Development of light-weight video-tracking technology for use in wildlife research: A case study on kangaroos

2020 ◽  
Vol 40 (3) ◽  
pp. 364-378 ◽  
Author(s):  
C.A. Herbert ◽  
M. Dassis ◽  
M. Pye ◽  
P.W. Jones ◽  
P.H.W. Leong ◽  
...  
Keyword(s):  
Plant Species ◽  
Spatial Scales ◽  
Diet Selection ◽  
Video Tracking ◽  
Environmental Data ◽  
Light Weight ◽  
Video Footage ◽  
Novel Approach ◽  
Need To Evaluate ◽  
Recipient Animal

There have been significant advances in the development of animal-borne sensor technologies, or biologgers, in recent years. This has resulted in tremendous capacity for wildlife researchers to remotely collect physiological, behavioural and social data from wildlife in circumstances that were unthinkable just decades ago. While this technology can provide us with a unique insight into the “secret lives” of wild animals, there is a need to evaluate the utility of these new sensors versus traditional wildlife research methodologies, and to critically evaluate the integrity of the data collected by ensuring that these devices themselves do not alter the physiology or behaviour of the recipient animal. This paper reports on the development of a light weight “animal borne video and environmental data collection system” (AVED), which can be deployed on animals as small as 11 kg, whilst still meeting the desired 3% body weight threshold. This AVED (referred to as the “Kangaroo-cam”) simultaneously collects video footage and GPS location data for an average of 19 h. Kangaroo-cams were deployed on seven kangaroos as a proof of concept of their potential utility for the study of location specific behaviour and diet in a medium-sized terrestrial herbivore. Following device recovery and data processing, we were able to successfully score 83 foraging events which allowed us to determine diet based on visual identification (to the family level) of plants consumed. This approach could be further broadened to include a comparison of plant species consumed versus plant species encountered to provide a novel approach to diet selection analysis. When combined with GPS mapping of foraging locations, this approach would allow researchers to address questions on diet selection at both fine (within patch) and broad (habitat) spatial scales, overcoming some of the limitations of traditional diet selection methodologies. However, animal capture and collar deployment caused a significant elevation in stress hormone concentrations within the first 24 h post-capture, which highlighted the need to incorporate a time-delay capacity into these devices. We conclude the paper by reviewing recent advances in the development of AVED technology and providing suggestions for the improvement of this Kangaroo-cam device.

On The Field: Examining Differences in Video Format in Sports Media Viewing

2020 ◽  
Vol 64 (1) ◽  
pp. 781-785
Author(s):  
Ragan Wilson ◽  
Christopher B. Mayhorn
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Spatial Presence ◽  
Sports Media ◽  
User Perceptions ◽  
Video Footage ◽  
Confirmatory Factor ◽  
Need To Evaluate ◽  
The Relationship ◽  
Video Format

With virtual reality’s emerging popularity and the subsequent push for more sports media experiences, there is a need to evaluate virtual reality’s use into more video watching experiences. This research explores differences in experiences between Monitor (2D) video and HMD (360-Degree) video footage by measuring user perceptions of presence, suspense, and enjoyment. Furthermore, this study examines the relationship between presence, game attractiveness, suspense, and enjoyment as explored by Kim, Cheong, and Kim (2016). Differences were assessed via a MANOVA examining specifically presence, suspense, and enjoyment while the relationships were explored via a confirmatory factor analysis. Results suggest that there was a difference between Monitor (2D) video and HMD (360-Degree) in regard to spatial presence, engagement, suspense, and enjoyment, but the previous model from Kim et al. (2016) was not a good fit to this study’s data.

scholarly journals A minimal 3D model of mosquito flight behaviour around the human baited bed net

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jeff Jones ◽  
Gregory P D Murray ◽  
Philip J McCall
Keyword(s):  
Spatial Scales ◽  
Video Tracking ◽  
Sub Saharan Africa ◽  
Bed Nets ◽  
State Transitions ◽  
Bed Net ◽  
Flight Behaviour ◽  
Individual Agent ◽  
Host Seeking ◽  
Mosquito Behaviour

