A proposal for a set of attributes relevant for Web portal data quality

Data Quality is a critical issue in today’s interconnected society. Advances in technology are making the use of the Internet an ever-growing phenomenon and we are witnessing the creation of a great variety of applications such as Web Portals. These applications are important data sources and/or means of accessing information which many people use to make decisions or to carry out tasks. Quality is a very important factor in any software product and also in data. As quality is a wide concept, quality models are usually used to assess the quality of a software product. From the software point of view there is a widely accepted standard proposed by ISO/IEC (the ISO/IEC 9126) which proposes a quality model for software products. However, until now a similar proposal for data quality has not existed. Although we have found some proposals of data quality models, some of them working as “de facto” standards, none of them focus specifically on web portal data quality and the user’s perspective. In this paper, we propose a set of 33 attributes which are relevant for portal data quality. These have been obtained from a revision of literature and a validation process carried out by means of a survey. Although these attributes do not conform to a usable model, we think that it might be considered as a good starting point for constructing one.

Context-based object-class recognition and retrieval by generalized correlograms

We present a novel approach for retrieval of object categories based on a novel type of image representation: the Generalized Correlogram (GC). In our image representation, the object is described as a constellation of GCs where each one encodes information about some local part and the spatial relations from this part to others (i.e., the part's context). We show how such a representation can be used with fast procedures that learn the object category with weak supervision and efficiently match the model of the object against large collections of images. In the learning stage, we show that by integrating our representation with Boosting the system is able to obtain a compact model that is represented by very few features, where each feature conveys key properties about the object's parts and their spatial arrangement. In the matching step, we propose direct procedures that exploit our representation for efficiently considering spatial coherence between the matching of local parts. Combined with an appropriate data organization such as Inverted Files, we show that thousands of images can be evaluated efficiently. The framework has been applied to different standard databases and we show that our results are favorably compared against state-of-the-art methods in both computational cost and accuracy.     

Learning from syntax generalizations for automatic semantic annotation

Nowadays, there is a huge amount of textual data coming from on-line social communities like Twitter or encyclopedic data provided by Wikipedia and similar platforms. This Big Data Era created novel challenges to be faced in order to make sense of large data storages as well as to efficiently find specific information within them. In a more domain-specific scenario like the management of legal documents, the extraction of semantic knowledge can support domain engineers to find relevant information in more rapid ways, and to provide assistance within the process of constructing application-based legal ontologies. In this work, we face the problem of automatically extracting structured knowledge to improve semantic search and ontology creation on textual databases. To achieve this goal, we propose an approach that first relies on well-known Natural Language Processing techniques like Part-Of-Speech tagging and Syntactic Parsing. Then, we transform these information into generalized features that aim at capturing the surrounding linguistic variability of the target semantic units. These new featured data are finally fed into a Support Vector Machine classifier that computes a model to automate the semantic annotation. We first tested our technique on the problem of automatically extracting semantic entities and involved objects within legal texts. Then, we focus on the identification of hypernym relations and definitional sentences, demonstrating the validity of the approach on different tasks and domains.     

Two walking gaits for a planar bipedal robot equipped with a four-bar mechanism for the knee joint

The design of a knee joint is a key issue in robotics and biomechanics to improve the compatibility between prosthesis and human movements, and to improve the bipedal robot performances. We propose a novel design for the knee joint of a planar bipedal robot, based on a four-bar linkage. The dynamic model of the planar bipedal robot is calculated. Two kinds of cyclic walking gaits are considered. The first gait is composed of successive single support phases with stance flat-foot on the ground separated by impacts. The second gait is a succession of finite time double support phases, single support phases, and impacts. During the double support phase, both feet rotate. This phase is ended by an impact of the toe of the forward foot, while the rear foot is taking off. The single support phase is ended by an impact of the swing foot heel, the other foot keeping contact with the ground through its toe. For both gaits, the reference trajectories of the rotational joints are prescribed by cubic spline functions in time. A parametric optimization problem is presented for the determination of the parameters corresponding to the optimal cyclic walking gaits. The main contribution of this paper is the design of a dynamical stable walking gait with double support phases with feet rotation, impacts, and single support phases for this bipedal robot.     

