589 research outputs found
Multi-Step Processing of Spatial Joins
Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended spatial objects in twodimensional data space. We present an approach for spatial join processing that is based on three steps. First, a spatial join is performed on the minimum bounding rectangles of the objects returning a set of candidates. Various approaches for accelerating this step of join processing have been examined at the last year’s conference [BKS 93a]. In this paper, we focus on the problem how to compute the answers from the set of candidates which is handled by
the following two steps. First of all, sophisticated approximations
are used to identify answers as well as to filter out false hits from
the set of candidates. For this purpose, we investigate various types
of conservative and progressive approximations. In the last step, the
exact geometry of the remaining candidates has to be tested against
the join predicate. The time required for computing spatial join
predicates can essentially be reduced when objects are adequately
organized in main memory. In our approach, objects are first decomposed
into simple components which are exclusively organized
by a main-memory resident spatial data structure. Overall, we
present a complete approach of spatial join processing on complex
spatial objects. The performance of the individual steps of our approach
is evaluated with data sets from real cartographic applications.
The results show that our approach reduces the total execution
time of the spatial join by factors
Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
Clustering non-Euclidean data is difficult, and one of the most used
algorithms besides hierarchical clustering is the popular algorithm
Partitioning Around Medoids (PAM), also simply referred to as k-medoids. In
Euclidean geometry the mean-as used in k-means-is a good estimator for the
cluster center, but this does not hold for arbitrary dissimilarities. PAM uses
the medoid instead, the object with the smallest dissimilarity to all others in
the cluster. This notion of centrality can be used with any (dis-)similarity,
and thus is of high relevance to many domains such as biology that require the
use of Jaccard, Gower, or more complex distances.
A key issue with PAM is its high run time cost. We propose modifications to
the PAM algorithm to achieve an O(k)-fold speedup in the second SWAP phase of
the algorithm, but will still find the same results as the original PAM
algorithm. If we slightly relax the choice of swaps performed (at comparable
quality), we can further accelerate the algorithm by performing up to k swaps
in each iteration. With the substantially faster SWAP, we can now also explore
alternative strategies for choosing the initial medoids. We also show how the
CLARA and CLARANS algorithms benefit from these modifications. It can easily be
combined with earlier approaches to use PAM and CLARA on big data (some of
which use PAM as a subroutine, hence can immediately benefit from these
improvements), where the performance with high k becomes increasingly
important.
In experiments on real data with k=100, we observed a 200-fold speedup
compared to the original PAM SWAP algorithm, making PAM applicable to larger
data sets as long as we can afford to compute a distance matrix, and in
particular to higher k (at k=2, the new SWAP was only 1.5 times faster, as the
speedup is expected to increase with k)
What Gets Measured in Reentry Research? A Scoping Review on Community Reentry From Jail and Prison for Persons With Mental Illnesses
Research on reentry for individuals with mental illnesses leaving jails and prisons lacks outcome specificity and standardization needed to advance knowledge about the efficacy and effectiveness of interventions. This scoping review aims to provide clarity about reentry outcomes by: (a) ascertaining what outcomes are a focus in reentry research, (b) explicating how outcomes are defined, and (c) identifying commonalities or gaps in outcomes reported. A search of multiple databases yielded 415 articles for potential inclusion. After independent document review by two of the authors, 61 articles were included in the review. Recidivism was the most used construct, accounting for 58% of total outcomes and 95% of criminal legal outcomes. Behavioral health indicators were reported the second most frequently and other outcomes were rarely reported. Increasing the specificity of commonly used concepts while also expanding the breadth of outcomes considered is needed to build an evidence base this area of research
CFD modelling of an animal occupied zone using an anisotropic porous medium model with velocity depended resistance parameters
The airflow in dairy barns is affected by many factors, such as the barn's geometry, weather conditions, configurations of the openings, cows acting as heat sources, flow obstacles, etc. Computational fluids dynamics (CFD) has the advantages of providing detailed airflow information and allowing fully-controlled boundary conditions, and therefore is widely used in livestock building research. However, due to the limited computing power, numerous animals are difficult to be designed in detail. Consequently, there is the need to develop and use smart numerical models in order to reduce the computing power needed while at the same time keeping a comparable level of accuracy.
In this work the porous medium modeling is considered to solve this problem using Ansys Fluent. A comparison between an animal occupied zone (AOZ) filled with randomly arranged 22 simplified cows' geometry model (CM) and the porous medium model (PMM) of it, was made. Anisotropic behavior of the PMM was implemented in the porous modeling to account for turbulence influences. The velocity at the inlet of the domain has been varied from 0.1 m s(-1) to 3 in s(-1) and the temperature difference between the animals and the incoming air was set at 20 K. Leading to Richardson numbers Ri corresponding to the three types of heat transfer convection, i.e. natural, mixed and forced convection. It has been found that the difference between two models (the cow geometry model and the PMM) was around 2% for the pressure drop and less than 6% for the convective heat transfer. Further the usefulness of parametrized PMM with a velocity adaptive pressure drop and heat transfer coefficient is shown by velocity field validation of an on-farm measurement
Predicting the Next Best View for 3D Mesh Refinement
3D reconstruction is a core task in many applications such as robot
navigation or sites inspections. Finding the best poses to capture part of the
scene is one of the most challenging topic that goes under the name of Next
Best View. Recently, many volumetric methods have been proposed; they choose
the Next Best View by reasoning over a 3D voxelized space and by finding which
pose minimizes the uncertainty decoded into the voxels. Such methods are
effective, but they do not scale well since the underlaying representation
requires a huge amount of memory. In this paper we propose a novel mesh-based
approach which focuses on the worst reconstructed region of the environment
mesh. We define a photo-consistent index to evaluate the 3D mesh accuracy, and
an energy function over the worst regions of the mesh which takes into account
the mutual parallax with respect to the previous cameras, the angle of
incidence of the viewing ray to the surface and the visibility of the region.
We test our approach over a well known dataset and achieve state-of-the-art
results.Comment: 13 pages, 5 figures, to be published in IAS-1
Personhood, consciousness, and god : how to be a proper pantheist
© Springer Nature B.V. 2018In this paper I develop a theory of personhood which leaves open the possibility of construing the universe as a person. If successful, it removes one bar to endorsing pantheism. I do this by examining a rising school of thought on personhood, on which persons, or selves, are understood as identical to episodes of consciousness. Through a critique of this experiential approach to personhood, I develop a theory of self as constituted of qualitative mental contents, but where these contents are also capable of unconscious existence. On this theory, though we can be conscious of our selves, consciousness turns out to be inessential to personhood. This move, I then argue, provides resources for responding to the pantheist’s problem of God’s person.Peer reviewedFinal Accepted Versio
On the Whitham hierarchy: dressing scheme, string equations and additional symmetrie
A new description of the universal Whitham hierarchy in terms of a
factorization problem in the Lie group of canonical transformations is
provided. This scheme allows us to give a natural description of dressing
transformations, string equations and additional symmetries for the Whitham
hierarchy. We show how to dress any given solution and prove that any solution
of the hierarchy may be undressed, and therefore comes from a factorization of
a canonical transformation. A particulary important function, related to the
-function, appears as a potential of the hierarchy. We introduce a class
of string equations which extends and contains previous classes of string
equations considered by Krichever and by Takasaki and Takebe. The scheme is
also applied for an convenient derivation of additional symmetries. Moreover,
new functional symmetries of the Zakharov extension of the Benney gas equations
are given and the action of additional symmetries over the potential in terms
of linear PDEs is characterized
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