939 resultados para Statistical Language Model


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The main goal of this work is to build a sketch on how language is used in mathematics classrooms. We specifically try to understand how teachers use language in order to share meanings with their students. We initially present our main intentions, summarizing some studies that are close to our purposes. The two theoretical frameworks which support our study – the Model of Semantic Fields and the Wittgensteinian “games of language” – are then presented and discussed about their similarities and distinctions. Our empirical data are some classroom activities recorded and turned into “clips”. Such clips were transcribed and our analysis was based on these transcriptions. Data analysis – developed according to our theoretical framework – allowed us to build the so-called “events” and, then, comment on some understandings on how language can be used in mathematics classrooms.

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Hypernuclear physics is currently attracting renewed interest, due tornthe important role of hypernuclei spectroscopy rn(hyperon-hyperon and hyperon-nucleon interactions) rnas a unique toolrnto describe the baryon-baryon interactions in a unified way and to rnunderstand the origin of their short-range.rnrnHypernuclear research will be one of the main topics addressed by the {sc PANDA} experimentrnat the planned Facility for Antiproton and Ion Research {sc FAIR}.rnThanks to the use of stored $overline{p}$ beams, copiousrnproduction of double $Lambda$ hypernuclei is expected at thern{sc PANDA} experiment, which will enable high precision $gamma$rnspectroscopy of such nuclei for the first time.rnAt {sc PANDA} excited states of $Xi^-$ hypernuclei will be usedrnas a basis for the formation of double $Lambda$ hypernuclei.rnFor their detection, a devoted hypernuclear detector setup is planned. This setup consists ofrna primary nuclear target for the production of $Xi^{-}+overline{Xi}$ pairs, a secondary active targetrnfor the hypernuclei formation and the identification of associated decay products and a germanium array detector to perform $gamma$ spectroscopy.rnrnIn the present work, the feasibility of performing high precision $gamma$rnspectroscopy of double $Lambda$ hypernuclei at the {sc PANDA} experiment has been studiedrnby means of a Monte Carlo simulation. For this issue, the designing and simulation of the devoted detector setup as well as of the mechanism to produce double $Lambda$ hypernuclei have been optimizedrntogether with the performance of the whole system. rnIn addition, the production yields of double hypernuclei in excitedrnparticle stable states have been evaluated within a statistical decay model.rnrnA strategy for the unique assignment of various newly observed $gamma$-transitions rnto specific double hypernuclei has been successfully implemented by combining the predicted energy spectra rnof each target with the measurement of two pion momenta from the subsequent weak decays of a double hypernucleus.rn% Indeed, based on these Monte Carlo simulation, the analysis of the statistical decay of $^{13}_{Lambda{}Lambda}$B has been performed. rn% As result, three $gamma$-transitions associated to the double hypernuclei $^{11}_{Lambda{}Lambda}$Bern% and to the single hyperfragments $^{4}_{Lambda}$H and $^{9}_{Lambda}$Be, have been well identified.rnrnFor the background handling a method based on time measurement has also been implemented.rnHowever, the percentage of tagged events related to the production of $Xi^{-}+overline{Xi}$ pairs, variesrnbetween 20% and 30% of the total number of produced events of this type. As a consequence, further considerations have to be made to increase the tagging efficiency by a factor of 2.rnrnThe contribution of the background reactions to the radiation damage on the germanium detectorsrnhas also been studied within the simulation. Additionally, a test to check the degradation of the energyrnresolution of the germanium detectors in the presence of a magnetic field has also been performed.rnNo significant degradation of the energy resolution or in the electronics was observed. A correlationrnbetween rise time and the pulse shape has been used to correct the measured energy. rnrnBased on the present results, one can say that the performance of $gamma$ spectroscopy of double $Lambda$ hypernuclei at the {sc PANDA} experiment seems feasible.rnA further improvement of the statistics is needed for the background rejection studies. Moreover, a more realistic layout of the hypernuclear detectors has been suggested using the results of these studies to accomplish a better balance between the physical and the technical requirements.rn