Wool bleaching with reducing agents in the presence of sodium laurylsulphate. Part 2 — bleaching with non-stabilised hydrosulphite

Wool bleaching with non-stabilised hydrosulphite in the presence of sodium laurylsulphate (SLS) at a concentration of 5 g/l provides far better whites than when bleaching without this surfactant. In addition to better whiteness and lower yellowness index, wools bleached with SLS incorporated into the bath have a cysteine content some 20–30% lower.     

Influence of different sources of microstructural heterogeneity on the degradation of asphalt mixtures

The response and degradation of the hot mix asphalt (HMA) materials used in pavement structures are affected by their inherent heterogeneity. The objective of this work is to study the impact of two different sources of HMA heterogeneity in the uncertainty of the mechanical moisture degradation of HMA. The first source of heterogeneity is the spatial variability of the properties of the bulk fine aggregate matrix (FAM) of the mixture, and the second is the location and shape of the coarse aggregate particles. The heterogeneity of the bulk FAM phase was modelled using a random field technique, while that of the coarse aggregates was accounted for by randomly generating realistic probable sets of aggregate particles. Thus, ‘computational replicates’ of HMA microstructures were generated and subjected to moisture diffusion and mechanical loading using a finite element approach. In the mechanical simulations, a non-linear viscoelastic moisture damage constitutive relationship based on continuum damage mechanics theory was selected to characterise the response of the bulk FAM phase. The results show that conducting computational simulations with realistic HMA microstructures that properly capture the heterogeneity of the material is useful to quantify the mean values and dispersion (i.e. uncertainty) associated with the response and degradation of the mixture. This information, which cannot be easily obtained in the field or in the laboratory due to the difficulty of acquiring a sufficient amount of data, is useful to conduct structural reliability analysis and to predict the life cycle behaviour of the material.     

Epitaxial La0.7Sr0.3MnO3 thin films on silicon with excellent magnetic and electric properties by combining physical and chemical methods

Half-metallic ferromagnetic La_0.7Sr_0.3MnO₃ (LSMO) represents an appealing candidate to be integrated on silicon substrates for technological devices such as sensors, data storage media, IR detectors, and so on. Here, we report high-quality epitaxial LSMO thin films obtained by an original combination of chemical solution deposition (CSD) and molecular beam epitaxy (MBE). A detailed study of the thermal, chemical, and physical compatibility between SrTiO₃ (STO)/Si buffer layers and LSMO films, grown by MBE and CSD, respectively, enables a perfect integration of both materials. Importantly, we show a precise control of the coercive field of LSMO films by tuning the mosaicity of the STO/Si buffer layer. These results demonstrate the enormous potential of combining physical and chemical processes for the development of low-cost functional oxide-based devices compatible with the complementary metal oxide semiconductor technology.     

Electric and Mechanical Switching of Ferroelectric and Resistive States in Semiconducting BaTiO3–δ Films on Silicon

Materials that can couple electrical and mechanical properties constitute a key element of smart actuators, energy harvesters, or many sensing devices. Within this class, functional oxides display specific mesoscale responses which often result in great sensitivity to small external stimuli. Here, a novel combination of molecular beam epitaxy and a water‐based chemical‐solution method is used for the design of mechanically controlled multilevel device integrated on silicon. In particular, the possibility of adding extra functionalities to a ferroelectric oxide heterostructure by n‐doping and nanostructuring a BaTiO₃ thin film on Si(001) is explored. It is found that the ferroelectric polarization can be reversed, and resistive switching can be measured, upon a mechanical load in epitaxial BaTiO_3?δ /La_0.7Sr_0.3MnO₃/SrTiO₃/Si columnar nanostructures. A flexoelectric effect is found, stemming from substantial strain gradients that can be created with moderate loads. Simultaneously, mechanical effects on the local conductivity can be used to modulate a nonvolatile resistive state of the BaTiO_3?δ heterostructure. As a result, three different configurations of the system become accessible on top of the usual voltage reversal of polarization and resistive states.