Abstract
In this work a magnetic field sensor based on an FBG coated with a thin film of Terfenol-D is presented. The sensor was tested with two optical interrogation systems: one, a scanning laser system with a 1 pm resolution, and the other a differential white light interferometer (WLI). The results obtained in the magnetic field range of 20 mT to 100 mT, show the possibility of increasing the magnetic field measurement resolution, with temperature fluctuations invariance, by a factor of 4.5 when using the WLI system.

Abstract
In this work, an all-fiber loop mirror using a clover microstructured fiber for the simultaneous measurement of temperature and strain is presented. The sensing head is formed by a short piece of clover microstructured fiber with 35 mm length. The geometry of the fiber allowed observing different interferences created by the microstructured fiber core section. Different sensitivities to temperature and strain were obtained and, using a matrix method, it is possible to discriminate both physical parameters. Resolutions of ±2°C and ±11 µe, for temperature and strain, respectively, were attained. © 2012 SPIE.

Abstract
Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumption. Having a high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

Abstract
Benzene is a carcinogenic and genotoxic pollutant which mainly affects the people health through the inhalation. Nevertheless, this pollutant is not frequently measured by air-quality networks. To solve this problem, some models have been published to estimate benzene concentrations in the atmosphere. However, the lack of measures makes difficult the application of complex models in order to get a detailed spatio-temporal analysis, namely in urban areas. In this work was developed a simple semi-empirical model to predict benzene concentrations based on the ratio of benzene and carbon monoxide concentrations in order to predict the concentrations of this pollutant in large areas and periods with lack of benzene measurements but with higher impact in the human health. The model was applied to an urban area, the Metropolitan Area of Oporto, for a period of 12 years (1995-2006). Monthly correlations between benzene and carbon monoxide concentrations at Custias air-quality station are significant (p = 0.01) and higher in winter (r (s) > 0.7) than in summer (0.3 > r (s) > 0.7). Estimate of the monthly ratio of the concentration of these two pollutants range between 199 and 305. The methodology validation shows good results (r (s) = 0.81) which allow, assuming the availability of carbon monoxide data, the use of this tool for areas with low benzene recorded data. The application of this methodology in the study area shows an annual average trend decrease of benzene concentrations during the study period, which may be linked to a general trend decrease of benzene emissions in European urban areas, including the study domain.

Abstract
Personalised video can be achieved by inserting objects into a video play-out according to the viewer's profile. Content which has been authored and produced for general broadcast can take on additional commercial service features when personalised either for individual viewers or for groups of viewers participating in entertainment, training, gaming or informational activities. Although several scenarios and use-cases can be envisaged, we are focussed on the application of personalised product placement. Targeted advertising and product placement are currently garnering intense interest in the commercial networked media industries. Personalisation of product placement is a relevant and timely service for next generation online marketing and advertising and for many other revenue generating interactive services. This paper discusses the acquisition and insertion of media objects into a TV video play-out stream where the objects are determined by the profile of the viewer. The technology is based on MPEG-4 standards using object based video and MPEG-7 for metadata. No proprietary technology or protocol is proposed. To trade the objects into the video play-out, a Software-as-a-Service brokerage platform based on intelligent agent technology is adopted. Agencies, libraries and service providers are represented in a commercial negotiation to facilitate the contractual selection and usage of objects to be inserted into the video play-out. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Abstract
Existing bidirectional languages are either state-based or operation-based, depending on whether they represent updates as mere states or as sequences of edit operations. In-between both worlds are delta-based frameworks, where updates are represented using alignment relationships between states. In this paper, we formalize delta lenses over inductive types using dependent type theory and develop a point-free delta lens language with an explicit separation of shape and data. In contrast with the already known issue of data alignment, we identify the new problem of shape alignment and solve it by lifting standard recursion patterns such as folds and unfolds to delta lenses that use alignment to infer meaningful shape updates. © Bidirectional Transformations 2012.