OpenRaiser/Intern-Atlas huggingface dataset:
Achieving Data Privacy through Secrecy Views and Null-Based Virtual Updates
Venue: arXiv cs.DB 2012
Year: 2012

There may be sensitive information in a relational database, and we might want to keep it hidden from a user or group thereof. In this work, sensitive data is characterized as the contents of a set of secrecy views. For a user without permission to access that sensitive data, the database instance he queries is updated to make the contents of the views empty or contain only tuples with null values. In particular, if this user poses a query about any of these views, no meaningful information is returned. Since the database is not expected to be physically changed to produce this result, the updates are only virtual. And also minimal in a precise way. These minimal updates are reflected in the secrecy view contents, and also in the fact that query answers, while being privacy preserving, are also maximally informative. Virtual updates are based on the use of null values as used in the SQL standard. We provide the semantics of secrecy views and the virtual updates. The different ways in which the underlying database is virtually updated are specified as the models of a logic program with stable model semantics. The program becomes the basis for the computation of the "secret answers" to queries, i.e. those that do not reveal the sensitive information.
Diffusion in Social Networks with Competing Products
Venue: arXiv cs.SI 2012
Year: 2012

We introduce a new threshold model of social networks, in which the nodes influenced by their neighbours can adopt one out of several alternatives. We characterize the graphs for which adoption of a product by the whole network is possible (respectively necessary) and the ones for which a unique outcome is guaranteed. These characterizations directly yield polynomial time algorithms that allow us to determine whether a given social network satisfies one of the above properties. We also study algorithmic questions for networks without unique outcomes. We show that the problem of computing the minimum possible spread of a product is NP-hard to approximate with an approximation ratio better than $Ω(n)$, in contrast to the maximum spread, which is efficiently computable. We then move on to questions regarding the behavior of a node with respect to adopting some (resp. a given) product. We show that the problem of determining whether a given node has to adopt some (resp. a given) product in all final networks is co-NP-complete.
Optimal grid exploration by asynchronous oblivious robots
Venue: arXiv cs.DC 2012
Year: 2012

We consider a team of {\em autonomous weak robots} that are endowed with visibility sensors and motion actuators. Autonomous means that the team cannot rely on any kind of central coordination mechanism or scheduler. By weak we mean that the robots are devoid of (1) any (observable) IDs allowing to differentiate them (anonymous), (2) means of communication allowing them to communicate directly, and (3) any way to remember any previous observation nor computation performed in any previous step (oblivious). Robots asynchronously operate in cycles of three phases: Look, Compute, and Move. Furthermore, the network is an anonymous unoriented grid. In such settings, the robots must collaborate to solve a collective task, here the terminating grid exploration (exploration for short), despite being limited with respect to input from the environment, asymmetry, memory, etc. Exploration requires that robots explore the grid and stop when the task is complete. We propose optimal (w.r.t. the number of robots) solutions for the deterministic terminating exploration of a grid shaped network by a team of $k$ asynchronous oblivious robots in the fully asynchronous and non-atomic model, so called CORDA. In more details, we first assume the ATOM model in which each Look-Compute-Move cycle execution is executed atomically, ie every robot that is activated at instant t instantaneously executes a full cycle between t and t+1. ATOM being strictly stronger than CORDA, all impossibility results in ATOM also hold in CORDA. We show that it is impossible to explore a grid of at least three nodes with less than three robots in ATOM. (This first result holds for both deterministic and probabilistic settings.) Next, we show that it is impossible to deterministically explore a (2,2)-Grid with less than 4 robots, and a (3,3)-Grid with less than 5 robots, respectively. Then, we propose deterministic algorithms in CORDA to exhibit the optimal number of robots allowing to explore of a given grid. Our results show that except in two particular cases, 3 robots are necessary and sufficient to deterministically explore a grid of at least three nodes. The optimal number of robots for the two remaining cases is: 4 for the (2,2)-Grid and 5 for the (3,3)-Grid.
The game of go as a complex network
Venue: arXiv cs.GT 2012
Year: 2012

We study the game of go from a complex network perspective. We construct a directed network using a suitable definition of tactical moves including local patterns, and study this network for different datasets of professional tournaments and amateur games. The move distribution follows Zipf's law and the network is scale free, with statistical peculiarities different from other real directed networks, such as e. g. the World Wide Web. These specificities reflect in the outcome of ranking algorithms applied to it. The fine study of the eigenvalues and eigenvectors of matrices used by the ranking algorithms singles out certain strategic situations. Our results should pave the way to a better modelization of board games and other types of human strategic scheming.
Random Walks, Electric Networks and The Transience Class problem of Sandpiles
Venue: arXiv cs.DM 2012
Year: 2012

