Computationally efficient rule-based classification for continuous streaming data

Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

Automated identification of neural correlates of continuous variables

Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

Brain-computer music interfacing for continuous control of musical tempo

A Brain-computer music interface (BCMI) is developed to allow for continuous modification of the tempo of dynamically generated music. Six out of seven participants are able to control the BCMI at significant accuracies and their performance is observed to increase over time.

A comparative corpus-assisted discourse study of the representations of hosts in promotional tourism discourse

Most studies concerned with the representations of local people in tourism discourse point to the prevalence of stereotypic images asserting that contemporary tourism perpetuates colonial legacy and gendered discursive practices. This claim has been, to some extent, contested in research that explores representations of hosts in local tourism materials claiming that tourism can also discursively resist the dominant Western imagery. While the evidence for the existence of hegemonic and diverging discourses about the local ‘Other’ seems compelling, the empirical basis of this research is rather small and often limited to one geographic context. The present study addresses these shortcomings by examining representations of hosts in a larger corpus of promotional tourism materials including texts produced by Western and local tourism industries. The data is investigated using the methodology of Corpus-Assisted Discourse Studies (CADS). By comparing external with internal (self) representations, this study verifies and refines some of the claims on the subject and offers a much more nuanced picture of representations that defies the black and white scenarios proposed in previous research

Intersections and differentiations: a corpus-assisted discourse study of gender representations in the British press before, during and after the London Olympics 2012

This study examines the impact of a global sports event on gender representations in media reporting. Whereas previous research on gender, sport and media has been mainly concerned with sports events in the North American or Australian context, this study investigates the British media reporting before, during and after the London Olympics 2012. Our study follows the approach of Corpus-Assisted Discourse Studies (CADS) and uses both quantitative and qualitative research procedures. The results reveal more balanced gender representations during the London Olympics in that the ‘regular’ biased associations were supressed in favour of positive references to female achievements. However, little carry-though of the ‘gains’ was noted. Also, this study shows that the positive associations intersected with national sentiments and were used to celebrate the nation-state. At the same time, some subtle resistance was observed to accepting as ‘truly’ British the non-white athletes and those not born in Britain.

Shape-controlled continuous synthesis of metal nanostructures

A segmented flow-based microreactor is used for the continuous production of faceted nanocrystals. Flow segmentation is proposed as a versatile tool to manipulate the reduction kinetics and control the growth of faceted nanostructures; tuning the size and shape. Switching the gas from oxygen to carbon monoxide permits the adjustment in nanostructure growth from 1D (nanorods) to 2D (nanosheets). CO is a key factor in the formation of Pd nanosheets and Pt nanocubes; operating as a second phase, a reductant, and a capping agent. This combination confines the growth to specific structures. In addition, the segmented flow microfluidic reactor inherently has the ability to operate in a reproducible manner at elevated temperatures and pressures whilst confining potentially toxic reactants, such as CO, in nanoliter slugs. This continuous system successfully synthesised Pd nanorods with an aspect ratio of 6; thin palladium nanosheets with a thickness of 1.5 nm; and Pt nanocubes with a 5.6 nm edge length, all in a synthesis time as low as 150 s.

Order and disorder in fiction labyrinths: the librarians` representations in some contemporary cultural productions

This paper, first result of a larger research, proposes a query about some aspects of social representation of libraries and librarians, as they appear in literary and cinematographic productions. Little by little, this query, which arose from purposes of organizing catalogues, revealed elements that established different series, in which the narrative genre (literary or cinematographic) has no relevance to either libraries or librarians` representations. The presence of these elements seems to show some expectations and utopias in relation to the common knowledge, independently from narratives being located in the past, in the present or in the future, stimulating reflection on some medieval and baroque traditions about the library universe and its main characters, the librarians. The cinematographic material selected for research was The time machine, Farenheit 451, The day after tomorrow, Star Wars - episode II and the novels Martin Eden, The man without qualities, The time machine and La sombra del viento.

