An Efficient Algorithm for Partial Order Production

Abstract: We consider the problem of partial order production: arrange the elements of an unknown totally ordered set T into a target partially ordered set S, by comparing a minimum number of pairs in T. Special cases include sorting by comparisons, selection, multiple selection, and heap construction. We give an algorithm performing ITLB + o(ITLB) + O(n) comparisons in the worst case. Here, n denotes the size of the ground sets, and ITLB denotes a natural information-theoretic lower bound on the number of comparisons needed to produce the target partial order. Our approach is to replace the target partial order by a weak order (that is, a partial order with a layered structure) extending it, without increasing the information theoretic lower bound too much. We then solve the problem by applying an efficient multiple selection algorithm. The overall complexity of our algorithm is polynomial. This answers a question of Yao (SIAM J. Comput. 18, 1989). We base our analysis on the entropy of the target partial order, a quantity that can be efficiently computed and provides a good estimate of the information-theoretic lower bound.


Encapsulation theory: the configuration efficiency limit

Abstract: This paper shows how maximum possible configuration efficiency of an indefinitely large software system is constrained by chosing a fixed upper limit to the number of program units per subsystem. It is then shown how the configuration efficiency of an indefinitely large software system depends on the ratio of the total number of informaiton hiding violational software units divided by the total number of program units.


On models of a nondeterministic computation

Abstract: In this paper we consider a nondeterministic computation by deterministic multi-head 2-way automata having a read-only access to an auxiliary memory. The memory contains additional data (a guess) and computation is successful iff it is successful for some memory content. Also we consider the case of restricted guesses in which a guess should satisfy some constraint. We show that the standard complexity classes such as L, NL, P, NP, PSPACE can be characterized in terms of these models of nondeterministic computation. These characterizations differ from the well-known ones by absence of alternation.


An Enhanced Mathematical Model for Performance Evaluation of Optical Burst Switched Networks

Abstract: This paper has been withdrawn by the authors.


Characterizations of probe interval graphs

Abstract: In this paper we obtain several characterizations of the adjacency matrix of a probe interval graph. In course of this study we describe an easy method of obtaining interval representation of an interval bipartite graph from its adjacency matrix. Finally, we note that if we add a loop at every probe vertex of a probe interval graph, then the Ferrers dimension of the corresponding symmetric bipartite graph is at most 3.


Topological Dynamics of Cellular Automata: Dimension Matters

Abstract: Topological dynamics of cellular automata (CA), inherited from classical dynamical systems theory, has been essentially studied in dimension 1. This paper focuses on higher dimensional CA and aims at showing that the situation is different and more complex starting from dimension 2. The main results are the existence of non sensitive CA without equicontinuous points, the non-recursivity of sensitivity constants, the existence of CA having only non-recursive equicontinuous points and the existence of CA having only countably many equicontinuous points. They all show a difference between dimension 1 and higher dimensions. Thanks to these new constructions, we also extend undecidability results concerning topological classification previously obtained in the 1D case. Finally, we show that the set of sensitive CA is only Pi_2 in dimension 1, but becomes Sigma_3-hard for dimension 3.


Universally Utility-Maximizing Privacy Mechanisms

Abstract: A mechanism for releasing information about a statistical database with sensitive data must resolve a trade-off between utility and privacy. Privacy can be rigorously quantified using the framework of {\em differential privacy}, which requires that a mechanism's output distribution is nearly the same whether or not a given database row is included or excluded. The goal of this paper is strong and general utility guarantees, subject to differential privacy. We pursue mechanisms that guarantee near-optimal utility to every potential user, independent of its side information (modeled as a prior distribution over query results) and preferences (modeled via a loss function). Our main result is: for each fixed count query and differential privacy level, there is a {\em geometric mechanism} $M^*$ -- a discrete variant of the simple and well-studied Laplace mechanism -- that is {\em simultaneously expected loss-minimizing} for every possible user, subject to the differential privacy constraint. This is an extremely strong utility guarantee: {\em every} potential user $u$, no matter what its side information and preferences, derives as much utility from $M^*$ as from interacting with a differentially private mechanism $M_u$ that is optimally tailored to $u$.


Secondary Indexing in One Dimension: Beyond B-trees and Bitmap Indexes

Abstract: Let S be a finite, ordered alphabet, and let x = x_1 x_2 ... x_n be a string over S. A "secondary index" for x answers alphabet range queries of the form: Given a range [a_l,a_r] over S, return the set I_{[a_l;a_r]} = {i |x_i \in [a_l; a_r]}. Secondary indexes are heavily used in relational databases and scientific data analysis. It is well-known that the obvious solution, storing a dictionary for the position set associated with each character, does not always give optimal query time. In this paper we give the first theoretically optimal data structure for the secondary indexing problem. In the I/O model, the amount of data read when answering a query is within a constant factor of the minimum space needed to represent I_{[a_l;a_r]}, assuming that the size of internal memory is (|S| log n)^{delta} blocks, for some constant delta > 0. The space usage of the data structure is O(n log |S|) bits in the worst case, and we further show how to bound the size of the data structure in terms of the 0-th order entropy of x. We show how to support updates achieving various time-space trade-offs. We also consider an approximate version of the basic secondary indexing problem where a query reports a superset of I_{[a_l;a_r]} containing each element not in I_{[a_l;a_r]} with probability at most epsilon, where epsilon > 0 is the false positive probability. For this problem the amount of data that needs to be read by the query algorithm is reduced to O(|I_{[a_l;a_r]}| log(1/epsilon)) bits.


Sensitivity Analysis Using a Fixed Point Interval Iteration

Abstract: Proving the existence of a solution to a system of real equations is a central issue in numerical analysis. In many situations, the system of equations depend on parameters which are not exactly known. It is then natural to aim proving the existence of a solution for all values of these parameters in some given domains. This is the aim of the parametrization of existence tests. A new parametric existence test based on the Hansen-Sengupta operator is presented and compared to a similar one based on the Krawczyk operator. It is used as a basis of a fixed point iteration dedicated to rigorous sensibility analysis of parametric systems of equations.


Exact phase transition of backtrack-free search with implications on the power of greedy algorithms

Abstract: Backtracking is a basic strategy to solve constraint satisfaction problems (CSPs). A satisfiable CSP instance is backtrack-free if a solution can be found without encountering any dead-end during a backtracking search, implying that the instance is easy to solve. We prove an exact phase transition of backtrack-free search in some random CSPs, namely in Model RB and in Model RD. This is the first time an exact phase transition of backtrack-free search can be identified on some random CSPs. Our technical results also have interesting implications on the power of greedy algorithms, on the width of random hypergraphs and on the exact satisfiability threshold of random CSPs.


Dynamic External Hashing: The Limit of Buffering

Abstract: Hash tables are one of the most fundamental data structures in computer science, in both theory and practice. They are especially useful in external memory, where their query performance approaches the ideal cost of just one disk access. Knuth gave an elegant analysis showing that with some simple collision resolution strategies such as linear probing or chaining, the expected average number of disk I/Os of a lookup is merely $1+1/2^{\Omega(b)}$, where each I/O can read a disk block containing $b$ items. Inserting a new item into the hash table also costs $1+1/2^{\Omega(b)}$ I/Os, which is again almost the best one can do if the hash table is entirely stored on disk. However, this assumption is unrealistic since any algorithm operating on an external hash table must have some internal memory (at least $\Omega(1)$ blocks) to work with. The availability of a small internal memory buffer can dramatically reduce the amortized insertion cost to $o(1)$ I/Os for many external memory data structures. In this paper we study the inherent query-insertion tradeoff of external hash tables in the presence of a memory buffer. In particular, we show that for any constant $c>1$, if the query cost is targeted at $1+O(1/b^{c})$ I/Os, then it is not possible to support insertions in less than $1-O(1/b^{\frac{c-1}{4}})$ I/Os amortized, which means that the memory buffer is essentially useless. While if the query cost is relaxed to $1+O(1/b^{c})$ I/Os for any constant $c<1$, there is a simple dynamic hash table with $o(1)$ insertion cost. These results also answer the open question recently posed by Jensen and Pagh.


Geometric properties of satisfying assignments of random $\epsilon$-1-in-k SAT

Abstract: We study the geometric structure of the set of solutions of random $\epsilon$-1-in-k SAT problem. For $l\geq 1$, two satisfying assignments $A$ and $B$ are $l$-connected if there exists a sequence of satisfying assignments connecting them by changing at most $l$ bits at a time. We first prove that w.h.p. two assignments of a random $\epsilon$-1-in-$k$ SAT instance are $O(\log n)$-connected, conditional on being satisfying assignments. Also, there exists $\epsilon_{0}\in (0,\frac{1}{k-2})$ such that w.h.p. no two satisfying assignments at distance at least $\epsilon_{0}\cdot n$ form a "hole" in the set of assignments. We believe that this is true for all $\epsilon >0$, and thus satisfying assignments of a random 1-in-$k$ SAT instance form a single cluster.


Collecting and Preserving Videogames and Their Related Materials: A Review of Current Practice, Game-Related Archives and Research Projects

Abstract: This paper reviews the major methods and theories regarding the preservation of new media artifacts such as videogames, and argues for the importance of collecting and coming to a better understanding of videogame artifacts of creation, which will help build a more detailed understanding of the essential qualities of these culturally significant artifacts. We will also review the major videogame collections in the United States, Europe and Japan to give an idea of the current state of videogame archives, and argue for a fuller, more comprehensive coverage of these materials in institutional repositories.


Desynched channels on IRCnet

Abstract: In this paper we describe what a desynchronised channel on IRC is. We give procedures on how to create such a channel and how to remove desynchronisation. We explain which types of desynchronisation there are, what properties desynchronised channels have, and which properties can be exploited.


