title: Encouraging better hand drying hygiene

authors: Cunningham, Sally Jo

subjects: computer science

abstract: Electric hand driers have the potential to improve sanitation when using public toilets; if used properly, electric driers can dry hands more thoroughly than towels, and users do not come into physical contact with potentially contaminated objects. But electric driers are frequently used for just a few seconds--and so the potential advantage is lost. This paper describes the prototyping and evaluation of a system intended to encourage longer hand drying times in public toilets. The challenges are: to develop hygienic interfaces for use in toilet areas; to design simple to use software that is engaging enough to be used several times a day; and to conduct usability and system acceptance tests in an environment in which users are highly sensitive about privacy issues.

text: Encouraging better hand drying hygiene Electric hand driers have the potential to improve sanitation when using public toilets; if used properly, electric driers can dry hands more thoroughly than towels, and users do not come into physical contact with potentially contaminated objects. But electric driers are frequently used for just a few seconds--and so the potential advantage is lost. This paper describes the prototyping and evaluation of a system intended to encourage longer hand drying times in public toilets. The challenges are: to develop hygienic interfaces for use in toilet areas; to design simple to use software that is engaging enough to be used several times a day; and to conduct usability and system acceptance tests in an environment in which users are highly sensitive about privacy issues.

year: 2008

title: Fault detection and path optimisation for a meat-processing robot

authors: Hurd, Shaun A.

abstract: An automated Y-cutting system has been developed by the Automation Systems team of Industrial Research Limited. This robotic device performs the Y-cut operation on sheep carcasses. The robotic Y-cutting system must deal with a variety of carcass shapes and sizes, and it is important that process faults are detected, diagnosed and corrected as quickly as possible. This thesis addresses the fault detection and path optimisation requirements of the Y-cutting system. 

The development of a neural network-based fault detection module is documented. This module classifies process faults using axial motor current data from the Y-cutting robot. The module successfully classifies 98% of the presented cut signals during offline training, and 100% of cuts during an extended trial in an Australian meat-processing plant. An online training scheme is implemented to allow for the retraining of the neural network weights as required. The fault detection module is extended to handle a greater number of fault conditions and to detect variations in the process load. 

A path optimisation algorithm is developed to optimise the parameters that define the cut-path of the robot based on the output of the fault detection module. A line-search within the parameter space is used to estimate the position of the optimum parameter value. The optimisation of fifteen path parameters requires 4760 simulated Y-cuts, equating to approximately 1.5 days of processing in a typical meat-plant. This is significantly faster than the existing method for manually tuning the Y-cutting system. The fault detection and path optimisation systems can be generically applied to other robotic systems produced by Industrial Research Limited for the handling and processing of highly varying natural products.

text: Fault detection and path optimisation for a meat-processing robot An automated Y-cutting system has been developed by the Automation Systems team of Industrial Research Limited. This robotic device performs the Y-cut operation on sheep carcasses. The robotic Y-cutting system must deal with a variety of carcass shapes and sizes, and it is important that process faults are detected, diagnosed and corrected as quickly as possible. This thesis addresses the fault detection and path optimisation requirements of the Y-cutting system. 

The development of a neural network-based fault detection module is documented. This module classifies process faults using axial motor current data from the Y-cutting robot. The module successfully classifies 98% of the presented cut signals during offline training, and 100% of cuts during an extended trial in an Australian meat-processing plant. An online training scheme is implemented to allow for the retraining of the neural network weights as required. The fault detection module is extended to handle a greater number of fault conditions and to detect variations in the process load. 

A path optimisation algorithm is developed to optimise the parameters that define the cut-path of the robot based on the output of the fault detection module. A line-search within the parameter space is used to estimate the position of the optimum parameter value. The optimisation of fifteen path parameters requires 4760 simulated Y-cuts, equating to approximately 1.5 days of processing in a typical meat-plant. This is significantly faster than the existing method for manually tuning the Y-cutting system. The fault detection and path optimisation systems can be generically applied to other robotic systems produced by Industrial Research Limited for the handling and processing of highly varying natural products.

year: 2005

title: Keynote address: Is there a distinctive Māori psychology?

authors: Durie, Mason

subjects: Maori

abstract: Many of the theoretical paradigms that underpin the study of psychology pay marginal attention to culture as a determinant of psychology.
While there are some aspects of human experience that are universal, patterns of thinking, feeling and behaving are by no means divorced from specific cultural influence. A challenge for Māori psychologists is to re-examine psychological theory from a Māori perspective. In attempting to identify the psychological distinctiveness underlying a Māori perspective, this paper has introduced marae encounters as a rich source of information within which distinctive psychological characteristics can be identified.

text: Keynote address: Is there a distinctive Māori psychology? Many of the theoretical paradigms that underpin the study of psychology pay marginal attention to culture as a determinant of psychology.
While there are some aspects of human experience that are universal, patterns of thinking, feeling and behaving are by no means divorced from specific cultural influence. A challenge for Māori psychologists is to re-examine psychological theory from a Māori perspective. In attempting to identify the psychological distinctiveness underlying a Māori perspective, this paper has introduced marae encounters as a rich source of information within which distinctive psychological characteristics can be identified.

year: 2003