854 resultados para audio features


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We explore the prospects of predicting emission-line features present in galaxy spectra given broad-band photometry alone. There is a general consent that colours, and spectral features, most notably the 4000 angstrom break, can predict many properties of galaxies, including star formation rates and hence they could infer some of the line properties. We argue that these techniques have great prospects in helping us understand line emission in extragalactic objects and might speed up future galaxy redshift surveys if they are to target emission-line objects only. We use two independent methods, Artificial Neural Networks (based on the ANNz code) and Locally Weighted Regression (LWR), to retrieve correlations present in the colour N-dimensional space and to predict the equivalent widths present in the corresponding spectra. We also investigate how well it is possible to separate galaxies with and without lines from broad-band photometry only. We find, unsurprisingly, that recombination lines can be well predicted by galaxy colours. However, among collisional lines some can and some cannot be predicted well from galaxy colours alone, without any further redshift information. We also use our techniques to estimate how much information contained in spectral diagnostic diagrams can be recovered from broad-band photometry alone. We find that it is possible to classify active galactic nuclei and star formation objects relatively well using colours only. We suggest that this technique could be used to considerably improve redshift surveys such as the upcoming Fibre Multi Object Spectrograph (FMOS) survey and the planned Wide Field Multi Object Spectrograph (WFMOS) survey.

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Analysis of floristic similarity relationships between plant communities can detect patterns of species occurrence and also explain conditioning factors. Searching for such patterns, floristic similarity relationships among Atlantic Forest sites situated at Ibiuna Plateau, Sao Paulo state, Brazil, were analyzed by multivariate techniques. Twenty one forest fragments and six sites within a continuous Forest Reserve were included in the analyses. Floristic composition and structure of the tree community (minimum dbh 5 cm) were assessed using the point centered quarter method. Two methods were used for multivariate analysis: Detrended Correspondence Analysis (DCA) and Two-Way Indicator Species Analysis (TWINSPAN). Similarity relationships among the study areas were based on the successional stage of the community and also on spatial proximity. The more similar the successional stage of the communities, the higher the floristic similarity between them, especially if the communities are geographically close. A floristic gradient from north to south was observed, suggesting a transition between biomes, since northern indicator species are mostly heliophytes, occurring also in cerrado vegetation and seasonal semideciduous forest, while southern indicator species are mostly typical ombrophilous and climax species from typical dense evergreen Atlantic Forest.

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Acanthamoeba spp., known to cause keratitis and granulomatous encephalitis in humans, are frequently isolated from a variety of water sources. Here we report for the first time the characterization of an Acanthamoeba sp. (ACC01) isolated from tap water in Brazil. This organism is currently being maintained in an axenic growth medium. Phylogenetic analysis based on SSU rRNA gene sequences positioned the new isolate in genotype T4, closest to the keratitis-causing isolate, A. polyphaga ATCC 30461 (similar to 99% similarity). Acanthamoeba ACC01 and A. polyphaga 30461 both grew at 37 degrees C and were osmotically resistant, multiplying in hyperosmolar medium. Both isolates secreted comparable amounts of proteolytic enzymes, including serine peptidases that were optimally active at a near neutral/alkaline pH and resolved identically in gelatin gels. Incubation of gels at pH 4.0 with 2 mM DTT also indicated the secretion of similar cysteine peptidases. Altogether, the results point to the pathogenic potential of Acanthamoeba ACC01. (C) 2009 Elsevier Inc. All rights reserved.

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Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009

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Erbium-doped single crystal fibers, with low phonon energy and fairly high absorption and emission cross sections are interesting laser active media, for compact, near-infrared and/or upconversion lasers. In this work, high optical quality Er3+-doped CaNb2O6 and CaTa2O6 single crystal fibers were successfully grown by the versatile laser-heated pedestal growth technique, and characterized from the structural and spectroscopic points of view. The results indicate that these crystal fiber compositions, which had not been explored so far, offer potential applications, not only as laser active media, but also in other optical devices. (c) 2007 Elsevier B.V. All rights reserved.

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Mebendazole (MBZ) is a common benzimidazole anthelmintic that exists in three different polymorphic forms, A, B, and C. Polymorph C is the pharmaceutically preferred form due to its adequated aqueous solubility. No single crystal structure determinations depicting the nature of the crystal packing and molecular conformation and geometry have been performed on this compound. The crystal structure of mebendazole form C is resolved for the first time. Mebendazole form C crystallizes in the triclinic centrosymmetric space group and this drug is practically planar, since the least-squares methyl benzimidazolylcarbamate plane is much fitted on the forming atoms. However, the benzoyl group is twisted by 31(1)degrees from the benzimidazole ring, likewise the torsional angle between the benzene and carbonyl moieties is 27(1)degrees. The formerly described bends and other interesting intramolecular geometry features were viewed as consequence of the intermolecular contacts occurring within mebendazole C structure. Among these features, a conjugation decreasing through the imine nitrogen atom of the benzimidazole core and a further resonance path crossing the carbamate one were described. At last, the X-ray powder diffractogram of a form C rich mebendazole mixture was overlaid to the calculated one with the mebendazole crystal structure. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:2336-2344, 2009

