346 resultados para Music genre classification
Resumo:
The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.
Resumo:
The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.
Resumo:
We present the findings of a study into the implementation of explicitly criterion- referenced assessment in undergraduate courses in mathematics. We discuss students' concepts of criterion referencing and also the various interpretations that this concept has among mathematics educators. Our primary goal was to move towards a classification of criterion referencing models in quantitative courses. A secondary goal was to investigate whether explicitly presenting assessment criteria to students was useful to them and guided them in responding to assessment tasks. The data and feedback from students indicates that while students found the criteria easy to understand and useful in informing them as to how they would be graded, it did not alter the way the actually approached the assessment activity.
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This paper describes algorithms that can musically augment the realtime performance of electronic dance music by generating new musical material by morphing. Note sequence morphing involves the algorithmic generation of music that smoothly transitions between two existing musical segments. The potential of musical morphing in electronic dance music is outlined and previous research is summarised; including discussions of relevant music theoretic and algorithmic concepts. An outline and explanation is provided of a novel Markov morphing process that uses similarity measures to construct transition matrices. The paper reports on a ‘focus-concert’ study used to evaluate this morphing algorithm and to compare its output with performances from a professional DJ. Discussions of this trial include reflections on some of the aesthetic characteristics of note sequence morphing. The research suggests that the proposed morphing technique could be effectively used in some electronic dance music contexts.
Resumo:
Music has played an important role in social life for thousands of years, and its varied forms of communication have significantly influenced the types of public services reported in this book. It is now time for practitioners and academics to sing songs of resilience that reinvigorate the public’s understanding of the positive role music can play in all of our lives, and for public services to better resource music projects. The last twenty years have seen major advances in studies of music and its affects on the brain’s neuroplasticity, but as yet no one has managed to provide a comprehensive response to Oliver Sachs’ (2006) question: why does music, for better or worse, have so much power? This chapter seeks to demonstrate the power of those music making experiences that bridge the gap between the physicaland social sciences across commercial, social and cultural contexts.
Resumo:
Many music programs in Australia deliver a United States (US) package created by the Recreational Music-Making Movement, founded by Karl Bruhn and Barry Bittman. This quasi-formal group of music makers, academics and practitioners uses the logic of decentralised global networks to connect with local musicians, offering them benefits associated with their ‘Recreational Music Program’ (RMP). These RMPs encapsulate the broad goals of the movement, developed in the US during the 1980s, and now available as a package, endorsed by the National Association of Music Merchants (NAMM), for music retailers and community organisations to deliver locally (Bittman et al., 2003). High participation rates in RMPs have been historically documented amongst baby boomers with disposable income. Yet the Australian programs increasingly target marginalised groups and associated funding sources, which in turn has lowered the costs of participation. This chapter documents how Australian manifestations of RMPs presently report on the benefits of participation to attract cross-sector funding. It seeks to show the diversity of participants who claim to have developed and accessed resources that improve their capacity for resilience through recreational music performance events. We identify funding issues pertaining to partnerships between local agencies and state governments that have begun to commission such music programs. Our assessment of eight Australian RMPs includes all additional music groups implemented since the first program, their purposes and costs, the skills and coping strategies that participants developed, how organisers have reported on resources, outcomes and attracted funding. We represent these features through a summary table, standard descriptive statistics and commentaries from participants and organisers.
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This presentation discusses some of the general issues relating to the classification of UAS for the purposes of defining and promulgating safety regulations. One possible approach for the definition of a classification scheme for UAS Type Certification Categories reviewed.
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Computers are now being widely used in the making of music and the extent of computer use in the music that we hear is farlarger than most people realise. This paper will discuss how computer technology is used in music, with particular reference to music education.
Resumo:
Participatory sensing enables collection, processing, dissemination and analysis of environmental sensory data by ordinary citizens, through mobile devices. Researchers have recognized the potential of participatory sensing and attempted applying it to many areas. However, participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data quality has become a significant issue. This study proposes using reputation management to classify the gathered data and provide useful information for campaign organizers and data analysts to facilitate their decisions.
Resumo:
Workflow nets, a particular class of Petri nets, have become one of the standard ways to model and analyze workflows. Typically, they are used as an abstraction of the workflow that is used to check the so-called soundness property. This property guarantees the absence of livelocks, deadlocks, and other anomalies that can be detected without domain knowledge. Several authors have proposed alternative notions of soundness and have suggested to use more expressive languages, e.g., models with cancellations or priorities. This paper provides an overview of the different notions of soundness and investigates these in the presence of different extensions of workflow nets.We will show that the eight soundness notions described in the literature are decidable for workflow nets. However, most extensions will make all of these notions undecidable. These new results show the theoretical limits of workflow verification. Moreover, we discuss some of the analysis approaches described in the literature.