The Social Network Induced by the Common Knowledge of Proverbs.

2009 International Conference on Advances in Social Network Analysis and Data Mining (ASONAM 2009), 20-22 July, Athens, Greece.In a series of interviews, we collected a heterogeneous set of several million relations of positive and negative knowledge that a group of thousands of people has about a set of circa twenty-two thousand Portuguese proverbs. One of the interesting questions was if we could find a minimum base of proverbs as an indicator to decide from which place a person came due to their specific profile of proverbial knowledge. Before trying this challenge, we will analyse, in this article, the probability of achieving such an idea by trying to find out if a homomorphism between the proverbial knowledge and the geographical location of a person could exist. To solve this question, we chose an approach based on the analysis of social networks where the broadcast of oral culture, at least historically, could be interpreted as a trace of direct social contact between some of their users. We found, in the present pilot-project based on small data sets, that there are clusters where the neighbourhood relation inducted by the minimum Hamming distance could be a reflex of the geographical distribution and of some migration flux of the population

Hierarchical clique analysis in social networks due to common knowledge of proverbs.

24th European Conference on Operational Research (EURO XXIV). Lisboa, 11 a 14 de Julho de 2010 (Comunicação).We present the Hierarchical Clique Analysis, a new algorithm for social networks analysis. The algorithm is exemplified with data about the recognition of proverbs collected in interviews in all Azorean islands and also in three Azorean emigration locations in the USA. Interpreting the set of this data as an incidence matrix of a graph, we obtain 8 oriented and isolated sub-graphs which distinguish the society in a kind of different families of proverbial users. The Hierarchical Clique Analysis finds distinct clusters with a high inner homogeneity

Prever a origem do utilizador de um conjunto de provérbios.

XIV Jornadas de Classificação e Análise de Dados, Instituto Superior de Engenharia, Porto, 8-10 Fevereiro de 2007.Em geral, salienta-se o aspecto de os provérbios representarem uma matriz conceptual dos diversos esquemas de pensamento do povo português. Parece promissor estudar os Adagiários para adquirir um conhecimento básico das correntes de pensamento colectivo. Partindo de três colectâneas regionais baseadas em métodos quantitativos (Funk e Funk 2001a, 2001b e 2002), este artigo explora as diversidades regionais. Um estudo preliminar (Mendes, et al. 2006) confirmou as hipóteses dos autores dos adagiários açorianos da existência de uma relação significativa e positiva entre o conhecimento quantitativo de provérbios e a idade, nomeadamente o maior grau de reconhecimento de provérbios para inquiridos com idades superiores a 40 anos. Verificou-se que, nas ilhas do arquipélago dos Açores, se encontra uma taxa de reconhecimento superior às zonas de emigração açoriana. Esta observação pode reflectir o facto de, nestes últimos locais, a assimilação de uma cultura anglo-saxónica reduzir o repertório proverbial em Português, apesar de ser evidente que alguns provérbios são preservados como relíquias culturais. Registou-se que, em algumas ilhas pequenas, a quantidade dos provérbios era reduzida. (da Introdução

Extrair conhecimento de bases de dados: o caso dos provérbios.

