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0803.1025
|
Asymptotic Concentration Behaviors of Linear Combinations of Weight
Distributions on Random Linear Code Ensemble
|
cs.IT math.IT
|
Asymptotic concentration behaviors of linear combinations of weight
distributions on the random linear code ensemble are presented. Many important
properties of a binary linear code can be expressed as the form of a linear
combination of weight distributions such as number of codewords, undetected
error probability and upper bound on the maximum likelihood error probability.
The key in this analysis is the covariance formula of weight distributions of
the random linear code ensemble, which reveals the second-order statistics of a
linear function of the weight distributions. Based on the covariance formula,
several expressions of the asymptotic concentration rate, which indicate the
speed of convergence to the average, are derived.
|
0803.1087
|
The Future of Scientific Simulations: from Artificial Life to Artificial
Cosmogenesis
|
cs.AI
|
This philosophical paper explores the relation between modern scientific
simulations and the future of the universe. We argue that a simulation of an
entire universe will result from future scientific activity. This requires us
to tackle the challenge of simulating open-ended evolution at all levels in a
single simulation. The simulation should encompass not only biological
evolution, but also physical evolution (a level below) and cultural evolution
(a level above). The simulation would allow us to probe what would happen if we
would "replay the tape of the universe" with the same or different laws and
initial conditions. We also distinguish between real-world and artificial-world
modelling. Assuming that intelligent life could indeed simulate an entire
universe, this leads to two tentative hypotheses. Some authors have argued that
we may already be in a simulation run by an intelligent entity. Or, if such a
simulation could be made real, this would lead to the production of a new
universe. This last direction is argued with a careful speculative
philosophical approach, emphasizing the imperative to find a solution to the
heat death problem in cosmology. The reader is invited to consult Annex 1 for
an overview of the logical structure of this paper. -- Keywords: far future,
future of science, ALife, simulation, realization, cosmology, heat death,
fine-tuning, physical eschatology, cosmological natural selection, cosmological
artificial selection, artificial cosmogenesis, selfish biocosm hypothesis,
meduso-anthropic principle, developmental singularity hypothesis, role of
intelligent life.
|
0803.1090
|
Self-Corrected Min-Sum decoding of LDPC codes
|
cs.IT math.IT
|
In this paper we propose a very simple but powerful self-correction method
for the Min-Sum decoding of LPDC codes. Unlike other correction methods known
in the literature, our method does not try to correct the check node processing
approximation, but it modifies the variable node processing by erasing
unreliable messages. However, this positively affects check node messages,
which become symmetric Gaussian distributed, and we show that this is
sufficient to ensure a quasi-optimal decoding performance. Monte-Carlo
simulations show that the proposed Self-Corrected Min-Sum decoding performs
very close to the Sum-Product decoding, while preserving the main features of
the Min-Sum decoding, that is low complexity and independence with respect to
noise variance estimation errors.
|
0803.1094
|
Min-Max decoding for non binary LDPC codes
|
cs.IT math.IT
|
Iterative decoding of non-binary LDPC codes is currently performed using
either the Sum-Product or the Min-Sum algorithms or slightly different versions
of them. In this paper, several low-complexity quasi-optimal iterative
algorithms are proposed for decoding non-binary codes. The Min-Max algorithm is
one of them and it has the benefit of two possible LLR domain implementations:
a standard implementation, whose complexity scales as the square of the Galois
field's cardinality and a reduced complexity implementation called selective
implementation, which makes the Min-Max decoding very attractive for practical
purposes.
|
0803.1096
|
Algebraic-geometric codes from vector bundles and their decoding
|
cs.IT math.IT
|
Algebraic-geometric codes can be constructed by evaluating a certain set of
functions on a set of distinct rational points of an algebraic curve. The set
of functions that are evaluated is the linear space of a given divisor or,
equivalently, the set of section of a given line bundle. Using arbitrary rank
vector bundles on algebraic curves, we propose a natural generalization of the
above construction. Our codes can also be seen as interleaved versions of
classical algebraic-geometric codes. We show that the algorithm of Brown,
Minder and Shokrollahi can be extended to this new class of codes and it
corrects any number of errors up to $t^{*} - g/2$, where $t^{*}$ is the
designed correction capacity of the code and $g$ is the curve genus.
|
0803.1120
|
The Rate Loss of Single-Letter Characterization: The "Dirty" Multiple
Access Channel
|
cs.IT math.IT
|
For general memoryless systems, the typical information theoretic solution -
when exists - has a "single-letter" form. This reflects the fact that optimum
performance can be approached by a random code (or a random binning scheme),
generated using independent and identically distributed copies of some
single-letter distribution. Is that the form of the solution of any
(information theoretic) problem? In fact, some counter examples are known. The
most famous is the "two help one" problem: Korner and Marton showed that if we
want to decode the modulo-two sum of two binary sources from their independent
encodings, then linear coding is better than random coding. In this paper we
provide another counter example, the "doubly-dirty" multiple access channel
(MAC). Like the Korner-Marton problem, this is a multi-terminal scenario where
side information is distributed among several terminals; each transmitter knows
part of the channel interference but the receiver is not aware of any part of
it. We give an explicit solution for the capacity region of a binary version of
the doubly-dirty MAC, demonstrate how the capacity region can be approached
using a linear coding scheme, and prove that the "best known single-letter
region" is strictly contained in it. We also state a conjecture regarding a
similar rate loss of single letter characterization in the Gaussian case.
|
0803.1144
|
Asymptotic Capacity and Optimal Precoding Strategy of Multi-Level
Precode & Forward in Correlated Channels
|
cs.IT math.IT
|
We analyze a multi-level MIMO relaying system where a multiple-antenna
transmitter sends data to a multipleantenna receiver through several relay
levels, also equipped with multiple antennas. Assuming correlated fading in
each hop, each relay receives a faded version of the signal transmitted by the
previous level, performs precoding on the received signal and retransmits it to
the next level. Using free probability theory and assuming that the noise power
at the relay levels - but not at the receiver - is negligible, a closed-form
expression of the end-to-end asymptotic instantaneous mutual information is
derived as the number of antennas in all levels grow large with the same rate.
This asymptotic expression is shown to be independent from the channel
realizations, to only depend on the channel statistics and to also serve as the
asymptotic value of the end-to-end average mutual information. We also provide
the optimal singular vectors of the precoding matrices that maximize the
asymptotic mutual information : the optimal transmit directions represented by
the singular vectors of the precoding matrices are aligned on the eigenvectors
of the channel correlation matrices, therefore they can be determined only
using the known statistics of the channel matrices and do not depend on a
particular channel realization.
|
0803.1195
|
Secure Lossless Compression with Side Information
|
cs.IT math.IT
|
Secure data compression in the presence of side information at both a
legitimate receiver and an eavesdropper is explored. A noise-free, limited rate
link between the source and the receiver, whose output can be perfectly
observed by the eavesdropper, is assumed. As opposed to the wiretap channel
model, in which secure communication can be established by exploiting the noise
in the channel, here the existence of side information at the receiver is used.
Both coded and uncoded side information are considered. In the coded side
information scenario, inner and outer bounds on the compression-equivocation
rate region are given. In the uncoded side information scenario, the
availability of the legitimate receiver's and the eavesdropper's side
information at the encoder is considered, and the compression-equivocation rate
region is characterized for these cases. It is shown that the side information
at the encoder can increase the equivocation rate at the eavesdropper. Hence,
the side information at the encoder is shown to be useful in terms of security;
this is in contrast with the pure lossless data compression case where side
information at the encoder would not help.
|
0803.1207
|
Serious Flaws in Korf et al.'s Analysis on Time Complexity of A*
|
cs.AI
|
This paper has been withdrawn.
|
0803.1221
|
Non-Singular Assembly-mode Changing Motions for 3-RPR Parallel
Manipulators
|
cs.RO physics.class-ph
|
When moving from one arbitrary location at another, a parallel manipulator
may change its assembly-mode without crossing a singularity. Because the
non-singular change of assembly-mode cannot be simply detected, the actual
assembly-mode during motion is difficult to track. This paper proposes a global
explanatory approach to help better understand non-singular assembly-mode
changing motions for 3-RPR planar parallel manipulators. The approach consists
in fixing one of the actuated joints and analyzing the configuration-space as a
surface in a 3-dimensional space. Such a global description makes it possible
to display all possible non-singular assembly-mode changing trajectories.
|
0803.1227
|
Linear programming bounds for unitary space time codes
|
cs.IT math.IT
|
The linear programming method is applied to the space $\U_n(\C)$ of unitary
matrices in order to obtain bounds for codes relative to the diversity sum and
the diversity product. Theoretical and numerical results improving previously
known bounds are derived.
|
0803.1323
|
A Game Theoretic Framework for Decentralized Power Allocation in IDMA
Systems
|
cs.IT cs.GT math.IT
|
In this contribution we present a decentralized power allocation algorithm
for the uplink interleave division multiple access (IDMA) channel. Within the
proposed optimal strategy for power allocation, each user aims at selfishly
maximizing its own utility function. An iterative chip by chip (CBC) decoder at
the receiver and a rational selfish behavior of all the users according to a
classical game-theoretical framework are the underlying assumptions of this
work. This approach leads to a power allocation based on a channel inversion
policy where the optimal power level is set locally at each terminal based on
the knowledge of its own channel realization, the noise level at the receiver
and the number of active users in the network.
|
0803.1443
|
Lexical growth, entropy and the benefits of networking
|
cs.IT math.IT q-bio.QM
|
If each node of an idealized network has an equal capacity to efficiently
exchange benefits, then the network's capacity to use energy is scaled by the
average amount of energy required to connect any two of its nodes. The scaling
factor equals \textit{e}, and the network's entropy is $\ln(n)$. Networking
emerges in consequence of nodes minimizing the ratio of their energy use to the
benefits obtained for such use, and their connectability. Networking leads to
nested hierarchical clustering, which multiplies a network's capacity to use
its energy to benefit its nodes. Network entropy multiplies a node's capacity.
