Computing a Finite Size Representation of the Set of Approximate Solutions of an MOP

Abstract: Recently, a framework for the approximation of the entire set of $\epsilon$-efficient solutions (denote by $E_\epsilon$) of a multi-objective optimization problem with stochastic search algorithms has been proposed. It was proven that such an algorithm produces -- under mild assumptions on the process to generate new candidate solutions --a sequence of archives which converges to $E_{\epsilon}$ in the limit and in the probabilistic sense. The result, though satisfactory for most discrete MOPs, is at least from the practical viewpoint not sufficient for continuous models: in this case, the set of approximate solutions typically forms an $n$-dimensional object, where $n$ denotes the dimension of the parameter space, and thus, it may come to perfomance problems since in practise one has to cope with a finite archive. Here we focus on obtaining finite and tight approximations of $E_\epsilon$, the latter measured by the Hausdorff distance. We propose and investigate a novel archiving strategy theoretically and empirically. For this, we analyze the convergence behavior of the algorithm, yielding bounds on the obtained approximation quality as well as on the cardinality of the resulting approximation, and present some numerical results.


Symmetry Breaking for Maximum Satisfiability

Abstract: Symmetries are intrinsic to many combinatorial problems including Boolean Satisfiability (SAT) and Constraint Programming (CP). In SAT, the identification of symmetry breaking predicates (SBPs) is a well-known, often effective, technique for solving hard problems. The identification of SBPs in SAT has been the subject of significant improvements in recent years, resulting in more compact SBPs and more effective algorithms. The identification of SBPs has also been applied to pseudo-Boolean (PB) constraints, showing that symmetry breaking can also be an effective technique for PB constraints. This paper extends further the application of SBPs, and shows that SBPs can be identified and used in Maximum Satisfiability (MaxSAT), as well as in its most well-known variants, including partial MaxSAT, weighted MaxSAT and weighted partial MaxSAT. As with SAT and PB, symmetry breaking predicates for MaxSAT and variants are shown to be effective for a representative number of problem domains, allowing solving problem instances that current state of the art MaxSAT solvers could not otherwise solve.


Steganography from weak cryptography

Abstract: We introduce a problem setting which we call ``the freedom fighters' problem''. It subtly differs from the prisoners' problem. We propose a steganographic method that allows Alice and Bob to fool Wendy the warden in this setting. Their messages are hidden in encryption keys. The recipient has no prior knowledge of these keys, and has to cryptanalyze ciphertexts in order to recover them. We show an example of the protocol and give a partial security analysis.


Weak Affine Light Typing is complete with respect to Safe Recursion on Notation

Abstract: Weak affine light typing (WALT) assigns light affine linear formulae as types to a subset of lambda-terms of System F. WALT is poly-time sound: if a lambda-term M has type in WALT, M can be evaluated with a polynomial cost in the dimension of the derivation that gives it a type. The evaluation proceeds under any strategy of a rewriting relation which is a mix of both call-by-name and call-by-value beta-reductions. WALT weakens, namely generalizes, the notion of "stratification of deductions", common to some Light Systems -- those logical systems, derived from Linear logic, to characterize the set of Polynomial functions -- . A weaker stratification allows to define a compositional embedding of Safe recursion on notation (SRN) into WALT. It turns out that the expressivity of WALT is strictly stronger than the one of the known Light Systems. The embedding passes through the representation of a subsystem of SRN. It is obtained by restricting the composition scheme of SRN to one that can only use its safe variables linearly. On one side, this suggests that SRN, in fact, can be redefined in terms of more primitive constructs. On the other, the embedding of SRN into WALT enjoys the two following remarkable aspects. Every datatype, required by the embedding, is represented from scratch, showing the strong structural proof-theoretical roots of WALT. Moreover, the embedding highlights a stratification structure of the normal and safe arguments, normally hidden inside the world of SRN-normal/safe variables: the less an argument is "polyomially impredicative", the deeper, in a formal, proof-theoretical sense, it is represented inside WALT. Finally, since WALT is SRN-complete it is also polynomial-time complete since SRN is.


A Memetic Algorithm for the Generalized Traveling Salesman Problem

Abstract: The generalized traveling salesman problem (GTSP) is an extension of the well-known traveling salesman problem. In GTSP, we are given a partition of cities into groups and we are required to find a minimum length tour that includes exactly one city from each group. The recent studies on this subject consider different variations of a memetic algorithm approach to the GTSP. The aim of this paper is to present a new memetic algorithm for GTSP with a powerful local search procedure. The experiments show that the proposed algorithm clearly outperforms all of the known heuristics with respect to both solution quality and running time. While the other memetic algorithms were designed only for the symmetric GTSP, our algorithm can solve both symmetric and asymmetric instances.


Generalized Traveling Salesman Problem Reduction Algorithms

Abstract: The generalized traveling salesman problem (GTSP) is an extension of the well-known traveling salesman problem. In GTSP, we are given a partition of cities into groups and we are required to find a minimum length tour that includes exactly one city from each group. The aim of this paper is to present a problem reduction algorithm that deletes redundant vertices and edges, preserving the optimal solution. The algorithm's running time is O(N^3) in the worst case, but it is significantly faster in practice. The algorithm has reduced the problem size by 15-20% on average in our experiments and this has decreased the solution time by 10-60% for each of the considered solvers.


Scalable Distributed Video-on-Demand: Theoretical Bounds and Practical Algorithms

Abstract: We analyze a distributed system where n nodes called boxes store a large set of videos and collaborate to serve simultaneously n videos or less. We explore under which conditions such a system can be scalable while serving any sequence of demands. We model this problem through a combination of two algorithms: a video allocation algorithm and a connection scheduling algorithm. The latter plays against an adversary that incrementally proposes video requests.


Sarbanes-Oxley: What About all the Spreadsheets?

Abstract: The Sarbanes-Oxley Act of 2002 has finally forced corporations to examine the validity of their spreadsheets. They are beginning to understand the spreadsheet error literature, including what it tells them about the need for comprehensive spreadsheet testing. However, controlling for fraud will require a completely new set of capabilities, and a great deal of new research will be needed to develop fraud control capabilities. This paper discusses the riskiness of spreadsheets, which can now be quantified to a considerable degree. It then discusses how to use control frameworks to reduce the dangers created by spreadsheets. It focuses especially on testing, which appears to be the most crucial element in spreadsheet controls.


On the Influence of Selection Operators on Performances in Cellular Genetic Algorithms

Abstract: In this paper, we study the influence of the selective pressure on the performance of cellular genetic algorithms. Cellular genetic algorithms are genetic algorithms where the population is embedded on a toroidal grid. This structure makes the propagation of the best so far individual slow down, and allows to keep in the population potentially good solutions. We present two selective pressure reducing strategies in order to slow down even more the best solution propagation. We experiment these strategies on a hard optimization problem, the quadratic assignment problem, and we show that there is a value for of the control parameter for both which gives the best performance. This optimal value does not find explanation on only the selective pressure, measured either by take over time and diversity evolution. This study makes us conclude that we need other tools than the sole selective pressure measures to explain the performances of cellular genetic algorithms.


On ad hoc routing with guaranteed delivery

Abstract: We point out a simple poly-time log-space routing algorithm in ad hoc networks with guaranteed delivery using universal exploration sequences.


Semi-continuous Sized Types and Termination

Abstract: Some type-based approaches to termination use sized types: an ordinal bound for the size of a data structure is stored in its type. A recursive function over a sized type is accepted if it is visible in the type system that recursive calls occur just at a smaller size. This approach is only sound if the type of the recursive function is admissible, i.e., depends on the size index in a certain way. To explore the space of admissible functions in the presence of higher-kinded data types and impredicative polymorphism, a semantics is developed where sized types are interpreted as functions from ordinals into sets of strongly normalizing terms. It is shown that upper semi-continuity of such functions is a sufficient semantic criterion for admissibility. To provide a syntactical criterion, a calculus for semi-continuous functions is developed.


The equations of the ideal latches

Abstract: The latches are simple circuits with feedback from the digital electrical engineering. We have included in our work the C element of Muller, the RS latch, the clocked RS latch, the D latch and also circuits containing two interconnected latches: the edge triggered RS flip-flop, the D flip-flop, the JK flip-flop, the T flip-flop. The purpose of this study is to model with equations the previous circuits, considered to be ideal, i.e. non-inertial. The technique of analysis is the pseudoboolean differential calculus.


A Unified Semi-Supervised Dimensionality Reduction Framework for Manifold Learning

Abstract: We present a general framework of semi-supervised dimensionality reduction for manifold learning which naturally generalizes existing supervised and unsupervised learning frameworks which apply the spectral decomposition. Algorithms derived under our framework are able to employ both labeled and unlabeled examples and are able to handle complex problems where data form separate clusters of manifolds. Our framework offers simple views, explains relationships among existing frameworks and provides further extensions which can improve existing algorithms. Furthermore, a new semi-supervised kernelization framework called ``KPCA trick'' is proposed to handle non-linear problems.


Cache-Oblivious Selection in Sorted X+Y Matrices

Abstract: Let X[0..n-1] and Y[0..m-1] be two sorted arrays, and define the mxn matrix A by A[j][i]=X[i]+Y[j]. Frederickson and Johnson gave an efficient algorithm for selecting the k-th smallest element from A. We show how to make this algorithm IO-efficient. Our cache-oblivious algorithm performs O((m+n)/B) IOs, where B is the block size of memory transfers.


