title: Notes: an experiment in CSCW

authors: Apperley, Mark

subjects: computer science

abstract: Computer Supported Co-operative Work (CSCW) systems are complex, yet no computer-based tools of any sophistication exist to support their development. Since several people often need to work together on the same project simultaneously, the computer system often proves to be a bottleneck. CSCW tools are a means of allowing several users to work towards their goal. Systems development is essentially a team process, yet support for CSCW on these systems is in its infancy.

text: Notes: an experiment in CSCW Computer Supported Co-operative Work (CSCW) systems are complex, yet no computer-based tools of any sophistication exist to support their development. Since several people often need to work together on the same project simultaneously, the computer system often proves to be a bottleneck. CSCW tools are a means of allowing several users to work towards their goal. Systems development is essentially a team process, yet support for CSCW on these systems is in its infancy.

year: 1996-04

title: Reinforcement learning for optimisation of a cascade river system

authors: Waddington, Nicolaas

subjects: hydropower

abstract: Getting the most out of renewable power stations has financial benefits and the environmental benefits of displacing electricity generation from fossil fuels. This thesis considers how to reduce losses in the Waikato Hydro Scheme that are due to inefficient operation while ensuring no operating constraints are breached. The hydroelectric dams are currently centrally run by a human "hydro controller" who makes decisions on how much generation to assign to each station at any given time. The hydro controller ensures no operating constraints are breached, but it may be possible to improve the running efficiency of the hydro stations. Currently, hydro controllers only have basic tools to assist them when deciding which action to take. The aim of this thesis is to create live recommendations to help them make decisions. To this end, historical data is used to train a model using reinforcement learning that can be used to provide such live recommendations on how much generation to assign to each station. The Waikato River hydro control problem is formulated as a Markov decision process and several variations on the Monte Carlo control algorithm for reinforcement learning are proposed and compared empirically. The Waikato River hydro control problem has a large action space with billions of distinct ways to assign generation to stations. The K-medoids algorithm is used to cluster actions so that 
 learning becomes practical. Furthermore, once a model has been learned, a hill-climbing approach is used to improve the quality of the selected actions. Combining these techniques gave better running efficiency than historical human performance in 18% of scenarios without breaching any operating constraints. 34% of scenarios did breach constraints so possible improvements to address this are also discussed.

text: Reinforcement learning for optimisation of a cascade river system Getting the most out of renewable power stations has financial benefits and the environmental benefits of displacing electricity generation from fossil fuels. This thesis considers how to reduce losses in the Waikato Hydro Scheme that are due to inefficient operation while ensuring no operating constraints are breached. The hydroelectric dams are currently centrally run by a human "hydro controller" who makes decisions on how much generation to assign to each station at any given time. The hydro controller ensures no operating constraints are breached, but it may be possible to improve the running efficiency of the hydro stations. Currently, hydro controllers only have basic tools to assist them when deciding which action to take. The aim of this thesis is to create live recommendations to help them make decisions. To this end, historical data is used to train a model using reinforcement learning that can be used to provide such live recommendations on how much generation to assign to each station. The Waikato River hydro control problem is formulated as a Markov decision process and several variations on the Monte Carlo control algorithm for reinforcement learning are proposed and compared empirically. The Waikato River hydro control problem has a large action space with billions of distinct ways to assign generation to stations. The K-medoids algorithm is used to cluster actions so that 
 learning becomes practical. Furthermore, once a model has been learned, a hill-climbing approach is used to improve the quality of the selected actions. Combining these techniques gave better running efficiency than historical human performance in 18% of scenarios without breaching any operating constraints. 34% of scenarios did breach constraints so possible improvements to address this are also discussed.

year: 2025

title: How do colorectal cancer patients rate their GP: a mixed methods study

authors: Blackmore, Tania Louise

subjects: Science & Technology

abstract: Background: New Zealand (NZ) has a high incidence of colorectal cancer (CRC) and low rates of early diagnosis. With screening not yet nationwide, the majority of CRC is diagnosed through general practice. A good patient-general practitioner (GP) relationship can facilitate prompt diagnosis, but when there is a breakdown in this relationship, delays can occur. Delayed diagnosis of CRC in NZ receives a disproportionally high number of complaints directed against GPs, suggesting deficits in the patient-GP connection. We aimed to investigate patient-reported confidence and ratings of their GP following the diagnostic process. 
Methods: This study is a mixed methods analysis of responses to a structured questionnaire and free text comments from patients newly diagnosed with CRC in the Midland region of NZ. A total of 195 patients responded to the structured questionnaire, and 113 patients provided additional free text comments. Descriptive statistics were used to describe the study population and chi square analysis determined the statistical significance of factors possibly linked to delay. Free text comments were analysed using a thematic framework. 
Results: Most participants rated their GP as ‘Very good/Good’ at communication with patients about their health conditions and involving them in decisions about their care, and 6.7% of participants rated their overall level of confidence and trust in their GP as ‘Not at all’. Age, gender, ethnicity and a longer diagnostic interval were associated with lower confidence and trust. Free text comments were grouped in to three themes: 1. GP Interpersonal skills; (communication, listening, taking patient symptoms seriously), 2. Technical competence; (speed of referral, misdiagnoses, lack of physical examination), and 3. Organisation of general practice care; (appointment length, getting an appointment, continuity of care). 
Conclusions: Māori, females, and younger participants were more likely to report low confidence and trust in their GP. Participants associate a poor diagnostic experience with deficits in the interpersonal and technical skills of their GP, and health system factors within general practice. Short appointment times, access to appointments and poor GP continuity are important components of how patients assess their experience and are particularly important to ensure equal access for Māori patients.

text: How do colorectal cancer patients rate their GP: a mixed methods study Background: New Zealand (NZ) has a high incidence of colorectal cancer (CRC) and low rates of early diagnosis. With screening not yet nationwide, the majority of CRC is diagnosed through general practice. A good patient-general practitioner (GP) relationship can facilitate prompt diagnosis, but when there is a breakdown in this relationship, delays can occur. Delayed diagnosis of CRC in NZ receives a disproportionally high number of complaints directed against GPs, suggesting deficits in the patient-GP connection. We aimed to investigate patient-reported confidence and ratings of their GP following the diagnostic process. 
Methods: This study is a mixed methods analysis of responses to a structured questionnaire and free text comments from patients newly diagnosed with CRC in the Midland region of NZ. A total of 195 patients responded to the structured questionnaire, and 113 patients provided additional free text comments. Descriptive statistics were used to describe the study population and chi square analysis determined the statistical significance of factors possibly linked to delay. Free text comments were analysed using a thematic framework. 
Results: Most participants rated their GP as ‘Very good/Good’ at communication with patients about their health conditions and involving them in decisions about their care, and 6.7% of participants rated their overall level of confidence and trust in their GP as ‘Not at all’. Age, gender, ethnicity and a longer diagnostic interval were associated with lower confidence and trust. Free text comments were grouped in to three themes: 1. GP Interpersonal skills; (communication, listening, taking patient symptoms seriously), 2. Technical competence; (speed of referral, misdiagnoses, lack of physical examination), and 3. Organisation of general practice care; (appointment length, getting an appointment, continuity of care). 
Conclusions: Māori, females, and younger participants were more likely to report low confidence and trust in their GP. Participants associate a poor diagnostic experience with deficits in the interpersonal and technical skills of their GP, and health system factors within general practice. Short appointment times, access to appointments and poor GP continuity are important components of how patients assess their experience and are particularly important to ensure equal access for Māori patients.

year: 2021-04-08