AN EARLY CLASSIFICATION OF NEW ZEALAND COASTAL CLIMATES

1964 ◽  
Vol 16 (2) ◽  
pp. 6-10
Author(s):  
R. P. Hargreaves ◽  
W. J. Maunder
Keyword(s):  
New Zealand ◽  
Early Classification

Early Classification of Time Series: Cost-based multiclass Algorithms

2021 ◽  
Author(s):  
Paul-Emile Zafar ◽  
Youssef Achenchabe ◽  
Alexis Bondu ◽  
Antoine Cornuejols ◽  
Vincent Lemaire
Keyword(s):  
Time Series ◽  
Early Classification

scholarly journals A Hardware-Deployable Neuromorphic Solution for Encoding and Classification of Electronic Nose Data

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4831 ◽  
Author(s):  
Anup Vanarse ◽  
Adam Osseiran ◽  
Alexander Rassau ◽  
Peter van der Made
Keyword(s):  
Data Processing ◽  
Electronic Nose ◽  
Spike Timing ◽  
Sensor Data ◽  
Development Environment ◽  
Early Classification ◽  
Recent Developments ◽  
Efficient Data ◽  
Olfactory Systems

In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking neural network (SNN)-based classifier, implemented in a chip-emulation-based development environment, that can be seamlessly deployed on a neuromorphic system-on-a-chip (NSoC). Under three different scenarios of increasing complexity, the SNN was determined to be able to classify real-valued sensor data with greater than 90% accuracy and with a maximum latency of 3 s on the software-based platform. Highlights of this work included the design and implementation of a novel encoder for artificial olfactory systems, implementation of unsupervised spike-timing-dependent plasticity (STDP) for learning, and a foundational study on early classification capability using the SNN-based classifier.

scholarly journals Approaches and Applications of Early Classification of Time Series: A Review

2020 ◽  
Vol 1 (1) ◽  
pp. 47-61
Author(s):  
Ashish Gupta ◽  
Hari Prabhat Gupta ◽  
Bhaskar Biswas ◽  
Tanima Dutta
Keyword(s):  
Time Series ◽  
Early Classification

scholarly journals O1A.6 The carcinogenicity of pesticides used in new zealand

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A4.2-A4
Author(s):  
Andrea ‘t Mannetje
Keyword(s):  
New Zealand ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Agricultural Sector ◽  
Intervention Strategy ◽  
Epidemiological Studies ◽  
Regulatory Agencies ◽  
International Agency ◽  
Active Ingredients

IntroductionYearly over 3000 tonnes of pesticide active ingredients are applied in New Zealand agriculture. Since the 1980’s, epidemiological studies have reported increased risks of lymphopoietic cancers in agricultural sectors with high pesticide use. Here we aim to estimate the number and total volume of currently used pesticides in New Zealand that are known or suspected human carcinogens, in order to inform interventions.MethodsFor each of the pesticide active ingredients most commonly used in New Zealand, the carcinogenicity classification of three regulatory agencies (The New Zealand Environmental Protection Authority [NZ-EPA], the US Environmental Protection Agency [US-EPA], and the European Chemicals Agency [EU]) were extracted, as well as the classification of the International Agency for Research on Cancer (IARC) Monograph Programme. Total tonnes of active ingredients that are known or suspected human carcinogens was calculated for each classification.ResultsNone of the pesticides used in New Zealand are classified as known human carcinogens by any of the three regulatory agencies or IARC. Annually New Zealand uses 148–756 tonnes of active pesticide ingredients that are classified as suspected human carcinogens by the three regulatory agencies. If also including the pesticides classified by IARC as possible or probable human carcinogens, the upper estimate doubles to 1475 tonnes, representing half of the total volume of pesticide active ingredients used in New Zealand agriculture. The percentage and volume of active ingredients classified as suspected carcinogens by the three regulatory agencies was highest for the fungicides (8%–60%; 72–540 tonnes), followed by herbicides (3%–10%; 60–200 tonnes), and insecticides (8%, 16 tonnes).ConclusionsAlthough no known human carcinogens are used as pesticides, New Zealand’s high use of pesticides that are suspected carcinogens requires a greater awareness of the presence of potential carcinogens in the agricultural sector and the development of an intervention strategy to reduce cancer risk.

