44 resultados para VANet, gps, algoritmi distribuiti, V2V, 802.11p, I2V


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To test the hypothesis that more disadvantaged patients are perceived by general practitioners (GPs) as being less attractive than their more affluent peers.

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The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted from these large movement data sets. Geovisual analytics offers powerful techniques to achieve this. This article describes a new geovisual analytics tool specifically designed for movement data. The tool features the classic space-time cube augmented with a novel clustering approach to identify common behaviour. These techniques were used to analyse pedestrian movement in a city environment which revealed the effectiveness of the tool for identifying spatiotemporal patterns. © 2014 Taylor & Francis.

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The upcoming IEEE 802.11ac standard boosts the throughput of previous IEEE 802.11n by adding wider 80 MHz and 160 MHz channels with up to 8 antennas (versus 40 MHz channel and 4 antennas in 802.11n). This necessitates new 1-8 stream 256/512-point Fast Fourier Transform (FFT) / inverse FFT (IFFT) processing with 80/160 MSample/s throughput. Although there are abundant related work, they all fail to meet the requirements of IEEE 802.11ac FFT/IFFT on point size, throughput and multiple data streams at the same time. This paper proposes the first software defined FFT/IFFT architecture as a solution. By making use of a customised soft stream processor on FPGA, we show how a software defined FFT architecture can meet all the requirements of IEEE 802.11ac with low cost and high resource efficiency. When compared with dedicated Xilinx FFT core, our implementation exhibits only one third of the resources also up to three times of resource efficiency.

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Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.