For a real network in which the nodes have the capacity to exchange benefits,
network entropy may be estimated as $C \log_L(n)$, where the base of the log is
the path length $L$, and $C$ is the clustering coefficient. Since $n$, $L$ and
$C$ can be calculated for real networks, network entropy for real networks can
be calculated and can reveal aspects of emergence and also of economic,
biological, conceptual and other networks, such as the relationship between
rates of lexical growth and divergence, and the economic benefit of adding
customers to a commercial communications network. \textit{Entropy dating} can
help estimate the age of network processes, such as the growth of hierarchical
society and of language.
|
0803.1445
|
Distributed Joint Source-Channel Coding on a Multiple Access Channel
with Side Information
|
cs.IT math.IT
|
We consider the problem of transmission of several distributed sources over a
multiple access channel (MAC) with side information at the sources and the
decoder. Source-channel separation does not hold for this channel. Sufficient
conditions are provided for transmission of sources with a given distortion.
The source and/or the channel could have continuous alphabets (thus Gaussian
sources and Gaussian MACs are special cases). Various previous results are
obtained as special cases. We also provide several good joint source-channel
coding schemes for a discrete/continuous source and discrete/continuous
alphabet channel. Channels with feedback and fading are also considered.
Keywords: Multiple access channel, side information, lossy joint
source-channel coding, channels with feedback, fading channels.
|
0803.1454
|
Tight Bounds on the Capacity of Binary Input random CDMA Systems
|
cs.IT math.IT
|
We consider multiple access communication on a binary input additive white
Gaussian noise channel using randomly spread code division. For a general class
of symmetric distributions for spreading coefficients, in the limit of a large
number of users, we prove an upper bound on the capacity, which matches a
formula that Tanaka obtained by using the replica method. We also show
concentration of various relevant quantities including mutual information,
capacity and free energy. The mathematical methods are quite general and allow
us to discuss extensions to other multiuser scenarios.
|
0803.1457
|
Hybrid Reasoning and the Future of Iconic Representations
|
cs.AI cs.LO
|
We give a brief overview of the main characteristics of diagrammatic
reasoning, analyze a case of human reasoning in a mastermind game, and explain
why hybrid representation systems (HRS) are particularly attractive and
promising for Artificial General Intelligence and Computer Science in general.
|
0803.1511
|
The Capacity Region of the Degraded Finite-State Broadcast Channel
|
cs.IT math.IT
|
We consider the discrete, time-varying broadcast channel with memory under
the assumption that the channel states belong to a set of finite cardinality.
We first define the physically degraded finite-state broadcast channel for
which we derive the capacity region. We then define the stochastically degraded
finite-state broadcast channel and derive the capacity region for this scenario
as well. In both scenarios we consider the non-indecomposable finite-state
channel as well as the indecomposable one.
|
0803.1555
|
Privacy Preserving ID3 over Horizontally, Vertically and Grid
Partitioned Data
|
cs.DB cs.LG
|
We consider privacy preserving decision tree induction via ID3 in the case
where the training data is horizontally or vertically distributed. Furthermore,
we consider the same problem in the case where the data is both horizontally
and vertically distributed, a situation we refer to as grid partitioned data.
We give an algorithm for privacy preserving ID3 over horizontally partitioned
data involving more than two parties. For grid partitioned data, we discuss two
different evaluation methods for preserving privacy ID3, namely, first merging
horizontally and developing vertically or first merging vertically and next
developing horizontally. Next to introducing privacy preserving data mining
over grid-partitioned data, the main contribution of this paper is that we
show, by means of a complexity analysis that the former evaluation method is
the more efficient.
|
0803.1568
|
Dempster-Shafer for Anomaly Detection
|
cs.NE cs.AI cs.CR
|
In this paper, we implement an anomaly detection system using the
Dempster-Shafer method. Using two standard benchmark problems we show that by
combining multiple signals it is possible to achieve better results than by
using a single signal. We further show that by applying this approach to a
real-world email dataset the algorithm works for email worm detection.
Dempster-Shafer can be a promising method for anomaly detection problems with
multiple features (data sources), and two or more classes.
|
0803.1576
|
Simulation Optimization of the Crossdock Door Assignment Problem
|
cs.NE cs.CE
|
The purpose of this report is to present the Crossdock Door Assignment
Problem, which involves assigning destinations to outbound dock doors of
Crossdock centres such that travel distance by material handling equipment is
minimized. We propose a two fold solution; simulation and optimization of the
simulation model simulation optimization. The novel aspect of our solution
approach is that we intend to use simulation to derive a more realistic
objective function and use Memetic algorithms to find an optimal solution. The
main advantage of using Memetic algorithms is that it combines a local search
with Genetic Algorithms. The Crossdock Door Assignment Problem is a new domain
application to Memetic Algorithms and it is yet unknown how it will perform.
|
0803.1586
|
Spatio-activity based object detection
|
cs.CV
|
We present the SAMMI lightweight object detection method which has a high
level of accuracy and robustness, and which is able to operate in an
environment with a large number of cameras. Background modeling is based on DCT
coefficients provided by cameras. Foreground detection uses similarity in
temporal characteristics of adjacent blocks of pixels, which is a
computationally inexpensive way to make use of object coherence. Scene model
updating uses the approximated median method for improved performance.
Evaluation at pixel level and application level shows that SAMMI object
detection performs better and faster than the conventional Mixture of Gaussians
method.
|
0803.1596
|
Using Intelligent Agents to understand organisational behaviour
|
cs.NE cs.MA
|
This paper introduces two ongoing research projects which seek to apply
computer modelling techniques in order to simulate human behaviour within
organisations. Previous research in other disciplines has suggested that
complex social behaviours are governed by relatively simple rules which, when
identified, can be used to accurately model such processes using computer
technology. The broad objective of our research is to develop a similar
capability within organisational psychology.
|
0803.1598
|
A Multi-Agent Simulation of Retail Management Practices
|
cs.NE
|
We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of
problems in a retail context. Specifically, we are working to understand the
relationship between human resource management practices and retail
productivity. Despite the fact we are working within a relatively novel and
complex domain, it is clear that intelligent agents do offer potential for
developing organizational capabilities in the future. Our multi-disciplinary
research team has worked with a UK department store to collect data and capture
perceptions about operations from actors within departments. Based on this case
study work, we have built a simulator that we present in this paper. We then
use the simulator to gather empirical evidence regarding two specific
management practices: empowerment and employee development.
|
0803.1600
|
Understanding Retail Productivity by Simulating Management Practise
|
cs.NE
|
Intelligent agents offer a new and exciting way of understanding the world of
work. In this paper we apply agent-based modeling and simulation to investigate
a set of problems in a retail context. Specifically, we are working to
understand the relationship between human resource management practices and
retail productivity. Despite the fact we are working within a relatively novel
and complex domain, it is clear that intelligent agents could offer potential
for fostering sustainable organizational capabilities in the future. Our
research so far has led us to conduct case study work with a top ten UK
retailer, collecting data in four departments in two stores. Based on our case
study data we have built and tested a first version of a department store
simulator. In this paper we will report on the current development of our
simulator which includes new features concerning more realistic data on the
pattern of footfall during the day and the week, a more differentiated view of
customers, and the evolution of customers over time. This allows us to
investigate more complex scenarios and to analyze the impact of various
management practices.
|
0803.1604
|
Using Intelligent Agents to Understand Management Practices and Retail
Productivity
|
cs.NE cs.CE cs.MA
|
Intelligent agents offer a new and exciting way of understanding the world of
work. In this paper we apply agent-based modeling and simulation to investigate
a set of problems in a retail context. Specifically, we are working to
understand the relationship between human resource management practices and
retail productivity. Despite the fact we are working within a relatively novel
and complex domain, it is clear that intelligent agents could offer potential
for fostering sustainable organizational capabilities in the future. The
project is still at an early stage. So far we have conducted a case study in a
UK department store to collect data and capture impressions about operations
and actors within departments. Furthermore, based on our case study we have
built and tested our first version of a retail branch simulator which we will
present in this paper.
|
0803.1621
|
An Agent-Based Simulation of In-Store Customer Experiences
|
cs.NE cs.CE cs.MA
|
Agent-based modelling and simulation offers a new and exciting way of
understanding the world of work. In this paper we describe the development of
an agent-based simulation model, designed to help to understand the
relationship between human resource management practices and retail
productivity. We report on the current development of our simulation model
which includes new features concerning the evolution of customers over time. To
test some of these features we have conducted a series of experiments dealing
with customer pool sizes, standard and noise reduction modes, and the spread of
the word of mouth. Our multi-disciplinary research team draws upon expertise
from work psychologists and computer scientists. Despite the fact we are
working within a relatively novel and complex domain, it is clear that
intelligent agents offer potential for fostering sustainable organisational
capabilities in the future.
|
0803.1626
|
Genetic-Algorithm Seeding Of Idiotypic Networks For Mobile-Robot
Navigation
|
cs.NE cs.RO
|
Robot-control designers have begun to exploit the properties of the human
immune system in order to produce dynamic systems that can adapt to complex,
varying, real-world tasks. Jernes idiotypic-network theory has proved the most
popular artificial-immune-system (AIS) method for incorporation into
behaviour-based robotics, since idiotypic selection produces highly adaptive
responses. However, previous efforts have mostly focused on evolving the
network connections and have often worked with a single, pre-engineered set of
behaviours, limiting variability. This paper describes a method for encoding
behaviours as a variable set of attributes, and shows that when the encoding is
used with a genetic algorithm (GA), multiple sets of diverse behaviours can
develop naturally and rapidly, providing much greater scope for flexible
behaviour-selection. The algorithm is tested extensively with a simulated
e-puck robot that navigates around a maze by tracking colour. Results show that
highly successful behaviour sets can be generated within about 25 minutes, and
that much greater diversity can be obtained when multiple autonomous
populations are used, rather than a single one.
|
0803.1695
|
Use of self-correlation metrics for evaluation of information properties
of binary strings
|
cs.IT math.IT
|
It is demonstrated that appropriately chosen computable metrics based on
self-correlation properties provide a degree of determinism sufficient to
segregate binary strings by level of information content.
|
0803.1716
|
Citation Counting, Citation Ranking, and h-Index of Human-Computer
Interaction Researchers: A Comparison between Scopus and Web of Science
|
cs.HC cs.IR
|
This study examines the differences between Scopus and Web of Science in the
citation counting, citation ranking, and h-index of 22 top human-computer
interaction (HCI) researchers from EQUATOR--a large British Interdisciplinary
Research Collaboration project. Results indicate that Scopus provides
significantly more coverage of HCI literature than Web of Science, primarily
due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings.
