title: Distinguishing between the concepts of steady state and dynamic equilibrium in geomorphology

authors: Abrahams, Athol D.

abstract: The development of the concept of equilibrium in geomorphology over the past 15 years has been marked by linguistic difficulties due, in part, to the interchangeable use of the terms, dynamic equilibrium and steady state. It is here proposed that the range of steady state conditions constitute a sub-set of the range of conditions of dynamic equilibrium.
The application of General Systems Theory is responsible for the introduction to geomorphology of the term steady state which in the strictest sense refers to the tendency for constant forms to develop. Gilbert understood dynamic equilibrium to mean an adjustment between the processes of erosion and the resistance of the bedrock. More recently, Leopold and Langbein described dynamic or quasi-equilibrium as a state of energy distribution which does not necessarily involve any regularity of form. However, dynamic equilibrium finds expression over space and time, in the evolving regularity and mutual adjustment of form elements. The development of regular erosional landforms reflects the tendency of the energy conditions of a system to make the final adjustment to the most probable state. If the manner of landform evolution is the point in question, the concepts of dynamic equilibrium and steady state become clearly distinguishable and system boundaries must be precisely defined. In field studies the theoretical approach is often superseded by the pragmatic approach. However, unless the logical distinction between the two concepts is made in the first place confusion will continue to persist in geomorphic analysis.

text: Distinguishing between the concepts of steady state and dynamic equilibrium in geomorphology The development of the concept of equilibrium in geomorphology over the past 15 years has been marked by linguistic difficulties due, in part, to the interchangeable use of the terms, dynamic equilibrium and steady state. It is here proposed that the range of steady state conditions constitute a sub-set of the range of conditions of dynamic equilibrium.
The application of General Systems Theory is responsible for the introduction to geomorphology of the term steady state which in the strictest sense refers to the tendency for constant forms to develop. Gilbert understood dynamic equilibrium to mean an adjustment between the processes of erosion and the resistance of the bedrock. More recently, Leopold and Langbein described dynamic or quasi-equilibrium as a state of energy distribution which does not necessarily involve any regularity of form. However, dynamic equilibrium finds expression over space and time, in the evolving regularity and mutual adjustment of form elements. The development of regular erosional landforms reflects the tendency of the energy conditions of a system to make the final adjustment to the most probable state. If the manner of landform evolution is the point in question, the concepts of dynamic equilibrium and steady state become clearly distinguishable and system boundaries must be precisely defined. In field studies the theoretical approach is often superseded by the pragmatic approach. However, unless the logical distinction between the two concepts is made in the first place confusion will continue to persist in geomorphic analysis.

year: 1968

title: Real-time New Zealand sign language translator using convolution neural network

authors: Jayasekera, Mathes Kankanamge Chami

subjects: Sign Language Translator

abstract: Over the past quarter of a century, machine Learning performs an essential role in information technology revolution. From predictive internet web browsing to autonomous vehicles; machine learning has become the heart of all intelligence applications in service today. Image classification through gesture recognition is sub field which has benefited immensely from the existence of this machine learning method. In particular, a subset of Machine Learning known as deep learning has exhibited impressive performance in this regard while outperforming other conventional approaches such as image processing. The advanced Deep Learning architectures come with artificial neural networks particularly convolution neural networks (CNN). Deep Learning has dominated the field of computer vision since 2012; however, a general criticism of this deep learning method is its dependence on large datasets. In order to overcome this criticism, research focusing on discovering data- efficient deep learning methods have been carried out. The foremost finding of the data-efficient deep learning function is a transfer learning technique, which is basically carried out with pre-trained networks. In this research, the InceptionV3 pre trained model has been used to perform the transfer learning method in a convolution neural network to implement New Zealand sign language translator in real-time. 
The focus of this research is to introduce a vision-based application that offers New Zealand sign language translation into text format by recognizing sign gestures to overcome the communication barriers between the deaf community and hearing-unimpaired community in New Zealand. As a byproduct of this research work, a new dataset for New Zealand sign Language alphabet has been created. After training the pre-trained InceptionV3 network with this captured dataset, a prototype for this New Zealand sign language translating system has been created.

