scholarly journals Peer Review #2 of "Low relative error in consumer-grade GPS units make them ideal for measuring small-scale animal movement patterns (v0.1)"

2015 ◽  
Author(s):  
D Burton
Keyword(s):  
Peer Review ◽  
Relative Error ◽  
Animal Movement ◽  
Movement Patterns ◽  
Small Scale

scholarly journals Fencing affects African wild dog movement patterns and population dynamics

Oryx ◽  
2021 ◽  
pp. 1-9
Author(s):  
Helen M. K. O'Neill ◽  
Sarah M. Durant ◽  
Stefanie Strebel ◽  
Rosie Woodroffe
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Animal Movement ◽  
Landscape Connectivity ◽  
Ecological Impact ◽  
Movement Patterns ◽  
Wrong Side ◽  
African Wild Dog ◽  
Wild Dog ◽  
Wild Dogs

Abstract Wildlife fences are often considered an important tool in conservation. Fences are used in attempts to prevent human–wildlife conflict and reduce poaching, despite known negative impacts on landscape connectivity and animal movement patterns. Such impacts are likely to be particularly important for wide-ranging species, such as the African wild dog Lycaon pictus, which requires large areas of continuous habitat to fulfil its resource requirements. Laikipia County in northern Kenya is an important area for wild dogs but new wildlife fences are increasingly being built in this ecosystem. Using a long-term dataset from the area's free-ranging wild dog population, we evaluated the effect of wildlife fence structure on the ability of wild dogs to cross them. The extent to which fences impeded wild dog movement differed between fence designs, although individuals crossed fences of all types. Purpose-built fence gaps increased passage through relatively impermeable fences. Nevertheless, low fence permeability can lead to packs, or parts of packs, becoming trapped on the wrong side of a fence, with consequences for population dynamics. Careful evaluation should be given to the necessity of erecting fences; ecological impact assessments should incorporate evaluation of impacts on animal movement patterns and should be undertaken for all large-scale fencing interventions. Where fencing is unavoidable, projects should use the most permeable fencing structures possible, both in the design of the fence and including as many purpose-built gaps as possible, to minimize impacts on wide-ranging wildlife.

scholarly journals Identification of animal movement patterns using tri-axial accelerometry

2008 ◽  
Vol 10 ◽  
pp. 47-60 ◽  
Author(s):  
ELC Shepard ◽  
RP Wilson ◽  
F Quintana ◽  
A Gómez Laich ◽  
N Liebsch ◽  
...  
Keyword(s):  
Animal Movement ◽  
Movement Patterns

Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
David Park ◽  
Francine Battaglia
Keyword(s):  
Mathematical Model ◽  
Relative Error ◽  
Natural Ventilation ◽  
Thermal Conditions ◽  
Ambient Air ◽  
Maximum Error ◽  
Scale Model ◽  
Small Scale ◽  
Maximum Relative Error ◽  
Solar Chimney

A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.

Environmental and individual drivers of animal movement patterns across a wide geographical gradient

2012 ◽  
Vol 82 (1) ◽  
pp. 96-106 ◽  
Author(s):  
Tal Avgar ◽  
Anna Mosser ◽  
Glen S. Brown ◽  
John M. Fryxell
Keyword(s):  
Animal Movement ◽  
Movement Patterns ◽  
Geographical Gradient

An adjustable oil film thickness test rig for detecting lubrication characteristics of slipper/swash-pair in piston pumps

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haiji Wang ◽  
Guanglin Shi
Keyword(s):  
Film Thickness ◽  
Peer Review ◽  
Relative Error ◽  
Mathematical Analysis ◽  
Test Rig ◽  
Content Type ◽  
Oil Film ◽  
Displacement Sensors ◽  
Measuring Machine ◽  
Lubrication Characteristics

Purpose The purpose of this paper is to propose an adjustable oil film thickness test rig for detecting lubrication characteristics of the slipper. The mathematical analysis of lubrication is introduced. Based on the results from the test rig, the results comparison from test rig and mathematical analysis is carried out. Design/methodology/approach This paper introduces a mechanism which can adjust the oil film thickness between the slipper and swash-plate. Feasibility is ensured, and the accuracy of test rig is guaranteed by the three-coordinate measuring machine. Three displacement sensors show the oil film thickness and its shape. The reacting force and torque resulting from oil film can be achieved by three S-type force sensors and a torque sensor, respectively. Findings The relative error of the reacting force is small. The relative error reduces and is acceptable when the deformation of retainer is taken into account. The thickness and tilt angle of oil film have less effect on the reacting force. However, they are significantly impact on torque. Originality/value The test rig proposed in this paper is able to adjust the oil film thickness, which is used to detecting the lubrication characteristics in pump design. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2020-0166/

scholarly journals Animal Movement Prediction Based on Predictive Recurrent Neural Network

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4411 ◽  
Author(s):  
Jehyeok Rew ◽  
Sungwoo Park ◽  
Yongjang Cho ◽  
Seungwon Jung ◽  
Eenjun Hwang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Architecture ◽  
Animal Movement ◽  
Movement Patterns ◽  
Behavior Changes ◽  
Movement Prediction ◽  
Prediction Scheme ◽  
Spatiotemporal Changes ◽  
Breeding Seasons

Observing animal movements enables us to understand animal behavior changes, such as migration, interaction, foraging, and nesting. Based on spatiotemporal changes in weather and season, animals instinctively change their position for foraging, nesting, or breeding. It is known that moving patterns are closely related to their traits. Analyzing and predicting animals’ movement patterns according to spatiotemporal change offers an opportunity to understand their unique traits and acquire ecological insights into animals. Hence, in this paper, we propose an animal movement prediction scheme using a predictive recurrent neural network architecture. To do that, we first collect and investigate geo records of animals and conduct pattern refinement by using random forest interpolation. Then, we generate animal movement patterns using the kernel density estimation and build a predictive recurrent neural network model to consider the spatiotemporal changes. In the experiment, we perform various predictions using 14 K long-billed curlew locations that contain their five-year movements of the breeding, non-breeding, pre-breeding, and post-breeding seasons. The experimental results confirm that our predictive model based on recurrent neural networks can be effectively used to predict animal movement.

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