lama Qasem - Academia.edu (original) (raw)

Papers by lama Qasem

The plot contains prototypes (big dots) for the six behavioural classes modelled by rand... more The plot contains prototypes (big dots) for the six behavioural classes modelled by random forests. Prototypes are median values of samples with the largest number of k-nearest neighbours of the same class. In this way, they mark the center of each class and indicate how the variables relate to the classification.</p

Changes in orientation of the surge, sway and heave acceleration axes are illustrated du... more Changes in orientation of the surge, sway and heave acceleration axes are illustrated during standing, walking and swimming (top to bottom).</p

Contour lines show 2.5% intervals.</p

A relative ranking of significant predictors, the permutation-based variable importance ... more A relative ranking of significant predictors, the permutation-based variable importance measure of the random forest model, is shown as the mean decrease in accuracy in percent. Higher values of mean decrease in accuracy indicate variables that contribute more to the accuracy of the classification.</p

Example of the static surge, sway and heave acceleration of Eurasian beavers during a wh... more Example of the static surge, sway and heave acceleration of Eurasian beavers during a whole sleeping session. (a) Static heave acceleration values towards -1 g indicate lying on the back. (b) Static surge acceleration values towards +1 g and static sway acceleration values towards 0 g imply that the animal is sleeping in a sitting posture on its belly. (c) Static sway acceleration values towards -1 g indicate that the animal is lying on the left side, while (d) static sway acceleration values towards +1 g indicate lying on the right side.</p

In this example, as with all other participants, the relationship between ODBA&... more In this example, as with all other participants, the relationship between ODBA and VeDBA was highly significant (VeDBA = 0.014+0.6418 ODBA, r2 = 0.987, P<0.001).</p

Schematic representation of a movement arc (curved arrow) elicited by one bone (light gr... more Schematic representation of a movement arc (curved arrow) elicited by one bone (light grey) with respect to another and brought about by contraction of multiple muscles (dark grey) with varying forces (F) with differing angles of insertion (θ).</p

Only data during the period when the participant did not exceed the ventilatory threshol... more Only data during the period when the participant did not exceed the ventilatory threshold (for definition see text) are included. as with all other participants, the relationship between ODBA and VeDBA was highly significant (VeDBA = 0.014+0.6418 ODBA, r2 = 0.987, P<0.001).</p

An example plot of uptake against ODBA (black circles) and V... more An example plot of uptake against ODBA (black circles) and VeDBA (grey triangles) over the duration of the trial following removal of the points above the participant's anaerobic threshold.</p

aSimilar-shaped, comparable dive types were only found in 8 indiv... more aSimilar-shaped, comparable dive types were only found in 8 individuals.bSleeping consists of a series of different postures (e.g. lying on the belly, on the sides, or on the back), thereby impeding the specification of mean values.Statistics of the static surge, sway and heave acceleration signal and overall dynamic body acceleration for the seven identified Eurasian beaver behaviours.</p

r2-values for relationships between ODBA and &... more r2-values for relationships between ODBA and VeDBA and recorded using an acceleration data logger on a range of animals during activity at Buenos Aires Zoo.</p

Overall relationships between and ODBA or VeDBA re... more Overall relationships between and ODBA or VeDBA recorded for humans locomoting on a treadmill using an acceleration logger in a straight orientation or a skewed orientation.</p

The partial dependence function plots a grid of values over the range of the mean heave ... more The partial dependence function plots a grid of values over the range of the mean heave acceleration on the x-axis, with decile rugs at the bottom of the plot representing the distribution of the total mean heave acceleration. The y-axis is on the logit scale and is centred to have zero mean over the data distribution.</p

Each point denotes a mean value derived from a three-minute trial of a participant movin... more Each point denotes a mean value derived from a three-minute trial of a participant moving at one particular speed below the lactate threshold. Data from all participants are included.</p

Heave (continuous line), sway (dotted line) and surge (dashed line) acceleration axes di... more Heave (continuous line), sway (dotted line) and surge (dashed line) acceleration axes displayed graphically over one stride (from each leg) during walking (i) and running (ii).</p