Saxipoa and Sylvipoa - two new genera and a new classification for Australian Poa (Poaceae: Poinae)

2009 ◽  
Vol 22 (6) ◽  
pp. 401 ◽  
Author(s):  
Robert J. Soreng ◽  
Lynn J. Gillespie ◽  
Surrey W. L. Jacobs
Keyword(s):  
New Zealand ◽  
New Genera ◽  
New Classification ◽  
Indigenous Australian ◽  
Infrageneric Classification ◽  
Australian Species

Two species are removed from the genus Poa in Australia on the basis of morphology and DNA and placed in new genera. One is placed in Saxipoa Soreng, L.J.Gillespie & S.W.L.Jacobs – type: S. saxicola (R.Br.) Soreng, L.J.Gillespie & S.W.L.Jacobs; and one is placed in Sylvipoa Soreng, L.J.Gillespie & S.W.L.Jacobs – type: S. queenslandica (C.E.Hubb.) Soreng, L.J.Gillespie & S.W.L.Jacobs. An infrageneric classification of Poa is proposed that places all 41 indigenous Australian species in P. subg. Poa supersect. Homalopoa sect. Brizoides. Thirty-three of these species, plus six species of New Zealand Poa, are placed in a new P. subsect. Australopoa Soreng, L.J.Gillespie & S.W.L.Jacobs. Two species are placed in P. subsect. Austrofestuca (Tzvelev) Soreng, L.J.Gillespie & S.W.L.Jacobs, one in P. subsect. Brizoides (Pilg. ex Potztal) Soreng, L.J.Gillespie & S.W.L.Jacobs, and one in P. subsect. Neuropoa (Clayton) Soreng, L.J.Gillespie & S.W.L.Jacobs.

scholarly journals Work-Related Fatalities Involving Children in New Zealand, 1999–2014

Children ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 4
Author(s):  
Rebbecca Lilley ◽  
Bronwen McNoe ◽  
Gabrielle Davie ◽  
Brandon de Graaf ◽  
Tim Driscoll
Keyword(s):  
New Zealand ◽  
Moving Objects ◽  
Unintentional Injury ◽  
Child Work ◽  
Workplace Hazards ◽  
Work Related ◽  
International Classification Of Disease ◽  
Injury Mortality ◽  
Work Related Injury

In high income countries, children under 15 years of age are exposed to workplace hazards when they visit or live on worksites or participate in formal or informal work. This study describes the causes and circumstances of unintentional child work-related fatal injuries (child WRFI) in New Zealand. Potential cases were identified from the Mortality Collection using International Classification of Disease external cause codes: these were matched to Coronial records and reviewed for work-relatedness. Data were abstracted on the socio-demographic, employment and injury-related circumstances. Of the 1335 unintentional injury deaths in children from 1999 through 2014, 206 (15%) were identified as dying from a work-related injury: 9 workers and 197 bystanders—the majority involving vehicle crashes or being stuck by moving objects in incidents occurring on farms or public roads. Those at highest risk were males, preschoolers, and those of Māori or European ethnicity. Work made a notable contribution to the burden of unintentional fatal injury in children with most deaths highly preventable, largely by adult intervention and legislation. To address the determinants of child WRFI greater attention on rural farm and transport settings would result in a significant reduction in the injury mortality rates of New Zealand children.

An Ecoregion Classification of the South Island, New Zealand

1997 ◽  
Vol 51 (3) ◽  
pp. 275-287 ◽  
Author(s):  
Jon S. Harding ◽  
Michael J. Winterbourn
Keyword(s):  
New Zealand ◽  
The South
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