3D sparse feature model using short baseline stereo and multiple view registration

This paper outlines a methodology to generate a distinctive object representation offline, using short-baseline stereo fundamentals to triangulate highly descriptive object features in multiple pairs of stereo images. A group of sparse 2.5D perspective views are built and the multiple views are then fused into a single sparse 3D model using a common 3D shape registration technique. Having prior knowledge, such as the proposed sparse feature model, is useful when detecting an object and estimating its pose for real-time systems like augmented reality.

Three-feature model to reproduce the topology of citation networks and the effects from authors' visibility on their h-index

Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in Clouds: four kinds of schema.

The proposed research will focus on developing a novel approach to solve Software Service Evolution problems in Computing Clouds. The approach will support dynamic evolution of the software service in clouds via a set of discovered evolution patterns. An initial survey informed us that such an approach does not exist yet and is in urgent need. Evolution Requirement can be classified into evolution features; researchers can describe the whole requirement by using evolution feature typology, the typology will define the relation and dependency between each features. After the evolution feature typology has been constructed, evolution model will be created to make the evolution more specific. Aspect oriented approach can be used for enhance evolution feature-model modularity. Aspect template code generation technique will be used for model transformation in the end. Product Line Engineering contains all the essential components for driving the whole evolution process.

Weaving behavior into feature models for embedded system families

Product Line software Engineering depends on capturing the commonality and variability within a family of products, typically using feature modeling, and using this information to evolve a generic reference architecture for the family. For embedded systems, possible variability in hardware and operating system platforms is an added complication. The design process can be facilitated by first exploring the behavior associated with features. In this paper we outline a bidirectional feature modeling scheme that supports the capture of commonality and variability in the platform environment as well as within the required software. Additionally, 'behavior' associated with features can be included in the overall model. This is achieved by integrating the UCM path notation in a way that exploits UCM's static and dynamic stubs to capture behavioral variability and link it to the feature model structure. The resulting model is a richer source of information to support the architecture development process.

Phonological similarity effects without a phonological store: an individual differences model

The feature model of immediate memory (Nairne, 1990) is applied to an experiment testing individual differences in phonological confusions amongst a group (N=100) of participants performing a verbal memory test. By simulating the performance of an equivalent number of “pseudo-participants” the model fits both the mean performance and the variability within the group. Experimental data show that high-performing individuals are significantly more likely to demonstrate phonological confusions than low performance individuals and this is also true of the model, despite the model’s lack of either an explicit phonological store or a performance-linked strategy shift away from phonological storage. It is concluded that a dedicated phonological store is not necessary to explain the basic phonological confusion effect, and the reduction in such an effect can also be explained without requiring a change in encoding or rehearsal strategy or the deployment of a different storage buffer.

Feature-oriented regional modeling and simulations (FORMS) for the western South Atlantic: Southeastern Brazil region

The multi-scale synoptic circulation system in the southeastern Brazil (SEBRA) region is presented using a feature-oriented approach. Prevalent synoptic circulation structures, or ""features,"" are identified from previous observational studies. These features include the southward-flowing Brazil Current (BC), the eddies off Cabo Sao Tome (CST - 22 degrees S) and off Cabo Frio (CF - 23 degrees S), and the upwelling region off CF and CST. Their synoptic water-mass (T-S) structures are characterized and parameterized to develop temperature-salinity (T-S) feature models. Following [Gangopadhyay, A., Robinson, A.R., Haley, PJ., Leslie, W.J., Lozano, C.j., Bisagni, J., Yu, Z., 2003. Feature-oriented regional modeling and simulation (forms) in the gulf of maine and georges bank. Cont. Shelf Res. 23 (3-4), 317-353] methodology, a synoptic initialization scheme for feature-oriented regional modeling and simulation (FORMS) of the circulation in this region is then developed. First, the temperature and salinity feature-model profiles are placed on a regional circulation template and objectively analyzed with available background climatology in the deep region. These initialization fields are then used for dynamical simulations via the Princeton Ocean Model (POM). A few first applications of this methodology are presented in this paper. These include the BC meandering, the BC-eddy interaction and the meander-eddy-upwelling system (MEUS) simulations. Preliminary validation results include realistic wave-growth and eddy formation and sustained upwelling. Our future plan includes the application of these feature models with satellite, in-situ data and advanced data-assimilation schemes for nowcasting and forecasting the SEBRA region. (c) 2008 Elsevier Ltd. All rights reserved.