An Almost Optimal Rank Bound for Depth-3 Identities

Abstract: We show that the rank of a depth-3 circuit (over any field) that is simple, minimal and zero is at most k^3\log d. The previous best rank bound known was 2^{O(k^2)}(\log d)^{k-2} by Dvir and Shpilka (STOC 2005). This almost resolves the rank question first posed by Dvir and Shpilka (as we also provide a simple and minimal identity of rank \Omega(k\log d)). Our rank bound significantly improves (dependence on k exponentially reduced) the best known deterministic black-box identity tests for depth-3 circuits by Karnin and Shpilka (CCC 2008). Our techniques also shed light on the factorization pattern of nonzero depth-3 circuits, most strikingly: the rank of linear factors of a simple, minimal and nonzero depth-3 circuit (over any field) is at most k^3\log d. The novel feature of this work is a new notion of maps between sets of linear forms, called "ideal matchings", used to study depth-3 circuits. We prove interesting structural results about depth-3 identities using these techniques. We believe that these can lead to the goal of a deterministic polynomial time identity test for these circuits.


Trading GRH for algebra: algorithms for factoring polynomials and related structures

Abstract: In this paper we develop techniques that eliminate the need of the Generalized Riemann Hypothesis (GRH) from various (almost all) known results about deterministic polynomial factoring over finite fields. Our main result shows that given a polynomial f(x) of degree n over a finite field k, we can find in deterministic poly(n^{\log n},\log |k|) time "either" a nontrivial factor of f(x) "or" a nontrivial automorphism of k[x]/(f(x)) of order n. This main tool leads to various new GRH-free results, most striking of which are: (1) Given a noncommutative algebra over a finite field, we can find a zero divisor in deterministic subexponential time. (2) Given a positive integer r such that either 8|r or r has at least two distinct odd prime factors. There is a deterministic polynomial time algorithm to find a nontrivial factor of the r-th cyclotomic polynomial over a finite field. In this paper, following the seminal work of Lenstra (1991) on constructing isomorphisms between finite fields, we further generalize classical Galois theory constructs like cyclotomic extensions, Kummer extensions, Teichmuller subgroups, to the case of commutative semisimple algebras with automorphisms. These generalized constructs help eliminate the dependence on GRH.


Self-stabilizing Numerical Iterative Computation

Abstract: Many challenging tasks in sensor networks, including sensor calibration, ranking of nodes, monitoring, event region detection, collaborative filtering, collaborative signal processing, {\em etc.}, can be formulated as a problem of solving a linear system of equations. Several recent works propose different distributed algorithms for solving these problems, usually by using linear iterative numerical methods. In this work, we extend the settings of the above approaches, by adding another dimension to the problem. Specifically, we are interested in {\em self-stabilizing} algorithms, that continuously run and converge to a solution from any initial state. This aspect of the problem is highly important due to the dynamic nature of the network and the frequent changes in the measured environment. In this paper, we link together algorithms from two different domains. On the one hand, we use the rich linear algebra literature of linear iterative methods for solving systems of linear equations, which are naturally distributed with rapid convergence properties. On the other hand, we are interested in self-stabilizing algorithms, where the input to the computation is constantly changing, and we would like the algorithms to converge from any initial state. We propose a simple novel method called \syncAlg as a self-stabilizing variant of the linear iterative methods. We prove that under mild conditions the self-stabilizing algorithm converges to a desired result. We further extend these results to handle the asynchronous case. As a case study, we discuss the sensor calibration problem and provide simulation results to support the applicability of our approach.


A Rational Deconstruction of Landin's SECD Machine with the J Operator

Abstract: Landin's SECD machine was the first abstract machine for applicative expressions, i.e., functional programs. Landin's J operator was the first control operator for functional languages, and was specified by an extension of the SECD machine. We present a family of evaluation functions corresponding to this extension of the SECD machine, using a series of elementary transformations (transformation into continu-ation-passing style (CPS) and defunctionalization, chiefly) and their left inverses (transformation into direct style and refunctionalization). To this end, we modernize the SECD machine into a bisimilar one that operates in lockstep with the original one but that (1) does not use a data stack and (2) uses the caller-save rather than the callee-save convention for environments. We also identify that the dump component of the SECD machine is managed in a callee-save way. The caller-save counterpart of the modernized SECD machine precisely corresponds to Thielecke's double-barrelled continuations and to Felleisen's encoding of J in terms of call/cc. We then variously characterize the J operator in terms of CPS and in terms of delimited-control operators in the CPS hierarchy. As a byproduct, we also present several reduction semantics for applicative expressions with the J operator, based on Curien's original calculus of explicit substitutions. These reduction semantics mechanically correspond to the modernized versions of the SECD machine and to the best of our knowledge, they provide the first syntactic theories of applicative expressions with the J operator.


Linear Time Approximation Schemes for the Gale-Berlekamp Game and Related Minimization Problems

Abstract: We design a linear time approximation scheme for the Gale-Berlekamp Switching Game and generalize it to a wider class of dense fragile minimization problems including the Nearest Codeword Problem (NCP) and Unique Games Problem. Further applications include, among other things, finding a constrained form of matrix rigidity and maximum likelihood decoding of an error correcting code. As another application of our method we give the first linear time approximation schemes for correlation clustering with a fixed number of clusters and its hierarchical generalization. Our results depend on a new technique for dealing with small objective function values of optimization problems and could be of independent interest.


An experimental analysis of Lemke-Howson algorithm

Abstract: We present an experimental investigation of the performance of the Lemke-Howson algorithm, which is the most widely used algorithm for the computation of a Nash equilibrium for bimatrix games. Lemke-Howson algorithm is based upon a simple pivoting strategy, which corresponds to following a path whose endpoint is a Nash equilibrium. We analyze both the basic Lemke-Howson algorithm and a heuristic modification of it, which we designed to cope with the effects of a 'bad' initial choice of the pivot. Our experimental findings show that, on uniformly random games, the heuristics achieves a linear running time, while the basic Lemke-Howson algorithm runs in time roughly proportional to a polynomial of degree seven. To conduct the experiments, we have developed our own implementation of Lemke-Howson algorithm, which turns out to be significantly faster than state-of-the-art software. This allowed us to run the algorithm on a much larger set of data, and on instances of much larger size, compared with previous work.


SINR Diagrams: Towards Algorithmically Usable SINR Models of Wireless Networks

Abstract: The rules governing the availability and quality of connections in a wireless network are described by physical models such as the signal-to-interference & noise ratio (SINR) model. For a collection of simultaneously transmitting stations in the plane, it is possible to identify a reception zone for each station, consisting of the points where its transmission is received correctly. The resulting SINR diagram partitions the plane into a reception zone per station and the remaining plane where no station can be heard. SINR diagrams appear to be fundamental to understanding the behavior of wireless networks, and may play a key role in the development of suitable algorithms for such networks, analogous perhaps to the role played by Voronoi diagrams in the study of proximity queries and related issues in computational geometry. So far, however, the properties of SINR diagrams have not been studied systematically, and most algorithmic studies in wireless networking rely on simplified graph-based models such as the unit disk graph (UDG) model, which conveniently abstract away interference-related complications, and make it easier to handle algorithmic issues, but consequently fail to capture accurately some important aspects of wireless networks. The current paper focuses on obtaining some basic understanding of SINR diagrams, their properties and their usability in algorithmic applications. Specifically, based on some algebraic properties of the polynomials defining the reception zones we show that assuming uniform power transmissions, the reception zones are convex and relatively well-rounded. These results are then used to develop an efficient approximation algorithm for a fundamental point location problem in wireless networks.


Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound

Abstract: The Dynamic Time Warping (DTW) is a popular similarity measure between time series. The DTW fails to satisfy the triangle inequality and its computation requires quadratic time. Hence, to find closest neighbors quickly, we use bounding techniques. We can avoid most DTW computations with an inexpensive lower bound (LB Keogh). We compare LB Keogh with a tighter lower bound (LB Improved). We find that LB Improved-based search is faster. As an example, our approach is 2-3 times faster over random-walk and shape time series.


chi2TeX Semi-automatic translation from chiwriter to LaTeX

Abstract: Semi-automatic translation of math-filled book from obsolete ChiWriter format to LaTeX. Is it possible? Idea of criterion whether to use automatic or hand mode for translation. Illustrations.


Belief functions on lattices

Abstract: We extend the notion of belief function to the case where the underlying structure is no more the Boolean lattice of subsets of some universal set, but any lattice, which we will endow with a minimal set of properties according to our needs. We show that all classical constructions and definitions (e.g., mass allocation, commonality function, plausibility functions, necessity measures with nested focal elements, possibility distributions, Dempster rule of combination, decomposition w.r.t. simple support functions, etc.) remain valid in this general setting. Moreover, our proof of decomposition of belief functions into simple support functions is much simpler and general than the original one by Shafer.


Broadcasting in Prefix Space: P2P Data Dissemination with Predictable Performance

Abstract: A broadcast mode may augment peer-to-peer overlay networks with an efficient, scalable data replication function, but may also give rise to a virtual link layer in VPN-type solutions. We introduce a simple broadcasting mechanism that operates in the prefix space of distributed hash tables without signaling. This paper concentrates on the performance analysis of the prefix flooding scheme. Starting from simple models of recursive $k$-ary trees, we analytically derive distributions of hop counts and the replication load. Extensive simulation results are presented further on, based on an implementation within the OverSim framework. Comparisons are drawn to Scribe, taken as a general reference model for group communication according to the shared, rendezvous-point-centered distribution paradigm. The prefix flooding scheme thereby confirmed its widely predictable performance and consistently outperformed Scribe in all metrics. Reverse path selection in overlays is identified as a major cause of performance degradation.


