A Better Reduction Theorem for Store Buffers

Abstract: When verifying a concurrent program, it is usual to assume that memory is sequentially consistent. However, most modern multiprocessors depend on store buffering for efficiency, and provide native sequential consistency only at a substantial performance penalty. To regain sequential consistency, a programmer has to follow an appropriate programming discipline. However, na\"ive disciplines, such as protecting all shared accesses with locks, are not flexible enough for building high-performance multiprocessor software. We present a new discipline for concurrent programming under TSO (total store order, with store buffer forwarding). It does not depend on concurrency primitives, such as locks. Instead, threads use ghost operations to acquire and release ownership of memory addresses. A thread can write to an address only if no other thread owns it, and can read from an address only if it owns it or it is shared and the thread has flushed its store buffer since it last wrote to an address it did not own. This discipline covers both coarse-grained concurrency (where data is protected by locks) as well as fine-grained concurrency (where atomic operations race to memory). We formalize this discipline in Isabelle/HOL, and prove that if every execution of a program in a system without store buffers follows the discipline, then every execution of the program with store buffers is sequentially consistent. Thus, we can show sequential consistency under TSO by ordinary assertional reasoning about the program, without having to consider store buffers at all.


The directed Hausdorff distance between imprecise point sets

Abstract: We consider the directed Hausdorff distance between point sets in the plane, where one or both point sets consist of imprecise points. An imprecise point is modelled by a disc given by its centre and a radius. The actual position of an imprecise point may be anywhere within its disc. Due to the direction of the Hausdorff Distance and whether its tight upper or lower bound is computed there are several cases to consider. For every case we either show that the computation is NP-hard or we present an algorithm with a polynomial running time. Further we give several approximation algorithms for the hard cases and show that one of them cannot be approximated better than with factor 3, unless P=NP.


A Graph Spectral Approach for Computing Approximate Nash Equilibria

Abstract: We present a new methodology for computing approximate Nash equilibria for two-person non-cooperative games based upon certain extensions and specializations of an existing optimization approach previously used for the derivation of fixed approximations for this problem. In particular, the general two-person problem is reduced to an indefinite quadratic programming problem of special structure involving the $n \times n$ adjacency matrix of an induced simple graph specified by the input data of the game, where $n$ is the number of players' strategies. Using this methodology and exploiting certain properties of the positive part of the spectrum of the induced graph, we show that for any $\varepsilon > 0$ there is an algorithm to compute an $\varepsilon$-approximate Nash equilibrium in time $n^{\xi(m)/\varepsilon}$, where, $\xi (m) = \sum_{i=1}^m \lambda_i / n$ and $\lambda_1, \lambda_2, >..., \lambda_m$ are the positive eigenvalues of the adjacency matrix of the graph. For classes of games for which $\xi (m)$ is a constant, there is a PTAS. Based on the best upper bound derived for $\xi(m)$ so far, the worst case complexity of the method is bounded by the subexponential $n^{\sqrt{m}/\varepsilon}$.


Planar Subgraph Isomorphism Revisited

Abstract: The problem of Subgraph Isomorphism is defined as follows: Given a pattern H and a host graph G on n vertices, does G contain a subgraph that is isomorphic to H? Eppstein [SODA 95, J'GAA 99] gives the first linear time algorithm for subgraph isomorphism for a fixed-size pattern, say of order k, and arbitrary planar host graph, improving upon the O(n^\sqrt{k})-time algorithm when using the ``Color-coding'' technique of Alon et al [J'ACM 95]. Eppstein's algorithm runs in time k^O(k) n, that is, the dependency on k is superexponential. We solve an open problem posed in Eppstein's paper and improve the running time to 2^O(k) n, that is, single exponential in k while keeping the term in n linear. Next to deciding subgraph isomorphism, we can construct a solution and enumerate all solutions in the same asymptotic running time. We may list w subgraphs with an additive term O(w k) in the running time of our algorithm. We introduce the technique of "embedded dynamic programming" on a suitably structured graph decomposition, which exploits the topology of the underlying embeddings of the subgraph pattern (rather than of the host graph). To achieve our results, we give an upper bound on the number of partial solutions in each dynamic programming step as a function of pattern size--as it turns out, for the planar subgraph isomorphism problem, that function is single exponential in the number of vertices in the pattern.


