Tropopause level Rossby wave breaking in the Northern Hemisphere: a feature-based validation of the ECHAM5-HAM climate model

Breaking synoptic-scale Rossby waves (RWB) at the tropopause level are central to the daily weather evolution in the extratropics and the subtropics. RWB leads to pronounced meridional transport of heat, moisture, momentum, and chemical constituents. RWB events are manifest as elongated and narrow structures in the tropopause-level potential vorticity (PV) field. A feature-based validation approach is used to assess the representation of Northern Hemisphere RWB in present-day climate simulations carried out with the ECHAM5-HAM climate model at three different resolutions (T42L19, T63L31, and T106L31) against the ERA-40 reanalysis data set. An objective identification algorithm extracts RWB events from the isentropic PV field and allows quantifying the frequency of occurrence of RWB. The biases in the frequency of RWB are then compared to biases in the time mean tropopause-level jet wind speeds. The ECHAM5-HAM model captures the location of the RWB frequency maxima in the Northern Hemisphere at all three resolutions. However, at coarse resolution (T42L19) the overall frequency of RWB, i.e. the frequency averaged over all seasons and the entire hemisphere, is underestimated by 28%.The higher-resolution simulations capture the overall frequency of RWB much better, with a minor difference between T63L31 and T106L31 (frequency errors of −3.5 and 6%, respectively). The number of large-size RWB events is significantly underestimated by the T42L19 experiment and well represented in the T106L31 simulation. On the local scale, however, significant differences to ERA-40 are found in the higher-resolution simulations. These differences are regionally confined and vary with the season. The most striking difference between T106L31 and ERA-40 is that ECHAM5-HAM overestimates the frequency of RWB in the subtropical Atlantic in all seasons except for spring. This bias maximum is accompanied by an equatorward extension of the subtropical westerlies.

Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

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.

Feature LDA:a supervised topic model for automatic detection of web API documentations from the web

Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.

A dynamic feature information model for integrated manufacturing planning and optimization

This paper presents a new, dynamic feature representation method for high value parts consisting of complex and intersecting features. The method first extracts features from the CAD model of a complex part. Then the dynamic status of each feature is established between various operations to be carried out during the whole manufacturing process. Each manufacturing and verification operation can be planned and optimized using the real conditions of a feature, thus enhancing accuracy, traceability and process control. The dynamic feature representation is complementary to the design models used as underlining basis in current CAD/CAM and decision support systems. © 2012 CIRP.

Provocative feature deletion: a syntactic model of agreement alternations in noun incorporation contexts

The relationship between noun incorporation (NI) and the agreement alternations that occur in such contexts (NI Transitivity Alternations) remains inadequately understood. Three interpretations of these alternations (Baker, Aranovich & Golluscio 2005; Mithun 1984; Rosen 1989) are shown to be undermined by foundational or mechanical issues. I propose a syntactic model, adopting Branigan's (2011) interpretation of NI as the result of “provocative” feature valuation, which triggers generation of a copy of the object that subsequently merges inside the verb. Provocation triggers a reflexive Refine operation that deletes duplicate features from chains, making them interpretable for Transfer. NI Transitivity Alternations result from variant deletion preferences exhibited during Refine. I argue that the NI contexts discussed (Generic NI, Partial NI and Double Object NI) result from different restrictions on phonetic and semantic identity in chain formation. This provides us with a consistent definition of NI Transitivity Alternations across contexts, as well as a new typology that distinguishes NI contexts, rather than incorporating languages.

Large volume metrology process model:measurability analysis with integration of metrology classification model and feature-based selection model

Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in clouds: A04BPEL3.0 proposal.

Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.