A Cloning Pushout Approach to Term-Graph Transformation

Abstract: We address the problem of cyclic termgraph rewriting. We propose a new framework where rewrite rules are tuples of the form $(L,R,\tau,\sigma)$ such that $L$ and $R$ are termgraphs representing the left-hand and the right-hand sides of the rule, $\tau$ is a mapping from the nodes of $L$ to those of $R$ and $\sigma$ is a partial function from nodes of $R$ to nodes of $L$. $\tau$ describes how incident edges of the nodes in $L$ are connected in $R$. $\tau$ is not required to be a graph morphism as in classical algebraic approaches of graph transformation. The role of $\sigma$ is to indicate the parts of $L$ to be cloned (copied). Furthermore, we introduce a new notion of \emph{cloning pushout} and define rewrite steps as cloning pushouts in a given category. Among the features of the proposed rewrite systems, we quote the ability to perform local and global redirection of pointers, addition and deletion of nodes as well as cloning and collapsing substructures.


Binar Sort: A Linear Generalized Sorting Algorithm

Abstract: Sorting is a common and ubiquitous activity for computers. It is not surprising that there exist a plethora of sorting algorithms. For all the sorting algorithms, it is an accepted performance limit that sorting algorithms are linearithmic or O(N lg N). The linearithmic lower bound in performance stems from the fact that the sorting algorithms use the ordering property of the data. The sorting algorithm uses comparison by the ordering property to arrange the data elements from an initial permutation into a sorted permutation. Linear O(N) sorting algorithms exist, but use a priori knowledge of the data to use a specific property of the data and thus have greater performance. In contrast, the linearithmic sorting algorithms are generalized by using a universal property of data-comparison, but have a linearithmic performance lower bound. The trade-off in sorting algorithms is generality for performance by the chosen property used to sort the data elements. A general-purpose, linear sorting algorithm in the context of the trade-off of performance for generality at first consideration seems implausible. But, there is an implicit assumption that only the ordering property is universal. But, as will be discussed and examined, it is not the only universal property for data elements. The binar sort is a general-purpose sorting algorithm that uses this other universal property to sort linearly.


Binar Shuffle Algorithm: Shuffling Bit by Bit

Abstract: Frequently, randomly organized data is needed to avoid an anomalous operation of other algorithms and computational processes. An analogy is that a deck of cards is ordered within the pack, but before a game of poker or solitaire the deck is shuffled to create a random permutation. Shuffling is used to assure that an aggregate of data elements for a sequence S is randomly arranged, but avoids an ordered or partially ordered permutation. Shuffling is the process of arranging data elements into a random permutation. The sequence S as an aggregation of N data elements, there are N! possible permutations. For the large number of possible permutations, two of the possible permutations are for a sorted or ordered placement of data elements--both an ascending and descending sorted permutation. Shuffling must avoid inadvertently creating either an ascending or descending permutation. Shuffling is frequently coupled to another algorithmic function -- pseudo-random number generation. The efficiency and quality of the shuffle is directly dependent upon the random number generation algorithm utilized. A more effective and efficient method of shuffling is to use parameterization to configure the shuffle, and to shuffle into sub-arrays by utilizing the encoding of the data elements. The binar shuffle algorithm uses the encoding of the data elements and parameterization to avoid any direct coupling to a random number generation algorithm, but still remain a linear O(N) shuffle algorithm.


Faster Approximate String Matching for Short Patterns

Abstract: We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$ O(nk \cdot \min(\frac{\log^2 m}{\log n},\frac{\log^2 m\log w}{w}) + n) $$ When $P$ is short, namely, $m = 2^{o(\sqrt{\log n})}$ or $m = 2^{o(\sqrt{w/\log w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.


Dynamic System Adaptation by Constraint Orchestration

Abstract: For Paradigm models, evolution is just-in-time specified coordination conducted by a special reusable component McPal. Evolution can be treated consistently and on-the-fly through Paradigm's constraint orchestration, also for originally unforeseen evolution. UML-like diagrams visually supplement such migration, as is illustrated for the case of a critical section solution evolving into a pipeline architecture.


Craig Interpolation for Quantifier-Free Presburger Arithmetic

Abstract: Craig interpolation has become a versatile algorithmic tool for improving software verification. Interpolants can, for instance, accelerate the convergence of fixpoint computations for infinite-state systems. They also help improve the refinement of iteratively computed lazy abstractions. Efficient interpolation procedures have been presented only for a few theories. In this paper, we introduce a complete interpolation method for the full range of quantifier-free Presburger arithmetic formulas. We propose a novel convex variable projection for integer inequalities and a technique to combine them with equalities. The derivation of the interpolant has complexity low-degree polynomial in the size of the refutation proof and is typically fast in practice.


Analyse de la rigidit\'e des machines outils 3 axes d'architecture parall\`ele hyperstatique

Abstract: The paper presents a new stiffness modelling method for overconstrained parallel manipulators, which is applied to 3-d.o.f. translational mechanisms. It is based on a multidimensional lumped-parameter model that replaces the link flexibility by localized 6-d.o.f. virtual springs. In contrast to other works, the method includes a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations, which allows computing the stiffness matrix for the overconstrained architectures and for the singular manipulator postures. The advantages of the developed technique are confirmed by application examples, which deal with comparative stiffness analysis of two translational parallel manipulators.


Low-Memory Adaptive Prefix Coding

Abstract: In this paper we study the adaptive prefix coding problem in cases where the size of the input alphabet is large. We present an online prefix coding algorithm that uses $O(\sigma^{1 / \lambda + \epsilon}) $ bits of space for any constants $\eps>0$, $\lambda>1$, and encodes the string of symbols in $O(\log \log \sigma)$ time per symbol \emph{in the worst case}, where $\sigma$ is the size of the alphabet. The upper bound on the encoding length is $\lambda n H (s) +(\lambda \ln 2 + 2 + \epsilon) n + O (\sigma^{1 / \lambda} \log^2 \sigma)$ bits.


Solving package dependencies: from EDOS to Mancoosi

Abstract: Mancoosi (Managing the Complexity of the Open Source Infrastructure) is an ongoing research project funded by the European Union for addressing some of the challenges related to the "upgrade problem" of interdependent software components of which Debian packages are prototypical examples. Mancoosi is the natural continuation of the EDOS project which has already contributed tools for distribution-wide quality assurance in Debian and other GNU/Linux distributions. The consortium behind the project consists of several European public and private research institutions as well as some commercial GNU/Linux distributions from Europe and South America. Debian is represented by a small group of Debian Developers who are working in the ranks of the involved universities to drive and integrate back achievements into Debian. This paper presents relevant results from EDOS in dependency management and gives an overview of the Mancoosi project and its objectives, with a particular focus on the prospective benefits for Debian.


Description of the CUDF Format

Abstract: This document contains several related specifications, together they describe the document formats related to the solver competition which will be organized by Mancoosi. In particular, this document describes: - DUDF (Distribution Upgradeability Description Format), the document format to be used to submit upgrade problem instances from user machines to a (distribution-specific) database of upgrade problems; - CUDF (Common Upgradeability Description Format), the document format used to encode upgrade problems, abstracting over distribution-specific details. Solvers taking part in the competition will be fed with input in CUDF format.


Revisiting Norm Estimation in Data Streams

Abstract: The problem of estimating the pth moment F_p (p nonnegative and real) in data streams is as follows. There is a vector x which starts at 0, and many updates of the form x_i <-- x_i + v come sequentially in a stream. The algorithm also receives an error parameter 0 < eps < 1. The goal is then to output an approximation with relative error at most eps to F_p = ||x||_p^p. Previously, it was known that polylogarithmic space (in the vector length n) was achievable if and only if p <= 2. We make several new contributions in this regime, including: (*) An optimal space algorithm for 0 < p < 2, which, unlike previous algorithms which had optimal dependence on 1/eps but sub-optimal dependence on n, does not rely on a generic pseudorandom generator. (*) A near-optimal space algorithm for p = 0 with optimal update and query time. (*) A near-optimal space algorithm for the "distinct elements" problem (p = 0 and all updates have v = 1) with optimal update and query time. (*) Improved L_2 --> L_2 dimensionality reduction in a stream. (*) New 1-pass lower bounds to show optimality and near-optimality of our algorithms, as well as of some previous algorithms (the "AMS sketch" for p = 2, and the L_1-difference algorithm of Feigenbaum et al.). As corollaries of our work, we also obtain a few separations in the complexity of moment estimation problems: F_0 in 1 pass vs. 2 passes, p = 0 vs. p > 0, and F_0 with strictly positive updates vs. arbitrary updates.


Temporal Support of Regular Expressions in Sequential Pattern Mining

Abstract: Classic algorithms for sequential pattern discovery, return all frequent sequences present in a database, but, in general, only a few ones are interesting for the user. Languages based on regular expressions (RE) have been proposed to restrict frequent sequences to the ones that satisfy user-specified constraints. Although the support of a sequence is computed as the number of data-sequences satisfying a pattern with respect to the total number of data-sequences in the database, once regular expressions come into play, new approaches to the concept of support are needed. For example, users may be interested in computing the support of the RE as a whole, in addition to the one of a particular pattern. Also, when the items are frequently updated, the traditional way of counting support in sequential pattern mining may lead to incorrect (or, at least incomplete), conclusions. The problem gets more involved if we are interested in categorical sequential patterns. In light of the above, in this paper we propose to revise the classic notion of support in sequential pattern mining, introducing the concept of temporal support of regular expressions, intuitively defined as the number of sequences satisfying a target pattern, out of the total number of sequences that could have possibly matched such pattern, where the pattern is defined as a RE over complex items (i.e., not only item identifiers, but also attributes and functions).


