Approximated Poncelet configurations

In this short note we present the approximate construction of closed Poncelet configurations using the simulation of a mathematical pendulum. Although the idea goes back to the work of Jacobi, only the use of modern computer technologies assures the success of the construction. We present also some remarks on using such problems in project based university courses and we present a Matlab program able to produce animated Poncelet configurations with given period. In the same spirit we construct Steiner configurations and we give a few teaching oriented remarks on the Poncelet grid theorem. (DIPF/authors)

Compiling Exceptions Correctly

Exceptions are an important feature of modern programming languages, but their compilation has traditionally been viewed as an advanced topic. In this article we show that the basic method of compiling exceptions using stack unwinding can be explained and verified both simply and precisely, using elementary functional programming techniques. In particular, we develop a compiler for a small language with exceptions, together with a proof of its correctness.

Guiding Monte Carlo tree searches with neural networks in the game of go

A dissertation submitted in fulfillment of the requirements to the degree of Master in Computer Science and Computer Engineering

The role of musical aptitude in the pronunciation of English vowels among Polish learners of English

It has long been held that people who have musical training or talent acquire L2 pronunciation more successfully than those that do not. Indeed, there have been empirical studies to support this hypothesis (Pastuszek-Lipińska 2003, Fonseca-Mora et al. 2011, Zatorre and Baum 2012). However, in many of such studies, musical abilities in subjects were mostly verified through questionnaires rather than tested in a reliable, empirical manner. Therefore, we run three different musical hearing tests, i.e. pitch perception test, musical memory test, and rhythm perception test (Mandell 2009) to measure the actual musical aptitude in our subjects. The main research question is whether a better musical ear correlates with a higher rate of acquisition of English vowels in Polish EFL learners. Our group consists of 40 Polish university students studying English as their major who learn the British pronunciation model during an intense pronunciation course. 10 male and 30 female subjects with mean age of 20.1 were recorded in a recording studio. The procedure comprised spontaneous conversations, reading passages and reading words in isolation. Vowel measurements were conducted in Praat in all three speech styles and several consonantal contexts. The assumption was that participants who performed better in musical tests would produce vowels that are closer to the Southern British English model. We plotted them onto vowel charts and calculated the Euclidean distances. Preliminary results show that there is potential correlation between specific aspects of musical hearing and different elements of pronunciation. The study is a longitudinal project and will encompass two more years, during which we will repeat the recording procedure twice to measure the participants’ progress in mastering the English pronunciation and comparing it with their musical aptitude.

Subject categories used in Nuclear science abstracts, 1967-1975 /

"TID-26500/R1. Distribution category: UC-2."

Self-regulated learning in computer programming : strategies students adopted during an assignment

The SimProgramming teaching approach has the goal to help students overcome their learning difficulties in the transition from entry-level to advanced computer programming and prepare them for real-world labour environments, adopting learning strategies. It immerses learners in a businesslike learning environment, where students develop a problem-based learning activity with a specific set of tasks, one of which is filling weekly individual forms. We conducted thematic analysis of 401 weekly forms, to identify the students’ strategies for self-regulation of learning during assignment. The students are adopting different strategies in each phase of the approach. The early phases are devoted to organization and planning, later phases focus on applying theoretical knowledge and hands-on programming. Based on the results, we recommend the development of educational practices to help students conduct self-reflection of their performance during tasks.

Discrete breathers in a two-dimensional hexagonal Fermi-Pasta-Ulam lattice

We consider a two-dimensional Fermi-Pasta-Ulam (FPU) lattice with hexagonal symmetry. Using asymptotic methods based on small amplitude ansatz, at third order we obtain a eduction to a cubic nonlinear Schr{\"o}dinger equation (NLS) for the breather envelope. However, this does not support stable soliton solutions, so we pursue a higher-order analysis yielding a generalised NLS, which includes known stabilising terms. We present numerical results which suggest that long-lived stationary and moving breathers are supported by the lattice. We find breather solutions which move in an arbitrary direction, an ellipticity criterion for the wavenumbers of the carrier wave, symptotic estimates for the breather energy, and a minimum threshold energy below which breathers cannot be found. This energy threshold is maximised for stationary breathers, and becomes vanishingly small near the boundary of the elliptic domain where breathers attain a maximum speed. Several of the results obtained are similar to those obtained for the square FPU lattice (Butt \& Wattis, {\em J Phys A}, {\bf 39}, 4955, (2006)), though we find that the square and hexagonal lattices exhibit different properties in regard to the generation of harmonics, and the isotropy of the generalised NLS equation.

Discrete breathers in a two-dimensional Fermi-Pasta-Ulam lattice

Using asymptotic methods, we investigate whether discrete breathers are supported by a two-dimensional Fermi-Pasta-Ulam lattice. A scalar (one-component) two-dimensional Fermi-Pasta-Ulam lattice is shown to model the charge stored within an electrical transmission lattice. A third-order multiple-scale analysis in the semi-discrete limit fails, since at this order, the lattice equations reduce to the (2+1)-dimensional cubic nonlinear Schrödinger (NLS) equation which does not support stable soliton solutions for the breather envelope. We therefore extend the analysis to higher order and find a generalised $(2+1)$-dimensional NLS equation which incorporates higher order dispersive and nonlinear terms as perturbations. We find an ellipticity criterion for the wave numbers of the carrier wave. Numerical simulations suggest that both stationary and moving breathers are supported by the system. Calculations of the energy show the expected threshold behaviour whereby the energy of breathers does {\em not} go to zero with the amplitude; we find that the energy threshold is maximised by stationary breathers, and becomes arbitrarily small as the boundary of the domain of ellipticity is approached.

Model Probability in Self-organising Maps

Growing models have been widely used for clustering or topology learning. Traditionally these models work on stationary environments, grow incrementally and adapt their nodes to a given distribution based on global parameters. In this paper, we present an enhanced unsupervised self-organising network for the modelling of visual objects. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product.

Convolution of Orbital Measures on Symmetric Spaces of type Cp and Dp

International audience

Transdiscipline and research in health: Science, society and decision making

Significant advances in science should be given to addressing the needs of society and the historical context of the territories. Although technological developments that began with modernity and the industrial revolution allowed human beings to control the resources of nature to put to your service without limits, it is clear that the crisis of the prevailing development models manifest themselves in many ways but with three common denominators: environmental degradation, social injustice and extreme poverty. Consequently, today should not be possible to think a breakthrough in the development of science without addressing global environmental problems and the deep social injustices that increase at all scales under the gaze, impassively in many occasions, of formal science.

MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.