title: Clustering based active learning for evolving data streams

authors: Ienco, Dino

subjects: computer science

abstract: Data labeling is an expensive and time-consuming task. Choosing which labels to use is increasingly becoming important. In the active learning setting, a classifier is trained by asking for labels for only a small fraction of all instances. While many works exist that deal with this issue in non-streaming scenarios, few works exist in the data stream setting. In this paper we propose a new active learning approach for evolving data streams based on a pre-clustering step, for selecting the most informative instances for labeling. We consider a batch incremental setting: when a new batch arrives, first we cluster the examples, and then, we select the best instances to train the learner. The clustering approach allows to cover the whole data space avoiding to oversample examples from only few areas. We compare our method w.r.t. state of the art active learning strategies over real datasets. The results highlight the improvement in performance of our proposal. Experiments on parameter sensitivity are also reported.

text: Clustering based active learning for evolving data streams Data labeling is an expensive and time-consuming task. Choosing which labels to use is increasingly becoming important. In the active learning setting, a classifier is trained by asking for labels for only a small fraction of all instances. While many works exist that deal with this issue in non-streaming scenarios, few works exist in the data stream setting. In this paper we propose a new active learning approach for evolving data streams based on a pre-clustering step, for selecting the most informative instances for labeling. We consider a batch incremental setting: when a new batch arrives, first we cluster the examples, and then, we select the best instances to train the learner. The clustering approach allows to cover the whole data space avoiding to oversample examples from only few areas. We compare our method w.r.t. state of the art active learning strategies over real datasets. The results highlight the improvement in performance of our proposal. Experiments on parameter sensitivity are also reported.

year: 2013

title: Treating Water Using a Perforated Electrode Flow Through Cell

authors: Hettiarachchi, Jayani

abstract: Perforated Electrode Flow Through cell (PEFT cell) is an undivided electro –chlorination cell designed by the University of Waikato. A new design was developed that consists of two sets of perforated electrodes assembled in a 3D printed casing. The aim of this research was to test the new PEFT cell for chlorine production, trial it for E-coli disinfection and iron and manganese removal by coupling it to a DMI-65 column. Maximum chlorine concentration was achieved at 0.1 mol/L NaCl concentration at a flow rate of 1.8 ml/s at 5 volts and 10 amps, and a current density of 44 mA/cm2, resulting in a chlorine concentration of 510 mg/L. Chlorine production increased with increasing salt concentration but decreased with flow rate. Maximum chlorine production rate was at 0.14 mg/s.amp at 7.41 ml/s flow rate. Total inactivation of E-coli bacteria was achieved for all conditions tested. Iron and manganese removals of 92.5% and 90% respectively were achieved for synthetic bore water when the PEFT cell was coupled to a DMI-65 column.

text: Treating Water Using a Perforated Electrode Flow Through Cell Perforated Electrode Flow Through cell (PEFT cell) is an undivided electro –chlorination cell designed by the University of Waikato. A new design was developed that consists of two sets of perforated electrodes assembled in a 3D printed casing. The aim of this research was to test the new PEFT cell for chlorine production, trial it for E-coli disinfection and iron and manganese removal by coupling it to a DMI-65 column. Maximum chlorine concentration was achieved at 0.1 mol/L NaCl concentration at a flow rate of 1.8 ml/s at 5 volts and 10 amps, and a current density of 44 mA/cm2, resulting in a chlorine concentration of 510 mg/L. Chlorine production increased with increasing salt concentration but decreased with flow rate. Maximum chlorine production rate was at 0.14 mg/s.amp at 7.41 ml/s flow rate. Total inactivation of E-coli bacteria was achieved for all conditions tested. Iron and manganese removals of 92.5% and 90% respectively were achieved for synthetic bore water when the PEFT cell was coupled to a DMI-65 column.

year: 2017

title: Maori perspectives of the environment: A review of spatial databases

authors: Whangapirita, Laura

subjects: Maori

abstract: As part of our broader brief to gather, summarise, analyse and distribute information held by Environment Waikato on Maori and the environment, we identified and analysed a number of spatial datasets managed by the Information Resource Group. This report has been prepared to contribute towards developing a resource fro Environment Waikato’s Strategic Plan Review Teams.

text: Maori perspectives of the environment: A review of spatial databases As part of our broader brief to gather, summarise, analyse and distribute information held by Environment Waikato on Maori and the environment, we identified and analysed a number of spatial datasets managed by the Information Resource Group. This report has been prepared to contribute towards developing a resource fro Environment Waikato’s Strategic Plan Review Teams.

year: 2003-11