Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of the idiotypic robot. In this paper an attempt is made to imitate idiotypic dynamics by creating controllers that use reinforcement with a number of different probabilistic schemes to select robot behaviour. The aims are to show that the idiotypic system is not merely performing some kind of periodic random behaviour selection, and to try to gain further insight into the processes that govern the idiotypic mechanism. Trials are carried out using simulated Pioneer robots that undertake navigation exercises. Results show that a scheme that boosts the probability of selecting highly-ranked alternative behaviours to 50% during stall conditions comes closest to achieving the properties of the idiotypic system, but remains unable to match it in terms of all round performance.

Early consumption of liquids different to breast milk in Mexican infants under 1 year: results of the probabilistic National Health and Nutrition Survey 2012

Introduction: Studies on infant dietary intake do not generally focus on the types of liquids consumed. Objective: To document by age and breastfeeding status, the types of liquids present in the diet of Mexican children under 1 year of age (< 1 y) who participated in the National Health and Nutrition Survey 2012 (ENSANUT-2012). Methods: Analysis of the infant < 1 y feeding practices from the ENSANUT-2012 survey in non-breastfed (non-BF) and breastfed (BF) infants by status quo for the consumption of liquids grouped in: water, formula, fortified LICONSA milk, nutritive liquids (NL; thin cereal-based gruel with water or milk and coffee with milk) and non-nutritive liquids (non-NL) as sugared water, water-based drinks, tea, beans or chicken broth, aguamiel and coffee. In this infants < 1 y we analyzed the not grouped consumption of liquids in the first three days of life (newborns) from the mother's recall. Percentage and confidence intervals (95% CI) were calculated adjusting for survey design. Statistical differences were analyzed by Z test. Results: We observed a high consumption of human milk followed by formula (56.7%) and water (51.1%) in infants under 6 months of age (< 6 mo). The proportion of non-BF infants consuming non-NL was higher than for BF infants (p < 0.05). More than 60% of older infants (6 mo and < 1 y) consumed formula and were non-BF. In newborns formula consumption was predominant, followed by tea or infusion and water. Conclusions: Non-breast milk liquids are present undesirably in Mexican infants' diet and non-NL are consumed earlier than NL, revealing inadequate early dietary practices.

Probabilistic Imaging and Dynamic Modeling of Earthquake Source Processes

Investigation of large, destructive earthquakes is challenged by their infrequent occurrence and the remote nature of geophysical observations. This thesis sheds light on the source processes of large earthquakes from two perspectives: robust and quantitative observational constraints through Bayesian inference for earthquake source models, and physical insights on the interconnections of seismic and aseismic fault behavior from elastodynamic modeling of earthquake ruptures and aseismic processes.

To constrain the shallow deformation during megathrust events, we develop semi-analytical and numerical Bayesian approaches to explore the maximum resolution of the tsunami data, with a focus on incorporating the uncertainty in the forward modeling. These methodologies are then applied to invert for the coseismic seafloor displacement field in the 2011 Mw 9.0 Tohoku-Oki earthquake using near-field tsunami waveforms and for the coseismic fault slip models in the 2010 Mw 8.8 Maule earthquake with complementary tsunami and geodetic observations. From posterior estimates of model parameters and their uncertainties, we are able to quantitatively constrain the near-trench profiles of seafloor displacement and fault slip. Similar characteristic patterns emerge during both events, featuring the peak of uplift near the edge of the accretionary wedge with a decay toward the trench axis, with implications for fault failure and tsunamigenic mechanisms of megathrust earthquakes.

To understand the behavior of earthquakes at the base of the seismogenic zone on continental strike-slip faults, we simulate the interactions of dynamic earthquake rupture, aseismic slip, and heterogeneity in rate-and-state fault models coupled with shear heating. Our study explains the long-standing enigma of seismic quiescence on major fault segments known to have hosted large earthquakes by deeper penetration of large earthquakes below the seismogenic zone, where mature faults have well-localized creeping extensions. This conclusion is supported by the simulated relationship between seismicity and large earthquakes as well as by observations from recent large events. We also use the modeling to connect the geodetic observables of fault locking with the behavior of seismicity in numerical models, investigating how a combination of interseismic geodetic and seismological estimates could constrain the locked-creeping transition of faults and potentially their co- and post-seismic behavior.

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

A novel ranking procedure for forecasting approaches using Data Envelopment Analysis

To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreement on which approach should be used. Generally forecasting measures represent ratios or percentages providing an overall image of how well fitted the forecasting technique is to the observations. This paper proposes a multiplicative Data Envelopment Analysis (DEA) model in order to rank several forecasting techniques. We demonstrate the proposed model by applying it to the set of yearly time series of the M3 competition. The usefulness of the proposed approach has been tested using the M3-competition where five error measures have been applied in and aggregated to a single DEA score.

