title: Léonce de Saint-Martin: Organist and composer

authors: Smith, Philip Andrew

subjects: Leonce de Saint-Martin

abstract: This study examines the life and work of the largely forgotten organist Léonce de Saint-Martin and the role he played in the life of Notre-Dame Cathedral Paris.
The Study consists of two parts:
A)	 Performance
The performance part consisted of four performances in addition to the final recital. These were related to both the topic and the requirements of the University of Waikato.
1.	Liturgical Improvisations on "The Stations of the Cross."
2.	Organ Concerto in G minor -  Francis Poulenc
3.	Requiem – Maurice Duruflé 
4.	Solo Recital - St. Peter’s Cathedral Hamilton.
5.	Final recital - Holy Trinity Cathedral Auckland.

B) Thesis
The thesis examines the development of the French organ in relation to the organ of Notre-Dame de Paris from 1198 to 1954. In addition, the life and work of the main protagonists Louis Vierne and Marcel Dupré are examined to put the role of Saint-Martin in context. The bulk of the work places the career of Saint-Martin into a fresh context, and examines his compositional and performance output purely on its musical merit, from a position of both chronological and geographical distance.

text: Léonce de Saint-Martin: Organist and composer This study examines the life and work of the largely forgotten organist Léonce de Saint-Martin and the role he played in the life of Notre-Dame Cathedral Paris.
The Study consists of two parts:
A)	 Performance
The performance part consisted of four performances in addition to the final recital. These were related to both the topic and the requirements of the University of Waikato.
1.	Liturgical Improvisations on "The Stations of the Cross."
2.	Organ Concerto in G minor -  Francis Poulenc
3.	Requiem – Maurice Duruflé 
4.	Solo Recital - St. Peter’s Cathedral Hamilton.
5.	Final recital - Holy Trinity Cathedral Auckland.

B) Thesis
The thesis examines the development of the French organ in relation to the organ of Notre-Dame de Paris from 1198 to 1954. In addition, the life and work of the main protagonists Louis Vierne and Marcel Dupré are examined to put the role of Saint-Martin in context. The bulk of the work places the career of Saint-Martin into a fresh context, and examines his compositional and performance output purely on its musical merit, from a position of both chronological and geographical distance.

year: 2018

title: Browsing tree structures

authors: Apperley, Mark

subjects: computer science

abstract: Graphic representations of tree structures are notoriously difficult to create, display, and interpret, particularly when the volume of information they contain, and hence the number of nodes, is large. The problem of interactively browsing information held in tree structures is examined, and the implementation of an innovative tree browser described. This browser is based on distortion-oriented display techniques and intuitive direct manipulation interaction. The tree layout is automatically generated, but the location and extent of detail shown is controlled by the user. It is suggested that these techniques could be extended to the browsing of more general networks.

text: Browsing tree structures Graphic representations of tree structures are notoriously difficult to create, display, and interpret, particularly when the volume of information they contain, and hence the number of nodes, is large. The problem of interactively browsing information held in tree structures is examined, and the implementation of an innovative tree browser described. This browser is based on distortion-oriented display techniques and intuitive direct manipulation interaction. The tree layout is automatically generated, but the location and extent of detail shown is controlled by the user. It is suggested that these techniques could be extended to the browsing of more general networks.

year: 1999-05

title: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand

authors: Owen, Mahonri W.

subjects: Prosthetics

abstract: Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

text: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

year: 2019