978 resultados para open video tools


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The use of stones to crack open encapsulated fruit is widespread among wild bearded capuchin monkeys (Cebus libidinosus) inhabiting savanna-like environments. Some populations in Serra da Capivara National Park (Piaui, Brazil), though, exhibit a seemingly broader toolkit, using wooden sticks as probes, and employing stone tools for a variety of purposes. Over the course of 701.5 hr of visual contact of two wild capuchin groups we recorded 677 tool use episodes. Five hundred and seventeen of these involved the use of stones, and 160 involved the use of sticks (or other plant parts) as probes to access water, arthropods, or the contents of insects` nests. Stones were mostly used as ""hammers""-not only to open fruit or seeds, or smash other food items, but also to break dead wood, conglomerate rock, or cement in search of arthropods, to dislodge bigger stones, and to pulverize embedded quartz pebbles (licking, sniffing, or rubbing the body with the powder produced). Stones also were used in a ""hammer-like"" fashion to loosen the soil for digging out roots and arthropods, and sometimes as ""hoes"" to pull the loosened soil. In a few cases, we observed the re-utilization of stone tools for different purposes (N = 3), or the combined use of two tools-stones and sticks (N = 4) or two stones (N = 5), as sequential or associative tools. On three occasions, the monkeys used smaller stones to loosen bigger quartz pebbles embedded in conglomerate rock, which were subsequently used as tools. These could be considered the first reports of secondary tool use by wild capuchin monkeys. Am. J. Primatol. 71:242-251, 2009. (c) 2008 Wiley-Liss, Inc.

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Appreciation of objects` affordances and planning is a hallmark of human technology. Archeological evidence suggests that Pliocene hominins selected raw material for tool making [1, 2]. Stone pounding has been considered a precursor to tool making [3, 4], and tool use by living primates provides insight into the origins of material selection by human ancestors. No study has experimentally investigated selectivity of stone tools in wild animals, although chimpanzees appear to select stones according to properties of different nut species [5, 6]. We recently discovered that wild capuchins with terrestrial habits [7] use hammers to crack open nuts on anvils [8-10]. As for chimpanzees, examination of anvil sites suggests stone selectivity [11], but indirect evidence cannot prove it. Here, we demonstrate that capuchins, which last shared a common ancestor with humans 35 million years ago, faced with stones differing in functional features (friability and weight) choose, transport, and use the effective stone to crack nuts. Moreover, when weight cannot be judged by visual attributes, capuchins act to gain information to guide their selection. Thus, planning actions and intentional selection of tools is within the ken of monkeys and similar to the tool activities of hominins and apes.

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This article describes the design, implementation, and experiences with AcMus, an open and integrated software platform for room acoustics research, which comprises tools for measurement, analysis, and simulation of rooms for music listening and production. Through use of affordable hardware, such as laptops, consumer audio interfaces and microphones, the software allows evaluation of relevant acoustical parameters with stable and consistent results, thus providing valuable information in the diagnosis of acoustical problems, as well as the possibility of simulating modifications in the room through analytical models. The system is open-source and based on a flexible and extensible Java plug-in framework, allowing for cross-platform portability, accessibility and experimentation, thus fostering collaboration of users, developers and researchers in the field of room acoustics.

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Juvenile nasopharyngeal angiofibroma is a rare benign vascular tumor of the nasopharynx. Although the treatment of choice is surgery, there is no consensus on what is the best approach. Aim: To compare surgical time and intraoperative transfusion requirements in patients undergoing endoscopic surgery versus open / combined and relate the need for transfusion during surgery with the time between embolization and surgery. Material and Methods: Study descriptive, analytical, retrospective study with a quantitative approach developed in the Otorhinolaryngology department of a teaching hospital. Analyzed 37 patients with angiofibroma undergoing surgical treatment. Data obtained from medical records. Analyzed with tests of the Fisher-Freeman-Halton and Games-Howell. Was considered significant if p <0.05. Study design: Historical cohort study with cross-sectional. Results: The endoscopic approach had a shorter operative time (p <0.0001). There is less need for transfusion during surgery when the embolization was performed on the fourth day. Conclusion: This suggests that the period ahead would be ideal to perform the process of embolization and endoscopic surgery by demanding less time would be associated with a lower morbidity. This study, however, failed to show which group of patients according to tumor stage would benefit from specific technical.