Note on ""Continuous matter creation and the acceleration of the universe: the growth of density fluctuations""

Recently, de Roany and Pacheco (Gen Relativ Gravit, doi:10.1007/s10714-010-1069-2) performed a Newtonian analysis on the evolution of perturbations for a class of relativistic cosmological models with Creation of Cold Dark Matter (CCDM) proposed by the present authors (Lima et al. in JCAP 1011:027, 2010). In this note we demonstrate that the basic equations adopted in their work do not recover the specific (unperturbed) CCDM model. Unlike to what happens in the original CCDM cosmology, their basic conclusions refer to a decelerating cosmological model in which there is no transition from a decelerating to an accelerating regime as required by SNe type Ia and complementary observations.

Cladistic analysis of continuous modularized traits provides phylogenetic signals in Homo evolution

Evolutionary novelties in the skeleton are usually expressed as changes in the timing of growth of features intrinsically integrated at different hierarchical levels of development(1). As a consequence, most of the shape- traits observed across species do vary quantitatively rather than qualitatively(2), in a multivariate space(3) and in a modularized way(4,5). Because most phylogenetic analyses normally use discrete, hypothetically independent characters(6), previous attempts have disregarded the phylogenetic signals potentially enclosed in the shape of morphological structures. When analysing low taxonomic levels, where most variation is quantitative in nature, solving basic requirements like the choice of characters and the capacity of using continuous, integrated traits is of crucial importance in recovering wider phylogenetic information. This is particularly relevant when analysing extinct lineages, where available data are limited to fossilized structures. Here we show that when continuous, multivariant and modularized characters are treated as such, cladistic analysis successfully solves relationships among main Homo taxa. Our attempt is based on a combination of cladistics, evolutionary- development- derived selection of characters, and geometric morphometrics methods. In contrast with previous cladistic analyses of hominid phylogeny, our method accounts for the quantitative nature of the traits, and respects their morphological integration patterns. Because complex phenotypes are observable across different taxonomic groups and are potentially informative about phylogenetic relationships, future analyses should point strongly to the incorporation of these types of trait.

Continuous and High-Level In Vivo Delivery of Endostatin From Recombinant Cells Encapsulated in TheraCyte (R) Immunoisolation Devices

Endostatin (ES) is a potent inhibitor of angiogenesis and tumor growth. Continuous ES delivery of ES improves the efficacy and potency of the antitumoral therapy. The TheraCyte (R) system is a polytetrafluoroethylene (PTFE) semipermeable membrane macroencapsulation system for implantation of genetically engineered cells specially designed for the in vivo delivery of therapeutic proteins, such as ES, which circumvents the problem of limited half-life and variation in circulating levels. In order to enable neovascularization at the tissues adjacent to the devices prior to ES secretion by the cells inside them, we designed a scheme in which empty TheraCyte (R) devices were preimplanted SC into immunodeficient mice. Only after healing (17 days later) were Chinese hamster ovary cells expressing ES injected into the preimplanted devices. In another model for device implantation, the cells expressing ES where loaded into the immunoisolation devices prior to implantation into the animals, and the TheraCyte (R) were then immediately implanted SC into the mice. Throughout the 2-month study, constant high ES levels of up to 3.7 mu g/ml were detected in the plasma of the mice preimplanted with the devices, while lower but also constant levels of ES (up to 2.1 mu g/ml plasma) were detected in the mice that had received devices preloaded with the ES-expressing cells. Immunohistochemistry using anti-ES antibody showed reaction within the device and outside it, demonstrating that ES, secreted by the confined recombinant cells, permeated through the membrane and reached the surrounding tissues.

THE POINCARE-BENDIXSON THEOREM ON THE KLEIN BOTTLE FOR CONTINUOUS VECTOR FIELDS

We present a version of the Poincare-Bendixson Theorem on the Klein bottle K(2) for continuous vector fields. As a consequence, we obtain the fact that K(2) does not admit continuous vector fields having a omega-recurrent injective trajectory.

THE IMPLICIT FUNCTION THEOREM FOR CONTINUOUS FUNCTIONS

In the present paper we obtain a new homological version of the implicit function theorem and some versions of the Darboux theorem. Such results are proved for continuous maps on topological manifolds. As a consequence. some versions of these classic theorems are proved when we consider differenciable (not necessarily C-1) maps.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.