Numerical Methods for Obtaining Multimedia Graphical Effects

This paper is an explanatory document about how several animations effects can be obtained using different numerical methods, as well as investigating the possibility of implementing them on very simple yet powerful massive parallel machines. The methods are clearly described, containing graphical examples of the effects, as well as workflow for the algorithms. All of the methods presented in this paper use only numerical matrix manipulations, which usually are fast, and do not require the use of any other graphical software application.raster graphics, numerical matrix manipulation, animation effects

Recommendation Heuristics for Improving Product Line Configuration Processes

In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line configuration should be guided by the product line model. However, in the industrial context, the configuration of products from product line models is complex and error prone due to the large number of variables in the models. The configuration activity quickly becomes cumbersome due to the number of decisions needed to get a proper configuration, to the fact that they should be taken in pre-defined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interactivity of product line configuration so as to make it scalable to common engineering situations.We describe the principles, benefits and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry

L'extraction d'information des sources de données non structurées et semi-structurées

L'objectif de la thèse: Dans le contexte des dépôts de connaissances de grandes dimensions récemment apparues, on exige l'investigation de nouvelles méthodes innovatrices pour résoudre certains problèmes dans le domaine de l'Extraction de l'Information (EI), tout comme dans d'autres sous-domaines apparentés. La thèse débute par un tour d'ensemble dans le domaine de l'Extraction de l'Information, tout en se concentrant sur le problème de l'identification des entités dans des textes en langage naturel. Cela constitue une démarche nécessaire pour tout système EI. L'apparition des dépôts de connaissances de grandes dimensions permet le traitement des sous-problèmes de désambigüisation au Niveau du Sens (WSD) et La Reconnaissance des Entités dénommées (NER) d'une manière unifiée. Le premier système implémenté dans cette thèse identifie les entités (les noms communs et les noms propres) dans un texte libre et les associe à des entités dans une ontologie, pratiquement, tout en les désambigüisant. Un deuxième système implémenté, inspiré par l'information sémantique contenue dans les ontologies, essaie, également, l'utilisation d'une nouvelle méthode pour la solution du problème classique de classement de texte, obtenant de bons résultats.Thesis objective: In the context of recently developed large scale knowledge sources (general ontologies), investigate possible new approaches to major areas of Information Extraction (IE) and related fields. The thesis overviews the field of Information Extraction and focuses on the task of entity recognition in natural language texts, a required step for any IE system. Given the availability of large knowledge resources in the form of semantic graphs, an approach that treats the sub-tasks of Word Sense Disambiguation and Named Entity Recognition in a unified manner is possible. The first implemented system using this approach recognizes entities (words, both common and proper nouns) from free text and assigns them ontological classes, effectively disambiguating them. A second implemented system, inspired by the semantic information contained in the ontologies, also attempts a new approach to the classic problem of text classification, showing good results

Total Quality Management, a New Culture Model of the Enterprise

The paper brings bags of clarifications about concept definition and bases principles of TQM, presenting the critical factors during the implementation of those fundamentals. Also, it has been proposed a lot of models to present the Total Quality Management, being also presented its evolution

Quantum Quasi-Monte Carlo algorithm for out-of-equilibrium Green functions at long times

We extend the recently developed Quantum Quasi-Monte Carlo (QQMC) approach to obtain the full frequency dependence of Green functions in a single calculation. QQMC is a general approach for calculating high-order perturbative expansions in power of the electron-electron interaction strength. In contrast to conventional Markov chain Monte Carlo sampling, QQMC uses low-discrepancy sequences for a more uniform sampling of the multi-dimensional integrals involved and can potentially outperform Monte Carlo by several orders of magnitudes. A core concept of QQMC is the a priori construction of a "model function" that approximates the integrand and is used to optimize the sampling distribution. In this paper, we show that the model function concept extends to a kernel approach for the computation of Green functions. We illustrate the approach on the Anderson impurity model and show that the scaling of the error with the number of integrand evaluations $N$ is $\sim 1/N^{0.86}$ in the best cases, and comparable to Monte Carlo scaling $\sim 1/N^{0.5}$ in the worst cases. We find a systematic improvement over Monte Carlo sampling by at least two orders of magnitude while using a basic form of model function. Finally, we compare QQMC results with calculations performed with the Fork Tensor Product State (FTPS) method, a recently developed tensor network approach for solving impurity problems. Applying a simple Pad\'e approximant for the series resummation, we find that QQMC matches the FTPS results beyond the perturbative regime.Comment: 18 pages, 11 figure

Structuring Framework for Early Validation of Product Ideas

The advancing digitalization leads to new challenges in the development of new product ideas. The systems, which need to be developed, are becoming increasingly complex. As complexity rises, so does the slowness of organizations. In order to remain innovative and be able to react quickly to changes in the market, validation approaches offer great potential. An essential focus is the early, customer-centric and continuous validation of development artefacts. This is the only way to cope with shorter development cycles, and develop products that address a real need. To plan a validation, engineers need to have an idea about the possibilities within a validation. This paper presents a structuring framework for early validation of product ideas, which contains the three tools of Validation Map, Building Block Cards and Validation Canvas. The objective is to enable easier planning of validation experiments

Analysis Model of GDP Dependence on the Structural Variables

In this paper, the authors present an analysis model designed to outline some of the Gross Domestic dependences, on the case of Romanian economy. The study is based on the VAR methodology, and the steps pursued in the article are the study of evolution for Final Consumption, direct foreign investments flow and GDP, the presentation of the estimated VAR models, the testing for the number of lags, the testing for the stationery of the first difference of the data series