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This work is supported by Brazilian agencies Fapesp, CAPES and CNPq

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Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

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El Grupo de Trabajo Open Access y Derechos de Autor de la Biblioteca Universitaria pretende con este video promocionar el movimiento de Acceso Abierto (Open Access) con el fin de concienciar a la comunidad universitaria de la importancia de dar mayor visibilidad a la producción científica y académica generada por la misma.

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[EN] This abstract describes the development of a wildfire forecasting plugin using Capaware. Capaware is designed as an easy to use open source framework to develop 3D graphics applications over large geographic areas offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community.

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In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

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[EN]Parliamentary websites have become one of the most important windows for citizens and media to follow the activities of their legislatures and to hold parliaments to account. Therefore, most parliamentary institutions aim to provide new multimedia solutions capable of displaying video fragments on demand on plenary activities. This paper presents a multimedia system for parliamentary institutions to produce video fragments on demand through a website with linked information and public feedback that helps to explain the content shown in these fragments. A prototype implementation has been developed for the Canary Islands Parliament (Spain) and shows how traditional parliamentary streaming systems can be enhanced by the use of semantics and computer vision for video analytics...

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In questa tesi viene affrontato il tema del tracciamento video, analizzando le principali tecniche, metodologie e strumenti per la video analytics. L'intero lavoro, è stato svolto interamente presso l'azienda BitBang, dal reperimento di informazioni e materiale utile, fino alla stesura dell'elaborato. Nella stessa azienda ho avuto modo di svolgere il tirocinio, durante il quale ho approfondito gli aspetti pratici della web e video analytics, osservando il lavoro sul campo degli specialisti del settore e acquisendo familiarità con gli strumenti di analisi dati tramite l'utilizzo delle principali piattaforme di web analytics. Per comprendere a pieno questo argomento, è stato necessario innanzitutto conoscere la web analytics di base. Saranno illustrate quindi, le metodologie classiche della web analytics, ovvero come analizzare il comportamento dei visitatori nelle pagine web con le metriche più adatte in base alle diverse tipologie di business, fino ad arrivare alla nuova tecnica di tracciamento eventi. Questa nasce subito dopo la diffusione nelle pagine dei contenuti multimediali, i quali hanno portato a un cambiamento nelle modalità di navigazione degli utenti e, di conseguenza, all'esigenza di tracciare le nuove azioni generate su essi, per avere un quadro completo dell'esperienza dei visitatori sul sito. Non sono più sufficienti i dati ottenuti con i tradizionali metodi della web analytics, ma è necessario integrarla con tecniche nuove, indispensabili se si vuole ottenere una panoramica a 360 gradi di tutto ciò che succede sul sito. Da qui viene introdotto il tracciamento video, chiamato video analytics. Verranno illustrate le principali metriche per l'analisi, e come sfruttarle al meglio in base alla tipologia di sito web e allo scopo di business per cui il video viene utilizzato. Per capire in quali modi sfruttare il video come strumento di marketing e analizzare il comportamento dei visitatori su di esso, è necessario fare prima un passo indietro, facendo una panoramica sui principali aspetti legati ad esso: dalla sua produzione, all'inserimento sulle pagine web, i player per farlo, e la diffusione attraverso i siti di social netwok e su tutti i nuovi dispositivi e le piattaforme connessi nella rete. A questo proposito viene affrontata la panoramica generale di approfondimento sugli aspetti più tecnici, dove vengono mostrate le differenze tra i formati di file e i formati video, le tecniche di trasmissione sul web, come ottimizzare l'inserimento dei contenuti sulle pagine, la descrizione dei più famosi player per l'upload, infine un breve sguardo sulla situazione attuale riguardo alla guerra tra formati video open source e proprietari sul web. La sezione finale è relativa alla parte più pratica e sperimentale del lavoro. Nel capitolo 7 verranno descritte le principali funzionalità di due piattaforme di web analytics tra le più utilizzate, una gratuita, Google Analytics e una a pagamento, Omniture SyteCatalyst, con particolare attenzione alle metriche per il tracciamento video, e le differenze tra i due prodotti. Inoltre, mi è sembrato interessante illustrare le caratteristiche di alcune piattaforme specifiche per la video analytics, analizzando le più interessanti funzionalità offerte, anche se non ho avuto modo di testare il loro funzionamento nella pratica. Nell'ultimo capitolo vengono illustrate alcune applicazioni pratiche della video analytics, che ho avuto modo di osservare durante il periodo di tirocinio e tesi in azienda. Vengono descritte in particolare le problematiche riscontrate con i prodotti utilizzati per il tracciamento, le soluzioni proposte e le questioni che ancora restano irrisolte in questo campo.

