Sökning: "ensemble"

Visar resultat 1 - 5 av 245 avhandlingar innehållade ordet ensemble.

1. 1. Free Ensemble Improvisation

   Författare :Harald Stenström; Göteborgs universitet; Göteborgs universitet; Gothenburg University; []
   Nyckelord :aleatorics; artistic research; attractor state; central tone; chaotic systems; collective understanding; comprovisation; conceptual model; directed motion; ensemble size; feedback and feedforward; free ensemble improvisation; gesture; importance of rhythm; indeterminacy; interactional skill; listening skill; musical evaluation; musical interaction; musical maturity; musical chemistry; musical interpretation; musical composition; non-idiomatic improvisation; rhythmic flow; sound properties; stylistic influences;

   Sammanfattning : The aim of this doctoral project has been to study so-called non-idiomatic improvisation in ensembles consisting of two or three musicians who play together without any restrictions regarding style or genre and without having predetermined what is to be played or how they should play. The background to this thesis has been the author’s own free improvising, which he has pursued since 1974, and the questions that have arisen whilst music-making. LÄS MER

3. 2. Utilizing Diversity and Performance Measures for Ensemble Creation

   Författare :Tuve Löfström; Högskolan i Skövde; []
   Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; Ensemble Learning; Machine Learning; Diversity; Artificial Neural Networks; Data Mining; Information Fusion; Computer science; Datavetenskap; Teknik; Technology; ensemble learning; machine learning; diversity; artificial neural networks; information fusion; Computer Science; data mining;

   Sammanfattning : An ensemble is a composite model, aggregating multiple base models into one predictive model. An ensemble prediction, consequently, is a function of all included base models. Both theory and a wealth of empirical studies have established that ensembles are generally more accurate than single predictive models. LÄS MER

4. 3. Spelets regler : En studie av ensembleundervisning i klass

   Författare :Anna Backman Bister; Cecilia Hultberg; Sidsel Karlsen; Stockholms universitet; []
   Nyckelord :HUMANITIES; HUMANIORA; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SAMHÄLLSVETENSKAP; HUMANIORA; SOCIAL SCIENCES; HUMANITIES; individually adapted education; peer-teaching and -learning; ensemble teaching; music class teaching; musikpedagogik; Music Education;

   Sammanfattning : The aim of this study is to explore criteria characterizing music teacher’s strategies when trying to adapt their teaching to individual students. The interaction of three music teachers with their students was explored in case studies in different parts of Sweden (a pre-study, and the main study consisting of two parallel studies). LÄS MER

5. 4. Optimal weather routing using ensemble weather forecasts

   Författare :Lukas Skoglund; Jakob Kuttenkeuler; Anders Rosén; Wengang Mao; KTH; []
   Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; route optimization; ensemble weather forecasts;

   Sammanfattning : Ships small and large all battle the elements when crossing the worlds oceans.  As such, ships are designed to operate in situations with high speed winds and heavy waves.  There are however limits to what any ship can handle safely and it is thus important to avoid the worst weather systems as much as possible. LÄS MER

7. 5. Nonconformity Measures and Ensemble Strategies : An Analysis of Conformal Predictor Efficiency and Validity

   Författare :Henrik Linusson; Ulf Johansson; Henrik Boström; Alexander Gammerman; Stockholms universitet; []
   Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Data Science; Machine Learning; Conformal Prediction; Classification; Regression; Computer and Systems Sciences; data- och systemvetenskap;

   Sammanfattning : Conformal predictors are a family of predictive models that associate with each of their predictions a measure of confidence, enabling them to provide quantitative information about their own trustworthiness. In risk-laden machine learning applications, where bad predictions may lead to economic loss, personal injury, or worse, such inherent quality control appears highly beneficial, if not required. LÄS MER