Theoretical results on a weightless neural classifier and application to computational linguistics

WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado.WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado

The Value of Private Schools: Evidence from Pakistan

Using unique data from Pakistan we estimate a model of demand for differentiated products in 112 rural education markets with significant choice among public and private schools. Families are willing to pay substantially for reductions in distance to school, but in contrast, price elasticities are low. Using the demand estimates, we show that the existence of a low fee private school market is of great value for households in our sample, reaching 2% to 7% of annual per capita expenditure for those choosing private schools

Whose Emotion Matters? Speaking Activity Localisation without Prior Knowledge

The task of emotion recognition in conversations (ERC) benefits from the availability of multiple modalities, as provided, for example, in the video-based Multimodal EmotionLines Dataset (MELD). However, only a few research approaches use both acoustic and visual information from the MELD videos. There are two reasons for this: First, label-to-video alignments in MELD are noisy, making those videos an unreliable source of emotional speech data. Second, conversations can involve several people in the same scene, which requires the localisation of the utterance source. In this paper, we introduce MELD with Fixed Audiovisual Information via Realignment (MELD-FAIR) by using recent active speaker detection and automatic speech recognition models, we are able to realign the videos of MELD and capture the facial expressions from speakers in 96.92% of the utterances provided in MELD. Experiments with a self-supervised voice recognition model indicate that the realigned MELD-FAIR videos more closely match the transcribed utterances given in the MELD dataset. Finally, we devise a model for emotion recognition in conversations trained on the realigned MELD-FAIR videos, which outperforms state-of-the-art models for ERC based on vision alone. This indicates that localising the source of speaking activities is indeed effective for extracting facial expressions from the uttering speakers and that faces provide more informative visual cues than the visual features state-of-the-art models have been using so far. The MELD-FAIR realignment data, and the code of the realignment procedure and of the emotional recognition, are available at https://github.com/knowledgetechnologyuhh/MELD-FAIR.Comment: 17 pages, 8 figures, 7 tables, Published in Neurocomputin

Please call me John: name choice and the assimilation of immigrants in the United States, 1900–1930

The majority of immigrants to the United States at the beginning of the 20th century adopted American first names. In this paper we study the economic determinants of name choice, by relating the propensity of immigrants to carry an American first name to the local concentration of their compatriots and local labor market conditions. We find that high concentrations of immigrants of a given nationality discouraged members of that nationality from taking American names, in particular for more recent arrivals. In contrast, labor market conditions for immigrants do not seem to be associated with more frequent name changes among immigrants.info:eu-repo/semantics/publishedVersio

BakSIM : an application for control, monitoring and simulation of baker's yeast fermentation process

This paper describes an experience based on the final project work for the Industrial Electronics Engineering undergraduate course. The main goal was the development of an application for the simulation and monitorization of the baker’s yeast fermentation. The BakSIM application simulates a Mini-Bioreactor for the control, monitorization and simulation of the process running in open and closed loop modes. It permits to make the acquisition of the most important system variables: biomass, ethanol, oxygen, glucose and dioxide of carbon, and the writing in files for future analysis and for future contrast with previous experiences. Different modules were considered: simulation, monitorization and simulation and monitorization. The BakSIM application also allows not only the comparison of the experimental data with the simulated data as the study of the effectiveness of several numerical methods. One more advantage of this project was its multidisciplinary work, enclosing several areas covered during the undergraduate course, namely Programming, Process Control and Numerical Methods.Centre ALGORITMI

Vibration damping and acoustic behavior of PU-filled non-stochastic aluminum cellular solids

Aluminum-based cellular solids are promising lightweight structural materials considering their high specific strength and vibration damping, being potential candidates for future railway vehicles with enhanced riding comfort and low fuel consumption. The filling of these lattices with polymer-based (i.e., polyurethane) foams may further improve the overall vibration/noise-damping without significantly increasing their density. This study explores the dynamic (i.e., frequency response) and acoustic properties of unfilled and polyurethane-filled aluminum cellular solids to characterize their behavior and explore their benefits in terms of vibration and noise-damping. It is shown that polyurethane filling can increase the vibration damping and transmission loss, especially if the infiltration process uses flexible foams. Considering sound reflection, however, it is shown that polyurethane filled samples (0.27–0.30 at 300 Hz) tend to display lower values of sound absorption coefficient relatively to unfilled samples (0.75 at 600 Hz), is this attributed to a reduction in overall porosity, tortuosity and flow resistivity. Foam-filled samples (43–44 dB at 700–1200 Hz) were shown to be more suitable to reduce sound transmission rather than reflection than unfilled samples (21 dB at 700 Hz). It was shown that the morphology of these cellular solids might be optimized depending on the desired application: (i) unfilled aluminum cellular solids are appropriate to mitigate internal noises due to their high sound absorption coefficient; and (ii) PU filled cellular solids are appropriate to prevent exterior noises and vibration damping due to their high transmission loss in a wide range of frequencies and vibration damping.This work was supported by Fundação para a Ciência e a Tecnologia FCT under the research Doctoral Grant PD/BD/114096/2015, project UIDP/04077/2020 and UIDB/04436/2020, and Stimulus of Scientific Employment Application CEECIND/03991/2017

Significance of cell number on the bulk elastic properties of auxetic reentrant lattices

Auxetics are characterized by a negative Poisson’s ratio, expanding/contracting in tension/compression. Given this behavior, they are expected topossess high shear, fracture and indentation resistance, and superior damping. The lack of natural isotropic auxetics promoted an effort to designstructures that mimic this behavior, e.g. reentrant model. This last is based on honeycombs with inverted protruding ribs. Commonly, this modelis employed in lattices and has been thoroughly studied in terms of mechanical properties and deformation behavior. Given that the amount ofcells has an influence in the overall internal structural behavior, there seems to be an absence of data that determines the minimum number of cellsfor such structure to present internal static bulk properties. Recurring to FEA, this study determines the minimum number of cells to obtain anoverall face constrained auxetic lattice with internal bulk elastic behavior, namely in terms of normalized Young’s modulus and Poisson’s ratio. Itis shown that adding reentrant cells increases the Poisson’s ratio on an exponential rise to maximum function, reducing the normalized Young’smodulus on an exponential decay function. Fundamentally, a minimum number of 13 cells per row to obtain an internal bulk behavior in latticeswith constrained faces.Supported by the project iRAIL Innovation in Railway Systems and Technologies Doctoral Programme funds and by national funds through FCT – Portuguese Foundation for Science and Technology and was developed on the aim of the Doctoral grant PD/BD/114096/2015