title: Predicting apple bruising relationships using machine learning

authors: Holmes, Geoffrey

subjects: computer science

abstract: Many models have been used to describe the influence of internal or external factors on apple bruising. Few of these have addressed the application of derived relationships to the evaluation of commercial operations. From an industry perspective, a model must enable fruit to be rejected on the basis of a commercially significant bruise and must also accurately quantify the effects of various combinations of input features (such as cultivar, maturity, size, and so on) on bruise prediction. Input features must in turn have characteristics which are measurable commercially; for example, the measure of force should be impact energy rather than energy absorbed. Further, as the commercial criteria for acceptable damage levels change, the model should be versatile enough to regenerate new bruise thresholds from existing data. 
Machine learning is a burgeoning technology with a vast range of potential applications particularly in agriculture where large amounts of data can be readily collected [1]. The main advantage of using a machine learning method in an application is that the models built for prediction can be viewed and understood by the owner of the data who is in a position to determine the usefulness of the model, an essential component in a commercial environment.

text: Predicting apple bruising relationships using machine learning Many models have been used to describe the influence of internal or external factors on apple bruising. Few of these have addressed the application of derived relationships to the evaluation of commercial operations. From an industry perspective, a model must enable fruit to be rejected on the basis of a commercially significant bruise and must also accurately quantify the effects of various combinations of input features (such as cultivar, maturity, size, and so on) on bruise prediction. Input features must in turn have characteristics which are measurable commercially; for example, the measure of force should be impact energy rather than energy absorbed. Further, as the commercial criteria for acceptable damage levels change, the model should be versatile enough to regenerate new bruise thresholds from existing data. 
Machine learning is a burgeoning technology with a vast range of potential applications particularly in agriculture where large amounts of data can be readily collected [1]. The main advantage of using a machine learning method in an application is that the models built for prediction can be viewed and understood by the owner of the data who is in a position to determine the usefulness of the model, an essential component in a commercial environment.

year: 1998-04

title: Why unavoidable moral wrongdoing is impossible

authors: Lane, Aaron

subjects: ethics

abstract: We can be faced with situations in which we act in accordance with the all-things-considered morally right course of action, and yet nevertheless experience an emotion of self-directed distress at the fact that we have so acted. Moreover, we have the intuition that this emotion is rational or appropriate. Literature is scattered with such examples, and they crop up not infrequently in life.

The fact that agents experience justified distress in such situations has been taken as evidence that unavoidable moral wrongdoing is possible. However, if this is the case, then the compelling intuition that an all-things-considered morally right action cannot be wrong must be false.

In this thesis, I offer a way of reconciling these two compelling intuitions that denies the possibility of unavoidable moral wrongdoing. I argue that existing attempts to dissolve this contradiction by arguing in favour of the possibility of unavoidable moral wrongdoing are unsatisfactory; and I contend that, by utilising Susan Wolf’s ideas on the “nameless virtue” (2001), developed in order to solve the problem of resultant moral luck, we can arrive at a more compelling method of dissolving the apparent contradiction. This solution is one that allows us to retain the intuition that a right act cannot also be wrong, while simultaneously allowing for the rationality of emotion of self-directed distress agents experience in situations of apparent unavoidable moral wrongdoing.

text: Why unavoidable moral wrongdoing is impossible We can be faced with situations in which we act in accordance with the all-things-considered morally right course of action, and yet nevertheless experience an emotion of self-directed distress at the fact that we have so acted. Moreover, we have the intuition that this emotion is rational or appropriate. Literature is scattered with such examples, and they crop up not infrequently in life.

The fact that agents experience justified distress in such situations has been taken as evidence that unavoidable moral wrongdoing is possible. However, if this is the case, then the compelling intuition that an all-things-considered morally right action cannot be wrong must be false.

In this thesis, I offer a way of reconciling these two compelling intuitions that denies the possibility of unavoidable moral wrongdoing. I argue that existing attempts to dissolve this contradiction by arguing in favour of the possibility of unavoidable moral wrongdoing are unsatisfactory; and I contend that, by utilising Susan Wolf’s ideas on the “nameless virtue” (2001), developed in order to solve the problem of resultant moral luck, we can arrive at a more compelling method of dissolving the apparent contradiction. This solution is one that allows us to retain the intuition that a right act cannot also be wrong, while simultaneously allowing for the rationality of emotion of self-directed distress agents experience in situations of apparent unavoidable moral wrongdoing.

year: 2025-10-17

title: Māori in the Faculty of Arts and Social Sciences: An analysis of the Faculty of Arts and Social Science data records from 1997-2002

authors: Ashwell, Allanah

subjects: Maori students

abstract: The Ministry of Education has compiled annual reports on the participation of Maori in
tertiary education. The 2002 report presented a comprehensive description of Maori
participation across all tertiary institutions within New Zealand in that year. The figures
show that Maori are markedly under-represented in tertiary institutions, particularly
universities.
The barriers encountered by Maori students can either directly or indirectly impact on
Maori participation, retention and success. The more disturbing outcome is that of
withdrawal or dropping out of higher education, is more likely when a Maori student
experiences and has to confront multiple rather than single barriers.
With this in mind, the aim of this study was to examine and identify trends apparent in
data records of Maori students enrolled in courses offered by the Faculty of Arts and
Social Sciences at the University of Waikato between 1997 and 2002 and to make
recommendations to the Faculty about how negative trends might be addressed. Specific
areas for analysis are detailed in the report.

text: Māori in the Faculty of Arts and Social Sciences: An analysis of the Faculty of Arts and Social Science data records from 1997-2002 The Ministry of Education has compiled annual reports on the participation of Maori in
tertiary education. The 2002 report presented a comprehensive description of Maori
participation across all tertiary institutions within New Zealand in that year. The figures
show that Maori are markedly under-represented in tertiary institutions, particularly
universities.
The barriers encountered by Maori students can either directly or indirectly impact on
Maori participation, retention and success. The more disturbing outcome is that of
withdrawal or dropping out of higher education, is more likely when a Maori student
experiences and has to confront multiple rather than single barriers.
With this in mind, the aim of this study was to examine and identify trends apparent in
data records of Maori students enrolled in courses offered by the Faculty of Arts and
Social Sciences at the University of Waikato between 1997 and 2002 and to make
recommendations to the Faculty about how negative trends might be addressed. Specific
areas for analysis are detailed in the report.

year: 2003-06