Bus line trajectories classification using weightless neural networks

Geo-enabled devices are ubiquitous nowadays. Within a diversity of possible applications using the huge of amount data generated by this technology, our work focuses on a chronic problem of Rio de Janeiro city: its public bus system. This text presents a framework for GPS trajectories classification, whose focus is the identification of bus routes of a public bus system. In order to do that, it was used the lightweight and versatile WiSARD, a weightless neural network classifier. Different binarization methods were used to adapt raw data to WiSARD’s binary input, making use of a set of rules defined by the application domain. Yet, it is evaluated a way of combining WiSARD through decision directed acyclic graphs. All these approachs result in different flavors of a neuro-symbolic learning system. The framework was tested against a vast data set created from open access and real-time data acquired from the current bus system of Rio de Janeiro city. Results obtained suggest the applicability of the proposed solution in a classification problem with more than 500 classes. Comparisons made also indicate an equivalent performance of WiSARD and other state-of-art and widely used machine learning methods. In addition, the framework described here is believed to be adaptable to other application domains.Dispositivos com localização espacial estão em toda parte hoje em dia. Dentre várias possíveis aplicações com a grande quantidade de dados gerada por esse tipo de equipamento, nosso trabalho foca em um problema crônico da cidade do Rio de Janeiro: seu sistema público de ônibus. Apresenta-se neste texto uma arquitetura para classificação de trajetórias GPS, cujo foco é a identificação de rotas de ônibus do sistema público. Para isso, utilizamos o leve e versátil classificador baseado em redes neurais sem peso WiSARD. Para a geração da entrada da rede, experimentamos diferentes formas de binarização, fazendo uso de regras definidas pelo problema. Ainda, avaliamos uma forma de combinação das redes WiSARD com o uso de um grafo acíclico de decisões. Todas essas propostas resultam em diferentes sabores de um sistema de aprendizado neurossimbólico. Tal arquitetura foi testada contra um vasto conjunto de dados construído a partir de dados fornecido em tempo real e de forma pública pelo sistema corrente da cidade do Rio de Janeiro. Os resultados obtidos indicam a aplicabilidade da solução proposta em um problema de classificação envolvendo mais de 500 classes. As comparações efetuadas indicam uma equiparação do modelo WiSARD com outros modelos em estado da arte. No mais, acreditamos que a metodologia aqui descrita possa ser utilizada com sucesso em outros domínios

Development of Plant Extract-Based Composite Fibers and Aerogels

The aim of this study is to use the solid templating process of pullulan nanofibers in order to produce biocompatible, biodegradable, and antibacterial aerogels. The developed aerogels were produced using cross-linked pullulan nanofibers, which provide a water-stable structure allowing them to be used as wound dressing material. The morphology, thermal properties, water solubility, and thermal and physical properties of the nanofibers and aerogels were characterized. Furthermore, the antibacterial effect against gram-negative bacteria, Escherichia coli, and the biocompatibility using mouse embryonic fibroblasts (NIH 3T3) were investigated

Directed cycles and related structures in random graphs: II--Dynamic properties

We study directed random graphs (random graphs whose edges are directed) as they evolve in discrete time by the addition of nodes and edges. For two distinct evolution strategies, one that forces the graph to a condition of near acyclicity at all times and another that allows the appearance of nontrivial directed cycles, we provide analytic and simulation results related to the distributions of degrees. Within the latter strategy, in particular, we investigate the appearance and behavior of the strong components that were our subject in the first part of this study.Comment: submitted to Physica

Early appraisal of the fixation probability in directed networks

In evolutionary dynamics, the probability that a mutation spreads through the whole population, having arisen in a single individual, is known as the fixation probability. In general, it is not possible to find the fixation probability analytically given the mutant's fitness and the topological constraints that govern the spread of the mutation, so one resorts to simulations instead. Depending on the topology in use, a great number of evolutionary steps may be needed in each of the simulation events, particularly in those that end with the population containing mutants only. We introduce two techniques to accelerate the determination of the fixation probability. The first one skips all evolutionary steps in which the number of mutants does not change and thereby reduces the number of steps per simulation event considerably. This technique is computationally advantageous for some of the so-called layered networks. The second technique, which is not restricted to layered networks, consists of aborting any simulation event in which the number of mutants has grown beyond a certain threshold value, and counting that event as having led to a total spread of the mutation. For large populations, and regardless of the network's topology, we demonstrate, both analytically and by means of simulations, that using a threshold of about 100 mutants leads to an estimate of the fixation probability that deviates in no significant way from that obtained from the full-fledged simulations. We have observed speedups of two orders of magnitude for layered networks with 10000 nodes

Modelos de Maturidade em um Cenário Educacional: Um Mapeamento Sistemático

Este paper apresenta um mapeamento sistemático em modelos de maturidade educacionais, almejando identificar e reunir as suas principais características, inspirações e métodos de desenvolvimento. Foram identificados 22 modelos de maturidade educacionais, divididos em 25 estudos. Os resultados apontam que CMM, CMMI e SPICE são as inspirações mais comuns para os modelos educacionais existentes. Também foi constatado que estudos literários, pilot testing, workshops e surveys foram os métodos mais comuns utilizados para desenvolver tais modelos. Finalmente, não foi possível encontrar nenhum estudo especificamente relacionado a modelos de maturidade para recursos educacionais abertos, destacando uma lacuna na área que pode ser apurada em trabalhos futuros