text: Real-time New Zealand sign language translator using convolution neural network Over the past quarter of a century, machine Learning performs an essential role in information technology revolution. From predictive internet web browsing to autonomous vehicles; machine learning has become the heart of all intelligence applications in service today. Image classification through gesture recognition is sub field which has benefited immensely from the existence of this machine learning method. In particular, a subset of Machine Learning known as deep learning has exhibited impressive performance in this regard while outperforming other conventional approaches such as image processing. The advanced Deep Learning architectures come with artificial neural networks particularly convolution neural networks (CNN). Deep Learning has dominated the field of computer vision since 2012; however, a general criticism of this deep learning method is its dependence on large datasets. In order to overcome this criticism, research focusing on discovering data- efficient deep learning methods have been carried out. The foremost finding of the data-efficient deep learning function is a transfer learning technique, which is basically carried out with pre-trained networks. In this research, the InceptionV3 pre trained model has been used to perform the transfer learning method in a convolution neural network to implement New Zealand sign language translator in real-time. 
The focus of this research is to introduce a vision-based application that offers New Zealand sign language translation into text format by recognizing sign gestures to overcome the communication barriers between the deaf community and hearing-unimpaired community in New Zealand. As a byproduct of this research work, a new dataset for New Zealand sign Language alphabet has been created. After training the pre-trained InceptionV3 network with this captured dataset, a prototype for this New Zealand sign language translating system has been created.

year: 2021

title: Me ko Māui: Harnessing the sun to provide better outcomes for marae and communities

authors: Greensill, Waikauri

abstract: Marae are the cultural centres of Māori communities, providing a space for important gatherings both joyful and sad. With the advent of solar energy capture technologies and rising electricity bills, many marae are becoming interested in whether a solar powered system will be beneficial for them. However, marae have unique electricity demand profiles, distinct from commonly modelled building types such as residential or commercial buildings. It is thus difficult to estimate an appropriate solar and battery system size based on annual or even monthly electricity usage data, which may be the only data readily available, requiring more in-depth analysis at a highly site-specific level to find an answer. This thesis aims to increase understanding around how solar power could benefit marae, first by investigating the characteristic electricity demand profile of marae, then by observing how proposed system configurations meet the demand. The potential community benefits arising from such a system was also investigated. Using a year’s worth of half-hourly data from three marae, five characteristic day types were found in the analysis of the demand profile, namely a “Non-Event” profile that maintained a low baseload and accounted for 70% of the days in a year, a “1-Day Event” profile that lasted only a few hours, and for events spanning multiple days a “Start”, “Middle” and “End” day profile that varied greatly in demand magnitude. The demand profiles were then used to develop an annual demand profile for an average marae that was broadly representative of a wide range of marae. Different configurations of solar and battery powered systems were then applied to the annual demand and a technoeconomic analysis performed to determine whether a specific configuration met the needs of the average marae or not, which then produced a range of acceptable system sizes based on the needs specified. Not many solar and battery configurations resulted in positive economic returns for the marae alone, but widening the scope of the analysis to the surrounding community allows other interests such as local grid resilience to be considered, some of which may justify a marae’s decision to invest in a non-economic system to gain better community benefits. While investigating the use of peer-to-peer energy trading and community energy scenarios, sharing excess energy generated by a system with the wider community was also found to improve the economic outlook of solar for marae.

text: Me ko Māui: Harnessing the sun to provide better outcomes for marae and communities Marae are the cultural centres of Māori communities, providing a space for important gatherings both joyful and sad. With the advent of solar energy capture technologies and rising electricity bills, many marae are becoming interested in whether a solar powered system will be beneficial for them. However, marae have unique electricity demand profiles, distinct from commonly modelled building types such as residential or commercial buildings. It is thus difficult to estimate an appropriate solar and battery system size based on annual or even monthly electricity usage data, which may be the only data readily available, requiring more in-depth analysis at a highly site-specific level to find an answer. This thesis aims to increase understanding around how solar power could benefit marae, first by investigating the characteristic electricity demand profile of marae, then by observing how proposed system configurations meet the demand. The potential community benefits arising from such a system was also investigated. Using a year’s worth of half-hourly data from three marae, five characteristic day types were found in the analysis of the demand profile, namely a “Non-Event” profile that maintained a low baseload and accounted for 70% of the days in a year, a “1-Day Event” profile that lasted only a few hours, and for events spanning multiple days a “Start”, “Middle” and “End” day profile that varied greatly in demand magnitude. The demand profiles were then used to develop an annual demand profile for an average marae that was broadly representative of a wide range of marae. Different configurations of solar and battery powered systems were then applied to the annual demand and a technoeconomic analysis performed to determine whether a specific configuration met the needs of the average marae or not, which then produced a range of acceptable system sizes based on the needs specified. Not many solar and battery configurations resulted in positive economic returns for the marae alone, but widening the scope of the analysis to the surrounding community allows other interests such as local grid resilience to be considered, some of which may justify a marae’s decision to invest in a non-economic system to gain better community benefits. While investigating the use of peer-to-peer energy trading and community energy scenarios, sharing excess energy generated by a system with the wider community was also found to improve the economic outlook of solar for marae.

year: 2024