Validating the reported random errors of ACE‐FTS measurements

In order to validate the reported precision of space‐based atmospheric composition measurements, validation studies often focus on measurements in the tropical stratosphere, where natural variability is weak. The scatter in tropical measurements can then be used as an upper limit on single‐profile measurement precision. Here we introduce a method of quantifying the scatter of tropical measurements which aims to minimize the effects of short‐term atmospheric variability while maintaining large enough sample sizes that the results can be taken as representative of the full data set. We apply this technique to measurements of O3, HNO3, CO, H2O, NO, NO2, N2O, CH4, CCl2F2, and CCl3F produced by the Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE‐FTS). Tropical scatter in the ACE‐FTS retrievals is found to be consistent with the reported random errors (RREs) for H2O and CO at altitudes above 20 km, validating the RREs for these measurements. Tropical scatter in measurements of NO, NO2, CCl2F2, and CCl3F is roughly consistent with the RREs as long as the effect of outliers in the data set is reduced through the use of robust statistics. The scatter in measurements of O3, HNO3, CH4, and N2O in the stratosphere, while larger than the RREs, is shown to be consistent with the variability simulated in the Canadian Middle Atmosphere Model. This result implies that, for these species, stratospheric measurement scatter is dominated by natural variability, not random error, which provides added confidence in the scientific value of single‐profile measurements.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

Back to the margins in search of the core: "Foreign Land"'s geography of exclusion

The crisis of the national project in the early 1990s, caused by a short-lived but disastrous government, led Brazilian art cinema, for the first time, to look at itself as periphery and re-approach the old colonial center, Portugal. Terra estrangeira/Foreign Land (Walter Salles & Daniela Thomas, Brazil/Portugal, 1995), a film about Brazilian exiles in Portugal, is the best illustration of this perspective shift which provides a new sense of Brazil’s scale and position within a global context. Shot mainly on location in São Paulo, Lisbon and Cape Verde, it promotes the encounter of Lusophone peoples who find a common ground in their marginal situation. Rather than as a former empire, Portugal is defined by its situation at the edge of Europe and by beliefs such as Sebastianism, whose origins go back to the time when the country was dominated by Spain. As a result, notions of “core” or “center” are devolved to the realm of myth. The film’s carefully crafted dialogue combines Brazilian, Portuguese and Creole linguistic peculiarities into a common dialect of exclusion, while language puns trigger visual rhymes which refer back to the Cinema Novo (the Brazilian New Wave) repertoire and restage the imaginary of the discovery turned into unfulfilled utopia. The main characters also acquire historical resonances, as they are depicted as descendants of Iberian conquistadors turned into smugglers of precious stones in the present. Their activities define a circuit of international exchange which resonates with that of globalized cinema, a realm in which Foreign Land, made up of citations and homage to other cinemas, tries to retrieve a sense of belonging.

Entity-based semantic search on conversational transcripts semantic

This paper describes the implementation of a semantic web search engine on conversation styled transcripts. Our choice of data is Hansard, a publicly available conversation style transcript of parliamentary debates. The current search engine implementation on Hansard is limited to running search queries based on keywords or phrases hence lacks the ability to make semantic inferences from user queries. By making use of knowledge such as the relationship between members of parliament, constituencies, terms of office, as well as topics of debates the search results can be improved in terms of both relevance and coverage. Our contribution is not algorithmic instead we describe how we exploit a collection of external data sources, ontologies, semantic web vocabularies and named entity extraction in the analysis of underlying semantics of user queries as well as the semantic enrichment of the search index thereby improving the quality of results.

Back to the margins in search of the core: foreign land's geography of exclusion

The crisis of the national project in the early 1990s, caused by a short-lived but disastrous government, led Brazilian art cinema, for the first time, to look at itself as periphery and re-approach the old colonial centre, Portugal. Terra estrangeira/Foreign Land (Walter Salles & Daniela Thomas, Brazil/Portugal, 1995), a film about Brazilian exiles in Portugal, is the best illustration of this perspective shift aimed at providing a new sense of Brazil’s scale and position within a global context. Shot mainly on location in São Paulo, Lisbon and Cape Verde, it promotes the encounter of Lusophone peoples who find a common ground in their marginal situation. Even Portugal is defined by its location at the edge of Europe and by beliefs such as Sebastianism, whose origins go back to the time when the country was dominated by Spain. As a result, notions of ‘core’ or ‘centre’ are devolved to the realm of myth. The film’s carefully crafted dialogues combine Brazilian, Portuguese and Creole linguistic peculiarities into a common dialect of exclusion, while language puns trigger visual rhymes which refer back to the Cinema Novo (the Brazilian New Wave) repertoire and restage the imaginary of the discovery turned into unfulfilled utopia. The main characters also acquire historical resonances, as they are depicted as descendants of Iberian conquistadors turned into smugglers of precious stones in the present. Their activities define a circuit of international exchange which resonates with that of globalized cinema, a realm in which Foreign Land, made up of citations and homage to other cinemas, tries to retrieve a sense of belonging.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Sparse polynomial approximation in positive order Sobolev spaces with bounded mixed derivatives and applications to elliptic problems with random loading

In the present paper we study the approximation of functions with bounded mixed derivatives by sparse tensor product polynomials in positive order tensor product Sobolev spaces. We introduce a new sparse polynomial approximation operator which exhibits optimal convergence properties in L2 and tensorized View the MathML source simultaneously on a standard k-dimensional cube. In the special case k=2 the suggested approximation operator is also optimal in L2 and tensorized H1 (without essential boundary conditions). This allows to construct an optimal sparse p-version FEM with sparse piecewise continuous polynomial splines, reducing the number of unknowns from O(p2), needed for the full tensor product computation, to View the MathML source, required for the suggested sparse technique, preserving the same optimal convergence rate in terms of p. We apply this result to an elliptic differential equation and an elliptic integral equation with random loading and compute the covariances of the solutions with View the MathML source unknowns. Several numerical examples support the theoretical estimates.

