Personal, musical and social benefits of singing in a community ensemble: three case studies in Melbourne (Australia)

Australia has a diverse, multilayered society that reflects its rich musical life. There are many community choirs formed by various cultural and linguistically diverse groups. This article is part of an ongoing project, Well-being and ageing: community, diversity and the arts (since 2008), undertaken by Deakin University and Monash University, that explores the cultural diversity within Australian society and how active music engagement fosters well-being. The singing groups selected for this discussion are the Skylarkers, the Bosnian Behar Choir, and the Coro Furlan. The Skylarkers and the Bosnian Behar Choir are mixed groups who respectively perform popular music from their generation and celebrate their culture through music. The Coro Furlan is an Italian male choir who understand themselves as custodians of their heritage. In these interpretative, qualitative case studies semi-structured interviews were undertaken and analyzed using Interpretative Phenomenological Analysis. In this approach there is an exploration of participants’ understanding of their lived experiences. The analysis of the combined data identified musical and social benefits that contribute to participants’ sense of individual well-being. Musical benefits occurred through sharing, learning and singing together. Social benefits included opportunities to build friendships, overcome isolation and gain a sense of validation. Many found that singing enhanced their health and happiness. Active music making in community choirs and music ensembles continues to be an effective way to support individuals, build community, and share culture and heritage.

Iterative construction of hierarchical classifiers for phishing website detection

This article is devoted to a new iterative construction of hierarchical classifiers in SimpleCLI for the detection of phishing websites. Our new construction of hierarchical systems creates ensembles of ensembles in SimpleCLI by iteratively linking a top-level ensemble to another middle-level ensemble instead of a base classifier so that the top-level ensemble can generate a large multilevel system. This new construction makes it easy to set up and run such large systems in SimpleCLI. The present article concentrates on the investigation of performance of the iterative construction of such classifiers for the example of detection of phishing websites. We carried out systematic experiments evaluating several essential ensemble techniques as well as more recent approaches and studying their performance as parts of the iterative construction of hierarchical classifiers. The results presented here demonstrate that the iterative construction of hierarchical classifiers performed better than the base classifiers and standard ensembles. This example of application to the classification of phishing websites shows that the new iterative construction combining diverse ensemble techniques into the iterative construction of hierarchical classifiers can be applied to increase the performance in situations where data can be processed on a large computer. © 2014 ACADEMY PUBLISHER.

Cultural pedagogies in the museum: walking, listening and feeling

Pedagogy is often glossed as the ‘art and science of teaching’ but this focus typically ties it to the instructional practices of formalised schooling. Like the emerging work on ‘public pedagogies’, the notion of cultural pedagogies signals the importance of the pedagogic in realms other than institutionalised education, but goes beyond the notion of public pedagogies in two ways: it includes spaces which are not so public, and it includes an emphasis on material and non-human actors. This collection foregrounds this broader understanding of pedagogy by framing enquiry through a series of questions and across a range of settings. How, for example, are the processes of ‘teaching’ and ‘learning’ realised within and across the pedagogic processes specific to various social sites? What ensembles of people, things and practices are brought together in specific institutional and everyday settings to accomplish these processes? This collection brings together researchers whose work across the interdisciplinary nexus of cultural studies, sociology, media studies, education and museology offers significant insights into these ‘cultural pedagogies’ – the practices and relations through which cumulative changes in how we act, feel and think occur. Cultural Pedagogies and Human Conduct opens up debate across disciplines, theoretical perspectives and empirical foci to explore both what is pedagogical about culture and what is cultural about pedagogy.

Intelligent facial emotion recognition using a layered encoding cascade optimization model

In this research, we propose a facial expression recognition system with a layered encoding cascade optimization model. Since generating an effective facial representation is a vital step to the success of facial emotion recognition, a modified Local Gabor Binary Pattern operator is first employed to derive a refined initial face representation and we then propose two evolutionary algorithms for feature optimization including (i) direct similarity and (ii) Pareto-based feature selection, under the layered cascade model. The direct similarity feature selection considers characteristics within the same emotion category that give the minimum within-class variation while the Pareto-based feature optimization focuses on features that best represent each expression category and at the same time provide the most distinctions to other expressions. Both a neural network and an ensemble classifier with weighted majority vote are implemented for the recognition of seven expressions based on the selected optimized features. The ensemble model also automatically updates itself with the most recent concepts in the data. Evaluated with the Cohn-Kanade database, our system achieves the best accuracies when the ensemble classifier is applied, and outperforms other research reported in the literature with 96.8% for direct similarity based optimization and 97.4% for the Pareto-based feature selection. Cross-database evaluation with frontal images from the MMI database has also been conducted to further prove system efficiency where it achieves 97.5% for Pareto-based approach and 90.7% for direct similarity-based feature selection and outperforms related research for MMI. When evaluated with 90° side-view images extracted from the videos of the MMI database, the system achieves superior performances with >80% accuracies for both optimization algorithms. Experiments with other weighting and meta-learning combination methods for the construction of ensembles are also explored with our proposed ensemble showing great adpativity to new test data stream for cross-database evaluation. In future work, we aim to incorporate other filtering techniques and evolutionary algorithms into the optimization models to further enhance the recognition performance.