The Abelian Sandpile Model is a discrete diffusion process defined on graphs (Dhar \cite{DD90}, Dhar et al. \cite{DD95}) which serves as the standard model of \textit{self-organized criticality}. The transience class of a sandpile is defined as the maximum number of particles that can be added without making the system recurrent (\cite{BT05}). We develop the theory of discrete diffusions in contrast to continuous harmonic functions on graphs and establish deep connections between standard results in the study of random walks on graphs and sandpiles on graphs. Using this connection and building other necessary machinery we improve the main result of Babai and Gorodezky (SODA 2007,\cite{LB07}) of the bound on the transience class of an $n \times n$ grid, from $O(n^{30})$ to $O(n^{7})$. Proving that the transience class is small validates the general notion that for most natural phenomenon, the time during which the system is transient is small. In addition, we use the machinery developed to prove a number of auxiliary results. We exhibit an equivalence between two other tessellations of plane, the honeycomb and triangular lattices. We give general upper bounds on the transience class as a function of the number of edges to the sink. Further, for planar sandpiles we derive an explicit algebraic expression which provably approximates the transience class of $G$ to within $O(|E(G)|)$. This expression is based on the spectrum of the Laplacian of the dual of the graph $G$. We also show a lower bound of $Ω(n^{3})$ on the transience class on the grid improving the obvious bound of $Ω(n^{2})$.
The Complexity of Manipulative Attacks in Nearly Single-Peaked Electorates
Venue: arXiv cs.GT 2012
Year: 2012

Many electoral bribery, control, and manipulation problems (which we will refer to in general as "manipulative actions" problems) are NP-hard in the general case. It has recently been noted that many of these problems fall into polynomial time if the electorate is single-peaked (i.e., is polarized along some axis/issue). However, real-world electorates are not truly single-peaked. There are usually some mavericks, and so real-world electorates tend to merely be nearly single-peaked. This paper studies the complexity of manipulative-action algorithms for elections over nearly single-peaked electorates, for various notions of nearness and various election systems. We provide instances where even one maverick jumps the manipulative-action complexity up to $\np$-hardness, but we also provide many instances where a reasonable number of mavericks can be tolerated without increasing the manipulative-action complexity.
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
Venue: arXiv cs.IT 2012
Year: 2012

The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. The focus of the paper is on binary-input channels with constraints on the allowed input configurations. The problem of numerically computing the information rate, and even the noiseless capacity, of such channels has so far remained largely unsolved. Both problems can be reduced to computing a Monte Carlo estimate of a partition function. The proposed algorithms use tree-based Gibbs sampling and multilayer (multitemperature) importance sampling. The viability of the proposed algorithms is demonstrated by simulation results.
Windowed Decoding of Spatially Coupled Codes
Venue: arXiv cs.IT 2012
Year: 2012

Spatially coupled codes have been of interest recently owing to their superior performance over memoryless binary-input channels. The performance is good both asymptotically, since the belief propagation thresholds approach capacity, as well as for finite lengths, since degree-2 variables that result in high error floors can be completely avoided. However, to realize the promised good performance, one needs large blocklengths. This in turn implies a large latency and decoding complexity. For the memoryless binary erasure channel, we consider the decoding of spatially coupled codes through a windowed decoder that aims to retain many of the attractive features of belief propagation, while trying to reduce complexity further. We characterize the performance of this scheme by defining thresholds on channel erasure rates that guarantee a target erasure rate. We give analytical lower bounds on these thresholds and show that the performance approaches that of belief propagation exponentially fast in the window size. We give numerical results including the thresholds computed using density evolution and the erasure rate curves for finite-length spatially coupled codes.
Algorithms for Low-Dimensional Topology
Venue: arXiv cs.CG 2012
Year: 2012

In this article, we re-introduce the so called "Arkaden-Faden-Lage" (AFL for short) representation of knots in 3 dimensional space introduced by Kurt Reidemeister and show how it can be used to develop efficient algorithms to compute some important topological knot structures. In particular, we introduce an efficient algorithm to calculate holonomic representation of knots introduced by V. Vassiliev and give the main ideas how to use the AFL representations of knots to compute the Kontsevich Integral. The methods introduced here are to our knowledge novel and can open new perspectives in the development of fast algorithms in low dimensional topology.
From Boolean Functional Equations to Control Software
Venue: arXiv cs.SY 2012
Year: 2012

