160 resultados para collaborative piano


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Agitate Piano Short is an instrumental piece featuring some experimental sounds (a crystal wine glass being tapped and a plastic wrapper being ripped and processed) and more traditional sounds piano/guitar and synths (several pads and a drum beat) put together to create an atmosphere of tension. Good for cinema type projects.

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A composition written on the piano and accompanied by synth strings; a light, elegant and beautiful journey.

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A composition written on the piano; a light, elegant and beautiful journey.

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An elegant piano solo.

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and on is a short instrumental featuring a nylon stringed acoustic guitar with an echo, chorus and tap reverb added to the tail, piano, and two synth pads.

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Just over a minute long this piano arpeggio plays out a joyful melody and dramatic timpani, cymbals and vocal pads assist the journey.

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A stinger featuring piano arpeggio in dramatic fashion with timpani, cymbals and vocal pads.

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Atmos (Piano and Guitar) is a short instrumental with piano and guitar.

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This audio features vocals, piano, strings, synth and bells a curious and unique piece with a light feel.

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Collaborative filtering is an effective recommendation technique wherein the preference of an individual can potentially be predicted based on preferences of other members. Early algorithms often relied on the strong locality in the preference data, that is, it is enough to predict preference of a user on a particular item based on a small subset of other users with similar tastes or of other items with similar properties. More recently, dimensionality reduction techniques have proved to be equally competitive, and these are based on the co-occurrence patterns rather than locality. This paper explores and extends a probabilistic model known as Boltzmann Machine for collaborative filtering tasks. It seamlessly integrates both the similarity and cooccurrence in a principled manner. In particular, we study parameterisation options to deal with the ordinal nature of the preferences, and propose a joint modelling of both the user-based and item-based processes. Experiments on moderate and large-scale movie recommendation show that our framework rivals existing well-known methods.

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Ranking is an important task for handling a large amount of content. Ideally, training data for supervised ranking would include a complete rank of documents (or other objects such as images or videos) for a particular query. However, this is only possible for small sets of documents. In practice, one often resorts to document rating, in that a subset of documents is assigned with a small number indicating the degree of relevance. This poses a general problem of modelling and learning rank data with ties. In this paper, we propose a probabilistic generative model, that models the process as permutations over partitions. This results in super-exponential combinatorial state space with unknown numbers of partitions and unknown ordering among them. We approach the problem from the discrete choice theory, where subsets are chosen in a stagewise manner, reducing the state space per each stage significantly. Further, we show that with suitable parameterisation, we can still learn the models in linear time. We evaluate the proposed models on two application areas: (i) document ranking with the data from the recently held Yahoo! challenge, and (ii) collaborative filtering with movie data. The results demonstrate that the models are competitive against well-known rivals.

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This study reports on the effect of different levels of proficiency on the students' achievements in collaborative learning instruction among 30 Persian-speaking EFL college students. Having been divided into dyads with different levels of proficiency, these subjects participated in nine sessions of collaborative instruction based on the form focused collaborative text-editing task. The results of this study are obtained through the analyses of the proficiency gains in formal aspects of language in text-editing pre and post-tests and text-reconstruction post-test. The study highlights the significant effect of this type of instruction on more proficient students. Reasons provided in this study are the language analytic ability of the students, learning styles and strategies, and motivation. The findings of this study are helpful to teachers of the classes with heterogeneous language proficiency.

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Summary: Hip fractures are a significant cause of morbidity and mortality worldwide and the burden of disability associated with hip fractures globally vindicates the need for high-quality research to advance the care of patients with hip fractures. Historically, large, multi-centre randomized controlled trials have been rare in the orthopaedic trauma literature. Similar to other medical specialties, orthopaedic research is currently undergoing a paradigm shift from single centre initiatives to larger collaborative groups. This is evident with the establishment of several collaborative groups in Canada, in the United States, and in Europe, which has proven that multi-centre trials can be extremely successful in orthopaedic trauma research.

Despite ever increasing literature on the topic of his fractures, the optimal treatment of hip ftractures remains unknown and controversial. To resolve this controversy large multi-national collaborative randomized controlled trials are required. In 2005, the International Hip Fracture Research Collaborative was officially established following funding from the Canadian Institute of Health Research International Oppurtunity Program with the mandate of resolving controversies in hip fracture management. This manuscript will describe the need, the information, the organization, and the accomplishments to date of the International Hip Fracture Research Collaborative.

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The current global economic instability and the vulnerability of small nations provide the impetus for greater integration between the countries of the South Pacific region. This exercise is critical for their survival. Past efforts of regional integration in the South Pacific have mostly failed. However, today’s IT collaborative capabilities provide the opportunity to develop a shared IT infrastructure to facilitate integration in the South Pacific. In developing an IT-backed model of regional integration, this study identifies and reports on the antecedents of the current stage for integration in the Pacific. We conducted interviews with twenty five individuals from various sectors and find that while most respondents were optimistic about the potential of IT-backed regional integration, significant challenges exists. The study identifies and discusses these challenges providing policy implications to stakeholders in the regional integration process. The findings will assist in suggesting a model of regional integration 2.0 for the Pacific region.