On the evolution of monopoly pricing in Internet-assisted search markets

This study examines the evolution of prices in markets with Internet price-comparison search engines. The empirical study analyzes laboratory data of prices available to informed consumers, for two industry sizes and two conditions on the sample (complete and incomplete). Distributions are typically bimodal. One of the two modes of distribution, corresponding to monopoly pricing, tends to attract such pricing strategies increasingly over time. The second one, corresponding to interior pricing, follows a decreasing trend. Monopoly pricing can serve as a means of insurance against more competitive (but riskier) behavior. In fact, experimental subjects who initially earn low profits due to interior pricing are more likely to switch to monopoly pricing than subjects who experience good returns from the start.

On the spectra and pseudospectra of a class of non-self-adjoint random matrices and operators

In this paper we develop and apply methods for the spectral analysis of non-selfadjoint tridiagonal infinite and finite random matrices, and for the spectral analysis of analogous deterministic matrices which are pseudo-ergodic in the sense of E. B. Davies (Commun. Math. Phys. 216 (2001), 687–704). As a major application to illustrate our methods we focus on the “hopping sign model” introduced by J. Feinberg and A. Zee (Phys. Rev. E 59 (1999), 6433–6443), in which the main objects of study are random tridiagonal matrices which have zeros on the main diagonal and random ±1’s as the other entries. We explore the relationship between spectral sets in the finite and infinite matrix cases, and between the semi-infinite and bi-infinite matrix cases, for example showing that the numerical range and p-norm ε - pseudospectra (ε > 0, p ∈ [1,∞] ) of the random finite matrices converge almost surely to their infinite matrix counterparts, and that the finite matrix spectra are contained in the infinite matrix spectrum Σ. We also propose a sequence of inclusion sets for Σ which we show is convergent to Σ, with the nth element of the sequence computable by calculating smallest singular values of (large numbers of) n×n matrices. We propose similar convergent approximations for the 2-norm ε -pseudospectra of the infinite random matrices, these approximations sandwiching the infinite matrix pseudospectra from above and below.

Visual search for basic emotional expressions in autism; impaired processing of anger, fear and sadness, but a typical happy face advantage

Facial expression recognition was investigated in 20 males with high functioning autism (HFA) or Asperger syndrome (AS), compared to typically developing individuals matched for chronological age (TD CA group) and verbal and non-verbal ability (TD V/NV group). This was the first study to employ a visual search, “face in the crowd” paradigm with a HFA/AS group, which explored responses to numerous facial expressions using real-face stimuli. Results showed slower response times for processing fear, anger and sad expressions in the HFA/AS group, relative to the TD CA group, but not the TD V/NV group. Reponses to happy, disgust and surprise expressions showed no group differences. Results are discussed with reference to the amygdala theory of autism.

Transient reconnection: Search for ionospheric signatures

The concept of magnetic reconnection originated with the suggestion by Giovanelli [1946] that particles could be energized during solar flares near nulls in the magnetic field. Hoyle [1949] subsequently proposed that such a process could also act at nulls between the geomagnetic field and the interplanetary magnetic field (IMF) to generate the energized particles responsible for auroral displays. However, the idea of the interconnection of the two magnetic fields, as we know it today, was first presented by Hoyle's student, Dungey [1953, 1961].

Crossbred cow adoption and its correlates: countable adoption specification search in Sri Lanka's small holder dairy sector

Considerable specification choice confronts countable adoption investigations and there is need to measure, formally, the evidence in favor of competing formulations. This article presents alternative countable adoption specifications—hitherto neglected in the agricultural-economics literature—and assesses formally their usefulness to practitioners. Reference to the left side of de Finetti's (1937) famous representation theorem motivates Bayesian unification of agricultural adoption studies and facilitates comparisons with conventional binary-choice specifications. Such comparisons have not previously been considered. The various formulations and the specific techniques are highlighted in an application to crossbred cow adoption in Sri Lanka's small-holder dairy sector.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

Associations between FTO genotype and total energy and macronutrients intake: a systematic review and meta-analysis

Risk variants of the fat-mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrients intake has not been reviewed systematically. Our aim was to evaluate potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in Medline, Scopus, EMBASE and Cochrane of associations between macronutrients intake and FTO genotype in adults. Beta coefficients and confidence intervals were used for per-allele comparisons. Random-effects models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213 173 adults. For each copy of the FTO risk allele, individuals reported 6.46 kcal/day (95% CI: 10.76, 2.16) lower total energy intake (P=0.003). Total fat (P=0.028) and protein (P=0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P=0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrients intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting.