id stringlengths 9 16 | title stringlengths 4 278 | categories stringlengths 5 104 | abstract stringlengths 6 4.09k |
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1401.4605 | Consistency Techniques for Flow-Based Projection-Safe Global Cost
Functions in Weighted Constraint Satisfaction | cs.AI cs.DS | Many combinatorial problems deal with preferences and violations, the goal of
which is to find solutions with the minimum cost. Weighted constraint
satisfaction is a framework for modeling such problems, which consists of a set
of cost functions to measure the degree of violation or preferences of
different combinations of variable assignments. Typical solution methods for
weighted constraint satisfaction problems (WCSPs) are based on branch-and-bound
search, which are made practical through the use of powerful consistency
techniques such as AC*, FDAC*, EDAC* to deduce hidden cost information and
value pruning during search. These techniques, however, are designed to be
efficient only on binary and ternary cost functions which are represented in
table form. In tackling many real-life problems, high arity (or global) cost
functions are required. We investigate efficient representation scheme and
algorithms to bring the benefits of the consistency techniques to also high
arity cost functions, which are often derived from hard global constraints from
classical constraint satisfaction. The literature suggests some global cost
functions can be represented as flow networks, and the minimum cost flow
algorithm can be used to compute the minimum costs of such networks in
polynomial time. We show that naive adoption of this flow-based algorithmic
method for global cost functions can result in a stronger form of null-inverse
consistency. We further show how the method can be modified to handle cost
projections and extensions to maintain generalized versions of AC* and FDAC*
for cost functions with more than two variables. Similar generalization for the
stronger EDAC* is less straightforward. We reveal the oscillation problem when
enforcing EDAC* on cost functions sharing more than one variable. To avoid
oscillation, we propose a weak version of EDAC* and generalize it to weak
EDGAC* for non-binary cost functions. Using various benchmarks involving the
soft variants of hard global constraints ALLDIFFERENT, GCC, SAME, and REGULAR,
empirical results demonstrate that our proposal gives improvements of up to an
order of magnitude when compared with the traditional constraint optimization
approach, both in terms of time and pruning.
|
1401.4606 | Drake: An Efficient Executive for Temporal Plans with Choice | cs.AI | This work presents Drake, a dynamic executive for temporal plans with choice.
Dynamic plan execution strategies allow an autonomous agent to react quickly to
unfolding events, improving the robustness of the agent. Prior work developed
methods for dynamically dispatching Simple Temporal Networks, and further
research enriched the expressiveness of the plans executives could handle,
including discrete choices, which are the focus of this work. However, in some
approaches to date, these additional choices induce significant storage or
latency requirements to make flexible execution possible.
Drake is designed to leverage the low latency made possible by a
preprocessing step called compilation, while avoiding high memory costs through
a compact representation. We leverage the concepts of labels and environments,
taken from prior work in Assumption-based Truth Maintenance Systems (ATMS), to
concisely record the implications of the discrete choices, exploiting the
structure of the plan to avoid redundant reasoning or storage. Our labeling and
maintenance scheme, called the Labeled Value Set Maintenance System, is
distinguished by its focus on properties fundamental to temporal problems, and,
more generally, weighted graph algorithms. In particular, the maintenance
system focuses on maintaining a minimal representation of non-dominated
constraints. We benchmark Drakes performance on random structured problems, and
find that Drake reduces the size of the compiled representation by a factor of
over 500 for large problems, while incurring only a modest increase in run-time
latency, compared to prior work in compiled executives for temporal plans with
discrete choices.
|
1401.4607 | Reformulating the Situation Calculus and the Event Calculus in the
General Theory of Stable Models and in Answer Set Programming | cs.AI cs.LO | Circumscription and logic programs under the stable model semantics are two
well-known nonmonotonic formalisms. The former has served as a basis of
classical logic based action formalisms, such as the situation calculus, the
event calculus and temporal action logics; the latter has served as a basis of
a family of action languages, such as language A and several of its
descendants. Based on the discovery that circumscription and the stable model
semantics coincide on a class of canonical formulas, we reformulate the
situation calculus and the event calculus in the general theory of stable
models. We also present a translation that turns the reformulations further
into answer set programs, so that efficient answer set solvers can be applied
to compute the situation calculus and the event calculus.
|
1401.4609 | Computing All-Pairs Shortest Paths by Leveraging Low Treewidth | cs.DS cs.AI | We present two new and efficient algorithms for computing all-pairs shortest
paths. The algorithms operate on directed graphs with real (possibly negative)
weights. They make use of directed path consistency along a vertex ordering d.
Both algorithms run in O(n^2 w_d) time, where w_d is the graph width induced by
this vertex ordering. For graphs of constant treewidth, this yields O(n^2)
time, which is optimal. On chordal graphs, the algorithms run in O(nm) time. In
addition, we present a variant that exploits graph separators to arrive at a
run time of O(n w_d^2 + n^2 s_d) on general graphs, where s_d andlt= w_d is the
size of the largest minimal separator induced by the vertex ordering d. We show
empirically that on both constructed and realistic benchmarks, in many cases
the algorithms outperform Floyd-Warshalls as well as Johnsons algorithm, which
represent the current state of the art with a run time of O(n^3) and O(nm + n^2
log n), respectively. Our algorithms can be used for spatial and temporal
reasoning, such as for the Simple Temporal Problem, which underlines their
relevance to the planning and scheduling community.
|
1401.4612 | Modelling Observation Correlations for Active Exploration and Robust
Object Detection | cs.RO cs.CV | Today, mobile robots are expected to carry out increasingly complex tasks in
multifarious, real-world environments. Often, the tasks require a certain
semantic understanding of the workspace. Consider, for example, spoken
instructions from a human collaborator referring to objects of interest; the
robot must be able to accurately detect these objects to correctly understand
the instructions. However, existing object detection, while competent, is not
perfect. In particular, the performance of detection algorithms is commonly
sensitive to the position of the sensor relative to the objects in the scene.
This paper presents an online planning algorithm which learns an explicit model
of the spatial dependence of object detection and generates plans which
maximize the expected performance of the detection, and by extension the
overall plan performance. Crucially, the learned sensor model incorporates
spatial correlations between measurements, capturing the fact that successive
measurements taken at the same or nearby locations are not independent. We show
how this sensor model can be incorporated into an efficient forward search
algorithm in the information space of detected objects, allowing the robot to
generate motion plans efficiently. We investigate the performance of our
approach by addressing the tasks of door and text detection in indoor
environments and demonstrate significant improvement in detection performance
during task execution over alternative methods in simulated and real robot
experiments.
|
1401.4613 | Local Consistency and SAT-Solvers | cs.AI cs.LO | Local consistency techniques such as k-consistency are a key component of
specialised solvers for constraint satisfaction problems. In this paper we show
that the power of using k-consistency techniques on a constraint satisfaction
problem is precisely captured by using a particular inference rule, which we
call negative-hyper-resolution, on the standard direct encoding of the problem
into Boolean clauses. We also show that current clause-learning SAT-solvers
will discover in expected polynomial time any inconsistency that can be deduced
from a given set of clauses using negative-hyper-resolvents of a fixed size. We
combine these two results to show that, without being explicitly designed to do
so, current clause-learning SAT-solvers efficiently simulate k-consistency
techniques, for all fixed values of k. We then give some experimental results
to show that this feature allows clause-learning SAT-solvers to efficiently
solve certain families of constraint problems which are challenging for
conventional constraint-programming solvers.
|
1401.4633 | Efficient Codes for Adversarial Wiretap Channels | cs.IT math.IT | In [13] we proposed a ({\rho}_r , {\rho}_w )-adversarial wiretap channel
model (AWTP) in which the adversary can adaptively choose to see a fraction
{\rho}_r of the codeword sent over the channel, and modify a fraction {\rho}_w
of the codeword by adding arbitrary noise values to them. In this paper we give
the first efficient construction of a capacity achieving code family that
provides perfect secrecy for this channel.
|
1401.4634 | The Capacity of String-Replication Systems | cs.IT cs.CL math.IT | It is known that the majority of the human genome consists of repeated
sequences. Furthermore, it is believed that a significant part of the rest of
the genome also originated from repeated sequences and has mutated to its
current form. In this paper, we investigate the possibility of constructing an
exponentially large number of sequences from a short initial sequence and
simple replication rules, including those resembling genomic replication
processes. In other words, our goal is to find out the capacity, or the
expressive power, of these string-replication systems. Our results include
exact capacities, and bounds on the capacities, of four fundamental
string-replication systems.
|
1401.4642 | On the Capacity of Memoryless Adversary | cs.IT math.IT | In this paper, we study a model of communication under adversarial noise. In
this model, the adversary makes online decisions on whether to corrupt a
transmitted bit based on only the value of that bit. Like the usual binary
symmetric channel of information theory or the fully adversarial channel of
combinatorial coding theory, the adversary can, with high probability,
introduce at most a given fraction of error.
It is shown that, the capacity (maximum rate of reliable information
transfer) of such memoryless adversary is strictly below that of the binary
symmetric channel. We give new upper bound on the capacity of such channel --
the tightness of this upper bound remains an open question. The main component
of our proof is the careful examination of error-correcting properties of a
code with skewed distance distribution.
|
1401.4644 | Time series modeling and large scale global solar radiation forecasting
from geostationary satellites data | cs.CE physics.comp-ph stat.AP | When a territory is poorly instrumented, geostationary satellites data can be
useful to predict global solar radiation. In this paper, we use geostationary
satellites data to generate 2-D time series of solar radiation for the next
hour. The results presented in this paper relate to a particular territory, the
Corsica Island, but as data used are available for the entire surface of the
globe, our method can be easily exploited to another place. Indeed 2-D hourly
time series are extracted from the HelioClim-3 surface solar irradiation
database treated by the Heliosat-2 model. Each point of the map have been used
as training data and inputs of artificial neural networks (ANN) and as inputs
for two persistence models (scaled or not). Comparisons between these models
and clear sky estimations were proceeded to evaluate the performances. We found
a normalized root mean square error (nRMSE) close to 16.5% for the two best
predictors (scaled persistence and ANN) equivalent to 35-45% related to ground
measurements. Finally in order to validate our 2-D predictions maps, we
introduce a new error metric called the gamma index which is a criterion for
comparing data from two matrixes in medical physics. As first results, we found
that in winter and spring, scaled persistence gives the best results (gamma
index test passing rate is respectively 67.7% and 86%), in autumn simple
persistence is the best predictor (95.3%) and ANN is the best in summer
(99.8%).
|
1401.4648 | Visual Tracking using Particle Swarm Optimization | cs.CV | The problem of robust extraction of visual odometry from a sequence of images
obtained by an eye in hand camera configuration is addressed. A novel approach
toward solving planar template based tracking is proposed which performs a
non-linear image alignment for successful retrieval of camera transformations.
In order to obtain global optimum a bio-metaheuristic is used for optimization
of similarity among the planar regions. The proposed method is validated on
image sequences with real as well as synthetic transformations and found to be
resilient to intensity variations. A comparative analysis of the various
similarity measures as well as various state-of-art methods reveal that the
algorithm succeeds in tracking the planar regions robustly and has good
potential to be used in real applications.
|
1401.4650 | A Gray Code for cross-bifix-free sets | cs.IT cs.DM math.CO math.IT | A cross-bifix-free set of words is a set in which no prefix of any length of
any word is the suffix of any other word in the set. A construction of
cross-bifix-free sets has recently been proposed by Chee {\it et al.} in 2013
within a constant factor of optimality. We propose a \emph{trace partitioned}
Gray code for these cross-bifix-free sets and a CAT algorithm generating it.
|
1401.4657 | Power Control Factor Selection in Uplink OFDMA Cellular Networks | cs.IT math.IT | Uplink power control plays a key role on the performance of uplink cellular
network. In this work, the power control factor ($\in[0,1]$) is evaluated based
on three parameters namely: average transmit power, coverage probability and
average rate. In other words, we evaluate power control factor such that
average transmit power should be low, coverage probability of cell-edge users
should be high and also average rate over all the uplink users should be high.
We show through numerical studies that the power control factor should be close
to $0.5$ in order to achieve an acceptable trade-off between these three
parameters.
|
1401.4660 | On the Resilience of an Ant-based System in Fuzzy Environments. An
Empirical Study | cs.NE | The current work describes an empirical study conducted in order to
investigate the behavior of an optimization method in a fuzzy environment.
MAX-MIN Ant System, an efficient implementation of a heuristic method is used
for solving an optimization problem derived from the Traveling Salesman Problem
(TSP). Several publicly-available symmetric TSP instances and their fuzzy
variants are tested in order to extract some general features. The entry data
was adapted by introducing a two-dimensional systematic degree of fuzziness,
proportional with the number of nodes, the dimension of the instance and also
with the distances between nodes, the scale of the instance. The results show
that our proposed method can handle the data uncertainty, showing good
resilience and adaptability.
|
1401.4662 | Optimal Thresholds for Coverage and Rate in FFR Schemes for Planned
Cellular Networks | cs.IT math.IT | Fractional frequency reuse (FFR) is an inter-cell interference coordination
scheme that is being actively researched for emerging wireless cellular
networks. In this work, we consider hexagonal tessellation based planned FFR
deployments, and derive expressions for the coverage probability and normalized
average rate for the downlink. In particular, given reuse $\frac{1}{3}$ (FR$3$
) and reuse $1$ (FR$1$) regions, and a Signal-to-Interference-plus-noise-Ratio
(SINR) threshold $S_{th}$ which decides the user assignment to either the FR$1$
or FR$3$ regions, we theoretically show that: $(i)$ The optimal choice of
$S_{th}$ which maximizes the coverage probability is $S_{th} = T$, where $T$ is
the required target SINR (for ensuring coverage), and $(ii)$ The optimal choice
of $S_{th}$ which maximizes the normalized average rate is given by the
expression $S_{th}=\max(T, T')$, where $T'$ is a function of the path loss
exponent and the fade parameters. For the optimal choice of $S_{th}$, we show
that FFR gives a higher rate than FR$1$ and a better coverage probability than
FR$3$. The impact of frequency correlation over the sub-bands allocated to the
FR$1$ and FR$3$ regions is analysed, and it is shown that correlation decreases
the average rate of the FFR network. Numerical results are provided, and these
match with the analytical results.
|
1401.4663 | Impact of Correlation between Nakagami-m Interferers on Coverage
Probability and Rate in Cellular Systems | cs.IT math.IT | Coverage probability and rate expressions are theoretically compared for the
following cases: $(i).$ Both the user channel and the $N$ interferers are
independent and non identical Nakagami-m distributed random variables (RVs).
$(ii).$ The $N$ interferers are correlated Nakagami-m RVs. It is analytically
shown that the coverage probability in the presence of correlated interferers
is greater than or equal to the coverage probability in the presence of
non-identical independent interferers when the shape parameter of the channel
between the user and its base station is not greater than one. It is further
analytically shown that the average rate in the presence of correlated
interferers is greater than or equal to the average rate in the presence of
non-identical independent interferers. Simulation results are provided and
these match with the obtained theoretical results. The utility of our results
are also discussed.
|
1401.4672 | Parallel versus Sequential Update and the Evolution of Cooperation with
the Assistance of Emotional Strategies | physics.soc-ph cs.SI | Our study contributes to the debate on the evolution of cooperation in the
single-shot Prisoner's Dilemma (PD) played on networks. We construct a model in
which individuals are connected with positive and negative ties. Some agents
play sign-dependent strategies that use the sign of the relation as a shorthand
for determining appropriate action toward the opponent. In the context of our
model in which network topology, agent strategic types and relational signs
coevolve, the presence of sign-dependent strategies catalyzes the evolution of
cooperation. We highlight how the success of cooperation depends on a crucial
aspect of implementation: whether we apply parallel or sequential strategy
update. Parallel updating, with averaging of payoffs across interactions in the
social neighborhood, supports cooperation in a much wider set of parameter
values than sequential updating. Our results cast doubts about the realism and
generalizability of models that claim to explain the evolution of cooperation
but implicitly assume parallel updating.
|
1401.4674 | Evolving Accuracy: A Genetic Algorithm to Improve Election Night
Forecasts | cs.NE | In this paper, we apply genetic algorithms to the field of electoral studies.
Forecasting election results is one of the most exciting and demanding tasks in
the area of market research, especially due to the fact that decisions have to
be made within seconds on live television. We show that the proposed method
outperforms currently applied approaches and thereby provide an argument to
tighten the intersection between computer science and social science,
especially political science, further. We scrutinize the performance of our
algorithm's runtime behavior to evaluate its applicability in the field.
Numerical results with real data from a local election in the Austrian province
of Styria from 2010 substantiate the applicability of the proposed approach.
|
1401.4676 | Universal hierarchical behavior of citation networks | physics.soc-ph cs.DL cs.SI physics.data-an | Many of the essential features of the evolution of scientific research are
imprinted in the structure of citation networks. Connections in these networks
imply information about the transfer of knowledge among papers, or in other
words, edges describe the impact of papers on other publications. This inherent
meaning of the edges infers that citation networks can exhibit hierarchical
features, that is typical of networks based on decision-making. In this paper,
we investigate the hierarchical structure of citation networks consisting of
papers in the same field. We find that the majority of the networks follow a
universal trend towards a highly hierarchical state, and i) the various fields
display differences only concerning their phase in life (distance from the
"birth" of a field) or ii) the characteristic time according to which they are
approaching the stationary state. We also show by a simple argument that the
alterations in the behavior are related to and can be understood by the degree
of specialization corresponding to the fields. Our results suggest that during
the accumulation of knowledge in a given field, some papers are gradually
becoming relatively more influential than most of the other papers.
|
1401.4680 | Multiple Hybrid Phase Transition: Bootstrap Percolation on Complex
Networks with Communities | physics.soc-ph cs.SI | Bootstrap percolation is a well-known model to study the spreading of rumors,
new products or innovations on social networks. The empirical studies show that
community structure is ubiquitous among various social networks. Thus, studying
the bootstrap percolation on the complex networks with communities can bring us
new and important insights of the spreading dynamics on social networks. It
attracts a lot of scientists' attentions recently. In this letter, we study the
bootstrap percolation on Erd\H{o}s-R\'{e}nyi networks with communities and
observed second order, hybrid (both second and first order) and multiple hybrid
phase transitions, which is rare in natural system. Moreover, we have
analytically solved this system and obtained the phase diagram, which is
further justified well by the corresponding simulations.
|
1401.4691 | An algorithm for calculating steady state probabilities of $M|E_r|c|K$
queueing systems | cs.SY cs.PF | This paper presents a method for calculating steady state probabilities of
$M|E_r|c|K$ queueing systems. The infinitesimal generator matrix is used to
define all possible states in the system and their transition probabilities.
While this matrix can be written down immediately for many other $M|PH|c|K$
queueing systems with phase-type service times (e.g. Coxian, Hypoexponential,
\ldots), it requires a more careful analysis for systems with Erlangian service
times. The constructed matrix may then be used to calculate steady state
probabilities using an iterative algorithm. The resulting steady state
probabilities can be used to calculate various performance measures, e.g. the
average queue length. Additionally, computational issues of the implementation
are discussed and an example from the field of telecommunication call-center
queue length will be outlined to substantiate the applicability of these
efforts. In the appendix, tables of the average queueing length given a
specific number of service channels, traffic density, and system size are
presented.
|
1401.4696 | Evolutionary Optimization for Decision Making under Uncertainty | cs.NE | Optimizing decision problems under uncertainty can be done using a variety of
solution methods. Soft computing and heuristic approaches tend to be powerful
for solving such problems. In this overview article, we survey Evolutionary
Optimization techniques to solve Stochastic Programming problems - both for the
single-stage and multi-stage case.
|
1401.4709 | Adaptive Power Allocation Strategies using DSTC in Cooperative MIMO
Networks | cs.IT math.IT | Adaptive Power Allocation (PA) algorithms with different criteria for a
cooperative Multiple-Input Multiple-Output (MIMO) network equipped with
Distributed Space-Time Coding (DSTC) are proposed and evaluated. Joint
constrained optimization algorithms to determine the power allocation
parameters, the channel parameters and the receive filter are proposed for each
transmitted stream in each link. Linear receive filter and maximum-likelihood
(ML) detection are considered with Amplify-and-Forward (AF) and
Decode-and-Forward (DF) cooperation strategies. In the proposed algorithms, the
elements in the PA matrices are optimized at the destination node and then
transmitted back to the relay nodes via a feedback channel. The effects of the
feedback errors are considered. Linear MMSE expressions and the PA matrices
depend on each other and are updated iteratively. Stochastic gradient (SG)
algorithms are developed with reduced computational complexity. Simulation
results show that the proposed algorithms obtain significant performance gains
as compared to existing power allocation schemes.
|
1401.4714 | Revolutionary Algorithms | cs.NE | The optimization of dynamic problems is both widespread and difficult. When
conducting dynamic optimization, a balance between reinitialization and
computational expense has to be found. There are multiple approaches to this.
