Schema-based Web wrapping

An effective solution to automate information extraction from Web pages is represented by wrappers. A wrapper associates a Web page with an XML document that represents part of the information in that page in a machine-readable format. Most existing wrapping approaches have traditionally focused on how to generate extraction rules, while they have ignored potential benefits deriving from the use of the schema of the information being extracted in the wrapper evaluation. In this paper, we investigate how the schema of extracted information can be effectively used in both the design and evaluation of a Web wrapper. We define a clean declarative semantics for schema-based wrappers by introducing the notion of (preferred) extraction model, which is essential to compute a valid XML document containing the information extracted from a Web page. We developed the SCRAP (SChema-based wRAPper for web data) system for the proposed schema-based wrapping approach, which also provides visual support tools to the wrapper designer. Moreover, we present a wrapper generalization framework to profitably speed up the design of schema-based wrappers. Experimental evaluation has shown that SCRAP wrappers are not only able to successfully extract the required data, but also they are robust to changes that may occur in the source Web pages.     

Adaptive soft k-nearest-neighbour classifiers

A novel classifier is introduced to overcome the limitations of the k-NN classification systems. It estimates the posterior class probabilities using a local Parzen window estimation with the k-nearest-neighbour prototypes (in the Euclidean sense) to the pattern to classify. A learning algorithm is also presented to reduce the number of data points to store. Experimental results in two hand-written classification problems demonstrate the potential of the proposed classification system.     

Entanglement of formation and concurrence for mixed states

We review some results on analytical computations of the measures for quantum entanglement: entanglement of formation and concurrence. We introduce some estimations of the lower bounds for the entanglement of formation in bipartite mixed states, and of lower bounds for the concurrence in bipartite and tripartite systems. The results on lower bounds for the concurrence are also generalized to arbitrary multipartite systems.     

Software Architectures for Reducing Priority Inversion and Non-determinism in Real-time Object Request Brokers

There is increasing demand to extend Object RequestBroker (ORB) middleware to support distributed applications withstringent real-time requirements. However, conventional ORB implementations,such as CORBA ORBs, exhibit substantial priority inversion andnon-determinism, which makes them unsuitable for applicationswith deterministic real-time requirements. This paper providestwo contributions to the study and design of real-time ORB middleware.First, it illustrates empirically why conventional ORBs do notyet support real-time quality of service. Second, it evaluatesconnection and concurrency software architectures to identifystrategies that reduce priority inversion and non-determinismin real-time CORBA ORBs. The results presented in this paperdemonstrate the feasibility of using standard OO middleware likeCORBA to support certain types of real-time applications overthe Internet.     

Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.

Determination of the Fe content of embedded Cu-rich particles in ferritic alloys using energy-filtered TEM

A novel technique for the quantification of the iron content of copper precipitates in ferritic steels is presented. Energy-filtered (EF) imaging has been used to extract elemental maps with high spatial resolution. These maps contain enough information to attempt the quantification of the signal produced by the precipitates when either a line profile is measured across them or the whole image signal is integrated. Assumptions such as sphericity of the precipitates and composition variations are discussed. Special attention to the assessment of drift on the information extracted from EF images has been taken. Minimum detectability and optimum acquisition conditions are discussed.     

GPGPU implementation of growing neural gas: Application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6×$6\times$ compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.     

Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application

A generalized Bayesian inference framework in order to embed fuzzy sets and partial probabilistic information is provided. The general framework of reference is that of coherent conditional probabilities, which allows giving a rigorous interpretation of membership function as a conditional probability, regarded as a function of the conditioning event. The inferential problem needs to be studied in situations where the prior can be partial; moreover, membership and prior can be given on different classes of events. This inferential model is applied for the virtual representation of a female avatar.     

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.     

Synthesis of MCM-41 frameworks incorporating oxygen-sulphur derivates of molybdenum and tungsten

The first examples of mesostructured materials containing Mo- and W-oxo-sulphur species incorporated into a poorly ordered MCM-41 framework have been prepared under hydrothermal condition and alkaline medium. The incorporation of oxygen-sulphur derivates of molybdenum and tungsten not only increases significantly the pore diameter, but also improves the thermal stability of the MCM-41-related mesoporous material.