Rules and Strategies for Contextual Specialization of Constraint Logic Programs

We address the problem of specializing a constraint logic program w.r.t. a constrained atom which specifies the context of use of the program. We follow an approach based on transformation rules and strategies. We introduce a novel transformation rule, called contextual constraint replacement, to be combined with variants of the traditional unfolding and folding rules. We present a general Partial Evaluation Strategy for automating the application of these rules, and two additional strategies: the Context Propagation Strategy which is instrumental for the application of our contextual constraint replacement rule, and the Invariant Promotion Strategy for taking advantage of invariance properties of the computation. We show through some examples the power of our method and we compare it with existing methods for partial deduction of constraint logic programs based on extensions of Lloyd and Shepherdson's approach.     

Determination of three-dimensional joint loading within the lower extremities in snowboarding

In the biomechanical literature only a few studies are available focusing on the determination of joint loading within the lower extremities in snowboarding. These studies are limited to analysis in a restricted capture volume due to the use of optical video-based systems. To overcome this restriction the aim of the present study was to develop a method to determine net joint moments within the lower extremities in snowboarding for complete measurement runs. An experienced snowboarder performed several runs equipped with two custom-made force plates as well as a full-body inertial measurement system. A rigid, multi-segment model was developed to describe the motion and loads within the lower extremities. This model is based on an existing lower-body model and designed to be run by the OpenSim software package. Measured kinetic and kinematic data were imported into the OpenSim program and inverse dynamic calculations were performed. The results illustrate the potential of the developed method for the determination of joint loadings within the lower extremities for complete measurement runs in a real snowboarding environment. The calculated net joint moments of force are reasonable in comparison to the data presented in the literature. A good reliability of the method seems to be indicated by the low data variation between different turns. Due to the unknown accuracy of this method the application for inter-individual studies as well as studies of injury mechanisms may be limited. For intra-individual studies comparing different snowboarding techniques as well as different snowboard equipment the method seems to be beneficial. The validity of the method needs to be studied further.     

High‐quality pagination for publishing

The problem of line breaking consists of finding the best way to split paragraphs into lines. It has been cleverly addressed by the total‐fit algorithm exposed by Knuth and Plass in a well‐known paper. Similarly, page‐breaking algorithms break the content flow of a document into page units. Formatting languages—such as the World Wide Web Consortium standard Extensible Stylesheet Language Formatting Objects (XSL‐FO)—allow users to set which content should be kept in the same page and how many isolated lines are acceptable at the beginning/end of each page. The strategies most formatters adopt to meet these requirements, however, are not satisfactory for many publishing contexts as they very often generate unpleasant empty areas. In that case, typographers are required to manually craft the results in order to completely fill pages. This paper presents a page‐breaking algorithm that extends the original Knuth and Plass line‐breaking approach and produces high‐quality documents without unwanted empty areas. The basic idea consists of delaying the definitive choice of breaks in the line‐breaking process in order to provide a larger set of alternatives to the actual pagination step. The algorithm also allows users to decide the set of properties to be adjusted for pagination and their variation ranges. An application of the algorithm to XSL‐FO is also presented, with an extension of the language that allows users to drive the pagination process. The tool, named FOP+, is a customized version of the open‐source Apache Formatting Objects Processor formatter. Copyright © 2011 John Wiley & Sons, Ltd.     

ISHair: Importance Sampling for Hair Scattering

We present an importance sampling method for the bidirectional scattering distribution function (bsdf) of hair. Our method is based on the multi‐lobe hair scattering model presented by Sadeghi et al. [ [SPJT10] ]. We reduce noise by drawing samples from a distribution that approximates the bsdf well. Our algorithm is efficient and easy to implement, since the sampling process requires only the evaluation of a few analytic functions, with no significant memory overhead or need for precomputation. We tested our method in a research raytracer and a production renderer based on micropolygon rasterization. We show significant improvements for rendering direct illumination using multiple importance sampling and for rendering indirect illumination using path tracing.     

Dense versus Sparse Approaches for Estimating the Fundamental Matrix

There are two main strategies for solving correspondence problems in computer vision: sparse local feature based approaches and dense global energy based methods. While sparse feature based methods are often used for estimating the fundamental matrix by matching a small set of sophistically optimised interest points, dense energy based methods mark the state of the art in optical flow computation. The goal of our paper is to show that this separation into different application domains is unnecessary and can be bridged in a natural way. As a first contribution we present a new application of dense optical flow for estimating the fundamental matrix. Comparing our results with those obtained by feature based techniques we identify cases in which dense methods have advantages over sparse approaches. Motivated by these promising results we propose, as a second contribution, a new variational model that recovers the fundamental matrix and the optical flow simultaneously as the minimisers of a single energy functional. In experiments we show that our coupled approach is able to further improve the estimates of both the fundamental matrix and the optical flow. Our results prove that dense variational methods can be a serious alternative even in classical application domains of sparse feature based approaches.     

Distributed estimation via iterative projections with application to power network monitoring

This work presents a distributed method for control centers to monitor the operating condition of a power network, i.e., to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements.     

A covert attention P300-based brain-computer interface: Geospell

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities. PRACTITIONER SUMMARY: This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.     

Load forecasting framework of electricity consumptions for an Intelligent Energy Management System in the user-side

This work presents an electricity consumption-forecasting framework configured automatically and based on an Adaptative Neural Network Inference System (ANFIS). This framework is aimed to be implemented in industrial plants, such as automotive factories, with the objective of giving support to an Intelligent Energy Management System (IEMS). The forecasting purpose is to support the decision-making (i.e. scheduling workdays, on-off production lines, shift power loads to avoid load peaks, etc.) to optimize and improve economical, environmental and electrical key performance indicators. The base structure algorithm, the ANFIS algorithm, was configured by means of a Multi Objective Genetic Algorithm (MOGA), with the aim of getting an automatic-configuration system modelling. This system was implemented in an independent section of an automotive factory, which was selected for the high randomness of its main loads. The time resolution for forecasting was the quarter hour. Under these challenging conditions, the autonomous configuration, system learning and prognosis were tested with success.     

Dual three-phase induction motor drive with digital current control in the stationary reference frame

Among different multiphase motor drive solutions, one of the most widely discussed is the voltage source inverter (VSI) fed dual three-phase induction machine. Over the years, various topics pertinent to this specific motor drive system have been investigated in considerable depth and, more recently, various reports on real-world applications have emerged. In this paper, a drive system that has been developed specifically for electrical vehicles is described. For vector control purposes, the drive was modeled using an approach that is based on the vector space decomposition technique since it directly leads to the proposed current control method in the stationary reference frame.     

An efficient technique for implementing an image-compression neural algorithm on concurrent multiprocessor architectures

The paper describes a parallel implementation of a neural algorithm performing vector quantization for very low bit-rate video compression on toroidal-mesh multiprocessor systems. The neural model considered is a plastic version of the Neural Gas algorithm, whose features are suitable for implementations on toroidal mesh topologies. The architecture adopted, and the data-allocation strategy, enhance the method's scaling properties and remarkable efficiency. The parallel approach is supported by a theoretical analysis of the efficiency of the overall structure. Experimental results on a significant testbed and the fit between predicted and measured values confirm the validity of the parallel approach.