Many software as well digital hardware automatic synthesis methods define the set of implementations meeting the given system specifications with a boolean relation K. In such a context a fundamental step in the software (hardware) synthesis process is finding effective solutions to the functional equation defined by K. This entails finding a (set of) boolean function(s) F (typically represented using OBDDs, Ordered Binary Decision Diagrams) such that: 1) for all x for which K is satisfiable, K(x, F(x)) = 1 holds; 2) the implementation of F is efficient with respect to given implementation parameters such as code size or execution time. While this problem has been widely studied in digital hardware synthesis, little has been done in a software synthesis context. Unfortunately the approaches developed for hardware synthesis cannot be directly used in a software context. This motivates investigation of effective methods to solve the above problem when F has to be implemented with software. In this paper we present an algorithm that, from an OBDD representation for K, generates a C code implementation for F that has the same size as the OBDD for F and a WCET (Worst Case Execution Time) at most O(nr), being n = |x| the number of arguments of functions in F and r the number of functions in F.
MMSE of "Bad" Codes
Venue: arXiv cs.IT 2012
Year: 2012

We examine codes, over the additive Gaussian noise channel, designed for reliable communication at some specific signal-to-noise ratio (SNR) and constrained by the permitted minimum mean-square error (MMSE) at lower SNRs. The maximum possible rate is below point-to-point capacity, and hence these are non-optimal codes (alternatively referred to as "bad" codes). We show that the maximum possible rate is the one attained by superposition codebooks. Moreover, the MMSE and mutual information behavior as a function of SNR, for any code attaining the maximum rate under the MMSE constraint, is known for all SNR. We also provide a lower bound on the MMSE for finite length codes, as a function of the error probability of the code.
Naturally Supervised Learning in Manipulable Technologies
Venue: arXiv cs.HC 2012
Year: 2012

The relationship between physiological systems and modern electromechanical technologies is fast becoming intimate with high degrees of complex interaction. It can be argued that muscular function, limb movements, and touch perception serve supervisory functions for movement control in motion and touch-based (e.g. manipulable) devices/interfaces and human-machine interfaces in general. To get at this hypothesis requires the use of novel techniques and analyses which demonstrate the multifaceted and regulatory role of adaptive physiological processes in these interactions. Neuromechanics is an approach that unifies the role of physiological function, motor performance, and environmental effects in determining human performance. A neuromechanical perspective will be used to explain the effect of environmental fluctuations on supervisory mechanisms, which leads to adaptive physiological responses. Three experiments are presented using two different types of virtual environment that allowed for selective switching between two sets of environmental forces. This switching was done in various ways to maximize the variety of results. Electromyography (EMG) and kinematic information contributed to the development of human performance-related measures. Both descriptive and specialized analyses were conducted: peak amplitude analysis, loop trace analysis, and the analysis of unmatched muscle power. Results presented here provide a window into performance under a range of conditions. These analyses also demonstrated myriad consequences for force-related fluctuations on dynamic physiological regulation. The findings presented here could be applied to the dynamic control of touch-based and movement-sensitive human-machine systems. In particular, the design of systems such as human-robotic systems, touch screen devices, and rehabilitative technologies could benefit from this research.
Byzantine Broadcast in Point-to-Point Networks using Local Linear Coding
Venue: arXiv cs.DC 2012
Year: 2012

The goal of Byzantine Broadcast (BB) is to allow a set of fault-free nodes to agree on information that a source node wants to broadcast to them, in the presence of Byzantine faulty nodes. We consider design of efficient algorithms for BB in {\em synchronous} point-to-point networks, where the rate of transmission over each communication link is limited by its "link capacity". The throughput of a particular BB algorithm is defined as the average number of bits that can be reliably broadcast to all fault-free nodes per unit time using the algorithm without violating the link capacity constraints. The {\em capacity} of BB in a given network is then defined as the supremum of all achievable BB throughputs in the given network, over all possible BB algorithms. We develop NAB -- a Network-Aware Byzantine broadcast algorithm -- for arbitrary point-to-point networks consisting of $n$ nodes, wherein the number of faulty nodes is at most $f$, $f<n/3$, and the network connectivity is at least $2f+1$. We also prove an upper bound on the capacity of Byzantine broadcast, and conclude that NAB can achieve throughput at least 1/3 of the capacity. When the network satisfies an additional condition, NAB can achieve throughput at least 1/2 of the capacity. To the best of our knowledge, NAB is the first algorithm that can achieve a constant fraction of capacity of Byzantine Broadcast (BB) in arbitrary point-to-point networks.
The Complexity of Mean-Payoff Automaton Expression
Venue: arXiv cs.LO 2012
Year: 2012