No significant differences exist between the two databases if citations in
journals only are compared. Although broader coverage of the literature does
not significantly alter the relative citation ranking of individual
researchers, Scopus helps distinguish between the researchers in a more nuanced
fashion than Web of Science in both citation counting and h-index. Scopus also
generates significantly different maps of citation networks of individual
scholars than those generated by Web of Science. The study also presents a
comparison of h-index scores based on Google Scholar with those based on the
union of Scopus and Web of Science. The study concludes that Scopus can be used
as a sole data source for citation-based research and evaluation in HCI,
especially if citations in conference proceedings are sought and that h scores
should be manually calculated instead of relying on system calculations.
|
0803.1728
|
Investigating a Hybrid Metaheuristic For Job Shop Rescheduling
|
cs.NE cs.CE
|
Previous research has shown that artificial immune systems can be used to
produce robust schedules in a manufacturing environment. The main goal is to
develop building blocks (antibodies) of partial schedules that can be used to
construct backup solutions (antigens) when disturbances occur during
production. The building blocks are created based upon underpinning ideas from
artificial immune systems and evolved using a genetic algorithm (Phase I). Each
partial schedule (antibody) is assigned a fitness value and the best partial
schedules are selected to be converted into complete schedules (antigens). We
further investigate whether simulated annealing and the great deluge algorithm
can improve the results when hybridised with our artificial immune system
(Phase II). We use ten fixed solutions as our target and measure how well we
cover these specific scenarios.
|
0803.1733
|
Degrees of Freedom of the MIMO Interference Channel with Cooperation and
Cognition
|
cs.IT math.IT
|
In this paper, we explore the benefits, in the sense of total (sum rate)
degrees of freedom (DOF), of cooperation and cognitive message sharing for a
two-user multiple-input-multiple-output (MIMO) Gaussian interference channel
with $M_1$, $M_2$ antennas at transmitters and $N_1$, $N_2$ antennas at
receivers. For the case of cooperation (including cooperation at transmitters
only, at receivers only, and at transmitters as well as receivers), the DOF is
$\min \{M_1+M_2, N_1+N_2, \max(M_1, N_2)), \max(M_2, N_1)\}$, which is the same
as the DOF of the channel without cooperation. For the case of cognitive
message sharing, the DOF is $\min \{M_1+M_2, N_1+N_2, (1-1_{T2})((1-1_{R2})
\max(M_1, N_2) + 1_{R2} (M_1+N_2)), (1-1_{T1})((1-1_{R1}) \max(M_2, N_1) +
1_{R1} (M_2+N_1)) \}$ where $1_{Ti} = 1$ $(0)$ when transmitter $i$ is (is not)
a cognitive transmitter and $1_{Ri}$ is defined in the same fashion. Our
results show that while both techniques may increase the sum rate capacity of
the MIMO interference channel, only cognitive message sharing can increase the
DOF. We also find that it may be more beneficial for a user to have a cognitive
transmitter than to have a cognitive receiver.
|
0803.1807
|
Minimum-Delay Decoding of Turbo-Codes for Upper-Layer FEC
|
cs.IT math.IT
|
In this paper we investigate the decoding of parallel turbo codes over the
binary erasure channel suited for upper-layer error correction. The proposed
algorithm performs on-the-fly decoding, i.e. it starts decoding as soon as the
first symbols are received. This algorithm compares with the iterative decoding
of codes defined on graphs, in that it propagates in the trellises of the turbo
code by removing transitions in the same way edges are removed in a bipartite
graph under message-passing decoding. Performance comparison with LDPC codes
for different coding rates is shown.
|
0803.1926
|
Improved evolutionary generation of XSLT stylesheets
|
cs.NE cs.AI
|
This paper introduces a procedure based on genetic programming to evolve XSLT
programs (usually called stylesheets or logicsheets). XSLT is a general
purpose, document-oriented functional language, generally used to transform XML
documents (or, in general, solve any problem that can be coded as an XML
document). The proposed solution uses a tree representation for the stylesheets
as well as diverse specific operators in order to obtain, in the studied cases
and a reasonable time, a XSLT stylesheet that performs the transformation.
Several types of representation have been compared, resulting in different
performance and degree of success.
|
0803.1945
|
Resampling and requantization of band-limited Gaussian stochastic
signals with flat power spectrum
|
cs.IT math.IT
|
A theoretical analysis, aimed at characterizing the degradation induced by
the resampling and requantization processes applied to band-limited Gaussian
signals with flat power spectrum, available through their digitized samples, is
presented. The analysis provides an efficient algorithm for computing the
complete {joint} bivariate discrete probability distribution associated to the
true quantized version of the Gaussian signal and to the quantity estimated
after resampling and requantization of the input digitized sequence. The use of
Fourier transform techniques allows deriving {approximate} analytical
expressions for the quantities of interest, as well as implementing their
efficient computation. Numerical experiments are found to be in good agreement
with the theoretical results, and confirm the validity of the whole approach.
|
0803.1985
|
An Investigation of the Sequential Sampling Method for Crossdocking
Simulation Output Variance Reduction
|
cs.NE cs.CE
|
This paper investigates the reduction of variance associated with a
simulation output performance measure, using the Sequential Sampling method
while applying minimum simulation replications, for a class of JIT (Just in
Time) warehousing system called crossdocking. We initially used the Sequential
Sampling method to attain a desired 95% confidence interval half width of
plus/minus 0.5 for our chosen performance measure (Total usage cost, given the
mean maximum level of 157,000 pounds and a mean minimum level of 149,000
pounds). From our results, we achieved a 95% confidence interval half width of
plus/minus 2.8 for our chosen performance measure (Total usage cost, with an
average mean value of 115,000 pounds). However, the Sequential Sampling method
requires a huge number of simulation replications to reduce variance for our
simulation output value to the target level. Arena (version 11) simulation
software was used to conduct this study.
|
0803.1992
|
Achievable Rates and Optimal Resource Allocation for Imperfectly-Known
Fading Relay Channels
|
cs.IT math.IT
|
In this paper, achievable rates and optimal resource allocation strategies
for imperfectly-known fading relay channels are studied. It is assumed that
communication starts with the network training phase in which the receivers
estimate the fading coefficients of their respective channels. In the data
transmission phase, amplify-and-forward and decode-and-forward relaying schemes
with different degrees of cooperation are considered, and the corresponding
achievable rate expressions are obtained. Three resource allocation problems
are addressed: 1) power allocation between data and training symbols; 2)
time/bandwidth allocation to the relay; 3) power allocation between the source
and relay in the presence of total power constraints. The achievable rate
expressions are employed to identify the optimal resource allocation
strategies. Finally, energy efficiency is investigated by studying the bit
energy requirements in the low-SNR regime.
|
0803.1993
|
Improved Squeaky Wheel Optimisation for Driver Scheduling
|
cs.NE cs.CE
|
This paper presents a technique called Improved Squeaky Wheel Optimisation
for driver scheduling problems. It improves the original Squeaky Wheel
Optimisations effectiveness and execution speed by incorporating two additional
steps of Selection and Mutation which implement evolution within a single
solution. In the ISWO, a cycle of
Analysis-Selection-Mutation-Prioritization-Construction continues until
stopping conditions are reached. The Analysis step first computes the fitness
of a current solution to identify troublesome components. The Selection step
then discards these troublesome components probabilistically by using the
fitness measure, and the Mutation step follows to further discard a small
number of components at random. After the above steps, an input solution
becomes partial and thus the resulting partial solution needs to be repaired.
The repair is carried out by using the Prioritization step to first produce
priorities that determine an order by which the following Construction step
then schedules the remaining components. Therefore, the optimisation in the
ISWO is achieved by solution disruption, iterative improvement and an iterative
constructive repair process performed. Encouraging experimental results are
reported.
|
0803.1994
|
The Application of Bayesian Optimization and Classifier Systems in Nurse
Scheduling
|
cs.NE cs.CE
|
Two ideas taken from Bayesian optimization and classifier systems are
presented for personnel scheduling based on choosing a suitable scheduling rule
from a set for each persons assignment. Unlike our previous work of using
genetic algorithms whose learning is implicit, the learning in both approaches
is explicit, i.e. we are able to identify building blocks directly. To achieve
this target, the Bayesian optimization algorithm builds a Bayesian network of
the joint probability distribution of the rules used to construct solutions,
while the adapted classifier system assigns each rule a strength value that is
constantly updated according to its usefulness in the current situation.