Publicado também com o título “Extrair Conhecimento de Provérbios” em: Salgueiro, Maria de Fátima; Mendes, Diana A. e Martins, Luis F. (Eds.), «Temas e Métodos Quantitativos», vol. 6, Sílabo: Lisboa: 91-110, 2009. ISBN: 978-972-618-540-6.Para apoiar actividades de gestão de dados de um projecto para identificação de provérbios, tem vindo a ser construída uma base de dados ao longo de vários anos. No momento da presente análise, esta base de dados integrava informação sobre 25.000 expressões idiomáticas, incluindo mais de um milhar de respostas válidas a inquéritos de reconhecimento de provérbios. Neste artigo, descreve-se um projecto em curso com o objectivo de extrair conhecimento desta base de dados, de modo a conhecer melhor os inquiridos, o seu grau de reconhecimento de provérbios e a relação com os locais onde têm vivido. De modo a alcançar os objectivos delineados, propõe-se a utilização de metodologias de prospecção de dados (data mining), com passos como: preparação e pré-processamento, limpeza (data cleansing) e técnicas de redução de dados. A fase de preparação é cuidadosamente trabalhada, uma vez que nem sempre é descrita em estudos de prospecção de dados, apesar de constituir um passo fundamental na análise de dados provenientes de bases de dados. Para a descoberta de conhecimento, após a produção de uma tabela de dados desnormalizada, utilizam-se modelos de regressão linear múltipla e árvores de regressão segundo dois algoritmos distintos. Os resultados são comparados com o conhecimento de domínio paremiológico, com algumas conclusões inesperadas.ABSTRACT: For data management activities in a project for proverbial sentences identification, a data base has being assembled during several years. This data base collects, in the moment of this study, information about 25.000 idiomatic sentences, including more than one thousand valid answers for proverbial sentences recognition surveys. In this article a project is described with the purpose to extract knowledge from this data base, in order to better characterize the individuals participating in the surveys about their level of proverbial recognition and the influence of the locations they have been living. In order to reach the study objectives we use data mining methodologies including: data preparation and preprocessing, data cleansing, and data reduction techniques. This data preparation stage is carefully described because we believe this is sometimes forgotten in statistical data mining studies and is a fundamental step to attain any data mining study objective. For data analysis, after a denormalized file is produced, we use linear regression models and regression trees with two different algorithms. The descriptive results are compared with paremiology domain knowledge, with some unexpected conclusions

Application of Deep Learning methods to analysis of Imaging Atmospheric Cherenkov Telescopes data

Ground based gamma-ray observations with Imaging Atmospheric Cherenkov Telescopes (IACTs) play a significant role in the discovery of very high energy (E > 100 GeV) gamma-ray emitters. The analysis of IACT data demands a highly efficient background rejection technique, as well as methods to accurately determine the energy of the recorded gamma-ray and the position of its source in the sky. We present results for background rejection and signal direction reconstruction from first studies of a novel data analysis scheme for IACT measurements. The new analysis is based on a set of Convolutional Neural Networks (CNNs) applied to images from the four H.E.S.S. phase-I telescopes. As the H.E.S.S. cameras pixels are arranged in a hexagonal array, we demonstrate two ways to use such image data to train CNNs: by resampling the images to a square grid and by applying modified convolution kernels that conserve the hexagonal grid properties. The networks were trained on sets of Monte-Carlo simulated events and tested on both simulations and measured data from the H.E.S.S. array. A comparison between the CNN analysis to current state-of-the-art algorithms reveals a clear improvement in background rejection performance. When applied to H.E.S.S. observation data, the CNN direction reconstruction performs at a similar level as traditional methods. These results serve as a proof-of-concept for the application of CNNs to the analysis of events recorded by IACTs

Logical Analysis of Inconsistent Data (LAID) for a paremiologic study

15th Portuguese Conference on Artificial Inteligence - EPIA 2011. Lisboa, Faculdade de Ciências da Universidade de LisboaA paremiologic (study of proverbs) case is presented as a part of a wider project, based on data collected by thousands of interviews made to people from Azores, and involving a set of twenty-two thousand Portuguese proverbs, where we searched for the minimum information needed to identify the birthplace island of an interviewee. The concept of birthplace was extended for all respondents that have lived in any locations more than 5 years,unintentionally introducing inconsistencies in the data classification task. The rough sets differ from classical sets by their ability to deal with inconsistent data. A parallel approach to data reduction is given by the logical analysis of data (LAD). LAD handicaps, like the inability to cope with the contradiction and the limited number of classification classes, will be overcome in this version of Logical Analysis of Inconsistent Data (LAID)