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Con questa dissertazione di tesi miro ad illustrare i risultati della mia ricerca nel campo del Semantic Publishing, consistenti nello sviluppo di un insieme di metodologie, strumenti e prototipi, uniti allo studio di un caso d‟uso concreto, finalizzati all‟applicazione ed alla focalizzazione di Lenti Semantiche (Semantic Lenses).

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La neuroriabilitazione è un processo attraverso cui individui affetti da patologie neurologiche mirano al conseguimento di un recupero completo o alla realizzazione del loro potenziale ottimale benessere fisico, mentale e sociale. Elementi essenziali per una riabilitazione efficace sono: una valutazione clinica da parte di un team multidisciplinare, un programma riabilitativo mirato e la valutazione dei risultati conseguiti mediante misure scientifiche e clinicamente appropriate. Obiettivo principale di questa tesi è stato sviluppare metodi e strumenti quantitativi per il trattamento e la valutazione motoria di pazienti neurologici. I trattamenti riabilitativi convenzionali richiedono a pazienti neurologici l’esecuzione di esercizi ripetitivi, diminuendo la loro motivazione. La realtà virtuale e i feedback sono in grado di coinvolgerli nel trattamento, permettendo ripetibilità e standardizzazione dei protocolli. È stato sviluppato e valutato uno strumento basato su feedback aumentati per il controllo del tronco. Inoltre, la realtà virtuale permette l’individualizzare il trattamento in base alle esigenze del paziente. Un’applicazione virtuale per la riabilitazione del cammino è stata sviluppata e testata durante un training su pazienti di sclerosi multipla, valutandone fattibilità e accettazione e dimostrando l'efficacia del trattamento. La valutazione quantitativa delle capacità motorie dei pazienti viene effettuata utilizzando sistemi di motion capture. Essendo il loro uso nella pratica clinica limitato, una metodologia per valutare l’oscillazione delle braccia in soggetti parkinsoniani basata su sensori inerziali è stata proposta. Questi sono piccoli, accurati e flessibili ma accumulano errori durante lunghe misurazioni. È stato affrontato questo problema e i risultati suggeriscono che, se il sensore è sul piede e le accelerazioni sono integrate iniziando dalla fase di mid stance, l’errore e le sue conseguenze nella determinazione dei parametri spaziali sono contenuti. Infine, è stata presentata una validazione del Kinect per il tracking del cammino in ambiente virtuale. Risultati preliminari consentono di definire il campo di utilizzo del sensore in riabilitazione.

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Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.

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BACKGROUND: Physiologic data display is essential to decision making in critical care. Current displays echo first-generation hemodynamic monitors dating to the 1970s and have not kept pace with new insights into physiology or the needs of clinicians who must make progressively more complex decisions about their patients. The effectiveness of any redesign must be tested before deployment. Tools that compare current displays with novel presentations of processed physiologic data are required. Regenerating conventional physiologic displays from archived physiologic data is an essential first step. OBJECTIVES: The purposes of the study were to (1) describe the SSSI (single sensor single indicator) paradigm that is currently used for physiologic signal displays, (2) identify and discuss possible extensions and enhancements of the SSSI paradigm, and (3) develop a general approach and a software prototype to construct such "extended SSSI displays" from raw data. RESULTS: We present Multi Wave Animator (MWA) framework-a set of open source MATLAB (MathWorks, Inc., Natick, MA, USA) scripts aimed to create dynamic visualizations (eg, video files in AVI format) of patient vital signs recorded from bedside (intensive care unit or operating room) monitors. Multi Wave Animator creates animations in which vital signs are displayed to mimic their appearance on current bedside monitors. The source code of MWA is freely available online together with a detailed tutorial and sample data sets.