Effect of GPS sample interval and paddock size on estimates of distance travelled by grazing cattle in rangeland, Australia

2018 ◽  
Vol 40 (1) ◽  
pp. 55 ◽  
Author(s):  
Sharon L. McGavin ◽  
Greg J. Bishop-Hurley ◽  
Ed Charmley ◽  
Paul L. Greenwood ◽  
Matthew J. Callaghan
Keyword(s):  
Sampling Rate ◽  
Apparent Distance ◽  
Sampling Interval ◽  
Short Sample ◽  
Gps Measurement ◽  
Global Positioning ◽  
Linear Movement ◽  
Sample Interval ◽  
Logarithmic Relationship ◽  
Free Ranging

The distance travelled by an animal, when determined by using global positioning system (GPS) coordinates, is usually calculated assuming linear movement between the recorded coordinates. When using long sample intervals, some movement may be overlooked if linear movement between each recorded position is assumed, because of the tendency of livestock to move in meandering paths. Conversely, overestimation of the true distance travelled could occur with short sample intervals because of the accumulation of extra distance due to GPS measurement error. Data from 10 experiments were used to explore the effect of paddock size and GPS sampling rate on the calculation of distance travelled by free-ranging cattle. Shortening the sample interval increased apparent distance travelled according to a power function. As paddock size increased from <1 ha to >450 ha, distance travelled increased according to a logarithmic relationship; however, other variation between experiments could have affected these results. It was concluded that selecting an optimal GPS sampling interval is critical to accurately determining the distance travelled by free-ranging cattle.

Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles

2010 ◽  
Author(s):  
Wilson O. Achicanoy M. ◽  
Carlos F. Rodriguez H.
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Sampling Rate ◽  
System A ◽  
Accelerometer Signal ◽  
Gps Measurement ◽  
Global Positioning ◽  
The Individual ◽  
Uncertainty Models

Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases with time, first a resetting of the estimator based on accelerometer by the GPS measurement is done. Next, a second method makes the fusion of both sensor uncertainties to calculate the estimation. Finally, a double estimation is done, one for each sensor, and a estimated state is calculated joining the individual estimations. These methods are explained by a case study of a guided bomb.

scholarly journals Cerebral CT Perfusion in Acute Stroke: The Effect of Lowering the Tube Load and Sampling Rate on the Reproducibility of Parametric Maps

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1121
Author(s):  
Georgios S. Ioannidis ◽  
Søren Christensen ◽  
Katerina Nikiforaki ◽  
Eleftherios Trivizakis ◽  
Kostas Perisinakis ◽  
...  
Keyword(s):  
Cerebral Blood Volume ◽  
Ct Perfusion ◽  
Sampling Rate ◽  
Volumetric Analysis ◽  
Sampling Interval ◽  
Diagnostic Efficiency ◽  
Temporal Sampling ◽  
Sampling Intervals ◽  
The Mean ◽  
Parametric Maps

The aim of this study was to define lower dose parameters (tube load and temporal sampling) for CT perfusion that still preserve the diagnostic efficiency of the derived parametric maps. Ninety stroke CT examinations from four clinical sites with 1 s temporal sampling and a range of tube loads (mAs) (100–180) were studied. Realistic CT noise was retrospectively added to simulate a CT perfusion protocol, with a maximum reduction of 40% tube load (mAs) combined with increased sampling intervals (up to 3 s). Perfusion maps from the original and simulated protocols were compared by: (a) similarity using a voxel-wise Pearson’s correlation coefficient r with in-house software; (b) volumetric analysis of the infarcted and hypoperfused volumes using commercial software. Pearson’s r values varied for the different perfusion metrics from 0.1 to 0.85. The mean slope of increase and cerebral blood volume present the highest r values, remaining consistently above 0.7 for all protocol versions with 2 s sampling interval. Reduction of the sampling rate from 2 s to 1 s had only modest impacts on a TMAX volume of 0.4 mL (IQR −1–3) (p = 0.04) and core volume of −1.1 mL (IQR −4–0) (p < 0.001), indicating dose savings of 50%, with no practical loss of diagnostic accuracy. The lowest possible dose protocol was 2 s temporal sampling and a tube load of 100 mAs.

Causes and Consequences of Timing Errors Associated With Global Positioning System Collar Accelerometer Activity Monitors

2014 ◽  
Vol 5 (2) ◽  
pp. 372-379 ◽  
Author(s):  
Adam J. Gaylord ◽  
Dana M. Sanchez
Keyword(s):  
Global Positioning System ◽  
Animal Behavior ◽  
Cervus Elaphus ◽  
Activity Monitor ◽  
Positioning System ◽  
Activity Monitors ◽  
Timing Errors ◽  
Global Positioning ◽  
Free Ranging ◽  
Monitor Data

Abstract Direct behavioral observations of multiple free-ranging animals over long periods of time and large geographic areas is prohibitively difficult. However, recent improvements in technology, such as Global Positioning System (GPS) collars equipped with motion-sensitive activity monitors, create the potential to remotely monitor animal behavior. Accelerometer-equipped activity monitors quantify animal motion with different amounts of movement presumably corresponding to different animal activities. Variations in motion among species and differences in collar design necessitate calibration for each collar and species of interest. We paired activity monitor data collected using Lotek GPS_4400 collars worn by captive Rocky Mountain elk Cervus elaphus nelsoni with simultaneously collected behavior observations. During our initial data screening, we observed many sampling intervals of directly observed behavior that did not pair to activity monitor data in a logical fashion. For example, intervals containing behaviors associated with little or no motion sometimes aligned with relatively high activity monitor values. These misalignments, due to errors associated with collar timekeeping mechanisms, would likely result in inaccurate classification models. We corrected timing errors by using defined breaks in animal behavior to shift times given by collar output, improving the average correct classification rate 61.7 percentage points for specific behaviors. Furthermore, timing errors were significantly reduced by increasing the GPS fix rate, by using a sampling interval divisible by 8 seconds, and by accurately timing the initial collar activation. Awareness and management of collar timing error will enable users to obtain the best possible estimates of true behavior when calibrating these collars and interpreting data from free-ranging animals.

Short- and long-term movement patterns in the freshwater whipray (Himantura dalyensis) determined by the signal processing of passive acoustic telemetry data

2012 ◽  
Vol 63 (4) ◽  
pp. 341 ◽  
Author(s):  
Hamish A. Campbell ◽  
Matthew Hewitt ◽  
Matthew E. Watts ◽  
Stirling Peverell ◽  
Craig E. Franklin
Keyword(s):  
Signal Processing ◽  
Acoustic Telemetry ◽  
Movement Patterns ◽  
Wet Season ◽  
Aquatic Animals ◽  
Location Data ◽  
Linear Movement ◽  
Passive Acoustic ◽  
Free Ranging ◽  
Periodic Components

Patterns of movement in aquatic animals reflect ecologically important behaviours. Cyclical changes in the abiotic environment influence these movements, but when multiple processes occur simultaneously, identifying which is responsible for the observed movement can be complex. Here we used acoustic telemetry and signal processing to define the abiotic processes responsible for movement patterns in freshwater whiprays (Himantura dalyensis). Acoustic transmitters were implanted into the whiprays and their movements detected over 12 months by an array of passive acoustic receivers, deployed throughout 64 km of the Wenlock River, Qld, Australia. The time of an individual’s arrival and departure from each receiver detection field was used to estimate whipray location continuously throughout the study. This created a linear-movement-waveform for each whipray and signal processing revealed periodic components within the waveform. Correlation of movement periodograms with those from abiotic processes categorically illustrated that the diel cycle dominated the pattern of whipray movement during the wet season, whereas tidal and lunar cycles dominated during the dry season. The study methodology represents a valuable tool for objectively defining the relationship between abiotic processes and the movement patterns of free-ranging aquatic animals and is particularly expedient when periods of no detection exist within the animal location data.