Jointly event extraction and visualization on Twitter via probabilistic modelling

Event extraction from texts aims to detect structured information such as what has happened, to whom, where and when. Event extraction and visualization are typically considered as two different tasks. In this paper, we propose a novel approach based on probabilistic modelling to jointly extract and visualize events from tweets where both tasks benefit from each other. We model each event as a joint distribution over named entities, a date, a location and event-related keywords. Moreover, both tweets and event instances are associated with coordinates in the visualization space. The manifold assumption that the intrinsic geometry of tweets is a low-rank, non-linear manifold within the high-dimensional space is incorporated into the learning framework using a regularization. Experimental results show that the proposed approach can effectively deal with both event extraction and visualization and performs remarkably better than both the state-of-the-art event extraction method and a pipeline approach for event extraction and visualization.

Probabilistic Security Constrained Fuzzy Power Flow Models

In restructured power systems, generation and commercialization activities became market activities, while transmission and distribution activities continue as regulated monopolies. As a result, the adequacy of transmission network should be evaluated independent of generation system. After introducing the constrained fuzzy power flow (CFPF) as a suitable tool to quantify the adequacy of transmission network to satisfy 'reasonable demands for the transmission of electricity' (as stated, for instance, at European Directive 2009/72/EC), the aim is now showing how this approach can be used in conjunction with probabilistic criteria in security analysis. In classical security analysis models of power systems are considered the composite system (generation plus transmission). The state of system components is usually modeled with probabilities and loads (and generation) are modeled by crisp numbers, probability distributions or fuzzy numbers. In the case of CFPF the component’s failure of the transmission network have been investigated. In this framework, probabilistic methods are used for failures modeling of the transmission system components and possibility models are used to deal with 'reasonable demands'. The enhanced version of the CFPF model is applied to an illustrative case.

A probabilistic approach to user mobility prediction for wireless services.

Mobile and wireless networks have long exploited mobility predictions, focused on predicting the future location of given users, to perform more efficient network resource management. In this paper, we present a new approach in which we provide predictions as a probability distribution of the likelihood of moving to a set of future locations. This approach provides wireless services a greater amount of knowledge and enables them to perform more effectively. We present a framework for the evaluation of this new type of predictor, and develop 2 new predictors, HEM and G-Stat. We evaluate our predictors accuracy in predicting future cells for mobile users, using two large geolocation data sets, from MDC [11], [12] and Crawdad [13]. We show that our predictors can successfully predict with as low as an average 2.2% inaccuracy in certain scenarios.

Ranking de ciudades Latinoamericanas para la atracción de inversiones. INAI 2011

En las últimas décadas, la naturaleza y el alcance de los territorios —en particular, de las ciudades— se han transformado aceleradamente. La introducción de las perspectivas del desarrollo económico y del desarrollo humano sustentable ha dado lugar a una fuerte tendencia para que los territorios sean los principales jugadores de un escenario cada vez más global, que se ha visto acelerado por la masificación de las tecnologías de la información y las telecomunicaciones, la mayor tendencia a la liberalización del comercio, las menores restricciones a los flujos de capital, así como la localización de multinacionales con plantas globales. En este contexto, las ciudades se consolidan como un sistema interactivo e integrado a una red global que se relaciona con sus pares, que compite por conseguir recursos y que busca posicionarse en el escenario global como un nodo atractivo.

Ranking e qualidade educativa. Uma relação (im)provável? Um estudo em duas escolas públicas

Com o presente trabalho pretendemos compreender eventuais relações entre a posição de uma escola no ranking dos exames nacionais do 9.º ano do ensino básico e a qualidade do serviço educativo prestado. O estudo decorreu em dois agrupamentos de escolas com posições diferenciadas nas listas de ordenação (rankings) publicadas no ano de 2013. Recolhemos informação através de entrevista aos diretores dos órgãos de gestão, análise documental e inquérito por questionário. Adotámos metodologia qualitativa e quantitativa cujos dados foram triangulados e analisados à luz do quadro teórico. A posição bastante diferenciada entre os dois agrupamentos no ranking (249.º e 848.º, respetivamente) não parece estar relacionado com a prestação do serviço educativo, para além de a classificação ser a mesma nos relatórios de avaliação externa, as diferenças identificadas através dos questionários e das entrevistas são pontuais e pouco relevantes reforçando que efetivamente a posição no ranking diz muito pouco sobre o trabalho realizado nas escolas, sobre as suas dinâmicas e lógicas de ação; Abstract: Ranking and educational quality. An (un)likely relationship? A study in two public schools With this study we aim to understand possible links between the ranking position of two different school based on the 9th grade’s national exams results and the quality of educational services provided. The study took place in two groups of schools with different ranking positions published in 2013. We collect information through interviews to the directors of the management bodies, document analysis and questionnaire survey. We adopted qualitative and quantitative methodology and data were triangulated and analyzed in the light of the theoretical framework. The rather unique position between the two groups in the rankings (249 and 848, respectively) does not seem to be related to the provision of educational services, as well as the classification is the same in the external evaluation reports, the differences identified by questionnaires and interviews are timely and very relevant stressing that effectively ranking position says very little about the work done in schools, on its dynamics and logics of action.