Abstract Background Advances in digitized video-tracking and behavioural analysis have enabled accurate recording and quantification of mosquito flight and host-seeking behaviours, facilitating development of individual (agent) based models at much finer spatial scales than previously possible. Methods Quantified behavioural parameters were used to create a novel virtual testing model, capable of accurately simulating indoor flight behaviour by a virtual population of host-seeking mosquitoes as they interact with and respond to simulated stimuli from a human-occupied bed net. The model is described, including base mosquito behaviour, state transitions, environmental representation and host stimulus representation. Results In the absence of a bed net and human host bait, flight distribution of the model population was relatively uniform throughout the arena. Introducing an unbaited untreated bed net induced a change in distribution with an increase in landing events on the net surface, predominantly on the sides of the net. Adding the presence of a simulated human bait dramatically impacted flight distribution patterns, exploratory foraging and, the number and distribution of landing positions on the net, which were determined largely by the orientation of the human within. The model replicates experimental results with free-flying living mosquitoes at human-occupied bed nets, where contact occurs predominantly on the top surface of the net. This accuracy is important as it quantifies exposure to the lethal insecticide residues that may be unique to the net roof (or theoretically any other surface). Number of net contacts and height of contacts decreased with increasing attractant dispersal noise. Conclusions Results generated by the model are an accurate representation of actual mosquito behaviour recorded at and around a human-occupied bed net in untreated and insecticide-treated nets. This fine-grained model is highly flexible and has significant potential for in silico screening of novel bed net designs, potentially reducing time and cost and accelerating the deployment of new and more effective tools for protecting against malaria in sub-Saharan Africa.

scholarly journals Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
João Gama Monteiro ◽  
Jesús L. Jiménez ◽  
Francesca Gizzi ◽  
Petr Přikryl ◽  
Jonathan S. Lefcheck ◽  
...  
Keyword(s):  
Anthropogenic Impacts ◽  
Spatial Scales ◽  
Low Cost ◽  
Human Populations ◽  
Coastal Habitat ◽  
Coastal Monitoring ◽  
Monitoring Programs ◽  
Novel Approach ◽  
Aerial Platforms ◽  
Rocky Habitats

AbstractUnderstanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps.

A Novel Approach for Underbalanced Well Completions in Depleted and Highly Fractured Carbonate Reservoirs

2021 ◽  
Author(s):  
Ali Khalid ◽  
Qasim Ashraf ◽  
Khurram Luqman ◽  
Ayoub Hadj-Moussa ◽  
Nasir Hamim
Keyword(s):  
Oil And Gas ◽  
Control Device ◽  
No Production ◽  
Light Weight ◽  
Subject Field ◽  
Underbalanced Drilling ◽  
Novel Approach ◽  
Fractured Carbonate ◽  
The Subject ◽  
Multiphase Fluid

Abstract A prime objective of oil and gas operators is to maximize reservoir productivity and increase the ultimate recovery from all depleting fields. Underbalanced drilling is one such enabling technology that has been adopted world wide to achieve a number of objectives in maximizing the reservoir potential. Chief among these objectives are to reduce formation invasion damage, identify sweet spots in the reservoir, and reduce well costs. Underblanaced operations however introduces more complexity into the successful drilling and completion of a candidate well. An improperly executed underbalanced operation can result in having less productivity in contrast to a conventionally drilled and completed well. Pakistan a country currently highly dependent on foreign hydrocarbon fuels, once had total independence in at least natural gas. The southern part of Pakistan is known for its rich hydrocarbon potential, but most fields were discovered decades ago and have depleted at a rapid pace. Numerous fields in the vicinity have depleted to an extent that the reservoir pressure has reduced to a mere 3.9 PPG in EMW. In the most recently drilled well the pressure depletion caused massive circulation losses while drilling the reservoir formation and the operator had resorted to pumping of heavy LCM pills and blind drilling to complete the section. After completing the well conventionally the operator made multiple attempts to kick off the well but observed no production. Subsequently multiple acid stimulation jobs were performed to reduce the formation damage, but all efforts were in vain. It was evaluated that the heavy LCM and drilled cuttings had bridged off and choked the reservoir skin completely from which there was no return. Ultimately the well had to be plugged and abandoned. In relatively higher pressured and non-fractured formations the option exists to drill a well in underbalanced mode and trip the running string by balancing the well with a light weight fluid. For the subject case however, this option was impossible due to the highly fractured nature of the formation. A plan was devised to include a downhole casing isolation valve in the last casing string and drill the well with an extremely light weight multiphase fluid. A rotating control device would be used to strip the running string in and out of the well. The completion packer was also to be stripped into a live well and set in place without the need of ever killing or balancing the well. By executing the mentioned methodology, the operator was able to drill and complete a well all the while keeping the reservoir formation in a virgin state. The paper discusses the planning, design, execution, and lessons learnt in underbalanced drilling and completion operations in the subject field.