In parallel genetic algorithms, multiple sub-populations concurrently try to
optimize a potentially dynamic problem. But as the number of sub-population
increases, their efficiency decreases. Cultural algorithms provide a framework
that has the potential to make optimizations more efficient. But they adapt
slowly to changing environments. We thus suggest a confluence of these
approaches: revolutionary algorithms. These algorithms seek to extend the
evolutionary and cultural aspects of the former to approaches with a notion of
the political. By modeling how belief systems are changed by means of
revolution, these algorithms provide a framework to model and optimize dynamic
problems in an efficient fashion.
|
1401.4715 | Construction of Partial MDS (PMDS) and Sector-Disk (SD) Codes with Two
Global Parity Symbols | cs.IT math.IT | Partial MDS (PMDS) codes are erasure codes combining local (row) correction
with global additional correction of entries, while Sector-Disk (SD) codes are
erasure codes that address the mixed failure mode of current RAID systems. It
has been an open problem to construct general codes that have the PMDS and the
SD properties, and previous work has relied on Monte-Carlo searches. In this
paper, we present a general construction that addresses the case of any number
of failed disks and in addition, two erased sectors. The construction requires
a modest field size. This result generalizes previous constructions extending
RAID~5 and RAID~6.
|
1401.4725 | Information profiles for DNA pattern discovery | q-bio.GN cs.IT math.IT | Finite-context modeling is a powerful tool for compressing and hence for
representing DNA sequences. We describe an algorithm to detect genomic
regularities, within a blind discovery strategy. The algorithm uses information
profiles built using suitable combinations of finite-context models. We used
the genome of the fission yeast Schizosaccharomyces pombe strain 972 h- for
illustration, unveilling locations of low information content, which are
usually associated with DNA regions of potential biological interest.
|
1401.4734 | Optimal Fractional Repetition Codes based on Graphs and Designs | cs.IT cs.DM math.IT | Fractional repetition (FR) codes is a family of codes for distributed storage
systems that allow for uncoded exact repairs having the minimum repair
bandwidth. However, in contrast to minimum bandwidth regenerating (MBR) codes,
where a random set of a certain size of available nodes is used for a node
repair, the repairs with FR codes are table based. This usually allows to store
more data compared to MBR codes. In this work, we consider bounds on the
fractional repetition capacity, which is the maximum amount of data that can be
stored using an FR code. Optimal FR codes which attain these bounds are
presented. The constructions of these FR codes are based on combinatorial
designs and on families of regular and biregular graphs. These constructions of
FR codes for given parameters raise some interesting questions in graph theory.
These questions and some of their solutions are discussed in this paper. In
addition, based on a connection between FR codes and batch codes, we propose a
new family of codes for DSS, namely fractional repetition batch codes, which
have the properties of batch codes and FR codes simultaneously. These are the
first codes for DSS which allow for uncoded efficient exact repairs and load
balancing which can be performed by several users in parallel. Other concepts
related to FR codes are also discussed.
|
1401.4740 | Generalization of the PageRank Model | cs.SI cs.IR | This paper develops a generalization of the PageRank model of page
centralities in the global webgraph of hyperlinks. The webgraph of adjacencies
is generalized to a valued directed graph, and the scalar dampening coefficient
for walks through the graph is relaxed to allow for heterogeneous values. A
visitation count approach may be employed to apply the more general model,
based on the number of visits to a page and the page's proportionate
allocations of these visits to other nodes of the webgraph.
|
1401.4750 | How Much Frequency Can Be Reused in 5G Cellular Networks---A Matrix
Graph Model | cs.IT math.IT | The 5th Generation cellular network may have the key feature of smaller cell
size and denser resource employment, resulted from diminishing resource and
increasing communication demands. However, small cell may result in high
interference between cells. Moreover, the random geographic patterns of small
cell networks make them hard to analyze, at least excluding schemes in the
well-accepted hexagonal grid model. In this paper, a new model---the matrix
graph is proposed which takes advantage of the small cell size and high
inter-cell interference to reduce computation complexity. This model can
simulate real world networks accurately and offers convenience in frequency
allocation problems which are usually NP-complete. An algorithm dealing with
this model is also given, which asymptotically achieves the theoretical limit
of frequency allocation, and has a complexity which decreases with cell size
and grows linearly with the network size. This new model is specifically
proposed to characterize the next-generation cellular networks.
|
1401.4753 | Multi-Branch Tomlinson-Harashima Precoding for MU-MIMO Systems: Theory
and Algorithms | cs.IT math.IT | Tomlinson-Harashima precoding (THP) is a nonlinear processing technique
employed at the transmit side and is a dual to the successive interference
cancelation (SIC) detection at the receive side. Like SIC detection, the
performance of THP strongly depends on the ordering of the precoded symbols.
The optimal ordering algorithm, however, is impractical for multiuser MIMO
(MU-MIMO) systems with multiple receive antennas due to the fact that the users
are geographically distributed. In this paper, we propose a multi-branch THP
(MB-THP) scheme and algorithms that employ multiple transmit processing and
ordering strategies along with a selection scheme to mitigate interference in
MU-MIMO systems. Two types of multi-branch THP (MB-THP) structures are
proposed. The first one employs a decentralized strategy with diagonal weighted
filters at the receivers of the users and the second uses a diagonal weighted
filter at the transmitter. The MB-MMSE-THP algorithms are also derived based on
an extended system model with the aid of an LQ decomposition, which is much
simpler compared to the conventional MMSE-THP algorithms. Simulation results
show that a better bit error rate (BER) performance can be achieved by the
proposed MB-MMSE-THP precoder with a small computational complexity increase.
|
1401.4786 | Common Information based Markov Perfect Equilibria for Linear-Gaussian
Games with Asymmetric Information | cs.SY cs.GT math.OC | We consider a class of two-player dynamic stochastic nonzero-sum games where
the state transition and observation equations are linear, and the primitive
random variables are Gaussian. Each controller acquires possibly different
dynamic information about the state process and the other controller's past
actions and observations. This leads to a dynamic game of asymmetric
information among the controllers. Building on our earlier work on finite games
with asymmetric information, we devise an algorithm to compute a Nash
equilibrium by using the common information among the controllers. We call such
equilibria common information based Markov perfect equilibria of the game,
which can be viewed as a refinement of Nash equilibrium in games with
asymmetric information. If the players' cost functions are quadratic, then we
show that under certain conditions a unique common information based Markov
perfect equilibrium exists. Furthermore, this equilibrium can be computed by
solving a sequence of linear equations. We also show through an example that
there could be other Nash equilibria in a game of asymmetric information, not
corresponding to common information based Markov perfect equilibria.
|
1401.4788 | Generalized Bhattacharyya and Chernoff upper bounds on Bayes error using
quasi-arithmetic means | cs.CV cs.IT math.IT | Bayesian classification labels observations based on given prior information,
namely class-a priori and class-conditional probabilities. Bayes' risk is the
minimum expected classification cost that is achieved by the Bayes' test, the
optimal decision rule. When no cost incurs for correct classification and unit
cost is charged for misclassification, Bayes' test reduces to the maximum a
posteriori decision rule, and Bayes risk simplifies to Bayes' error, the
probability of error. Since calculating this probability of error is often
intractable, several techniques have been devised to bound it with closed-form
formula, introducing thereby measures of similarity and divergence between
distributions like the Bhattacharyya coefficient and its associated
Bhattacharyya distance. The Bhattacharyya upper bound can further be tightened
using the Chernoff information that relies on the notion of best error
exponent. In this paper, we first express Bayes' risk using the total variation
distance on scaled distributions. We then elucidate and extend the
Bhattacharyya and the Chernoff upper bound mechanisms using generalized
weighted means. We provide as a byproduct novel notions of statistical
divergences and affinity coefficients. We illustrate our technique by deriving
new upper bounds for the univariate Cauchy and the multivariate
$t$-distributions, and show experimentally that those bounds are not too
distant to the computationally intractable Bayes' error.
|
1401.4799 | LDPC Codes for Partial-Erasure Channels in Multi-Level Memories | cs.IT math.IT | In this paper, we develop a new channel model, which we name the $q$-ary
partial erasure channel (QPEC). QPEC has a $q$-ary input, and its output is
either one symbol or a set of $M$ possible values. This channel mimics
situations when current/voltage levels in measurement channels are only
partially known, due to high read rates or imperfect current/voltage sensing.
Our investigation is concentrated on the performance of low-density
parity-pheck (LDPC) codes when used over this channel, due to their low
decoding complexity with iterative-decoding algorithms. We give the density
evolution equations of this channel, and develop its decoding-threshold
analysis. Part of the analysis shows that finding the exact decoding threshold
efficiently lies upon a solution to an open problem in additive combinatorics.
For this part we give bounds and approximations.
|
1401.4831 | Approximate Capacities of Two-Dimensional Codes by Spatial Mixing | cs.IT math.IT | We apply several state-of-the-art techniques developed in recent advances of
counting algorithms and statistical physics to study the spatial mixing
property of the two-dimensional codes arising from local hard (independent set)
constraints, including: hard-square, hard-hexagon, read/write isolated memory
(RWIM), and non-attacking kings (NAK). For these constraints, the strong
spatial mixing would imply the existence of polynomial-time approximation
scheme (PTAS) for computing the capacity. It was previously known for the
hard-square constraint the existence of strong spatial mixing and PTAS. We show
the existence of strong spatial mixing for hard-hexagon and RWIM constraints by
establishing the strong spatial mixing along self-avoiding walks, and
consequently we give PTAS for computing the capacities of these codes. We also
show that for the NAK constraint, the strong spatial mixing does not hold along
self-avoiding walks.
|
1401.4834 | On Low-Complexity Full-diversity Detection In Multi-User MIMO
Multiple-Access Channels | cs.IT math.IT | Multiple-input multiple-output (MIMO) techniques are becoming commonplace in
recent wireless communication standards. This added dimension (i.e., space) can
be efficiently used to mitigate the interference in the multi-user MIMO
context. In this paper, we focus on the uplink of a MIMO multiple access
channel (MAC) where perfect channel state information (CSI) is only available
at the destination. We provide a new set of sufficient conditions for a wide
range of space-time block codes (STBC)s to achieve full-diversity under
\emph{partial interference cancellation group decoding} (PICGD) with or without
successive interference cancellation (SIC) for completely blind users. Explicit
interference cancellation (IC) schemes for two and three users are then
provided and shown to satisfy the derived full-diversity criteria. Besides the
complexity reduction due to the fact that the proposed IC schemes enable
separate decoding of distinct users without sacrificing the diversity gain,
further reduction of the decoding complexity may be obtained. In fact, thanks
to the structure of the proposed schemes, the real and imaginary parts of each
user's symbols may be decoupled without any loss of performance. Finally, our
theoretical claims are corroborated by simulation results and the new IC scheme
for two-user MIMO MAC is shown to outperform the recently proposed two-user IC
scheme especially for high spectral efficiency while requiring significantly
less decoding complexity.
|
1401.4840 | Termination of oblivious chase is undecidable | cs.DB | We show that all--instances termination of chase is undecidable. More
precisely, there is no algorithm deciding, for a given set $\cal T$ consisting
of Tuple Generating Dependencies (a.k.a. Datalog$^\exists$ program), whether
the $\cal T$-chase on $D$ will terminate for every finite database instance
$D$. Our method applies to Oblivious Chase, Semi-Oblivious Chase and -- after a
slight modification -- also for Standard Chase. This means that we give a
(negative) solution to the all--instances termination problem for all version
of chase that are usually considered.
The arity we need for our undecidability proof is three. We also show that
the problem is EXPSPACE-hard for binary signatures, but decidability for this
case is left open.
Both the proofs -- for ternary and binary signatures -- are easy. Once you
know them.
|
1401.4848 | An Evolutionary Approach towards Clustering Airborne Laser Scanning Data | cs.NE | In land surveying, the generation of maps was greatly simplified with the
introduction of orthophotos and at a later stage with airborne LiDAR laser
scanning systems. While the original purpose of LiDAR systems was to determine
the altitude of ground elevations, newer full wave systems provide additional
information that can be used on classifying the type of ground cover and the
generation of maps. The LiDAR resulting point clouds are huge, multidimensional
data sets that need to be grouped in classes of ground cover. We propose a
genetic algorithm that aids in classifying these data sets and thus make them
usable for map generation. A key feature are tailor-made genetic operators and
fitness functions for the subject. The algorithm is compared to a traditional
k-means clustering.
|
1401.4849 | On the influence of the seed graph in the preferential attachment model | math.PR cs.DM cs.SI math.ST stat.TH | We study the influence of the seed graph in the preferential attachment
model, focusing on the case of trees. We first show that the seed has no effect
from a weak local limit point of view. On the other hand, we conjecture that
different seeds lead to different distributions of limiting trees from a total
variation point of view. We take a first step in proving this conjecture by
showing that seeds with different degree profiles lead to different limiting
distributions for the (appropriately normalized) maximum degree, implying that
such seeds lead to different (in total variation) limiting trees.
|
1401.4857 | A Genetic Algorithm to Optimize a Tweet for Retweetability | cs.NE cs.CY cs.SI physics.soc-ph | Twitter is a popular microblogging platform. When users send out messages,
other users have the ability to forward these messages to their own subgraph.
Most research focuses on increasing retweetability from a node's perspective.
Here, we center on improving message style to increase the chance of a message
being forwarded. To this end, we simulate an artificial Twitter-like network
with nodes deciding deterministically on retweeting a message or not. A genetic
algorithm is used to optimize message composition, so that the reach of a
message is increased. When analyzing the algorithm's runtime behavior across a
set of different node types, we find that the algorithm consistently succeeds
in significantly improving the retweetability of a message.
|
1401.4869 | Does Syntactic Knowledge help English-Hindi SMT? | cs.CL cs.AI | In this paper we explore various parameter settings of the state-of-art
Statistical Machine Translation system to improve the quality of the
translation for a `distant' language pair like English-Hindi. We proposed new
techniques for efficient reordering. A slight improvement over the baseline is
reported using these techniques. We also show that a simple pre-processing step
can improve the quality of the translation significantly.
|
1401.4872 | Classification of IDS Alerts with Data Mining Techniques | cs.CR cs.DB cs.LG | A data mining technique to reduce the amount of false alerts within an IDS
system is proposed. The new technique achieves an accuracy of 99% compared to
97% by the current systems.
|
1401.4907 | Impact of Transceiver Power Consumption on the Energy Efficiency of
Zero-Forcing Detector in Massive MIMO Systems | cs.IT math.IT | We consider the impact of transceiver power consumption on the energy
efficiency (EE) of the Zero Forcing (ZF) detector in the uplink of massive MIMO
systems, where a base station (BS) with $M$ antennas communicates coherently
with $K$ single antenna user terminals (UTs). We consider the problem of
maximizing the EE with respect to (M,K) for a fixed sum spectral efficiency.
Through analysis we study the impact of system parameters on the optimal EE.
System parameters consists of the average channel gain to the users and the
power consumption parameters (PCPs) (e.g., power consumed by each RF
antenna/receiver at BS). When the average user channel gain is high or else the
BS/UT design is power inefficient, our analysis reveals that it is optimal to
have a few BS antennas and a single user, i.e., non-massive MIMO regime.
Similarly, when the channel gain is small or else the BS/UT design is power
efficient, it is optimal of have a larger (M,K), i.e., massive MIMO regime.
Tight analytical bounds on the optimal EE are proposed for both these regimes.
The impact of the system parameters on the optimal EE is studied and several
interesting insights are drawn.
|
1401.4912 | An Importance Sampling Scheme on Dual Factor Graphs. I. Models in a
Strong External Field | stat.CO cond-mat.stat-mech cs.IT math.IT | We propose an importance sampling scheme to estimate the partition function
of the two-dimensional ferromagnetic Ising model and the two-dimensional
ferromagnetic $q$-state Potts model, both in the presence of an external
magnetic field. The proposed scheme operates in the dual Forney factor graph
and is capable of efficiently computing an estimate of the partition function
under a wide range of model parameters. In particular, we consider models that
are in a strong external magnetic field.
|
1401.4935 | Performance Analysis of a Network of Event-based Systems | cs.SY cs.NI | We consider a scenario where multiple event-based systems use a wireless
network to communicate with their respective controllers. These systems use a
contention resolution mechanism (CRM) to arbitrate access to the network. We
present a Markov model for the network interactions between the event-based
systems. Using this model, we obtain an analytical expression for the
reliability, or the probability of successfully transmitting a packet, in this
network. There are two important aspects to our model. Firstly, our model
captures the joint interactions of the event-triggering policy and the CRM.
This is required because event-triggering policies typically adapt to the CRM
outcome. Secondly, the model is obtained by decoupling interactions between the
different systems in the network, drawing inspiration from Bianchi's analysis
of IEEE 802.11. This is required because the network interactions introduce a
correlation between the system variables. We present Monte-Carlo simulations
that validate our model under various network configurations, and verify our
performance analysis as well.
|
1401.4936 | Low-Complexity Robust Data-Adaptive Dimensionality Reduction Based on
Joint Iterative Optimization of Parameters | cs.IT math.IT | This paper presents a low-complexity robust data-dependent dimensionality
reduction based on a modified joint iterative optimization (MJIO) algorithm for
reduced-rank beamforming and steering vector estimation. The proposed robust
optimization procedure jointly adjusts the parameters of a rank-reduction
matrix and an adaptive beamformer. The optimized rank-reduction matrix projects
the received signal vector onto a subspace with lower dimension. The
beamformer/steering vector optimization is then performed in a
reduced-dimension subspace. We devise efficient stochastic gradient and
recursive least-squares algorithms for implementing the proposed robust MJIO
design. The proposed robust MJIO beamforming algorithms result in a faster
convergence speed and an improved performance. Simulation results show that the
proposed MJIO algorithms outperform some existing full-rank and reduced-rank
algorithms with a comparable complexity.
|
1401.4942 | Info-computational constructivism in modelling of life as cognition | cs.AI | This paper addresses the open question formulated as: Which levels of
abstraction are appropriate in the synthetic modelling of life and cognition?
within the framework of info-computational constructivism, treating natural
phenomena as computational processes on informational structures. At present we
lack the common understanding of the processes of life and cognition in living
organisms with the details of co-construction of informational structures and
computational processes in embodied, embedded cognizing agents, both living and
artifactual ones. Starting with the definition of an agent as an entity capable
of acting on its own behalf, as an actor in Hewitt Actor model of computation,
even so simple systems as molecules can be modelled as actors exchanging
messages (information). We adopt Kauffmans view of a living agent as something
that can reproduce and undergoes at least one thermodynamic work cycle. This
definition of living agents leads to the Maturana and Varelas identification of
life with cognition. Within the info-computational constructive approach to
living beings as cognizing agents, from the simplest to the most complex living
systems, mechanisms of cognition can be studied in order to construct synthetic
model classes of artifactual cognizing agents on different levels of
organization.
|
1401.4944 | Iterative pre-distortion of the non-linear satellite channel | cs.IT math.IT | Digital Video Broadcasting - Satellite - Second Generation (DVB-S2) is the
current European standard for satellite broadcast and broadband communications.
It relies on high order modulations up to 32-amplitude/phase-shift-keying
(APSK) in order to increase the system spectral efficiency. Unfortunately, as
the modulation order increases, the receiver becomes more sensitive to physical
layer impairments, and notably to the distortions induced by the power
amplifier and the channelizing filters aboard the satellite. Pre-distortion of
the non-linear satellite channel has been studied for many years. However, the
performance of existing pre-distortion algorithms generally becomes poor when
high-order modulations are used on a non-linear channel with a long memory. In
this paper, we investigate a new iterative method that pre-distorts blocks of
transmitted symbols so as to minimize the Euclidian distance between the
transmitted and received symbols. We also propose approximations to relax the
pre-distorter complexity while keeping its performance acceptable.
|
1401.4952 | Packing circles within circular containers: a new heuristic algorithm
for the balance constraints case | cs.CG cs.CE | In this work we propose a heuristic algorithm for the layout optimization for
disks installed in a rotating circular container. This is a unequal circle
packing problem with additional balance constraints. It proved to be an NP-hard
problem, which justifies heuristics methods for its resolution in larger
instances. The main feature of our heuristic is based on the selection of the
next circle to be placed inside the container according to the position of the
system's center of mass. Our approach has been tested on a series of instances
up to 55 circles and compared with the literature. Computational results show
good performance in terms of solution quality and computational time for the
proposed algorithm.
|
1401.4994 | A Review of Verbal and Non-Verbal Human-Robot Interactive Communication | cs.RO cs.CL | In this paper, an overview of human-robot interactive communication is
presented, covering verbal as well as non-verbal aspects of human-robot
interaction. Following a historical introduction, and motivation towards fluid
human-robot communication, ten desiderata are proposed, which provide an
organizational axis both of recent as well as of future research on human-robot
communication. Then, the ten desiderata are examined in detail, culminating to
a unifying discussion, and a forward-looking conclusion.
|
1401.5004 | Stability Analysis and Design of a Network of Event-based Systems | cs.SY | We consider a network of event-based systems that use a shared wireless
medium to communicate with their respective controllers. These systems use a
contention resolution mechanism to arbitrate access to the shared network. We
identify sufficient conditions for Lyapunov mean square stability of each
control system in the network, and design event-based policies that guarantee
it. Our stability analysis is based on a Markov model that removes the
network-induced correlation between the states of the control systems in the
network. Analyzing the stability of this Markov model remains a challenge, as
the event-triggering policy renders the estimation error non-Gaussian. Hence,
we identify an auxiliary system that furnishes an upper bound for the variance
of the system states. Using the stability analysis, we design policies, such as
the constant-probability policy, for adapting the event-triggering thresholds
to the delay in accessing the network. Realistic wireless networked control
examples illustrate the applicability of the presented approach.
