867 research outputs found
Snow metamorphism: a fractal approach
Snow is a porous disordered medium consisting of air and three water phases:
ice, vapour and liquid. The ice phase consists of an assemblage of grains, ice
matrix, initially arranged over a random load bearing skeleton. The
quantitative relationship between density and morphological characteristics of
different snow microstructures is still an open issue. In this work, a
three-dimensional fractal description of density corresponding to different
snow microstructure is put forward. First, snow density is simulated in terms
of a generalized Menger sponge model. Then, a fully three-dimensional compact
stochastic fractal model is adopted. The latter approach yields a quantitative
map of the randomness of the snow texture, which is described as a
three-dimensional fractional Brownian field with the Hurst exponent H varying
as continuous parameter. The Hurst exponent is found to be strongly dependent
on snow morphology and density. The approach might be applied to all those
cases where the morphological evolution of snow cover or ice sheets should be
conveniently described at a quantitative level
The self-excitation damping ratio: A chatter criterion for time-domain milling simulations
Regenerative chatter is known to be a key factor that limits the productivity of high speed machining. Consequently, a great deal of research has focused on developing predictive models of milling dynamics, to aid engineers involved in both research and manufacturing practice. Time-domain models suffer from being computationally intensive, particularly when they are used to predict the boundary of chatter stability, when a large number of simulation runs are required under different milling conditions. Furthermore, to identify the boundary of stability each simulation must run for sufficient time for the chatter effect to manifest itself in the numerical data, and this is a major contributor to the inefficiency of the chatter prediction process. In the present article, a new chatter criterion is proposed for time-domain milling simulations, that aims to overcome this draw-back by considering the transient response of the modeled behavior, rather than the steady-state response. Using a series of numerical investigations, it is shown that in many cases the new criterion can enable the numerical prediction to be computed more than five times faster than was previously possible. In addition, the analysis yields greater detail concerning the nature of the chatter vibrations, and the degree of stability that is observed
Near Real-Time Data Labeling Using a Depth Sensor for EMG Based Prosthetic Arms
Recognizing sEMG (Surface Electromyography) signals belonging to a particular
action (e.g., lateral arm raise) automatically is a challenging task as EMG
signals themselves have a lot of variation even for the same action due to
several factors. To overcome this issue, there should be a proper separation
which indicates similar patterns repetitively for a particular action in raw
signals. A repetitive pattern is not always matched because the same action can
be carried out with different time duration. Thus, a depth sensor (Kinect) was
used for pattern identification where three joint angles were recording
continuously which is clearly separable for a particular action while recording
sEMG signals. To Segment out a repetitive pattern in angle data, MDTW (Moving
Dynamic Time Warping) approach is introduced. This technique is allowed to
retrieve suspected motion of interest from raw signals. MDTW based on DTW
algorithm, but it will be moving through the whole dataset in a pre-defined
manner which is capable of picking up almost all the suspected segments inside
a given dataset an optimal way. Elevated bicep curl and lateral arm raise
movements are taken as motions of interest to show how the proposed technique
can be employed to achieve auto identification and labelling. The full
implementation is available at https://github.com/GPrathap/OpenBCIPytho
University Libraries Faculty Assembly Covid-19 Impact Statement
This University Libraries Faculty Assembly Covid-19 Impact Statement serves as documentation of changes that occurred across University Libraries and caused disparate, inequitable, impact to faculty throughout the pandemic, beginning in March 2020 and spanning into 2021. The document is necessarily limited in scope to assist faculty candidates in the tenure-track process and mitigate potential traumas as a result of the pandemic’s impact on that process. The structure of the tenure-track process is imperfect in nature, and this statement takes a trauma-informed, person-first, approach to investigating how to best support candidates in making their case for contract renewal, tenure, and/or promotion
Utility of the Occupation-Centered Intervention Assessment for Occupational Therapy Level I Fieldwork
This study examined the utility of the Occupation-Centered Intervention Assessment (OCIA) among occupational therapy students and their perceptions of the use of an occupation-centered approach to design interventions during level I fieldwork. Twenty-five students completed training on the OCIA, used the tool on level 1 fieldwork, and then completed a post-test survey containing closed and open-ended questions. Content analysis was used to analyze open-ended questions. Descriptive statistics was used to analyze quantitative data. Overall, students (N = 25) found the OCIA to be a beneficial tool to utilize during fieldwork experiences to recognize and develop interventions from an occupation-centered approach. Currently the Occupational Therapy Practice Framework and models of practice are the primary tools available for student reflection for intervention design. The findings of this study supported the need for a reflection tool to aide in the development and implementation of occupation-centered reasoning during fieldwork experiences
Processor Allocation for Optimistic Parallelization of Irregular Programs
Optimistic parallelization is a promising approach for the parallelization of
irregular algorithms: potentially interfering tasks are launched dynamically,
and the runtime system detects conflicts between concurrent activities,
aborting and rolling back conflicting tasks. However, parallelism in irregular
algorithms is very complex. In a regular algorithm like dense matrix
multiplication, the amount of parallelism can usually be expressed as a
function of the problem size, so it is reasonably straightforward to determine
how many processors should be allocated to execute a regular algorithm of a
certain size (this is called the processor allocation problem). In contrast,
parallelism in irregular algorithms can be a function of input parameters, and
the amount of parallelism can vary dramatically during the execution of the
irregular algorithm. Therefore, the processor allocation problem for irregular
algorithms is very difficult.
