title: Sustainable milk powder production using enhanced process integration and 100 % renewable energy

authors: Walmsley, Michael R.W.

abstract: This paper presents a Total Site analysis of the requirements to integrate 100 % renewable energy into a 10 t/h ultra-low energy milk power factory of the future in New Zealand and California. The location of the factory is important for selecting renewable energy options and therefore three case studies from three different locations are reported. In New Zealand the best option is to use renewable electricity from wind, hydro and geothermal for the factory electrical needs, and high temperature geothermal energy when available for process heating up to 210 °C and low temperature geothermal energy with MVR technology upgrading for process heating up to 180 °C. When no geothermal energy is available the best option is renewable electricity driven heat pumps for heating up to 85 °C, and biomass (wood residue) for high temperature heating up to 210 °C. Biomass production, however, will require 35 % more land than the farms require for producing the milk. In California renewable energy is best met using biogas from anaerobic digestion of cow manure and solar thermal. Biogas converted into biomethane on farm fuels a combine cycle gas turbine with a heat recover steam generator (HRSG) to meet process heating needs above 80 °C and all factory and biogas compression electrical needs. Solar thermal with day-night storage provides hot water utility. A cow manure collection rate of 37 % is required to meet both process heat and electricity needs.

text: Sustainable milk powder production using enhanced process integration and 100 % renewable energy This paper presents a Total Site analysis of the requirements to integrate 100 % renewable energy into a 10 t/h ultra-low energy milk power factory of the future in New Zealand and California. The location of the factory is important for selecting renewable energy options and therefore three case studies from three different locations are reported. In New Zealand the best option is to use renewable electricity from wind, hydro and geothermal for the factory electrical needs, and high temperature geothermal energy when available for process heating up to 210 °C and low temperature geothermal energy with MVR technology upgrading for process heating up to 180 °C. When no geothermal energy is available the best option is renewable electricity driven heat pumps for heating up to 85 °C, and biomass (wood residue) for high temperature heating up to 210 °C. Biomass production, however, will require 35 % more land than the farms require for producing the milk. In California renewable energy is best met using biogas from anaerobic digestion of cow manure and solar thermal. Biogas converted into biomethane on farm fuels a combine cycle gas turbine with a heat recover steam generator (HRSG) to meet process heating needs above 80 °C and all factory and biogas compression electrical needs. Solar thermal with day-night storage provides hot water utility. A cow manure collection rate of 37 % is required to meet both process heat and electricity needs.

year: 2016

title: Interactive concept learning for end-user applications

authors: Maulsby, David

subjects: computer science

abstract: Personalizable software agents will learn new tasks from their users. This implies being able to learn from instructions users might give: examples, yes/no responses, and ambiguous, incomplete hints. Agents should also exploit background knowledge customized for applications such as drawing, word processing and form-filling. The task models that agents learn describe data, actions and their context. Learning about data from examples and hints is the subject of this paper. The Cima learning system combines evidence from examples, task knowledge and user hints to form Disjunctive Normal Form (DNF) rules for classifying, generating or modifying data. Cima's dynamic bias manager generates candidate features (attribute values, functions or relations), from which its DNF learning algorithm selects relevant features and forms the rules. The algorithm is based on a classic greedy method, with two enhancements. First, the standard learning criterion, correct classification, is augmented with a set of utility and instructional criteria. Utility criteria ensure that descriptions are properly formed for use in actions, whether to classify, search for, generate or modify data. Instructional criteria ensure that descriptions include features that users suggest and avoid those that users reject. The second enhancement is to augment the usual statistical metric for selecting relevant attributes with a set of heuristics, including beliefs based on user suggestions and application-specific background knowledge. Using multiple heuristics increases the justification for selecting features; more important, it helps the learner choose among alternative interpretations of hints. When tested on dialogues observed in a prior user study on a simulated interface agent, the learning algorithm achieves 95% of the learning efficiency standard established in that study.

text: Interactive concept learning for end-user applications Personalizable software agents will learn new tasks from their users. This implies being able to learn from instructions users might give: examples, yes/no responses, and ambiguous, incomplete hints. Agents should also exploit background knowledge customized for applications such as drawing, word processing and form-filling. The task models that agents learn describe data, actions and their context. Learning about data from examples and hints is the subject of this paper. The Cima learning system combines evidence from examples, task knowledge and user hints to form Disjunctive Normal Form (DNF) rules for classifying, generating or modifying data. Cima's dynamic bias manager generates candidate features (attribute values, functions or relations), from which its DNF learning algorithm selects relevant features and forms the rules. The algorithm is based on a classic greedy method, with two enhancements. First, the standard learning criterion, correct classification, is augmented with a set of utility and instructional criteria. Utility criteria ensure that descriptions are properly formed for use in actions, whether to classify, search for, generate or modify data. Instructional criteria ensure that descriptions include features that users suggest and avoid those that users reject. The second enhancement is to augment the usual statistical metric for selecting relevant attributes with a set of heuristics, including beliefs based on user suggestions and application-specific background knowledge. Using multiple heuristics increases the justification for selecting features; more important, it helps the learner choose among alternative interpretations of hints. When tested on dialogues observed in a prior user study on a simulated interface agent, the learning algorithm achieves 95% of the learning efficiency standard established in that study.

year: 1995-02

title: Art, the aesthetics, and ethics of tattooing at Flax Roots Tattoo Studio

authors: Shaver, Mandy (Amanda)

subjects: aesthetic

abstract: Flax Roots Tattoo Studio, a tattoo business in Hamilton, Waikato, New Zealand, offers clients different styles of tattooing to choose from, i.e. Moko, Traditional European, Portrait, and Traditional American. Tattoo artists and their clients differ in ethnicity, nationality, religion, sex, occupation, age, hobbies, and so on.  Anthropological research and philosophical insight provided the framework texts for my case study.  My fieldwork consisted of semi-structured interviews and photographs of artists and clients.  By participating in tattooing, these individuals influence the art and the aesthetic tastes of their local culture.  Additionally, tattoo artists follow an ethical code that dictates how to run their business, preserve their art, and protect their clients.  By choosing Flax Roots Tattoo Studio as my fieldwork site, I was able to answer the questions: 1. How do tattoo artists and their clients engage with and shape tattoo art and its aesthetic at Flax Roots Tattoo Studio? ; and 2. How do these tattoo artists’ ethics influence their relationships with their clients and art?

text: Art, the aesthetics, and ethics of tattooing at Flax Roots Tattoo Studio Flax Roots Tattoo Studio, a tattoo business in Hamilton, Waikato, New Zealand, offers clients different styles of tattooing to choose from, i.e. Moko, Traditional European, Portrait, and Traditional American. Tattoo artists and their clients differ in ethnicity, nationality, religion, sex, occupation, age, hobbies, and so on.  Anthropological research and philosophical insight provided the framework texts for my case study.  My fieldwork consisted of semi-structured interviews and photographs of artists and clients.  By participating in tattooing, these individuals influence the art and the aesthetic tastes of their local culture.  Additionally, tattoo artists follow an ethical code that dictates how to run their business, preserve their art, and protect their clients.  By choosing Flax Roots Tattoo Studio as my fieldwork site, I was able to answer the questions: 1. How do tattoo artists and their clients engage with and shape tattoo art and its aesthetic at Flax Roots Tattoo Studio? ; and 2. How do these tattoo artists’ ethics influence their relationships with their clients and art?

year: 2018