Issues in Strategic Decision Modelling

Abstract: [Spreadsheet] Models are invaluable tools for strategic planning. Models help key decision makers develop a shared conceptual understanding of complex decisions, identify sensitivity factors and test management scenarios. Different modelling approaches are specialist areas in themselves. Model development can be onerous, expensive, time consuming, and often bewildering. It is also an iterative process where the true magnitude of the effort, time and data required is often not fully understood until well into the process. This paper explores the traditional approaches to strategic planning modelling commonly used in organisations and considers the application of a real-options approach to match and benefit from the increasing uncertainty in today's rapidly changing world.


Optimum Binary Search Trees on the Hierarchical Memory Model

Abstract: The Hierarchical Memory Model (HMM) of computation is similar to the standard Random Access Machine (RAM) model except that the HMM has a non-uniform memory organized in a hierarchy of levels numbered 1 through h. The cost of accessing a memory location increases with the level number, and accesses to memory locations belonging to the same level cost the same. Formally, the cost of a single access to the memory location at address a is given by m(a), where m: N -> N is the memory cost function, and the h distinct values of m model the different levels of the memory hierarchy. We study the problem of constructing and storing a binary search tree (BST) of minimum cost, over a set of keys, with probabilities for successful and unsuccessful searches, on the HMM with an arbitrary number of memory levels, and for the special case h=2. While the problem of constructing optimum binary search trees has been well studied for the standard RAM model, the additional parameter m for the HMM increases the combinatorial complexity of the problem. We present two dynamic programming algorithms to construct optimum BSTs bottom-up. These algorithms run efficiently under some natural assumptions about the memory hierarchy. We also give an efficient algorithm to construct a BST that is close to optimum, by modifying a well-known linear-time approximation algorithm for the RAM model. We conjecture that the problem of constructing an optimum BST for the HMM with an arbitrary memory cost function m is NP-complete.


Reducing Overconfidence in Spreadsheet Development

Abstract: Despite strong evidence of widespread errors, spreadsheet developers rarely subject their spreadsheets to post-development testing to reduce errors. This may be because spreadsheet developers are overconfident in the accuracy of their spreadsheets. This conjecture is plausible because overconfidence is present in a wide variety of human cognitive domains, even among experts. This paper describes two experiments in overconfidence in spreadsheet development. The first is a pilot study to determine the existence of overconfidence. The second tests a manipulation to reduce overconfidence and errors. The manipulation is modestly successful, indicating that overconfidence reduction is a promising avenue to pursue.


Spacetime Meshing for Discontinuous Galerkin Methods

Abstract: Spacetime discontinuous Galerkin (SDG) finite element methods are used to solve such PDEs involving space and time variables arising from wave propagation phenomena in important applications in science and engineering. To support an accurate and efficient solution procedure using SDG methods and to exploit the flexibility of these methods, we give a meshing algorithm to construct an unstructured simplicial spacetime mesh over an arbitrary simplicial space domain. Our algorithm is the first spacetime meshing algorithm suitable for efficient solution of nonlinear phenomena in anisotropic media using novel discontinuous Galerkin finite element methods for implicit solutions directly in spacetime. Given a triangulated d-dimensional Euclidean space domain M (a simplicial complex) and initial conditions of the underlying hyperbolic spacetime PDE, we construct an unstructured simplicial mesh of the (d+1)-dimensional spacetime domain M x [0,infinity). Our algorithm uses a near-optimal number of spacetime elements, each with bounded temporal aspect ratio for any finite prefix M x [0,T] of spacetime. Our algorithm is an advancing front procedure that constructs the spacetime mesh incrementally, an extension of the Tent Pitcher algorithm of Ungor and Sheffer (2000). In 2DxTime, our algorithm simultaneously adapts the size and shape of spacetime tetrahedra to a spacetime error indicator. We are able to incorporate more general front modification operations, such as edge flips and limited mesh smoothing. Our algorithm represents recent progress towards a meshing algorithm in 2DxTime to track moving domain boundaries and other singular surfaces such as shock fronts.


The Wall and The Ball: A Study of Domain Referent Spreadsheet Errors

Abstract: The Cell Error Rate in simple spreadsheets averages about 2% to 5%. This CER has been measured in domain free environments. This paper compares the CERs occurring in domain free and applied domain tasks. The applied domain task requires the application of simple linear algebra to a costing problem. The results show that domain referent knowledge influences participants' approaches to spreadsheet creation and spreadsheet usage. The conclusion is that spreadsheet error making is influenced by domain knowledge and domain perception. Qualitative findings also suggest that spreadsheet error making is a part of overall human behaviour, and ought to be analyzed against this wider canvas.


Efficient Spacetime Meshing with Nonlocal Cone Constraints

Abstract: Spacetime Discontinuous Galerkin (DG) methods are used to solve hyperbolic PDEs describing wavelike physical phenomena. When the PDEs are nonlinear, the speed of propagation of the phenomena, called the wavespeed, at any point in the spacetime domain is computed as part of the solution. We give an advancing front algorithm to construct a simplicial mesh of the spacetime domain suitable for DG solutions. Given a simplicial mesh of a bounded linear or planar space domain M, we incrementally construct a mesh of the spacetime domain M x [0,infinity) such that the solution can be computed in constant time per element. We add a patch of spacetime elements to the mesh at every step. The boundary of every patch is causal which means that the elements in the patch can be solved immediately and that the patches in the mesh are partially ordered by dependence. The elements in a single patch are coupled because they share implicit faces; however, the number of elements in each patch is bounded. The main contribution of this paper is sufficient constraints on the progress in time made by the algorithm at each step which guarantee that a new patch with causal boundary can be added to the mesh at every step even when the wavespeed is increasing discontinuously. Our algorithm adapts to the local gradation of the space mesh as well as the wavespeed that most constrains progress at each step. Previous algorithms have been restricted at each step by the maximum wavespeed throughout the entire spacetime domain.


Derandomizing the Isolation Lemma and Lower Bounds for Circuit Size

Abstract: The isolation lemma of Mulmuley et al \cite{MVV87} is an important tool in the design of randomized algorithms and has played an important role in several nontrivial complexity upper bounds. On the other hand, polynomial identity testing is a well-studied algorithmic problem with efficient randomized algorithms and the problem of obtaining efficient \emph{deterministic} identity tests has received a lot of attention recently. The goal of this note is to compare the isolation lemma with polynomial identity testing: 1. We show that derandomizing reasonably restricted versions of the isolation lemma implies circuit size lower bounds. We derive the circuit lower bounds by examining the connection between the isolation lemma and polynomial identity testing. We give a randomized polynomial-time identity test for noncommutative circuits of polynomial degree based on the isolation lemma. Using this result, we show that derandomizing the isolation lemma implies noncommutative circuit size lower bounds. The restricted versions of the isolation lemma we consider are natural and would suffice for the standard applications of the isolation lemma. 2. From the result of Klivans-Spielman \cite{KS01} we observe that there is a randomized polynomial-time identity test for commutative circuits of polynomial degree, also based on a more general isolation lemma for linear forms. Consequently, derandomization of (a suitable version of) this isolation lemma also implies circuit size lower bounds in the commutative setting.


Testing data types implementations from algebraic specifications

Abstract: Algebraic specifications of data types provide a natural basis for testing data types implementations. In this framework, the conformance relation is based on the satisfaction of axioms. This makes it possible to formally state the fundamental concepts of testing: exhaustive test set, testability hypotheses, oracle. Various criteria for selecting finite test sets have been proposed. They depend on the form of the axioms, and on the possibilities of observation of the implementation under test. This last point is related to the well-known oracle problem. As the main interest of algebraic specifications is data type abstraction, testing a concrete implementation raises the issue of the gap between the abstract description and the concrete representation. The observational semantics of algebraic specifications bring solutions on the basis of the so-called observable contexts. After a description of testing methods based on algebraic specifications, the chapter gives a brief presentation of some tools and case studies, and presents some applications to other formal methods involving datatypes.


Cauchy's Arm Lemma on a Growing Sphere

Abstract: We propose a variant of Cauchy's Lemma, proving that when a convex chain on one sphere is redrawn (with the same lengths and angles) on a larger sphere, the distance between its endpoints increases. The main focus of this work is a comparison of three alternate proofs, to show the links between Toponogov's Comparison Theorem, Legendre's Theorem and Cauchy's Arm Lemma.


Differentiation of Kaltofen's division-free determinant algorithm

Abstract: Kaltofen has proposed a new approach in [Kaltofen 1992] for computing matrix determinants. The algorithm is based on a baby steps/giant steps construction of Krylov subspaces, and computes the determinant as the constant term of a characteristic polynomial. For matrices over an abstract field and by the results of Baur and Strassen 1983, the determinant algorithm, actually a straight-line program, leads to an algorithm with the same complexity for computing the adjoint of a matrix [Kaltofen 1992]. However, the latter is obtained by the reverse mode of automatic differentiation and somehow is not ``explicit''. We study this adjoint algorithm, show how it can be implemented (without resorting to an automatic transformation), and demonstrate its use on polynomial matrices.


