9,744 research outputs found
Distributed execution of bigraphical reactive systems
The bigraph embedding problem is crucial for many results and tools about
bigraphs and bigraphical reactive systems (BRS). Current algorithms for
computing bigraphical embeddings are centralized, i.e. designed to run locally
with a complete view of the guest and host bigraphs. In order to deal with
large bigraphs, and to parallelize reactions, we present a decentralized
algorithm, which distributes both state and computation over several concurrent
processes. This allows for distributed, parallel simulations where
non-interfering reactions can be carried out concurrently; nevertheless, even
in the worst case the complexity of this distributed algorithm is no worse than
that of a centralized algorithm
Guest Editorial: Nonlinear Optimization of Communication Systems
Linear programming and other classical optimization techniques have found important applications in communication systems for many decades. Recently, there has been a surge in research activities that utilize the latest developments in nonlinear optimization to tackle a much wider scope of work in the analysis and design of communication systems. These activities involve every “layer” of the protocol stack and the principles of layered network architecture itself, and have made intellectual and practical impacts significantly beyond the established frameworks of optimization of communication systems in the early 1990s. These recent results are driven by new demands in the areas of communications and networking, as well as new tools emerging from optimization theory. Such tools include the powerful theories and highly efficient computational algorithms for nonlinear convex optimization, together with global solution methods and relaxation techniques for nonconvex optimization
Profiling a decade of information systems frontiers’ research
This article analyses the first ten years of research published in the Information Systems Frontiers (ISF) from 1999 to 2008. The analysis of the published material includes examining variables such as most productive authors, citation analysis, universities associated with the most publications, geographic diversity, authors’ backgrounds and research methods. The keyword analysis suggests that ISF research has evolved from establishing concepts and domain of information systems (IS), technology and management to contemporary issues such as outsourcing, web services and security. The analysis presented in this paper has identified intellectually significant studies that have contributed to the development and accumulation of intellectual wealth of ISF. The analysis has also identified authors published in other journals whose work largely shaped and guided the researchers published in ISF. This research has implications for researchers, journal editors, and research institutions
Feedforward data-aided phase noise estimation from a DCT basis expansion
This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of discrete cosine transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise independent contribution, that results front the phase noise modeling error. We investigate the effect of the symbol sequence length, the pilot symbol positions, the number of pilot symbols, and the number of estimated DCT coefficients it the estimation accuracy and on the corresponding bit error rate (PER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot Symbols, providing a considerable Performance improvement as compared to other pilot symbol configurations. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase. Copyright (C) 2009 J. Bhatti and M. Moeneclaey
A Revised Publication Model for ECML PKDD
ECML PKDD is the main European conference on machine learning and data
mining. Since its foundation it implemented the publication model common in
computer science: there was one conference deadline; conference submissions
were reviewed by a program committee; papers were accepted with a low
acceptance rate. Proceedings were published in several Springer Lecture Notes
in Artificial (LNAI) volumes, while selected papers were invited to special
issues of the Machine Learning and Data Mining and Knowledge Discovery
journals. In recent years, this model has however come under stress. Problems
include: reviews are of highly variable quality; the purpose of bringing the
community together is lost; reviewing workloads are high; the information
content of conferences and journals decreases; there is confusion among
scientists in interdisciplinary contexts. In this paper, we present a new
publication model, which will be adopted for the ECML PKDD 2013 conference, and
aims to solve some of the problems of the traditional model. The key feature of
this model is the creation of a journal track, which is open to submissions all
year long and allows for revision cycles.Comment: 13 page
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