|
1401.5027 | Tie Strength Distribution in Scientific Collaboration Networks | physics.soc-ph cs.SI | Science is increasingly dominated by teams. Understanding patterns of
scientific collaboration and their impacts on the productivity and evolution of
disciplines is crucial to understand scientific processes. Electronic
bibliography offers a unique opportunity to map and investigate the nature of
scientific collaboration. Recent work have demonstrated a counter-intuitive
organizational pattern of scientific collaboration networks: densely
interconnected local clusters consist of weak ties, whereas strong ties play
the role of connecting different clusters. This pattern contrasts itself from
many other types of networks where strong ties form communities while weak ties
connect different communities. Although there are many models for collaboration
networks, no model reproduces this pattern. In this paper, we present an
evolution model of collaboration networks, which reproduces many properties of
real-world collaboration networks, including the organization of tie strengths,
skewed degree and weight distribution, high clustering and assortative mixing.
|
1401.5031 | A Scalable Conditional Independence Test for Nonlinear, Non-Gaussian
Data | cs.AI stat.ME | Many relations of scientific interest are nonlinear, and even in linear
systems distributions are often non-Gaussian, for example in fMRI BOLD data. A
class of search procedures for causal relations in high dimensional data relies
on sample derived conditional independence decisions. The most common
applications rely on Gaussian tests that can be systematically erroneous in
nonlinear non-Gaussian cases. Recent work (Gretton et al. (2009), Tillman et
al. (2009), Zhang et al. (2011)) has proposed conditional independence tests
using Reproducing Kernel Hilbert Spaces (RKHS). Among these, perhaps the most
efficient has been KCI (Kernel Conditional Independence, Zhang et al. (2011)),
with computational requirements that grow effectively at least as O(N3),
placing it out of range of large sample size analysis, and restricting its
applicability to high dimensional data sets. We propose a class of O(N2) tests
using conditional correlation independence (CCI) that require a few seconds on
a standard workstation for tests that require tens of minutes to hours for the
KCI method, depending on degree of parallelization, with similar accuracy. For
accuracy on difficult nonlinear, non-Gaussian data sets, we also compare a
recent test due to Harris & Drton (2012), applicable to nonlinear, non-Gaussian
distributions in the Gaussian copula, as well as to partial correlation, a
linear Gaussian test.
|
1401.5037 | Achieving SK Capacity in the Source Model: When Must All Terminals Talk? | cs.IT math.IT | In this paper, we address the problem of characterizing the instances of the
multiterminal source model of Csisz\'ar and Narayan in which communication from
all terminals is needed for establishing a secret key of maximum rate. We give
an information-theoretic sufficient condition for identifying such instances.
We believe that our sufficient condition is in fact an exact characterization,
but we are only able to prove this in the case of the three-terminal source
model. We also give a relatively simple criterion for determining whether or
not our condition holds for a given multiterminal source model.
|
1401.5039 | Experimental Design for Human-in-the-Loop Driving Simulations | cs.SY cs.HC | This report describes a new experimental setup for human-in-the-loop
simulations. A force feedback simulator with four axis motion has been setup
for real-time driving experiments. The simulator will move to simulate the
forces a driver feels while driving, which allows for a realistic experience
for the driver. This setup allows for flexibility and control for the
researcher in a realistic simulation environment. Experiments concerning driver
distraction can also be carried out safely in this test bed, in addition to
multi-agent experiments. All necessary code to run the simulator, the
additional sensors, and the basic processing is available for use.
|
1401.5051 | WaterFowl, a Compact, Self-indexed RDF Store with Inference-enabled
Dictionaries | cs.DB | In this paper, we present a novel approach -- called WaterFowl -- for the
storage of RDF triples that addresses some key issues in the contexts of big
data and the Semantic Web. The architecture of our prototype, largely based on
the use of succinct data structures, enables the representation of triples in a
self-indexed, compact manner without requiring decompression at query answering
time. Moreover, it is adapted to efficiently support RDF and RDFS entailment
regimes thanks to an optimized encoding of ontology concepts and properties
that does not require a complete inference materialization or extensive query
rewriting algorithms. This approach implies to make a distinction between the
terminological and the assertional components of the knowledge base early in
the process of data preparation, i.e., preprocessing the data before storing it
in our structures. The paper describes the complete architecture of this system
and presents some preliminary results obtained from evaluations conducted on
our first prototype.
|
1401.5054 | An\'alisis e implementaci\'on de algoritmos evolutivos para la
optimizaci\'on de simulaciones en ingenier\'ia civil. (draft) | cs.NE cs.AI | This paper studies the applicability of evolutionary algorithms,
particularly, the evolution strategies family in order to estimate a
degradation parameter in the shear design of reinforced concrete members. This
problem represents a great computational task and is highly relevant in the
framework of the structural engineering that for the first time is solved using
genetic algorithms.
You are viewing a draft, the authors appreciate corrections, comments and
suggestions to this work.
|
1401.5092 | Symmetric Two-User Gaussian Interference Channel with Common Messages | cs.IT math.IT | We consider symmetric two-user Gaussian interference channel with common
messages. We derive an upper bound on the sum capacity, and show that the upper
bound is tight in the low interference regime, where the optimal transmission
scheme is to send no common messages and each receiver treats interference as
noise. Our result shows that although the availability of common messages
provides a cooperation opportunity for transmitters, in the low interference
regime the presence of common messages does not help increase the sum capacity.
|
1401.5093 | Localization and centrality in networks | cs.SI cond-mat.stat-mech physics.soc-ph | Eigenvector centrality is a common measure of the importance of nodes in a
network. Here we show that under common conditions the eigenvector centrality
displays a localization transition that causes most of the weight of the
centrality to concentrate on a small number of nodes in the network. In this
regime the measure is no longer useful for distinguishing among the remaining
nodes and its efficacy as a network metric is impaired. As a remedy, we propose
an alternative centrality measure based on the nonbacktracking matrix, which
gives results closely similar to the standard eigenvector centrality in dense
networks where the latter is well behaved, but avoids localization and gives
useful results in regimes where the standard centrality fails.
|
1401.5098 | Study of Efficient Technique Based On 2D Tsallis Entropy For Image
Thresholding | cs.CV | Thresholding is an important task in image processing. It is a main tool in
pattern recognition, image segmentation, edge detection and scene analysis. In
this paper, we present a new thresholding technique based on two-dimensional
Tsallis entropy. The two-dimensional Tsallis entropy was obtained from the
twodimensional histogram which was determined by using the gray value of the
pixels and the local average gray value of the pixels, the work it was applied
a generalized entropy formalism that represents a recent development in
statistical mechanics. The effectiveness of the proposed method is demonstrated
by using examples from the real-world and synthetic images. The performance
evaluation of the proposed technique in terms of the quality of the thresholded
images are presented. Experimental results demonstrate that the proposed method
achieve better result than the Shannon method.
|
1401.5108 | An Identification System Using Eye Detection Based On Wavelets And
Neural Networks | cs.CV | The randomness and uniqueness of human eye patterns is a major breakthrough
in the search for quicker, easier and highly reliable forms of automatic human
identification. It is being used extensively in security solutions. This
includes access control to physical facilities, security systems and
information databases, Suspect tracking, surveillance and intrusion detection
and by various Intelligence agencies through out the world. We use the
advantage of human eye uniqueness to identify people and approve its validity
as a biometric. . Eye detection involves first extracting the eye from a
digital face image, and then encoding the unique patterns of the eye in such a
way that they can be compared with pre-registered eye patterns. The eye
detection system consists of an automatic segmentation system that is based on
the wavelet transform, and then the Wavelet analysis is used as a pre-processor
for a back propagation neural network with conjugate gradient learning. The
inputs to the neural network are the wavelet maxima neighborhood coefficients
of face images at a particular scale. The output of the neural network is the
classification of the input into an eye or non-eye region. An accuracy of 90%
is observed for identifying test images under different conditions included in
training stage.
|
1401.5124 | Channels with cost constraints: strong converse and dispersion | cs.IT math.IT | This paper shows the strong converse and the dispersion of memoryless
channels with cost constraints and performs refined analysis of the third order
term in the asymptotic expansion of the maximum achievable channel coding rate,
showing that it is equal to $\frac 1 2 \frac {\log n}{n}$ in most cases of
interest. The analysis is based on a non-asymptotic converse bound expressed in
terms of the distribution of a random variable termed the $\mathsf b$-tilted
information density, which plays a role similar to that of the $\mathsf
d$-tilted information in lossy source coding. We also analyze the fundamental
limits of lossy joint-source-channel coding over channels with cost
constraints.
|
1401.5125 | Nonasymptotic noisy lossy source coding | cs.IT math.IT | This paper shows new general nonasymptotic achievability and converse bounds
and performs their dispersion analysis for the lossy compression problem in
which the compressor observes the source through a noisy channel. While this
problem is asymptotically equivalent to a noiseless lossy source coding problem
with a modified distortion function, nonasymptotically there is a noticeable
gap in how fast their minimum achievable coding rates approach the common
rate-distortion function, as evidenced both by the refined asymptotic analysis
(dispersion) and the numerical results. The size of the gap between the
dispersions of the noisy problem and the asymptotically equivalent noiseless
problem depends on the stochastic variability of the channel through which the
compressor observes the source.
|
1401.5136 | A Unifying Framework for Typical Multi-Task Multiple Kernel Learning
Problems | cs.LG | Over the past few years, Multi-Kernel Learning (MKL) has received significant
attention among data-driven feature selection techniques in the context of
kernel-based learning. MKL formulations have been devised and solved for a
broad spectrum of machine learning problems, including Multi-Task Learning
(MTL). Solving different MKL formulations usually involves designing algorithms
that are tailored to the problem at hand, which is, typically, a non-trivial
accomplishment.