Probing Convolutional Neural Networks for Event Reconstruction in {\gamma}-Ray Astronomy with Cherenkov Telescopes

A dramatic progress in the field of computer vision has been made in recent years by applying deep learning techniques. State-of-the-art performance in image recognition is thereby reached with Convolutional Neural Networks (CNNs). CNNs are a powerful class of artificial neural networks, characterized by requiring fewer connections and free parameters than traditional neural networks and exploiting spatial symmetries in the input data. Moreover, CNNs have the ability to automatically extract general characteristic features from data sets and create abstract data representations which can perform very robust predictions. This suggests that experiments using Cherenkov telescopes could harness these powerful machine learning algorithms to improve the analysis of particle-induced air-showers, where the properties of primary shower particles are reconstructed from shower images recorded by the telescopes. In this work, we present initial results of a CNN-based analysis for background rejection and shower reconstruction, utilizing simulation data from the H.E.S.S. experiment. We concentrate on supervised training methods and outline the influence of image sampling on the performance of the CNN-model predictions.Comment: 8 pages, 4 figures, Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Busan, Kore

Probing the momentum relaxation time of charge carriers in ultrathin semiconductor layers

We report on a terahertz time-domain technique for measuring the momentum relaxation time of charge carriers in ultrathin semiconductor layers. The phase sensitive modulation technique directly provides the relaxation time. Time-resolved THz experiments were performed on n-doped GaAs and show precise agreement with data obtained by electrical characterization. The technique is well suited for studying novel materials where parameters such as the charge carriers' effective mass or the carrier density are not known a priori

In-vitro-Untersuchung zur Korrelation von Präparationsdesign und klinischer Haltbarkeit CAD/CAM-gefertigter Zirkondioxidkronen

Das Ziel dieser In-vitro-Studie war es, die Bruchfestigkeit von Kronengerüsten aus Y-TZP-Zirkondioxid unter Berücksichtigung unterschiedlicher Präparationsgeometrien zu untersuchen. Die Prüfstümpfe aus einer CoCr-Legierung wurden hierzu mit fünf unterschiedlichen Präparationsformen versehen: Tangentiale Präparation, starke Hohlkehle, dezente Hohlkehle, Stufenpräparation und Stufenpräparation mit Abschrägung. Die Kronengerüste für die fünf unterschiedlichen Präparationsformen wurden über das CAD/CAM-Verfahren CerconÒ von DeguDent (Hanau) hergestellt. Insgesamt wurden für jede Präparationsfom 10 Prüfkäppchen gefräst und aufgepasst. Es wurde auf eine gleich bleibende Wandstärke der Zirkondioxidkäppchen von 0,4mm geachtet. Vor dem Bruchtest wurden die Gerüste mit Glasionomer-Zement unter Zuhilfenahme einer Zementiervorrichtung mit 50 N auf den Prüfstümpfen befestigt. In der Universalprüfmaschine wurde die Zirkondioxidkeramik bis zum Eintreten des Bruches belastet. Bei der anschließenden Auswertung der Ergebnisse stellte sich heraus, dass sich die Stufenpräparation mit einer mittleren Belastbarkeit von 2453 N signifikant von den übrigen Präparationsformen abhob. Trotzdem diese Präparationsform auch die größte Streuung mit einer Standardabweichung von ±628 N aufwies, blieb sie dennoch über den geforderten Belastungswerten. Die Tangentialpräparation ereichte einen Mittelwert von 1555 N, die starke Hohlkehle 1508 N, die dezente Hohlkehle m1430 N und die Stufenpräparation mit Abschrägung 1245 N. Als Ergebnis dieser Untersuchung stellte sich heraus, dass alle Präparationsformen die im Seitenzahnbereich geforderte minimale Bruchfestigkeit von 1000 N erreicht haben, wobei sich jedoch die Stufenpräparation noch signifikant nach oben hin absetzen konnte