A Semi-Automatic Framework to Discover Epistemic Modalities in Scientific Articles

Abstract: Documents in scientific newspapers are often marked by attitudes and opinions of the author and/or other persons, who contribute with objective and subjective statements and arguments as well. In this respect, the attitude is often accomplished by a linguistic modality. As in languages like english, french and german, the modality is expressed by special verbs like can, must, may, etc. and the subjunctive mood, an occurrence of modalities often induces that these verbs take over the role of modality. This is not correct as it is proven that modality is the instrument of the whole sentence where both the adverbs, modal particles, punctuation marks, and the intonation of a sentence contribute. Often, a combination of all these instruments are necessary to express a modality. In this work, we concern with the finding of modal verbs in scientific texts as a pre-step towards the discovery of the attitude of an author. Whereas the input will be an arbitrary text, the output consists of zones representing modalities.


On the Stretch Factor of Convex Delaunay Graphs

Abstract: Let C be a compact and convex set in the plane that contains the origin in its interior, and let S be a finite set of points in the plane. The Delaunay graph DG_C(S) of S is defined to be the dual of the Voronoi diagram of S with respect to the convex distance function defined by C. We prove that DG_C(S) is a t-spanner for S, for some constant t that depends only on the shape of the set C. Thus, for any two points p and q in S, the graph DG_C(S) contains a path between p and q whose Euclidean length is at most t times the Euclidean distance between p and q.


Discrete schemes for Gaussian curvature and their convergence

Abstract: In this paper, several discrete schemes for Gaussian curvature are surveyed. The convergence property of a modified discrete scheme for the Gaussian curvature is considered. Furthermore, a new discrete scheme for Gaussian curvature is resented. We prove that the new scheme converges at the regular vertex with valence not less than 5. By constructing a counterexample, we also show that it is impossible for building a discrete scheme for Gaussian curvature which converges over the regular vertex with valence 4. Finally, asymptotic errors of several discrete scheme for Gaussian curvature are compared.


P is a proper subset of NP

Abstract: The purpose of this article is to examine and limit the conditions in which the P complexity class could be equivalent to the NP complexity class. Proof is provided by demonstrating that as the number of clauses in a NP-complete problem approaches infinity, the number of input sets processed per computation performed also approaches infinity when solved by a polynomial time solution. It is then possible to determine that the only deterministic optimization of a NP-complete problem that could prove P = NP would be one that examines no more than a polynomial number of input sets for a given problem. It is then shown that subdividing the set of all possible input sets into a representative polynomial search partition is a problem in the FEXP complexity class. The findings of this article are combined with the findings of other articles in this series of 4 articles. The final conclusion will be demonstrated that P =/= NP.


Adaptive Dynamics of Realistic Small-World Networks

Abstract: Continuing in the steps of Jon Kleinberg's and others celebrated work on decentralized search in small-world networks, we conduct an experimental analysis of a dynamic algorithm that produces small-world networks. We find that the algorithm adapts robustly to a wide variety of situations in realistic geographic networks with synthetic test data and with real world data, even when vertices are uneven and non-homogeneously distributed. We investigate the same algorithm in the case where some vertices are more popular destinations for searches than others, for example obeying power-laws. We find that the algorithm adapts and adjusts the networks according to the distributions, leading to improved performance. The ability of the dynamic process to adapt and create small worlds in such diverse settings suggests a possible mechanism by which such networks appear in nature.


A Survey of Quantum Programming Languages: History, Methods, and Tools

Abstract: Quantum computer programming is emerging as a new subject domain from multidisciplinary research in quantum computing, computer science, mathematics (especially quantum logic, lambda calculi, and linear logic), and engineering attempts to build the first non-trivial quantum computer. This paper briefly surveys the history, methods, and proposed tools for programming quantum computers circa late 2007. It is intended to provide an extensive but non-exhaustive look at work leading up to the current state-of-the-art in quantum computer programming. Further, it is an attempt to analyze the needed programming tools for quantum programmers, to use this analysis to predict the direction in which the field is moving, and to make recommendations for further development of quantum programming language tools.


Prospective Algorithms for Quantum Evolutionary Computation

Abstract: This effort examines the intersection of the emerging field of quantum computing and the more established field of evolutionary computation. The goal is to understand what benefits quantum computing might offer to computational intelligence and how computational intelligence paradigms might be implemented as quantum programs to be run on a future quantum computer. We critically examine proposed algorithms and methods for implementing computational intelligence paradigms, primarily focused on heuristic optimization methods including and related to evolutionary computation, with particular regard for their potential for eventual implementation on quantum computing hardware.


Approximating L1-distances between mixture distributions using random projections

Abstract: We consider the problem of computing L1-distances between every pair ofcprobability densities from a given family. We point out that the technique of Cauchy random projections (Indyk'06) in this context turns into stochastic integrals with respect to Cauchy motion. For piecewise-linear densities these integrals can be sampled from if one can sample from the stochastic integral of the function x->(1,x). We give an explicit density function for this stochastic integral and present an efficient sampling algorithm. As a consequence we obtain an efficient algorithm to approximate the L1-distances with a small relative error. For piecewise-polynomial densities we show how to approximately sample from the distributions resulting from the stochastic integrals. This also results in an efficient algorithm to approximate the L1-distances, although our inability to get exact samples worsens the dependence on the parameters.


A Lower Bound on the Area of a 3-Coloured Disk Packing

Abstract: Given a set of unit-disks in the plane with union area $A$, what fraction of $A$ can be covered by selecting a pairwise disjoint subset of the disks? Rado conjectured 1/4 and proved $1/4.41$. Motivated by the problem of channel-assignment for wireless access points, in which use of 3 channels is a standard practice, we consider a variant where the selected subset of disks must be 3-colourable with disks of the same colour pairwise-disjoint. For this variant of the problem, we conjecture that it is always possible to cover at least $1/1.41$ of the union area and prove $1/2.09$. We also provide an $O(n^2)$ algorithm to select a subset achieving a $1/2.77$ bound.


A Dynamical Boolean Network

Abstract: We propose a Dynamical Boolean Network (DBN), which is a Virtual Boolean Network (VBN) whose set of states is fixed but whose transition matrix can change from one discrete time step to another. The transition matrix $T_{k}$ of our DBN for time step $k$ is of the form $Q^{-1}TQ$, where $T$ is a transition matrix (of a VBN) defined at time step $k$ in the course of the construction of our DBN and $Q$ is the matrix representation of some randomly chosen permutation $P$ of the states of our DBN. For each of several classes of such permutations, we carried out a number of simulations of a DBN with two nodes; each of our simulations consisted of 1,000 trials of 10,000 time steps each. In one of our simulations, only six of the 16 possible single-node transition rules for a VBN with two nodes were visited a total of 300,000 times (over all 1,000 trials). In that simulation, linearity appears to play a significant role in that three of those six single-node transition rules are transition rules of a Linear Virtual Boolean Network (LVBN); the other three are the negations of the first three. We also discuss the notions of a Probabilistic Boolean Network and a Hidden Markov Model--in both cases, in the context of using an arbitrary (though not necessarily one-to-one) function to label the states of a VBN.


Securing U-Healthcare Sensor Networks using Public Key Based Scheme

Abstract: Recent emergence of electronic culture uplifts healthcare facilities to a new era with the aid of wireless sensor network (WSN) technology. Due to the sensitiveness of medical data, austere privacy and security are inevitable for all parts of healthcare systems. However, the constantly evolving nature and constrained resources of sensors in WSN inflict unavailability of a lucid line of defense to ensure perfect security. In order to provide holistic security, protections must be incorporated in every component of healthcare sensor networks. This paper proposes an efficient security scheme for healthcare applications of WSN which uses the notion of public key cryptosystem. Our entire security scheme comprises basically of two parts; a key handshaking scheme based on simple linear operations and the derivation of decryption key by a receiver node for a particular sender in the network. Our architecture allows both base station to node or node to base station secure communications, and node-to-node secure communications. We consider both the issues of stringent security and network performance to propose our security scheme.


Cryptanalysis of Yang-Wang-Chang's Password Authentication Scheme with Smart Cards

Abstract: In 2005, Yang, Wang, and Chang proposed an improved timestamp-based password authentication scheme in an attempt to overcome the flaws of Yang-Shieh_s legendary timestamp-based remote authentication scheme using smart cards. After analyzing the improved scheme proposed by Yang-Wang-Chang, we have found that their scheme is still insecure and vulnerable to four types of forgery attacks. Hence, in this paper, we prove that, their claim that their scheme is intractable is incorrect. Also, we show that even an attack based on Sun et al._s attack could be launched against their scheme which they claimed to resolve with their proposal.


M\'ethode de calcul du rayonnement acoustique de structures complexes

Abstract: In the automotive industry, predicting noise during design cycle is a necessary step. Well-known methods exist to answer this issue in low frequency domain. Among these, Finite Element Methods, adapted to closed domains, are quite easy to implement whereas Boundary Element Methods are more adapted to infinite domains, but may induce singularity problems. In this article, the described method, the SDM, allows to use both methods in their best application domain. A new method is also presented to solve the SDM exterior problem. Instead of using Boundary Element Methods, an original use of Finite Elements is made. Efficiency of this new version of the Substructure Deletion Method is discussed.


New Lower Bounds for the Maximum Number of Runs in a String

Abstract: We show a new lower bound for the maximum number of runs in a string. We prove that for any e > 0, (a -- e)n is an asymptotic lower bound, where a = 56733/60064 = 0.944542. It is superior to the previous bound 0.927 given by Franek et al. Moreover, our construction of the strings and the proof is much simpler than theirs.


