An energy efficient middleware for an ad-hoc AAL wireless sensor network

DIA (Dispositivo Inteligente de Alarma, in Spanish) is an AAL (Ambient Assisted Living) system that allows to infer a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensorisation with sensor nodes (portables and fixes) and a reasoning layer embedded in a PC that learns of the users behaviour patterns and advices when actual one differs significantly of the normal patterns. In AAL systems, energy is a limited resource therefore sensor devices need to be properly managed to conserve energy. In this paper, we introduce the design and implementation of innovative and specific mechanisms at the sensory layer middleware which is capable of, first to discriminate spurious motion detections assuming that these signals do not resemble the patterns of real motion detections and, second to reduce the dynamics of messages by a sensor signal processing in order to compress the whole information in one single event. The middleware achieves power saving by modifying the raw information from sensors and adapting it to the predefined semantic of the reasoning layer. It manages the important task of data processing from sensors (raw information), and transfers the pre-processed information into the top layer of reasoning in a more energy efficient way. We also address the trade-off between reducing power consumption and reducing delay for incoming data. We present results from experiments using our implementation of these mechanisms at the middleware that comprises from node firmware to the PC driver. The number of messages of the proposed method with respect to the raw data is reduced by approximately 98.5%. The resources used in the PIR signal processing is reduced by approximately 85%. The resulting delay introduced is small (10–19 s) but system dynamics is slow enough to avoid contextualisation errors or reduction of system performance. We consider these results as very satisfactory.     

Assessment of the Use of NaClO as an Alternative to H2O2 in the Oxidant-Titanium Ore-Simulated Solar Light System for Thiabendazole Degradation

Topics in Catalysis - The use of the magnetic fraction (MF) of a low-grade titanium ore (TO) and two oxidants (H2O2 and NaClO), testing each one separately, were compared in photo-Fenton like...     

Predicting cetane number,kinematic viscosity,density and higher heating value of biodiesel from its fatty acid methyl ester composition

Biodiesel is a renewable bio-fuel derived from natural fats or vegetable oils, and it is considered as a promising alternative to substitute diesel fuels. Cetane number, viscosity, density, and higher heating value are important properties to affect the utilization of biodiesel fuels, because they are involved in the definition of fuel quality and are required as input data for predictive engine combustion models. This work presents the characterization of two biodiesel samples made from beef tallow and soybean oil through their fatty acid methyl esters (FAMEs) profile. Empirical equations were developed to estimate four physical properties of methyl esters; and an average absolute deviation (AAD) of 5.95%, 2.57%, 0.11% and 0.21% for the cetane number, kinematic viscosity, density, and higher heating value were founded. Cetane number, viscosity, and higher heating value increases because of the increase of molecular weight and these physical properties decrease as the number of double bonds increases. Unlike that of above properties, density decreases as molecular weight increases and density increases as the degree of unsaturation increases. Two general mixing rules and five biodiesel samples were used to study the influence of FAMEs over the physical properties of biodiesel. The prediction of the cetane number, kinematic viscosity, density and higher heating value of biodiesel is very close to the experimental values.     

Study of the cohesion of carbon fiber yarns: in-plane shear behavior

Cohesion of the fibers network is a key element in numerous manufacturing processes of textile structures and composite parts, because it significantly affects the implementability and the obtained result. However, cohesion remains at the moment an intuitive concept. This paper aims to deal with this concept, first proposing a first interpretation of yarn cohesion. Thanks to this definition, the in-plane shear test is proposed to characterize and measure cohesion. Among many difficulties, it appears to be an interesting way to analyze the cohesion of yarns extracted from 7 different batches and to establish the link between cohesion and implementation in manufacturing processes of Herakles which supports this study. In addition, the phenomenon responsible for the yarn cohesion are tackled and the influence of the yarn constitution is analyzed.     

The ALTER-NATIVA knowledge management approach

Nowadays, it is commonly known that information systems need an agile capability of handling knowledge. To accomplish this, systems have to have a formal knowledge representation ability supported by specific and advanced reasoning features. This research work proposes a knowledge management approach with the purpose to gather, model and consume community knowledge for specific recommendation commitments. Such approach is accomplished by a semantic lexicon alignment between the various community knowledge assets, to facilitate collaborations establishment between people and systems in an interoperable fashion. Thus, a knowledge base supported by a thesaurus able to represent all the metadata needed to represent and characterize the various community stakeholders’ resources is proposed. The thesaurus represents the lexicon in the domain, which in the ALTER-NATIVA systems is mostly used to support the various e-Learning elements (e.g. courses) and users categorization, sustained by synchronization features to facilitate a constant update of its information. A set of services designed to recommend specific resources in relation to a determined profile of user is provided. Additionally, a discussion about how the ALTER-NATIVA knowledge management approach can be applied to industrial environments is presented.     

Determination of deuterium site occupancy in ZrCoD3 and its role in improved durability of Zr–Co–Ni deuterides against disproportionation

In the present study, we have for the first time reported the occupancy of deuterium in a new interstitial site of ZrCoD₃ which explain the hydrogen induced disproportionation behavior of ZrCo alloy. We have also reported the effect of Ni substitution on interstitial site occupancy of deuterium in ZrCo_1−xNi_xD₃, which in turn explains the improved durability of these Ni substituted deuterides against disproportionation. The crystal structure of the ZrCo_1−xNi_x (x = 0.0, 0.1, 0.2, 0.3) deuterides was investigated by X-ray powder diffraction and neutron diffraction methods. The XRD data reveals a single phase formation for all deuterides with varying Ni content (x). The neutron diffraction study shows that deuterium occupies a new site 8e in addition to 4c₂ and 8f₁. Additionally, the Zr–D distance in 8e site is shorter than that in ZrD₂. Therefore, increase in 8e site occupancy will in turn decreases the durability against disproportionation and vice-versa. Furthermore, the neutron diffraction reveals that occupancy of new 8e site decreases and its Zr–D distance increases with increase in Ni content, which explicate the higher durability against disproportionation for Ni rich compound.     

A Spatial‐Context‐Based Approach for Automated Spatial Change Analysis of Piece‐Wise Linear Building Elements

Changes of designs and construction plans often cause propagative design modifications, tedious construction coordination, cascading effects of errors, reworks, and delays in project management. Among various building elements, those having piece‐wise linear geometries (i.e., connected straight line segments), such as connected straight sections of ducts in mechanical, electrical, and plumbing systems, frequently undergo spatial changes in response to the changes of their surroundings. On the other hand, the piece‐wise linear geometries pose challenges to analyzing and controlling changes in construction and facility management. State‐of‐the‐art 3D change detection algorithms often face ambiguities about which points belong to which objects when piece‐wise linear object are spacked in small spaces. This article examines a spatial‐context‐based framework that uses spatial relationships between piece‐wise linear building elements (ducts in this article) to enable fast and reliable association of 3D data with ducts in as‐designed models for supporting reliable change analysis. Three case studies showed that this framework outperformed a conventional change detection method, and could handle large dislocations of piece‐wise linear elements and occlusions.