Automated Modeling of Building HVAC Systems for MPC

2014 ◽  
Author(s):  
Rohit H. Chintala ◽  
Christopher J. Bay ◽  
Bryan P. Rasmussen
Keyword(s):  
System Identification ◽  
Real Time ◽  
Air Conditioning ◽  
Mean Squared Error ◽  
Sampling Rate ◽  
Sampling Interval ◽  
Hvac Systems ◽  
Parametric Models ◽  
Automated Modeling ◽  
Air Conditioning Systems

Model predictive control (MPC) offers a tremendous scope in optimizing the consumption of energy by building HVAC systems. This paper presents an automated real-time procedure for the development of linear parametric models of building air-conditioning systems through system identification for the implementation of the MPC algorithms. The procedure is used to decide on the various aspects of system identification such as selecting the model structure, the inputs to the system, the interaction of the systems with their neighbors, and the updating of the model coefficients in real-time. The effectiveness of the procedure is demonstrated by modeling the various components air-conditioning systems of a real building. The root mean squared error was used as a performance metric to gauge the models. The paper also demonstrates that a 15 minute sampling interval is sufficient to model the dynamics of the air-handling unit and the room temperatures, but a faster sampling rate may be required to model the VAV boxes.

scholarly journals A Trajectory Collaboration Based Map Matching Approach for Low-Sampling-Rate GPS Trajectories

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2057 ◽  
Author(s):  
Wentao Bian ◽  
Ge Cui ◽  
Xin Wang
Keyword(s):  
Sampling Rate ◽  
Longest Common Subsequence ◽  
Map Matching ◽  
Missing Information ◽  
The Road ◽  
Global Positioning ◽  
Common Subsequence ◽  
Gps Trajectories ◽  
Gps Trajectory ◽  
Effectiveness And Efficiency

GPS (Global Positioning System) trajectories with low sampling rates are prevalent in many applications. However, current map matching methods do not perform well for low-sampling-rate GPS trajectories due to the large uncertainty between consecutive GPS points. In this paper, a collaborative map matching method (CMM) is proposed for low-sampling-rate GPS trajectories. CMM processes GPS trajectories in batches. First, it groups similar GPS trajectories into clusters and then supplements the missing information by resampling. A collaborative GPS trajectory is then extracted for each cluster and matched to the road network, based on longest common subsequence (LCSS) distance. Experiments are conducted on a real GPS trajectory dataset and a simulated GPS trajectory dataset. The results show that the proposed CMM outperforms the baseline methods in both, effectiveness and efficiency.

Oestrus in a secretive species: endogenous estradiol varies throughout the shed cycle and influences attractiveness in wild northern watersnakes (Nerodia sipedon)

Behaviour ◽  
2014 ◽  
Vol 151 (4) ◽  
pp. 403-419 ◽  
Author(s):  
Benjamin C. Jellen ◽  
Sean P. Graham ◽  
Robert D. Aldridge ◽  
Ryan L. Earley
Keyword(s):  
Sex Pheromone ◽  
Sex Steroids ◽  
Sampling Interval ◽  
Pheromone Production ◽  
Nerodia Sipedon ◽  
17Β Estradiol ◽  
Reproductive Females ◽  
Free Ranging ◽  
The Relationship ◽  
Sex Pheromone Production

Oestrogen (e.g., 17β-estradiol, E2) stimulates vitellogenesis, female sexual behaviour, and induces sex pheromone production throughout vertebrates. Therefore, the quantification of its role in any one these may prove challenging; particularly in taxa such as snakes where mating coincides with vitellogenesis. Studies examining steroid hormones in snakes are further confounded by the typical sampling interval (monthly) which is likely insufficient to observe the brief hormone fluctuations associated with an oestrus period. Thus, the relationship between oestrus and endogenous sex steroids in snakes remains equivocal. We sampled plasma E2 of 12 radio-equipped free-ranging adult female northern watersnakes (Nerodia sipedon) twice weekly during the 2008–2009 mating periods. Reproductive females experienced a large E2 surge coincident with shedding, movement, and male accompaniment indicating that endogenous E2 is involved in oestrus, a phenomenon that has previously not been documented in snakes.

scholarly journals Research on presice point positioning and Real-Time Kinematics corrections for unmanned aerial vehicle global positioning systems

Aviation ◽  
2017 ◽  
Vol 21 (1) ◽  
pp. 17-22
Author(s):  
Ugnius RAGAUSKAS ◽  
Domantas BRUČAS ◽  
Jūratė SUŽIEDELYTĖ VISOCKIENĖ
Keyword(s):  
Real Time ◽  
Precise Point Positioning ◽  
Flight Trajectory ◽  
Accuracy Improvement ◽  
Positioning Systems ◽  
Gps Measurement ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
Point Positioning ◽  
Gps Accuracy