Geometric Data Analysis, From Correspondence Analysis to Structured Data Analysis (book review)

Abstract: Review of: Brigitte Le Roux and Henry Rouanet, Geometric Data Analysis, From Correspondence Analysis to Structured Data Analysis, Kluwer, Dordrecht, 2004, xi+475 pp.


Immune System Approaches to Intrusion Detection - A Review

Abstract: The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.


Data Reduction in Intrusion Alert Correlation

Abstract: Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.


Asymptotic behavior of growth functions of D0L-systems

Abstract: A D0L-system is a triple (A, f, w) where A is a finite alphabet, f is an endomorphism of the free monoid over A, and w is a word over A. The D0L-sequence generated by (A, f, w) is the sequence of words (w, f(w), f(f(w)), f(f(f(w))), ...). The corresponding sequence of lengths, that is the function mapping each non-negative integer n to |f^n(w)|, is called the growth function of (A, f, w). In 1978, Salomaa and Soittola deduced the following result from their thorough study of the theory of rational power series: if the D0L-sequence generated by (A, f, w) is not eventually the empty word then there exist a non-negative integer d and a real number b greater than or equal to one such that |f^n(w)| behaves like n^d b^n as n tends to infinity. The aim of the present paper is to present a short, direct, elementary proof of this theorem.


Discovering More Accurate Frequent Web Usage Patterns

Abstract: Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web users. As in classical data mining, data preparation and pattern discovery are the main issues in web usage mining. The first phase of web usage mining is the data processing phase, which includes the session reconstruction operation from server logs. Session reconstruction success directly affects the quality of the frequent patterns discovered in the next phase. In reactive web usage mining techniques, the source data is web server logs and the topology of the web pages served by the web server domain. Other kinds of information collected during the interactive browsing of web site by user, such as cookies or web logs containing similar information, are not used. The next phase of web usage mining is discovering frequent user navigation patterns. In this phase, pattern discovery methods are applied on the reconstructed sessions obtained in the first phase in order to discover frequent user patterns. In this paper, we propose a frequent web usage pattern discovery method that can be applied after session reconstruction phase. In order to compare accuracy performance of session reconstruction phase and pattern discovery phase, we have used an agent simulator, which models behavior of web users and generates web user navigation as well as the log data kept by the web server.


A $O(\log m)$, deterministic, polynomial-time computable approximation of Lewis Carroll's scoring rule

Abstract: We provide deterministic, polynomial-time computable voting rules that approximate Dodgson's and (the ``minimization version'' of) Young's scoring rules to within a logarithmic factor. Our approximation of Dodgson's rule is tight up to a constant factor, as Dodgson's rule is $\NP$-hard to approximate to within some logarithmic factor. The ``maximization version'' of Young's rule is known to be $\NP$-hard to approximate by any constant factor. Both approximations are simple, and natural as rules in their own right: Given a candidate we wish to score, we can regard either its Dodgson or Young score as the edit distance between a given set of voter preferences and one in which the candidate to be scored is the Condorcet winner. (The difference between the two scoring rules is the type of edits allowed.) We regard the marginal cost of a sequence of edits to be the number of edits divided by the number of reductions (in the candidate's deficit against any of its opponents in the pairwise race against that opponent) that the edits yield. Over a series of rounds, our scoring rules greedily choose a sequence of edits that modify exactly one voter's preferences and whose marginal cost is no greater than any other such single-vote-modifying sequence.


The Geometry of Interaction of Differential Interaction Nets

Abstract: The Geometry of Interaction purpose is to give a semantic of proofs or programs accounting for their dynamics. The initial presentation, translated as an algebraic weighting of paths in proofnets, led to a better characterization of the lambda-calculus optimal reduction. Recently Ehrhard and Regnier have introduced an extension of the Multiplicative Exponential fragment of Linear Logic (MELL) that is able to express non-deterministic behaviour of programs and a proofnet-like calculus: Differential Interaction Nets. This paper constructs a proper Geometry of Interaction (GoI) for this extension. We consider it both as an algebraic theory and as a concrete reversible computation. We draw links between this GoI and the one of MELL. As a by-product we give for the first time an equational theory suitable for the GoI of the Multiplicative Additive fragment of Linear Logic.


On Kernelization of Supervised Mahalanobis Distance Learners

Abstract: This paper focuses on the problem of kernelizing an existing supervised Mahalanobis distance learner. The following features are included in the paper. Firstly, three popular learners, namely, "neighborhood component analysis", "large margin nearest neighbors" and "discriminant neighborhood embedding", which do not have kernel versions are kernelized in order to improve their classification performances. Secondly, an alternative kernelization framework called "KPCA trick" is presented. Implementing a learner in the new framework gains several advantages over the standard framework, e.g. no mathematical formulas and no reprogramming are required for a kernel implementation, the framework avoids troublesome problems such as singularity, etc. Thirdly, while the truths of representer theorems are just assumptions in previous papers related to ours, here, representer theorems are formally proven. The proofs validate both the kernel trick and the KPCA trick in the context of Mahalanobis distance learning. Fourthly, unlike previous works which always apply brute force methods to select a kernel, we investigate two approaches which can be efficiently adopted to construct an appropriate kernel for a given dataset. Finally, numerical results on various real-world datasets are presented.


Fast k Nearest Neighbor Search using GPU

Abstract: The recent improvements of graphics processing units (GPU) offer to the computer vision community a powerful processing platform. Indeed, a lot of highly-parallelizable computer vision problems can be significantly accelerated using GPU architecture. Among these algorithms, the k nearest neighbor search (KNN) is a well-known problem linked with many applications such as classification, estimation of statistical properties, etc. The main drawback of this task lies in its computation burden, as it grows polynomially with the data size. In this paper, we show that the use of the NVIDIA CUDA API accelerates the search for the KNN up to a factor of 120.


Distributed and Recursive Parameter Estimation in Parametrized Linear State-Space Models

Abstract: We consider a network of sensors deployed to sense a spatio-temporal field and estimate a parameter of interest. We are interested in the case where the temporal process sensed by each sensor can be modeled as a state-space process that is perturbed by random noise and parametrized by an unknown parameter. To estimate the unknown parameter from the measurements that the sensors sequentially collect, we propose a distributed and recursive estimation algorithm, which we refer to as the incremental recursive prediction error algorithm. This algorithm has the distributed property of incremental gradient algorithms and the on-line property of recursive prediction error algorithms. We study the convergence behavior of the algorithm and provide sufficient conditions for its convergence. Our convergence result is rather general and contains as special cases the known convergence results for the incremental versions of the least-mean square algorithm. Finally, we use the algorithm developed in this paper to identify the source of a gas-leak (diffusing source) in a closed warehouse and also report numerical simulations to verify convergence.


Mechanizing the Metatheory of LF

Abstract: LF is a dependent type theory in which many other formal systems can be conveniently embedded. However, correct use of LF relies on nontrivial metatheoretic developments such as proofs of correctness of decision procedures for LF's judgments. Although detailed informal proofs of these properties have been published, they have not been formally verified in a theorem prover. We have formalized these properties within Isabelle/HOL using the Nominal Datatype Package, closely following a recent article by Harper and Pfenning. In the process, we identified and resolved a gap in one of the proofs and a small number of minor lacunae in others. We also formally derive a version of the type checking algorithm from which Isabelle/HOL can generate executable code. Besides its intrinsic interest, our formalization provides a foundation for studying the adequacy of LF encodings, the correctness of Twelf-style metatheoretic reasoning, and the metatheory of extensions to LF.


A classification of invasive patterns in AOP

Abstract: Aspect-Oriented Programming (AOP) improves modularity by encapsulating crosscutting concerns into aspects. Some mechanisms to compose aspects allow invasiveness as a mean to integrate concerns. Invasiveness means that AOP languages have unrestricted access to program properties. Such kind of languages are interesting because they allow performing complex operations and better introduce functionalities. In this report we present a classification of invasive patterns in AOP. This classification characterizes the aspects invasive behavior and allows developers to abstract about the aspect incidence over the program they crosscut.


Information Acquisition and Exploitation in Multichannel Wireless Networks

Abstract: A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by transmitting a control packet in it. Since probing all channels consumes significant energy and time, a user needs to determine what and how much information it needs to acquire about the instantaneous states of the available channels so that it can maximize its transmission rate. This motivates the study of the trade-off between the cost of information acquisition and its value towards improving the transmission rate. A simple model is presented for studying this information acquisition and exploitation trade-off when the channels are multi-state, with different distributions and information acquisition costs. The objective is to maximize a utility function which depends on both the cost and value of information. Solution techniques are presented for computing near-optimal policies with succinct representation in polynomial time. These policies provably achieve at least a fixed constant factor of the optimal utility on any problem instance, and in addition, have natural characterizations. The techniques are based on exploiting the structure of the optimal policy, and use of Lagrangean relaxations which simplify the space of approximately optimal solutions.


On affine usages in signal-based communication

Abstract: We describe a type system for a synchronous pi-calculus formalising the notion of affine usage in signal-based communication. In particular, we identify a limited number of usages that preserve affinity and that can be composed. As a main application of the resulting system, we show that typable programs are deterministic.


The Choquet integral for the aggregation of interval scales in multicriteria decision making

Abstract: This paper addresses the question of which models fit with information concerning the preferences of the decision maker over each attribute, and his preferences about aggregation of criteria (interacting criteria). We show that the conditions induced by these information plus some intuitive conditions lead to a unique possible aggregation operator: the Choquet integral.