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The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

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Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

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I denna uppsats har filmljudet i krigsfilmerna Apocalypse Now och Saving Private Ryan undersökts. Detta har gjorts för att försöka bidra med ökad förståelse för filmljudets användningsområde och funktioner, främst för filmerna i fråga, men även för krigsfilm rent generellt. Filmljud i denna kontext omfattar allt det ljud som finns i film, men utesluter dock all ickediegetisk musik. Båda filmerna har undersökts genom en audio-visuell analys. En sådan analys görs genom att detaljgranska båda filmernas ljud- och bildinnehåll var för sig, för att slutligen undersöka samma filmsekvens som helhet då ljudet och bilden satts ihop igen. Den audio-visuella analysmetod som nyttjats i uppsatsen är Michel Chions metod, Masking. De 30 minuter film som analyserades placerades sedan i olika filmljudzoner, där respektive filmljudzons ljudinnehåll bland annat visade vilka främsta huvudfunktioner somfilmljudet hade i dessa filmer. Dessa funktioner är till för att bibehålla åskådarens fokus och intresse, att skapa närhet till rollkaraktärerna, samt att tillföra en hög känsla av realism och närvaro. Intentionerna med filmljudet verkade vara att flytta åskådaren in i filmens verklighet, att låta åskådaren bli ett med filmen. Att återspegla denna känsla av realism, närvaro, fokus samt intresse, visade sig också vara de intentioner som funnits redan i de båda filmernas förproduktionsstadier. Detta bevisar att de lyckats åstadkomma det de eftersträvat. Men om filmljudet använts på samma sätt eller innehar samma funktioner i krigsfilm rent genrellt går inte att säga.I have for this bachelor’s thesis examined the movie sound of the classic warfare movies Apocalypse Now and Saving Private Ryan. This is an attempt to contribute to a more profound comprehension of the appliance and importance of movie sound. In this context movie sound implies all kinds of sounds within the movies, accept from non-diegetic music. These two movies have been examined by an audio-visual analysis. It's done by auditing the sound and picture content separately, and then combined to audit the same sequence as a whole. Michel Chion, which is the founder of this analysis, calls this method Masking. The sound in this 30 minute sequence was then divided into different zones, where every zone represented a certain main function. These functions are provided to create a stronger connection to the characters, sustain the viewers interest and bring a sense of realism and presence. It seems though the intention with the movies sound is to bring the viewers to the scene in hand, and let it become their reality. To mirror this sense of realism, presence, focus and interest, proves to be the intention from an early stage of the production. This bachelor’s thesis demonstrates a success in their endeavours. Although it can’t confirm whether the movie sound have been utilized in the same manner or if they posess the same functions to warefare movies in general.

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The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

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Johansson, Fredrik (2012). Filmljudets funktioner i dramafilm – En audio-visuell analys av filmen The King´s Speech. Examensuppsats inom Ljudproduktion, Högskolan Dalarna, Akademin för språk och medier, Falun. I denna uppsats undersöktes filmljudet i dramafilmen The King´s Speech. Detta för att ta reda på vilka funktioner filmljudet fyller i de valda sekvenserna ur nämnda film, samt hur ljudet är placerat i filmens flerkanalsmix. Filmen granskades med hjälp av en audio-visuell analys. Denna metod går ut på att ljudet och bilden undersöks separat, för att sedan åter kombineras och analyseras som helhet. Den audio-visuella analysmetod som använts kommer från ljudteoretikern Michel Chion, och kallas Masking. Resultatet av den audio-visuella analysen pekade mot att ljudets huvudsakliga funktioner var att skapa en realistisk skildring av karaktärer och omgivningar, skapa en känsla av närvaro, samt att skapa och bibehålla olika perspektiv i den narrativa världen. Den stora majoriteten av ljud visade sig vara placerade i centerkanalen, medan främst ickediegetisk musik och ambiensljud var placerade i front- och surroundkanalerna. Detta kanalanvändande tycktes gynna de funna funktionerna, främst genom att bidra till känslan av närvaro och realism, genom att omsluta filmpubliken med ambienta ljud.

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This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

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This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

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For the past few decades, researchers have increased our understanding of how sound functions within various audio–visual media formats. With a different focus in mind, this study aims to identify the roles and functions of sound in relation to the game form Audio Games, in order to explore the potential of sound when acting as an autonomous narrative form. Because this is still a relatively unexplored research field, the main purpose of this study is to help establish a theoretical ground and stimulate further research within the field of audio games. By adopting an interdisciplinary approach to the topic, this research relies on theoretical studies, examinations of audio games and contact with the audio game community. In order to reveal the roles of sound, the gathered data is analyzed according to both a contextual and a functional perspective. The research shows that a distinction between the terms ‘function’ and ‘role’ is important when analyzing sound in digital games. The analysis therefore results in the identification of two analytical levels that help define the functions and roles of an entity within a social context, named the Functional and the Interfunctional levels. In addition to successfully identifying three main roles of sound within audio games—each describing the relationship between sound and the entities game system, player and virtual environment—many other issues are also addressed. Consequently, and in accordance with its purpose, this study provides a broad foundation for further research of sound in both audio games and video games.

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This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.