RANKING DEL BIENESTAR SEGÚN CATEGORÍAS URBANAS EN LA ARGENTINA (2001)

Existe una estrecha relación entre bienestar y escala urbana. Considerando una combinación ponderada de indicadores socioeconómicos y ambientales tenemos que las Aglomeraciones de Tamaño Intermedio (ATIS) grandes (entre 400.000 y 999.999 habitantes) poseen el mayor nivel de bienestar, seguidas por las ATIS medias (entre 50.000 y 399.999). Las ciudades grandes (más de un millón de habitantes) recientemente se ubican en un tercer escalón. Cruzando la escala urbana y la región se evidencian mejor estas diferencias. La mejor conjunción corresponde a las ATIS medias patagónicas, mientras que la peor es la que reúne a las ATIS medias del Nordeste Argentino (NEA). Es decir que, más allá de la jerarquía urbana como factor de diferenciación, también deben considerarse los contextos regionales para intentar dimensionar más ajustadamente las diferencias del bienestar en Argentina. ABSTRACT A very close relationship exists between well-being and urban scale. If we consider a weighted combination of socioeconomic and environmental indicators, we find that bigger middle-sized cities (ATIS in Spanish) of between 400,000 and 1,000,000 inhabitants have the highest level of well-being, followed by middle ATIS, or cities, of 50,000 to 400,000 in population. The largest cities, those with a population of more than 1,000,000 ranked third. However, these differences are better evidenced by crossing urban scale and region. In other words, beyond urban hierarchy as a differentiation factor, the regional context must also be considered to more accurately gage differences in well-being.

Analysis of human posterior EEG alpha frequency as a function of implicit learning of probabilistic lateralized stimuli in a visual detection task

Alpha oscillatory activity has long been associated with perceptual and cognitive processes related to attention control. The aim of this study is to explore the task-dependent role of alpha frequency in a lateralized visuo-spatial detection task. Specifically, the thesis focuses on consolidating the scientific literature's knowledge about the role of alpha frequency in perceptual accuracy, and deepening the understanding of what determines trial-by-trial fluctuations of alpha parameters and how these fluctuations influence overall task performance. The hypotheses, confirmed empirically, were that different implicit strategies are put in place based on the task context, in order to maximize performance with optimal resource distribution (namely alpha frequency, associated positively with performance): “Lateralization” of the attentive resources towards one hemifield should be associated with higher alpha frequency difference between contralateral and ipsilateral hemisphere; “Distribution” of the attentive resources across hemifields should be associated with lower alpha frequency difference between hemispheres; These strategies, used by the participants according to their brain capabilities, have proven themselves adaptive or maladaptive depending on the different tasks to which they have been set: "Distribution" of the attentive resources seemed to be the best strategy when the distribution probability between hemifields was balanced: i.e. the neutral condition task. "Lateralization" of the attentive resources seemed to be more effective when the distribution probability between hemifields was biased towards one hemifield: i.e., the biased condition task.

[gait Speed, Grip Strength And Self-rated Health Among The Elderly: Data From The Fibra Campinas Network, São Paulo, Brazil].

The article seeks to investigate patterns of performance and relationships between grip strength, gait speed and self-rated health, and investigate the relationships between them, considering the variables of gender, age and family income. This was conducted in a probabilistic sample of community-dwelling elderly aged 65 and over, members of a population study on frailty. A total of 689 elderly people without cognitive deficit suggestive of dementia underwent tests of gait speed and grip strength. Comparisons between groups were based on low, medium and high speed and strength. Self-related health was assessed using a 5-point scale. The males and the younger elderly individuals scored significantly higher on grip strength and gait speed than the female and oldest did; the richest scored higher than the poorest on grip strength and gait speed; females and men aged over 80 had weaker grip strength and lower gait speed; slow gait speed and low income arose as risk factors for a worse health evaluation. Lower muscular strength affects the self-rated assessment of health because it results in a reduction in functional capacity, especially in the presence of poverty and a lack of compensatory factors.