On graphs without a C4 or a diamond

Abstract: We consider the class of (C4, diamond)-free graphs; graphs in this class do not contain a C4 or a diamond as an induced subgraph. We provide an efficient recognition algorithm for this class. We count the number of maximal cliques in a (C4, diamond)-free graph and the number of n-vertex, labeled (C4, diamond)-free graphs. We also give an efficient algorithm for finding a largest clique in the more general class of (house, diamond)-free graphs.


A regularity lemma, and low-weight approximators, for low-degree polynomial threshold functions

Abstract: We give a "regularity lemma" for degree-d polynomial threshold functions (PTFs) over the Boolean cube {-1,1}^n. This result shows that every degree-d PTF can be decomposed into a constant number of subfunctions such that almost all of the subfunctions are close to being regular PTFs. Here a "regular PTF is a PTF sign(p(x)) where the influence of each variable on the polynomial p(x) is a small fraction of the total influence of p. As an application of this regularity lemma, we prove that for any constants d \geq 1, \eps \geq 0, every degree-d PTF over n variables has can be approximated to accuracy eps by a constant-degree PTF that has integer weights of total magnitude O(n^d). This weight bound is shown to be optimal up to constant factors.


Bayesian Algorithmic Mechanism Design

Abstract: The principal problem in algorithmic mechanism design is in merging the incentive constraints imposed by selfish behavior with the algorithmic constraints imposed by computational intractability. This field is motivated by the observation that the preeminent approach for designing incentive compatible mechanisms, namely that of Vickrey, Clarke, and Groves; and the central approach for circumventing computational obstacles, that of approximation algorithms, are fundamentally incompatible: natural applications of the VCG approach to an approximation algorithm fails to yield an incentive compatible mechanism. We consider relaxing the desideratum of (ex post) incentive compatibility (IC) to Bayesian incentive compatibility (BIC), where truthtelling is a Bayes-Nash equilibrium (the standard notion of incentive compatibility in economics). For welfare maximization in single-parameter agent settings, we give a general black-box reduction that turns any approximation algorithm into a Bayesian incentive compatible mechanism with essentially the same approximation factor.


A Secure and Fault tolerant framework for Mobile IPv6 based networks

Abstract: Mobile IPv6 will be an integral part of the next generation Internet protocol. The importance of mobility in the Internet gets keep on increasing. Current specification of Mobile IPv6 does not provide proper support for reliability in the mobile network and there are other problems associated with it. In this paper, we propose Virtual Private Network (VPN) based Home Agent Reliability Protocol (VHAHA) as a complete system architecture and extension to Mobile IPv6 that supports reliability and offers solutions to the security problems that are found in Mobile IP registration part. The key features of this protocol over other protocols are: better survivability, transparent failure detection and recovery, reduced complexity of the system and workload, secure data transfer and improved overall performance.


A New Generic Taxonomy on Hybrid Malware Detection Technique

Abstract: Malware is a type of malicious program that replicate from host machine and propagate through network. It has been considered as one type of computer attack and intrusion that can do a variety of malicious activity on a computer. This paper addresses the current trend of malware detection techniques and identifies the significant criteria in each technique to improve malware detection in Intrusion Detection System (IDS). Several existing techniques are analyzing from 48 various researches and the capability criteria of malware detection technique have been reviewed. From the analysis, a new generic taxonomy of malware detection technique have been proposed named Hybrid Malware Detection Technique (Hybrid MDT) which consists of Hybrid Signature and Anomaly detection technique and Hybrid Specification based and Anomaly detection technique to complement the weaknesses of the existing malware detection technique in detecting known and unknown attack as well as reducing false alert before and during the intrusion occur.


Approximating Mathematical Semantic Web Services Using Approximation Formulas and Numerical Methods

Abstract: Mathematical semantic web services are very useful in practice, but only a small number of research results are reported in this area. In this paper we present a method of obtaining an approximation of a mathematical semantic web service, from its semantic description, using existing mathematical semantic web services, approximation formulas, and numerical methods techniques. We also give a method for automatic comparison of two complexity functions. In addition, we present a method for classifying the numerical methods mathematical semantic web services from a library.


Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS

Abstract: This paper proposes an intrusion detection and prediction system based on uncertain and imprecise inference networks and its implementation. Giving a historic of sessions, it is about proposing a method of supervised learning doubled of a classifier permitting to extract the necessary knowledge in order to identify the presence or not of an intrusion in a session and in the positive case to recognize its type and to predict the possible intrusions that will follow it. The proposed system takes into account the uncertainty and imprecision that can affect the statistical data of the historic. The systematic utilization of an unique probability distribution to represent this type of knowledge supposes a too rich subjective information and risk to be in part arbitrary. One of the first objectives of this work was therefore to permit the consistency between the manner of which we represent information and information which we really dispose.


Range Non-Overlapping Indexing

Abstract: We study the non-overlapping indexing problem: Given a text T, preprocess it so that you can answer queries of the form: given a pattern P, report the maximal set of non-overlapping occurrences of P in T. A generalization of this problem is the range non-overlapping indexing where in addition we are given two indexes i,j to report the maximal set of non-overlapping occurrences between these two indexes. We suggest new solutions for these problems. For the non-overlapping problem our solution uses O(n) space with query time of O(m + occ_{NO}). For the range non-overlapping problem we propose a solution with O(n\log^\epsilon n) space for some 0<\epsilon<1 and O(m + \log\log n + occ_{ij,NO}) query time.


Modelling and Analysing Dynamic Decentralised Systems

Abstract: We introduce a method to specify and analyse decentralised dynamic systems; the method is based on the combination of an event-based multi-process system specification approach with a multi-facet analysis approach that considers a reference abstract model and several specific ones derived from the abstract model in order to support facet-wise analysis. The method is illustrated with the modelling and the analysis of a mobile ad-hoc network. The Event-B framework and its related tools B4free and ProB are used to conduct the experiments.


Characteristics of multithreading models for high-performance IO driven network applications

Abstract: In a technological landscape that is quickly moving toward dense multi-CPU and multi-core computer systems, where using multithreading is an increasingly popular application design decision, it is important to choose a proper model for distributing tasks across multiple threads that will result in the best efficiency for the application and the system as a whole. The work described in this paper creates, implements and evaluates various models of distributing tasks to CPU threads and investigates their characteristics for use in modern high-performance network servers. The results presented here comprise a roadmap of models for building multithreaded server applications for modern server hardware and Unix-like operating systems.


On the Different Shapes Arising in a Family of Rational Curves Depending on a Parameter

Abstract: Given a family of rational curves depending on a real parameter, defined by its parametric equations, we provide an algorithm to compute a finite partition of the parameter space (${\Bbb R}$, in general) so that the shape of the family stays invariant along each element of the partition. So, from this partition the topology types in the family can be determined. The algorithm is based on a geometric interpretation of previous work (\cite{JGRS}) for the implicit case. However, in our case the algorithm works directly with the parametrization of the family, and the implicit equation does not need to be computed. Timings comparing the algorithm in the implicit and the parametric cases are given; these timings show that the parametric algorithm developed here provides in general better results than the known algorithm for the implicit case.


Local Shape of Generalized Offsets to Algebraic Curves

Abstract: In this paper we study the local behavior of an algebraic curve under a geometric construction which is a variation of the usual offsetting construction, namely the {\it generalized} offsetting process (\cite {SS99}). More precisely, here we discuss when and how this geometric construction may cause local changes in the shape of an algebraic curve, and we compare our results with those obtained for the case of classical offsets (\cite{JGS07}). For these purposes, we use well-known notions of Differential Geometry, and also the notion of {\it local shape} introduced in \cite{JGS07}.


MACH: Fast Randomized Tensor Decompositions

Abstract: Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer vision, psychometrics and neuroimaging analysis. Tensor decompositions such as the Tucker decomposition are used to analyze multi-aspect data and extract latent factors, which capture the multilinear data structure. Such decompositions are powerful mining tools, for extracting patterns from large data volumes. However, most frequently used algorithms for such decompositions involve the computationally expensive Singular Value Decomposition. In this paper we propose MACH, a new sampling algorithm to compute such decompositions. Our method is of significant practical value for tensor streams, such as environmental monitoring systems, IP traffic matrices over time, where large amounts of data are accumulated and the analysis is computationally intensive but also in "post-mortem" data analysis cases where the tensor does not fit in the available memory. We provide the theoretical analysis of our proposed method, and verify its efficacy in monitoring system applications.


