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32 results on '"Kenny, Owen"'

2. DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning

Author

Olsen, Alex, Konovalov, Dmitry A., Philippa, Bronson, Ridd, Peter, Wood, Jake C., Johns, Jamie, Banks, Wesley, Girgenti, Benjamin, Kenny, Owen, Whinney, James, Calvert, Brendan, Azghadi, Mostafa Rahimi, and White, Ronald D.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Robotic weed control has seen increased research of late with its potential for boosting productivity in agriculture. Majority of works focus on developing robotics for croplands, ignoring the weed management problems facing rangeland stock farmers. Perhaps the greatest obstacle to widespread uptake of robotic weed control is the robust classification of weed species in their natural environment. The unparalleled successes of deep learning make it an ideal candidate for recognising various weed species in the complex rangeland environment. This work contributes the first large, public, multiclass image dataset of weed species from the Australian rangelands; allowing for the development of robust classification methods to make robotic weed control viable. The DeepWeeds dataset consists of 17,509 labelled images of eight nationally significant weed species native to eight locations across northern Australia. This paper presents a baseline for classification performance on the dataset using the benchmark deep learning models, Inception-v3 and ResNet-50. These models achieved an average classification accuracy of 95.1% and 95.7%, respectively. We also demonstrate real time performance of the ResNet-50 architecture, with an average inference time of 53.4 ms per image. These strong results bode well for future field implementation of robotic weed control methods in the Australian rangelands., Comment: 14 pages, 8 figures, 4 tables

Published
2018
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8. Characterization and in vitro assessment of seaweed bioactives with potential to reduce methane production

Author

Krizsan, Sophie Julie, Hayes, Maria, Gröndahl, Fredrik, Ramin, Mohammad, O'Hara, Peter, and Kenny, Owen

Subjects
Botany
Abstract

This study collates compositional analysis of seaweeds data with information generated from in vitro gas production assays in the presence and absence of seaweeds. The aim was to assess and rank 27 native northern European seaweeds as potential feed ingredients for use to reduce methane emissions from ruminants. It provides information for use in future in vivo dietary trials concerning feed manipulation strategies to reduce CH4 emissions efficiently from domestic ruminants based on dietary seaweed supplementation. The seaweeds H. siliquosa and A. nodosum belonging to phylum Phaeophyta displayed the highest concentration of phlorotannins and antioxidant activity among the macroalgae giving anti-methanogenic effect in vitro, while this explanation was not valid for the observed reduction in methane when supplementing with C. filum and L. digitata in this study. D. carnosa and C. tenuicorne belonging to phylum Rhodophyta had the highest protein content among the macroalgae that reduced methane production in vitro. There were no obvious explanation from the compositional analysis conducted in this study to the reduced methane production in vitro when supplementing with U. lactuca belonging to phylum Chlorophyta. The strongest and most complete methane inhibition in vitro was observed when supplementing with Asparagopsis taxiformis that was used as a positive control in this study.

Published
2022
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9. Characterization and in vitro assessment of seaweed bioactives with potential to reduce methane production

Author

Krizsan, Sophie J., Hayes, Maria, Gröndahl, Fredrik, Ramin, Mohammad, O'Hara, Peter, Kenny, Owen, Krizsan, Sophie J., Hayes, Maria, Gröndahl, Fredrik, Ramin, Mohammad, O'Hara, Peter, and Kenny, Owen

Abstract

This study collates compositional analysis of seaweeds data with information generated from in vitro gas production assays in the presence and absence of seaweeds. The aim was to assess and rank 27 native northern European seaweeds as potential feed ingredients for use to reduce methane emissions from ruminants. It provides information for use in future in vivo dietary trials concerning feed manipulation strategies to reduce CH4 emissions efficiently from domestic ruminants based on dietary seaweed supplementation. The seaweeds H. siliquosa and A. nodosum belonging to phylum Phaeophyta displayed the highest concentration of phlorotannins and antioxidant activity among the macroalgae giving anti-methanogenic effect in vitro, while this explanation was not valid for the observed reduction in methane when supplementing with C. filum and L. digitata in this study. D. carnosa and C. tenuicorne belonging to phylum Rhodophyta had the highest protein content among the macroalgae that reduced methane production in vitro. There were no obvious explanation from the compositional analysis conducted in this study to the reduced methane production in vitro when supplementing with U. lactuca belonging to phylum Chlorophyta. The strongest and most complete methane inhibition in vitro was observed when supplementing with Asparagopsis taxiformis that was used as a positive control in this study., QC 20230706

Published
2022
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14. Application of a three-dimensional hyperbolic location system to the false killer whale (Pseudorca crassidens) depredation issue

Author

McPherson, Craig, Turner, Phil, McPherson, Geoff, and Kenny, Owen P.