Revisiting knowledge distillation for light-weight visual object detection

2021 ◽  
Vol 43 (13) ◽  
pp. 2888-2898
Author(s):  
Tianze Gao ◽  
Yunfeng Gao ◽  
Yu Li ◽  
Peiyuan Qin
Keyword(s):  
Object Detection ◽  
Essential Element ◽  
Detection Algorithm ◽  
Positive Sample ◽  
Detection Methods ◽  
Visual Object ◽  
Light Weight ◽  
Model Compression ◽  
Novel Approach ◽  
Knowledge Distillation

An essential element for intelligent perception in mechatronic and robotic systems (M&RS) is the visual object detection algorithm. With the ever-increasing advance of artificial neural networks (ANN), researchers have proposed numerous ANN-based visual object detection methods that have proven to be effective. However, networks with cumbersome structures do not befit the real-time scenarios in M&RS, necessitating the techniques of model compression. In the paper, a novel approach to training light-weight visual object detection networks is developed by revisiting knowledge distillation. Traditional knowledge distillation methods are oriented towards image classification is not compatible with object detection. Therefore, a variant of knowledge distillation is developed and adapted to a state-of-the-art keypoint-based visual detection method. Two strategies named as positive sample retaining and early distribution softening are employed to yield a natural adaption. The mutual consistency between teacher model and student model is further promoted through a hint-based distillation. By extensive controlled experiments, the proposed method is testified to be effective in enhancing the light-weight network’s performance by a large margin.

scholarly journals Extending U.S. Biodiversity Collections to Address National Challenges

2019 ◽  
Vol 3 ◽  
Author(s):  
Barbara Thiers ◽  
Paula Mabee ◽  
Anna Monfils
Keyword(s):  
Spatial Scales ◽  
Tracking System ◽  
Environmental Data ◽  
Digital Data ◽  
Data Repository ◽  
Data Types ◽  
Voucher Specimen ◽  
Core Data ◽  
Research Questions ◽  
Temporal And Spatial

