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Makams are well-defined modes of classical Turkish music. They can be taken as the Turkish music counterparts of Western music tonal structures at a certain level. Nevertheless, makams have additional features such as the usage of specific notes resulting from their different architecture and the special use of scales (i.e. progression). The main goal of this study is to construct a platform for identifying makams through a computer program by proposing a machine learning mechanism. There are restrictionson the mechanism related to the characteristics of the task. Such a mechanism should represent real-time sequential input with continuous values, should handle possible errors in this input and show immediate learning with limited data. These restrictions are valid and necessary for an analogy with the act of listening to music. A Boltzmann machine, modified for this purpose is designed, implemented and used in this study as this learning mechanism. Two characteristics of this study define its significance. First, this study is on the structural features of makams of classical Turkish music. Second, the identifying mechanism is a Boltzmann machine having a different schema than statistical identification tasks in tonality induction.

IsaMill is a stirred type mill used in mineral industry for fine and ultra-fine grinding. The difficulty in obtaining the internal flow information in the mill by experimental techniques has prevented the development of the fundamental understanding of the flow and generating general methods for reliable scale-up and optimized design and control parameters. This difficulty can be effectively overcome by numerical simulation based on discrete element method (DEM). In this work a DEM model was developed to study particle flow in a simplified IsaMill. The DEM model was validated by comparing the simulated results of the flow pattern, mixing pattern and power draw with those measured from a same scale lab mill. Spatial distributions of microdynamic variables related to flow and force structure such as local porosity, particle interaction forces, collision velocity and collision frequency have been analyzed. Among the materials properties of particles, it is shown that by decreasing particle/particle sliding friction coefficient, the particle flow becomes more vigorous which is useful to grinding performance. Restitution coefficient does not affect the particle flow significantly. A too low or too high particle density could decrease grinding efficiency. Although grinding medium size affects the flow, its selection may depend on the particle size of the products. Among the operational variables considered, the results show that fill volume and mill speed proved to be important factors in IsaMil process. Increase of fill volume or mill speed increases the interaction between particles and agitating discs which results in a more vigorous motion of the particles. Among the mill properties, particle/stirrer sliding friction plays a major role in energy transfer from stirrer to particles. Although there exists a minimum collision energy as particle/stirrer sliding friction increases, large particle/stirrer sliding friction may improve grinding performance as it has both large collision frequency and collision energy. However, that improvement is only up to a critical particle/disc sliding friction beyond which only input energy increases with little improvement on collision frequency and collision energy. Reducing the distance between stirrers or increasing the size of disc holes improves high energy transfer from discs to particles, leading to high collision frequency and collision energy. Among the different stirrer types, the energy transfer is more effective when disc holes are present. Pin stirrer shows increased collision energy and collision frequency which also result in a high power draw. Using the DEM results, a wear model has been developed to predict the wear pattern of the discs. This model can be used to predict the evolution of the disc wear with the time. It is shown that energy transfer from discs to particles are increased when discs are worn out. An attempt has also been made to analyze the microdynamic properties of the mill for different sizes. It is shown that specific power consumption and impact energy are correlated regardless of the mill size and mill speed.

This work investigates some of the issues and consequences for the field of artificial intelligence and cognitive science, which are related to the perceived limits of computation with current digital equipment. The Church -Turing thesis and the specific properties of Turing machines are examined and some of the philosophical 'in principle' objections, such as the application of G??del's incompleteness theorem, are discussed. It is argued that the misinterpretation of the Church-Turing thesis has led to unfounded assumptions about the limitations of computing machines in general. Modern digital computers, which are based on the von Neuman architecture, can typically be programmed so that they interact effectively with the real word. It is argued that digital computing machines are supersets of Turing machines, if they are, for example, programmed to interact with the real world. Moreover, computing is not restricted to the domain of discrete state machines. Analog computers and real or simulated neural nets exhibit properties that may not be accommodated in a definition of computing, which is based on Turing machines. Consequently, some of the philosophical 'in principle' objections to artificial intelligence may not apply in reference to engineering efforts in artificial intelligence.

Condition monitoring involves taking measurements on an induction motor while it is operating in order to detect faults. For this purpose normally a single sensor type, for example current is used to detect broken rotor bar using fault frequency components only under the full-load condition or a limited number of load cases. The correlations among the different types of sensors and their ability to diagnose single and multiple faults over a wide range of loads have not been the focused in previous research. Furthermore, to detect different faults in machines using any fault frequency components, it is important to investigate the variability in its amplitude to other effects apart from fault severity and load. This area has also often been neglected in the literature on condition monitoring. The stator current and axial flux have been widely used as suitable sensors for detecting different faults i.e. broken rotor bar and eccentricity faults in motors. Apart from detecting the broken rotor bar faults in generalized form, the use of instantaneous power signal has often been neglected in the literature condition monitoring. This thesis aims to improve machine condition monitoring and includes accurate and reliable detection of single and multiple faults (faults in the presence of other faults) in induction machines over a wide range of loads of rated output by using current, flux and instantaneous power as the best diagnostic medium. The research presents the following specific tasks: A comprehensive real database from non–invasive sensor measurements, i.e. vibration measurements, axial flux, 3-phase voltage, 3-phase current and speed measurements of induction motor is obtained by using laboratory testing on a large set of identical motors with different single and multiple faults. Means for introducing these faults of varying severity have been developed for this study. The collected data from the studied machines has been analysed using a custom-written analysis programme to detect the severity of different faults in the machines. This helps to improve the accuracy and reliability in detecting of single and multiple faults in motors using fault frequency components from current, axial flux and instantaneous power spectra. This research emphasises the importance of instantaneous power as a medium of detecting different single and multiple faults in induction motor under varying load conditions. This enables the possibility of obtaining accurate and reliable diagnostic medium to detect different faults existing in machines, which is vital in providing a new direction for future studies into condition monitoring. Another feature of this report is to check the variability in healthy motors due to: test repeatability, difference between nominally identical motors, and differences between the phases of the same motor. This has been achieved by conducting extensive series of laboratory tests to examine fault frequency amplitudes versus fault severity, load, and other factors such as test repeatability and machine phases. The information about the variations in the amplitudes of the fault frequency components is used to check the accuracy and reliability of the experimental set-up, which is necessary for the practical application of the results to reliably detect the different faults in the machines reliably. Finally, this study also considers the detection of eccentricity faults using fault frequency amplitudes as a function of average eccentricity, instead of as a function of load under different levels of loading. This has not been reported in previous studies. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1298314 / Thesis (Ph.D.)-- University of Adelaide, School of Electrical and Electronic Engineering, 2008

Thesis (Ph. D.)--University of Adelaide, Dept. of Applied Mathematics, 1986. / Includes bibliographical references (leaves 95-97).

Thèse (M.A.)--Université Laval, 2007. / Bibliogr.: f. [136]-139. Publié aussi en version électronique dans la Collection Mémoires et thèses électroniques.

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references.

Thesis (M.S.)--University of Nevada, Reno, 2006. / "December, 2006." Includes bibliographical references (leaves 123-127). Online version available on the World Wide Web.

Thesis: Ph.D.-- University of Western Sydney, Macarthur, 2000. / [A thesis presented to the Faculty of Arts and Social Sciences, Dept. of Psychology]. Bibliography: p. 299-314.