Performance Modeling and Evaluation for Information-Driven Networks

Abstract: Information-driven networks include a large category of networking systems, where network nodes are aware of information delivered and thus can not only forward data packets but may also perform information processing. In many situations, the quality of service (QoS) in information-driven networks is provisioned with the redundancy in information. Traditional performance models generally adopt evaluation measures suitable for packet-oriented service guarantee, such as packet delay, throughput, and packet loss rate. These performance measures, however, do not align well with the actual need of information-driven networks. New performance measures and models for information-driven networks, despite their importance, have been mainly blank, largely because information processing is clearly application dependent and cannot be easily captured within a generic framework. To fill the vacancy, we present a new performance evaluation framework particularly tailored for information-driven networks, based on the recent development of stochastic network calculus. We analyze the QoS with respect to information delivery and study the scheduling problem with the new performance metrics. Our analytical framework can be used to calculate the network capacity in information delivery and in the meantime to help transmission scheduling for a large body of systems where QoS is stochastically guaranteed with the redundancy in information.


Tight Approximation Ratio of a General Greedy Splitting Algorithm for the Minimum k-Way Cut Problem

Abstract: For an edge-weighted connected undirected graph, the minimum $k$-way cut problem is to find a subset of edges of minimum total weight whose removal separates the graph into $k$ connected components. The problem is NP-hard when $k$ is part of the input and W[1]-hard when $k$ is taken as a parameter. A simple algorithm for approximating a minimum $k$-way cut is to iteratively increase the number of components of the graph by $h-1$, where $2 \le h \le k$, until the graph has $k$ components. The approximation ratio of this algorithm is known for $h \le 3$ but is open for $h \ge 4$. In this paper, we consider a general algorithm that iteratively increases the number of components of the graph by $h_i-1$, where $h_1 \le h_2 \le ... \le h_q$ and $\sum_{i=1}^q (h_i-1) = k-1$. We prove that the approximation ratio of this general algorithm is $2 - (\sum_{i=1}^q {h_i \choose 2})/{k \choose 2}$, which is tight. Our result implies that the approximation ratio of the simple algorithm is $2-h/k + O(h^2/k^2)$ in general and $2-h/k$ if $k-1$ is a multiple of $h-1$.


Communication Efficiency in Self-stabilizing Silent Protocols

Abstract: Self-stabilization is a general paradigm to provide forward recovery capabilities to distributed systems and networks. Intuitively, a protocol is self-stabilizing if it is able to recover without external intervention from any catastrophic transient failure. In this paper, our focus is to lower the communication complexity of self-stabilizing protocols \emph{below} the need of checking every neighbor forever. In more details, the contribution of the paper is threefold: (i) We provide new complexity measures for communication efficiency of self-stabilizing protocols, especially in the stabilized phase or when there are no faults, (ii) On the negative side, we show that for non-trivial problems such as coloring, maximal matching, and maximal independent set, it is impossible to get (deterministic or probabilistic) self-stabilizing solutions where every participant communicates with less than every neighbor in the stabilized phase, and (iii) On the positive side, we present protocols for coloring, maximal matching, and maximal independent set such that a fraction of the participants communicates with exactly one neighbor in the stabilized phase.


Finding Sparse Cuts Locally Using Evolving Sets

Abstract: A {\em local graph partitioning algorithm} finds a set of vertices with small conductance (i.e. a sparse cut) by adaptively exploring part of a large graph $G$, starting from a specified vertex. For the algorithm to be local, its complexity must be bounded in terms of the size of the set that it outputs, with at most a weak dependence on the number $n$ of vertices in $G$. Previous local partitioning algorithms find sparse cuts using random walks and personalized PageRank. In this paper, we introduce a randomized local partitioning algorithm that finds a sparse cut by simulating the {\em volume-biased evolving set process}, which is a Markov chain on sets of vertices. We prove that for any set of vertices $A$ that has conductance at most $\phi$, for at least half of the starting vertices in $A$ our algorithm will output (with probability at least half), a set of conductance $O(\phi^{1/2} \log^{1/2} n)$. We prove that for a given run of the algorithm, the expected ratio between its computational complexity and the volume of the set that it outputs is $O(\phi^{-1/2} polylog(n))$. In comparison, the best previous local partitioning algorithm, due to Andersen, Chung, and Lang, has the same approximation guarantee, but a larger ratio of $O(\phi^{-1} polylog(n))$ between the complexity and output volume. Using our local partitioning algorithm as a subroutine, we construct a fast algorithm for finding balanced cuts. Given a fixed value of $\phi$, the resulting algorithm has complexity $O((m+n\phi^{-1/2}) polylog(n))$ and returns a cut with conductance $O(\phi^{1/2} \log^{1/2} n)$ and volume at least $v_{\phi}/2$, where $v_{\phi}$ is the largest volume of any set with conductance at most $\phi$.


Adaptive Fault Masking With Incoherence Scoring

Abstract: An adaptive voting algorithm for digital media was introduced in this study. Availability was improved by incoherence scoring in voting mechanism of Multi-Modular Redundancy. Regulation parameters give the algorithm flexibility of adjusting priorities in decision process. Proposed adaptive voting algorithm was shown to be more aware of fault status of redundant modules


Optimal Filtering of Malicious IP Sources

Abstract: How can we protect the network infrastructure from malicious traffic, such as scanning, malicious code propagation, and distributed denial-of-service (DDoS) attacks? One mechanism for blocking malicious traffic is filtering: access control lists (ACLs) can selectively block traffic based on fields of the IP header. Filters (ACLs) are already available in the routers today but are a scarce resource because they are stored in the expensive ternary content addressable memory (TCAM). In this paper, we develop, for the first time, a framework for studying filter selection as a resource allocation problem. Within this framework, we study five practical cases of source address/prefix filtering, which correspond to different attack scenarios and operator's policies. We show that filter selection optimization leads to novel variations of the multidimensional knapsack problem and we design optimal, yet computationally efficient, algorithms to solve them. We also evaluate our approach using data from Dshield.org and demonstrate that it brings significant benefits in practice. Our set of algorithms is a building block that can be immediately used by operators and manufacturers to block malicious traffic in a cost-efficient way.


On the Complexity of Matroid Isomorphism Problem

Abstract: We study the complexity of testing if two given matroids are isomorphic. The problem is easily seen to be in $\Sigma_2^p$. In the case of linear matroids, which are represented over polynomially growing fields, we note that the problem is unlikely to be $\Sigma_2^p$-complete and is $\co\NP$-hard. We show that when the rank of the matroid is bounded by a constant, linear matroid isomorphism, and matroid isomorphism are both polynomial time many-one equivalent to graph isomorphism. We give a polynomial time Turing reduction from graphic matroid isomorphism problem to the graph isomorphism problem. Using this, we are able to show that graphic matroid isomorphism testing for planar graphs can be done in deterministic polynomial time. We then give a polynomial time many-one reduction from bounded rank matroid isomorphism problem to graphic matroid isomorphism, thus showing that all the above problems are polynomial time equivalent. Further, for linear and graphic matroids, we prove that the automorphism problem is polynomial time equivalent to the corresponding isomorphism problems. In addition, we give a polynomial time membership test algorithm for the automorphism group of a graphic matroid.


Extractors and an efficient variant of Muchnik's theorem

Abstract: Muchnik's theorem about simple conditional descriprion states that for all words $a$ and $b$ there exists a short program $p$ transforming $a$ to $b$ that has the least possible length and is simple conditional on $b$. This paper presents a new proof of this theorem, based on extractors. Employing the extractor technique, two new versions of Muchnik's theorem for space- and time-bounded Kolmogorov complexity are proven.


A polytime proof of correctness of the Rabin-Miller algorithm from Fermat's little theorem

Abstract: Although a deterministic polytime algorithm for primality testing is now known, the Rabin-Miller randomized test of primality continues being the most efficient and widely used algorithm. We prove the correctness of the Rabin-Miller algorithm in the theory V1 for polynomial time reasoning, from Fermat's little theorem. This is interesting because the Rabin-Miller algorithm is a polytime randomized algorithm, which runs in the class RP (i.e., the class of polytime Monte-Carlo algorithms), with a sampling space exponential in the length of the binary encoding of the input number. (The class RP contains polytime P.) However, we show how to express the correctness in the language of V1, and we also show that we can prove the formula expressing correctness with polytime reasoning from Fermat's Little theorem, which is generally expected to be independent of V1. Our proof is also conceptually very basic in the sense that we use the extended Euclid's algorithm, for computing greatest common divisors, as the main workhorse of the proof. For example, we make do without proving the Chinese Reminder theorem, which is used in the standard proofs.


Determinacy and Decidability of Reachability Games with Partial Observation on Both Sides

Abstract: We prove two determinacy and decidability results about two-players stochastic reachability games with partial observation on both sides and finitely many states, signals and actions.


Optimal Strategies in Perfect-Information Stochastic Games with Tail Winning Conditions

Abstract: We prove that optimal strategies exist in every perfect-information stochastic game with finitely many states and actions and a tail winning condition.


The Simultaneous Membership Problem for Chordal, Comparability and Permutation graphs

Abstract: In this paper we introduce the 'simultaneous membership problem', defined for any graph class C characterized in terms of representations, e.g. any class of intersection graphs. Two graphs G_1 and G_2, sharing some vertices X (and the corresponding induced edges), are said to be 'simultaneous members' of graph class C, if there exist representations R_1 and R_2 of G_1 and G_2 that are "consistent" on X. Equivalently (for the classes C that we consider) there exist edges E' between G_1-X and G_2-X such that G_1 \cup G_2 \cup E' belongs to class C. Simultaneous membership problems have application in any situation where it is desirable to consistently represent two related graphs, for example: interval graphs capturing overlaps of DNA fragments of two similar organisms; or graphs connected in time, where one is an updated version of the other. Simultaneous membership problems are related to simultaneous planar embeddings, graph sandwich problems and probe graph recognition problems. In this paper we give efficient algorithms for the simultaneous membership problem on chordal, comparability and permutation graphs. These results imply that graph sandwich problems for the above classes are tractable for an interesting special case: when the set of optional edges form a complete bipartite graph. Our results complement the recent polynomial time recognition algorithms for probe chordal, comparability, and permutation graphs, where the set of optional edges form a clique.


Analytical Framework for Optimizing Weighted Average Download Time in Peer-to-Peer Networks

Abstract: This paper proposes an analytical framework for peer-to-peer (P2P) networks and introduces schemes for building P2P networks to approach the minimum weighted average download time (WADT). In the considered P2P framework, the server, which has the information of all the download bandwidths and upload bandwidths of the peers, minimizes the weighted average download time by determining the optimal transmission rate from the server to the peers and from the peers to the other peers. This paper first defines the static P2P network, the hierarchical P2P network and the strictly hierarchical P2P network. Any static P2P network can be decomposed into an equivalent network of sub-peers that is strictly hierarchical. This paper shows that convex optimization can minimize the WADT for P2P networks by equivalently minimizing the WADT for strictly hierarchical networks of sub-peers. This paper then gives an upper bound for minimizing WADT by constructing a hierarchical P2P network, and lower bound by weakening the constraints of the convex problem. Both the upper bound and the lower bound are very tight. This paper also provides several suboptimal solutions for minimizing the WADT for strictly hierarchical networks, in which peer selection algorithms and chunk selection algorithm can be locally designed.


Benchmarking the solar dynamo with Maxima

Abstract: Recently, Jouve et al(A&A, 2008) published the paper that presents the numerical benchmark for the solar dynamo models. Here, I would like to show a way how to get it with help of computer algebra system Maxima. This way was used in our paper (Pipin & Seehafer, A&A 2008, in print) to test some new ideas in the large-scale stellar dynamos. In the present paper I complement the dynamo benchmark with the standard test that address the problem of the free-decay modes in the sphere which is submerged in vacuum.


String Art: Circle Drawing Using Straight Lines

Abstract: An algorithm to generate the locus of a circle using the intersection points of straight lines is proposed. The pixels on the circle are plotted independent of one another and the operations involved in finding the locus of the circle from the intersection of straight lines are parallelizable. Integer only arithmetic and algorithmic optimizations are used for speedup. The proposed algorithm makes use of an envelope to form a parabolic arc which is consequent transformed into a circle. The use of parabolic arcs for the transformation results in higher pixel errors as the radius of the circle to be drawn increases. At its current state, the algorithm presented may be suitable only for generating circles for string art.


LACK - a VoIP Steganographic Method

Abstract: The paper presents a new steganographic method called LACK (Lost Audio PaCKets Steganography) which is intended mainly for VoIP. The method is presented in a broader context of network steganography and of VoIP steganography in particular. The analytical results presented in the paper concern the influence of LACK's hidden data insertion procedure on the method's impact on quality of voice transmission and its resistance to steganalysis.


Search Result Clustering via Randomized Partitioning of Query-Induced Subgraphs

Abstract: In this paper, we present an approach to search result clustering, using partitioning of underlying link graph. We define the notion of "query-induced subgraph" and formulate the problem of search result clustering as a problem of efficient partitioning of given subgraph into topic-related clusters. Also, we propose a novel algorithm for approximative partitioning of such graph, which results in cluster quality comparable to the one obtained by deterministic algorithms, while operating in more efficient computation time, suitable for practical implementations. Finally, we present a practical clustering search engine developed as a part of this research and use it to get results about real-world performance of proposed concepts.


Cryptanalysis of the SASI Ultralightweight RFID Authentication Protocol with Modular Rotations

Abstract: In this work we present the first passive attack over the SASI lightweight authentication protocol with modular rotations. This can be used to fully recover the secret $ID$ of the RFID tag, which is the value the protocol is designed to conceal. The attack is described initially for recovering $\lfloor log_2(96) \rfloor=6$ bits of the secret value $ID$, a result that by itself allows to mount traceability attacks on any given tag. However, the proposed scheme can be extended to obtain any amount of bits of the secret $ID$, provided a sufficiently large number of successful consecutive sessions are eavesdropped. We also present results on the attack's efficiency, and some ideas to secure this version of the SASI protocol.


Ensuring Query Compatibility with Evolving XML Schemas

Abstract: During the life cycle of an XML application, both schemas and queries may change from one version to another. Schema evolutions may affect query results and potentially the validity of produced data. Nowadays, a challenge is to assess and accommodate the impact of theses changes in rapidly evolving XML applications. This article proposes a logical framework and tool for verifying forward/backward compatibility issues involving schemas and queries. First, it allows analyzing relations between schemas. Second, it allows XML designers to identify queries that must be reformulated in order to produce the expected results across successive schema versions. Third, it allows examining more precisely the impact of schema changes over queries, therefore facilitating their reformulation.


Dynamic Indexability: The Query-Update Tradeoff for One-Dimensional Range Queries

Abstract: The B-tree is a fundamental secondary index structure that is widely used for answering one-dimensional range reporting queries. Given a set of $N$ keys, a range query can be answered in $O(\log_B \nm + \frac{K}{B})$ I/Os, where $B$ is the disk block size, $K$ the output size, and $M$ the size of the main memory buffer. When keys are inserted or deleted, the B-tree is updated in $O(\log_B N)$ I/Os, if we require the resulting changes to be committed to disk right away. Otherwise, the memory buffer can be used to buffer the recent updates, and changes can be written to disk in batches, which significantly lowers the amortized update cost. A systematic way of batching up updates is to use the logarithmic method, combined with fractional cascading, resulting in a dynamic B-tree that supports insertions in $O(\frac{1}{B}\log\nm)$ I/Os and queries in $O(\log\nm + \frac{K}{B})$ I/Os. Such bounds have also been matched by several known dynamic B-tree variants in the database literature. In this paper, we prove that for any dynamic one-dimensional range query index structure with query cost $O(q+\frac{K}{B})$ and amortized insertion cost $O(u/B)$, the tradeoff $q\cdot \log(u/q) = \Omega(\log B)$ must hold if $q=O(\log B)$. For most reasonable values of the parameters, we have $\nm = B^{O(1)}$, in which case our query-insertion tradeoff implies that the bounds mentioned above are already optimal. Our lower bounds hold in a dynamic version of the {\em indexability model}, which is of independent interests.


Revisiting the Core Ontology and Problem in Requirements Engineering

Abstract: In their seminal paper in the ACM Transactions on Software Engineering and Methodology, Zave and Jackson established a core ontology for Requirements Engineering (RE) and used it to formulate the "requirements problem", thereby defining what it means to successfully complete RE. Given that stakeholders of the system-to-be communicate the information needed to perform RE, we show that Zave and Jackson's ontology is incomplete. It does not cover all types of basic concerns that the stakeholders communicate. These include beliefs, desires, intentions, and attitudes. In response, we propose a core ontology that covers these concerns and is grounded in sound conceptual foundations resting on a foundational ontology. The new core ontology for RE leads to a new formulation of the requirements problem that extends Zave and Jackson's formulation. We thereby establish new standards for what minimum information should be represented in RE languages and new criteria for determining whether RE has been successfully completed.


Hybrid: A Definitional Two-Level Approach to Reasoning with Higher-Order Abstract Syntax

Abstract: Combining higher-order abstract syntax and (co)induction in a logical framework is well known to be problematic. Previous work described the implementation of a tool called Hybrid, within Isabelle HOL, which aims to address many of these difficulties. It allows object logics to be represented using higher-order abstract syntax, and reasoned about using tactical theorem proving and principles of (co)induction. In this paper we describe how to use it in a multi-level reasoning fashion, similar in spirit to other meta-logics such as Twelf. By explicitly referencing provability in a middle layer called a specification logic, we solve the problem of reasoning by (co)induction in the presence of non-stratifiable hypothetical judgments, which allow very elegant and succinct specifications of object logic inference rules.


How robust is quicksort average complexity?

Abstract: The paper questions the robustness of average case time complexity of the fast and popular quicksort algorithm. Among the six standard probability distributions examined in the paper, only continuous uniform, exponential and standard normal are supporting it whereas the others are supporting the worst case complexity measure. To the question -why are we getting the worst case complexity measure each time the average case measure is discredited? -- one logical answer is average case complexity under the universal distribution equals worst case complexity. This answer, which is hard to challenge, however gives no idea as to which of the standard probability distributions come under the umbrella of universality. The morale is that average case complexity measures, in cases where they are different from those in worst case, should be deemed as robust provided only they get the support from at least the standard probability distributions, both discrete and continuous. Regretfully, this is not the case with quicksort.


A Spectral Algorithm for Learning Hidden Markov Models

Abstract: Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computationally hard (under cryptographic assumptions), and practitioners typically resort to search heuristics which suffer from the usual local optima issues. We prove that under a natural separation condition (bounds on the smallest singular value of the HMM parameters), there is an efficient and provably correct algorithm for learning HMMs. The sample complexity of the algorithm does not explicitly depend on the number of distinct (discrete) observations---it implicitly depends on this quantity through spectral properties of the underlying HMM. This makes the algorithm particularly applicable to settings with a large number of observations, such as those in natural language processing where the space of observation is sometimes the words in a language. The algorithm is also simple, employing only a singular value decomposition and matrix multiplications.


