910 resultados para Cartographic feature
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This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.
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Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.
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In the last decade, the research community has focused on new classification methods that rely on statistical characteristics of Internet traffic, instead of pre-viously popular port-number-based or payload-based methods, which are under even bigger constrictions. Some research works based on statistical characteristics generated large fea-ture sets of Internet traffic; however, nowadays it?s impossible to handle hun-dreds of features in big data scenarios, only leading to unacceptable processing time and misleading classification results due to redundant and correlative data. As a consequence, a feature selection procedure is essential in the process of Internet traffic characterization. In this paper a survey of feature selection methods is presented: feature selection frameworks are introduced, and differ-ent categories of methods are briefly explained and compared; several proposals on feature selection in Internet traffic characterization are shown; finally, future application of feature selection to a concrete project is proposed.
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This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.
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The existing seismic isolation systems are based on well-known and accepted physical principles, but they are still having some functional drawbacks. As an attempt of improvement, the Roll-N-Cage (RNC) isolator has been recently proposed. It is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of vertical rigid support, horizontal flexibility with enhanced stability, resistance to low service loads and minor vibration, and hysteretic energy dissipation characteristics. It is characterized by two unique features that are a self-braking (buffer) and a self-recentering mechanism. This paper presents an advanced representation of the main and unique features of the RNC isolator using an available finite element code called SAP2000. The validity of the obtained SAP2000 model is then checked using experimental, numerical and analytical results. Then, the paper investigates the merits and demerits of activating the built-in buffer mechanism on both structural pounding mitigation and isolation efficiency. The paper addresses the problem of passive alleviation of possible inner pounding within the RNC isolator, which may arise due to the activation of its self-braking mechanism under sever excitations such as near-fault earthquakes. The results show that the obtained finite element code-based model can closely match and accurately predict the overall behavior of the RNC isolator with effectively small errors. Moreover, the inherent buffer mechanism of the RNC isolator could mitigate or even eliminate direct structure-tostructure pounding under severe excitation considering limited septation gaps between adjacent structures. In addition, the increase of inherent hysteretic damping of the RNC isolator can efficiently limit its peak displacement together with the severity of the possibly developed inner pounding and, therefore, alleviate or even eliminate the possibly arising negative effects of the buffer mechanism on the overall RNC-isolated structural responses.
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Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.
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Una de las características de la cartografía y SIG Participativos (SIGP) es incluir en sus métodos a la sociedad civil para aportar contenidos cualitativos a la información de sus territorios. Sin embargo no sólo se trata de datos, sino de los efectos que pueden tener estas prácticas sobre el territorio y su sociedad. El acceso a esa información se ve reducida en contraste con el incremento de información difundida a través de servicios de visualización, geoinformación y cartografía on-line. Todo esto hace que sea necesario el análisis del alcance real de las metodologías participativas en el uso de Información Geográfica (IG) y la comparación desde distintos contextos geográficos. También es importante conocer los beneficios e inconvenientes del acceso a la información para el planeamiento; desde la visibilidad de muchos pueblos desapercibidos en zonas rurales y periféricas, hasta la influencia en programas de gobierno sobre la gestión del territorio pasando por el conocimiento local espacial. El análisis se centró en los niveles de participación de la sociedad civil y sus grados de accesibilidad a la información (acceso y uso), dentro del estudio de los SIGP, Participatory Mapping, además se estudió de los TIG (Tecnologías de Información Geográfica), cartografías on-line (geoweb) y plataformas de geovisualización espacial, como recursos de Neocartografía. En este sentido, se realizó un trabajo de campo de cartografía participativa en Bolivia, se evaluaron distintos proyectos SIGP en países del norte y sur (comparativa de contextos en países en desarrollo) y se analizaron los resultados del cruce de las distintas variables.(validación, accesibilidad, verificación de datos, valor en la planificación e identidad) La tesis considera que ambos factores (niveles de participación y grado de accesibilidad) afectan a la (i) validación, verificación y calidad de los datos, la (ii) valor analítico en la planificación, y al (iii) modelo de identidad de un lugar, y que al ser tratados de forma integral, constituyen el valor añadido que los SIGP pueden aportar para lograr una planificación efectiva. Asimismo se comprueba, que la dimensión participativa en los SIGP varía según el contexto, la centralización de sus actores e intereses sectoriales. La información resultante de las prácticas SIGP tiende a estar restringida por la falta de legislaciones y por la ausencia de formatos estándar, que limitan la difusión e intercambio de la información. Todo esto repercute en la efectividad de una planificación estratégica y en la viabilidad de la implementación de cualquier proyecto sobre el territorio, y en consecuencia sobre los niveles de desarrollo de un país. Se confirma la hipótesis de que todos los elementos citados en los SIGP y mapeo participativo actuarán como herramientas válidas para el fortalecimiento y la eficacia en la planificación sólo si están interconectadas y vinculadas entre sí. Se plantea una propuesta metodológica ante las formas convencionales de planificación (nueva ruta del planeamiento; que incluye el intercambio de recursos y determinación participativa local antes de establecer la implementación), con ello, se logra incorporar los beneficios de las metodologías participativas en el manejo de la IG y los SIG (Sistemas de Información Geográfica) como instrumentos estratégicos para el desarrollo de la identidad local y la optimización en los procesos de planeamiento y estudios del territorio. Por último, se fomenta que en futuras líneas de trabajo los mapas de los SIGP y la cartografía participativa puedan llegar a ser instrumentos visuales representativos que transfieran valores identitarios del territorio y de su sociedad, y de esta manera, ayudar a alcanzar un mayor