6,875 research outputs found
Regularity Preserving but not Reflecting Encodings
Encodings, that is, injective functions from words to words, have been
studied extensively in several settings. In computability theory the notion of
encoding is crucial for defining computability on arbitrary domains, as well as
for comparing the power of models of computation. In language theory much
attention has been devoted to regularity preserving functions.
A natural question arising in these contexts is: Is there a bijective
encoding such that its image function preserves regularity of languages, but
its pre-image function does not? Our main result answers this question in the
affirmative: For every countable class C of languages there exists a bijective
encoding f such that for every language L in C its image f[L] is regular.
Our construction of such encodings has several noteworthy consequences.
Firstly, anomalies arise when models of computation are compared with respect
to a known concept of implementation that is based on encodings which are not
required to be computable: Every countable decision model can be implemented,
in this sense, by finite-state automata, even via bijective encodings. Hence
deterministic finite-state automata would be equally powerful as Turing machine
deciders.
A second consequence concerns the recognizability of sets of natural numbers
via number representations and finite automata. A set of numbers is said to be
recognizable with respect to a representation if an automaton accepts the
language of representations. Our result entails that there is one number
representation with respect to which every recursive set is recognizable
An extensive English language bibliography on graph theory and its applications
Bibliography on graph theory and its application
Statistics of self-avoiding walks on randomly diluted lattice
A comprehensive numerical study of self-avoiding walks (SAW's) on randomly
diluted lattices in two and three dimensions is carried out. The critical
exponents and are calculated for various different occupation
probabilities, disorder configuration ensembles, and walk weighting schemes.
These results are analyzed and compared with those previously available.
Various subtleties in the calculation and definition of these exponents are
discussed. Precise numerical values are given for these exponents in most
cases, and many new properties are recognized for them.Comment: 34 pages (+ 12 figures), REVTEX 3.
On the combination of argumentation solvers into parallel portfolios
In the light of the increasing interest in efficient algorithms for solving abstract argumentation problems and the pervasive availability of multicore machines, a natural research issue is to combine existing argumentation solvers into parallel portfolios. In this work, we introduce six methodologies for the automatic configuration of parallel portfolios of argumentation solvers for enumerating the preferred extensions of a given framework. In particular, four methodologies aim at combining solvers in static portfolios, while two methodologies are designed for the dynamic configuration of parallel portfolios. Our empirical results demonstrate that the configuration of parallel portfolios is a fruitful way for exploiting multicore machines, and that the presented approaches outperform the state of the art of parallel argumentation solvers
Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems
The first-ever Ukraine cyberattack on power grid has proven its devastation
by hacking into their critical cyber assets. With administrative privileges
accessing substation networks/local control centers, one intelligent way of
coordinated cyberattacks is to execute a series of disruptive switching
executions on multiple substations using compromised supervisory control and
data acquisition (SCADA) systems. These actions can cause significant impacts
to an interconnected power grid. Unlike the previous power blackouts, such
high-impact initiating events can aggravate operating conditions, initiating
instability that may lead to system-wide cascading failure. A systemic
evaluation of "nightmare" scenarios is highly desirable for asset owners to
manage and prioritize the maintenance and investment in protecting their
cyberinfrastructure. This survey paper is a conceptual expansion of real-time
monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework
that emphasizes on the resulting impacts, both on steady-state and dynamic
aspects of power system stability. Hypothetically, we associate the
combinatorial analyses of steady state on substations/components outages and
dynamics of the sequential switching orders as part of the permutation. The
expanded framework includes (1) critical/noncritical combination verification,
(2) cascade confirmation, and (3) combination re-evaluation. This paper ends
with a discussion of the open issues for metrics and future design pertaining
the impact quantification of cyber-related contingencies
GLB: Lifeline-based Global Load Balancing library in X10
We present GLB, a programming model and an associated implementation that can
handle a wide range of irregular paral- lel programming problems running over
large-scale distributed systems. GLB is applicable both to problems that are
easily load-balanced via static scheduling and to problems that are hard to
statically load balance. GLB hides the intricate syn- chronizations (e.g.,
inter-node communication, initialization and startup, load balancing,
termination and result collection) from the users. GLB internally uses a
version of the lifeline graph based work-stealing algorithm proposed by
Saraswat et al. Users of GLB are simply required to write several pieces of
sequential code that comply with the GLB interface. GLB then schedules and
orchestrates the parallel execution of the code correctly and efficiently at
scale. We have applied GLB to two representative benchmarks: Betweenness
Centrality (BC) and Unbalanced Tree Search (UTS). Among them, BC can be
statically load-balanced whereas UTS cannot. In either case, GLB scales well--
achieving nearly linear speedup on different computer architectures (Power,
Blue Gene/Q, and K) -- up to 16K cores
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