Improving the quality of prediction intervals through optimal aggregation

Neural networks (NNs) are an effective tool to model nonlinear systems. However, their forecasting performance significantly drops in the presence of process uncertainties and disturbances. NN-based prediction intervals (PIs) offer an alternative solution to appropriately quantify uncertainties and disturbances associated with point forecasts. In this paper, an NN ensemble procedure is proposed to construct quality PIs. A recently developed lower-upper bound estimation method is applied to develop NN-based PIs. Then, constructed PIs from the NN ensemble members are combined using a weighted averaging mechanism. Simulated annealing and a genetic algorithm are used to optimally adjust the weights for the aggregation mechanism. The proposed method is examined for three different case studies. Simulation results reveal that the proposed method improves the average PI quality of individual NNs by 22%, 18%, and 78% for the first, second, and third case studies, respectively. The simulation study also demonstrates that a 3%-4% improvement in the quality of PIs can be achieved using the proposed method compared to the simple averaging aggregation method.

Examining performance of aggregation algorithms for neural network-based electricity demand forecasting

The aim of this research is to examine the efficiency of different aggregation algorithms to the forecasts obtained from individual neural network (NN) models in an ensemble. In this study an ensemble of 100 NN models are constructed with a heterogeneous architecture. The outputs from NN models are combined by three different aggregation algorithms. These aggregation algorithms comprise of a simple average, trimmed mean, and a Bayesian model averaging. These methods are utilized with certain modifications and are employed on the forecasts obtained from all individual NN models. The output of the aggregation algorithms is analyzed and compared with the individual NN models used in NN ensemble and with a Naive approach. Thirty-minutes interval electricity demand data from Australian Energy Market Operator (AEMO) and the New York Independent System Operator's web site (NYISO) are used in the empirical analysis. It is observed that the aggregation algorithm perform better than many of the individual NN models. In comparison with the Naive approach, the aggregation algorithms exhibit somewhat better forecasting performance.

Testing the transferability of a coarse-grained model to intrinsically disordered proteins

The intermediate-resolution coarse-grained protein model PLUM [T. Bereau and M. Deserno, J. Chem. Phys., 2009, 130, 235106] is used to simulate small systems of intrinsically disordered proteins involved in biomineralisation. With minor adjustments to reduce bias toward stable secondary structure, the model generates conformational ensembles conforming to structural predictions from atomistic simulation. Without additional structural information as input, the model distinguishes regions of the chain by predicted degree of disorder, manifestation of structure, and involvement in chain dimerisation. The model is also able to distinguish dimerisation behaviour between one intrinsically disordered peptide and a closely related mutant. We contrast this against the poor ability of PLUM to model the S1 quartz-binding peptide.

A clustering-based multi-layer distributed ensemble for neurological diagnostics in cloud services

This paper investigates the problem of minimizing data transfer between different data centers of the cloud during the neurological diagnostics of cardiac autonomic neuropathy (CAN). This problem has never been considered in the literature before. All classifiers considered for the diagnostics of CAN previously assume complete access to all data, which would lead to enormous burden of data transfer during training if such classifiers were deployed in the cloud. We introduce a new model of clustering-based multi-layer distributed ensembles (CBMLDE). It is designed to eliminate the need to transfer data between different data centers for training of the classifiers. We conducted experiments utilizing a dataset derived from an extensive DiScRi database. Our comprehensive tests have determined the best combinations of options for setting up CBMLDE classifiers. The results demonstrate that CBMLDE classifiers not only completely eliminate the need in patient data transfer, but also have significantly outperformed all base classifiers and simpler counterpart models in all cloud frameworks.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Aspects de la syntaxe, de la semantique et de la morphologie des verbes a trait de /complexite/