In this paper we present a general Multi-Task Multi-Kernel Learning
(Multi-Task MKL) framework that subsumes well-known Multi-Task MKL
formulations, as well as several important MKL approaches on single-task
problems. We then derive a simple algorithm that can solve the unifying
framework. To demonstrate the flexibility of the proposed framework, we
formulate a new learning problem, namely Partially-Shared Common Space (PSCS)
Multi-Task MKL, and demonstrate its merits through experimentation.
|
1401.5151 | Signal recovery using expectation consistent approximation for linear
observations | cs.IT cond-mat.dis-nn math.IT | A signal recovery scheme is developed for linear observation systems based on
expectation consistent (EC) mean field approximation. Approximate message
passing (AMP) is known to be consistent with the results obtained using the
replica theory, which is supposed to be exact in the large system limit, when
each entry of the observation matrix is independently generated from an
identical distribution. However, this is not necessarily the case for general
matrices. We show that EC recovery exhibits consistency with the replica theory
for a wider class of random observation matrices. This is numerically confirmed
by experiments for the Bayesian optimal signal recovery of compressed sensing
using random row-orthogonal matrices.
|
1401.5156 | Harmony Search Algorithm for Curriculum-Based Course Timetabling Problem | cs.AI | In this paper, harmony search algorithm is applied to curriculum-based course
timetabling. The implementation, specifically the process of improvisation
consists of memory consideration, random consideration and pitch adjustment. In
memory consideration, the value of the course number for new solution was
selected from all other course number located in the same column of the Harmony
Memory. This research used the highest occurrence of the course number to be
scheduled in a new harmony. The remaining courses that have not been scheduled
by memory consideration will go through random consideration, i.e. will select
any feasible location available to be scheduled in the new harmony solution.
Each course scheduled out of memory consideration is examined as to whether it
should be pitch adjusted with probability of eight procedures. However, the
algorithm produced results that were not comparatively better than those
previously known as best solution. With proper modification in terms of the
approach in this algorithm would make the algorithm perform better on
curriculum-based course timetabling.
|
1401.5157 | Skill Analysis with Time Series Image Data | cs.AI | We present a skill analysis with time series image data using data mining
methods, focused on table tennis. We do not use body model, but use only
hi-speed movies, from which time series data are obtained and analyzed using
data mining methods such as C4.5 and so on. We identify internal models for
technical skills as evaluation skillfulness for the forehand stroke of table
tennis, and discuss mono and meta-functional skills for improving skills.
|
1401.5162 | A Simple Software Application for Simulating Commercially Available
Solar Panels | cs.CE | This article addresses the formulation and validation of a simple PC based
software application developed for simulating commercially available solar
panels. The important feature of this application is its capability to produce
speedy results in the form of solar panel output characteristics at given
environmental conditions by using minimal input data. Besides, it is able to
deliver critical information about the maximum power point of the panel at a
given environmental condition in quick succession. The application is based on
a standard equation which governs solar panels and works by means of estimating
unknown parameters in the equation to fit a given solar panel. The process of
parameter estimation is described in detail with the aid of equations and data
of a commercial solar panel. A validation of obtained results for commercial
solar panels is also presented by comparing the panel manufacturers' results
with the results generated by the application. In addition, implications of the
obtained results are discussed along with possible improvements to the
developed software application.
|
1401.5168 | Distributed Storage Schemes over Unidirectional Ring Networks | cs.IT math.IT | In this paper, we study distributed storage problems over unidirectional ring
networks. A lower bound on the reconstructing bandwidth to recover total
original data for each user is proposed, and it is achievable for arbitrary
parameters. If a distributed storage scheme can achieve this lower bound with
equality for each user, we say it an optimal reconstructing distributed storage
scheme (ORDSS). Furthermore, the repair problem for a failed storage node in
ORDSSes is under consideration and a tight lower bound on the repair bandwidth
for each storage node is obtained. Particularly, we indicate the fact that for
any ORDSS, every storage node can be repaired with repair bandwidth achieving
the lower bound with equality. In addition, we present an efficient approach to
construct ORDSSes for arbitrary parameters by using the concept of Euclidean
division. Finally, we take an example to characterize the above approach.
|
1401.5175 | Supporting MOOC Instruction with Social Network Analysis | cs.SI | With an expansive and ubiquitously available gold mine of educational data,
Massive Open Online courses (MOOCs) have become the an important foci of
learning analytics research. In this paper, we investigate potential reasons as
to why are these digitalized learning repositories being plagued with huge
attrition rates. We analyze an ongoing online course offered in Coursera using
a social network perspective, with an objective to identify students who are
actively participating in course discussions and those who are potentially at a
risk of dropping off. We additionally perform extensive forum analysis to
visualize student's posting patterns longitudinally. Our results provide
insights that can assist educational designers in establishing a pedagogical
basis for decision-making while designing MOOCs. We infer prominent
characteristics about the participation patterns of distinct groups of students
in the networked learning community, and effectively discover important
discussion threads. These methods can, despite the otherwise prohibitive number
of students involved, allow an instructor to leverage forum behavior to
identify opportunities for support.
|
1401.5181 | Automation of Prosthetic Upper Limbs for Transhumeral Amputees Using
Switch-controlled Motors | cs.HC cs.RO | The issues of research required in the field of bio medical engineering and
externally-powered prostheses are attracting attention of regulatory bodies and
the common people in various parts of the globe. Today, 90 percent of
prostheses used are conventional body powered cable-controlled ones which are
very uncomfortable to the amputees as fairly large amount of forces and
excursions have to be generated by the amputee. Additionally, its amount of
rotation is limited. Alternatively, prosthetic limbs driven using electrical
motors might deliver added functionality and improved control, accompanied by
better cosmesis, however,it could be bulky and costly. Presently existing
proposals usually require fewer bodily response and need additional upkeep than
the cable operated prosthetic limbs. Due to the motives mentioned, proposal for
mechanization of body-powered prostheses, with ease of maintenance and cost in
mind, is presented in this paper. The prosthetic upper limb which is being
automated is for Transhumeral type of amputees that is amputated from above
elbow. The study consists of two main portions: one is lifting mechanism of the
limb and the other is gripping mechanism for the hand using switch controls,
which is the most cost effective and optimized solution, rather than using
complex and expensive myoelectric control signals.
|
1401.5187 | Inequalities for the Bayes Risk | cs.IT math.IT math.ST stat.TH | Several inequalities are presented which, in part, generalize inequalities by
Weinstein and Weiss, giving rise to new lower bounds for the Bayes risk under
squared error loss.
|
1401.5194 | Fundamental Finite Key Limits for One-Way Information Reconciliation in
Quantum Key Distribution | quant-ph cs.IT math.IT | The security of quantum key distribution protocols is guaranteed by the laws
of quantum mechanics. However, a precise analysis of the security properties
requires tools from both classical cryptography and information theory. Here,
we employ recent results in non-asymptotic classical information theory to show
that one-way information reconciliation imposes fundamental limitations on the
amount of secret key that can be extracted in the finite key regime. In
particular, we find that an often used approximation for the information
leakage during information reconciliation is not generally valid. We propose an
improved approximation that takes into account finite key effects and
numerically test it against codes for two probability distributions, that we
call binary-binary and binary-Gaussian, that typically appear in quantum key
distribution protocols.
|
1401.5197 | A user-friendly nano-CT image alignment and 3D reconstruction platform
based on LabVIEW | cs.CE physics.med-ph | X-ray computed tomography at the nanometer scale (nano-CT) offers a wide
range of applications in scientific and industrial areas. Here we describe a
reliable, user-friendly and fast software package based on LabVIEW that may
allow to perform all procedures after the acquisition of raw projection images
in order to obtain the inner structure of the investigated sample. A suitable
image alignment process to address misalignment problems among image series due
to mechanical manufacturing errors, thermal expansion and other external
factors has been considered together with a novel fast parallel beam 3D
reconstruction procedure, developed ad hoc to perform the tomographic
reconstruction. Remarkably improved reconstruction results obtained at the
Beijing Synchrotron Radiation Facility after the image calibration confirmed
the fundamental role of this image alignment procedure that minimizes unwanted
blurs and additional streaking artifacts always present in reconstructed
slices. Moreover, this nano-CT image alignment and its associated 3D
reconstruction procedure fully based on LabVIEW routines, significantly reduce
the data post-processing cycle, thus making faster and easier the activity of
the users during experimental runs.
|
1401.5200 | Conformance Testing as Falsification for Cyber-Physical Systems | cs.SY | In Model-Based Design of Cyber-Physical Systems (CPS), it is often desirable
to develop several models of varying fidelity. Models of different fidelity
levels can enable mathematical analysis of the model, control synthesis, faster
simulation etc. Furthermore, when (automatically or manually) transitioning
from a model to its implementation on an actual computational platform, then
again two different versions of the same system are being developed. In all
previous cases, it is necessary to define a rigorous notion of conformance
between different models and between models and their implementations. This
paper argues that conformance should be a measure of distance between systems.
Albeit a range of theoretical distance notions exists, a way to compute such
distances for industrial size systems and models has not been proposed yet.
This paper addresses exactly this problem. A universal notion of conformance as
closeness between systems is rigorously defined, and evidence is presented that
this implies a number of other application-dependent conformance notions. An
algorithm for detecting that two systems are not conformant is then proposed,
which uses existing proven tools. A method is also proposed to measure the
degree of conformance between two systems. The results are demonstrated on a
range of models.
|
1401.5216 | Multi-GPU parallel memetic algorithm for capacitated vehicle routing
problem | cs.DC cs.NE | The goal of this paper is to propose and test a new memetic algorithm for the
capacitated vehicle routing problem in parallel computing environment. In this
paper we consider simple variation of vehicle routing problem in which the only
parameter is the capacity of the vehicle and each client only needs one
package. We present simple reduction to prove the existence of polynomial-time
algorithm for capacity 2. We analyze the efficiency of the algorithm using
hierarchical Parallel Random Access Machine (PRAM) model and run experiments
with code written in CUDA (for capacities larger than 2).
|
1401.5221 | Optimal Intelligent Control for Wind Turbulence Rejection in WECS Using
ANNs and Genetic Fuzzy Approach | cs.SY cs.NE | One of the disadvantages in Connection of wind energy conversion systems
(WECSs) to transmission networks is plentiful turbulence of wind speed.
Therefore effects of this problem must be controlled. Nowadays,
pitch-controlled WECSs are increasingly used for variable speed and pitch wind
turbines. Megawatt class wind turbines generally turn at variable speed in wind
farm. Thus turbine operation must be controlled in order to maximize the
conversion efficiency below rated power and reduce loading on the drive-train.
Due to random and non-linear nature of the wind turbulence and the ability of
Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) Artificial Neural
Networks (ANNs) in the modeling and control of this turbulence, in this study,
widespread changes of wind have been perused using MLP and RBF artificial NNs.
In addition in this study, a new genetic fuzzy system has been successfully
applied to identify disturbance wind in turbine input. Thus output power has
been regulated in optimal and nominal range by pitch angle regulation.