conocimiento, reconocimiento y valoración de los territorios para sus habitantes y sus planificadores. ABSTRACT A feature of participatory mapping and PGIS is to include the participation of the civil society, to provide qualitative information of their territories. However, focus is not only data, but also the effects that such practices themselves may have on the territory and their society. Access to this information is reduced in contrast to the increase of information disseminated through visualization services, geoinformation, and online cartography. Thus, the analysis of the real scope of participatory methodologies in the use of Geographic Information (GI) is necessary, including the comparison of different geographical contexts. It is also important to know the benefits and disadvantages of access to information needed for planning in different contexts, ranging from unnoticed rural areas and suburbs to influence on government programs on land management through local spatial knowledge. The analysis focused on the participation levels of civil society and the degrees of accessibility of the information (access and use) within the study of Participatory GIS (PGIS). In addition, this work studies GIT (Geographic Information Technologies), online cartographies (Geoweb) and platforms of spatial geovisualization, as resources of Neocartography. A participatory cartographic fieldwork was carried out in Bolivia. Several PGIS projects were evaluated in Northern and Southern countries (comparatively with the context of developing countries), and the results were analyzed for each these different variables. (validation, accessibility, verification,value, identity). The thesis considers that both factors (participation levels and degree of accessibility) affect the (i) validation, verification and quality of the data, (ii) analytical value for planning, and (iii) the identity of a place. The integrated management of all the above cited criteria constitutes an added value that PGISs can contribute to reach an effective planning. Also, it confirms the participatory dimension of PGISs varies according to the context, the centralization of its actors, and to sectorial interests. The resulting information from PGIS practices tends to be restricted by the lack of legislation and by the absence of standard formats, which limits in turn the diffusion and exchange of the information. All of this has repercussions in the effectiveness of a strategic planning and in the viability of the implementation of projects about the territory, and consequentially in the land development levels. The hypothesis is confirmed since all the described elements in PGISs and participatory mapping will act as valid tools in strengthening and improving the effectivity in planning only if they are interconnected and linked amongst themselves. This work, therefore, suggests a methodological proposal when faced with the conventional ways of planning: a new planning route which includes the resources exchange and local participatory determination before any plan is established -. With this, the benefits of participatory methodologies in the management of GI and GIS (Geographic Information Systems) is incorporated as a strategic instrument for development of local identity and optimization in planning processes and territory studies. Finally, the study outlines future work on PGIS maps and Participatory Mapping, such that these could eventually evolve into visual representative instruments that transfer identity values of the territory and its society. In this way, they would contribute to attain a better knowledge, recognition, and appraisement of the territories for their inhabitants and planners.
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This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.
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This feature issue highlights contributions from authors who presented their research at the OSA Light, Energy and the Environment Congress, held in Canberra, Australia from 2-5 December, 2014.
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The human visual system is able to effortlessly integrate local features to form our rich perception of patterns, despite the fact that visual information is discretely sampled by the retina and cortex. By using a novel perturbation technique, we show that the mechanisms by which features are integrated into coherent percepts are scale-invariant and nonlinear (phase and contrast polarity independent). They appear to operate by assigning position labels or “place tags” to each feature. Specifically, in the first series of experiments, we show that the positional tolerance of these place tags in foveal, and peripheral vision is about half the separation of the features, suggesting that the neural mechanisms that bind features into forms are quite robust to topographical jitter. In the second series of experiment, we asked how many stimulus samples are required for pattern identification by human and ideal observers. In human foveal vision, only about half the features are needed for reliable pattern interpolation. In this regard, human vision is quite efficient (ratio of ideal to real ≈ 0.75). Peripheral vision, on the other hand is rather inefficient, requiring more features, suggesting that the stimulus may be relatively underrepresented at the stage of feature integration.
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The ectodomain of the Ebola virus Gp2 glycoprotein was solubilized with a trimeric, isoleucine zipper derived from GCN4 (pIIGCN4) in place of the hydrophobic fusion peptide at the N terminus. This chimeric molecule forms a trimeric, highly α-helical, and very thermostable molecule, as determined by chemical crosslinking and circular dichroism. Electron microscopy indicates that Gp2 folds into a rod-like structure like influenza HA2 and HIV-1 gp41, providing further evidence that viral fusion proteins from diverse families such as Orthomyxoviridae (Influenza), Retroviridae (HIV-1), and Filoviridae (Ebola) share common structural features, and suggesting a common membrane fusion mechanism.
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Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.
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We characterize a class of spatio-temporal illusions with two complementary properties. Firstly, if a vernier stimulus is flashed for a short time on a monitor and is followed immediately by a grating, the latter can express features of the vernier, such as its offset, its orientation, or its motion (feature inheritance). Yet the vernier stimulus itself remains perceptually invisible. Secondly, the vernier can be rendered visible by presenting gratings with a larger number of elements (shine-through). Under these conditions, subjects perceive two independent “objects” each carrying their own features. Transition between these two domains can be effected by subtle changes in the spatio-temporal layout of the grating. This should allow psychophysicists and electrophysiologists to investigate feature binding in a precise and quantitative manner.
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In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.
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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.