Methods. Changing shapes for frequency distributions. Figure S1. A 3-d scatter plot (g-sphere) of... more Methods. Changing shapes for frequency distributions. Figure S1. A 3-d scatter plot (g-sphere) of static (orthogonal) tri-axial acceleration data. Figure S2. A spherical coordinateâ s visualization of (a) postural state plotted onto the surface of a sphere in three-dimensional space, (b) points joined together in chronological order, (c) projecting the data outwards from the sphere according to other parameters. Figure S3. A spherical histogram (Dubai plot) visualization to depict frequent postural states. Figure S4. Histogram, Frequency shape (stacked), fixed shape (skittle) from urchin plots. Figure S5. G-urchin of skittle shape and stacked frequency urchins emitted from the centre of each facet of the sphere. Figure S6. Overview of user interface for a program in which spherical plots can be created. Figure S7. G-spheres and comparable g-urchins derived from a rod-mounted tri-axial accelerometer showing fly-fishing visualisations. (DOCX 5289 kb)

Recent technological innovations have led to the development of miniature, accelerometer-containi... more Recent technological innovations have led to the development of miniature, accelerometer-containing electronic loggers which can be attached to free-living animals. Accelerometers provide information on both body posture and dynamism which can be used as descriptors to define behaviour. We deployed tri-axial accelerometer loggers on 12 free-ranging Eur-asian beavers Castor fiber in the county of Telemark, Norway, and on four captive beavers (two Eurasian beavers and two North American beavers C. canadensis) to corroborate acceleration signals with observed behaviours. By using random forests for classifying behavioural patterns of beavers from accelerometry data, we were able to distinguish seven behaviours; standing, walking, swimming, feeding, grooming, diving and sleeping. We show how to apply the use of acceleration to determine behaviour, and emphasise the ease with which this non-invasive method can be implemented. Furthermore, we discuss the strengths and weaknesses of this, ...

Emergence of multicore architectures has opened up new opportunities for thread-level parallelism... more Emergence of multicore architectures has opened up new opportunities for thread-level parallelism and dramatically increased the theoretical peak on current systems. However, achieving a high fraction of peak performance requires careful orchestration of many architecture-sensitive parameters, both on-chip and across the interconnect. In particular, the presence of shared-caches on multicore architectures makes it necessary to consider, in concert, issues related to thread synchronization and data locality. This paper studies the complex interaction among several compiler-level code transformations that affect data locality, achieved parallelism and synchronization and communication costs. We characterize this interaction using static analysis and generate a search space suitable for efficient automatic performance tuning. We also develop a heuristic based on number of threads; data reuse patterns, and the size and configuration of the shared cache, to estimate the optimal synchroni...

Journal of the Academy of Nutrition and Dietetics, 2018

Learning Outcome: Upon completion, participants will be able to understand the positive impact of... more Learning Outcome: Upon completion, participants will be able to understand the positive impact of Clinical nutrition managed formula lab operations including detailed policies and procedures, training, and competencies aligned with national standards Funding source: Tallahassee Memorial HealthCare (non-profit hospital)

Movement Ecology, 2016

Background: We are increasingly using recording devices with multiple sensors operating at high f... more Background: We are increasingly using recording devices with multiple sensors operating at high frequencies to produce large volumes of data which are problematic to interpret. A particularly challenging example comes from studies on animals and humans where researchers use animal-attached accelerometers on moving subjects to attempt to quantify behaviour, energy expenditure and condition. Results: The approach taken effectively concatinated three complex lines of acceleration into one visualization that highlighted patterns that were otherwise not obvious. The summation of data points within sphere facets and presentation into histograms on the sphere surface effectively dealt with data occlusion. Further frequency binning of data within facets and representation of these bins as discs on spines radiating from the sphere allowed patterns in dynamic body accelerations (DBA) associated with different postures to become obvious. Method: We examine the extent to which novel, gravity-based spherical plots can produce revealing visualizations to incorporate the complexity of such multidimensional acceleration data using a suite of different acceleration-derived metrics with a view to highlighting patterns that are not obvious using current approaches. The basis for the visualisation involved three-dimensional plots of the smoothed acceleration values, which then occupied points on the surface of a sphere. This sphere was divided into facets and point density within each facet expressed as a histogram. Within each facet-dependent histogram, data were also grouped into frequency bins of any desirable parameters, most particularly dynamic body acceleration (DBA), which were then presented as discs on a central spine radiating from the facet. Greater radial distances from the sphere surface indicated greater DBA values while greater disc diameter indicated larger numbers of data points with that particular value. Conclusions: We indicate how this approach links behaviour and proxies for energetics and can inform our identification and understanding of movement-related processes, highlighting subtle differences in movement and its associated energetics. This approach has ramifications that should expand to areas as disparate as disease identification, lifestyle, sports practice and wild animal ecology.

Contour lines show 2.5% intervals.</p

Journal of the Academy of Nutrition and Dietetics, 2018

Movement Ecology, 2016