Consequently, our proposed approaches have regulated output aerodynamic power
and torque in the nominal rang.
|
1401.5224 | Least Entropy-Like Approach for Reconstructing L-Shaped Surfaces Using a
Rotating Array of Ultrasonic Sensors | cs.RO | This paper introduces a new algorithm for accurately reconstructing two
smooth orthogonal surfaces by processing ultrasonic data. The proposed
technique is based on a preliminary analysis of a waveform energy indicator in
order to classify the data as belonging to one of the two flat surfaces. The
following minimization of a nonlinear cost function, inspired by the
mathematical definition of Gibbs entropy, allows to estimate the plane
parameters robustly with respect to the presence of outlying data. These
outliers are mainly due to the effect of multiple reflections arising in the
surfaces intersection region. The scanning system consists of four inexpensive
ultrasonic sensors rotated by means of a precision servo digital motor in order
to obtain distance measurements for each orientation. Experimental results are
presented and compared with the classic Least Squares Method demonstrating the
potentiality of the proposed approach in terms of precision and reliability.
|
1401.5226 | The Why and How of Nonnegative Matrix Factorization | stat.ML cs.IR cs.LG math.OC | Nonnegative matrix factorization (NMF) has become a widely used tool for the
analysis of high-dimensional data as it automatically extracts sparse and
meaningful features from a set of nonnegative data vectors. We first illustrate
this property of NMF on three applications, in image processing, text mining
and hyperspectral imaging --this is the why. Then we address the problem of
solving NMF, which is NP-hard in general. We review some standard NMF
algorithms, and also present a recent subclass of NMF problems, referred to as
near-separable NMF, that can be solved efficiently (that is, in polynomial
time), even in the presence of noise --this is the how. Finally, we briefly
describe some problems in mathematics and computer science closely related to
NMF via the nonnegative rank.
|
1401.5232 | Bio-inspired friction switches: adaptive pulley systems | cs.RO | Frictional influences in tendon-driven robotic systems are generally
unwanted, with efforts towards minimizing them where possible. In the human
hand however, the tendon-pulley system is found to be frictional with a
difference between high-loaded static post-eccentric and post-concentric force
production of 9-12% of the total output force. This difference can be directly
attributed to tendon-pulley friction. Exploiting this phenomenon for robotic
and prosthetic applications we can achieve a reduction of actuator size, weight
and consequently energy consumption. In this study, we present the design of a
bio-inspired friction switch. The adaptive pulley is designed to minimize the
influence of frictional forces under low and medium-loading conditions and
maximize it under high-loading conditions. This is achieved with a
dual-material system that consists of a high-friction silicone substrate and
low-friction polished steel pins. The system, designed to switch its frictional
properties between the low-loaded and high-loaded conditions, is described and
its behavior experimentally validated with respect to the number and spacing of
pins. The results validate its intended behavior, making it a viable choice for
robotic tendon-driven systems.
|
1401.5234 | On the third weight of generalized Reed-Muller codes | cs.IT math.IT math.NT | In this paper, we study the third weight of generalized Reed-Muller codes. We
prove under some restrictive condition that the third weight of generalized
Reed-Muller codes depends on the third weight of generalized Reed-Muller codes
of small order with two variables. In some cases, we are able to determine the
third weight and the third weight codewords of generalized Reed-Muller codes.
|
1401.5245 | Edge detection of binary images using the method of masks | cs.CV | In this work the method of masks, creating and using of inverted image masks,
together with binary operation of image data are used in edge detection of
binary images, monochrome images, which yields about 300 times faster than
ordinary methods. The method is divided into three stages: Mask construction,
Fundamental edge detection, and Edge Construction Comparison with an ordinary
method and a fuzzy based method is carried out.
|
1401.5246 | Genetic Algorithms and its use with back-propagation network | cs.NE | Genetic algorithms are considered as one of the most efficient search
techniques. Although they do not offer an optimal solution, their ability to
reach a suitable solution in considerably short time gives them their
respectable role in many AI techniques. This work introduces genetic algorithms
and describes their characteristics. Then a novel method using genetic
algorithm in best training set generation and selection for a back-propagation
network is proposed. This work also offers a new extension to the original
genetic algorithms
|
1401.5247 | Information content: assessing meso-scale structures in complex networks | physics.soc-ph cs.SI | We propose a novel measure to assess the presence of meso-scale structures in
complex networks. This measure is based on the identification of regular
patterns in the adjacency matrix of the network, and on the calculation of the
quantity of information lost when pairs of nodes are iteratively merged. We
show how this measure is able to quantify several meso-scale structures, like
the presence of modularity, bipartite and core-periphery configurations, or
motifs. Results corresponding to a large set of real networks are used to
validate its ability to detect non-trivial topological patterns.
|
1401.5272 | The Rate-Distortion Function and Excess-Distortion Exponent of Sparse
Regression Codes with Optimal Encoding | cs.IT math.IT math.ST stat.TH | This paper studies the performance of sparse regression codes for lossy
compression with the squared-error distortion criterion. In a sparse regression
code, codewords are linear combinations of subsets of columns of a design
matrix. It is shown that with minimum-distance encoding, sparse regression
codes achieve the Shannon rate-distortion function for i.i.d. Gaussian sources
$R^*(D)$ as well as the optimal excess-distortion exponent. This completes a
previous result which showed that $R^*(D)$ and the optimal exponent were
achievable for distortions below a certain threshold. The proof of the
rate-distortion result is based on the second moment method, a popular
technique to show that a non-negative random variable $X$ is strictly positive
with high probability. In our context, $X$ is the number of codewords within
target distortion $D$ of the source sequence. We first identify the reason
behind the failure of the standard second moment method for certain
distortions, and illustrate the different failure modes via a stylized example.
We then use a refinement of the second moment method to show that $R^*(D)$ is
achievable for all distortion values. Finally, the refinement technique is
applied to Suen's correlation inequality to prove the achievability of the
optimal Gaussian excess-distortion exponent.
|
1401.5297 | Navigating MazeMap: indoor human mobility, spatio-logical ties and
future potential | cs.SY cs.NI cs.SI | Global navigation systems and location-based services have found their way
into our daily lives. Recently, indoor positioning techniques have also been
proposed, and there are several live or trial systems already operating. In
this paper, we present insights from MazeMap, the first live indoor/outdoor
positioning and navigation system deployed at a large university campus in
Norway. Our main contribution is a measurement case study; we show the spatial
and temporal distribution of MazeMap geo-location and wayfinding requests,
construct the aggregated human mobility map of the campus and find strong
logical ties between different locations. On one hand, our findings are
specific to the venue; on the other hand, the nature of available data and
insights coupled with our discussion on potential usage scenarios for indoor
positioning and location-based services predict a successful future for these
systems and applications.
|
1401.5305 | Bounds on the ML Decoding Error Probability of RS-Coded Modulation over
AWGN Channels | cs.IT math.IT | This paper is concerned with bounds on the maximum-likelihood (ML) decoding
error probability of Reed-Solomon (RS) codes over additive white Gaussian noise
(AWGN) channels. To resolve the difficulty caused by the dependence of the
Euclidean distance spectrum on the way of signal mapping, we propose to use
random mapping, resulting in an ensemble of RS-coded modulation (RS-CM)
systems. For this ensemble of RS-CM systems, analytic bounds are derived, which
can be evaluated from the known (symbol-level) Hamming distance spectrum. Also
presented in this paper are simulation-based bounds, which are applicable to
any specific RS-CM system and can be evaluated by the aid of a list decoding
(in the Euclidean space) algorithm. The simulation-based bounds do not need
distance spectrum and are numerically tight for short RS codes in the regime
where the word error rate (WER) is not too low. Numerical comparison results
are relevant in at least three aspects. First, in the short code length regime,
RS-CM using BPSK modulation with random mapping has a better performance than
binary random linear codes. Second, RS-CM with random mapping (time varying)
can have a better performance than with specific mapping. Third, numerical
results show that the recently proposed Chase-type decoding algorithm is
essentially the ML decoding algorithm for short RS codes.
|
1401.5311 | Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face
Recognition | cs.CV | To perform unconstrained face recognition robust to variations in
illumination, pose and expression, this paper presents a new scheme to extract
"Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face
images. Specifically, the MDMLDCPs scheme exploits the first derivative of
Gaussian operator to reduce the impact of differences in illumination and then
computes the DCP feature at both the holistic and component levels. DCP is a
novel face image descriptor inspired by the unique textural structure of human
faces. It is computationally efficient and only doubles the cost of computing
local binary patterns, yet is extremely robust to pose and expression
variations. MDML-DCPs comprehensively yet efficiently encodes the invariant
characteristics of a face image from multiple levels into patterns that are
highly discriminative of inter-personal differences but robust to
intra-personal variations. Experimental results on the FERET, CAS-PERL-R1, FRGC
2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local
descriptors (e.g. LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face
identification and face verification tasks. More impressively, the best
performance is achieved on the challenging LFW and FRGC 2.0 databases by
deploying MDML-DCPs in a simple recognition scheme.
|
1401.5321 | An Integer Programming Approach to UEP Coding for Multiuser Broadcast
Channels | cs.IT math.IT | In this paper, an integer programming approach is introduced to construct
Unequal Error Protection (UEP) codes for multiuser broadcast channels. We show
that the optimal codes can be constructed that satisfy the integer programming
bound. Based on the bound, we compute asymptotic code rate and perform
throughput analysis for the degraded broadcast channel.
|
1401.5327 | Compositional Operators in Distributional Semantics | cs.CL cs.AI math.CT | This survey presents in some detail the main advances that have been recently
taking place in Computational Linguistics towards the unification of the two
prominent semantic paradigms: the compositional formal semantics view and the
distributional models of meaning based on vector spaces. After an introduction
to these two approaches, I review the most important models that aim to provide
compositionality in distributional semantics. Then I proceed and present in
more detail a particular framework by Coecke, Sadrzadeh and Clark (2010) based
on the abstract mathematical setting of category theory, as a more complete
example capable to demonstrate the diversity of techniques and scientific
disciplines that this kind of research can draw from. This paper concludes with
a discussion about important open issues that need to be addressed by the
researchers in the future.
|
1401.5330 | Study of Neural Network Algorithm for Straight-Line Drawings of Planar
Graphs | cs.CG cs.NE | Graph drawing addresses the problem of finding a layout of a graph that
satisfies given aesthetic and understandability objectives. The most important
objective in graph drawing is minimization of the number of crossings in the
drawing, as the aesthetics and readability of graph drawings depend on the
number of edge crossings. VLSI layouts with fewer crossings are more easily
realizable and consequently cheaper. A straight-line drawing of a planar graph
G of n vertices is a drawing of G such that each edge is drawn as a
straight-line segment without edge crossings. However, a problem with current
graph layout methods which are capable of producing satisfactory results for a
wide range of graphs is that they often put an extremely high demand on
computational resources. This paper introduces a new layout method, which
nicely draws internally convex of planar graph that consumes only little
computational resources and does not need any heavy duty preprocessing. Here,
we use two methods: The first is self organizing map known from unsupervised
neural networks which is known as (SOM) and the second method is Inverse Self
Organized Map (ISOM).
|
1401.5334 | A Microkernel Architecture for Constraint Programming | cs.AI cs.PL | This paper presents a microkernel architecture for constraint programming
organized around a number of small number of core functionalities and minimal
interfaces. The architecture contrasts with the monolithic nature of many
implementations. Experimental results indicate that the software engineering
benefits are not incompatible with runtime efficiency.
|
1401.5339 | Complex Objects in the Polytopes of the Linear State-Space Process | math.OC cs.MA | A simple object (one point in $m$-dimensional space) is the resultant of the
evolving matrix polynomial of walks in the irreducible aperiodic network
structure of the first order DeGroot (weighted averaging) state-space process.
