289 research outputs found
Compressive Sensing
This work is an expository overview of certain key elements in the area of compressive sensing. As a sub-discipline of signal processing, compressive sensing is concerned with both sampling and reconstruction techniques. In this expository, sampling will center on random matrices and expander graphs, while reconstruction will use multiple numerical optimization techniques. Although theoretical performance bounds for these techniques can be found scattered throughout the published literature, there are few practical rules for concrete problems. This thesis helps fill this gap by experimenting on the asymptotic bounds of the number of measurements needed to guarantee perfect reconstruction. These numerical experiments help to identify specific sensing regimes in which performance begin to break down
Neural Acceleration of Incomplete Cholesky Preconditioners
The solution of a sparse system of linear equations is ubiquitous in
scientific applications. Iterative methods, such as the Preconditioned
Conjugate Gradient method (PCG), are normally chosen over direct methods due to
memory and computational complexity constraints. However, the efficiency of
these methods depends on the preconditioner utilized. The development of the
preconditioner normally requires some insight into the sparse linear system and
the desired trade-off of generating the preconditioner and the reduction in the
number of iterations. Incomplete factorization methods tend to be black box
methods to generate these preconditioners but may fail for a number of reasons.
These reasons include numerical issues that require searching for adequate
scaling, shifting, and fill-in while utilizing a difficult to parallelize
algorithm. With a move towards heterogeneous computing, many sparse
applications find GPUs that are optimized for dense tensor applications like
training neural networks being underutilized. In this work, we demonstrate that
a simple artificial neural network trained either at compile time or in
parallel to the running application on a GPU can provide an incomplete sparse
Cholesky factorization that can be used as a preconditioner. This generated
preconditioner is as good or better in terms of reduction of iterations than
the one found using multiple preconditioning techniques such as scaling and
shifting. Moreover, the generated method also works and never fails to produce
a preconditioner that does not reduce the iteration count
Are within-person Numerical Rating Scale (NRS) ratings of breathlessness 'on average' valid in advanced disease for patients and for patients' informal carers?
INTRODUCTION: The Numerical Rating Scale (NRS) is frequently used to assess patient-reported breathlessness in both a research and clinical context. A subgroup of patients report average breathlessness as worse than their worst breathlessness in the last 24 hours (paradoxical average). The Peak/End rule describes how the most extreme and current breathlessness influence reported average. This study seeks to highlight the existence of a subpopulation who give 'paradoxical averages using the NRS, to characterise this group and to investigate the explanatory relevance of the 'Peak/End' rule. METHODS: Data were collected within mixed method face-to-face interviews for three studies: the Living with Breathlessness Study and the two subprotocols of the Breathlessness Intervention Service phase III randomised controlled trial. Key variables from the three datasets were pooled (n=561), and cases where participants reported a paradoxical average (n=45) were identified. These were compared with non-cases and interview transcripts interrogated. NRS ratings of average breathlessness were assessed for fit to Peak/End rule. RESULTS: Patients in the paradoxical average group had higher Chronic Respiratory Questionnaire physical domain scores on average p=0.042). Peak/End rule analysis showed high positive correlation (Spearman's rho=0.756, p<0.001). CONCLUSIONS: The NRS requires further standardisation with reporting of question order and construction of scale used to enable informed interpretation. The application of the Peak/End rule demonstrates fallibility of NRS-Average as a construct as it is affected by current breathlessness. Measurement of breathlessness is important for both clinical management and research, but standardisation and transparency are required for meaningful results
Targeting Net Zero Energy at Marine Corps Air Station Miramar: Assessment and Recommendations
In 2008, the Department of Defense (DoD) and Department of Energy (DOE) defined a joint initiative to address military energy use by identifying specific actions to reduce energy demand and increase use of renewable energy on DoD installations. A Task Force comprised of representatives from the Office of the Secretary of Defense (OSD), the four military Services, DOE’s Federal Energy Management Program (FEMP), and the National Renewable Energy Laboratory (NREL) was established. In light of DoD priorities, early attention was given to the possibility of net zero energy military installations (NZEI), that is, installations that would meet their energy needs with local renewable resources. Marine Corps Air Station (MCAS) The Task Force selected Miramar to be the prototype installation for net zero energy assessment and planning. This selection was based on Miramar’s strong history of energy advocacy and extensive track record of successful energy projects
Beyond the angle of repose: A review and synthesis of landslide processes in response to rapid uplift, Eel River, Northern California