"Quantitative languages are extension of boolean languages that assign to each word a real number. Mean-payoff automata are finite automata with numerical weights on transitions that assign to each infinite path the long-run average of the transition weights. The class of \emph{mean-payoff automaton expressions}, introduced in [1], is a class of quantitative languages, which is robust: it is closed under the four pointwise operations of max, min, sum and numerical complement."[1] In this paper we improve the computational complexity for solving the classical decision problems for mean-payoff automaton expressions: while the previously best known upper bound was 4EXPTIME, and no lower bound was known, we give an optimal PSPACE complete bound. As a consequence we also obtain a conceptually simple algorithm to solve the classical decision problems for mean-payoff automaton expressions.
System Identification in Wireless Relay Networks via Gaussian Process
Venue: arXiv cs.IT 2012
Year: 2012

We present a flexible stochastic model for a class of cooperative wireless relay networks, in which the relay processing functionality is not known at the destination. In addressing this problem we develop efficient algorithms to perform relay identification in a wireless relay network. We first construct a statistical model based on a representation of the system using Gaussian Processes in a non-standard manner due to the way we treat the imperfect channel state information. We then formulate the estimation problem to perform system identification, taking into account complexity and computational efficiency. Next we develop a set of three algorithms to solve the identification problem each of decreasing complexity, trading-off the estimation bias for computational efficiency. The joint optimisation problem is tackled via a Bayesian framework using the Iterated Conditioning on the Modes methodology. We develop a lower bound and several sub-optimal computationally efficient solutions to the identification problem, for comparison. We illustrate the estimation performance of our methodology for a range of widely used relay functionalities. The relative total error attained by our algorithm when compared to the lower bound is found to be at worst 9% for low SNR values under all functions considered. The effect of the relay functional estimation error is also studied via BER simulations and is shown to be less than 2dB worse than the lower bound.
On the Asymptotic Validity of the Decoupling Assumption for Analyzing 802.11 MAC Protocol
Venue: arXiv cs.NI 2012
Year: 2012

Performance evaluation of the 802.11 MAC protocol is classically based on the decoupling assumption, which hypothesizes that the backoff processes at different nodes are independent. This decoupling assumption results from mean field convergence and is generally true in transient regime in the asymptotic sense (when the number of wireless nodes tends to infinity), but, contrary to widespread belief, may not necessarily hold in stationary regime. The issue is often related with the existence and uniqueness of a solution to a fixed point equation; however, it was also recently shown that this condition is not sufficient; in contrast, a sufficient condition is a global stability property of the associated ordinary differential equation. In this paper, we give a simple condition that establishes the asymptotic validity of the decoupling assumption for the homogeneous case. We also discuss the heterogeneous and the differentiated service cases and formulate a new ordinary differential equation. We show that the uniqueness of a solution to the associated fixed point equation is not sufficient; we exhibit one case where the fixed point equation has a unique solution but the decoupling assumption is not valid in the asymptotic sense in stationary regime.
3D Terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology
Venue: arXiv cs.CV 2012
Year: 2012

3D point clouds of natural environments relevant to problems in geomorphology often require classification of the data into elementary relevant classes. A typical example is the separation of riparian vegetation from ground in fluvial environments, the distinction between fresh surfaces and rockfall in cliff environments, or more generally the classification of surfaces according to their morphology. Natural surfaces are heterogeneous and their distinctive properties are seldom defined at a unique scale, prompting the use of multi-scale criteria to achieve a high degree of classification success. We have thus defined a multi-scale measure of the point cloud dimensionality around each point, which characterizes the local 3D organization. We can thus monitor how the local cloud geometry behaves across scales. We present the technique and illustrate its efficiency in separating riparian vegetation from ground and classifying a mountain stream as vegetation, rock, gravel or water surface. In these two cases, separating the vegetation from ground or other classes achieve accuracy larger than 98 %. Comparison with a single scale approach shows the superiority of the multi-scale analysis in enhancing class separability and spatial resolution. The technique is robust to missing data, shadow zones and changes in point density within the scene. The classification is fast and accurate and can account for some degree of intra-class morphological variability such as different vegetation types. A probabilistic confidence in the classification result is given at each point, allowing the user to remove the points for which the classification is uncertain. The process can be both fully automated, but also fully customized by the user including a graphical definition of the classifiers. Although developed for fully 3D data, the method can be readily applied to 2.5D airborne lidar data.