In this paper, we describe the first systematic strategy for addressing this
problem. Our approach is based on a construct called the conflict graph, which
(i) provides insight into the amount of parallelism that can be extracted from
an irregular algorithm, and (ii) can be used to address the processor
allocation problem for irregular algorithms. We show that this problem is
related to a generalization of the unfriendly seating problem and, by extending
Tur\'an's theorem, we obtain a worst-case class of problems for optimistic
parallelization, which we use to derive a lower bound on the exploitable
parallelism. Finally, using some theoretically derived properties and some
experimental facts, we design a quick and stable control strategy for solving
the processor allocation problem heuristically.Comment: 12 pages, 3 figures, extended version of SPAA 2011 brief announcemen
Growth form and leaf habit drive contrasting effects of Arctic amplification in long-lived woody species
Current global change is inducing heterogeneous warming trends worldwide, with faster rates at higher latitudes in the Northern Hemisphere. Consequently, tundra vegetation is experiencing an increase in growth rate and uneven but expanding distribution. Yet, the drivers of this heterogeneity in woody species responses are still unclear. Here, applying a retrospective approach and focusing on long-term responses, we aim to get insight into growth trends and climate sensitivity of long-lived woody species belonging to different functional types with contrasting growth forms and leaf habits (shrub vs. tree and deciduous vs. evergreen). A total of 530 samples from 7 species (common juniper, dwarf birch, woolly willow, Norway spruce, lodgepole pine, rowan, and downy birch) were collected in 10 sites across Iceland. We modelled growth trends and contrasted yearly ring-width measurements, filtering in high- and low-frequency components, with precipitation, land- and sea-surface temperature records (1967-2018). Shrubs and trees showed divergent growth trends, with shrubs closely tracking the recent warming, whereas trees, especially broadleaved, showed strong fluctuations but no long-term growth trends. Secondary growth, particularly the high-frequency component, was positively correlated with summer temperatures for most of the species. On the contrary, growth responses to sea surface temperature, especially in the low frequency, were highly diverging between growth forms, with a strong positive association for shrubs and a negative for trees. Within comparable vegetation assemblage, long-lived woody species could show contrasting responses to similar climatic conditions. Given the predominant role of oceanic masses in shaping climate patterns in the Arctic and Low Arctic, further investigations are needed to deepen the knowledge on the complex interplay between coastal tundra ecosystems and land-sea surface temperature dynamics
A Wavelet-Based Algorithm for the Spatial Analysis of Poisson Data
Wavelets are scaleable, oscillatory functions that deviate from zero only
within a limited spatial regime and have average value zero. In addition to
their use as source characterizers, wavelet functions are rapidly gaining
currency within the source detection field. Wavelet-based source detection
involves the correlation of scaled wavelet functions with binned,
two-dimensional image data. If the chosen wavelet function exhibits the
property of vanishing moments, significantly non-zero correlation coefficients
will be observed only where there are high-order variations in the data; e.g.,
they will be observed in the vicinity of sources.
In this paper, we describe the mission-independent, wavelet-based source
detection algorithm WAVDETECT, part of the CIAO software package. Aspects of
our algorithm include: (1) the computation of local, exposure-corrected
normalized (i.e. flat-fielded) background maps; (2) the correction for exposure
variations within the field-of-view; (3) its applicability within the
low-counts regime, as it does not require a minimum number of background counts
per pixel for the accurate computation of source detection thresholds; (4) the
generation of a source list in a manner that does not depend upon a detailed
knowledge of the point spread function (PSF) shape; and (5) error analysis.
These features make our algorithm considerably more general than previous
methods developed for the analysis of X-ray image data, especially in the low
count regime. We demonstrate the algorithm's robustness by applying it to
various images.Comment: Accepted for publication in Ap. J. Supp. (v. 138 Jan. 2002). 61
pages, 23 figures, expands to 3.8 Mb. Abstract abridged for astro-ph
submissio
Partial Photoionization Cross Sections And Photoelectron Angular Distributions For Double Excitations Up To The N=5 Threshold In Helium
Partial photoionization cross sections sigma(n) and photoelectron angular distributions beta(n) were measured for all possible final ionic states He+(n) in the region of the double excitations N(K,T)(A) up to the N=5 threshold. At a photon energy bandpass of 12 meV below the thresholds N=3,4, and 5, this level of differentiation offers the most critical assessment of the dynamics of the two-electron excitations to date. The experimental data are very well described by the most advanced theoretical calculations. Weaker double-excitation series with K=N-4 are clearly visible in the beta(n) data, and even previously unobserved extremely weak series members with A=-1 can be discerned, showing the high sensitivity of the angular resolved measurements. The shapes of the resonance-induced variations of sigma(n) or beta(n) in the double excitations below a given threshold N change radically depending on the final ionic state n but display striking similarities when comparing the satellite states with n=N-1 and n=N-2 below each threshold N. These systematic patterns may indicate a general rule for the underlying two-electron dynamics
Investigations of solutions of Einstein's field equations close to lambda-Taub-NUT
We present investigations of a class of solutions of Einstein's field
equations close to the family of lambda-Taub-NUT spacetimes. The studies are
done using a numerical code introduced by the author elsewhere. One of the main
technical complication is due to the S3-topology of the Cauchy surfaces.
Complementing these numerical results with heuristic arguments, we are able to
yield some first insights into the strong cosmic censorship issue and the
conjectures by Belinskii, Khalatnikov, and Lifschitz in this class of
spacetimes. In particular, the current investigations suggest that strong
cosmic censorship holds in this class. We further identify open issues in our
current approach and point to future research projects.Comment: 24 pages, 12 figures, uses psfrag and hyperref; replaced with
published version, only minor corrections of typos and reference
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