Phutball is PSPACE-hard

Abstract: We consider the $n\times n$ game of Phutball. It is shown that, given an arbitrary position of stones on the board, it is a PSPACE-hard problem to determine whether the specified player can win the game, regardless of the opponent's choices made during the game.


Prediciendo el generador cuadratico (in Spanish)

Abstract: Let p be a prime and a, c be integers such that a<>0 mod p. The quadratic generator is a sequence (u_n) of pseudorandom numbers defined by u_{n+1}=a*(u_n)^2+c mod p. In this article we probe that if we know sufficiently many of the most significant bits of two consecutive values u_n, u_{n+1}, then we can compute the seed u_0 except for a small number of exceptional values. ----- Sean p un primo, a y c enteros tales que a<>0 mod p. El generador cuadratico es una sucesion (u_n) de numeros pseudoaleatorios definidos por la relacion u_{n+1}=a*(u_n)^2+c mod p. En este trabajo demostramos que si conocemos un numero suficientemente grande de los bits mas significativos para dos valores consecutivos u_n, u_{n+1}, entonces podemos descubrir en tiempo polinomial la semilla u_0, excepto para un conjunto pequeno de valores excepcionales.


An Optimal Bloom Filter Replacement Based on Matrix Solving

Abstract: We suggest a method for holding a dictionary data structure, which maps keys to values, in the spirit of Bloom Filters. The space requirements of the dictionary we suggest are much smaller than those of a hashtable. We allow storing n keys, each mapped to value which is a string of k bits. Our suggested method requires nk + o(n) bits space to store the dictionary, and O(n) time to produce the data structure, and allows answering a membership query in O(1) memory probes. The dictionary size does not depend on the size of the keys. However, reducing the space requirements of the data structure comes at a certain cost. Our dictionary has a small probability of a one sided error. When attempting to obtain the value for a key that is stored in the dictionary we always get the correct answer. However, when testing for membership of an element that is not stored in the dictionary, we may get an incorrect answer, and when requesting the value of such an element we may get a certain random value. Our method is based on solving equations in GF(2^k) and using several hash functions. Another significant advantage of our suggested method is that we do not require using sophisticated hash functions. We only require pairwise independent hash functions. We also suggest a data structure that requires only nk bits space, has O(n2) preprocessing time, and has a O(log n) query time. However, this data structures requires a uniform hash functions. In order replace a Bloom Filter of n elements with an error proability of 2^{-k}, we require nk + o(n) memory bits, O(1) query time, O(n) preprocessing time, and only pairwise independent hash function. Even the most advanced previously known Bloom Filter would require nk+O(n) space, and a uniform hash functions, so our method is significantly less space consuming especially when k is small.


Lambda-Free Logical Frameworks

Abstract: We present the definition of the logical framework TF, the Type Framework. TF is a lambda-free logical framework; it does not include lambda-abstraction or product kinds. We give formal proofs of several results in the metatheory of TF, and show how it can be conservatively embedded in the logical framework LF: its judgements can be seen as the judgements of LF that are in beta-normal, eta-long normal form. We show how several properties, such as adequacy theorems for object theories and the injectivity of constants, can be proven more easily in TF, and then `lifted' to LF.


A Reliability-based Framework for Multi-path Routing Analysis in Mobile Ad-Hoc Networks

Abstract: Unlike traditional routing procedures that, at the best, single out a unique route, multi-path routing protocols discover proactively several alternative routes. It has been recognized that multi-path routing can be more efficient than traditional one mainly for mobile ad hoc networks, where route failure events are frequent. Most studies in the area of multi-path routing focus on heuristic methods, and the performances of these strategies are commonly evaluated by numerical simulations. The need of a theoretical analysis motivates such a paper, which proposes to resort to the terminal-pair routing reliability as performance metric. This metric allows one to assess the performance gain due to the availability of route diversity. By resorting to graph theory, we propose an analytical framework to evaluate the tolerance of multi-path route discovery processes against route failures for mobile ad hoc networks. Moreover, we derive a useful bound to easily estimate the performance improvements achieved by multi-path routing with respect to any traditional routing protocol. Finally, numerical simulation results show the effectiveness of this performance analysis.


On the Extension of Pseudo-Boolean Functions for the Aggregation of Interacting Criteria

Abstract: The paper presents an analysis on the use of integrals defined for non-additive measures (or capacities) as the Choquet and the \Sipos{} integral, and the multilinear model, all seen as extensions of pseudo-Boolean functions, and used as a means to model interaction between criteria in a multicriteria decision making problem. The emphasis is put on the use, besides classical comparative information, of information about difference of attractiveness between acts, and on the existence, for each point of view, of a ``neutral level'', allowing to introduce the absolute notion of attractive or repulsive act. It is shown that in this case, the Sipos integral is a suitable solution, although not unique. Properties of the Sipos integral as a new way of aggregating criteria are shown, with emphasis on the interaction among criteria.


Characterizing User Mobility in Second Life

Abstract: In this work we present a measurement study of user mobility in Second Life. We first discuss different techniques to collect user traces and then focus on results obtained using a crawler that we built. Tempted by the question whether our methodology could provide similar results to those obtained in real-world experiments, we study the statistical distribution of user contacts and show that from a qualitative point of view user mobility in Second Life presents similar traits to those of real humans. We further push our analysis to line of sight networks that emerge from user interaction and show that they are highly clustered. Lastly, we focus on the spatial properties of user movements and observe that users in Second Life revolve around several point of interests traveling in general short distances. Besides our findings, the traces collected in this work can be very useful for trace-driven simulations of communication schemes in delay tolerant networks and their performance evaluation.


A complexity dichotomy for partition functions with mixed signs

Abstract: Partition functions, also known as homomorphism functions, form a rich family of graph invariants that contain combinatorial invariants such as the number of k-colourings or the number of independent sets of a graph and also the partition functions of certain "spin glass" models of statistical physics such as the Ising model. Building on earlier work by Dyer, Greenhill and Bulatov, Grohe, we completely classify the computational complexity of partition functions. Our main result is a dichotomy theorem stating that every partition function is either computable in polynomial time or #P-complete. Partition functions are described by symmetric matrices with real entries, and we prove that it is decidable in polynomial time in terms of the matrix whether a given partition function is in polynomial time or #P-complete. While in general it is very complicated to give an explicit algebraic or combinatorial description of the tractable cases, for partition functions described by a Hadamard matrices -- these turn out to be central in our proofs -- we obtain a simple algebraic tractability criterion, which says that the tractable cases are those "representable" by a quadratic polynomial over the field GF(2).


A Security Protocol for Multi-User Authentication

Abstract: In this note we propose an encryption communication protocol which also provides database security. For the encryption of the data communication we use a transformation similar to the Cubic Public-key transformation. This method represents a many-to-one mapping which increases the complexity for any brute force attack. Some interesting properties of the transformation are also included which are basic in the authentication protocol.


Schemes for Deterministic Polynomial Factoring

Abstract: In this work we relate the deterministic complexity of factoring polynomials (over finite fields) to certain combinatorial objects we call m-schemes. We extend the known conditional deterministic subexponential time polynomial factoring algorithm for finite fields to get an underlying m-scheme. We demonstrate how the properties of m-schemes relate to improvements in the deterministic complexity of factoring polynomials over finite fields assuming the generalized Riemann Hypothesis (GRH). In particular, we give the first deterministic polynomial time algorithm (assuming GRH) to find a nontrivial factor of a polynomial of prime degree n where (n-1) is a smooth number.


Linear Time Recognition Algorithms for Topological Invariants in 3D

Abstract: In this paper, we design linear time algorithms to recognize and determine topological invariants such as the genus and homology groups in 3D. These properties can be used to identify patterns in 3D image recognition. This has tremendous amount of applications in 3D medical image analysis. Our method is based on cubical images with direct adjacency, also called (6,26)-connectivity images in discrete geometry. According to the fact that there are only six types of local surface points in 3D and a discrete version of the well-known Gauss-Bonnett Theorem in differential geometry, we first determine the genus of a closed 2D-connected component (a closed digital surface). Then, we use Alexander duality to obtain the homology groups of a 3D object in 3D space.


Tight Bounds and Faster Algorithms for Directed Max-Leaf Problems

Abstract: An out-tree $T$ of a directed graph $D$ is a rooted tree subgraph with all arcs directed outwards from the root. An out-branching is a spanning out-tree. By $l(D)$ and $l_s(D)$ we denote the maximum number of leaves over all out-trees and out-branchings of $D$, respectively. We give fixed parameter tractable algorithms for deciding whether $l_s(D)\geq k$ and whether $l(D)\geq k$ for a digraph $D$ on $n$ vertices, both with time complexity $2^{O(k\log k)} \cdot n^{O(1)}$. This improves on previous algorithms with complexity $2^{O(k^3\log k)} \cdot n^{O(1)}$ and $2^{O(k\log^2 k)} \cdot n^{O(1)}$, respectively. To obtain the complexity bound in the case of out-branchings, we prove that when all arcs of $D$ are part of at least one out-branching, $l_s(D)\geq l(D)/3$. The second bound we prove in this paper states that for strongly connected digraphs $D$ with minimum in-degree 3, $l_s(D)\geq \Theta(\sqrt{n})$, where previously $l_s(D)\geq \Theta(\sqrt[3]{n})$ was the best known bound. This bound is tight, and also holds for the larger class of digraphs with minimum in-degree 3 in which every arc is part of at least one out-branching.


