Influencing the perceived emotions of music with intent

Music is an immensely powerful affective medium that pervades our everyday life. With ever advancing technology, the reproduction and application of music for emotive and information transfer purposes has never been more prevalent. In this paper we introduce a rule-based engine for influencing the perceived emotions of music. Based on empirical music psychology, we attempt to formalise the relationship between musical elements and their perceived emotion. We examine the modification to structural aspects of music to allow for a graduated transition between perceived emotive states. This engine is intended to provide music reproduction systems with a finer grained control over this affective medium; where perceived musical emotion can be influenced with intent. This intent comes from both an external application and the audience. Using a series of affective computing technologies, an audience’s response metrics and attitudes can be incorporated to model this intent. A generative feedback loop is set up between the external application, the influencing process and the audience’s response to this, which together shape the modification of musical structure. The effectiveness of our rule system for influencing perceived musical emotion was examined in earlier work, with a small test study providing generally encouraging results.

Virtual teachers: Negotiating new spaces for teaching bodies

In 2002, the authors reviewed the educational performance of a state education department virtual schooling service during its first 2 years of operation, 2000-2001 (Pendergast, Kapitzke, Land, Luke, & Bahr, 2002). Established by Education Queensland, the Virtual Schooling Service (VSS) utilises synchronous and asynchronous online delivery strategies and a range of learning technologies to support students at a distance (see http://education.qld.gov.au/learningplace/vss/). The service commenced with a focus on senior secondary subjects. At present, there are over 700 students in 89 schools across the state enrolled in 9 subjects. In response to the recommendations of the study, a series of professional development activities were conducted with the VSS teachers by the authors. Opportunity for critical reflection was provided, including consideration of the ways in which the teachers were developing as a learning community. Some data, including visual representations, were collected from participants with the purpose of understanding how VSS teachers are constructed as professionals. This study compares and contrasts that data with self-constructions of teacher professionals in other fields.

Termination of real-time programs: Definitely, definitely not, or maybe

Real-time control programs are often used in contexts where (conceptually) they run forever. Repetitions within such programs (or their specifications) may either (i) be guaranteed to terminate, (ii) be guaranteed to never terminate (loop forever), or (iii) may possibly terminate. In dealing with real-time programs and their specifications, we need to be able to represent these possibilities, and define suitable refinement orderings. A refinement ordering based on Dijkstra's weakest precondition only copes with the first alternative. Weakest liberal preconditions allow one to constrain behaviour provided the program terminates, which copes with the third alternative to some extent. However, neither of these handles the case when a program does not terminate. To handle this case a refinement ordering based on relational semantics can be used. In this paper we explore these issues and the definition of loops for real-time programs as well as corresponding refinement laws.

Maximum-likelihood noncoherent lattice decoding of QAM

We present a novel, maximum-likelihood (ML), lattice-decoding algorithm for noncoherent block detection of QAM signals. The computational complexity is polynomial in the block length; making it feasible for implementation compared with the exhaustive search ML detector. The algorithm works by enumerating the nearest neighbor regions for a plane defined by the received vector; in a conceptually similar manner to sphere decoding. Simulations show that the new algorithm significantly outperforms existing approaches