1,052 research outputs found
Pandemic Influenza: Ethics, Law, and the Public\u27s Health
Highly pathogenic Influenza (HPAI) has captured the close attention of policy makers who regard pandemic influenza as a national security threat. Although the prevalence is currently very low, recent evidence that the 1918 pandemic was caused by an avian influenza virus lends credence to the theory that current outbreaks could have pandemic potential. If the threat becomes a reality, massive loss of life and economic disruption would ensue. Therapeutic countermeasures (e.g., vaccines and antiviral medications) and public health interventions (e.g., infection control, social separation, and quarantine) form the two principal strategies for prevention and response, both of which present formidable legal and ethical challenges that have yet to receive sufficient attention. In part II, we examine the major medical countermeasures being being considered as an intervention for an influenza pandemic. In this section, we will evaluate the known effectiveness of these interventions and analyze the ethical claims relating to distributive justice in the allocation of scarce resources. In part III, we will discuss public health interventions, exploring the hard tradeoffs between population health on the one hand and personal (e.g., autonomy, privacy, and liberty) and economic (e.g., trade, tourism, and business) interests on the other. This section will focus on the ethical and human rights issues inherent in population-based interventions. Pandemics can be deeply socially divisive, and the political response to these issues not only impacts public health preparedness, but also reflects profoundly on the kind of society we aspire to be
Weighted ancestors in suffix trees
The classical, ubiquitous, predecessor problem is to construct a data
structure for a set of integers that supports fast predecessor queries. Its
generalization to weighted trees, a.k.a. the weighted ancestor problem, has
been extensively explored and successfully reduced to the predecessor problem.
It is known that any solution for both problems with an input set from a
polynomially bounded universe that preprocesses a weighted tree in O(n
polylog(n)) space requires \Omega(loglogn) query time. Perhaps the most
important and frequent application of the weighted ancestors problem is for
suffix trees. It has been a long-standing open question whether the weighted
ancestors problem has better bounds for suffix trees. We answer this question
positively: we show that a suffix tree built for a text w[1..n] can be
preprocessed using O(n) extra space, so that queries can be answered in O(1)
time. Thus we improve the running times of several applications. Our
improvement is based on a number of data structure tools and a
periodicity-based insight into the combinatorial structure of a suffix tree.Comment: 27 pages, LNCS format. A condensed version will appear in ESA 201
New Algorithms for Position Heaps
We present several results about position heaps, a relatively new alternative
to suffix trees and suffix arrays. First, we show that, if we limit the maximum
length of patterns to be sought, then we can also limit the height of the heap
and reduce the worst-case cost of insertions and deletions. Second, we show how
to build a position heap in linear time independent of the size of the
alphabet. Third, we show how to augment a position heap such that it supports
access to the corresponding suffix array, and vice versa. Fourth, we introduce
a variant of a position heap that can be simulated efficiently by a compressed
suffix array with a linear number of extra bits
Efficient Seeds Computation Revisited
The notion of the cover is a generalization of a period of a string, and
there are linear time algorithms for finding the shortest cover. The seed is a
more complicated generalization of periodicity, it is a cover of a superstring
of a given string, and the shortest seed problem is of much higher algorithmic
difficulty. The problem is not well understood, no linear time algorithm is
known. In the paper we give linear time algorithms for some of its versions ---
computing shortest left-seed array, longest left-seed array and checking for
seeds of a given length. The algorithm for the last problem is used to compute
the seed array of a string (i.e., the shortest seeds for all the prefixes of
the string) in time. We describe also a simpler alternative algorithm
computing efficiently the shortest seeds. As a by-product we obtain an
time algorithm checking if the shortest seed has length at
least and finding the corresponding seed. We also correct some important
details missing in the previously known shortest-seed algorithm (Iliopoulos et
al., 1996).Comment: 14 pages, accepted to CPM 201
Mathematical statistics functionally object model for monitoring and control
The paper chain is seen as a complex system that is subject to management. The complexity of the process of monitoring and control is caused mainly complicated objects. To describe the operation of the facility built its functional and static mathematical model that completely describes the state of the object. The functional and statistical models to determine the probabilistic characteristics of information and communication network as object management. The model allows direct determination of the probability of the phase-out of the facility
One-variable word equations in linear time
In this paper we consider word equations with one variable (and arbitrary
many appearances of it). A recent technique of recompression, which is
applicable to general word equations, is shown to be suitable also in this
case. While in general case it is non-deterministic, it determinises in case of
one variable and the obtained running time is O(n + #_X log n), where #_X is
the number of appearances of the variable in the equation. This matches the
previously-best algorithm due to D\k{a}browski and Plandowski. Then, using a
couple of heuristics as well as more detailed time analysis the running time is
lowered to O(n) in RAM model. Unfortunately no new properties of solutions are
shown.Comment: submitted to a journal, general overhaul over the previous versio
Cross-Document Pattern Matching
We study a new variant of the string matching problem called cross-document
string matching, which is the problem of indexing a collection of documents to
support an efficient search for a pattern in a selected document, where the
pattern itself is a substring of another document. Several variants of this
problem are considered, and efficient linear-space solutions are proposed with
query time bounds that either do not depend at all on the pattern size or
depend on it in a very limited way (doubly logarithmic). As a side result, we
propose an improved solution to the weighted level ancestor problem
Fast Label Extraction in the CDAWG
The compact directed acyclic word graph (CDAWG) of a string of length
takes space proportional just to the number of right extensions of the
maximal repeats of , and it is thus an appealing index for highly repetitive
datasets, like collections of genomes from similar species, in which grows
significantly more slowly than . We reduce from to
the time needed to count the number of occurrences of a pattern of
length , using an existing data structure that takes an amount of space
proportional to the size of the CDAWG. This implies a reduction from
to in the time needed to
locate all the occurrences of the pattern. We also reduce from
to the time needed to read the characters of the
label of an edge of the suffix tree of , and we reduce from
to the time needed to compute the matching
statistics between a query of length and , using an existing
representation of the suffix tree based on the CDAWG. All such improvements
derive from extracting the label of a vertex or of an arc of the CDAWG using a
straight-line program induced by the reversed CDAWG.Comment: 16 pages, 1 figure. In proceedings of the 24th International
Symposium on String Processing and Information Retrieval (SPIRE 2017). arXiv
admin note: text overlap with arXiv:1705.0864
Efficient LZ78 factorization of grammar compressed text
We present an efficient algorithm for computing the LZ78 factorization of a
text, where the text is represented as a straight line program (SLP), which is
a context free grammar in the Chomsky normal form that generates a single
string. Given an SLP of size representing a text of length , our
algorithm computes the LZ78 factorization of in time
and space, where is the number of resulting LZ78 factors.
We also show how to improve the algorithm so that the term in the
time and space complexities becomes either , where is the length of the
longest LZ78 factor, or where is a quantity
which depends on the amount of redundancy that the SLP captures with respect to
substrings of of a certain length. Since where
is the alphabet size, the latter is asymptotically at least as fast as
a linear time algorithm which runs on the uncompressed string when is
constant, and can be more efficient when the text is compressible, i.e. when
and are small.Comment: SPIRE 201
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