title: The creative university: Creative social development and academic entrepreneurship

authors: Besley, Tina

subjects: Education

abstract: The idea that the university needs re-imagining has gained considerable currency since the 21th century. Just why this should be needs some analysis and an examination of the functions and role(s) of universities. Some universities, especially in USA, have recently conducted exercises to achieve this in specific ways that deal with local issues (e.g. Cornell, Harvard, Minnesota, New York, Brown¹). It seems that much of the re-imagining discourse focuses on institutional financial issues, and this tends to play out as part of the crisis in universities literature, which may well be related to the crisis in schools and reform movements there as promoted by neoliberal policy agendas. Crisis discourses frequently use economic consultant advisory reports from large multinational companies (e.g. Ernst & Young and Pearson as described later in this chapter) to provide some degree of analysis. More often than not solutions offered tend to promote forms of university that such as the entrepreneurial university that emphasize research and forms of academic entrepreneurship beyond the traditional forms related to publishing. More recently teaching has become the focus in re-imagining as many universities not only become more global in their focus, but as they start to address modalities of pedagogy as presented by recent IT based systems in MOOCs.

text: The creative university: Creative social development and academic entrepreneurship The idea that the university needs re-imagining has gained considerable currency since the 21th century. Just why this should be needs some analysis and an examination of the functions and role(s) of universities. Some universities, especially in USA, have recently conducted exercises to achieve this in specific ways that deal with local issues (e.g. Cornell, Harvard, Minnesota, New York, Brown¹). It seems that much of the re-imagining discourse focuses on institutional financial issues, and this tends to play out as part of the crisis in universities literature, which may well be related to the crisis in schools and reform movements there as promoted by neoliberal policy agendas. Crisis discourses frequently use economic consultant advisory reports from large multinational companies (e.g. Ernst & Young and Pearson as described later in this chapter) to provide some degree of analysis. More often than not solutions offered tend to promote forms of university that such as the entrepreneurial university that emphasize research and forms of academic entrepreneurship beyond the traditional forms related to publishing. More recently teaching has become the focus in re-imagining as many universities not only become more global in their focus, but as they start to address modalities of pedagogy as presented by recent IT based systems in MOOCs.

year: 2013

title: Maximal Associated Regression: A nonlinear extension to Least Angle Regression

authors: Abeysekera, Sanush K.

abstract: This paper proposes Maximal Associated Regression (MAR), a novel algorithm that performs forward stage-wise regression by applying nonlinear transformations to fit predictor covariates. For each predictor, MAR selects between a linear or additive fit as determined by the dataset. The proposed algorithm is an adaptation of Least Angle Regression (LARS) and retains its efficiency in building sparse models. Constrained penalized splines are used to generate smooth nonlinear transformations for the additive fits. A monotonically constrained extension of MAR (MARm) is also introduced in this paper to fit isotonic regression problems. The proposed algorithms are validated on both synthetic and real datasets. The performances of MAR and MARm are compared against LARS, Generalized Linear Models (GLM), and Generalized Additive Models (GAM) under the Gaussian assumption with a unity link function. Results indicate that MAR-type algorithms achieve a superior subset selection accuracy, generating sparser models that generalize well to new data. MAR is also able to generate models for sample deficient datasets. Thus, MAR is proposed as a valuable tool for subset selection and data exploration, especially when a priori knowledge of the dataset is unavailable.

text: Maximal Associated Regression: A nonlinear extension to Least Angle Regression This paper proposes Maximal Associated Regression (MAR), a novel algorithm that performs forward stage-wise regression by applying nonlinear transformations to fit predictor covariates. For each predictor, MAR selects between a linear or additive fit as determined by the dataset. The proposed algorithm is an adaptation of Least Angle Regression (LARS) and retains its efficiency in building sparse models. Constrained penalized splines are used to generate smooth nonlinear transformations for the additive fits. A monotonically constrained extension of MAR (MARm) is also introduced in this paper to fit isotonic regression problems. The proposed algorithms are validated on both synthetic and real datasets. The performances of MAR and MARm are compared against LARS, Generalized Linear Models (GLM), and Generalized Additive Models (GAM) under the Gaussian assumption with a unity link function. Results indicate that MAR-type algorithms achieve a superior subset selection accuracy, generating sparser models that generalize well to new data. MAR is also able to generate models for sample deficient datasets. Thus, MAR is proposed as a valuable tool for subset selection and data exploration, especially when a priori knowledge of the dataset is unavailable.

year: 2021

title: Te whakaihonga: He tikanga tapahi makawe i te ao Māori

authors: McDonald, Rangihurihia Ann

subjects: Tapahi makawe

abstract: E ai ki te Māori, mai anō i a Māui Pōtiki, kua tapahia e te pouaru, e te kirimate, ngō rātou makawe i te tangihanga. He reureu, he tiotio, he pakipaki taha ngētehi o ngā tohu weriweri nei, i tauawhi, i whakaū i te aroha ki te mate. I ngētehi wā, he whakamaumahara, he take whakariri i te ngākau, he utu i te tangi kino o te manawa. Mutu kau ana te tangihanga, ko te heuenga hoki i te whare tauā, ki te wai whakaika. Ko ngētehi take ngēnei o te tapahi makawe a te kirimate, otirā, ko te tino whāinga o tēnei tuhinga whakapae. He whakapono makawe anō i whakaemingia, nā te rangahau mātātuhi, ko ngā pūrākau, ngā mōteatea, ngā whakataukī anō hoki a ngā tūpuna. He tirohanga kaumātua i kohikohingia nā roto mai o te uiui. Waiho mai ana ko ngā tikanga tawhito mō te tapahi i te uru tapu o te tangata, ki te ao tūroa.

text: Te whakaihonga: He tikanga tapahi makawe i te ao Māori E ai ki te Māori, mai anō i a Māui Pōtiki, kua tapahia e te pouaru, e te kirimate, ngō rātou makawe i te tangihanga. He reureu, he tiotio, he pakipaki taha ngētehi o ngā tohu weriweri nei, i tauawhi, i whakaū i te aroha ki te mate. I ngētehi wā, he whakamaumahara, he take whakariri i te ngākau, he utu i te tangi kino o te manawa. Mutu kau ana te tangihanga, ko te heuenga hoki i te whare tauā, ki te wai whakaika. Ko ngētehi take ngēnei o te tapahi makawe a te kirimate, otirā, ko te tino whāinga o tēnei tuhinga whakapae. He whakapono makawe anō i whakaemingia, nā te rangahau mātātuhi, ko ngā pūrākau, ngā mōteatea, ngā whakataukī anō hoki a ngā tūpuna. He tirohanga kaumātua i kohikohingia nā roto mai o te uiui. Waiho mai ana ko ngā tikanga tawhito mō te tapahi i te uru tapu o te tangata, ki te ao tūroa.

year: 2011