A comparative analysis of decision trees vis-a-vis other computational data mining techniques in automotive insurance fraud detection

The development and application of computational data mining techniques in financial fraud detection and business failure prediction has become a popular cross-disciplinary research area in recent times involving financial economists, forensic accountants and computational modellers. Some of the computational techniques popularly used in the context of - financial fraud detection and business failure prediction can also be effectively applied in the detection of fraudulent insurance claims and therefore, can be of immense practical value to the insurance industry. We provide a comparative analysis of prediction performance of a battery of data mining techniques using real-life automotive insurance fraud data. While the data we have used in our paper is US-based, the computational techniques we have tested can be adapted and generally applied to detect similar insurance frauds in other countries as well where an organized automotive insurance industry exists

Highlighting when animals expend excessive energy for travel using dynamic body acceleration

Travel represents a major cost for many animals so there should be selection pressure for it to be efficient – at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark (Rhincodon typus) to derive the minimum estimated power required to swim at defined vertical velocities. We show how subtraction of measured DBA from the estimated minimum power for any given vertical velocity provides a “proxy for power above minimum” metric (PPAmin), highlighting when these animals travel above minimum power. We suggest that the adoption of this metric across species has value in identifying where and when animals are subject to compelling conditions that lead them to deviate from ostensibly judicious energy expenditure

Physical limits of flight performance in the heaviest soaring bird

Flight costs are predicted to vary with environmental conditions, and this should ultimately determine the movement capacity and distributions of large soaring birds. Despite this, little is known about how flight effort varies with environmental parameters. We deployed bio-logging devices on the world’s heaviest soaring bird, the Andean condor (Vultur gryphus), to assess the extent to which these birds can operate without resorting to powered flight. Our records of individual wingbeats in >216 hours of flight show that condors can sustain soaring across a wide range of wind and thermal conditions, only flapping for 1 % of their flight time. This is amongst the very lowest estimated movement costs in vertebrates. One bird even flew for > 5 hours without flapping, covering ~ 172 km. Overall, > 70 % of flapping flight was associated with take-offs. Movement between weak thermal updrafts at the start of the day also imposed a metabolic cost, with birds flapping towards the end of glides to reach ephemeral thermal updrafts. Nonetheless, the investment required was still remarkably low, and even in winter conditions with weak thermals, condors are only predicted to flap for ~ 2 s per km. The overall flight effort in the largest soaring birds therefore appears to be constrained by the requirements for take-off

An “orientation sphere” visualization for examining animal head movements

Animal behavior is elicited, in part, in response to external conditions, but understanding how animals perceive the environment and make the decisions that bring about these behavioral responses is challenging.Animal heads often move during specific behaviors and, additionally, typically have sensory systems (notably vision, smell, and hearing) sampling in defined arcs (normally to the front of their heads). As such, head‐mounted electronic sensors consisting of accelerometers and magnetometers, which can be used to determine the movement and directionality of animal heads (where head “movement” is defined here as changes in heading [azimuth] and/or pitch [elevation angle]), can potentially provide information both on behaviors in general and also clarify which parts of the environment the animals might be prioritizing (“environmental framing”).We propose a new approach to visualize the data of such head‐mounted tags that combines the instantaneous outputs of head heading and pitch in a single intuitive spherical plot. This sphere has magnetic heading denoted by “longitude” position and head pitch by “latitude” on this “orientation sphere” (O‐sphere).We construct the O‐sphere for the head rotations of a number of vertebrates with contrasting body shape and ecology (oryx, sheep, tortoises, and turtles), illustrating various behaviors, including foraging, walking, and environmental scanning. We also propose correcting head orientations for body orientations to highlight specific heading‐independent head rotation, and propose the derivation of O‐sphere‐metrics, such as angular speed across the sphere. This should help identify the functions of various head behaviors.Visualizations of the O‐sphere provide an intuitive representation of animal behavior manifest via head orientation and rotation. This has ramifications for quantifying and understanding behaviors ranging from navigation through vigilance to feeding and, when used in tandem with body movement, should provide an important link between perception of the environment and response to it in free‐ranging animals

The physics of Martian weather and climate: a review

The planet Mars hosts an atmosphere that is perhaps the closest in terms of its meteorology and climate to that of the Earth. But Mars differs from Earth in its greater distance from the Sun, its smaller size, its lack of liquid oceans and its thinner atmosphere, composed mainly of CO2. These factors give Mars a rather different climate to that of the Earth. In this article we review various aspects of the martian climate system from a physicist's viewpoint, focusing on the processes that control the martian environment and comparing these with corresponding processes on Earth. These include the radiative and thermodynamical processes that determine the surface temperature and vertical structure of the atmosphere, the fluid dynamics of its atmospheric motions, and the key cycles of mineral dust and volatile transport. In many ways, the climate of Mars is as complicated and diverse as that of the Earth, with complex nonlinear feedbacks that affect its response to variations in external forcing. Recent work has shown that the martian climate is anything but static, but is almost certainly in a continual state of transient response to slowly varying insolation associated with cyclic variations in its orbit and rotation. We conclude with a discussion of the physical processes underlying these long- term climate variations on Mars, and an overview of some of the most intriguing outstanding problems that should be a focus for future observational and theoretical studies

Structure and dynamics of the Martian lower and middle atmosphere as observed by the Mars Climate Sounder: Seasonal variations in zonal mean temperature, dust, and water ice aerosols

The first Martian year and a half of observations by the Mars Climate Sounder aboard the Mars Reconnaissance Orbiter has revealed new details of the thermal structure and distributions of dust and water ice in the atmosphere. The Martian atmosphere is shown in the observations by the Mars Climate Sounder to vary seasonally between two modes: a symmetrical equinoctial structure with middle atmosphere polar warming and a solstitial structure with an intense middle atmosphere polar warming overlying a deep winter polar vortex. The dust distribution, in particular, is more complex than appreciated before the advent of these high (~5 km) vertical resolution observations, which extend from near the surface to above 80 km and yield 13 dayside and 13 nightside pole-to-pole cross sections each day. Among the new features noted is a persistent maximum in dust mass mixing ratio at 15–25 km above the surface (at least on the nightside) during northern spring and summer. The water ice distribution is very sensitive to the diurnal and seasonal variation of temperature and is a good tracer of the vertically propagating tide

Decision rules for determining terrestrial movement and the consequences for filtering high-resolution global positioning system tracks: a case study using the African lion ( Panthera leo )

The combined use of global positioning system (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequencies. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy being affected by signal reception. We hypothesized that animal behaviour was the main factor affecting fix inaccuracy, with inherent GPS positional noise (jitter) being most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A movement-verified filtering (MVF) protocol was constructed to compare GPS-derived speed data with dynamic body acceleration, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions (Panthera leo) fitted with collar-mounted GPS units and tri-axial motion sensors recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by greater than 80% prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high-resolution GPS datasets and demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement

Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks

BackgroundFine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub).ResultsThe Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed.ConclusionsThe function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application