Frustration and anomalous behavior in the Bell-Lavis model of liquid water

We have reconsidered the Bell-Lavis model of liquid water and investigated its relation to its isotropic version, the antiferromagnetic Blume-Emery-Griffiths model on the triangular lattice. Our study was carried out by means of an exact solution on the sequential Husimi cactus. We show that the ground states of both models share the same topology and that fluid phases (gas and low- and high-density liquids) can be mapped onto magnetic phases (paramagnetic, antiferromagnetic, and dense paramagnetic, respectively). Both models present liquid-liquid coexistence and several thermodynamic anomalies. This result suggests that anisotropy introduced through orientational variables play no specific role in producing the density anomaly, in agreement with a similar conclusion discussed previously following results for continuous soft core,models. We propose that the presence of liquid anomalies may be related to energetic frustration, a feature common to both models.

CERN LHC signals for a neutrino mass model with bilinear R-parity violating minimal anomaly mediated supersymmetry

We investigate a neutrino mass model in which the neutrino data is accounted for by bilinear R-parity violating supersymmetry with anomaly mediated supersymmetry breaking. We focus on the CERN Large Hadron Collider (LHC) phenomenology, studying the reach of generic supersymmetry search channels with leptons, missing energy and jets. A special feature of this model is the existence of long-lived neutralinos and charginos which decay inside the detector leading to detached vertices. We demonstrate that the largest reach is obtained in the displaced vertices channel and that practically all of the reasonable parameter space will be covered with an integrated luminosity of 10 fb(-1). We also compare the displaced vertex reaches of the LHC and Tevatron.

Ameloblast apoptosis and IGF-1 receptor expression in the continuously erupting rat incisor model

Enamel-producing cells (ameloblasts) pass through several phenotypic and functional stages during enamel formation. In the transition between secretory and maturation stages, about one quarter of the ameloblasts suddenly undergo apoptosis. We have studied this phenomenon using the continuously erupting rat incisor model. A special feature of this model is that all stages of ameloblast differentiation are presented within a single longitudinal section of the developing tooth. This permits investigation of the temporal sequence of gene and growth factor receptor expression during ameloblast differentiation and apoptosis. We describe the light and electron microscopic morphology of ameloblast apoptosis and the pattern of insulin-like growth factor-1 receptor expression by ameloblasts in the continuously erupting rat incisor model. In the developing rat incisor, ameloblast apoptosis is associated with downregulated expression of the insulin-like growth factor-1 receptor. These data are consistent with the hypothesis that ameloblasts are hard wired for apoptosis and that insulin-like growth factor-1 receptor expression is required to block the default apoptotic pathway. Possible mechanisms of insulin-like growth factor-1 inhibition of ameloblast apoptosis are presented. The rat incisor model may be useful in studies of physiological apoptosis as it presents apoptosis in a predictable pattern in adult tissues.

Temporal evolution of epithelial, vascular and interstitial lung injury in an experimental model of idiopathic pulmonary fibrosis induced by butyl-hydroxytoluene

This study was undertaken to test whether the structural remodelling of pulmonary parenchyma can be sequentially altered in a model and method that demonstrate the progression of the disease and result in remodelling within the lungs that is typical of idiopathic pulmonary fibrosis. Three groups of mice were studied: (i) animals that received 3-5-di-tert-butyl-4-hydroxytoluene (BHT) and were killed after 2 weeks (early BHT = 9); (ii) animals that received BHT and were killed after 4 weeks (late BHT = 11); (iii) animals that received corn oil solution (control = 10). The mice were placed in a ventilated Plexiglas chamber with a mixture of pure humidified oxygen and compressed air. Lung histological sections underwent haematoxylin-eosin, immunohistochemistry (epithelial, endothelial and immune cells) and specific staining (collagen/elastic fibres) methods for morphometric analysis. When compared with the control group, early BHT and late BHT groups showed significant decrease of type II pneumocytes, lower vascular density in both and higher endothelial activity. CD4 was increased in late BHT compared with early and control groups, while CD8, macrophage and neutrophil cells were more prominent only in early BHT. The collagenous fibre density were significantly higher only in late BHT, whereas elastic fibre content in late BHT was lower than that in control group. We conclude that the BHT experimental model is pathologically very similar to human usual interstitial pneumonia. This feature is important in the identification of animal models of idiopathic pulmonary fibrosis that can accurately reflect the pathogenesis and progression of the human disease.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.