6,049 research outputs found

    Effects of substrate and ambient gas on epitaxial growth indium oxide thin films

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    Indium oxide thin films were grown by pulsed electron beam deposition method at 500 °C on c-cut sapphire and (0 0 1) oriented LaAlO3 single crystal substrates in oxygen or argon gas. The effects of ambient gas and substrate symmetry on the growth of indium oxide thin films were studied. Stoichiometric In2O3 films are formed in oxygen, while oxygen deficient In2O2.5 films are grown in argon, with In metallic nanoclusters embedded in a In2O3 matrix (nanocomposite films). In both cases, epitaxial In2O3 films having the bixbyite phase were grown with various orientation relationships, depending upon the substrate symmetry and gas ambient (oxygen or argon). Domain matching epitaxy was used to describe the precise in-plane epitaxial film-substrate relationships. The differences in film texture were correlated to the differences in growth conditions, while the differences in the film properties were correlated to the film oxygen composition

    A reactive system for open terrain navigation: Performance and limitations

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    We describe a core system for autonomous navigation in outdoor natural terrain. The system consists of three parts: a perception module which processes range images to identify untraversable regions of the terrain, a local map management module which maintains a representation of the environment in the vicinity of the vehicle, and a planning module which issues commands to the vehicle controller. Our approach is to use the concept of 'early traversability evaluation', and on the use of reactive planning for generating commands to drive the vehicle. We argue that our approach leads to a robust and efficient navigation system. We illustrate our approach by an experiment in which a vehicle travelled autonomously for one kilometer through unmapped cross-country terrain

    Predictive-State Decoders: Encoding the Future into Recurrent Networks

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    Recurrent neural networks (RNNs) are a vital modeling technique that rely on internal states learned indirectly by optimization of a supervised, unsupervised, or reinforcement training loss. RNNs are used to model dynamic processes that are characterized by underlying latent states whose form is often unknown, precluding its analytic representation inside an RNN. In the Predictive-State Representation (PSR) literature, latent state processes are modeled by an internal state representation that directly models the distribution of future observations, and most recent work in this area has relied on explicitly representing and targeting sufficient statistics of this probability distribution. We seek to combine the advantages of RNNs and PSRs by augmenting existing state-of-the-art recurrent neural networks with Predictive-State Decoders (PSDs), which add supervision to the network's internal state representation to target predicting future observations. Predictive-State Decoders are simple to implement and easily incorporated into existing training pipelines via additional loss regularization. We demonstrate the effectiveness of PSDs with experimental results in three different domains: probabilistic filtering, Imitation Learning, and Reinforcement Learning. In each, our method improves statistical performance of state-of-the-art recurrent baselines and does so with fewer iterations and less data.Comment: NIPS 201

    On the relevance of large scale pulsed-laser deposition: Evidence of structural heterogeneities in ZnO thin films

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    Pulsed-laser deposition is known as a well-suited method for growing thin films of oxide compounds presenting a wide range of functional properties. A limitation of this method for industrial process is the very anisotropic expansion dynamics of the plasma plume, which induces difficulties to grow on large scale films with homogeneous thickness and composition. The specific aspect of the crystalline or orientation uniformity has not been investigated, despite its important role on oxide films properties. In this work, the crystalline parameters and the texture of zinc oxide films are studied as a function of position with respect to the central axis of the plasma plume. We demonstrate the existence of large non-uniformities in the films. The stoichiometry, the lattice parameter, and the distribution of crystallites orientations drastically depend on the position with respect to the plume axis, i.e., on the oblique incidence of the ablated species. The origin of these non-uniformities, in particular, the unexpected tilted orientation of the ZnO c-axis may be attributed to the combined effects of the oblique incidence and of the ratio between oxygen and zinc fluxes reaching the surface of the growing film

    Impacts of the COVID-19 Pandemic on Elementary School Teachers’ Practices and Perceptions Across the Spring and Fall 2020 Semesters

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    Following the closure of schools in the spring 2020 semester due to the COVID-19 pandemic, we developed two surveys to understand how the pandemic affected elementary education in the U.S. First, we distributed a survey at the end of the spring 2020 semester to understand how school closures impacted delivery of instruction. Second, we conducted a follow up survey in November 2020 to determine the nature of instruction provided to students when schools did or did not re-open in Fall 2020 and understand teachers’ perceptions of student learning and achievement during the pandemic. Each survey was sent to a sample of over 9,000 teachers who were randomly selected to be representative of the population of the U.S. Results indicated that many students did not receive direct instruction in academic skills during the spring 2020 semester. Although by late fall 2020 teachers reported broad use of some form of in-person instructional model, teachers indicated that many of their students were not ready to transition to the next grade level and that achievement gaps were larger in fall 2020 than in typical years. These findings have important implications for practices during potential school closures in the future

    A study of 2 GHz electromagnetic wave propagation over optical paths in three geographical regions of the United States

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    Statistical correlation between optical microwave propagation reliability, fade margin, path length, and geographic locatio
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