INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Field-programmable gate array & Control theory. The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Solving QBF with counterexample guided refinement

Abstract: We propose two novel approaches for using Counterexample-Guided Abstraction Refinement (CEGAR) in Quantified Boolean Formula (QBF) solvers. The first approach develops a recursive algorithm whose search is driven by CEGAR (rather than by DPLL). The second approach employs CEGAR as an additional learning technique in an existing DPLL-based QBF solver. Experimental evaluation of the implemented prototypes shows that the CEGAR-driven solver outperforms existing solvers on a number of families in the QBF-LIB and that the DPLL solver benefits from the additional type of learning. Thus this article opens two promising avenues in QBF: CEGAR-driven solvers as an alternative to existing approaches and a novel type of learning in DPLL.

Analysis of Typing Methods for Epidemiological Surveillance of both Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus Strains

Abstract: Sequence-based methods for typing Staphylococcus aureus, such as multilocus sequence typing (MLST) and spa typing, have increased interlaboratory reproducibility, portability, and speed in obtaining results, but pulsed-field gel electrophoresis (PFGE), remains the method of choice in many laboratories due to the extensive experience with this methodology and the large body of data accumulated using the technique. Comparisons between typing methods have been overwhelmingly based on a qualitative assessment of the overall agreement of results and the relative discriminatory indexes. In this study, we quantitatively assess the congruence of the major typing methods for S. aureus, using a diverse collection of 198 S. aureus strains previously characterized by PFGE, spa typing, MLST, and, in the case of methicillin-resistant S. aureus (MRSA), SCCmec typing in order to establish the quantitative congruence between the typing methods. The results of most typing methods agree in that MRSA and methicillin-susceptible S. aureus (MSSA) differ in terms of diversity of genetic backgrounds, with MSSA being more diverse. Our results show that spa typing has a very good predictive power over the clonal relationships defined by eBURST, while PFGE is less accurate for that purpose but nevertheless provides better typeability and discriminatory power. The combination of PFGE and spa typing provided even better results. Based on these observations, we suggest the use of the conjugation of spa typing and PFGE typing for epidemiological surveillance studies, since this combination provides the ability to infer long-term relationships while maintaining the discriminatory power and typeability needed in short-term studies.

Unscripted narrative for affectively driven characters

Abstract: In this article, we report on the emergent narrative concept aiming at the definition of a narrative theory adapted to the VR medium (whether a game or VR application). The inherent freedom of movement proper to VR - an indisputable element of immersion - collides with the Aristotelian vision of articulated plot events with respect to the given timeline associated with the story in display. This narrative paradox can only be observed in interactive VR applications and it doesn't seem possible to resolve it through the use of existing narrative theories. Interactivity is the novel element that storytellers must address. The authors discuss designing unscripted dramas with affectively driven intelligent autonomous characters based on the development of the FearNot! system for education against bullying

Design and evaluation of the clear-PEM scanner for positron emission mammography

Abstract: The design and evaluation of the imaging system Clear-PEM for positron emission mammography, under development by the PEM Consortium within the framework of the Crystal Clear Collaboration at CERN, is presented. The proposed apparatus is based on fast, segmented, high atomic number radiation sensors with depth-of-interaction measurement capabilities, and state-of-the-art data acquisition techniques. The camera consists of two compact and planar detector heads with dimensions 16.5/spl times/14.5 cm/sup 2/ for breast and axilla imaging. Low-noise integrated electronics provide signal amplification and analog multiplexing based on a new data-driven architecture. The coincidence trigger and data acquisition architecture makes extensive use of pipeline processing structures and multi-event memories for high efficiency up to a data acquisition rate of one million events/s. Experimental validation of the detection techniques, namely the basic properties of the radiation sensors and the ability to measure the depth-of-interaction of the incoming photons, are presented. System performance in terms of detection sensitivity, count-rates and reconstructed image spatial resolution were also evaluated by means of a detailed Monte Carlo simulation and an iterative image reconstruction algorithm.

Exact and Approximate Algorithms for the Optimization of Area and Delay in Multiple Constant Multiplications

Abstract: The main contribution of this paper is an exact common subexpression elimination algorithm for the optimum sharing of partial terms in multiple constant multiplications (MCMs). We model this problem as a Boolean network that covers all possible partial terms that may be used to generate the set of coefficients in the MCM instance. We cast this problem into a 0-1 integer linear programming (ILP) by requiring that the single output of this network is asserted while minimizing the number of gates representing operations in the MCM implementation that evaluate to one. A satisfiability (SAT)-based 0-1 ILP solver is used to obtain the exact solution. We argue that for many real problems, the size of the problem is within the capabilities of current SAT solvers. Because performance is often a primary design parameter, we describe how this algorithm can be modified to target the minimum area solution under a user-specified delay constraint. Additionally, we propose an approximate algorithm based on the exact approach with extremely competitive results. We have applied these algorithms on the design of digital filters and present a comprehensive set of results that evaluate ours and existing approximation schemes against exact solutions under different number representations and using different SAT solvers.