Computational results from 52 real data instances of nurse scheduling
demonstrate the success of both approaches. It is also suggested that the
learning mechanism in the proposed approaches might be suitable for other
scheduling problems.
|
0803.1997
|
Danger Theory: The Link between AIS and IDS?
|
cs.NE cs.AI cs.CR
|
We present ideas about creating a next generation Intrusion Detection System
based on the latest immunological theories. The central challenge with computer
security is determining the difference between normal and potentially harmful
activity. For half a century, developers have protected their systems by coding
rules that identify and block specific events. However, the nature of current
and future threats in conjunction with ever larger IT systems urgently requires
the development of automated and adaptive defensive tools. A promising solution
is emerging in the form of Artificial Immune Systems. The Human Immune System
can detect and defend against harmful and previously unseen invaders, so can we
not build a similar Intrusion Detection System for our computers.
|
0803.2092
|
An Ant-Based Model for Multiple Sequence Alignment
|
q-bio.QM cs.AI
|
Multiple sequence alignment is a key process in today's biology, and finding
a relevant alignment of several sequences is much more challenging than just
optimizing some improbable evaluation functions. Our approach for addressing
multiple sequence alignment focuses on the building of structures in a new
graph model: the factor graph model. This model relies on block-based
formulation of the original problem, formulation that seems to be one of the
most suitable ways for capturing evolutionary aspects of alignment. The
structures are implicitly built by a colony of ants laying down pheromones in
the factor graphs, according to relations between blocks belonging to the
different sequences.
|
0803.2212
|
Conditioning Probabilistic Databases
|
cs.DB cs.AI
|
Past research on probabilistic databases has studied the problem of answering
queries on a static database. Application scenarios of probabilistic databases
however often involve the conditioning of a database using additional
information in the form of new evidence. The conditioning problem is thus to
transform a probabilistic database of priors into a posterior probabilistic
database which is materialized for subsequent query processing or further
refinement. It turns out that the conditioning problem is closely related to
the problem of computing exact tuple confidence values.
It is known that exact confidence computation is an NP-hard problem. This has
led researchers to consider approximation techniques for confidence
computation. However, neither conditioning nor exact confidence computation can
be solved using such techniques.
In this paper we present efficient techniques for both problems. We study
several problem decomposition methods and heuristics that are based on the most
successful search techniques from constraint satisfaction, such as the
Davis-Putnam algorithm. We complement this with a thorough experimental
evaluation of the algorithms proposed. Our experiments show that our exact
algorithms scale well to realistic database sizes and can in some scenarios
compete with the most efficient previous approximation algorithms.
|
0803.2220
|
The Anatomy of Mitos Web Search Engine
|
cs.IR
|
Engineering a Web search engine offering effective and efficient information
retrieval is a challenging task. This document presents our experiences from
designing and developing a Web search engine offering a wide spectrum of
functionalities and we report some interesting experimental results. A rather
peculiar design choice of the engine is that its index is based on a DBMS,
while some of the distinctive functionalities that are offered include advanced
Greek language stemming, real time result clustering, and advanced link
analysis techniques (also for spam page detection).
|
0803.2257
|
High-Resolution Radar via Compressed Sensing
|
math.NA cs.IT math.IT
|
A stylized compressed sensing radar is proposed in which the time-frequency
plane is discretized into an N by N grid. Assuming the number of targets K is
small (i.e., K much less than N^2), then we can transmit a sufficiently
"incoherent" pulse and employ the techniques of compressed sensing to
reconstruct the target scene. A theoretical upper bound on the sparsity K is
presented. Numerical simulations verify that even better performance can be
achieved in practice. This novel compressed sensing approach offers great
potential for better resolution over classical radar.
|
0803.2262
|
Constant-Rank Codes and Their Connection to Constant-Dimension Codes
|
cs.IT math.IT
|
Constant-dimension codes have recently received attention due to their
significance to error control in noncoherent random linear network coding. What
the maximal cardinality of any constant-dimension code with finite dimension
and minimum distance is and how to construct the optimal constant-dimension
code (or codes) that achieves the maximal cardinality both remain open research
problems. In this paper, we introduce a new approach to solving these two
problems. We first establish a connection between constant-rank codes and
constant-dimension codes. Via this connection, we show that optimal
constant-dimension codes correspond to optimal constant-rank codes over
matrices with sufficiently many rows. As such, the two aforementioned problems
are equivalent to determining the maximum cardinality of constant-rank codes
and to constructing optimal constant-rank codes, respectively. To this end, we
then derive bounds on the maximum cardinality of a constant-rank code with a
given minimum rank distance, propose explicit constructions of optimal or
asymptotically optimal constant-rank codes, and establish asymptotic bounds on
the maximum rate of a constant-rank code.
|
0803.2306
|
Tableau-based decision procedures for logics of strategic ability in
multi-agent systems
|
cs.LO cs.AI cs.MA
|
We develop an incremental tableau-based decision procedures for the
Alternating-time temporal logic ATL and some of its variants.
While running within the theoretically established complexity upper bound, we
claim that our tableau is practically more efficient in the average case than
other decision procedures for ATL known so far. Besides, the ease of its
adaptation to variants of ATL demonstrates the flexibility of the proposed
procedure.
|
0803.2314
|
Problem Solving and Complex Systems
|
cs.NE
|
The observation and modeling of natural Complex Systems (CSs) like the human
nervous system, the evolution or the weather, allows the definition of special
abilities and models reusable to solve other problems. For instance, Genetic
Algorithms or Ant Colony Optimizations are inspired from natural CSs to solve
optimization problems. This paper proposes the use of ant-based systems to
solve various problems with a non assessing approach. This means that solutions
to some problem are not evaluated. They appear as resultant structures from the
activity of the system. Problems are modeled with graphs and such structures
are observed directly on these graphs. Problems of Multiple Sequences Alignment
and Natural Language Processing are addressed with this approach.
|
0803.2337
|
Data Fusion Trees for Detection: Does Architecture Matter?
|
cs.IT math.IT
|
We consider the problem of decentralized detection in a network consisting of
a large number of nodes arranged as a tree of bounded height, under the
assumption of conditionally independent, identically distributed observations.
We characterize the optimal error exponent under a Neyman-Pearson formulation.
We show that the Type II error probability decays exponentially fast with the
number of nodes, and the optimal error exponent is often the same as that
corresponding to a parallel configuration. We provide sufficient, as well as
necessary, conditions for this to happen. For those networks satisfying the
sufficient conditions, we propose a simple strategy that nearly achieves the
optimal error exponent, and in which all non-leaf nodes need only send 1-bit
messages.
|
0803.2363
|
lambda-Connectedness Determination for Image Segmentation
|
cs.CV cs.DM
|
Image segmentation is to separate an image into distinct homogeneous regions
belonging to different objects. It is an essential step in image analysis and
computer vision. This paper compares some segmentation technologies and
attempts to find an automated way to better determine the parameters for image
segmentation, especially the connectivity value of $\lambda$ in
$\lambda$-connected segmentation.
Based on the theories on the maximum entropy method and Otsu's minimum
variance method, we propose:(1)maximum entropy connectedness determination: a
method that uses maximum entropy to determine the best $\lambda$ value in
$\lambda$-connected segmentation, and (2) minimum variance connectedness
determination: a method that uses the principle of minimum variance to
determine $\lambda$ value. Applying these optimization techniques in real
images, the experimental results have shown great promise in the development of
the new methods. In the end, we extend the above method to more general case in
order to compare it with the famous Mumford-Shah method that uses variational
principle and geometric measure.
|
0803.2392
|
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
|
math.NA cs.IT math.IT
|
Compressive sampling offers a new paradigm for acquiring signals that are
compressible with respect to an orthonormal basis. The major algorithmic
challenge in compressive sampling is to approximate a compressible signal from
noisy samples. This paper describes a new iterative recovery algorithm called
CoSaMP that delivers the same guarantees as the best optimization-based
approaches. Moreover, this algorithm offers rigorous bounds on computational
cost and storage. It is likely to be extremely efficient for practical problems
because it requires only matrix-vector multiplies with the sampling matrix. For
many cases of interest, the running time is just O(N*log^2(N)), where N is the
length of the signal.
|
0803.2427
|
A General Rate Duality of the MIMO Multiple Access Channel and the MIMO
Broadcast Channel
|
cs.IT math.IT
|
We present a general rate duality between the multiple access channel (MAC)
and the broadcast channel (BC) which is applicable to systems with and without
nonlinear interference cancellation. Different to the state-of-the-art rate
duality with interference subtraction from Vishwanath et al., the proposed
duality is filter-based instead of covariance-based and exploits the arising
unitary degree of freedom to decorrelate every point-to-point link. Therefore,
it allows for noncooperative stream-wise decoding which reduces complexity and
latency. Moreover, the conversion from one domain to the other does not exhibit
any dependencies during its computation making it accessible to a parallel
implementation instead of a serial one. We additionally derive a rate duality
for systems with multi-antenna terminals when linear filtering without
interference (pre-)subtraction is applied and the different streams of a single
user are not treated as self-interference. Both dualities are based on a
framework already applied to a mean-square-error duality between the MAC and
the BC. Thanks to this novel rate duality, any rate-based optimization with
linear filtering in the BC can now be handled in the dual MAC where the arising
expressions lead to more efficient algorithmic solutions than in the BC due to
the alignment of the channel and precoder indices.
|
0803.2443
|
Discrete stochastic processes, replicator and Fokker-Planck equations of
coevolutionary dynamics in finite and infinite populations
|
q-bio.PE cond-mat.stat-mech cs.SI math.PR math.ST physics.bio-ph physics.soc-ph stat.TH
|
Finite-size fluctuations in coevolutionary dynamics arise in models of
biological as well as of social and economic systems. This brief tutorial
review surveys a systematic approach starting from a stochastic process
discrete both in time and state. The limit $N\to \infty$ of an infinite
population can be considered explicitly, generally leading to a replicator-type
equation in zero order, and to a Fokker-Planck-type equation in first order in
$1/\sqrt{N}$. Consequences and relations to some previous approaches are
outlined.
|
0803.2460
|
Upper Bound on Error Exponent of Regular LDPC Codes Transmitted over the
BEC
|
cs.IT math.IT
|
The error performance of the ensemble of typical LDPC codes transmitted over
the binary erasure channel (BEC) is analyzed. In the past, lower bounds on the
error exponents were derived. In this paper a probabilistic upper bound on this
error exponent is derived. This bound holds with some confidence level.
