Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Disorder By Design: A Data-Driven Approach To Amorphous Semiconductors Without Total-Energy Functionals, Dil K. Limbu, Stephen R. Elliott, Raymond Atta-Fynn, Parthapratim Biswas
Disorder By Design: A Data-Driven Approach To Amorphous Semiconductors Without Total-Energy Functionals, Dil K. Limbu, Stephen R. Elliott, Raymond Atta-Fynn, Parthapratim Biswas
Faculty Publications
X-ray diffraction, Amorphous silicon, Multi-objective optimization, Monte Carlo methods. This paper addresses a difficult inverse problem that involves the reconstruction of a three-dimensional model of tetrahedral amorphous semiconductors via inversion of diffraction data. By posing the material-structure determination as a multiobjective optimization program, it has been shown that the problem can be solved accurately using a few structural constraints, but no total-energy functionals/forces, which describe the local chemistry of amorphous networks. The approach yields highly realistic models of amorphous silicon, with no or only a few coordination defects (≤1%), a narrow bond-angle distribution of width 9–11.5°, and an electronic gap …
A Method For Automatic Detection Of Tongued And Slurred Note Transitions In Clarinet Playing, Whitney L. Coyle, Jack D. Gabriel
A Method For Automatic Detection Of Tongued And Slurred Note Transitions In Clarinet Playing, Whitney L. Coyle, Jack D. Gabriel
Faculty Publications
This study offers a simple method to characterize two transition types in passages of music in order to automatically distinguish slurred transitions from tongued transitions in musical settings. Data were recorded from musicians playing a clarinet with a sensor-equipped mouthpiece measuring blowing pressure in the mouth and pressure in the mouthpiece. This method allows for comparing transitions in different musical contexts, playing regimes, and between players. The method is highly reliable in automatically detecting transition types in recorded clarinet playing in both simple and more complex passages.