Exploring automatic feature selection for transition-based dependency parsing

En este artículo se investigan técnicas automáticas para encontrar un modelo óptimo de características en el caso de un analizador de dependencias basado en transiciones. Mostramos un estudio comparativo entre algoritmos de búsqueda, sistemas de validación y reglas de decisión demostrando al mismo tiempo que usando nuestros métodos es posible conseguir modelos complejos que proporcionan mejores resultados que los modelos que siguen configuraciones por defecto.

Object Detection at the Optimal Scale with Hidden State Shape Models

Hidden State Shape Models (HSSMs) [2], a variant of Hidden Markov Models (HMMs) [9], were proposed to detect shape classes of variable structure in cluttered images. In this paper, we formulate a probabilistic framework for HSSMs which provides two major improvements in comparison to the previous method [2]. First, while the method in [2] required the scale of the object to be passed as an input, the method proposed here estimates the scale of the object automatically. This is achieved by introducing a new term for the observation probability that is based on a object-clutter feature model. Second, a segmental HMM [6, 8] is applied to model the "duration probability" of each HMM state, which is learned from the shape statistics in a training set and helps obtain meaningful registration results. Using a segmental HMM provides a principled way to model dependencies between the scales of different parts of the object. In object localization experiments on a dataset of real hand images, the proposed method significantly outperforms the method of [2], reducing the incorrect localization rate from 40% to 15%. The improvement in accuracy becomes more significant if we consider that the method proposed here is scale-independent, whereas the method of [2] takes as input the scale of the object we want to localize.

La perception naïve non native des voyelles nasales du portugais

Les adultes peuvent éprouver des difficultés à discriminer des phonèmes d’une langue seconde (L2) qui ne servent pas à distinguer des items lexicaux dans leur langue maternelle (L1). Le Feature Model (FM) de Brown (1998) propose que les adultes peuvent réussir à créer des nouvelles catégories de sons seulement si celles-ci peuvent être construites à partir de traits distinctifs existant dans la L1 des auditeurs. Cette hypothèse a été testée sur plusieurs contrastes consonantiques dans différentes langues; cependant, il semble que les traits qui s’appliquent sur les voyelles n’aient jamais été examinés dans cette perspective et encore moins les traits qui opèrent à la fois dans les systèmes vocalique et consonantique et qui peuvent avoir un statut distinctif ou non-distinctif. Le principal objectif de la présente étude était de tester la validité du FM concernant le contraste vocalique oral-nasal du portugais brésilien (PB). La perception naïve du contraste /i/-/ĩ/ par des locuteurs du français, de l’anglais, de l’espagnol caribéen et de l’espagnol conservateur a été examinée, étant donné que ces quatre langues diffèrent en ce qui a trait au statut de la nasalité. De plus, la perception du contraste non-naïf /e/-/ẽ/ a été inclus afin de comparer les performances dans la perception naïve et non-naïve. Les résultats obtenus pour la discrimination naïve de /i/-/ĩ/ a permis de tirer les conclusions suivantes pour la première exposition à un contraste non natif : (1) le trait [nasal] qui opère de façon distinctive dans la grammaire d’une certaine L1 peut être redéployé au sein du système vocalique, (2) le trait [nasal] qui opère de façon distinctive dans la grammaire d’une certaine L1 ne peut pas être redéployé à travers les systèmes (consonne à voyelle) et (3) le trait [nasal] qui opère de façon non-distinctive dans la grammaire d’une certaine L1 peut être ou ne pas être redéployé au statut distinctif. En dernier lieu, la discrimination non-naïve de /e/-/ẽ/ a été réussie par tous les groupes, suggérant que les trois types de redéploiement s’avèrent possibles avec plus d’expérience dans la L2.

Modeling distributions of immediate memory effects: No strategies needed?

Many models of immediate memory predict the presence or absence of various effects, but none have been tested to see whether they predict an appropriate distribution of effect sizes. The authors show that the feature model (J. S. Nairne, 1990) produces appropriate distributions of effect sizes for both the phonological confusion effect and the word-length effect. The model produces the appropriate number of reversals, when participants are more accurate with similar items or long items, and also correctly predicts that participants performing less well overall demonstrate smaller and less reliable phonological similarity and word-length effects and are more likely to show reversals. These patterns appear within the model without the need to assume a change in encoding or rehearsal strategy or the deployment of a different storage buffer. The implications of these results and the wider applicability of the distributionmodeling approach are discussed.

