Search

Your search keyword '"Manchester Metropolitan University ( MMU )"' showing total 4 results
Start Over Author "Manchester Metropolitan University ( MMU )" Publisher wiley
4 results on '"Manchester Metropolitan University ( MMU )"'

1. Detecting and reducing heterogeneity of error in acoustic classification

Author

Oliver C. Metcalf, Jos Barlow, Yves Bas, Erika Berenguer, Christian Devenish, Filipe França, Stuart Marsden, Charlotte Smith, Alexander C. Lees, Manchester Metropolitan University (MMU), Lancaster University, Centre d'Ecologie et des Sciences de la COnservation (CESCO), Muséum national d'Histoire naturelle (MNHN)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), University of Oxford, School of Biological Sciences [Bristol], and University of Bristol [Bristol]

Subjects
autonomous recording unit, bioacoustics, ecoacoustics, [SDE.IE]Environmental Sciences/Environmental Engineering, Ecological Modeling, machine-learning, [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], [PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph], automated signal recognition, Ecology, Evolution, Behavior and Systematics, [PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph]
Abstract

Passive acoustic monitoring can be an effective method for monitoring species, allowing the assembly of large audio datasets, removing logistical constraints in data collection and reducing anthropogenic monitoring disturbances. However, the analysis of large acoustic datasets is challenging and fully automated machine learning processes are rarely developed or implemented in ecological field studies. One of the greatest uncertainties hindering the development of these methods is spatial generalisability—can an algorithm trained on data from one place be used elsewhere?We demonstrate that heterogeneity of error across space is a problem that could go undetected using common classification accuracy metrics. Second, we develop a method to assess the extent of heterogeneity of error in a random forest classification model for six Amazonian bird species. Finally, we propose two complementary ways to reduce heterogeneity of error, by (i) accounting for it in the thresholding process and (ii) using a secondary classifier that uses contextual data.We found that using a thresholding approach that accounted for heterogeneity of precision error reduced the coefficient of variation of the precision score from a mean of 0.61 ± 0.17 (SD) to 0.41 ± 0.25 in comparison to the initial classification with threshold selection based on F-score. The use of a secondary, contextual classification with thresholding selection accounting for heterogeneity of precision reduced it further still, to 0.16 ± 0.13, and was significantly lower than the initial classification in all but one species. Mean average precision scores increased, from 0.66 ± 0.4 for the initial classification, to 0.95 ± 0.19, a significant improvement for all species.We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.

Published
2022
Full Text
View/download PDF

2. GUEST EDITORIAL—SPECIAL ISSUE: Mapping and modelling soil erosion to address societal challenges in a changing world

Author

Nunes, João Pedro, Smetanova, Anna, Nunes, João, Symeonakis, Elias, Brevik, Eric, Schindelwolf, Marcus, Ciampalini, Rossano, Centre for Ecology - Evolution and Environmental Changes (cE3c), Universidade de Lisboa = University of Lisbon (ULISBOA), Technical University of Berlin / Technische Universität Berlin (TU), Centro de Estudos Sociais (CES), University of Coimbra [Portugal] (UC), Manchester Metropolitan University (MMU), Dickinson State University, Thuringian State Institute of Agriculture, Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Repositório da Universidade de Lisboa, Universidade de Lisboa (ULISBOA), Technical University Berlin, Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SDV]Life Sciences [q-bio], [SDE.MCG]Environmental Sciences/Global Changes, Land management, Soil Science, Climate change, 04 agricultural and veterinary sciences, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 15. Life on land, 010501 environmental sciences, Development, [SDE.ES]Environmental Sciences/Environmental and Society, 01 natural sciences, Modelling methods, Political science, 040103 agronomy & agriculture, Erosion, Land degradation, 0401 agriculture, forestry, and fisheries, Environmental Chemistry, Neutrality, Nexus (standard), Environmental planning, 0105 earth and related environmental sciences, General Environmental Science
Abstract

Submitted by Sara Bento (fc43143@alunos.fc.ul.pt) on 2021-09-28T16:56:17Z No. of bitstreams: 1 GUEST EDITORIA - SPECIAL ISSUE Mapping and modelling soil erosion_1.pdf: 337750 bytes, checksum: f8857dfe4d99b0b8e8ac46c0f19f908d (MD5) Approved for entry into archive by Sara Bento (fc43143@alunos.fc.ul.pt) on 2021-09-28T16:56:39Z (GMT) No. of bitstreams: 1 GUEST EDITORIA - SPECIAL ISSUE Mapping and modelling soil erosion_1.pdf: 337750 bytes, checksum: f8857dfe4d99b0b8e8ac46c0f19f908d (MD5) Approved for entry into archive by Margarida Matos (mmmatos@fc.ul.pt) on 2021-09-28T19:17:41Z (GMT) No. of bitstreams: 1 GUEST EDITORIA - SPECIAL ISSUE Mapping and modelling soil erosion_1.pdf: 337750 bytes, checksum: f8857dfe4d99b0b8e8ac46c0f19f908d (MD5) Made available in DSpace on 2021-09-28T19:17:56Z (GMT). No. of bitstreams: 1 GUEST EDITORIA - SPECIAL ISSUE Mapping and modelling soil erosion_1.pdf: 337750 bytes, checksum: f8857dfe4d99b0b8e8ac46c0f19f908d (MD5) Previous issue date: 2020-11 info:eu-repo/semantics/publishedVersion