Learning Class-Level Bayes Nets for Relational Data

Abstract: Many databases store data in relational format, with different types of entities and information about links between the entities. The field of statistical-relational learning (SRL) has developed a number of new statistical models for such data. In this paper we focus on learning class-level or first-order dependencies, which model the general database statistics over attributes of linked objects and links (e.g., the percentage of A grades given in computer science classes). Class-level statistical relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. Most current SRL methods find class-level dependencies, but their main task is to support instance-level predictions about the attributes or links of specific entities. We focus only on class-level prediction, and describe algorithms for learning class-level models that are orders of magnitude faster for this task. Our algorithms learn Bayes nets with relational structure, leveraging the efficiency of single-table nonrelational Bayes net learners. An evaluation of our methods on three data sets shows that they are computationally feasible for realistic table sizes, and that the learned structures represent the statistical information in the databases well. After learning compiles the database statistics into a Bayes net, querying these statistics via Bayes net inference is faster than with SQL queries, and does not depend on the size of the database.


Automatic Generation of the Axial Lines of Urban Environments to Capture What We Perceive

Abstract: Based on the concepts of isovists and medial axes, we developed a set of algorithms that can automatically generate axial lines for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between buildings, where people can freely move around. The generation of the axial lines has been a key aspect of space syntax research, conventionally relying on hand-drawn axial lines of an urban environment, often called axial map, for urban morphological analysis. Although various attempts have been made towards an automatic solution, few of them can produce the axial map that consists of the least number of longest visibility lines, and none of them really works for different urban environments. Our algorithms provide a better solution than existing ones. Throughout this paper, we have also argued and demonstrated that the axial lines constitute a true skeleton, superior to medial axes, in capturing what we perceive about the urban environment. Keywords: Visibility, space syntax, topological analysis, medial axes, axial lines, isovists


Homomorphism Preservation on Quasi-Wide Classes

Abstract: A class of structures is said to have the homomorphism-preservation property just in case every first-order formula that is preserved by homomorphisms on this class is equivalent to an existential-positive formula. It is known by a result of Rossman that the class of finite structures has this property and by previous work of Atserias et al. that various of its subclasses do. We extend the latter results by introducing the notion of a quasi-wide class and showing that any quasi-wide class that is closed under taking substructures and disjoint unions has the homomorphism-preservation property. We show, in particular, that classes of structures of bounded expansion and that locally exclude minors are quasi-wide. We also construct an example of a class of finite structures which is closed under substructures and disjoint unions but does not admit the homomorphism-preservation property.


Frozen Footprints

Abstract: Bibliometrics has the ambitious goal of measuring science. To this end, it exploits the way science is disseminated trough scientific publications and the resulting citation network of scientific papers. We survey the main historical contributions to the field, the most interesting bibliometric indicators, and the most popular bibliometric data sources. Moreover, we discuss distributions commonly used to model bibliometric phenomena and give an overview of methods to build bibliometric maps of science.


Fast and Quality-Guaranteed Data Streaming in Resource-Constrained Sensor Networks

Abstract: In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical demand is to online compress data streams continuously with quality guarantee. Although many data compression and digital signal processing methods have been developed to reduce data volume, their super-linear time and more-than-constant space complexity prevents them from being applied directly on data streams, particularly over resource-constrained sensor networks. In this paper, we tackle the problem of online quality guaranteed compression of data streams using fast linear approximation (i.e., using line segments to approximate a time series). Technically, we address two versions of the problem which explore quality guarantees in different forms. We develop online algorithms with linear time complexity and constant cost in space. Our algorithms are optimal in the sense they generate the minimum number of segments that approximate a time series with the required quality guarantee. To meet the resource constraints in sensor networks, we also develop a fast algorithm which creates connecting segments with very simple computation. The low cost nature of our methods leads to a unique edge on the applications of massive and fast streaming environment, low bandwidth networks, and heavily constrained nodes in computational power. We implement and evaluate our methods in the application of an acoustic wireless sensor network.


The Good, the Bad, and the Ugly: three different approaches to break their watermarking system

Abstract: The Good is Blondie, a wandering gunman with a strong personal sense of honor. The Bad is Angel Eyes, a sadistic hitman who always hits his mark. The Ugly is Tuco, a Mexican bandit who's always only looking out for himself. Against the backdrop of the BOWS contest, they search for a watermark in gold buried in three images. Each knows only a portion of the gold's exact location, so for the moment they're dependent on each other. However, none are particularly inclined to share...


Mapping Images with the Coherence Length Diagrams

Abstract: Statistical pattern recognition methods based on the Coherence Length Diagram (CLD) have been proposed for medical image analyses, such as quantitative characterisation of human skin textures, and for polarized light microscopy of liquid crystal textures. Further investigations are made on image maps originated from such diagram and some examples related to irregularity of microstructures are shown.


Compact Labelings For Efficient First-Order Model-Checking

Abstract: We consider graph properties that can be checked from labels, i.e., bit sequences, of logarithmic length attached to vertices. We prove that there exists such a labeling for checking a first-order formula with free set variables in the graphs of every class that is \emph{nicely locally cwd-decomposable}. This notion generalizes that of a \emph{nicely locally tree-decomposable} class. The graphs of such classes can be covered by graphs of bounded \emph{clique-width} with limited overlaps. We also consider such labelings for \emph{bounded} first-order formulas on graph classes of \emph{bounded expansion}. Some of these results are extended to counting queries.


Prospective Study for Semantic Inter-Media Fusion in Content-Based Medical Image Retrieval

Abstract: One important challenge in modern Content-Based Medical Image Retrieval (CBMIR) approaches is represented by the semantic gap, related to the complexity of the medical knowledge. Among the methods that are able to close this gap in CBMIR, the use of medical thesauri/ontologies has interesting perspectives due to the possibility of accessing on-line updated relevant webservices and to extract real-time medical semantic structured information. The CBMIR approach proposed in this paper uses the Unified Medical Language System's (UMLS) Metathesaurus to perform a semantic indexing and fusion of medical media. This fusion operates before the query processing (retrieval) and works at an UMLS-compliant conceptual indexing level. Our purpose is to study various techniques related to semantic data alignment, preprocessing, fusion, clustering and retrieval, by evaluating the various techniques and highlighting future research directions. The alignment and the preprocessing are based on partial text/image retrieval feedback and on the data structure. We analyze various probabilistic, fuzzy and evidence-based approaches for the fusion process and different similarity functions for the retrieval process. All the proposed methods are evaluated on the Cross Language Evaluation Forum's (CLEF) medical image retrieval benchmark, by focusing also on a more homogeneous component medical image database: the Pathology Education Instructional Resource (PEIR).


Automated Induction for Complex Data Structures

Abstract: We propose a procedure for automated implicit inductive theorem proving for equational specifications made of rewrite rules with conditions and constraints. The constraints are interpreted over constructor terms (representing data values), and may express syntactic equality, disequality, ordering and also membership in a fixed tree language. Constrained equational axioms between constructor terms are supported and can be used in order to specify complex data structures like sets, sorted lists, trees, powerlists... Our procedure is based on tree grammars with constraints, a formalism which can describe exactly the initial model of the given specification (when it is sufficiently complete and terminating). They are used in the inductive proofs first as an induction scheme for the generation of subgoals at induction steps, second for checking validity and redundancy criteria by reduction to an emptiness problem, and third for defining and solving membership constraints. We show that the procedure is sound and refutationally complete. It generalizes former test set induction techniques and yields natural proofs for several non-trivial examples presented in the paper, these examples are difficult to specify and carry on automatically with related induction procedures.


Kinematic Analysis of a Serial - Parallel Machine Tool: the VERNE machine

Abstract: The paper derives the inverse and the forward kinematic equations of a serial - parallel 5-axis machine tool: the VERNE machine. This machine is composed of a three-degree-of-freedom (DOF) parallel module and a two-DOF serial tilting table. The parallel module consists of a moving platform that is connected to a fixed base by three non-identical legs. These legs are connected in a way that the combined effects of the three legs lead to an over-constrained mechanism with complex motion. This motion is defined as a simultaneous combination of rotation and translation. In this paper we propose symbolical methods that able to calculate all kinematic solutions and identify the acceptable one by adding analytical constraint on the disposition of legs of the parallel module.


Stable normal forms for polynomial system solving

Abstract: This paper describes and analyzes a method for computing border bases of a zero-dimensional ideal $I$. The criterion used in the computation involves specific commutation polynomials and leads to an algorithm and an implementation extending the one provided in [MT'05]. This general border basis algorithm weakens the monomial ordering requirement for \grob bases computations. It is up to date the most general setting for representing quotient algebras, embedding into a single formalism Gr\"obner bases, Macaulay bases and new representation that do not fit into the previous categories. With this formalism we show how the syzygies of the border basis are generated by commutation relations. We also show that our construction of normal form is stable under small perturbations of the ideal, if the number of solutions remains constant. This new feature for a symbolic algorithm has a huge impact on the practical efficiency as it is illustrated by the experiments on classical benchmark polynomial systems, at the end of the paper.


An Integrated Software-based Solution for Modular and Self-independent Networked Robot

Abstract: An integrated software-based solution for a modular and self-independent networked robot is introduced. The wirelessly operatable robot has been developed mainly for autonomous monitoring works with full control over web. The integrated software solution covers three components : a) the digital signal processing unit for data retrieval and monitoring system; b) the externally executable codes for control system; and c) the web programming for interfacing the end-users with the robot. It is argued that this integrated software-based approach is crucial to realize a flexible, modular and low development cost mobile monitoring apparatus.