This paper draws on a second order generalization the DeGroot model that allows
complex object resultants, i.e, multiple points with distinct coordinates, in
the convex hull of the initial state-space. It is shown that, holding network
structure constant, a unique solution exists for the particular initial space
that is a sufficient condition for the convergence of the process to a
specified complex object. In addition, it is shown that, holding network
structure constant, a solution exists for dampening values sufficient for the
convergence of the process to a specified complex object. These dampening
values, which modify the values of the walks in the network, control the
system's outcomes, and any strongly connected typology is a sufficient
condition of such control.
|
1401.5341 | Domain Views for Constraint Programming | cs.AI cs.PL | Views are a standard abstraction in constraint programming: They make it
possible to implement a single version of each constraint, while avoiding to
create new variables and constraints that would slow down propagation.
Traditional constraint-programming systems provide the concept of {\em variable
views} which implement a view of the type $y = f(x)$ by delegating all (domain
and constraint) operations on variable $y$ to variable $x$. This paper proposes
the alternative concept of {\em domain views} which only delegate domain
operations. Domain views preserve the benefits of variable views but simplify
the implementation of value-based propagation. Domain views also support
non-injective views compositionally, expanding the scope of views
significantly. Experimental results demonstrate the practical benefits of
domain views.
|
1401.5360 | Positivity, Discontinuity, Finite Resources and Nonzero Error for
Arbitrarily Varying Quantum Channels | quant-ph cs.IT math-ph math.IT math.MP | This work is motivated by a quite general question: Under which circumstances
are the capacities of information transmission systems continuous? The research
is explicitly carried out on arbitrarily varying quantum channels (AVQCs). We
give an explicit example that answers the recent question whether the
transmission of messages over AVQCs can benefit from distribution of randomness
between the legitimate sender and receiver in the affirmative. The specific
class of channels introduced in that example is then extended to show that the
deterministic capacity does have discontinuity points, while that behaviour is,
at the same time, not generic: We show that it is continuous around its
positivity points. This is in stark contrast to the randomness-assisted
capacity, which is always continuous in the channel. Our results imply that the
deterministic message transmission capacity of an AVQC can be discontinuous
only in points where it is zero, while the randomness assisted capacity is
nonzero. Apart from the zero-error capacities, this is the first result that
shows a discontinuity of a capacity for a large class of quantum channels. The
continuity of the respective capacity for memoryless quantum channels had,
among others, been listed as an open problem on the problem page of the ITP
Hannover for about six years before it was proven to be continuous. We also
quantify the interplay between the distribution of finite amounts of randomness
between the legitimate sender and receiver, the (nonzero) decoding error with
respect to the average error criterion that can be achieved over a finite
number of channel uses and the number of messages that can be sent. This part
of our results also applies to entanglement- and strong subspace transmission.
In addition, we give a new sufficient criterion for the entanglement
transmission capacity with randomness assistance to vanish.
|
1401.5364 | HMACA: Towards Proposing a Cellular Automata Based Tool for Protein
Coding, Promoter Region Identification and Protein Structure Prediction | cs.CE cs.LG | Human body consists of lot of cells, each cell consist of DeOxaRibo Nucleic
Acid (DNA). Identifying the genes from the DNA sequences is a very difficult
task. But identifying the coding regions is more complex task compared to the
former. Identifying the protein which occupy little place in genes is a really
challenging issue. For understating the genes coding region analysis plays an
important role. Proteins are molecules with macro structure that are
responsible for a wide range of vital biochemical functions, which includes
acting as oxygen, cell signaling, antibody production, nutrient transport and
building up muscle fibers. Promoter region identification and protein structure
prediction has gained a remarkable attention in recent years. Even though there
are some identification techniques addressing this problem, the approximate
accuracy in identifying the promoter region is closely 68% to 72%. We have
developed a Cellular Automata based tool build with hybrid multiple attractor
cellular automata (HMACA) classifier for protein coding region, promoter region
identification and protein structure prediction which predicts the protein and
promoter regions with an accuracy of 76%. This tool also predicts the structure
of protein with an accuracy of 80%.
|
1401.5389 | Which Clustering Do You Want? Inducing Your Ideal Clustering with
Minimal Feedback | cs.IR cs.CL cs.LG | While traditional research on text clustering has largely focused on grouping
documents by topic, it is conceivable that a user may want to cluster documents
along other dimensions, such as the authors mood, gender, age, or sentiment.
Without knowing the users intention, a clustering algorithm will only group
documents along the most prominent dimension, which may not be the one the user
desires. To address the problem of clustering documents along the user-desired
dimension, previous work has focused on learning a similarity metric from data
manually annotated with the users intention or having a human construct a
feature space in an interactive manner during the clustering process. With the
goal of reducing reliance on human knowledge for fine-tuning the similarity
function or selecting the relevant features required by these approaches, we
propose a novel active clustering algorithm, which allows a user to easily
select the dimension along which she wants to cluster the documents by
inspecting only a small number of words. We demonstrate the viability of our
algorithm on a variety of commonly-used sentiment datasets.
|
1401.5390 | Learning to Win by Reading Manuals in a Monte-Carlo Framework | cs.CL cs.AI cs.LG | Domain knowledge is crucial for effective performance in autonomous control
systems. Typically, human effort is required to encode this knowledge into a
control algorithm. In this paper, we present an approach to language grounding
which automatically interprets text in the context of a complex control
application, such as a game, and uses domain knowledge extracted from the text
to improve control performance. Both text analysis and control strategies are
learned jointly using only a feedback signal inherent to the application. To
effectively leverage textual information, our method automatically extracts the
text segment most relevant to the current game state, and labels it with a
task-centric predicate structure. This labeled text is then used to bias an
action selection policy for the game, guiding it towards promising regions of
the action space. We encode our model for text analysis and game playing in a
multi-layer neural network, representing linguistic decisions via latent
variables in the hidden layers, and game action quality via the output layer.
Operating within the Monte-Carlo Search framework, we estimate model parameters
using feedback from simulated games. We apply our approach to the complex
strategy game Civilization II using the official game manual as the text guide.
Our results show that a linguistically-informed game-playing agent
significantly outperforms its language-unaware counterpart, yielding a 34%
absolute improvement and winning over 65% of games when playing against the
built-in AI of Civilization.
|
1401.5401 | Linear MIMO Precoding in Jointly-Correlated Fading Multiple Access
Channels with Finite Alphabet Signaling | cs.IT math.IT | In this paper, we investigate the design of linear precoders for
multiple-input multiple-output (MIMO) multiple access channels (MAC). We assume
that statistical channel state information (CSI) is available at the
transmitters and consider the problem under the practical finite alphabet input
assumption. First, we derive an asymptotic (in the large-system limit) weighted
sum rate (WSR) expression for the MIMO MAC with finite alphabet inputs and
general jointly-correlated fading. Subsequently, we obtain necessary conditions
for linear precoders maximizing the asymptotic WSR and propose an iterative
algorithm for determining the precoders of all users. In the proposed
algorithm, the search space of each user for designing the precoding matrices
is its own modulation set. This significantly reduces the dimension of the
search space for finding the precoding matrices of all users compared to the
conventional precoding design for the MIMO MAC with finite alphabet inputs,
where the search space is the combination of the modulation sets of all users.
As a result, the proposed algorithm decreases the computational complexity for
MIMO MAC precoding design with finite alphabet inputs by several orders of
magnitude. Simulation results for finite alphabet signalling indicate that the
proposed iterative algorithm achieves significant performance gains over
existing precoder designs, including the precoder design based on the Gaussian
input assumption, in terms of both the sum rate and the coded bit error rate.
|
1401.5407 | Patterns of Ship-borne Species Spread: A Clustering Approach for Risk
Assessment and Management of Non-indigenous Species Spread | cs.SI | The spread of non-indigenous species (NIS) through the global shipping
network (GSN) has enormous ecological and economic cost throughout the world.
Previous attempts at quantifying NIS invasions have mostly taken "bottom-up"
approaches that eventually require the use of multiple simplifying assumptions
due to insufficiency and/or uncertainty of available data. By modeling implicit
species exchanges via a graph abstraction that we refer to as the Species Flow
Network (SFN), a different approach that exploits the power of network science
methods in extracting knowledge from largely incomplete data is presented.
Here, coarse-grained species flow dynamics are studied via a graph clustering
approach that decomposes the SFN to clusters of ports and inter-cluster
connections. With this decomposition of ports in place, NIS flow among clusters
can be very efficiently reduced by enforcing NIS management on a few chosen
inter-cluster connections. Furthermore, efficient NIS management strategy for
species exchanges within a cluster (often difficult due higher rate of travel
and pathways) are then derived in conjunction with ecological and environmental
aspects that govern the species establishment. The benefits of the presented
approach include robustness to data uncertainties, implicit incorporation of
"stepping-stone" spread of invasive species, and decoupling of species spread
and establishment risk estimation. Our analysis of a multi-year (1997--2006)
GSN dataset using the presented approach shows the existence of a few large
clusters of ports with higher intra-cluster species flow that are fairly stable
over time. Furthermore, detailed investigations were carried out on vessel
types, ports, and inter-cluster connections. Finally, our observations are
discussed in the context of known NIS invasions and future research directions
are also presented.
|
1401.5424 | Real Time Strategy Language | cs.AI | Real Time Strategy (RTS) games provide complex domain to test the latest
artificial intelligence (AI) research. In much of the literature, AI systems
have been limited to playing one game. Although, this specialization has
resulted in stronger AI gaming systems it does not address the key concerns of
AI researcher. AI researchers seek the development of AI agents that can
autonomously interpret learn, and apply new knowledge. To achieve human level
performance, current AI systems rely on game specific knowledge of an expert.
The paper presents the full RTS language in hopes of shifting the current
research focus to the development of general RTS agents. General RTS agents are
AI gaming systems that can play any RTS games, defined in the RTS language.
This prevents game specific knowledge from being hard coded into the system,
thereby facilitating research that addresses the fundamental concerns of
artificial intelligence.
|
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