Eignets for function approximation on manifolds

Abstract: Let $\XX$ be a compact, smooth, connected, Riemannian manifold without boundary, $G:\XX\times\XX\to \RR$ be a kernel. Analogous to a radial basis function network, an eignet is an expression of the form $\sum_{j=1}^M a_jG(\circ,y_j)$, where $a_j\in\RR$, $y_j\in\XX$, $1\le j\le M$. We describe a deterministic, universal algorithm for constructing an eignet for approximating functions in $L^p(\mu;\XX)$ for a general class of measures $\mu$ and kernels $G$. Our algorithm yields linear operators. Using the minimal separation amongst the centers $y_j$ as the cost of approximation, we give modulus of smoothness estimates for the degree of approximation by our eignets, and show by means of a converse theorem that these are the best possible for every \emph{individual function}. We also give estimates on the coefficients $a_j$ in terms of the norm of the eignet. Finally, we demonstrate that if any sequence of eignets satisfies the optimal estimates for the degree of approximation of a smooth function, measured in terms of the minimal separation, then the derivatives of the eignets also approximate the corresponding derivatives of the target function in an optimal manner.


Average sensitivity and noise sensitivity of polynomial threshold functions

Abstract: We give the first non-trivial upper bounds on the average sensitivity and noise sensitivity of degree-$d$ polynomial threshold functions (PTFs). These bounds hold both for PTFs over the Boolean hypercube and for PTFs over $\R^n$ under the standard $n$-dimensional Gaussian distribution. Our bound on the Boolean average sensitivity of PTFs represents progress towards the resolution of a conjecture of Gotsman and Linial \cite{GL:94}, which states that the symmetric function slicing the middle $d$ layers of the Boolean hypercube has the highest average sensitivity of all degree-$d$ PTFs. Via the $L_1$ polynomial regression algorithm of Kalai et al. \cite{KKMS:08}, our bounds on Gaussian and Boolean noise sensitivity yield polynomial-time agnostic learning algorithms for the broad class of constant-degree PTFs under these input distributions. The main ingredients used to obtain our bounds on both average and noise sensitivity of PTFs in the Gaussian setting are tail bounds and anti-concentration bounds on low-degree polynomials in Gaussian random variables \cite{Janson:97,CW:01}. To obtain our bound on the Boolean average sensitivity of PTFs, we generalize the ``critical-index'' machinery of \cite{Servedio:07cc} (which in that work applies to halfspaces, i.e. degree-1 PTFs) to general PTFs. Together with the "invariance principle" of \cite{MOO:05}, this lets us extend our techniques from the Gaussian setting to the Boolean setting. Our bound on Boolean noise sensitivity is achieved via a simple reduction from upper bounds on average sensitivity of Boolean PTFs to corresponding bounds on noise sensitivity.


IRPF90: a programming environment for high performance computing

Abstract: IRPF90 is a Fortran programming environment which helps the development of large Fortran codes. In Fortran programs, the programmer has to focus on the order of the instructions: before using a variable, the programmer has to be sure that it has already been computed in all possible situations. For large codes, it is common source of error. In IRPF90 most of the order of instructions is handled by the pre-processor, and an automatic mechanism guarantees that every entity is built before being used. This mechanism relies on the {needs/needed by} relations between the entities, which are built automatically. Codes written with IRPF90 execute often faster than Fortran programs, are faster to write and easier to maintain.


