Towards the automatic generation of card games through Grammar-Guided Genetic Programming

We demonstrate generating complete and playable card games using evolutionary algorithms. Card games are represented in a previously devised card game description language, a context-free grammar. The syntax of this language allows us to use grammar-guided genetic programming. Candidate card games are evaluated through a cascading evaluation function, a multi-step process where games with undesired properties are progressively weeded out. Three representa- tive examples of generated games are analysed. We observed that these games are reasonably balanced and have skill ele- ments, they are not yet entertaining for human players. The particular shortcomings of the examples are discussed in re- gard to the generative process to be able to generate quality games

GMM-based classifiers for the automatic detection of obstructive sleep apnea

The aim of automatic pathological voice detection systems is to serve as tools, to medical specialists, for a more objective, less invasive and improved diagnosis of diseases. In this respect, the gold standard for those system include the usage of a optimized representation of the spectral envelope, either based on cepstral coefficients from the mel-scaled Fourier spectral envelope (Mel-Frequency Cepstral Coefficients) or from an all-pole estimation (Linear Prediction Coding Cepstral Coefficients) forcharacterization, and Gaussian Mixture Models for posterior classification. However, the study of recently proposed GMM-based classifiers as well as Nuisance mitigation techniques, such as those employed in speaker recognition, has not been widely considered inpathology detection labours. The present work aims at testing whether or not the employment of such speaker recognition tools might contribute to improve system performance in pathology detection systems, specifically in the automatic detection of Obstructive Sleep Apnea. The testing procedure employs an Obstructive Sleep Apnea database, in conjunction with GMM-based classifiers looking for a better performance. The results show that an improved performance might be obtained by using such approach.

Refined facial disparity maps for automatic creation of 3D avatars

We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

A Knowledge Model for Automatic Configuration of Traffic Messages

This paper describes a knowledge model for a configuration problem in the do-main of traffic control. The goal of this model is to help traffic engineers in the dynamic selection of a set of messages to be presented to drivers on variable message signals. This selection is done in a real-time context using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based solution that implements two abstract problem solving methods according to a model-based approach recently proposed in the knowledge engineering field. Finally, the paper presents a discussion about the advantages and drawbacks found for this problem as a consequence of the applied knowledge modeling ap-proach.

A Knowledge-based Approach for Automatic Generation of Summaries of Behavior

Effective automatic summarization usually requires simulating human reasoning such as abstraction or relevance reasoning. In this paper we describe a solution for this type of reasoning in the particular case of surveillance of the behavior of a dynamic system using sensor data. The paper first presents the approach describing the required type of knowledge with a possible representation. This includes knowledge about the system structure, behavior, interpretation and saliency. Then, the paper shows the inference algorithm to produce a summarization tree based on the exploitation of the physical characteristics of the system. The paper illustrates how the method is used in the context of automatic generation of summaries of behavior in an application for basin surveillance in the presence of river floods.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

Automatic quantification of matrix cracking and fiber rotation by X-ray computed tomography in shear-deformed carbon fiber-reinforced laminates

The deformation and damage mechanisms of carbon fiber-reinforced epoxy laminates deformed in shear were studied by means of X-ray computed tomography. In particular, the evolution of matrix cracking, interply delamination and fiber rotation was ascertained as a function of the applied strain. In order to provide quantitative information, an algorithm was developed to automatically determine the crack density and the fiber orientation from the tomograms. The investigation provided new insights about the complex interaction between the different damage mechanisms (i.e. matrix cracking and interply delamination) as a function of the applied strain, ply thickness and ply location within the laminate as well as quantitative data about the evolution of matrix cracking and fiber rotation during deformation

Novel educational assessment for building structures: Automatic evaluation of on-line graphics

This article presents a new automatic evaluation for on-line graphics, its application and the numerous advantages achieved applying this developed correcting method. The software application developed by the Innovation in Education Group “E4”, from the Technical University of Madrid, is oriented for the online self-assessment of the graphic drawings that students carry out as continuous training. The adaptation to the European Higher Educational Area is an important opportunity to research about the possibilities of on-line education assessment. In this way, a new software tool has been developed for continuous self-testing by undergraduates. Using this software it is possible to evaluate the graphical answer of the students. Thus, the drawings made on-line by students are automatically corrected according to the geometry (straight lines, sloping lines or second order curves) and by sizes (depending on the specific values which define the graphics).

A tool for the automatic analysis of single events effects on electronic circuits

Nowadays integrated circuit reliability is challenged by both variability and working conditions. Environmental radiation has become a major issue when ensuring the circuit correct behavior. The required radiation and later analysis performed to the circuit boards is both fund and time expensive. The lack of tools which support pre-manufacturing radiation hardness analysis hinders circuit designers tasks. This paper describes an extensively customizable simulation tool for the characterization of radiation effects on electronic systems. The proposed tool can produce an in depth analysis of a complete circuit in almost any kind of radiation environment in affordable computation times.

