Compositional and Performance Mapping in Computer Chamber Music: A Case Study

The mapping problem is inherent to digital musical instruments (DMIs), which require, at the very least, an association between physical gestures and digital synthesis algorithms to transform human bodily performance into sound. This article considers the DMI mapping problem in the context of the creation and performance of a heterogeneous computer chamber music piece, a trio for violin, biosensors, and computer. Our discussion situates the DMI mapping problem within the broader set of interdependent musical interaction issues that surfaced during the composition and rehearsal of the trio. Through descriptions of the development of the piece, development of the hardware and software interfaces, lessons learned through rehearsal, and self-reporting by the participants, the rich musical possibilities and technical challenges of the integration of digital musical instruments into computer chamber music are demonstrated.

Morphology dependence of the dielectric properties of epitaxial BaTiO3 films and epitaxial BaTiO3/SrTiO3 multilayers

Epitaxial BaTiO3 films and epitaxial BaTiO3/SrTiO3 multilayers were grown by pulsed laser deposition on vicinal surfaces of (001)-oriented Nb-doped SrTiO3 (SrTiO3:Nb) single-crystal substrates. Atomic force microscopy was used to investigate the surface topography of the deposited films. The morphology of the films, of the BaTiO3/SrTiO3 interfaces, and of the column boundaries was investigated by cross-sectional high-resolution transmission electron microscopy. Measurements of the dielectric properties were performed by comparing BaTiO3 films and BaTiO3/SrTiO3 multilayers of different numbers of individual layers, but equal overall thickness. The dielectric loss saturates for a thickness above 300 nm and linearly decreases with decreasing film thickness below a thickness of 75 nm. At the same thickness of 75 nm, the thickness dependence of the dielectric constant also exhibits a change in the linear slope both for BaTiO3 films and BaTiO3/SrTiO3 multilayers. This behaviour is explained by the change observed in the grain morphology at a thickness of 75 nm. For the thickness dependence of the dielectric constant, two phenomenological models are considered, viz. a 'series-capacitor' model and a 'dead-layer' model.

Site symmetry dependence of repulsive interactions between chemisorbed oxygen atoms on Pt{100}-(1x1)

Ab initio total energy calculations using density functional theory with the generalized gradient approximation have been performed for the chemisorption of oxygen atoms on a Pt{100}-(1 x 1) slab. Binding energies for the adsorption of oxygen on different high-symmetry sites are presented. The bridge site is the most stable at a coverage of 0.5 ML, followed by the fourfold hollow site. The atop site is the least stable. This finding is rationalized by analyzing the ''local structures'' formed upon oxygen chemisorption. The binding energies and heats of adsorption at different oxygen coverages show that pairwise repulsive interactions are considerably stronger between oxygen atoms occupying fourfold sites than those occupying bridge sites. Analysis of the partial charge densities associated with Bloch states demonstrates that the O-Pt bond is considerably more localized at the bridge site. These effects cause a sharp drop in the heats of adsorption for oxygen on hollow sites when the coverage is increased from 0.25 to 0.5 ML. Mixing between oxygen p orbitals and Pt d orbitals can be observed over the whole metal d-band energy range.

Novel Panel Cointegration Tests Emending for Cross-Section Dependence with N Fixed

In this paper, we propose new cointegration tests for single equations and panels. Inboth cases, the asymptotic distributions of the tests, which are derived with N fixed andT → ∞, are shown to be standard normals. The effects of serial correlation and crosssectionaldependence are mopped out via long-run variances. An effective bias correctionis derived which is shown to work well in finite samples; particularly when N is smallerthan T. Our panel tests are robust to possible cointegration across units.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Artificial neural network model to predict compositional viscosity over a broad range of temperatures

The objective of this study is to provide an alternative model approach, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of room temperature ionic liquids (in short as ILs) [C _n-mim] [NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity over a wide range of temperatures and more complex viscosity compositions, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. © 2010 IEEE.

Composing with Graphics: Revealing the Compositional Process through Performance.

The research presented here is product of a practice-based process that primarily generates knowledge through collaboration and exchange in performance situations. This collaboration and exchange with various musicians over a period of five years that constitutes a body of practice that is here reflected upon. The paper focuses on non-instructional graphic scores and presents some insights based on performances of works by the author. We address how composition processes are revealed in graphic scores by looking at the conditions of decision making at the point of preparing a performance. We argue that three key elements are at play in the interpretation of these types of graphic scores: performance practice, mapping and musical form. By reflecting particularly on the work Cipher Series (Rebelo, 2010) we offer insights into the strategies for approaching the performance of graphic scores that go beyond symbolic codification.

Compositional Data Analysis in Forensic Geoscience

Statistics are regularly used to make some form of comparison between trace evidence or deploy the exclusionary principle (Morgan and Bull, 2007) in forensic investigations. Trace evidence are routinely the results of particle size, chemical or modal analyses and as such constitute compositional data. The issue is that compositional data including percentages, parts per million etc. only carry relative information. This may be problematic where a comparison of percentages and other constraint/closed data is deemed a statistically valid and appropriate way to present trace evidence in a court of law. Notwithstanding an awareness of the existence of the constant sum problem since the seminal works of Pearson (1896) and Chayes (1960) and the introduction of the application of log-ratio techniques (Aitchison, 1986; Pawlowsky-Glahn and Egozcue, 2001; Pawlowsky-Glahn and Buccianti, 2011; Tolosana-Delgado and van den Boogaart, 2013) the problem that a constant sum destroys the potential independence of variances and covariances required for correlation regression analysis and empirical multivariate methods (principal component analysis, cluster analysis, discriminant analysis, canonical correlation) is all too often not acknowledged in the statistical treatment of trace evidence. Yet the need for a robust treatment of forensic trace evidence analyses is obvious. This research examines the issues and potential pitfalls for forensic investigators if the constant sum constraint is ignored in the analysis and presentation of forensic trace evidence. Forensic case studies involving particle size and mineral analyses as trace evidence are used to demonstrate the use of a compositional data approach using a centred log-ratio (clr) transformation and multivariate statistical analyses.