Complexity of Strong Implementability

Abstract: We consider the question of implementability of a social choice function in a classical setting where the preferences of finitely many selfish individuals with private information have to be aggregated towards a social choice. This is one of the central questions in mechanism design. If the concept of weak implementation is considered, the Revelation Principle states that one can restrict attention to truthful implementations and direct revelation mechanisms, which implies that implementability of a social choice function is easy to check. For the concept of strong implementation, however, the Revelation Principle becomes invalid, and the complexity of deciding whether a given social choice function is strongly implementable has been open so far. In this paper, we show by using methods from polyhedral theory that strong implementability of a social choice function can be decided in polynomial space and that each of the payments needed for strong implementation can always be chosen to be of polynomial encoding length. Moreover, we show that strong implementability of a social choice function involving only a single selfish individual can be decided in polynomial time via linear programming.


Cartesian product of hypergraphs: properties and algorithms

Abstract: Cartesian products of graphs have been studied extensively since the 1960s. They make it possible to decrease the algorithmic complexity of problems by using the factorization of the product. Hypergraphs were introduced as a generalization of graphs and the definition of Cartesian products extends naturally to them. In this paper, we give new properties and algorithms concerning coloring aspects of Cartesian products of hypergraphs. We also extend a classical prime factorization algorithm initially designed for graphs to connected conformal hypergraphs using 2-sections of hypergraphs.


Regular Matroids with Graphic Cocircuits

Abstract: We introduce the notion of graphic cocircuits and show that a large class of regular matroids with graphic cocircuits belongs to the class of signed-graphic matroids. Moreover, we provide an algorithm which determines whether a cographic matroid with graphic cocircuits is signed-graphic or not.


An Exponential Lower Bound on OBDD Refutations for Pigeonhole Formulas

Abstract: Haken proved that every resolution refutation of the pigeonhole formula has at least exponential size. Groote and Zantema proved that a particular OBDD computation of the pigeonhole formula has an exponential size. Here we show that any arbitrary OBDD refutation of the pigeonhole formula has an exponential size, too: we prove that the size of one of the intermediate OBDDs is at least $\Omega(1.025^n)$.


Deriving SN from PSN: a general proof technique

Abstract: In the framework of explicit substitutions there is two termination properties: preservation of strong normalization (PSN), and strong normalization (SN). Since there are not easily proved, only one of them is usually established (and sometimes none). We propose here a connection between them which helps to get SN when one already has PSN. For this purpose, we formalize a general proof technique of SN which consists in expanding substitutions into "pure" lambda-terms and to inherit SN of the whole calculus by SN of the "pure" calculus and by PSN. We apply it successfully to a large set of calculi with explicit substitutions, allowing us to establish SN, or, at least, to trace back the failure of SN to that of PSN.


A Conceivable Origin of Machine Consciousness in the IDLE process

Abstract: In this short paper, we would like to call professional community's attention to a daring idea that is surely unhelpful, but is exciting for programmers and anyway conflicts with the trend of energy consumption in computer systems.


Towards maintainer script modernization in FOSS distributions

Abstract: Free and Open Source Software (FOSS) distributions are complex software systems, made of thousands packages that evolve rapidly, independently, and without centralized coordination. During packages upgrades, corner case failures can be encountered and are hard to deal with, especially when they are due to misbehaving maintainer scripts: executable code snippets used to finalize package configuration. In this paper we report a software modernization experience, the process of representing existing legacy systems in terms of models, applied to FOSS distributions. We present a process to define meta-models that enable dealing with upgrade failures and help rolling back from them, taking into account maintainer scripts. The process has been applied to widely used FOSS distributions and we report about such experiences.


Expressing advanced user preferences in component installation

Abstract: State of the art component-based software collections - such as FOSS distributions - are made of up to dozens of thousands components, with complex inter-dependencies and conflicts. Given a particular installation of such a system, each request to alter the set of installed components has potentially (too) many satisfying answers. We present an architecture that allows to express advanced user preferences about package selection in FOSS distributions. The architecture is composed by a distribution-independent format for describing available and installed packages called CUDF (Common Upgradeability Description Format), and a foundational language called MooML to specify optimization criteria. We present the syntax and semantics of CUDF and MooML, and discuss the partial evaluation mechanism of MooML which allows to gain efficiency in package dependency solvers.


