Who am I talking with? A face memory for social robots

In order to provide personalized services and to develop human-like interaction capabilities robots need to rec- ognize their human partner. Face recognition has been studied in the past decade exhaustively in the context of security systems and with significant progress on huge datasets. However, these capabilities are not in focus when it comes to social interaction situations. Humans are able to remember people seen for a short moment in time and apply this knowledge directly in their engagement in conversation. In order to equip a robot with capabilities to recall human interlocutors and to provide user- aware services, we adopt human-human interaction schemes to propose a face memory on the basis of active appearance models integrated with the active memory architecture. This paper presents the concept of the interactive face memory, the applied recognition algorithms, and their embedding into the robot’s system architecture. Performance measures are discussed for general face databases as well as scenario-specific datasets

A Symbolic Execution Algorithm for Constraint-Based Testing of Database Programs

In so-called constraint-based testing, symbolic execution is a common technique used as a part of the process to generate test data for imperative programs. Databases are ubiquitous in software and testing of programs manipulating databases is thus essential to enhance the reliability of software. This work proposes and evaluates experimentally a symbolic ex- ecution algorithm for constraint-based testing of database programs. First, we describe SimpleDB, a formal language which offers a minimal and well-defined syntax and seman- tics, to model common interaction scenarios between pro- grams and databases. Secondly, we detail the proposed al- gorithm for symbolic execution of SimpleDB models. This algorithm considers a SimpleDB program as a sequence of operations over a set of relational variables, modeling both the database tables and the program variables. By inte- grating this relational model of the program with classical static symbolic execution, the algorithm can generate a set of path constraints for any finite path to test in the control- flow graph of the program. Solutions of these constraints are test inputs for the program, including an initial content for the database. When the program is executed with respect to these inputs, it is guaranteed to follow the path with re- spect to which the constraints were generated. Finally, the algorithm is evaluated experimentally using representative SimpleDB models.Comment: 12 pages - preliminary wor

Spots of interaction: an investigation on the relationship between firms and universities in Minas Gerais, Brazil

Spots of interaction summarize the nature of partial connections (between science and technology) operating in the Brazilian system of innovation. A pilot study in Minas Gerais, Brazil, uses two new research tools (for immature NSIs) and presents a database with research groups located in universities and a database built upon an adapted version of the pioneering Yale and Carnegie Mellon Surveys. These complementary databases identify spots of interaction, indicating how economic sectors use specific science and engineering fields. This investigation identifies a dual role of universities in immature NSIs, as substitutes and/or complements firms R&D.systems of innovation, underdevelopment, interactions between science and technology, surveys, universities

Power Deposition on Tokamak Plasma-Facing Components

The SMARDDA software library is used to model plasma interaction with complex engineered surfaces. A simple flux-tube model of power deposition necessitates the following of magnetic fieldlines until they meet geometry taken from a CAD (Computer Aided Design) database. Application is made to 1) models of ITER tokamak limiter geometry and 2) MASTU tokamak divertor designs, illustrating the accuracy and effectiveness of SMARDDA, even in the presence of significant nonaxisymmetric ripple field. SMARDDA's ability to exchange data with CAD databases and its speed of execution also give it the potential for use directly in the design of tokamak plasma facing components.Comment: 13 pages, 20 figure

A benchmark for galactic cosmic ray transport codes

A nontrivial analytic benchmark solution for galactic cosmic ray transport is presented for use in transport code validation. Computational accuracy for a previously-developed cosmic ray transport code is established to within one percent by comparison with this exact benchmark. Hence, solution accuracy for the transport problem is mainly limited by inaccuracies in the input spectra, input interaction databases, and the use of a straight ahead/velocity-conserving approximation

A network inference method for large-scale unsupervised identification of novel drug-drug interactions

Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and does not require any pharmacological or biochemical information about the drugs, their targets or their mechanisms of action. Because the models we use are abstract, our approach can deal with adverse interactions, synergistic/antagonistic/suppressing interactions, or any other type of drug interaction. We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. We also demonstrate that our algorithm can be used efficiently to discover interactions of new drugs as part of the drug discovery process