33,043 research outputs found
Expressive Stream Reasoning with Laser
An increasing number of use cases require a timely extraction of non-trivial
knowledge from semantically annotated data streams, especially on the Web and
for the Internet of Things (IoT). Often, this extraction requires expressive
reasoning, which is challenging to compute on large streams. We propose Laser,
a new reasoner that supports a pragmatic, non-trivial fragment of the logic
LARS which extends Answer Set Programming (ASP) for streams. At its core, Laser
implements a novel evaluation procedure which annotates formulae to avoid the
re-computation of duplicates at multiple time points. This procedure, combined
with a judicious implementation of the LARS operators, is responsible for
significantly better runtimes than the ones of other state-of-the-art systems
like C-SPARQL and CQELS, or an implementation of LARS which runs on the ASP
solver Clingo. This enables the application of expressive logic-based reasoning
to large streams and opens the door to a wider range of stream reasoning use
cases.Comment: 19 pages, 5 figures. Extended version of accepted paper at ISWC 201
Profile-Based Optimal Matchings in the Student-Project Allocation Problem
In the Student/Project Allocation problem (spa) we seek to assign students to individual or group projects offered by lecturers. Students provide a list of projects they find acceptable in order of preference. Each student can be assigned to at most one project and there are constraints on the maximum number of students that can be assigned to each project and lecturer. We seek matchings of students to projects that are optimal with respect to profile, which is a vector whose rth component indicates how many students have their rth-choice project. We present an efficient algorithm for finding agreedy maximum matching in the spa context – this is a maximum matching whose profile is lexicographically maximum. We then show how to adapt this algorithm to find a generous maximum matching – this is a matching whose reverse profile is lexicographically minimum. Our algorithms involve finding optimal flows in networks. We demonstrate how this approach can allow for additional constraints, such as lecturer lower quotas, to be handled flexibly
A semi-Markov model for stroke with piecewise-constant hazards in the presence of left, right and interval censoring.
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazards in the presence of left, right and interval censoring. We investigate transition intensities in a three-state illness-death model with no recovery. We relax the Markov assumption by adjusting the intensity for the transition from state 2 (illness) to state 3 (death) for the time spent in state 2 through a time-varying covariate. This involves the exact time of the transition from state 1 (healthy) to state 2. When the data are subject to left or interval censoring, this time is unknown. In the estimation of the likelihood, we take into account interval censoring by integrating out all possible times for the transition from state 1 to state 2. For left censoring, we use an Expectation-Maximisation inspired algorithm. A simulation study reflects the performance of the method. The proposed combination of statistical procedures provides great flexibility. We illustrate the method in an application by using data on stroke onset for the older population from the UK Medical Research Council Cognitive Function and Ageing Study
The Stable Roommates problem with short lists
We consider two variants of the classical Stable Roommates problem with
Incomplete (but strictly ordered) preference lists SRI that are degree
constrained, i.e., preference lists are of bounded length. The first variant,
EGAL d-SRI, involves finding an egalitarian stable matching in solvable
instances of SRI with preference lists of length at most d. We show that this
problem is NP-hard even if d=3. On the positive side we give a
(2d+3)/7-approximation algorithm for d={3,4,5} which improves on the known
bound of 2 for the unbounded preference list case. In the second variant of
SRI, called d-SRTI, preference lists can include ties and are of length at most
d. We show that the problem of deciding whether an instance of d-SRTI admits a
stable matching is NP-complete even if d=3. We also consider the "most stable"
version of this problem and prove a strong inapproximability bound for the d=3
case. However for d=2 we show that the latter problem can be solved in
polynomial time.Comment: short version appeared at SAGT 201
Dilated Convolutional Neural Networks for Cardiovascular MR Segmentation in Congenital Heart Disease
We propose an automatic method using dilated convolutional neural networks
(CNNs) for segmentation of the myocardium and blood pool in cardiovascular MR
(CMR) of patients with congenital heart disease (CHD).
Ten training and ten test CMR scans cropped to an ROI around the heart were
provided in the MICCAI 2016 HVSMR challenge. A dilated CNN with a receptive
field of 131x131 voxels was trained for myocardium and blood pool segmentation
in axial, sagittal and coronal image slices. Performance was evaluated within
the HVSMR challenge.
Automatic segmentation of the test scans resulted in Dice indices of
0.800.06 and 0.930.02, average distances to boundaries of
0.960.31 and 0.890.24 mm, and Hausdorff distances of 6.133.76
and 7.073.01 mm for the myocardium and blood pool, respectively.
Segmentation took 41.514.7 s per scan.
In conclusion, dilated CNNs trained on a small set of CMR images of CHD
patients showing large anatomical variability provide accurate myocardium and
blood pool segmentations
Further evidence for the planet around 51 Pegasi
The discovery of the planet around the solar-type star 51 Pegasi marked a
watershed in the search for extrasolar planets. Since then seven other
solar-type stars have been discovered, of which several have surprisingly short
orbital periods, like the planet around 51 Peg. These planets were detected
using the indirect technique of measuring variations in the Doppler shifts of
lines in the spectra of the primary stars. But it is possible that oscillations
of the stars themselves (or other effects) could mimic the signature of the
planets, particularly around the short-period planets. The apparent lack of
spectral and brightness variations, however, led to widespread acceptance that
there is a planet around 51 Peg. This conclusion was challenged by the
observation of systematic variations in the line profile shapes of 51 Peg,
which suggested stellar oscillations. If these observations are correct, then
there is no need to invoke a planet around 51 Peg to explain the data. Here we
report observations of 51 Peg at a much higher spectral resolution than those
in ref.9, in which we find no evidence for systematic changes in the line
shapes. The data are most consistent with a planetary companion to 51 Peg.Comment: LaTeX, 6 pages, 2 figures. To appear in 8 January 1998 issue of
Natur
Rapid turnover of effector-memory CD4(+) T cells in healthy humans
Memory T cells can be divided into central-memory (T(CM)) and effector-memory (T(EM)) cells, which differ in their functional properties. Although both subpopulations can persist long term, it is not known whether they are maintained by similar mechanisms. We used in vivo labeling with deuterated glucose to measure the turnover of CD4(+) T cells in healthy humans. The CD45R0(+)CCR7(-) T(EM) subpopulation was shown to have a rapid proliferation rate of 4.7% per day compared with 1.5% per day for CD45R0(+)CCR7(+) T(CM) cells; these values are equivalent to average intermitotic (doubling) times of 15 and 48 d, respectively. In contrast, the CD45RA(+)CCR7(+) naive CD4(+) T cell population was found to be much longer lived, being labeled at a rate of only 0.2% per day (corresponding to an intermitotic time of approximately 1 yr). These data indicate that human CD4(+) T(EM) cells constitute a short-lived cell population that requires continuous replenishment in vivo
An Integer Programming Approach to the Student-Project Allocation Problem with Preferences over Projects
The Student-Project Allocation problem with preferences over Projects (SPA-P) involves sets of students, projects and lecturers, where the students and lecturers each have preferences over the projects. In this context, we typically seek a stable matching of students to projects (and lecturers). However, these stable matchings can have different sizes, and the problem of finding a maximum stable matching (MAX-SPA-P) is NP-hard. There are two known approximation algorithms for MAX-SPA-P, with performance guarantees of 2 and 32 . In this paper, we describe an Integer Programming (IP) model to enable MAX-SPA-P to be solved optimally. Following this, we present results arising from an empirical analysis that investigates how the solution produced by the approximation algorithms compares to the optimal solution obtained from the IP model, with respect to the size of the stable matchings constructed, on instances that are both randomly-generated and derived from real datasets. Our main finding is that the 32 -approximation algorithm finds stable matchings that are very close to having maximum cardinality
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