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Am Mainzer Mikrotron können Lambda-Hyperkerne in (e,e'K^+)-Reaktionen erzeugt werden. Durch den Nachweis des erzeugten Kaons im KAOS-Spektrometer lassen sich Reaktionen markieren, bei denen ein Hyperon erzeugt wurde. Die Spektroskopie geladener Pionen, die aus schwachen Zweikörperzerfällen leichter Hyperkerne stammen, erlaubt es die Bindungsenergie des Hyperons im Kern mit hoher Präzision zu bestimmen. Neben der direkten Produktion von Hyperkernen ist auch die Erzeugung durch die Fragmentierung eines hoch angeregten Kontinuumszustands möglich. Dadurch können unterschiedliche Hyperkerne in einem Experiment untersucht werden. Für die Spektroskopie der Zerfallspionen stehen hochauflösende Magnetspektrometer zur Verfügung. Um die Grundzustandsmasse der Hyperkerne aus dem Pionimpuls zu berechnen, ist es erforderlich, dass das Hyperfragment vor dem Zerfall im Target abgebremst wird. Basierend auf dem bekannten Wirkungsquerschnitt der elementaren Kaon-Photoproduktion wurde eine Berechnung der zu erwartenden Ereignisrate vorgenommen. Es wurde eine Monte-Carlo-Simulation entwickelt, die den Fragmentierungsprozess und das Abbremsen der Hyperfragmente im Target beinhaltet. Diese nutzt ein statistisches Aufbruchsmodell zur Beschreibung der Fragmentierung. Dieser Ansatz ermöglicht für Wasserstoff-4-Lambda-Hyperkerne eine Vorhersage der zu erwartenden Zählrate an Zerfallspionen. In einem Pilotexperiment im Jahr 2011 wurde erstmalig an MAMI der Nachweis von Hadronen mit dem KAOS-Spektrometer unter einem Streuwinkel von 0° demonstriert, und koinzident dazu Pionen nachgewiesen. Es zeigte sich, dass bedingt durch die hohen Untergrundraten von Positronen in KAOS eine eindeutige Identifizierung von Hyperkernen in dieser Konfiguration nicht möglich war. Basierend auf diesen Erkenntnissen wurde das KAOS-Spektrometer so modifiziert, dass es als dedizierter Kaonenmarkierer fungierte. Zu diesem Zweck wurde ein Absorber aus Blei im Spektrometer montiert, in dem Positronen durch Schauerbildung abgestoppt werden. Die Auswirkung eines solchen Absorbers wurde in einem Strahltest untersucht. Eine Simulation basierend auf Geant4 wurde entwickelt mittels derer der Aufbau von Absorber und Detektoren optimiert wurde, und die Vorhersagen über die Auswirkung auf die Datenqualität ermöglichte. Zusätzlich wurden mit der Simulation individuelle Rückrechnungsmatrizen für Kaonen, Pionen und Protonen erzeugt, die die Wechselwirkung der Teilchen mit der Bleiwand beinhalteten, und somit eine Korrektur der Auswirkungen ermöglichen. Mit dem verbesserten Aufbau wurde 2012 eine Produktionsstrahlzeit durchgeführt, wobei erfolgreich Kaonen unter 0° Streuwinkel koninzident mit Pionen aus schwachen Zerfällen detektiert werden konnten. Dabei konnte im Impulsspektrum der Zerfallspionen eine Überhöhung mit einer Signifikanz, die einem p-Wert von 2,5 x 10^-4 entspricht, festgestellt werden. Diese Ereignisse können aufgrund ihres Impulses, den Zerfällen von Wasserstoff-4-Lambda-Hyperkernen zugeordnet werden, wobei die Anzahl detektierter Pionen konsistent mit der berechneten Ausbeute ist.

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In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.

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In this paper we propose a new system that allows reliable acetabular cup placement when the THA is operated in lateral approach. Conceptually it combines the accuracy of computer-generated patient-specific morphology information with an easy-to-use mechanical guide, which effectively uses natural gravity as the angular reference. The former is achieved by using a statistical shape model-based 2D-3D reconstruction technique that can generate a scaled, patient-specific 3D shape model of the pelvis from a single conventional anteroposterior (AP) pelvic X-ray radiograph. The reconstructed 3D shape model facilitates a reliable and accurate co-registration of the mechanical guide with the patient’s anatomy in the operating theater. We validated the accuracy of our system by conducting experiments on placing seven cups to four pelvises with different morphologies. Taking the measurements from an image-free navigation system as the ground truth, our system showed an average accuracy of 2.1 ±0.7 o for inclination and an average accuracy of 1.2 ±1.4 o for anteversion.

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Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.

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Computer assisted orthopaedic surgery (CAOS) technology has recently been introduced to overcome problems resulting from acetabular component malpositioning in total hip arthroplasty. Available navigation modules can conceptually be categorized as computer tomography (CT) based, fluoroscopy based, or image-free. The current study presents a comprehensive accuracy analysis on the computer assisted placement accuracy of acetabular cups. It combines analyses using mathematical approaches, in vitro testing environments, and an in vivo clinical trial. A hybrid navigation approach combining image-free with fluoroscopic technology was chosen as the best compromise to CT-based systems. It introduces pointer-based digitization for easily assessable points and bi-planar fluoroscopy for deep-seated landmarks. From the in vitro data maximum deviations were found to be 3.6 degrees for inclination and 3.8 degrees for anteversion relative to a pre-defined test position. The maximum difference between intraoperatively calculated cup inclination and anteversion with the postoperatively measured position was 4 degrees and 5 degrees, respectively. These data coincide with worst cases scenario predictions applying a statistical simulation model. The proper use of navigation technology can reduce variability of cup placement well within the surgical safe zone. Surgeons have to concentrate on a variety of error sources during the procedure, which may explain the reported strong learning curves for CAOS technologies.

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Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

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The highly pathogenic avian influenza (HPAI) H5N1 virus that emerged in southern China in the mid-1990s has in recent years evolved into the first HPAI panzootic. In many countries where the virus was detected, the virus was successfully controlled, whereas other countries face periodic reoccurrence despite significant control efforts. A central question is to understand the factors favoring the continuing reoccurrence of the virus. The abundance of domestic ducks, in particular free-grazing ducks feeding in intensive rice cropping areas, has been identified as one such risk factor based on separate studies carried out in Thailand and Vietnam. In addition, recent extensive progress was made in the spatial prediction of rice cropping intensity obtained through satellite imagery processing. This article analyses the statistical association between the recorded HPAI H5N1 virus presence and a set of five key environmental variables comprising elevation, human population, chicken numbers, duck numbers, and rice cropping intensity for three synchronous epidemic waves in Thailand and Vietnam. A consistent pattern emerges suggesting risk to be associated with duck abundance, human population, and rice cropping intensity in contrast to a relatively low association with chicken numbers. A statistical risk model based on the second epidemic wave data in Thailand is found to maintain its predictive power when extrapolated to Vietnam, which supports its application to other countries with similar agro-ecological conditions such as Laos or Cambodia. The model’s potential application to mapping HPAI H5N1 disease risk in Indonesia is discussed.

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As object-oriented languages are extended with novel modularization mechanisms, better underlying models are required to implement these high-level features. This paper describes CELL, a language model that builds on delegation-based chains of object fragments. Composition of groups of cells is used: 1) to represent objects, 2) to realize various forms of method lookup, and 3) to keep track of method references. A running prototype of CELL is provided and used to realize the basic kernel of a Smalltalk system. The paper shows, using several examples, how higher-level features such as traits can be supported by the lower-level model.

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Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

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We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.