Cette dissertation porte sur l’analyse syntactico-sémantique des verbes à trait de complexité. Le trait de complexité (Blanche-Benveniste et al. 1984) réunit une classe de verbes connue comme verbes ‘symétriques’, ‘réciproques’ ou ‘collectifs’ sans toutefois se limiter à ces ensembles (cf. grouiller, collectionner, amonceler, scinder, etc.). Ce trait induit une lecture ‘plurielle’ à l’entité formée du lexème verbal et de ses arguments et qui se traduit, sur le plan morphosyntaxique, par deux propriétés: sélection obligatoire d’une position syntaxique (sujet ou objet) au pluriel; en absence de ce pluriel morphologique, le trait de complexité se réalise par la sélection d’un complément prépositionnel correlié à une position syntaxique (sujet ou objet) et l’interprétation de ‘pluriel’ des deux éléments correliés. L’hypothèse générale, et point de départ de cette dissertation, consiste à préciser l’interprétation de ‘pluralité inhérente’ des verbes à trait de complexité comme étant de type ‘collectif’, défini comme désignant du ‘plus d’un en un’ (Jespersen, 1971). La notion de ‘collectif’ est à distinguer de la notion de ‘pluriel’ (Gillon, 1992) et permet d’expliquer le lien entre les deux propriétés morphosyntaxiques présentées. Cette hypothèse générale s’appuie sur la sélection d’un ensemble d’outils d’analyse. Un premier outil vise à rendre compte, du point de vue formel, des réseaux syntactico-sémantiques, par une représentation abstraite de la syntaxe verbale, conçue comme une ‘syntaxe de position’ et où sont délimitées, autour du noyau verbal, deux zones syntaxiques (zone SUJET et zone OBJET) constituées de points d’ancrage du trait de complexité. En tenant compte de la spécificité du ‘collectif’ par rapport à la ‘pluralité’, le recours au concept d’opérateurs de complexité, entendus comme des opérateurs du trait [+discret] (Doetjes, 1999), permet de mieux définir la notion du ‘collectif’ appliquée au domaine verbal. Les différents opérateurs – affixes dérivationnels, constructions prépositionnelles, constructions en SE - se situent à différents niveaux de structuration. L’analyse par ‘opérateurs de complexité’ ([+discret]) présuppose également la prise en compte de la fonction quantitative. Dans cette perspective, ces opérateurs induisent différents degrés de l‘individuation’ des constituants du ‘collectif’ dénoté par la sémantique des verbes à trait de complexité. Les échelles de gradation de [+discret] rendent compte de cette propriété. Les valeurs de ‘plus d’un’ et ‘en un’ dénotées par les expressions verbales à trait de complexité sont interprétées comme faisant partie d’une structure conceptuelle de type ‘tout-intégré’ d’après l’approche lexicale et multidimensionnelle de la sémantique conceptuelle des relations parties/tout de Moltmann (1997).

Implementação de classificador de tarefas mentais baseado em EEG

BARBOSA, André F. ; SOUZA, Bryan C. ; PEREIRA JUNIOR, Antônio ; MEDEIROS, Adelardo A. D.de, . Implementação de Classificador de Tarefas Mentais Baseado em EEG. In: CONGRESSO BRASILEIRO DE REDES NEURAIS, 9., 2009, Ouro Preto, MG. Anais... Ouro Preto, MG, 2009

An investigation of Hebbian phase sequences as assembly graphs

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition.

Projeto em Áreas Consolidadas de Patrimônio Cultural: Propostas para a Construção de uma Metodologia de Ensino

