23,413 research outputs found
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Process
This paper develops a unified, accurate and computationally efficient method
for change-point inference in non-stationary spatio-temporal processes. By
modeling a non-stationary spatio-temporal process as a piecewise stationary
spatio-temporal process, we consider simultaneous estimation of the number and
locations of change-points, and model parameters in each segment. A composite
likelihood-based criterion is developed for change-point and parameters
estimation. Asymptotic theories including consistency and distribution of the
estimators are derived under mild conditions. In contrast to classical results
in fixed dimensional time series that the asymptotic error of change-point
estimator is , exact recovery of true change-points is guaranteed in
the spatio-temporal setting. More surprisingly, the consistency of change-point
estimation can be achieved without any penalty term in the criterion function.
A computational efficient pruned dynamic programming algorithm is developed for
the challenging criterion optimization problem. Simulation studies and an
application to U.S. precipitation data are provided to demonstrate the
effectiveness and practicality of the proposed method
Algorithm Diversity for Resilient Systems
Diversity can significantly increase the resilience of systems, by reducing
the prevalence of shared vulnerabilities and making vulnerabilities harder to
exploit. Work on software diversity for security typically creates variants of
a program using low-level code transformations. This paper is the first to
study algorithm diversity for resilience. We first describe how a method based
on high-level invariants and systematic incrementalization can be used to
create algorithm variants. Executing multiple variants in parallel and
comparing their outputs provides greater resilience than executing one variant.
To prevent different parallel schedules from causing variants' behaviors to
diverge, we present a synchronized execution algorithm for DistAlgo, an
extension of Python for high-level, precise, executable specifications of
distributed algorithms. We propose static and dynamic metrics for measuring
diversity. An experimental evaluation of algorithm diversity combined with
implementation-level diversity for several sequential algorithms and
distributed algorithms shows the benefits of algorithm diversity
High efficiency realization for a wide-coverage unification grammar
We give a detailed account of an algorithm for efficient tactical generation from underspecified logical-form semantics, using a wide-coverage grammar and a corpus of real-world target utterances. Some earlier claims about chart realization are critically reviewed and corrected in the light of a series of practical experiments. As well as a set of algorithmic refinements, we present two novel techniques: the integration of subsumption-based local ambiguity factoring, and a procedure to selectively unpack the generation forest according to a probability distribution given by a conditional, discriminative model
- …