The relationship between absolute and proportion scores of serial order memory: simulation predictions and empirical data

The capability of a feature model of immediate memory (Nairne, 1990; Neath, 2000) to predict and account for a relationship between absolute and proportion scoring of immediate serial recall when memory load is varied (the list-length effect, LLE) is examined. The model correctly predicts the novel finding of an LLE in immediate serial order memory similar to that observed with free recall and previously assumed to be attributable to the long-term memory component of that procedure (Glanzer, 1972). The usefulness of formal models as predictive tools and the continuity between short-term serial order and longer term item memory are considered.

Storm surge frequency reduction in Venice under climate change

Increased tidal levels and storm surges related to climate change are projected to result in extremely adverse effects on coastal regions. Predictions of such extreme and small-scale events, however, are exceedingly challenging, even for relatively short time horizons. Here we use data from observations, ERA-40 reanalysis, climate scenario simulations, and a simple feature model to find that the frequency of extreme storm surge events affecting Venice is projected to decrease by about 30% by the end of the twenty-first century. In addition, through a trend assessment based on tidal observations we found a reduction in extreme tidal levels. Extrapolating the current +17 cm/century sea level trend, our results suggest that the frequency of extreme tides in Venice might largely remain unaltered under the projected twenty-first century climate simulations.

Um método para desenvolvimento de abordagens generativas com composição de linguagens específicas de domínio

The software systems development with domain-specific languages has become increasingly common. Domain-specific languages (DSLs) provide increased of the domain expressiveness, raising the abstraction level by facilitating the generation of models or low-level source code, thus increasing the productivity of systems development. Consequently, methods for the development of software product lines and software system families have also proposed the adoption of domain-specific languages. Recent studies have investigated the limitations of feature model expressiveness and proposing the use of DSLs as a complement or substitute for feature model. However, in complex projects, a single DSL is often insufficient to represent the different views and perspectives of development, being necessary to work with multiple DSLs. In order to address new challenges in this context, such as the management of consistency between DSLs, and the need to methods and tools that support the development with multiple DSLs, over the past years, several approaches have been proposed for the development of generative approaches. However, none of them considers matters relating to the composition of DSLs. Thus, with the aim to address this problem, the main objectives of this dissertation are: (i) to investigate the adoption of the integrated use of feature models and DSLs during the domain and application engineering of the development of generative approaches; (ii) to propose a method for the development of generative approaches with composition DSLs; and (iii) to investigate and evaluate the usage of modern technology based on models driven engineering to implement strategies of integration between feature models and composition of DSLs

Designing Software Product Lines for Testability

Software product line (SPL) engineering offers several advantages in the development of families of software products such as reduced costs, high quality and a short time to market. A software product line is a set of software intensive systems, each of which shares a common core set of functionalities, but also differs from the other products through customization tailored to fit the needs of individual groups of customers. The differences between products within the family are well-understood and organized into a feature model that represents the variability of the SPL. Products can then be built by generating and composing features described in the feature model. Testing of software product lines has become a bottleneck in the SPL development lifecycle, since many of the techniques used in their testing have been borrowed from traditional software testing and do not directly take advantage of the similarities between products. This limits the overall gains that can be achieved in SPL engineering. Recent work proposed by both industry and the research community for improving SPL testing has begun to consider this problem, but there is still a need for better testing techniques that are tailored to SPL development. In this thesis, I make two primary contributions to software product line testing. First I propose a new definition for testability of SPLs that is based on the ability to re-use test cases between products without a loss of fault detection effectiveness. I build on this idea to identify elements of the feature model that contribute positively and/or negatively towards SPL testability. Second, I provide a graph based testing approach called the FIG Basis Path method that selects products and features for testing based on a feature dependency graph. This method should increase our ability to re-use results of test cases across successive products in the family and reduce testing effort. I report the results of a case study involving several non-trivial SPLs and show that for these objects, the FIG Basis Path method is as effective as testing all products, but requires us to test no more than 24% of the products in the SPL.