The non-anticipation of the asynchronous systems

Abstract: The asynchronous systems are the models of the asynchronous circuits from the digital electrical engineering and non-anticipation is one of the most important properties in systems theory. Our present purpose is to introduce several concepts of non-anticipation of the asynchronous systems.


Towards Physarum robots: computing and manipulating on water surface

Abstract: Plasmodium of Physarym polycephalum is an ideal biological substrate for implementing concurrent and parallel computation, including combinatorial geometry and optimization on graphs. We report results of scoping experiments on Physarum computing in conditions of minimal friction, on the water surface. We show that plasmodium of Physarum is capable for computing a basic spanning trees and manipulating of light-weight objects. We speculate that our results pave the pathways towards design and implementation of amorphous biological robots.


Some properties of the regular asynchronous systems

Abstract: The asynchronous systems are the models of the asynchronous circuits from the digital electrical engineering. An asynchronous system f is a multi-valued function that assigns to each admissible input u a set f(u) of possible states x in f(u). A special case of asynchronous system consists in the existence of a Boolean function \Upsilon such that for any u and any x in f(u), a certain equation involving \Upsilon is fulfilled. Then \Upsilon is called the generator function of f (Moisil used the terminology of network function) and we say that f is generated by \Upsilon. The systems that have a generator function are called regular. Our purpose is to continue the study of the generation of the asynchronous systems that was started in [2], [3].


Analytical correlation of routing table length index and routing path length index in hierarchical routing model

Abstract: In Kleinrock and Kamoun's paper, the inverse relation of routing table length index and routing path length index in hierarchical routing model is illustrated. In this paper we give the analytical correlation of routing table length index and routing path length index in hierarchical routing model.


Comparing and Combining Methods for Automatic Query Expansion

Abstract: Query expansion is a well known method to improve the performance of information retrieval systems. In this work we have tested different approaches to extract the candidate query terms from the top ranked documents returned by the first-pass retrieval. One of them is the cooccurrence approach, based on measures of cooccurrence of the candidate and the query terms in the retrieved documents. The other one, the probabilistic approach, is based on the probability distribution of terms in the collection and in the top ranked set. We compare the retrieval improvement achieved by expanding the query with terms obtained with different methods belonging to both approaches. Besides, we have developed a na\"ive combination of both kinds of method, with which we have obtained results that improve those obtained with any of them separately. This result confirms that the information provided by each approach is of a different nature and, therefore, can be used in a combined manner.


Physical Layer Network Coding Over Finite And Infinite Fields

Abstract: Direct application of network coding at the physical layer - physical layer network coding (PNC) - is a promising technique for two-way relay wireless networks. In a two-way relay network, relay nodes are used to relay two-way information flows between pairs of end nodes. This paper proposes a precise definition for PNC. Specifically, in PNC, a relay node does not decode the source information from the two ends separately, but rather directly maps the combined signals received simultaneously to a signal to be relayed. Based on this definition, PNC can be further sub-classed into two categories - PNCF (PNC over finite field) and PNCI (PNC over infinite field) - according to whether the network-code field (or groups, rings) adopted is finite or infinite. For each of PNCF and PNCI, we consider two specific estimation techniques for dealing with noise in the mapping process. The performance of the four schemes is investigated by means of analysis and simulation, assuming symbol-level synchronization only.


A Logic Programming Framework for Combinational Circuit Synthesis

Abstract: Logic Programming languages and combinational circuit synthesis tools share a common "combinatorial search over logic formulae" background. This paper attempts to reconnect the two fields with a fresh look at Prolog encodings for the combinatorial objects involved in circuit synthesis. While benefiting from Prolog's fast unification algorithm and built-in backtracking mechanism, efficiency of our search algorithm is ensured by using parallel bitstring operations together with logic variable equality propagation, as a mapping mechanism from primary inputs to the leaves of candidate Leaf-DAGs implementing a combinational circuit specification. After an exhaustive expressiveness comparison of various minimal libraries, a surprising first-runner, Strict Boolean Inequality "<" together with constant function "1" also turns out to have small transistor-count implementations, competitive to NAND-only or NOR-only libraries. As a practical outcome, a more realistic circuit synthesizer is implemented that combines rewriting-based simplification of (<,1) circuits with exhaustive Leaf-DAG circuit search. Keywords: logic programming and circuit design, combinatorial object generation, exact combinational circuit synthesis, universal boolean logic libraries, symbolic rewriting, minimal transistor-count circuit synthesis


Optimal Mechansim Design and Money Burning

Abstract: Mechanism design is now a standard tool in computer science for aligning the incentives of self-interested agents with the objectives of a system designer. There is, however, a fundamental disconnect between the traditional application domains of mechanism design (such as auctions) and those arising in computer science (such as networks): while monetary transfers (i.e., payments) are essential for most of the known positive results in mechanism design, they are undesirable or even technologically infeasible in many computer systems. Classical impossibility results imply that the reach of mechanisms without transfers is severely limited. Computer systems typically do have the ability to reduce service quality--routing systems can drop or delay traffic, scheduling protocols can delay the release of jobs, and computational payment schemes can require computational payments from users (e.g., in spam-fighting systems). Service degradation is tantamount to requiring that users burn money}, and such ``payments'' can be used to influence the preferences of the agents at a cost of degrading the social surplus. We develop a framework for the design and analysis of money-burning mechanisms to maximize the residual surplus--the total value of the chosen outcome minus the payments required.


Truthful Unsplittable Flow for Large Capacity Networks

Abstract: In this paper, we focus our attention on the large capacities unsplittable flow problem in a game theoretic setting. In this setting, there are selfish agents, which control some of the requests characteristics, and may be dishonest about them. It is worth noting that in game theoretic settings many standard techniques, such as randomized rounding, violate certain monotonicity properties, which are imperative for truthfulness, and therefore cannot be employed. In light of this state of affairs, we design a monotone deterministic algorithm, which is based on a primal-dual machinery, which attains an approximation ratio of $\frac{e}{e-1}$, up to a disparity of $\epsilon$ away. This implies an improvement on the current best truthful mechanism, as well as an improvement on the current best combinatorial algorithm for the problem under consideration. Surprisingly, we demonstrate that any algorithm in the family of reasonable iterative path minimizing algorithms, cannot yield a better approximation ratio. Consequently, it follows that in order to achieve a monotone PTAS, if exists, one would have to exert different techniques. We also consider the large capacities \textit{single-minded multi-unit combinatorial auction problem}. This problem is closely related to the unsplittable flow problem since one can formulate it as a special case of the integer linear program of the unsplittable flow problem. Accordingly, we obtain a comparable performance guarantee by refining the algorithm suggested for the unsplittable flow problem.


From Qualitative to Quantitative Proofs of Security Properties Using First-Order Conditional Logic

Abstract: A first-order conditional logic is considered, with semantics given by a variant of epsilon-semantics, where p -> q means that Pr(q | p) approaches 1 super-polynomially --faster than any inverse polynomial. This type of convergence is needed for reasoning about security protocols. A complete axiomatization is provided for this semantics, and it is shown how a qualitative proof of the correctness of a security protocol can be automatically converted to a quantitative proof appropriate for reasoning about concrete security.


Products of Ordinary Differential Operators by Evaluation and Interpolation

Abstract: It is known that multiplication of linear differential operators over ground fields of characteristic zero can be reduced to a constant number of matrix products. We give a new algorithm by evaluation and interpolation which is faster than the previously-known one by a constant factor, and prove that in characteristic zero, multiplication of differential operators and of matrices are computationally equivalent problems. In positive characteristic, we show that differential operators can be multiplied in nearly optimal time. Theoretical results are validated by intensive experiments.


Push & Pull: autonomous deployment of mobile sensors for a complete coverage

Abstract: Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.


Object Re-Use & Exchange: A Resource-Centric Approach

Abstract: The OAI Object Reuse and Exchange (OAI-ORE) framework recasts the repository-centric notion of digital object to a bounded aggregation of Web resources. In this manner, digital library content is more integrated with the Web architecture, and thereby more accessible to Web applications and clients. This generalized notion of an aggregation that is independent of repository containment conforms more closely with notions in eScience and eScholarship, where content is distributed across multiple services and databases. We provide a motivation for the OAI-ORE project, review previous interoperability efforts, describe draft ORE specifications and report on promising results from early experimentation that illustrate improved interoperability and reuse of digital objects.


Parimutuel Betting on Permutations

Abstract: We focus on a permutation betting market under parimutuel call auction model where traders bet on the final ranking of n candidates. We present a Proportional Betting mechanism for this market. Our mechanism allows the traders to bet on any subset of the n x n 'candidate-rank' pairs, and rewards them proportionally to the number of pairs that appear in the final outcome. We show that market organizer's decision problem for this mechanism can be formulated as a convex program of polynomial size. More importantly, the formulation yields a set of n x n unique marginal prices that are sufficient to price the bets in this mechanism, and are computable in polynomial-time. The marginal prices reflect the traders' beliefs about the marginal distributions over outcomes. We also propose techniques to compute the joint distribution over n! permutations from these marginal distributions. We show that using a maximum entropy criterion, we can obtain a concise parametric form (with only n x n parameters) for the joint distribution which is defined over an exponentially large state space. We then present an approximation algorithm for computing the parameters of this distribution. In fact, the algorithm addresses the generic problem of finding the maximum entropy distribution over permutations that has a given mean, and may be of independent interest.


Power Series Composition and Change of Basis

Abstract: Efficient algorithms are known for many operations on truncated power series (multiplication, powering, exponential, ...). Composition is a more complex task. We isolate a large class of power series for which composition can be performed efficiently. We deduce fast algorithms for converting polynomials between various bases, including Euler, Bernoulli, Fibonacci, and the orthogonal Laguerre, Hermite, Jacobi, Krawtchouk, Meixner and Meixner-Pollaczek.


Random sampling of colourings of sparse random graphs with a constant number of colours

Abstract: In this work we present a simple and efficient algorithm which, with high probability, provides an almost uniform sample from the set of proper k-colourings on an instance of a sparse random graph G(n,d/n), where k=k(d) is a sufficiently large constant. Our algorithm is not based on the Markov Chain Monte Carlo method (M.C.M.C.). Instead, we provide a novel proof of correctness of our Algorithm that is based on interesting "spatial mixing" properties of colourings of G(n,d/n). Our result improves upon previous results (based on M.C.M.C.) that required a number of colours growing unboundedly with n.


Theory and Applications of Two-dimensional, Null-boundary, Nine-Neighborhood, Cellular Automata Linear rules

Abstract: This paper deals with the theory and application of 2-Dimensional, nine-neighborhood, null- boundary, uniform as well as hybrid Cellular Automata (2D CA) linear rules in image processing. These rules are classified into nine groups depending upon the number of neighboring cells influences the cell under consideration. All the Uniform rules have been found to be rendering multiple copies of a given image depending on the groups to which they belong where as Hybrid rules are also shown to be characterizing the phenomena of zooming in, zooming out, thickening and thinning of a given image. Further, using hybrid CA rules a new searching algorithm is developed called Sweepers algorithm which is found to be applicable to simulate many inter disciplinary research areas like migration of organisms towards a single point destination, Single Attractor and Multiple Attractor Cellular Automata Theory, Pattern Classification and Clustering Problem, Image compression, Encryption and Decryption problems, Density Classification problem etc.


Secure Remote Voting Using Paper Ballots

Abstract: Internet voting will probably be one of the most significant achievements of the future information society. It will have an enormous impact on the election process making it fast, reliable and inexpensive. Nonetheless, so far remote voting is considered to be very difficult, as one has to take into account susceptibility of the voter's PC to various cyber-attacks. As a result, most the research effort is put into developing protocols and machines for poll-site electronic voting. Although these solutions yield promising results, they cannot be directly adopted to Internet voting because of secure platform problem. However, the cryptographic components they utilize may be very useful. This paper presents a scheme based on combination of mixnets and homomorphic encryption borrowed from robust poll-site voting, along with techniques recommended for remote voting -- code sheets and test ballots. The protocol tries to minimize the trust put in voter's PC by making the voter responsible for manual encryption of his vote. To achieve this, the voter obtains a paper ballot that allows him to scramble the vote by performing simple operations (lookup in a table). Creation of paper ballots, as well as decryption of votes, is performed by a group of cooperating trusted servers. As a result, the scheme is characterized by strong asymmetry -- all computations are carried out on the server side. In consequence it does not require any additional hardware on the voter's side, and offers distributed trust, receipt-freeness and verifiability.


Information filtering based on wiki index database

Abstract: In this paper we present a profile-based approach to information filtering by an analysis of the content of text documents. The Wikipedia index database is created and used to automatically generate the user profile from the user document collection. The problem-oriented Wikipedia subcorpora are created (using knowledge extracted from the user profile) for each topic of user interests. The index databases of these subcorpora are applied to filtering information flow (e.g., mails, news). Thus, the analyzed texts are classified into several topics explicitly presented in the user profile. The paper concentrates on the indexing part of the approach. The architecture of an application implementing the Wikipedia indexing is described. The indexing method is evaluated using the Russian and Simple English Wikipedia.


Fast Conversion Algorithms for Orthogonal Polynomials

Abstract: We discuss efficient conversion algorithms for orthogonal polynomials. We describe a known conversion algorithm from an arbitrary orthogonal basis to the monomial basis, and deduce a new algorithm of the same complexity for the converse operation.


Causal models have no complete axiomatic characterization

Abstract: Markov networks and Bayesian networks are effective graphic representations of the dependencies embedded in probabilistic models. It is well known that independencies captured by Markov networks (called graph-isomorphs) have a finite axiomatic characterization. This paper, however, shows that independencies captured by Bayesian networks (called causal models) have no axiomatization by using even countably many Horn or disjunctive clauses. This is because a sub-independency model of a causal model may be not causal, while graph-isomorphs are closed under sub-models.


On the Expressiveness and Complexity of ATL

Abstract: ATL is a temporal logic geared towards the specification and verification of properties in multi-agents systems. It allows to reason on the existence of strategies for coalitions of agents in order to enforce a given property. In this paper, we first precisely characterize the complexity of ATL model-checking over Alternating Transition Systems and Concurrent Game Structures when the number of agents is not fixed. We prove that it is \Delta^P_2 - and \Delta^P_?_3-complete, depending on the underlying multi-agent model (ATS and CGS resp.). We also consider the same problems for some extensions of ATL. We then consider expressiveness issues. We show how ATS and CGS are related and provide translations between these models w.r.t. alternating bisimulation. We also prove that the standard definition of ATL (built on modalities "Next", "Always" and "Until") cannot express the duals of its modalities: it is necessary to explicitely add the modality "Release".


Short proofs of strong normalization

Abstract: This paper presents simple, syntactic strong normalization proofs for the simply-typed lambda-calculus and the polymorphic lambda-calculus (system F) with the full set of logical connectives, and all the permutative reductions. The normalization proofs use translations of terms and types to systems, for which strong normalization property is known.


Augmenting Actual Life Through MUVEs

Abstract: The necessity of supporting more and more social interaction (and not only the mere information sharing) in online environments is the disruptive force upon which phenomena ascribed to the Web2.0 paradigm continuously bud. People interacting in online socio-technical environments mould technology on their needs, seamlessly integrating it into their everyday life. MUVEs (Multi User Virtual Environments) are no exception and, in several cases, represent the new frontier in this field. In this work we analyze if and how MUVEs can be considered a mean for augmenting communities (and more in general people) life. We trace a framework of analysis based on four main observations, and through these lenses we look at Second Life and at several projects we are currently developing in that synthetic world.


Design and Implementation of a Master of Science in Information and Computer Sciences - An Inventory and retrospect for the last four years

Abstract: This Master of Science in Computer and Information Sciences (MICS) is an international accredited master program that has been initiated in 2004 and started in September 2005. MICS is a research-oriented academic study of 4 semesters and a continuation of the Bachelor towards the PhD. It is completely taught in English, supported by lecturers coming from more than ten different countries. This report compass a description of its underlying architecture, describes some implementation details and gives a presentation of diverse experiences and results. As the program has been designed and implemented right after the creation of the University, the significance of the program is moreover a self-discovery of the computer science department, which has finally led to the creation of the today's research institutes and research axes.


p-Symmetric fuzzy measures

Abstract: In this paper we propose a generalization of the concept of symmetric fuzzy measure based in a decomposition of the universal set in what we have called subsets of indifference. Some properties of these measures are studied, as well as their Choquet integral. Finally, a degree of interaction between the subsets of indifference is defined.


A Critique of a Polynomial-time SAT Solver Devised by Sergey Gubin

Abstract: This paper refutes the validity of the polynomial-time algorithm for solving satisfiability proposed by Sergey Gubin. Gubin introduces the algorithm using 3-SAT and eventually expands it to accept a broad range of forms of the Boolean satisfiability problem. Because 3-SAT is NP-complete, the algorithm would have implied P = NP, had it been correct. Additionally, this paper refutes the correctness of his polynomial-time reduction of SAT to 2-SAT.


Information Resources in High-Energy Physics: Surveying the Present Landscape and Charting the Future Course

Abstract: Access to previous results is of paramount importance in the scientific process. Recent progress in information management focuses on building e-infrastructures for the optimization of the research workflow, through both policy-driven and user-pulled dynamics. For decades, High-Energy Physics (HEP) has pioneered innovative solutions in the field of information management and dissemination. In light of a transforming information environment, it is important to assess the current usage of information resources by researchers and HEP provides a unique test-bed for this assessment. A survey of about 10% of practitioners in the field reveals usage trends and information needs. Community-based services, such as the pioneering arXiv and SPIRES systems, largely answer the need of the scientists, with a limited but increasing fraction of younger users relying on Google. Commercial services offered by publishers or database vendors are essentially unused in the field. The survey offers an insight into the most important features that users require to optimize their research workflow. These results inform the future evolution of information management in HEP and, as these researchers are traditionally ``early adopters'' of innovation in scholarly communication, can inspire developments of disciplinary repositories serving other communities.


Generalized Modal Satisfiability

Abstract: It is well known that modal satisfiability is PSPACE-complete (Ladner 1977). However, the complexity may decrease if we restrict the set of propositional operators used. Note that there exist an infinite number of propositional operators, since a propositional operator is simply a Boolean function. We completely classify the complexity of modal satisfiability for every finite set of propositional operators, i.e., in contrast to previous work, we classify an infinite number of problems. We show that, depending on the set of propositional operators, modal satisfiability is PSPACE-complete, coNP-complete, or in P. We obtain this trichotomy not only for modal formulas, but also for their more succinct representation using modal circuits. We consider both the uni-modal and the multi-modal case, and study the dual problem of validity as well.


