Abstract

Abstract
Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks.

Abstract
The main motivation of this work was to provide a valid contribution for the assessment of the cardiovascular condition by the analysis of several Arterial Pressure Waveform (APW) parameters collected by a new non-invasive device. Three sets of recordings for the carotid pressure waveform at left and right carotid arteries were performed, under standardized conditions, in 20 volunteers by three trained operators. The mean of the inter-operator differences were higher for the right artery, comparatively to the left artery. In this case, an Augmentation Index (AIx) value of -2.31 ± 7.29 % and a Systolic Wave Transit Time (SWTT) value of -12.94 ± 31.46 ms were observed, which are higher than the left measurements, 0.94 ± 7.52 % and -2.96 ± 22.67 ms, respectively. Intra-operator differences were calculated for each of the three sets of measurements and showed good reproducibility. The pulse-by-pulse variability analysis gives very good markers for the Left Ventricular Ejection Time (LVET), Dicrotic Wave Amplitude (DWA), Reflection Wave Amplitude (RWA), Coefficient of Variation (CV) < 10 %, and satisfactory values for the AIx (CV< 30 %). The SWTT and Reflected Wave Transit Time (RWTT) also presented satisfactory results (10 %

Abstract
Surface Plasmon Resonance (SPR) is the base for some of the most sensitive label free optical fiber biosensors. However, most solutions presented to date require the use of fragile fiber optic structure such as adiabatic tapers or side polished fibers. On the other hand, long-period fiber gratings (LPG) present themselves as an interesting solution to attain an evanescent wave refractive index sensor platform while preserving the optical fiber integrity. The combination of these two approaches constitute a powerful platform that can potentially reach the highest sensitivities as it was recently demonstrated by detailed theoretical study [1, 2]. In this work, a LPG-SPR platform is explored in different configurations (metal coating between two LPG - symmetric and asymmetric) operating in the telecom band (around 1550 nm). For this purpose LPGs with period of 396 mu m are combined with tailor made metallic thin films. In particular, the sensing regions were coated with 2 nm of chromium to improve the adhesion to the fiber and 16 nm of gold followed by a 100 nm thick layer of TiO2 dielectric material strategically chosen to attain plasmon resonance in the desired wavelength range. The obtained refractometric platforms were then validated as a biosensor. For this purpose the detection of thrombin using an aptamer based probe was used as a model system for protein detection. The surface of the sensing fibers were cleaned with isopropanol and dried with N-2 and then the aminated thrombin aptamer (5'-[NH2]-GGTTGGTGTGGTTGG-3') was immobilized by physisorption using Poly-L-Lysine (PLL) as cationic polymer. Preliminary results indicate the viability of the LPFG-SPR-APTAMER as a flexible platforms point of care diagnostic biosensors.

Abstract
An experimental setup has been developed for different gas species sensing based on the Wavelength Modulation Spectroscopy (WMS) principle. The target is the measurement of ammonia, carbon dioxide and methane concentrations. The WMS is a rather sensitive technique for detecting atomic/molecular species presenting the advantage that it can be used in the near-infrared region using optical telecommunications technology. In this technique, the laser wavelength and intensity are modulated applying a sine wave signal through the injection current, which allows the shift of the detection bandwidth to higher frequencies where laser intensity noise is reduced. The wavelength modulated laser light is tuned to the absorption line of the target gas and the absorption information can be retrieved by means of synchronous detection using a lock-in amplifier, where the amplitude of the second harmonic of the laser modulation frequency is proportional to the gas concentration. The amplitude of the second harmonic is normalised by the average laser intensity and detector gain through a LabVIEW (R) application, where the main advantage of normalising is that the effects of laser output power fluctuations and any variations in laser transmission, or optical-electrical detector gain are eliminated. Two types of sensing heads based on free space light propagation with different optical path length were used, permitting redundancy operation and technology validation.

Abstract
A common migration path for applications to high-performance multicore architectures relies on code annotations with concurrent semantics. Some annotations, however, are very target architecture specific and thus highly non-portable. In this paper we describe a source-to-source code transformation system that allows programmers to specify transformations using an aspect-oriented domain specific language - LARA. LARA allows programmers to specify strategies to search large code transformation design spaces while preserving the original source code. As the experimental results reveal, this approach leads to a substantial reduction in code maintenance costs, and promotes the portability of both programmers and performance. Copyright © 2014 ACM.