Moment matrices, trace matrices and the radical of ideals

Abstract: Let $f_1,...,f_s \in \mathbb{K}[x_1,...,x_m]$ be a system of polynomials generating a zero-dimensional ideal $\I$, where $\mathbb{K}$ is an arbitrary algebraically closed field. Assume that the factor algebra $\A=\mathbb{K}[x_1,...,x_m]/\I$ is Gorenstein and that we have a bound $\delta>0$ such that a basis for $\A$ can be computed from multiples of $f_1,...,f_s$ of degrees at most $\delta$. We propose a method using Sylvester or Macaulay type resultant matrices of $f_1,...,f_s$ and $J$, where $J$ is a polynomial of degree $\delta$ generalizing the Jacobian, to compute moment matrices, and in particular matrices of traces for $\A$. These matrices of traces in turn allow us to compute a system of multiplication matrices $\{M_{x_i}|i=1,...,m\}$ of the radical $\sqrt{\I}$, following the approach in the previous work by Janovitz-Freireich, R\'{o}nyai and Sz\'ant\'o. Additionally, we give bounds for $\delta$ for the case when $\I$ has finitely many projective roots in $\mathbb{P}^m_\CC$.


Lower Bounds on Performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions

Abstract: Within a mathematically rigorous model, we analyse the curse of dimensionality for deterministic exact similarity search in the context of popular indexing schemes: metric trees. The datasets $X$ are sampled randomly from a domain $\Omega$, equipped with a distance, $\rho$, and an underlying probability distribution, $\mu$. While performing an asymptotic analysis, we send the intrinsic dimension $d$ of $\Omega$ to infinity, and assume that the size of a dataset, $n$, grows superpolynomially yet subexponentially in $d$. Exact similarity search refers to finding the nearest neighbour in the dataset $X$ to a query point $\omega\in\Omega$, where the query points are subject to the same probability distribution $\mu$ as datapoints. Let $\mathscr F$ denote a class of all 1-Lipschitz functions on $\Omega$ that can be used as decision functions in constructing a hierarchical metric tree indexing scheme. Suppose the VC dimension of the class of all sets $\{\omega\colon f(\omega)\geq a\}$, $a\in\R$ is $o(n^{1/4}/\log^2n)$. (In view of a 1995 result of Goldberg and Jerrum, even a stronger complexity assumption $d^{O(1)}$ is reasonable.) We deduce the $\Omega(n^{1/4})$ lower bound on the expected average case performance of hierarchical metric-tree based indexing schemes for exact similarity search in $(\Omega,X)$. In paricular, this bound is superpolynomial in $d$.


A Simple Performance Analysis of a Core Node in an Optical Burst Switched Network

Abstract: This paper has been withdrawn


Contention Resolution in Optical Burst Switched Networks using Spectral- Amplitude-Coding Optical Code Division Multiple Access

Abstract: This paper has been withdrawn by the authors.


Zigzag Persistence

Abstract: We describe a new methodology for studying persistence of topological features across a family of spaces or point-cloud data sets, called zigzag persistence. Building on classical results about quiver representations, zigzag persistence generalises the highly successful theory of persistent homology and addresses several situations which are not covered by that theory. In this paper we develop theoretical and algorithmic foundations with a view towards applications in topological statistics.


Convergence to Equilibrium in Local Interaction Games and Ising Models

Abstract: Coordination games describe social or economic interactions in which the adoption of a common strategy has a higher payoff. They are classically used to model the spread of conventions, behaviors, and technologies in societies. Here we consider a two-strategies coordination game played asynchronously between the nodes of a network. Agents behave according to a noisy best-response dynamics. It is known that noise removes the degeneracy among equilibria: In the long run, the ``risk-dominant'' behavior spreads throughout the network. Here we consider the problem of computing the typical time scale for the spread of this behavior. In particular, we study its dependence on the network structure and derive a dichotomy between highly-connected, non-local graphs that show slow convergence, and poorly connected, low dimensional graphs that show fast convergence.


Optimal Tracking of Distributed Heavy Hitters and Quantiles

Abstract: We consider the the problem of tracking heavy hitters and quantiles in the distributed streaming model. The heavy hitters and quantiles are two important statistics for characterizing a data distribution. Let $A$ be a multiset of elements, drawn from the universe $U=\{1,...,u\}$. For a given $0 \le \phi \le 1$, the $\phi$-heavy hitters are those elements of $A$ whose frequency in $A$ is at least $\phi |A|$; the $\phi$-quantile of $A$ is an element $x$ of $U$ such that at most $\phi|A|$ elements of $A$ are smaller than $A$ and at most $(1-\phi)|A|$ elements of $A$ are greater than $x$. Suppose the elements of $A$ are received at $k$ remote {\em sites} over time, and each of the sites has a two-way communication channel to a designated {\em coordinator}, whose goal is to track the set of $\phi$-heavy hitters and the $\phi$-quantile of $A$ approximately at all times with minimum communication. We give tracking algorithms with worst-case communication cost $O(k/\eps \cdot \log n)$ for both problems, where $n$ is the total number of items in $A$, and $\eps$ is the approximation error. This substantially improves upon the previous known algorithms. We also give matching lower bounds on the communication costs for both problems, showing that our algorithms are optimal. We also consider a more general version of the problem where we simultaneously track the $\phi$-quantiles for all $0 \le \phi \le 1$.


An evaluation of Bradfordizing effects

Abstract: The purpose of this paper is to apply and evaluate the bibliometric method Bradfordizing for information retrieval (IR) experiments. Bradfordizing is used for generating core document sets for subject-specific questions and to reorder result sets from distributed searches. The method will be applied and tested in a controlled scenario of scientific literature databases from social and political sciences, economics, psychology and medical science (SOLIS, SoLit, USB Koeln Opac, CSA Sociological Abstracts, World Affairs Online, Psyndex and Medline) and 164 standardized topics. An evaluation of the method and its effects is carried out in two laboratory-based information retrieval experiments (CLEF and KoMoHe) using a controlled document corpus and human relevance assessments. The results show that Bradfordizing is a very robust method for re-ranking the main document types (journal articles and monographs) in today's digital libraries (DL). The IR tests show that relevance distributions after re-ranking improve at a significant level if articles in the core are compared with articles in the succeeding zones. The items in the core are significantly more often assessed as relevant, than items in zone 2 (z2) or zone 3 (z3). The improvements between the zones are statistically significant based on the Wilcoxon signed-rank test and the paired T-Test.


Stackelberg Network Pricing is Hard to Approximate

Abstract: In the Stackelberg Network Pricing problem, one has to assign tariffs to a certain subset of the arcs of a given transportation network. The aim is to maximize the amount paid by the user of the network, knowing that the user will take a shortest st-path once the tariffs are fixed. Roch, Savard, and Marcotte (Networks, Vol. 46(1), 57-67, 2005) proved that this problem is NP-hard, and gave an O(log m)-approximation algorithm, where m denote the number of arcs to be priced. In this note, we show that the problem is also APX-hard.


A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents

Abstract: We describe and provide code and examples for a polygonal edge matching method.


k-means requires exponentially many iterations even in the plane

Abstract: The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice. Theoretically, however, the best known upper bound on its running time (i.e. O(n^{kd})) can be exponential in the number of points. Recently, Arthur and Vassilvitskii [3] showed a super-polynomial worst-case analysis, improving the best known lower bound from \Omega(n) to 2^{\Omega(\sqrt{n})} with a construction in d=\Omega(\sqrt{n}) dimensions. In [3] they also conjectured the existence of superpolynomial lower bounds for any d >= 2. Our contribution is twofold: we prove this conjecture and we improve the lower bound, by presenting a simple construction in the plane that leads to the exponential lower bound 2^{\Omega(n)}.


Delaunay Triangulations in Linear Time? (Part I)

Abstract: We present a new and simple randomized algorithm for constructing the Delaunay triangulation using nearest neighbor graphs for point location. Under suitable assumptions, it runs in linear expected time for points in the plane with polynomially bounded spread, i.e., if the ratio between the largest and smallest pointwise distance is polynomially bounded. This also holds for point sets with bounded spread in higher dimensions as long as the expected complexity of the Delaunay triangulation of a sample of the points is linear in the sample size.


Approximation Algorithms for Bregman Co-clustering and Tensor Clustering

Abstract: In the past few years powerful generalizations to the Euclidean k-means problem have been made, such as Bregman clustering [7], co-clustering (i.e., simultaneous clustering of rows and columns of an input matrix) [9,18], and tensor clustering [8,34]. Like k-means, these more general problems also suffer from the NP-hardness of the associated optimization. Researchers have developed approximation algorithms of varying degrees of sophistication for k-means, k-medians, and more recently also for Bregman clustering [2]. However, there seem to be no approximation algorithms for Bregman co- and tensor clustering. In this paper we derive the first (to our knowledge) guaranteed methods for these increasingly important clustering settings. Going beyond Bregman divergences, we also prove an approximation factor for tensor clustering with arbitrary separable metrics. Through extensive experiments we evaluate the characteristics of our method, and show that it also has practical impact.


An Introduction to Knowledge Management

Abstract: Knowledge has been lately recognized as one of the most important assets of organizations. Managing knowledge has grown to be imperative for the success of a company. This paper presents an overview of Knowledge Management and various aspects of secure knowledge management. A case study of knowledge management activities at Tata Steel is also discussed


On the computational complexity of solving stochastic mean-payoff games

Abstract: We consider some well-known families of two-player, zero-sum, perfect information games that can be viewed as special cases of Shapley's stochastic games. We show that the following tasks are polynomial time equivalent: - Solving simple stochastic games. - Solving stochastic mean-payoff games with rewards and probabilities given in unary. - Solving stochastic mean-payoff games with rewards and probabilities given in binary.