Decentralized Knowledge and Learning in Strategic Multi-user Communication

Abstract: Please see the content of this report.


An Analysis of Key Factors for the Success of the Communal Management of Knowledge

Abstract: This paper explores the links between Knowledge Management and new community-based models of the organization from both a theoretical and an empirical perspective. From a theoretical standpoint, we look at Communities of Practice (CoPs) and Knowledge Management (KM) and explore the links between the two as they relate to the use of information systems to manage knowledge. We begin by reviewing technologically supported approaches to KM and introduce the idea of "Systemes d'Aide a la Gestion des Connaissances" SAGC (Systems to aid the Management of Knowledge). Following this we examine the contribution that communal structures such as CoPs can make to intraorganizational KM and highlight some of 'success factors' for this approach to KM that are found in the literature. From an empirical standpoint, we present the results of a survey involving the Chief Knowledge Officers (CKOs) of twelve large French businesses; the objective of this study was to identify the factors that might influence the success of such approaches. The survey was analysed using thematic content analysis and the results are presented here with some short illustrative quotes from the CKOs. Finally, the paper concludes with some brief reflections on what can be learnt from looking at this problem from these two perspectives.


The Concept of Appropriation as a Heuristic for Conceptualising the Relationship between Technology, People and Organisations

Abstract: The stated aim of this conference is to debate the continuing evolution of IS in businesses and other organisations. This paper seeks to contribute to this debate by exploring the concept of appropriation from a number of different epistemological, cultural and linguistic viewpoints to allow us to explore 'the black box' of appropriation and to gain a fuller understanding of the term. At the conceptual level, it will examine some of the different ways in which people have attempted to explain the relationship between the objective and concrete features of technology and the subjective and shifting nature of the people and organisation within which that technology is deployed. At the cultural and linguistic level the paper will examine the notion as it is found in the Francophone literature, where the term has a long and rich history, and the Anglophone literature where appropriation is seen as a rather more specialist term. The paper will conclude with some observations on the ongoing nature of the debate, the value of reading beyond the literature with which one is familiar and the rewards that come from exploring different historical (and linguistic) viewpoints.


Identifying 'Hidden' Communities of Practice within Electronic Networks: Some Preliminary Premises

Abstract: This paper examines the possibility of discovering 'hidden' (potential) Communities of Practice (CoPs) inside electronic networks, and then using this knowledge to nurture them into a fully developed Virtual Community of Practice (VCoP). Starting from the standpoint of the need to manage knowledge, it discusses several questions related to this subject: the characteristics of 'hidden' communities; the relation between CoPs, Virtual Communities (VCs), Distributed Communities of Practice (DCoPs) and Virtual Communities of Practice (VCoPs); the methods used to search for 'hidden' CoPs; and the possible ways of changing 'hidden' CoPs into fully developed VCoPs. The paper also presents some preliminary findings from a semi-structured interview conducted in The Higher Education Academy Psychology Network (UK). These findings are contrasted against the theory discussed and some additional proposals are suggested at the end.


Philosophical Smoke Signals: Theory and Practice in Information Systems Design

Abstract: Although the gulf between the theory and practice in Information Systems is much lamented, few researchers have offered a way forward except through a number of (failed) attempts to develop a single systematic theory for Information Systems. In this paper, we encourage researchers to re-examine the practical consequences of their theoretical arguments. By examining these arguments we may be able to form a number of more rigorous theories of Information Systems, allowing us to draw theory and practice together without undertaking yet another attempt at the holy grail of a single unified systematic theory of Information Systems.


Experiments in Model-Checking Optimistic Replication Algorithms

Abstract: This paper describes a series of model-checking experiments to verify optimistic replication algorithms based on Operational Transformation (OT) approach used for supporting collaborative edition. We formally define, using tool UPPAAL, the behavior and the main consistency requirement (i.e. convergence property) of the collaborative editing systems, as well as the abstract behavior of the environment where these systems are supposed to operate. Due to data replication and the unpredictable nature of user interactions, such systems have infinitely many states. So, we show how to exploit some features of the UPPAAL specification language to attenuate the severe state explosion problem. Two models are proposed. The first one, called concrete model, is very close to the system implementation but runs up against a severe explosion of states. The second model, called symbolic model, aims to overcome the limitation of the concrete model by delaying the effective selection and execution of editing operations until the construction of symbolic execution traces of all sites is completed. Experimental results have shown that the symbolic model allows a significant gain in both space and time. Using the symbolic model, we have been able to show that if the number of sites exceeds 2 then the convergence property is not satisfied for all OT algorithms considered here. A counterexample is provided for every algorithm.


Parameterized Low-distortion Embeddings - Graph metrics into lines and trees

Abstract: We revisit the issue of low-distortion embedding of metric spaces into the line, and more generally, into the shortest path metric of trees, from the parameterized complexity perspective.Let $M=M(G)$ be the shortest path metric of an edge weighted graph $G=(V,E)$ on $n$ vertices. We describe algorithms for the problem of finding a low distortion non-contracting embedding of $M$ into line and tree metrics. We give an $O(nd^4(2d+1)^{2d})$ time algorithm that for an unweighted graph metric $M$ and integer $d$ either constructs an embedding of $M$ into the line with distortion at most $d$, or concludes that no such embedding exists. We find the result surprising, because the considered problem bears a strong resemblance to the notoriously hard Bandwidth Minimization problem which does not admit any FPT algorithm unless an unlikely collapse of parameterized complexity classes occurs. We show that our algorithm can also be applied to construct small distortion embeddings of weighted graph metrics. The running time of our algorithm is $O(n(dW)^4(2d+1)^{2dW})$ where $W$ is the largest edge weight of the input graph. We also show that deciding whether a weighted graph metric $M(G)$ with maximum weight $W < |V(G)|$ can be embedded into the line with distortion at most $d$ is NP-Complete for every fixed rational $d \geq 2$. This rules out any possibility of an algorithm with running time $O((nW)^{h(d)})$ where $h$ is a function of $d$ alone. We generalize the result on embedding into the line by proving that for any tree $T$ with maximum degree $\Delta$, embedding of $M$ into a shortest path metric of $T$ is FPT, parameterized by $(\Delta,d)$.


Intelligence gathering by capturing the social processes within prisons

Abstract: We present a prototype system that can be used to capture longitudinal socialising processes by recording people's encounters in space. We argue that such a system can usefully be deployed in prisons and other detention facilities in order help intelligence analysts assess the behaviour or terrorist and organised crime groups, and their potential relationships. Here we present the results of a longitudinal study, carried out with civilians, which demonstrates the capabilities of our system.


Visibly Tree Automata with Memory and Constraints

Abstract: Tree automata with one memory have been introduced in 2001. They generalize both pushdown (word) automata and the tree automata with constraints of equality between brothers of Bogaert and Tison. Though it has a decidable emptiness problem, the main weakness of this model is its lack of good closure properties. We propose a generalization of the visibly pushdown automata of Alur and Madhusudan to a family of tree recognizers which carry along their (bottom-up) computation an auxiliary unbounded memory with a tree structure (instead of a symbol stack). In other words, these recognizers, called Visibly Tree Automata with Memory (VTAM) define a subclass of tree automata with one memory enjoying Boolean closure properties. We show in particular that they can be determinized and the problems like emptiness, membership, inclusion and universality are decidable for VTAM. Moreover, we propose several extensions of VTAM whose transitions may be constrained by different kinds of tests between memories and also constraints a la Bogaert and Tison comparing brother subtrees in the tree in input. We show that some of these classes of constrained VTAM keep the good closure and decidability properties, and we demonstrate their expressiveness with relevant examples of tree languages.


Size matters: performance declines if your pixels are too big or too small

Abstract: We present a conceptual model that describes the effect of pixel size on target acquisition. We demonstrate the use of our conceptual model by applying it to predict and explain the results of an experiment to evaluate users' performance in a target acquisition task involving three distinct display sizes: standard desktop, small and large displays. The results indicate that users are fastest on standard desktop displays, undershoots are the most common error on small displays and overshoots are the most common error on large displays. We propose heuristics to maintain usability when changing displays. Finally, we contribute to the growing body of evidence that amplitude does affect performance in a display-based pointing task.


A lower bound on web services composition

Abstract: A web service is modeled here as a finite state machine. A composition problem for web services is to decide if a given web service can be constructed from a given set of web services; where the construction is understood as a simulation of the specification by a fully asynchronous product of the given services. We show an EXPTIME-lower bound for this problem, thus matching the known upper bound. Our result also applies to richer models of web services, such as the Roman model.


On the performance of approximate equilibria in congestion games

Abstract: We study the performance of approximate Nash equilibria for linear congestion games. We consider how much the price of anarchy worsens and how much the price of stability improves as a function of the approximation factor $\epsilon$. We give (almost) tight upper and lower bounds for both the price of anarchy and the price of stability for atomic and non-atomic congestion games. Our results not only encompass and generalize the existing results of exact equilibria to $\epsilon$-Nash equilibria, but they also provide a unified approach which reveals the common threads of the atomic and non-atomic price of anarchy results. By expanding the spectrum, we also cast the existing results in a new light. For example, the Pigou network, which gives tight results for exact Nash equilibria of selfish routing, remains tight for the price of stability of $\epsilon$-Nash equilibria but not for the price of anarchy.