The U.S. national heritage of approximately one billion biodiversity specimens, once digitized, can be linked to emerging digital data sources to form an information-rich network for exploring earth’s biota across taxonomic, temporal and spatial scales. A workshop held 30 October - 1 November 2018 at Oak Spring Garden in Upperville, VA under the leadership of the Biodiversity Collections Network (BCoN) developed a plan for maximizing the value of our collections resource for research and education. In their deliberations, participants drew heavily on recent literature as well as surveys, and meetings and workshops held over the past year with the primary stakeholder community of collections professionals, researchers, and educators. We propose to focus future biodiversity infrastructure and digital resources on building a network of extended specimen data that encompasses the depth and breadth of biodiversity specimens and data held in U.S. collections institutions (BCoN 2019). The extended specimen network (ESN) includes the physical voucher specimen curated and housed in a collection and its associated genetic, phenotypic and environmental data. These core data types, selected because they are key to answering driving research questions, include physical preparations such as tissue samples and their derivative products such as gene sequences or metagenomes, digitized media and annotations, and taxon- or locality-specific data such as occurrence observations, phylogenies and species distributions. Existing voucher specimens will be extended both manually and through new automated methods, and data will be linked through unique identifiers, taxon name and location across collections, across disciplines and to outside sources of data. As we continue our documentation of earth’s biota, new collections will be enhanced from the outset, i.e., accessioned with a full suite of data. We envision the ESN proposed here will be the gold standard for the structured cloud of integrated data associated with all vouchered specimens. Collectively, data linked through the ESN will enhance the capacity to explore research questions across taxonomic, temporal and spatial scales. The ESN will allow researchers to explore the rules that govern how organisms, grow, diversify and interact, and enable scientists to ask more nuanced research questions specific to how environmental change and human activities may affect those rules. The specimen, coupled with the open access ESN, and immediate and relevant science resulting from the ESN, can play a unique role in promoting STEM education, involving citizen scientists, and empowering a scientifically literate society. The specimen and the associated data provide a relatable and engaging entry point to participate in iterative data driven science, learn core data literacy skills, and build open, transdisciplinary collaboration. Creating the ESN requires new infrastructure to provide the linkages between the specimen and data derived from it. On the established foundation of existing digital data from collections it will require the development of new standards, connections, and resources such as ontologies to facilitate discovery, and implementation of a robust identifier tracking system. Finally, continued digitization of established, as well as new collections, is necessary to ensure the grounding of extended specimen data in the framework of when and where it was collected. The ESN will also require new approaches to data sharing and collaboration, partnerships with national and international data providers, computer and data scientists, educators and industry. The ESN will benefit from research-driven episodic funding for the collection of new specimens, which in turn will require digitization and curation. For the ESN to function as envisaged above, it will require long-term support for a central organizing unit with responsibility for community coordination, education and outreach, data mobilization, and maintenance of the central data repository and the network infrastructure.

scholarly journals Bioregions in Marine Environments: Combining Biological and Environmental Data for Management and Scientific Understanding

BioScience ◽  
2019 ◽  
Vol 70 (1) ◽  
pp. 48-59 ◽  
Author(s):  
Skipton N C Woolley ◽  
Scott D Foster ◽  
Nicholas J Bax ◽  
Jock C Currie ◽  
Daniel C Dunn ◽  
...  
Keyword(s):  
Natural Resources ◽  
Biodiversity Conservation ◽  
Statistical Models ◽  
Spatial Representation ◽  
Spatial Scales ◽  
Scientific Understanding ◽  
Biological Data ◽  
Environmental Data ◽  
Marine Environments ◽  
Multiple Spatial Scales

Abstract Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.

Diet selection at three spatial scales: Implications for conservation of an endangered Hawaiian tree snail

Biotropica ◽  
2016 ◽  
Vol 49 (1) ◽  
pp. 130-136 ◽  
Author(s):  
Melissa R. Price ◽  
Richard O'Rorke ◽  
Anthony S. Amend ◽  
Michael G. Hadfield
Keyword(s):  
Spatial Scales ◽  
Diet Selection

Specialized ecological interactions and plant species rarity: The role of pollinators and mycorrhizal fungi across multiple spatial scales

2014 ◽  
Vol 169 ◽  
pp. 285-295 ◽  
Author(s):  
Ryan D. Phillips ◽  
Rod Peakall ◽  
Michael F. Hutchinson ◽  
Celeste C. Linde ◽  
Tingbao Xu ◽  
...  
Keyword(s):  
Plant Species ◽  
Mycorrhizal Fungi ◽  
Spatial Scales ◽  
Ecological Interactions ◽  
Multiple Spatial Scales ◽  
Species Rarity

Novel approach to automatically classify rat social behavior using a video tracking system

2016 ◽  
Vol 268 ◽  
pp. 163-170 ◽  
Author(s):  
Suzanne M. Peters ◽  
Ilona J. Pinter ◽  
Helen H.J. Pothuizen ◽  
Raymond C. de Heer ◽  
Johanneke E. van der Harst ◽  
...  
Keyword(s):  
Social Behavior ◽  
Tracking System ◽  
Video Tracking ◽  
Novel Approach ◽  
Video Tracking System
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