Trembling hand perfection is NP-hard

Abstract: It is NP-hard to decide if a given pure-strategy Nash equilibrium of a given three-player game in strategic form with integer payoffs is trembling hand perfect.


A Relaying Incentive Scheme in Multihop Cellular Networks Based on Coalitional Game with Externalities

Abstract: Cooperative multihop communication can greatly increase network throughput, yet packet forwarding for other nodes involves opportunity and energy cost for relays. Thus one of the pre-requisite problems in the successful implementation of multihop transmission is how to foster cooperation among selfish nodes. Existing researches mainly adopt monetary stimulating. In this manuscript, we propose instead a simple and self-enforcing forwarding incentive scheme free of indirect monetary remunerating for asymmetric (uplink multihop, downlink single-hop) cellar network based on coalitional game theory, which comprises double compensation, namely, Inter- BEA, global stimulating policy allotting resources among relaying coalitions according to group size, and Intra-BEA, local compensating and allocating rule within coalitions. Firstly, given the global allotting policy, we introduce a fair allocation estimating approach which includes remunerating for relaying cost using Myerson value for partition function game, to enlighten the design of local allocating rules. Secondly, given the inter- and intra-BEA relay fostering approach, we check stability of coalition structures in terms of internal and external stability as well as inductive core. Theoretic analysis and numerical simulation show that our measure can provide communication opportunities for outer ring nodes and enlarge system coverage, while at the same time provide enough motivation with respect to resource allocation and energy saving for nodes in inner and middle ring to relay for own profits.


Provenance Traces

Abstract: Provenance is information about the origin, derivation, ownership, or history of an object. It has recently been studied extensively in scientific databases and other settings due to its importance in helping scientists judge data validity, quality and integrity. However, most models of provenance have been stated as ad hoc definitions motivated by informal concepts such as "comes from", "influences", "produces", or "depends on". These models lack clear formalizations describing in what sense the definitions capture these intuitive concepts. This makes it difficult to compare approaches, evaluate their effectiveness, or argue about their validity. We introduce provenance traces, a general form of provenance for the nested relational calculus (NRC), a core database query language. Provenance traces can be thought of as concrete data structures representing the operational semantics derivation of a computation; they are related to the traces that have been used in self-adjusting computation, but differ in important respects. We define a tracing operational semantics for NRC queries that produces both an ordinary result and a trace of the execution. We show that three pre-existing forms of provenance for the NRC can be extracted from provenance traces. Moreover, traces satisfy two semantic guarantees: consistency, meaning that the traces describe what actually happened during execution, and fidelity, meaning that the traces "explain" how the expression would behave if the input were changed. These guarantees are much stronger than those contemplated for previous approaches to provenance; thus, provenance traces provide a general semantic foundation for comparing and unifying models of provenance in databases.


Pushing BitTorrent Locality to the Limit

Abstract: Peer-to-peer (P2P) locality has recently raised a lot of interest in the community. Indeed, whereas P2P content distribution enables financial savings for the content providers, it dramatically increases the traffic on inter-ISP links. To solve this issue, the idea to keep a fraction of the P2P traffic local to each ISP was introduced a few years ago. Since then, P2P solutions exploiting locality have been introduced. However, several fundamental issues on locality still need to be explored. In particular, how far can we push locality, and what is, at the scale of the Internet, the reduction of traffic that can be achieved with locality? In this paper, we perform extensive experiments on a controlled environment with up to 10 000 BitTorrent clients to evaluate the impact of high locality on inter-ISP links traffic and peers download completion time. We introduce two simple mechanisms that make high locality possible in challenging scenarios and we show that we save up to several orders of magnitude inter-ISP traffic compared to traditional locality without adversely impacting peers download completion time. In addition, we crawled 214 443 torrents representing 6 113 224 unique peers spread among 9 605 ASes. We show that whereas the torrents we crawled generated 11.6 petabytes of inter-ISP traffic, our locality policy implemented for all torrents would have reduced the global inter-ISP traffic by 40%.


Preference Games and Personalized Equilibria, with Applications to Fractional BGP

Abstract: We study the complexity of computing equilibria in two classes of network games based on flows - fractional BGP (Border Gateway Protocol) games and fractional BBC (Bounded Budget Connection) games. BGP is the glue that holds the Internet together and hence its stability, i.e. the equilibria of fractional BGP games (Haxell, Wilfong), is a matter of practical importance. BBC games (Laoutaris et al) follow in the tradition of the large body of work on network formation games and capture a variety of applications ranging from social networks and overlay networks to peer-to-peer networks. The central result of this paper is that there are no fully polynomial-time approximation schemes (unless PPAD is in FP) for computing equilibria in both fractional BGP games and fractional BBC games. We obtain this result by proving the hardness for a new and surprisingly simple game, the fractional preference game, which is reducible to both fractional BGP and BBC games. We define a new flow-based notion of equilibrium for matrix games -- personalized equilibria -- generalizing both fractional BBC and fractional BGP games. We prove not just the existence, but the existence of rational personalized equilibria for all matrix games, which implies the existence of rational equilibria for fractional BGP and BBC games. In particular, this provides an alternative proof and strengthening of the main result in [Haxell, Wilfong]. For k-player matrix games, where k = 2, we provide a combinatorial characterization leading to a polynomial-time algorithm for computing all personalized equilibria. For k >= 5, we prove that personalized equilibria are PPAD-hard to approximate in fully polynomial time. We believe that the concept of personalized equilibria has potential for real-world significance.


Dilation, smoothed distance, and minimization diagrams of convex functions

Abstract: We study Voronoi diagrams for distance functions that add together two convex functions, each taking as its argument the difference between Cartesian coordinates of two planar points. When the functions do not grow too quickly, then the Voronoi diagram has linear complexity and can be constructed in near-linear randomized expected time. Additionally, the level sets of the distances from the sites form a family of pseudocircles in the plane, all cells in the Voronoi diagram are connected, and the set of bisectors separating any one cell in the diagram from each of the others forms an arrangement of pseudolines in the plane. We apply these results to the smoothed distance or biotope transform metric, a geometric analogue of the Jaccard distance whose Voronoi diagrams can be used to determine the dilation of a star network with a given hub. For sufficiently closely spaced points in the plane, the Voronoi diagram of smoothed distance has linear complexity and can be computed efficiently. We also experiment with a variant of Lloyd's algorithm, adapted to smoothed distance, to find uniformly spaced point samples with exponentially decreasing density around a given point.


Dynamic spectrum sharing game by lease

Abstract: We propose and analyze a dynamic implementation of the property-rights model of cognitive radio. A primary link has the possibility to lease the owned spectrum to a MAC network of secondary nodes, in exchange for cooperation in the form of distributed space-time coding (DSTC). The cooperation and competition between the primary and secondary network are cast in the framework of sequential game. On one hand, the primary link attempts to maximize its quality of service in terms of signal-to-interference-plus-noise ratio (SINR); on the other hand, nodes in the secondary network compete for transmission within the leased time-slot following a power control mechanism. We consider both a baseline model with complete information and a more practical version with incomplete information, using the backward induction approach for the former and providing approximate algorithm for the latter. Analysis and numerical results show that our models and algorithms provide a promising framework for fair and effective spectrum sharing, both between primary and secondary networks and among secondary nodes.


Analysis of Group Multiuser Detection Based on Coalitional Game

Abstract: The issue of group-blind multiuser detection in MAC channel among wireless nodes in the environment of multiple networks coexisting and sharing spectrum is addressed under the Framework of coalitional game. We investigate the performance and stability of multiple access channel (MAC) with linear decorrelating multiuser detection under varying SNR, channel gains and coalitional structures, in which both single BS and multiple BSs cases were considered. The main results and conclusion are as follows: (1) the grand coalition is payoff maximizing under loose SNR; (2) it is in conformity with group and coalitional rationality forming coalition among nodes that have comparative channel gains.


Probabilistic reasoning with answer sets

Abstract: This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give several non-trivial examples and illustrate the use of P-log for knowledge representation and updating of knowledge. We argue that our approach to updates is more appealing than existing approaches. We give sufficiency conditions for the coherency of P-log programs and show that Bayes nets can be easily mapped to coherent P-log programs.


Cryptanalysis of the RSA-CEGD protocol

Abstract: Recently, Nenadi\'c et al. (2004) proposed the RSA-CEGD protocol for certified delivery of e-goods. This is a relatively complex scheme based on verifiable and recoverable encrypted signatures (VRES) to guarantee properties such as strong fairness and non-repudiation, among others. In this paper, we demonstrate how this protocol cannot achieve fairness by presenting a severe attack and also pointing out some other weaknesses.


Emergent Community Structure in Social Tagging Systems

Abstract: A distributed classification paradigm known as collaborative tagging has been widely adopted in new Web applications designed to manage and share online resources. Users of these applications organize resources (Web pages, digital photographs, academic papers) by associating with them freely chosen text labels, or tags. Here we leverage the social aspects of collaborative tagging and introduce a notion of resource distance based on the collective tagging activity of users. We collect data from a popular system and perform experiments showing that our definition of distance can be used to build a weighted network of resources with a detectable community structure. We show that this community structure clearly exposes the semantic relations among resources. The communities of resources that we observe are a genuinely emergent feature, resulting from the uncoordinated activity of a large number of users, and their detection paves the way for mapping emergent semantics in social tagging systems.