title: Coordinating knowledge to improve optical music recognition

authors: McPherson, John

abstract: Optical Music Recognition (OMR) is the process of automatically processing and understanding an image of a music score. This process involves various distinct phases to transform the image into primitive shapes, musical objects, and ultimately into a syntactic model representing the music's semantics. In general, OMR systems have performed these tasks in a linear sequence, so that the output of one component is the input to the next. However, this means that processing errors that occur in one of the tasks propagate through the system, and often when the error is eventually detected it is too late to reconsider the decisions leading to the incorrect classification or information. 
This thesis describes how OMR can be improved by modifying the recognition process from a sequence of linear tasks to a collection of modules that coordinate the information extracted from the data. Methods for_ data representation and controlling the system's flow of execution are investigated, and a practical implementation of such a system is described. This system has a message-passing design for providing contextual information from one module to another, such as suggesting possible classifications for an object. These messages are used to aid decision-making and to correct faulty decisions. This helps the system to adapt to a particular score while processing the image, increasing accuracy. 
This system is designed to aid in the research and evaluation of algorithms to achieve the above aims; therefore it is straightforward to modify various aspects of the system's behaviour, such as adding support for different music symbols. Examining the implemented system's behaviour clearly shows that this coordinated approach can correct many errors and can even identify some objects by only using syntactic information, based on the surrounding objects.

text: Coordinating knowledge to improve optical music recognition Optical Music Recognition (OMR) is the process of automatically processing and understanding an image of a music score. This process involves various distinct phases to transform the image into primitive shapes, musical objects, and ultimately into a syntactic model representing the music's semantics. In general, OMR systems have performed these tasks in a linear sequence, so that the output of one component is the input to the next. However, this means that processing errors that occur in one of the tasks propagate through the system, and often when the error is eventually detected it is too late to reconsider the decisions leading to the incorrect classification or information. 
This thesis describes how OMR can be improved by modifying the recognition process from a sequence of linear tasks to a collection of modules that coordinate the information extracted from the data. Methods for_ data representation and controlling the system's flow of execution are investigated, and a practical implementation of such a system is described. This system has a message-passing design for providing contextual information from one module to another, such as suggesting possible classifications for an object. These messages are used to aid decision-making and to correct faulty decisions. This helps the system to adapt to a particular score while processing the image, increasing accuracy. 
This system is designed to aid in the research and evaluation of algorithms to achieve the above aims; therefore it is straightforward to modify various aspects of the system's behaviour, such as adding support for different music symbols. Examining the implemented system's behaviour clearly shows that this coordinated approach can correct many errors and can even identify some objects by only using syntactic information, based on the surrounding objects.

year: 2006

title: The design of an optimistic AND-parallel Prolog

authors: Cleary, John G.

subjects: Computer Science

abstract: A distributed AND-parallel Prolog implementation is described.  The system can correctly handle all pure Prolog programs.  In particular, it deals with the problem of distributed backtracking.  Conflicts in variable bindings are resolved by assigning a time value to every unification. Bindings with smaller time values are given precedence over those with larger time values.  The algorithm is based on the optimistic Time Warp system, with Prolog-specific optimizations.  The optimizations include two new unification algorithms that permit unification and backtracking in any order.  The result is a system which can fully exploit the parallelism available in both dependent and independent AND-parallelism.

text: The design of an optimistic AND-parallel Prolog A distributed AND-parallel Prolog implementation is described.  The system can correctly handle all pure Prolog programs.  In particular, it deals with the problem of distributed backtracking.  Conflicts in variable bindings are resolved by assigning a time value to every unification. Bindings with smaller time values are given precedence over those with larger time values.  The algorithm is based on the optimistic Time Warp system, with Prolog-specific optimizations.  The optimizations include two new unification algorithms that permit unification and backtracking in any order.  The result is a system which can fully exploit the parallelism available in both dependent and independent AND-parallelism.