Published
2019
Full Text
View/download PDF

3. Defining the indigenous ranges of species to account for geographic and taxonomic variation in the history of human impacts: reply to Sanderson 2019

Author

Erik Meijaard, Thomas M. Brooks, Jon Paul Rodríguez, Ana S. L. Rodrigues, P. J. Stephenson, Molly K. Grace, Barney Long, Craig Hilton-Taylor, H. Resit Akçakaya, Richard P. Young, David Mallon, IUCN Species Survival Commission (IUCN SSC), Department of Zoology [Oxford], University of Oxford [Oxford], Department of Ecology and Evolution, Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), Global Wildlife Conservation (GWC), Division of Biology and Conservation Ecology, Manchester Metropolitan University (MMU), Durrell Institute of Conservation and Ecology, University of Kent [Canterbury], Durrell Wildlife Conservation Trust, International Union for Conservation of Nature (IUCN), Red List Unit, Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), University of Oxford, Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
0106 biological sciences, Conservation of Natural Resources, Ecology, Range (biology), 010604 marine biology & hydrobiology, Biodiversity, Geographic variation, [SDV.BID]Life Sciences [q-bio]/Biodiversity, 15. Life on land, 010603 evolutionary biology, 01 natural sciences, Indigenous, Geography, Variation (linguistics), Humans, IUCN Red List, Ecosystem, 14. Life underwater, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation
Abstract

International audience; Accounting for taxonomic and geographic variation in historic human impacts on indigenous range will facilitate use of IUCN’s Green List of Species.

Published
2021
Full Text
View/download PDF

4. Finding the polygon hull of a network without conditions on the starting vertex

Author

Mohammad Hammoudeh, Madani Bezoui, Reinhardt Euler, Ahcène Bounceur, Loïc Lagadec, Lab-STICC_UBS_CACS_MOCS, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Université M'Hamed Bougara Boumerdes, Manchester Metropolitan University (MMU), Lab-STICC_ENSTAB_ CACS_MOCS, Lab-STICC_UBO_CID_DECIDE, École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), and Université M'Hamed Bougara Boumerdes (UMBB)

Subjects
Computer science, business.industry, Polygon Hull, 020302 automobile design & engineering, 020206 networking & telecommunications, Image processing, 02 engineering and technology, Polar angle, Vertex (geometry), [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 0203 mechanical engineering, Boundary Node Detection, Euclidean geometry, 0202 electrical engineering, electronic engineering, information engineering, Combinatorial optimization, Wireless, Electrical and Electronic Engineering, Polar coordinate system, Cluster analysis, business, Algorithm, Wireless sensor network, Wireless Sensor Network
Abstract

International audience; Many real‐life problems arising within the fields of wireless communication, image processing, combinatorial optimization, etc, can be modeled by means of Euclidean graphs. In the case of wireless sensor networks, the overall topology of the graph is not known because sensor nodes are often randomly deployed. One of the significant problems in this field is the search for boundary nodes. This problem is important in cases such as the surveillance of an area of interest, image contour reconstruction, graph matching problems, routing or clustering data, etc. In the literature, many algorithms are proposed to solve this problem, a recent one of which is the least polar‐angle connected node (LPCN) algorithm and its distributed version D‐LPCN, which are both based on the concept of a polar angle visit. An inconvenience of these algorithms is the determination of the starting vertex. In effect, the point with the minimum x‐coordinate is a possible starting point, but it has to be known at the beginning, which considerably increases the algorithms' complexity. In this article, we propose a new method called RRLPCN (reset and restart with least polar‐angle connected node), which is based on the LPCN algorithm to find the boundary vertices of a Euclidean graph. The main idea is to start the LPCN algorithm from an arbitrary vertex, and whenever it finds a vertex with an x‐coordinate smaller than that of the starting one, LPCN is reset and restarted from this new vertex. The algorithm stops as soon as it visits the same edge for the second time in the same direction. In addition to finding the boundary vertices, RRLPCN also finds the vertex with minimum x‐coordinate, which is the last starting point of our algorithm. The distributed version of the proposed algorithm, called D‐RRLPCN, is then applied to boundary node detection in the wireless sensor network. It has been implemented using real sensor nodes (Arduino/XBee and TelosB). The simulation results have shown our algorithm to be very effective in comparison to other algorithms.

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results