Unmanned Aerial Vehicles (UAVs) are used in different tasks with different flight path accuracy. To achieve a greater accuracy of flight trajectory GPS accuracy improvement methods are analyzed. The present article explains the main principles of GPS measurement. Precise Point Positioning (PPP) and Real-Time Kinematics (RTK) methods are described. and compared. Also, both methods have been tested.

scholarly journals The effect of sampling rate on observed statistics in a correlated random walk

2013 ◽  
Vol 10 (85) ◽  
pp. 20130273 ◽  
Author(s):  
G. Rosser ◽  
A. G. Fletcher ◽  
P. K. Maini ◽  
R. E. Baker
Keyword(s):  
Random Walk ◽  
Sampling Rate ◽  
Bacterial Chemotaxis ◽  
Sampling Interval ◽  
Stochastic Simulations ◽  
Complex Nature ◽  
Correlated Random Walk ◽  
Rapid Sampling ◽  
Open Questions ◽  
Migrating Birds

Tracking the movement of individual cells or animals can provide important information about their motile behaviour, with key examples including migrating birds, foraging mammals and bacterial chemotaxis. In many experimental protocols, observations are recorded with a fixed sampling interval and the continuous underlying motion is approximated as a series of discrete steps. The size of the sampling interval significantly affects the tracking measurements, the statistics computed from observed trajectories, and the inferences drawn. Despite the widespread use of tracking data to investigate motile behaviour, many open questions remain about these effects. We use a correlated random walk model to study the variation with sampling interval of two key quantities of interest: apparent speed and angle change. Two variants of the model are considered, in which reorientations occur instantaneously and with a stationary pause, respectively. We employ stochastic simulations to study the effect of sampling on the distributions of apparent speeds and angle changes, and present novel mathematical analysis in the case of rapid sampling. Our investigation elucidates the complex nature of sampling effects for sampling intervals ranging over many orders of magnitude. Results show that inclusion of a stationary phase significantly alters the observed distributions of both quantities.

scholarly journals Choosing Sampling Interval Durations for Remotely Classifying Rocky Mountain Elk Behavior

2016 ◽  
Vol 7 (1) ◽  
pp. 213-221 ◽  
Author(s):  
Adam J. Gaylord ◽  
Dana M. Sanchez ◽  
John Van Sickle
Keyword(s):  
Global Positioning System ◽  
Rocky Mountain ◽  
Potential Effect ◽  
Sampling Interval ◽  
Positioning System ◽  
Activity Monitors ◽  
Global Positioning ◽  
Sampling Intervals ◽  
Rocky Mountain Elk ◽  
And Behavior

Abstract Dual-axis accelerometer global positioning system collars can be used to remotely record the activity level and behavior of free-ranging animals, but inter- and intraspecific variations in motion among behaviors necessitate calibration for each species of interest. To date, little work has been done to determine the best duration for sampling intervals when using activity monitors that incorporate dual-axis accelerometers. However, we expected that the duration of behaviors relative to the duration of sampling intervals could affect the accuracy of calibration and behavior classification models. Furthermore, we considered the potential effect of winter diet supplementation (hay) on behavior classification. We used Lotek 4500 global positioning system collars featuring dual-axis accelerometer activity monitors to collect data for calibration and classification trials on Rocky Mountain elk Cervus elaphus nelsoni. We used discriminant function model structures to determine the number of accurately classifiable behaviors that could be derived from data sampled over three sampling interval durations (5 min, 152 s, and 64 s) while also considering the potential effect of hay supplementation on classification. Our results suggest that investigators should ascertain whether their focal elk herd accesses or might access supplemental hay before deployment and analysis of activity sensor data. Similarly, researchers must weigh priorities when choosing a sampling interval, because no optimal solution emerged from our investigation. For example, of our acceptable models, only those constructed using 64-s intervals were able to distinguish short bouts of running. However, only models constructed with 5-min intervals accurately classified browsing while also maximizing the number of behaviors identified.

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