year: 1993-10

title: The physical health and premature mortality of Indigenous Māori following first-episode psychosis diagnosis: A 15-year follow-up study

authors: Monk, Nathan

subjects: First-episode psychosis, New Zealand, Māori, indigenous health, health equity, physical health, cardiometabolic health, premature mortality, cohort study

abstract: Background:
People experiencing psychosis are at greater risk of physical health conditions and premature mortality. It is likely that Indigenous Māori youth, who experience additional systemic inequities caused by settler-colonisation, face even greater physical health and mortality risks following a diagnosis of first-episode psychosis.
Objective:
Compare Māori and non-Māori for risk of hospitalisation and mortality for up to 15 years following first-episode psychosis diagnosis.
Methods:
A cohort (N = 14,122) of young people (16–24 years) with first-episode psychosis diagnosis between 2001 and 2019 were identified. Using crude Kaplan–Meier and adjusted Cox proportional hazards models, Māori (n = 5211) and non-Māori (n = 8911) were compared on hospitalisation and mortality outcomes for up to 15 years.
Results:
In the 15 years following first-episode psychosis diagnosis, Māori had higher adjusted risk of all-cause mortality (hazard ratio = 1.21, 95% confidence interval = [1.01, 1.45]), hospitalisation with diabetes (hazard ratio = 1.44, 95% confidence interval = [1.15, 1.79]), injury/poisoning (hazard ratio = 1.11, 95% confidence interval = [1.05, 1.16]), general physical health conditions (hazard ratio = 1.07, 95% confidence interval = [1.02, 1.13]) and also appeared to be at greater risk of cardiovascular hospitalisations (hazard ratio = 1.34, 95% confidence interval = [0.97, 1.86]). Kaplan–Meier plots show hospitalisation and mortality inequities emerging approximately 4–7 years following first-episode psychosis diagnosis.
Conclusions:
Māori are at greater risk for hospitalisation and premature mortality outcomes following first-episode psychosis. Early screening and intervention, facilitated by culturally safe health service delivery, is needed to target these inequities early.

text: The physical health and premature mortality of Indigenous Māori following first-episode psychosis diagnosis: A 15-year follow-up study Background:
People experiencing psychosis are at greater risk of physical health conditions and premature mortality. It is likely that Indigenous Māori youth, who experience additional systemic inequities caused by settler-colonisation, face even greater physical health and mortality risks following a diagnosis of first-episode psychosis.
Objective:
Compare Māori and non-Māori for risk of hospitalisation and mortality for up to 15 years following first-episode psychosis diagnosis.
Methods:
A cohort (N = 14,122) of young people (16–24 years) with first-episode psychosis diagnosis between 2001 and 2019 were identified. Using crude Kaplan–Meier and adjusted Cox proportional hazards models, Māori (n = 5211) and non-Māori (n = 8911) were compared on hospitalisation and mortality outcomes for up to 15 years.
Results:
In the 15 years following first-episode psychosis diagnosis, Māori had higher adjusted risk of all-cause mortality (hazard ratio = 1.21, 95% confidence interval = [1.01, 1.45]), hospitalisation with diabetes (hazard ratio = 1.44, 95% confidence interval = [1.15, 1.79]), injury/poisoning (hazard ratio = 1.11, 95% confidence interval = [1.05, 1.16]), general physical health conditions (hazard ratio = 1.07, 95% confidence interval = [1.02, 1.13]) and also appeared to be at greater risk of cardiovascular hospitalisations (hazard ratio = 1.34, 95% confidence interval = [0.97, 1.86]). Kaplan–Meier plots show hospitalisation and mortality inequities emerging approximately 4–7 years following first-episode psychosis diagnosis.
Conclusions:
Māori are at greater risk for hospitalisation and premature mortality outcomes following first-episode psychosis. Early screening and intervention, facilitated by culturally safe health service delivery, is needed to target these inequities early.

year: 2024