|
0803.2559
|
Logical Queries over Views: Decidability and Expressiveness
|
cs.LO cs.DB
|
We study the problem of deciding satisfiability of first order logic queries
over views, our aim being to delimit the boundary between the decidable and the
undecidable fragments of this language. Views currently occupy a central place
in database research, due to their role in applications such as information
integration and data warehousing. Our main result is the identification of a
decidable class of first order queries over unary conjunctive views that
generalises the decidability of the classical class of first order sentences
over unary relations, known as the Lowenheim class. We then demonstrate how
various extensions of this class lead to undecidability and also provide some
expressivity results. Besides its theoretical interest, our new decidable class
is potentially interesting for use in applications such as deciding implication
of complex dependencies, analysis of a restricted class of active database
rules, and ontology reasoning.
|
0803.2570
|
Unequal Error Protection: An Information Theoretic Perspective
|
cs.IT cs.DM math.CO math.IT
|
An information theoretic framework for unequal error protection is developed
in terms of the exponential error bounds. The fundamental difference between
the bit-wise and message-wise unequal error protection (UEP) is demonstrated,
for fixed length block codes on DMCs without feedback. Effect of feedback is
investigated via variable length block codes. It is shown that, feedback
results in a significant improvement in both bit-wise and message-wise UEP
(except the single message case for missed detection). The distinction between
false-alarm and missed-detection formalizations for message-wise UEP is also
considered. All results presented are at rates close to capacity.
|
0803.2639
|
Maximal Orders in the Design of Dense Space-Time Lattice Codes
|
cs.IT cs.DM math.IT math.RA
|
We construct explicit rate-one, full-diversity, geometrically dense matrix
lattices with large, non-vanishing determinants (NVD) for four transmit antenna
multiple-input single-output (MISO) space-time (ST) applications. The
constructions are based on the theory of rings of algebraic integers and
related subrings of the Hamiltonian quaternions and can be extended to a larger
number of Tx antennas. The usage of ideals guarantees a non-vanishing
determinant larger than one and an easy way to present the exact proofs for the
minimum determinants. The idea of finding denser sublattices within a given
division algebra is then generalized to a multiple-input multiple-output (MIMO)
case with an arbitrary number of Tx antennas by using the theory of cyclic
division algebras (CDA) and maximal orders. It is also shown that the explicit
constructions in this paper all have a simple decoding method based on sphere
decoding. Related to the decoding complexity, the notion of sensitivity is
introduced, and experimental evidence indicating a connection between
sensitivity, decoding complexity and performance is provided. Simulations in a
quasi-static Rayleigh fading channel show that our dense quaternionic
constructions outperform both the earlier rectangular lattices and the rotated
ABBA lattice as well as the DAST lattice. We also show that our quaternionic
lattice is better than the DAST lattice in terms of the diversity-multiplexing
gain tradeoff.
|
0803.2675
|
Digital Ecosystems: Self-Organisation of Evolving Agent Populations
|
cs.NE cs.CC
|
A primary motivation for our research in Digital Ecosystems is the desire to
exploit the self-organising properties of biological ecosystems. Ecosystems are
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. Self-organisation is perhaps one of the most
desirable features in the systems that we engineer, and it is important for us
to be able to measure self-organising behaviour. We investigate the
self-organising aspects of Digital Ecosystems, created through the application
of evolutionary computing to Multi-Agent Systems (MASs), aiming to determine a
macroscopic variable to characterise the self-organisation of the evolving
agent populations within. We study a measure for the self-organisation called
Physical Complexity; based on statistical physics, automata theory, and
information theory, providing a measure of information relative to the
randomness in an organism's genome, by calculating the entropy in a population.
We investigate an extension to include populations of variable length, and then
built upon this to construct an efficiency measure to investigate clustering
within evolving agent populations. Overall an insight has been achieved into
where and how self-organisation occurs in our Digital Ecosystem, and how it can
be quantified.
|
0803.2695
|
KohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern
Classification
|
cs.NE cs.CV
|
In this paper we introduce a new ant-based method that takes advantage of the
cooperative self-organization of Ant Colony Systems to create a naturally
inspired clustering and pattern recognition method. The approach considers each
data item as an ant, which moves inside a grid changing the cells it goes
through, in a fashion similar to Kohonen's Self-Organizing Maps. The resulting
algorithm is conceptually more simple, takes less free parameters than other
ant-based clustering algorithms, and, after some parameter tuning, yields very
good results on some benchmark problems.
|
0803.2812
|
Using Spatially Varying Pixels Exposures and Bayer-covered Photosensors
for High Dynamic Range Imaging
|
cs.CV
|
The method of a linear high dynamic range imaging using solid-state
photosensors with Bayer colour filters array is provided in this paper. Using
information from neighbour pixels, it is possible to reconstruct linear images
with wide dynamic range from the oversaturated images. Bayer colour filters
array is considered as an array of neutral filters in a quasimonochromatic
light. If the camera's response function to the desirable light source is known
then one can calculate correction coefficients to reconstruct oversaturated
images. Reconstructed images are linearized in order to provide a linear high
dynamic range images for optical-digital imaging systems. The calibration
procedure for obtaining the camera's response function to the desired light
source is described. Experimental results of the reconstruction of the images
from the oversaturated images are presented for red, green, and blue
quasimonochromatic light sources. Quantitative analysis of the accuracy of the
reconstructed images is provided.
|
0803.2827
|
Impact of CSI on Distributed Space-Time Coding in Wireless Relay
Networks
|
cs.IT math.IT
|
We consider a two-hop wireless network where a transmitter communicates with
a receiver via $M$ relays with an amplify-and-forward (AF) protocol. Recent
works have shown that sophisticated linear processing such as beamforming and
distributed space-time coding (DSTC) at relays enables to improve the AF
performance. However, the relative utility of these strategies depend on the
available channel state information at transmitter (CSIT), which in turn
depends on system parameters such as the speed of the underlying fading channel
and that of training and feedback procedures. Moreover, it is of practical
interest to have a single transmit scheme that handles different CSIT
scenarios. This motivates us to consider a unified approach based on DSTC that
potentially provides diversity gain with statistical CSIT and exploits some
additional side information if available. Under individual power constraints at
the relays, we optimize the amplifier power allocation such that pairwise error
probability conditioned on the available CSIT is minimized. Under perfect CSIT
we propose an on-off gradient algorithm that efficiently finds a set of relays
to switch on. Under partial and statistical CSIT, we propose a simple
waterfilling algorithm that yields a non-trivial solution between maximum power
allocation and a generalized STC that equalizes the averaged amplified noise
for all relays. Moreover, we derive closed-form solutions for M=2 and in
certain asymptotic regimes that enable an easy interpretation of the proposed
algorithms. It is found that an appropriate amplifier power allocation is
mandatory for DSTC to offer sufficient diversity and power gain in a general
network topology.
|
0803.2856
|
Figuring out Actors in Text Streams: Using Collocations to establish
Incremental Mind-maps
|
cs.CL cs.LG
|
The recognition, involvement, and description of main actors influences the
story line of the whole text. This is of higher importance as the text per se
represents a flow of words and expressions that once it is read it is lost. In
this respect, the understanding of a text and moreover on how the actor exactly
behaves is not only a major concern: as human beings try to store a given input
on short-term memory while associating diverse aspects and actors with
incidents, the following approach represents a virtual architecture, where
collocations are concerned and taken as the associative completion of the
actors' acting. Once that collocations are discovered, they become managed in
separated memory blocks broken down by the actors. As for human beings, the
memory blocks refer to associative mind-maps. We then present several priority
functions to represent the actual temporal situation inside a mind-map to
enable the user to reconstruct the recent events from the discovered temporal
results.
|
0803.2904
|
A Distance Metric for Tree-Sibling Time Consistent Phylogenetic Networks
|
q-bio.PE cs.CE cs.DM
|
The presence of reticulate evolutionary events in phylogenies turn
phylogenetic trees into phylogenetic networks. These events imply in particular
that there may exist multiple evolutionary paths from a non-extant species to
an extant one, and this multiplicity makes the comparison of phylogenetic
networks much more difficult than the comparison of phylogenetic trees. In
fact, all attempts to define a sound distance measure on the class of all
phylogenetic networks have failed so far. Thus, the only practical solutions
have been either the use of rough estimates of similarity (based on comparison
of the trees embedded in the networks), or narrowing the class of phylogenetic
networks to a certain class where such a distance is known and can be
efficiently computed. The first approach has the problem that one may identify
two networks as equivalent, when they are not; the second one has the drawback
that there may not exist algorithms to reconstruct such networks from
biological sequences.
We present in this paper a distance measure on the class of tree-sibling time
consistent phylogenetic networks, which generalize tree-child time consistent
phylogenetic networks, and thus also galled-trees. The practical interest of
this distance measure is twofold: it can be computed in polynomial time by
means of simple algorithms, and there also exist polynomial-time algorithms for
reconstructing networks of this class from DNA sequence data.
The Perl package Bio::PhyloNetwork, included in the BioPerl bundle,
implements many algorithms on phylogenetic networks, including the computation
of the distance presented in this paper.
|
0803.2925
|
Equivalence of Probabilistic Tournament and Polynomial Ranking Selection
|
cs.NE
|
Crucial to an Evolutionary Algorithm's performance is its selection scheme.
We mathematically investigate the relation between polynomial rank and
probabilistic tournament methods which are (respectively) generalisations of
the popular linear ranking and tournament selection schemes. We show that every
probabilistic tournament is equivalent to a unique polynomial rank scheme. In
fact, we derived explicit operators for translating between these two types of
selection. Of particular importance is that most linear and most practical
quadratic rank schemes are probabilistic tournaments.
|
0803.2957
|
Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall
Layout and Tenant Selection Problem
|
cs.NE cs.CE
|
During our earlier research, it was recognised that in order to be successful
with an indirect genetic algorithm approach using a decoder, the decoder has to
strike a balance between being an optimiser in its own right and finding
feasible solutions. Previously this balance was achieved manually. Here we
extend this by presenting an automated approach where the genetic algorithm
itself, simultaneously to solving the problem, sets weights to balance the
components out. Subsequently we were able to solve a complex and non-linear
scheduling problem better than with a standard direct genetic algorithm
implementation.
|
0803.2965
|
An Indirect Genetic Algorithm for Set Covering Problems
|
cs.NE cs.AI
|
This paper presents a new type of genetic algorithm for the set covering
problem. It differs from previous evolutionary approaches first because it is
an indirect algorithm, i.e. the actual solutions are found by an external
decoder function. The genetic algorithm itself provides this decoder with
permutations of the solution variables and other parameters. Second, it will be
shown that results can be further improved by adding another indirect
optimisation layer. The decoder will not directly seek out low cost solutions
but instead aims for good exploitable solutions. These are then post optimised
by another hill-climbing algorithm. Although seemingly more complicated, we
will show that this three-stage approach has advantages in terms of solution
quality, speed and adaptability to new types of problems over more direct
approaches. Extensive computational results are presented and compared to the
latest evolutionary and other heuristic approaches to the same data instances.
|
0803.2966
|
On the Application of Hierarchical Coevolutionary Genetic Algorithms:
Recombination and Evaluation Partners
|
cs.NE cs.AI
|
This paper examines the use of a hierarchical coevolutionary genetic
algorithm under different partnering strategies. Cascading clusters of
sub-populations are built from the bottom up, with higher-level sub-populations
optimising larger parts of the problem. Hence higher-level sub-populations
potentially search a larger search space with a lower resolution whilst
lower-level sub-populations search a smaller search space with a higher
resolution. The effects of different partner selection schemes amongst the
sub-populations on solution quality are examined for two constrained
optimisation problems. We examine a number of recombination partnering
strategies in the construction of higher-level individuals and a number of
related schemes for evaluating sub-solutions. It is shown that partnering
strategies that exploit problem-specific knowledge are superior and can counter
inappropriate (sub)fitness measurements.
|
0803.2967
|
Building Better Nurse Scheduling Algorithms
|
cs.NE cs.CE
|
The aim of this research is twofold: Firstly, to model and solve a complex
nurse scheduling problem with an integer programming formulation and
evolutionary algorithms. Secondly, to detail a novel statistical method of
comparing and hence building better scheduling algorithms by identifying
successful algorithm modifications. The comparison method captures the results
of algorithms in a single figure that can then be compared using traditional
statistical techniques. Thus, the proposed method of comparing algorithms is an
objective procedure designed to assist in the process of improving an
algorithm. This is achieved even when some results are non-numeric or missing
due to infeasibility. The final algorithm outperforms all previous evolutionary
algorithms, which relied on human expertise for modification.
|
0803.2969
|
An Indirect Genetic Algorithm for a Nurse Scheduling Problem
|
cs.NE cs.CE
|
This paper describes a Genetic Algorithms approach to a manpower-scheduling
problem arising at a major UK hospital. Although Genetic Algorithms have been
successfully used for similar problems in the past, they always had to overcome
the limitations of the classical Genetic Algorithms paradigm in handling the
conflict between objectives and constraints. The approach taken here is to use
an indirect coding based on permutations of the nurses, and a heuristic decoder
that builds schedules from these permutations. Computational experiments based
on 52 weeks of live data are used to evaluate three different decoders with
varying levels of intelligence, and four well-known crossover operators.
Results are further enhanced by introducing a hybrid crossover operator and by
making use of simple bounds to reduce the size of the solution space. The
results reveal that the proposed algorithm is able to find high quality
solutions and is both faster and more flexible than a recently published Tabu
Search approach.
|
0803.2970
|
A Recommender System based on Idiotypic Artificial Immune Networks
|
cs.NE cs.AI
|
The immune system is a complex biological system with a highly distributed,
adaptive and self-organising nature. This paper presents an Artificial Immune
System (AIS) that exploits some of these characteristics and is applied to the
task of film recommendation by Collaborative Filtering (CF). Natural evolution
and in particular the immune system have not been designed for classical
optimisation. However, for this problem, we are not interested in finding a
single optimum. Rather we intend to identify a sub-set of good matches on which
recommendations can be based. It is our hypothesis that an AIS built on two
central aspects of the biological immune system will be an ideal candidate to
achieve this: Antigen-antibody interaction for matching and idiotypic
antibody-antibody interaction for diversity. Computational results are
presented in support of this conjecture and compared to those found by other CF
techniques.
|
0803.2973
|
Rule Generalisation in Intrusion Detection Systems using Snort
|
cs.NE cs.CR
|
Intrusion Detection Systems (ids)provide an important layer of security for
computer systems and networks, and are becoming more and more necessary as
reliance on Internet services increases and systems with sensitive data are
more commonly open to Internet access. An ids responsibility is to detect
suspicious or unacceptable system and network activity and to alert a systems
administrator to this activity. The majority of ids use a set of signatures
that define what suspicious traffic is, and Snort is one popular and actively
developing open-source ids that uses such a set of signatures known as Snort
rules. Our aim is to identify a way in which Snort could be developed further
by generalising rules to identify novel attacks. In particular, we attempted to
relax and vary the conditions and parameters of current Snort rules, using a
similar approach to classic rule learning operators such as generalisation and
specialisation. We demonstrate the effectiveness of our approach through
experiments with standard datasets and show that we are able to detect
previously undeleted variants of various attacks. We conclude by discussing the
general effectiveness and appropriateness of generalisation in Snort based ids
rule processing.
|
0803.2975
|
An Estimation of Distribution Algorithm for Nurse Scheduling
|
cs.NE cs.CE
|
Schedules can be built in a similar way to a human scheduler by using a set
of rules that involve domain knowledge. This paper presents an Estimation of
Distribution Algorithm (eda) for the nurse scheduling problem, which involves
choosing a suitable scheduling rule from a set for the assignment of each
nurse. Unlike previous work that used Genetic Algorithms (ga) to implement
implicit learning, the learning in the proposed algorithm is explicit, i.e. we
identify and mix building blocks directly. The eda is applied to implement such
explicit learning by building a Bayesian network of the joint distribution of
solutions. The conditional probability of each variable in the network is
computed according to an initial set of promising solutions. Subsequently, each
new instance for each variable is generated by using the corresponding
conditional probabilities, until all variables have been generated, i.e. in our
case, a new rule string has been obtained. Another set of rule strings will be
generated in this way, some of which will replace previous strings based on
fitness selection. If stopping conditions are not met, the conditional
probabilities for all nodes in the Bayesian network are updated again using the
current set of promising rule strings. Computational results from 52 real data
instances demonstrate the success of this approach. It is also suggested that
the learning mechanism in the proposed approach might be suitable for other
scheduling problems.
|
0803.2981
|
Idiotypic Immune Networks in Mobile Robot Control
|
cs.NE cs.AI cs.RO
|
Jerne's idiotypic network theory postulates that the immune response involves
inter-antibody stimulation and suppression as well as matching to antigens. The
theory has proved the most popular Artificial Immune System (ais) model for
incorporation into behavior-based robotics but guidelines for implementing
idiotypic selection are scarce. Furthermore, the direct effects of employing
the technique have not been demonstrated in the form of a comparison with
non-idiotypic systems. This paper aims to address these issues. A method for
integrating an idiotypic ais network with a Reinforcement Learning based
control system (rl) is described and the mechanisms underlying antibody
stimulation and suppression are explained in detail. Some hypotheses that
account for the network advantage are put forward and tested using three
systems with increasing idiotypic complexity. The basic rl, a simplified hybrid
ais-rl that implements idiotypic selection independently of derived
concentration levels and a full hybrid ais-rl scheme are examined. The test bed
takes the form of a simulated Pioneer robot that is required to navigate
through maze worlds detecting and tracking door markers.
|
0803.3117
|
On the Diversity-Multiplexing Tradeoff in Multiple-Relay Network
|
cs.IT math.IT
|
This paper studies the setup of a multiple-relay network in which $K$
half-duplex multiple-antenna relays assist in the transmission between
a/several multiple-antenna transmitter(s) and a multiple-antenna receiver. Each
two nodes are assumed to be either connected through a quasi-static Rayleigh
fading channel, or disconnected. We propose a new scheme, which we call
\textit{random sequential} (RS), based on the amplify-and-forward relaying. We
prove that for general multiple-antenna multiple-relay networks, the proposed
scheme achieves the maximum diversity gain. Furthermore, we derive
diversity-multiplexing tradeoff (DMT) of the proposed RS scheme for general
single-antenna multiple-relay networks. It is shown that for single-antenna
two-hop multiple-access multiple-relay ($K>1$) networks (without direct link
between the transmitter(s) and the receiver), the proposed RS scheme achieves
the optimum DMT. However, for the case of multiple access single relay setup,
we show that the RS scheme reduces to the naive amplify-and-forward relaying
and is not optimum in terms of DMT, while the dynamic decode-and-forward scheme
is shown to be optimum for this scenario.
|
0803.3186
|
Towards a human eye behavior model by applying Data Mining Techniques on
Gaze Information from IEC
|
cs.HC cs.NE
|
In this paper, we firstly present what is Interactive Evolutionary
Computation (IEC) and rapidly how we have combined this artificial intelligence
technique with an eye-tracker for visual optimization. Next, in order to
correctly parameterize our application, we present results from applying data
mining techniques on gaze information coming from experiments conducted on
about 80 human individuals.
|
0803.3192
|
Eye-Tracking Evolutionary Algorithm to minimize user's fatigue in IEC
applied to Interactive One-Max problem
|
cs.AI
|
In this paper, we describe a new algorithm that consists in combining an
eye-tracker for minimizing the fatigue of a user during the evaluation process
of Interactive Evolutionary Computation. The approach is then applied to the
Interactive One-Max optimization problem.
|
0803.3224
|
A Model-Based Frequency Constraint for Mining Associations from
Transaction Data
|
cs.DB
|
Mining frequent itemsets is a popular method for finding associated items in
databases. For this method, support, the co-occurrence frequency of the items
which form an association, is used as the primary indicator of the
associations's significance. A single user-specified support threshold is used
to decided if associations should be further investigated. Support has some
known problems with rare items, favors shorter itemsets and sometimes produces
misleading associations.
In this paper we develop a novel model-based frequency constraint as an
alternative to a single, user-specified minimum support. The constraint
utilizes knowledge of the process generating transaction data by applying a
simple stochastic mixture model (the NB model) which allows for transaction
data's typically highly skewed item frequency distribution. A user-specified
precision threshold is used together with the model to find local frequency
thresholds for groups of itemsets. Based on the constraint we develop the
notion of NB-frequent itemsets and adapt a mining algorithm to find all
NB-frequent itemsets in a database. In experiments with publicly available
transaction databases we show that the new constraint provides improvements
over a single minimum support threshold and that the precision threshold is
more robust and easier to set and interpret by the user.
|
0803.3360
|
Asymptotics of input-constrained binary symmetric channel capacity
|
math.PR cs.IT math.IT
|
We study the classical problem of noisy constrained capacity in the case of
the binary symmetric channel (BSC), namely, the capacity of a BSC whose inputs
are sequences chosen from a constrained set. Motivated by a result of
Ordentlich and Weissman [In Proceedings of IEEE Information Theory Workshop
(2004) 117--122], we derive an asymptotic formula (when the noise parameter is
small) for the entropy rate of a hidden Markov chain, observed when a Markov
chain passes through a BSC. Using this result, we establish an asymptotic
formula for the capacity of a BSC with input process supported on an
irreducible finite type constraint, as the noise parameter tends to zero.
|
0803.3363
|
Node discovery in a networked organization
|
cs.AI
|
In this paper, I present a method to solve a node discovery problem in a
networked organization. Covert nodes refer to the nodes which are not
observable directly. They affect social interactions, but do not appear in the
surveillance logs which record the participants of the social interactions.
Discovering the covert nodes is defined as identifying the suspicious logs
where the covert nodes would appear if the covert nodes became overt. A
mathematical model is developed for the maximal likelihood estimation of the
network behind the social interactions and for the identification of the
suspicious logs. Precision, recall, and F measure characteristics are
demonstrated with the dataset generated from a real organization and the
computationally synthesized datasets. The performance is close to the
theoretical limit for any covert nodes in the networks of any topologies and
sizes if the ratio of the number of observation to the number of possible
communication patterns is large.
|
0803.3404
|
Some results on $\mathbb{R}$-computable structures
|
cs.DB cs.LO math.LO
|
This survey paper examines the effective model theory obtained with the BSS
model of real number computation. It treats the following topics: computable
ordinals, satisfaction of computable infinitary formulas, forcing as a
construction technique, effective categoricity, effective topology, and
relations with other models for the effective theory of uncountable structures.
|
0803.3448
|
Secure Hop-by-Hop Aggregation of End-to-End Concealed Data in Wireless
Sensor Networks
|
cs.CR cs.IT cs.NI math.IT
|
In-network data aggregation is an essential technique in mission critical
wireless sensor networks (WSNs) for achieving effective transmission and hence
better power conservation. Common security protocols for aggregated WSNs are
either hop-by-hop or end-to-end, each of which has its own encryption schemes
considering different security primitives. End-to-end encrypted data
aggregation protocols introduce maximum data secrecy with in-efficient data
aggregation and more vulnerability to active attacks, while hop-by-hop data
aggregation protocols introduce maximum data integrity with efficient data
aggregation and more vulnerability to passive attacks.
In this paper, we propose a secure aggregation protocol for aggregated WSNs
deployed in hostile environments in which dual attack modes are present. Our
proposed protocol is a blend of flexible data aggregation as in hop-by-hop
protocols and optimal data confidentiality as in end-to-end protocols. Our
protocol introduces an efficient O(1) heuristic for checking data integrity
along with cost-effective heuristic-based divide and conquer attestation
process which is $O(\ln{n})$ in average -O(n) in the worst scenario- for
further verification of aggregated results.
|
0803.3490
|
Robustness and Regularization of Support Vector Machines
|
cs.LG cs.AI
|
We consider regularized support vector machines (SVMs) and show that they are
precisely equivalent to a new robust optimization formulation. We show that
this equivalence of robust optimization and regularization has implications for
both algorithms, and analysis. In terms of algorithms, the equivalence suggests
more general SVM-like algorithms for classification that explicitly build in
protection to noise, and at the same time control overfitting. On the analysis
front, the equivalence of robustness and regularization, provides a robust
optimization interpretation for the success of regularized SVMs. We use the
this new robustness interpretation of SVMs to give a new proof of consistency
of (kernelized) SVMs, thus establishing robustness as the reason regularized
SVMs generalize well.
|
0803.3501
|
Multiagent Approach for the Representation of Information in a Decision
Support System
|
cs.AI
|
In an emergency situation, the actors need an assistance allowing them to
react swiftly and efficiently. In this prospect, we present in this paper a
decision support system that aims to prepare actors in a crisis situation
thanks to a decision-making support. The global architecture of this system is
presented in the first part. Then we focus on a part of this system which is
designed to represent the information of the current situation. This part is
composed of a multiagent system that is made of factual agents. Each agent
carries a semantic feature and aims to represent a partial part of a situation.
The agents develop thanks to their interactions by comparing their semantic
features using proximity measures and according to specific ontologies.
|
0803.3539
|
Reinforcement Learning by Value Gradients
|
cs.NE cs.AI
|
The concept of the value-gradient is introduced and developed in the context
of reinforcement learning. It is shown that by learning the value-gradients
exploration or stochastic behaviour is no longer needed to find locally optimal
trajectories. This is the main motivation for using value-gradients, and it is
argued that learning value-gradients is the actual objective of any
value-function learning algorithm for control problems. It is also argued that
learning value-gradients is significantly more efficient than learning just the
values, and this argument is supported in experiments by efficiency gains of
several orders of magnitude, in several problem domains. Once value-gradients
are introduced into learning, several analyses become possible. For example, a
surprising equivalence between a value-gradient learning algorithm and a
policy-gradient learning algorithm is proven, and this provides a robust
convergence proof for control problems using a value function with a general
function approximator.
|
0803.3553
|
New Families of Triple Error Correcting Codes with BCH Parameters
|
cs.IT cs.DM math.IT
|
Discovered by Bose, Chaudhuri and Hocquenghem, the BCH family of error
correcting codes are one of the most studied families in coding theory. They
are also among the best performing codes, particularly when the number of
errors being corrected is small relative to the code length. In this article we
consider binary codes with minimum distance of 7. We construct new families of
codes with these BCH parameters via a generalisation of the Kasami-Welch
Theorem.
|
0803.3608
|
The Category-Theoretic Arithmetic of Information
|
math.CT cs.IT math.IT
|
We highlight the underlying category-theoretic structure of measures of
information flow. We present an axiomatic framework in which communication
systems are represented as morphisms, and information flow is characterized by
its behavior when communication systems are combined. Our framework includes a
variety of discrete, continuous, and, conjecturally, quantum information
measures. It also includes some familiar mathematical constructs not normally
associated with information, such as vector space dimension. We discuss these
examples and prove basic results from the axioms.
|
0803.3645
|
A New Sphere-Packing Bound for Maximal Error Exponent for
Multiple-Access Channels
|
cs.IT math.IT
|
In this work, a new lower bound for the maximal error probability of a
two-user discrete memoryless (DM) multiple-access channel (MAC) is derived.
This is the first bound of this type that explicitly imposes independence of
the users' input distributions (conditioned on the time-sharing auxiliary
variable) and thus results in a tighter sphere-packing exponent when compared
to the tightest known exponent derived by Haroutunian.
|
0803.3657
|
Improved Lower Bounds for Constant GC-Content DNA Codes
|
cs.IT cs.DS math.CO math.IT q-bio.GN q-bio.QM
|
The design of large libraries of oligonucleotides having constant GC-content
and satisfying Hamming distance constraints between oligonucleotides and their
Watson-Crick complements is important in reducing hybridization errors in DNA
computing, DNA microarray technologies, and molecular bar coding. Various
techniques have been studied for the construction of such oligonucleotide
libraries, ranging from algorithmic constructions via stochastic local search
to theoretical constructions via coding theory. We introduce a new stochastic
local search method which yields improvements up to more than one third of the
benchmark lower bounds of Gaborit and King (2005) for n-mer oligonucleotide
libraries when n <= 14. We also found several optimal libraries by computing
maximum cliques on certain graphs.
|
0803.3658
|
The Sizes of Optimal q-Ary Codes of Weight Three and Distance Four: A
Complete Solution
|
cs.IT cs.DM math.CO math.IT
|
This correspondence introduces two new constructive techniques to complete
the determination of the sizes of optimal q-ary codes of constant weight three
and distance four.
|
0803.3693
|
Succinct Data Structures for Retrieval and Approximate Membership
|
cs.DS cs.DB cs.IR
|
The retrieval problem is the problem of associating data with keys in a set.
Formally, the data structure must store a function f: U ->{0,1}^r that has
specified values on the elements of a given set S, a subset of U, |S|=n, but
may have any value on elements outside S. Minimal perfect hashing makes it
possible to avoid storing the set S, but this induces a space overhead of
Theta(n) bits in addition to the nr bits needed for function values. In this
paper we show how to eliminate this overhead. Moreover, we show that for any k
query time O(k) can be achieved using space that is within a factor 1+e^{-k} of
optimal, asymptotically for large n. If we allow logarithmic evaluation time,
the additive overhead can be reduced to O(log log n) bits whp. The time to
construct the data structure is O(n), expected. A main technical ingredient is
to utilize existing tight bounds on the probability of almost square random
matrices with rows of low weight to have full row rank. In addition to direct
constructions, we point out a close connection between retrieval structures and
hash tables where keys are stored in an array and some kind of probing scheme
is used. Further, we propose a general reduction that transfers the results on
retrieval into analogous results on approximate membership, a problem
traditionally addressed using Bloom filters. Again, we show how to eliminate
the space overhead present in previously known methods, and get arbitrarily
close to the lower bound. The evaluation procedures of our data structures are
extremely simple (similar to a Bloom filter). For the results stated above we
assume free access to fully random hash functions. However, we show how to
justify this assumption using extra space o(n) to simulate full randomness on a
RAM.
|
0803.3746
|
Cluster Approach to the Domains Formation
|
cs.NE cs.DS
|
As a rule, a quadratic functional depending on a great number of binary
variables has a lot of local minima. One of approaches allowing one to find in
averaged deeper local minima is aggregation of binary variables into larger
blocks/domains. To minimize the functional one has to change the states of
aggregated variables (domains). In the present publication we discuss methods
of domains formation. It is shown that the best results are obtained when
domains are formed by variables that are strongly connected with each other.
|
0803.3773
|
Capacity of Gaussian MIMO Bidirectional Broadcast Channels
|
cs.IT math.IT
|
We consider the broadcast phase of a three-node network, where a relay node
establishes a bidirectional communication between two nodes using a spectrally
efficient two-phase decode-and-forward protocol. In the first phase the two
nodes transmit their messages to the relay node. Then the relay node decodes
the messages and broadcasts a re-encoded composition of them in the second
phase. We consider Gaussian MIMO channels and determine the capacity region for
the second phase which we call the Gaussian MIMO bidirectional broadcast
channel.
|
0803.3777
|
Lower Bounds on the Minimum Pseudodistance for Linear Codes with $q$-ary
PSK Modulation over AWGN
|
cs.IT math.IT
|
We present lower bounds on the minimum pseudocodeword effective Euclidean
distance (or minimum "pseudodistance") for coded modulation systems using
linear codes with $q$-ary phase-shift keying (PSK) modulation over the additive
white Gaussian noise (AWGN) channel. These bounds apply to both binary and
nonbinary coded modulation systems which use direct modulation mapping of coded
symbols. The minimum pseudodistance may serve as a first-order measure of
error-correcting performance for both linear-programming and message-passing
based receivers. In the case of a linear-programming based receiver, the
minimum pseudodistance may be used to form an exact bound on the codeword error
rate of the system.
|
0803.3781
|
Fourier Spectra of Binomial APN Functions
|
cs.DM cs.IT math.IT
|
In this paper we compute the Fourier spectra of some recently discovered
binomial APN functions. One consequence of this is the determination of the
nonlinearity of the functions, which measures their resistance to linear
cryptanalysis. Another consequence is that certain error-correcting codes
related to these functions have the same weight distribution as the
2-error-correcting BCH code. Furthermore, for fields of odd degree, our results
provide an alternative proof of the APN property of the functions.
|
0803.3812
|
Preferred extensions as stable models
|
cs.AI cs.SC
|
Given an argumentation framework AF, we introduce a mapping function that
constructs a disjunctive logic program P, such that the preferred extensions of
AF correspond to the stable models of P, after intersecting each stable model
with the relevant atoms. The given mapping function is of polynomial size
w.r.t. AF. In particular, we identify that there is a direct relationship
between the minimal models of a propositional formula and the preferred
extensions of an argumentation framework by working on representing the
defeated arguments. Then we show how to infer the preferred extensions of an
argumentation framework by using UNSAT algorithms and disjunctive stable model
solvers. The relevance of this result is that we define a direct relationship
between one of the most satisfactory argumentation semantics and one of the
most successful approach of non-monotonic reasoning i.e., logic programming
with the stable model semantics.
|
0803.3816
|
Approaching the Capacity of Wireless Networks through Distributed
Interference Alignment
|
cs.IT math.IT
|
Recent results establish the optimality of interference alignment to approach
the Shannon capacity of interference networks at high SNR. However, the extent
to which interference can be aligned over a finite number of signalling
dimensions remains unknown. Another important concern for interference
alignment schemes is the requirement of global channel knowledge. In this work
we provide examples of iterative algorithms that utilize the reciprocity of
wireless networks to achieve interference alignment with only local channel
knowledge at each node. These algorithms also provide numerical insights into
the feasibility of interference alignment that are not yet available in theory.
|
0803.3838
|
Recorded Step Directional Mutation for Faster Convergence
|
cs.NE cs.LG
|
Two meta-evolutionary optimization strategies described in this paper
accelerate the convergence of evolutionary programming algorithms while still
retaining much of their ability to deal with multi-modal problems. The
strategies, called directional mutation and recorded step in this paper, can
operate independently but together they greatly enhance the ability of
evolutionary programming algorithms to deal with fitness landscapes
characterized by long narrow valleys. The directional mutation aspect of this
combined method uses correlated meta-mutation but does not introduce a full
covariance matrix. These new methods are thus much more economical in terms of
storage for problems with high dimensionality. Additionally, directional
mutation is rotationally invariant which is a substantial advantage over
self-adaptive methods which use a single variance per coordinate for problems
where the natural orientation of the problem is not oriented along the axes.
|
0803.3850
|
State Estimation Over Wireless Channels Using Multiple Sensors:
Asymptotic Behaviour and Optimal Power Allocation
|
cs.IT math.IT
|
This paper considers state estimation of linear systems using analog amplify
and forwarding with multiple sensors, for both multiple access and orthogonal
access schemes. Optimal state estimation can be achieved at the fusion center
using a time varying Kalman filter. We show that in many situations, the
estimation error covariance decays at a rate of $1/M$ when the number of
sensors $M$ is large. We consider optimal allocation of transmission powers
that 1) minimizes the sum power usage subject to an error covariance constraint
and 2) minimizes the error covariance subject to a sum power constraint. In the
case of fading channels with channel state information the optimization
problems are solved using a greedy approach, while for fading channels without
channel state information but with channel statistics available a sub-optimal
linear estimator is derived.
|
0803.3880
|
Asymptotically Optimum Universal One-Bit Watermarking for Gaussian
Covertexts and Gaussian Attacks
|
cs.IT math.IT
|
The problem of optimum watermark embedding and detection was addressed in a
recent paper by Merhav and Sabbag, where the optimality criterion was the
maximum false-negative error exponent subject to a guaranteed false-positive
error exponent. In particular, Merhav and Sabbag derived universal
asymptotically optimum embedding and detection rules under the assumption that
the detector relies solely on second order joint empirical statistics of the
received signal and the watermark. In the case of a Gaussian host signal and a
Gaussian attack, however, closed-form expressions for the optimum embedding
strategy and the false-negative error exponent were not obtained in that work.
In this paper, we derive such expressions, again, under the universality
assumption that neither the host variance nor the attack power are known to
either the embedder or the detector. The optimum embedding rule turns out to be
very simple and with an intuitively-appealing geometrical interpretation. The
improvement with respect to existing sub-optimum schemes is demonstrated by
displaying the optimum false-negative error exponent as a function of the
guaranteed false-positive error exponent.
|
0803.3900
|
A Component Based Heuristic Search method with Adaptive Perturbations
for Hospital Personnel Scheduling
|
cs.NE cs.CE
|
Nurse rostering is a complex scheduling problem that affects hospital
personnel on a daily basis all over the world. This paper presents a new
component-based approach with adaptive perturbations, for a nurse scheduling
problem arising at a major UK hospital. The main idea behind this technique is
to decompose a schedule into its components (i.e. the allocated shift pattern
of each nurse), and then mimic a natural evolutionary process on these
components to iteratively deliver better schedules. The worthiness of all
components in the schedule has to be continuously demonstrated in order for
them to remain there. This demonstration employs a dynamic evaluation function
which evaluates how well each component contributes towards the final
objective. Two perturbation steps are then applied: the first perturbation
eliminates a number of components that are deemed not worthy to stay in the
current schedule; the second perturbation may also throw out, with a low level
of probability, some worthy components. The eliminated components are
replenished with new ones using a set of constructive heuristics using local
optimality criteria. Computational results using 52 data instances demonstrate
the applicability of the proposed approach in solving real-world problems.
|
0803.3905
|
Introduction to Multi-Agent Simulation
|
cs.NE cs.MA
|
When designing systems that are complex, dynamic and stochastic in nature,
simulation is generally recognised as one of the best design support
technologies, and a valuable aid in the strategic and tactical decision making
process. A simulation model consists of a set of rules that define how a system
changes over time, given its current state. Unlike analytical models, a
simulation model is not solved but is run and the changes of system states can
be observed at any point in time. This provides an insight into system dynamics
rather than just predicting the output of a system based on specific inputs.
Simulation is not a decision making tool but a decision support tool, allowing
better informed decisions to be made. Due to the complexity of the real world,
a simulation model can only be an approximation of the target system. The
essence of the art of simulation modelling is abstraction and simplification.
Only those characteristics that are important for the study and analysis of the
target system should be included in the simulation model.
|
0803.3912
|
Artificial Immune Systems Tutorial
|
cs.NE cs.AI cs.MA
|
The biological immune system is a robust, complex, adaptive system that
defends the body from foreign pathogens. It is able to categorize all cells (or
molecules) within the body as self-cells or non-self cells. It does this with
the help of a distributed task force that has the intelligence to take action
from a local and also a global perspective using its network of chemical
messengers for communication. There are two major branches of the immune
system. The innate immune system is an unchanging mechanism that detects and
destroys certain invading organisms, whilst the adaptive immune system responds
to previously unknown foreign cells and builds a response to them that can
remain in the body over a long period of time. This remarkable information
processing biological system has caught the attention of computer science in
recent years. A novel computational intelligence technique, inspired by
immunology, has emerged, called Artificial Immune Systems. Several concepts
from the immune have been extracted and applied for solution to real world
science and engineering problems. In this tutorial, we briefly describe the
immune system metaphors that are relevant to existing Artificial Immune Systems
methods. We will then show illustrative real-world problems suitable for
Artificial Immune Systems and give a step-by-step algorithm walkthrough for one
such problem. A comparison of the Artificial Immune Systems to other well-known
algorithms, areas for future work, tips & tricks and a list of resources will
round this tutorial off. It should be noted that as Artificial Immune Systems
is still a young and evolving field, there is not yet a fixed algorithm
template and hence actual implementations might differ somewhat from time to
time and from those examples given here.
|
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