Automatic segmentation of rivers as a tool for assessing river responses. Case study: the Porma and Curueño rivers, nw Spain.

Automatic segmentation using univariate and multivariate techniques provides more objective and efficient segmentations of the river systems (Alber & Piégay, 2011) and can be complementary to the expert criteria traditionally used (Brenden et al., 2008) INTEREST: A powerful tool to objectively segment the continuity of rivers, which is required for diagnosing problems associated to human impacts OBJECTIVE: To evaluate the potentiality of univariate and multivariate methods in the assessment of river adjustments produced by flow regulation

Ultrasonic tagging of light: Theory

A theory is provided for the detection efficiency of diffuse light whose frequency is modulated by an acoustical wave. We derive expressions for the speckle pattern of the modulated light, as well as an expression for the signal-to-noise ratio for the detector. The aim is to develop a new imaging technology for detection of tumors in humans. The acoustic wave is focused into a small geometrical volume, which provides the spatial resolution for the imaging. The wavelength of the light wave can be selected to provide information regarding the kind of tumor.

Differential Epitope Tagging of Actin in Transformed Drosophila Produces Distinct Effects on Myofibril Assembly and Function of the Indirect Flight Muscle

We have tested the impact of tags on the structure and function of indirect flight muscle (IFM)-specific Act88F actin by transforming mutant Drosophila melanogaster, which do not express endogenous actin in their IFMs, with tagged Act88F constructs. Epitope tagging is often the method of choice to monitor the fate of a protein when a specific antibody is not available. Studies addressing the functional significance of the closely related actin isoforms rely almost exclusively on tagged exogenous actin, because only few antibodies exist that can discriminate between isoforms. Thereby it is widely presumed that the tag does not significantly interfere with protein function. However, in most studies the tagged actin is expressed in a background of endogenous actin and, as a rule, represents only a minor fraction of the total actin. The Act88F gene encodes the only Drosophila actin isoform exclusively expressed in the highly ordered IFM. Null mutations in this gene do not affect viability, but phenotypic effects in transformants can be directly attributed to the transgene. Transgenic flies that express Act88F with either a 6x histidine tag or an 11-residue peptide derived from vesicular stomatitis virus G protein at the C terminus were flightless. Overall, the ultrastructure of the IFM resembled that of the Act88F null mutant, and only low amounts of C-terminally tagged actins were found. In contrast, expression of N-terminally tagged Act88F at amounts comparable with that of wild-type flies yielded fairly normal-looking myofibrils and partially reconstituted flight ability in the transformants. Our findings suggest that the N terminus of actin is less sensitive to modifications than the C terminus, because it can be tagged and still polymerize into functional thin filaments.

Transposon tagging of tobacco mosaic virus resistance gene N: its possible role in the TMV-N-mediated signal transduction pathway.

Plants can recognize and resist invading pathogens by signaling the induction of rapid defense responses. Often these responses are mediated by single dominant resistance genes (R genes). The products of R genes have been postulated to recognize the pathogen and trigger rapid host defense responses. Here we describe isolation of the classical resistance gene N of tobacco that mediates resistance to the well-characterized pathogen tobacco mosaic virus (TMV). The N gene was isolated by transposon tagging using the maize Activator (Ac) transposon. We confirmed isolation of the N gene by complementation of the TMV-sensitive phenotype with a genomic DNA fragment. Sequence analysis of the N gene shows that it encodes a protein with an amino-terminal domain similar to that of the cytoplasmic domains of the Drosophila Toll protein and the interleukin 1 receptor in mammals, a putative nucleotide-binding site and 14 imperfect leucine-rich repeats. The presence of these functional domains in the predicted N gene product is consistent with the hypothesis that the N resistance gene functions in a signal transduction pathway. Similarities of N to Toll and the interleukin 1 receptor suggest a similar signaling mechanism leading to rapid gene induction and TMV resistance.

Automatic extraction of syntactic semantic patterns for multilingual resources

In this paper we present an automatic system for the extraction of syntactic semantic patterns applied to the development of multilingual processing tools. In order to achieve optimum methods for the automatic treatment of more than one language, we propose the use of syntactic semantic patterns. These patterns are formed by a verbal head and the main arguments, and they are aligned among languages. In this paper we present an automatic system for the extraction and alignment of syntactic semantic patterns from two manually annotated corpora, and evaluate the main linguistic problems that we must deal with in the alignment process.

Automatic prediction of emotions from text in Spanish for expressive speech synthesis in the chat domain

This paper describes a module for the prediction of emotions in text chats in Spanish, oriented to its use in specific-domain text-to-speech systems. A general overview of the system is given, and the results of some evaluations carried out with two corpora of real chat messages are described. These results seem to indicate that this system offers a performance similar to other systems described in the literature, for a more complex task than other systems (identification of emotions and emotional intensity in the chat domain).