Online composition: strategies and processes during collaborative electroacoustic composition

This pilot study analysed the learning strategies of advanced students and professional electroacoustic composers engaged in creating new musical pieces through online collaboration. The participants were divided into three groups and interacted in a virtual setting using synchronous (chat and Skype) and asynchronous tools (forum, compositional software) to perform the compositional activities. A multiple case study design was used to describe and interpret the actions of the participants. Forum discussions, Skype dialogues and e-mail exchanges were examined to explore the participants’ interactions and understand their actions during the online activities. Individual semi-structured interviews focusing on the processes and working approaches were conducted. The following themes were considered for the analysis of the collaborative compositional activity: working approach, relational model, leadership, organisation and compositional process. The participants effectively completed the compositional activities on the online platform, and based on the results, the following phases emerged as: (a) context definition; (b) planning/organising; (c) experimenting/generating musical ideas; (d) constructing and (e) evaluating. The findings are discussed regarding the educational implications of developing didactic activities based on collaborative composition.

Run-Time Compositional Software Platform for Autonomous NXT Robots

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications' structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.

Run-Time Compositional Software Platform for Autonomous NXT Robots

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications’ structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.

Run-Time Compositional Software Platform for Autonomous NXT Robots

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications’ structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.