Le thème du patrimoine culturel architectural et urbain continue d avoir une place importante dans le milieu technique et scientifique. Le concept s est élargi et aujourd hui comprend différentes procédures de projets d intervention. L importance accordée au thème amène à l inclusion de la matière de techniques rétrospectives et aux contenus qui en sont liés: conservation, restauration, restructuration et reconstruction d édifices et ensembles urbains, dans les parcours des cours d architecture et d urbanisme au Brésil établies par le Ministère de l Education Nationale (MEC) dans les années quatre-vingt-dix, postérieurement incorporés dans les directrices disciplinaires nationales. Nous partons des discussions théoriques et conceptuelles du Domaine du Patrimoine Culturel, ainsi que des principales théories pédagogiques d enseignements et d apprentissage articulées au projet. Dans ce contexte les objectifs principaux de cette thèse consistent à systématiser et à analyser les principales procédures méthodologiques contribuant pour la construction de méthodes d enseignement tournée vers des activités pratiques dans ce domaine. Pour cela, la recherche a été systématisée dans une approche à deux niveaux. En ce qui concerne le premier, basé sur des données secondaires, neuf cours d architecture et urbanisme ont étés identifiés entre institutions publiques d enseignement supérieur dont huit brésiliennes et une française, considérées représentatives en ce qui concerne les pratiques d enseignement de projet et de patrimoine culturel. Trente disciplines dédiées à la matière ont été également reconnues initialement, et postérieurement, cinq disciplines qui possèdent un emploi du temps dédié à la pratique de projet ont aussi été reconnues. Dans le deuxième cas, basée sur des données primaires, ont étés analysées les méthodologies et les stratégies d enseignement de projet basées sur les définitions des matières et des autres éléments des plans de travail avec des observations, des entrevues et des questionnaires en trois ateliers. Par rapport aux résultats nous avons constaté que toutes les écoles possèdent les contenus de la matière, mais peu d entre elles privilégient la relation du projet appliqué au patrimoine culturel. Nous avons constaté que les questions des projets dans ce contexte, même s elles sont considérées complexes, ont privilégié le listage et l analyse du site. L atelier qui intègre les fondements des théories de préservation, l histoire de l architecture et urbanisme et techniques anciennes et actuelles, est mis en valeur comme un modèle cohérent avec les propositions d intégration des connaissances théoriques et pratiques du projet appliqué à la discipline. Basé sur ces constatations il est possible de démontrer quatre étapes du projet appliqué au patrimoine culturel: 1ª) les fondements généraux qui concernent les bases théoriques sur la préservation, histoire et technique rétrospective, par exemple, l appropriation de lois et normes et la sensibilisation de l élève sur les questions de patrimoine culturel; 2ª) le contacte avec la réalité qui inclut l appropriation du problème à partir de ces acteurs, de ces échelles, de cette lecture de site et l analyse de l objet d étude; 3ª) le développement de la proposition qui inclut programmes (fonctions existantes et propositions), définitions du partit (types d intervention), conception (hypothèse et discussion) et définition de proposition; 4ª) la finalisation du projet qui consiste à développer la proposition avec sa représentation graphique et sa présentation finale. Nous concluons que le projet en Domaine du Patrimoine Culturel demande une attention spéciale et doit être présent dans les cursus considérant les principes généraux nécessaires à la formation de l élève. Le binôme projet / patrimoine signifie avoir dans le cursus universitaire les contenus et questions nécessaires les connaissances, les variables et possibilités existantes dans le projet appliqué au patrimoine culturel de façon à ce que ces connaissances soient incorporées dans l exercice de projet et n apparaissent pas comme un simple contenu théorique sans articulation avec la pratique. Naturellement ces conclusions n épuisent pas la réflexion sur la question. Nous espérons que les analyses faites contribuent à définir des méthodologies d enseignements capables d êtres vérifiées et testées dans la pratique en salle de cours, et puisse collaborer avec les nouvelles recherches surtout celles qui ont pour but des nouvelles théories pédagogiques d enseignement apprentissage du projet en Domaine du Patrimoine Culturel

Interesses da habitação social : políticas e processos no Rio Grande do Norte

En 2003, le gouvernement brésilien (gestion Lula) a initié une nouvelle phase dans son histoire de l habitation, en intensifiant les constructions de logements sociaux au Brésil. Un tel accroissement a eut des répercussions tant en ville comme à la campagne, et fût marqué dans le Rio Grande do Norte, par la production a grande échelle d ensembles d habitations, dans les programmes de Gouvernement. Afin de viabiliser ces transformations, des instruments politiques, financiers et de gestion ont étés articulés conjointement, utilisant la répétition d une typologie d édification, comme modèle, accompagnée de la reproduction d une morphologie dans les constructions de logements sociaux. Afin de comprendre ce processus nous introduisons une recherche urbanistique et socio-économique du problème du logement social au Brésil, en cherchant à mettre en relation les aspects techniques avec les questions historique, professionnelles et culturelles, éléments complémentaires. Notre analyse cherche a identifier comment les politiques de gestion et financement officielles (administrées dans sa grande majorité par la Caisse Économique Fédérale -CEF-), influencent le processus de conception de projets, en provoquant les répétitions de type/morphologiques, déjà citées. Basée sur l observation directe au cour de deux expériences différenciées pour du logement social en milieu rural, au Rio Grande do Norte, nous montrerons aussi certaines limitations et possibilités des acteurs sociaux, face aux agents et politiques officielles pour le logement social au Brésil, proposant des solutions alternatives standardisées qui caractérisent le résultat des projets financées et gérés par la CEF. Nos principales références théoriques et méthodologiques sont Nabil Bonduki (1998), David Harvey (2009,1982), Henry Lefèbvre (1970), Ermínia Maricato (2010, 2009, 2000, 1987) et Raquel Rolnik (2010, 2009, 2008, 1997)

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification