8,740 research outputs found
A spatial signature of sprawl: or the proportion and distribution of linear networkcircuits
This paper sets out to investigate whether the frequency distribution ofthe linear network circuits within a graph-based representation of aroad transportation system can be helpful in identifying sprawl and, inparticular, whether a 'spatial signature of sprawl' can be determined.This paper is based upon an earlier study on Peachtree City, Georgia and in particular of its dual transportation system (roads and golf cartpaths). In order to fully understand the effect that the dualtransportation system has upon Peachtree City, the frequencydistribution of its circuits are compared to three, supposed, 'suburban' areas and three, supposed, 'urban' districts. The conclusion of thispaper is that there is, unquestionably, a measurable continuum between 'suburbia' and 'urbanity' and that this is reflected in the frequency,length and distribution of the graph network circuits. The main sectionof this paper is concerned with the presentation and discussion ofalternative algorithms for calculating these circuits. This section isfollowed by an introduction of a selection of methods for interpretingthe resultant data. Finally, with respect to Peachtree City, this paperconcludes that the effect of the dual transportation system is to make it more 'urban' than it would otherwise be, although it remains adistinctly suburban environment
Group Testing with Probabilistic Tests: Theory, Design and Application
Identification of defective members of large populations has been widely
studied in the statistics community under the name of group testing. It
involves grouping subsets of items into different pools and detecting defective
members based on the set of test results obtained for each pool.
In a classical noiseless group testing setup, it is assumed that the sampling
procedure is fully known to the reconstruction algorithm, in the sense that the
existence of a defective member in a pool results in the test outcome of that
pool to be positive. However, this may not be always a valid assumption in some
cases of interest. In particular, we consider the case where the defective
items in a pool can become independently inactive with a certain probability.
Hence, one may obtain a negative test result in a pool despite containing some
defective items. As a result, any sampling and reconstruction method should be
able to cope with two different types of uncertainty, i.e., the unknown set of
defective items and the partially unknown, probabilistic testing procedure.
In this work, motivated by the application of detecting infected people in
viral epidemics, we design non-adaptive sampling procedures that allow
successful identification of the defective items through a set of probabilistic
tests. Our design requires only a small number of tests to single out the
defective items. In particular, for a population of size and at most
defective items with activation probability , our results show that tests is sufficient if the sampling procedure should
work for all possible sets of defective items, while
tests is enough to be successful for any single set of defective items.
Moreover, we show that the defective members can be recovered using a simple
reconstruction algorithm with complexity of .Comment: Full version of the conference paper "Compressed Sensing with
Probabilistic Measurements: A Group Testing Solution" appearing in
proceedings of the 47th Annual Allerton Conference on Communication, Control,
and Computing, 2009 (arXiv:0909.3508). To appear in IEEE Transactions on
Information Theor
SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding
Scaffolding is an important subproblem in "de novo" genome assembly in which
mate pair data are used to construct a linear sequence of contigs separated by
gaps. Here we present SLIQ, a set of simple linear inequalities derived from
the geometry of contigs on the line that can be used to predict the relative
positions and orientations of contigs from individual mate pair reads and thus
produce a contig digraph. The SLIQ inequalities can also filter out unreliable
mate pairs and can be used as a preprocessing step for any scaffolding
algorithm. We tested the SLIQ inequalities on five real data sets ranging in
complexity from simple bacterial genomes to complex mammalian genomes and
compared the results to the majority voting procedure used by many other
scaffolding algorithms. SLIQ predicted the relative positions and orientations
of the contigs with high accuracy in all cases and gave more accurate position
predictions than majority voting for complex genomes, in particular the human
genome. Finally, we present a simple scaffolding algorithm that produces linear
scaffolds given a contig digraph. We show that our algorithm is very efficient
compared to other scaffolding algorithms while maintaining high accuracy in
predicting both contig positions and orientations for real data sets.Comment: 16 pages, 6 figures, 7 table
Multiple Fault Isolation in Redundant Systems
Fault diagnosis in large-scale systems that are products of modern technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption
Multiple Fault Isolation in Redundant Systems
Fault diagnosis in large-scale systems that are products of modem technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption
Computationally Tractable Algorithms for Finding a Subset of Non-defective Items from a Large Population
In the classical non-adaptive group testing setup, pools of items are tested
together, and the main goal of a recovery algorithm is to identify the
"complete defective set" given the outcomes of different group tests. In
contrast, the main goal of a "non-defective subset recovery" algorithm is to
identify a "subset" of non-defective items given the test outcomes. In this
paper, we present a suite of computationally efficient and analytically
tractable non-defective subset recovery algorithms. By analyzing the
probability of error of the algorithms, we obtain bounds on the number of tests
required for non-defective subset recovery with arbitrarily small probability
of error. Our analysis accounts for the impact of both the additive noise
(false positives) and dilution noise (false negatives). By comparing with the
information theoretic lower bounds, we show that the upper bounds on the number
of tests are order-wise tight up to a factor, where is the number
of defective items. We also provide simulation results that compare the
relative performance of the different algorithms and provide further insights
into their practical utility. The proposed algorithms significantly outperform
the straightforward approaches of testing items one-by-one, and of first
identifying the defective set and then choosing the non-defective items from
the complement set, in terms of the number of measurements required to ensure a
given success rate.Comment: In this revision: Unified some proofs and reorganized the paper,
corrected a small mistake in one of the proofs, added more reference
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