Subjects
Coral Sea -- Environmental aspects, Killer whale -- Research, Longlining (Fisheries) -- Environmental aspects, Longlining (Fisheries) -- Economic aspects, Environmental services industry
Abstract

Byline: Craig McPherson, Phil Turner, Geoff McPherson, Owen P. Kenny Depredation by false killer whale (Pseudorca crassidens) is a serious problem for pelagic longline fishing in the Coral Sea. These interactions have raised substantial ecological, economic and social concerns. McPherson et al. proposed post-processing of passive acoustic recordings to analyse general odontocete acoustic behaviour and assess the effectiveness of systems being developed to reduce depredation. The location system developed to address this need utilises signal Time of Arrival Differences (TOADs) between hydrophone pairs, which confines the signal source to a hyperboloid. Through the use of a sufficient number of receivers, the resultant intersecting hyperboloids can be analysed using a 'surface search' routine to determine source location. The results presented show the capabilities of the algorithm when used with a specific hydrophone array configuration, and the practicality of use for monitoring depredation. This paper provides an overview of the techniques and discusses the adaptability of its application.

Published
2007

19. Role of Lactobacilli in Flavour Development of Cheddar Cheese

Author

Beresford, Tom, Cogan, Tim, Rea, Mary C., Drinan, Finbarr, Fitzsimons, Nora, Brennan, N., Kenny, Owen, and Fox, P.F.

Subjects
Cheddar cheese, lactobacilli (NSLAB), food and beverages, flavour development
Abstract

End of Project Report Cheddar cheese is a complex microbial ecosystem. The internal cheese environment, in particular of hard and semi-hard cheeses, is not conducive to the growth of many microorganisms. At the beginning of ripening the dominant microorganisms are the starter bacteria which are present at high levels (~109/g). However, during ripening, non-starter lactic acid bacteria (NSLAB) grow from relatively low levels (

Published
2001

31. Statistical Performance of a TFD based Detection Scheme.

Author

Kenny, Owen and White, Langford

Abstract

This paper proposes a robust signal detection procedure based on generalised patterns in time-frequency space. The paper derives a non-linear time domain correlation process which is equivalent to a time-frequency based detection scheme. The performance of this robust detection scheme in the additive white Gaussian noise case is evaluated with the aid of receiver operating curves. Some examples are given which show that the proposed procedure under nominal conditions does not perform as well as standard detection scheme (ie matched filter) but gives better performance when the measured signal deviates from its nominal model. [ABSTRACT FROM AUTHOR]

Published
1998
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32. In Vitro Protocols for Measuring the Antioxidant Capacity of Algal Extracts.

Author

Kenny O, Brunton NP, and Smyth TJ

Subjects
Antioxidants chemistry, Benzothiazoles chemistry, Biphenyl Compounds chemistry, Carotenoids chemistry, Fluorometry methods, Free Radicals chemistry, High-Throughput Screening Assays methods, Hypochlorous Acid chemistry, Iron chemistry, Phenols chemistry, Picrates chemistry, Sulfonic Acids chemistry, Thiobarbiturates chemistry, Thiocyanates chemistry, Antioxidants pharmacology, Seaweed chemistry
Abstract

In the last decade a large amount of research has been directed at targeting algal resources for biologically active molecules. High-throughput in vitro antioxidant assays are routinely used to screen for biologically active compounds present in algal extracts when the requirement is to identify samples for progression to more detailed biological scrutiny. Whilst a myriad of antioxidant assays have been developed, this present chapter aims to give step-by-step practical guidance on how to carry out some of the most popular and biologically relevant assays at the bench.

Published
2015
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