speech synthesis

Traditional Text-To-Speech (TTS) systems have been developed using especially-designed non-expressive scripted recordings. In order to develop a new generation of expressive TTS systems in the Simple4All project, real recordings from the media should be used for training new voices with a whole new range of speaking styles. However, for processing this more spontaneous material, the new systems must be able to deal with imperfect data (multi-speaker recordings, background and foreground music and noise), filtering out low-quality audio segments and creating mono-speaker clusters. In this paper we compare several architectures for combining speaker diarization and music and noise detection which improve the precision and overall quality of the segmentation.