title: Scenario planning for climate change adaptation for natural resource management: Insights from the Australian East Coast Cluster

authors: Serrao-Neumann, Silvia

subjects: Science & Technology

abstract: Natural resources and inherent ecosystem services have long been under pressure from unsustainable exploitation further exacerbated by climate change impacts. Managing natural resources in the Australian context is also a complex task because it involves a raft of stakeholders subjected to ongoing institutional changes and reductions in funding for programme implementation. This paper explores the use of scenario planning as a suitable tool to deal with the uncertainty and complexity inherent to natural resource management. Specifically, it reports on the development and application of explorative scenarios (multiple plausible futures) involving six natural resource management organisations and their communities of practice operating along the East Coast of Australia. Scenarios were developed based on two key drivers of change, namely: maturing approach to natural resource management; and community driven climate change action, to test the robustness and flexibility of a suite of existing strategies, policies and targets. Findings indicate that explorative scenarios were useful in the identification of strategies that may result in perverse or negative impacts under different futures; guide selection of different approaches in response to unexpected events; encourage a forward-looking approach rather than relying on past experiences only; create flexible, robust strategies that are better able to deal with shocks and surprises; provide participating policy owners with an opportunity to consider future contexts for their policies to play out in; and, ascertain a range of possible pathways to achieve a vision or goals depending on changed circumstances.

text: Scenario planning for climate change adaptation for natural resource management: Insights from the Australian East Coast Cluster Natural resources and inherent ecosystem services have long been under pressure from unsustainable exploitation further exacerbated by climate change impacts. Managing natural resources in the Australian context is also a complex task because it involves a raft of stakeholders subjected to ongoing institutional changes and reductions in funding for programme implementation. This paper explores the use of scenario planning as a suitable tool to deal with the uncertainty and complexity inherent to natural resource management. Specifically, it reports on the development and application of explorative scenarios (multiple plausible futures) involving six natural resource management organisations and their communities of practice operating along the East Coast of Australia. Scenarios were developed based on two key drivers of change, namely: maturing approach to natural resource management; and community driven climate change action, to test the robustness and flexibility of a suite of existing strategies, policies and targets. Findings indicate that explorative scenarios were useful in the identification of strategies that may result in perverse or negative impacts under different futures; guide selection of different approaches in response to unexpected events; encourage a forward-looking approach rather than relying on past experiences only; create flexible, robust strategies that are better able to deal with shocks and surprises; provide participating policy owners with an opportunity to consider future contexts for their policies to play out in; and, ascertain a range of possible pathways to achieve a vision or goals depending on changed circumstances.

year: 2019

title: Delivering the 20 minute city in Hamilton, NZ

authors: White, Iain

abstract: University of Waikato Professor Iain White led much of the think behind the $500m "20 Minute city" concept that headlines the proposal. 
The aim of it was to create a city where most facilities and activities, including employment, were available within 20 minute walking distance of one's home.

text: Delivering the 20 minute city in Hamilton, NZ University of Waikato Professor Iain White led much of the think behind the $500m "20 Minute city" concept that headlines the proposal. 
The aim of it was to create a city where most facilities and activities, including employment, were available within 20 minute walking distance of one's home.

year: 2021

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