In mountainous settings, increases in rock uplift are often followed by a commensurate uptick in denudation as rivers incise and steepen hillslopes, making them increasingly prone to landsliding as slope angles approach a limiting value. For decades, the threshold slope model has been invoked to account for landslide-driven increases in sediment flux that limit topographic relief, but the manner by which slope failures organize themselves spatially and temporally in order for erosion to keep pace with rock uplift has not been well documented. Here, we review past work and present new findings from remote sensing, cosmogenic radionuclides, suspended sediment records, and airborne lidar data, to decipher patterns of landslide activity and geomorphic processes related to rapid uplift along the northward-migrating Mendocino Triple Junction in Northern California. From historical air photos and airborne lidar, we estimated the velocity and sediment flux associated with active, slow-moving landslides (or earthflows) in the mélange- and argillite-dominated Eel River watershed using the downslope displacement of surface markers such as trees and shrubs. Although active landslides that directly convey sediment into the channel network account for only 7% of the landscape surface, their sediment flux amounts to more than 50% of the suspended load recorded at downstream sediment gaging stations. These active slides tend to exhibit seasonal variations in velocity as satellite-based interferometry has demonstrated that rapid acceleration commences within 1 to 2 months of the onset of autumn rainfall events before slower deceleration ensues in the spring and summer months. Curiously, this seasonal velocity pattern does not appear to vary with landslide size, suggesting that complex hydrologic–mechanical feedbacks (rather than 1-D pore pressure diffusion) may govern slide dynamics. A new analysis of 14 yrs of discharge and sediment concentration data for the Eel River indicates that the characteristic mid-winter timing of earthflow acceleration corresponds with increased suspended concentration values, suggesting that the seasonal onset of landslide motion each year may be reflected in the export of sediments to the continental margin. The vast majority of active slides exhibit gullied surfaces and the gully networks, which are also seasonally active, may facilitate sediment export although the proportion of material produced by this pathway is poorly known. Along Kekawaka Creek, a prominent tributary to the Eel River, new analyses of catchment-averaged erosion rates derived from cosmogenic radionuclides reveal rapid erosion (0.76 mm/yr) below a prominent knickpoint and slower erosion (0.29 mm/yr) upstream. Such knickpoints are frequently observed in Eel tributaries and are usually comprised of massive (> 10 m) interlocking resistant boulders that likely persist in the landscape for long periods of time (> 105 yr). Upstream of these knickpoints, active landslides tend to be less frequent and average slope angles are slightly gentler than in downstream areas, which indicates that landslide density and average slope angle appear to increase with erosion rate. Lastly, we synthesize evidence for the role of large, catastrophic landslides in regulating sediment flux and landscape form. The emergence of resistant blocks within the mélange bedrock has promoted large catastrophic slides that have dammed the Eel River and perhaps generated outburst events in the past. The frequency and impact of these landslide dams likely depend on the spatial and size distributions of resistant blocks relative to the width and drainage area of adjacent valley networks. Overall, our findings demonstrate that landslides within the Eel River catchment do not occur randomly, but instead exhibit spatial and temporal patterns related to baselevel lowering, climate forcing, and lithologic variations. Combined with recent landscape evolution models that incorporate landslides, these results provide predictive capability for estimating erosion rates and managing hazards in mountainous regions
STS-k: A Multilevel Sparse Triangular Solution Scheme for NUMA Multicores
We consider techniques to improve the performance of parallel sparse triangular solution on non-uniform memory architecture multicores by extending earlier coloring and level set schemes for single-core multiprocessors. We develop sts-k, where k represents a small number of transformations for latency reduction from increased spatial and temporal locality of data accesses. We propose a graph model of data reuse to inform the development of sts-k and to prove that computing an optimal cost schedule is NP-complete. We observe significant speed-ups with sts-3 on 32-core Intel Westmere-EX and 24-core AMD `MagnyCours' processors.Incremental gains solely from the 3-level transformations in sts-3 for a fixed ordering, correspond to reductions in execution times by factors of 1.4 (Intel) and 1.5 (AMD) for level sets and 2 (Intel) and 2.2 (AMD) for coloring. On average, execution times are reduced by a factor of 6 (Intel) and 4 (AMD) for sts-3 with coloring compared to a reference implementation using level sets
The opportunities, challenges, and rewards of "community peer research": reflections on research practice
© 2024 The Authors. Published by SAGE. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1177/10778004241229789This article shares reflections from a group of academic researchers at the same University on their experience of conducting “community peer research” projects involving nonacademics in social research. We review a range of literature that has influenced the development of our practice, stressing the importance of co-production and power relations. We present six case studies that represent the breadth of our different engagements with community peer research, and then go on to reflect on the challenges and benefits of this approach. We identify a number of practical challenges, ways in which we overcame them, and in particular stress the importance of providing well-designed training for community peer researchers. We conclude with some recommendations for other researchers looking to conduct similar research
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