The main purpose of this study is to identify and compare classical pianists' understanding of sight-reading. Six pianists were interviewed, four professionals and two students. All of them concidered good sight-reading ability to be an advantage, especially when rehearsing, but most important is to be a good musicians performing music thoroghly gone through.

A MATLAB code for calculating neutron energy spectra from JET discharges was developed. The code uses the fuel ion distribution calculated by the computer code SELFO to generate the spectrum through a Monte-Carlo simulation. The calculated spectra were then compared against experimental results from the neutron spectrometer TOFOR. In the calculations, the exact orbits of the fuel ions are taken into account, in order to investigate what effects this has on the spectrum. The reason for this is that, for certain plasma heating scenarios, large populations of fast fuel ions are formed. These fast ions may have Larmor radii of the order of decimeters, which is comparable to the width of the sight line of TOFOR, and may therefore affect the recorded neutron spectrum. A JET discharge with both NBI and 3rd harmonic ICRF heating was analyzed. The results show that the details of the line of sight of the detector indeed affects the neutron spectrum. This effect is probably important for other diagnostics techniques, such as gamma-ray spectroscopy and neutral particle analysis, as well. Good agreement with TOFOR data is observed, but not for the exact same time slice of the discharge, which leaves some questions yet to be investigated.

The thesis is mainly focused on a hybrid location system, which processes wireless and inertial measurements by extended Kalman filtering. Inertial location system is usually used with Dead-Reckoning method, which calculates the present location and heading direction from a previous known state by using measurements of accelerometer and gyroscope, which have immunity from the environment. The system estimates the position by integrates the measurements of sensors, resulting in high accuracy during a short period. However, the unreliability grows with time due to the bias effect on sensors. By combining the wireless location and inertial system, the uncertainty of estimation can be reduced. In wireless communications, the locations of base stations and the times of signal arrival can be used in locating a mobile station. However, signal propagation could be blocked by objects. The non-line of sight (NLOS) effects cause arrival delay and is usually modeled as exponential distributions. Previously, the improved biased Kalman filters were designed to mitigate the NLOS effect in base station measurements. The system design has difficulty in accommodating inertial measurements. The inertial has immunity to the environment. The property is of help in the NLOS mitigation. Therefore, we propose a hybrid location system that integrating the wireless and inertial measurements by using a hybrid biased extended Kalman filter at the stage of positioning. The system provides better prediction with the assistance of enviroment-free inertial measurements. The NLOS mitigation with prediction feedback scheme results in better mitigation performance. Simulations of different situations have been conducted based on parameters in the IEEE 802.15.3a ultra-wideband environment. The performance differences between the proposed method and other approaches show that inertial assisted system effectively reduces the NLOS effects. Also, the proposed hybrid location system has more efficient mitigation performance and better tracking results.

For the mass demands of wireless communication services, the mobile location technologies have drawn much attention of the governments, academia, and industries around the world. In wireless communication, one of the main problems with accurate location is nonline of sight (NLoS) propagation. To solve the problem, we present a new location algorithm with clustering technology by utilizing the geometrical feature of cell layout, time of arrival (ToA) range measurements, and three base stations. The mobile location is estimated by solving the optimal solution of the objective function based on the high density cluster. Simulations study was conducted to evaluate the performance of the algorithm for different NLoS error distributions and various upper bound of NLoS error. The results of our experiments demonstrate that the proposed algorithm is significantly more effective in location accuracy than range scaling algorithm, linear lines of position algorithm, and Taylor series algorithm, and also satisfies the location accuracy demand of E-911.

The technique of mobile location has become a popular research topic since the number of related applications for the location information is growing rapidly. The decision to make the location of mobile phones under the U.S. Federal Communications Commission (FCC) in 1996 is one of the driving forces to research and provide solutions to it. But, in wireless communication systems, non line of sight (NLOS) propagation is a key and difficult issue to improve mobile location estimation. We propose an efficient location algorithm which can mitigate the influence of NLOS error. First, based on the geometric relationship between known positions of the base stations, the theorem of ¡§Fermat Point¡¨ is utilized to collect the candidate positions (CPs) of the mobile station. Then, a set of weighting parameters are computed using a density-based clustering method. Finally, the location of mobile station is estimated by solving the optimal solution of the weighted objective function. Different distributions of NLOS error models are used to evaluate the performance of this method. Simulation results show that the performance of the least range measure (LRM) algorithm is slightly better than density-based clustering algorithm (DCA), and superior to the range based linear lines of position algorithm (LLOP) and range scaling algorithm (RSA) on location accuracy under different NLOS environments. The simulation results also satisfy the location accuracy demand of Enhanced 911 (E-911).

In the thesis, we propose a non-line of sight (NLOS) mitigation approach based on the interacting multiple model (IMM) algorithm. The IMM-based structure, composed of a biased Kalman filter (BKF) and a Kalman filter with NLOS-discarding process (KF-D), is capable of mitigating the ranging error caused by the NLOS effects, and therefore improving the performance and accuracy in wireless location systems. The NLOS effect on signal transmission is one of the major factors that affect the accuracy of the time-based location systems. Effective NLOS identification and mitigation usually count on pre-determined statistic distribution and hypothesis assumption in the signals. Because the variance of the NLOS error is much large than that of measurement noise, hypothesis testing on the LOS/NLOS status can be formulated.The BKF combines the sliding window and decides the status by using hypothesis testing. The calculated variance and the detection result are used in switching between the biased and unbiased modes in the Kalman filter. In the contrast, the KF-D scheme identifies the NLOS status and tries to eliminate the NLOS effects by directly using the estimated results from the LOS stage. The KF-D scheme can achieve reasonably good NLOS mitigation if the estimates in the LOS status are obtained. Due to the discarding process, changes of the state vector within the NLOS stage are possibly ignored, and will cause larger errors in the state estimates. The BKF and KF-D can make up for each other by formulating the filters in an IMM structure, which could tune up the probabilities of BKF and KF-D. In our approach, the measured data are smoothed by sliding window and a BKF. The variance of data and the hypothesis test result are passed to the two filters. The BKF switches between the biased/unbiased modes by using the result. The KF-D may receive the estimated value from BKF based on the results. The probability computation unit changes the weights to get the estimated TOA values. With the simulations in ultra-wideband (UWB) signals, it can be seen that the proposed IMM-based approach can effectively mitigate the NLOS effects and increase the accuracy in wireless position.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 174-181). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 174-181). Also available on the Internet.

Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Ingram, Mary Ann; Committee Member: Durgin, Greg; Committee Member: Kenney, Steve; Committee Member: Landgren, Jack; Committee Member: Li, Ye. Part of the SMARTech Electronic Thesis and Dissertation Collection.

The present study investigated how knowledge of tonality is used in sight-reading by comparing sight-reading accuracy across three tonal constructs: major, minor and atonal. It was hypothesized that sight-reading performance would be the worst in instances with no tonal information, as participants would be unable to generate appropriate top-down expectancies to guide their sight-reading. To test this, twelve pianists sight-read major, minor and atonal versions of monophonic, homophonic and polyphonic excerpts. The results indicated that pianists performed the major excerpts with greater accuracy than the atonal excerpts. Furthermore, the errors made within the major excerpts were significantly biased towards diatonicism, and there was a global shift towards tonality in participants’ atonal performances, providing a clear demonstration of how pianists’ expectations might have contributed to their sight-reading performance. The diatonic bias was not found in the minor excerpts, suggesting that the minor hierarchy does exert as strong of an influence during sight-reading.