On the Scope of the Universal-Algebraic Approach to Constraint Satisfaction

Abstract: The universal-algebraic approach has proved a powerful tool in the study of the complexity of CSPs. This approach has previously been applied to the study of CSPs with finite or (infinite) omega-categorical templates, and relies on two facts. The first is that in finite or omega-categorical structures A, a relation is primitive positive definable if and only if it is preserved by the polymorphisms of A. The second is that every finite or omega-categorical structure is homomorphically equivalent to a core structure. In this paper, we present generalizations of these facts to infinite structures that are not necessarily omega-categorical. (This abstract has been severely curtailed by the space constraints of arXiv -- please read the full abstract in the article.) Finally, we present applications of our general results to the description and analysis of the complexity of CSPs. In particular, we give general hardness criteria based on the absence of polymorphisms that depend on more than one argument, and we present a polymorphism-based description of those CSPs that are first-order definable (and therefore can be solved in polynomial time).


Breaking Generator Symmetry

Abstract: Dealing with large numbers of symmetries is often problematic. One solution is to focus on just symmetries that generate the symmetry group. Whilst there are special cases where breaking just the symmetries in a generating set is complete, there are also cases where no irredundant generating set eliminates all symmetry. However, focusing on just generators improves tractability. We prove that it is polynomial in the size of the generating set to eliminate all symmetric solutions, but NP-hard to prune all symmetric values. Our proof considers row and column symmetry, a common type of symmetry in matrix models where breaking just generator symmetries is very effective. We show that propagating a conjunction of lexicographical ordering constraints on the rows and columns of a matrix of decision variables is NP-hard.


Fast Set Intersection and Two Patterns Matching

Abstract: In this paper we present a new problem, the fast set intersection problem, which is to preprocess a collection of sets in order to efficiently report the intersection of any two sets in the collection. In addition we suggest new solutions for the two-dimensional substring indexing problem and the document listing problem for two patterns by reduction to the fast set intersection problem.


An Algorithm for Mining Multidimensional Fuzzy Association Rules

Abstract: Multidimensional association rule mining searches for interesting relationship among the values from different dimensions or attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be partitioned at the fuzzy set level. This paper proposes a new algorithm for generating multidimensional association rules by utilizing fuzzy sets. A database consisting of fuzzy transactions, the Apriory property is employed to prune the useless candidates, itemsets.


Bounding the Sensitivity of Polynomial Threshold Functions

Abstract: We give the first non-trivial upper bounds on the average sensitivity and noise sensitivity of polynomial threshold functions. More specifically, for a Boolean function f on n variables equal to the sign of a real, multivariate polynomial of total degree d we prove 1) The average sensitivity of f is at most O(n^{1-1/(4d+6)}) (we also give a combinatorial proof of the bound O(n^{1-1/2^d}). 2) The noise sensitivity of f with noise rate \delta is at most O(\delta^{1/(4d+6)}). Previously, only bounds for the linear case were known. Along the way we show new structural theorems about random restrictions of polynomial threshold functions obtained via hypercontractivity. These structural results may be of independent interest as they provide a generic template for transforming problems related to polynomial threshold functions defined on the Boolean hypercube to polynomial threshold functions defined in Gaussian space.


Transform-based Distributed Data Gathering

Abstract: A general class of unidirectional transforms is presented that can be computed in a distributed manner along an arbitrary routing tree. Additionally, we provide a set of conditions under which these transforms are invertible. These transforms can be computed as data is routed towards the collection (or sink) node in the tree and exploit data correlation between nodes in the tree. Moreover, when used in wireless sensor networks, these transforms can also leverage data received at nodes via broadcast wireless communications. Various constructions of unidirectional transforms are also provided for use in data gathering in wireless sensor networks. New wavelet transforms are also proposed which provide significant improvements over existing unidirectional transforms.


Deterministic counting of graph colourings using sequences of subgraphs

Abstract: In this paper we propose a deterministic algorithm for approximately counting the $k$-colourings of sparse random graphs $G(n,d/n)$. In particular, our algorithm computes in polynomial time a $(1\pm n^{-\Omega(1)})$approximation of the logarithm of the number of $k$-colourings of $G(n,d/n)$ for $k\geq (2+\epsilon) d$ with high probability over the graph instances. Our algorithm is related to the algorithms of A. Bandyopadhyay et al. in SODA '06, and A. Montanari et al. in SODA '06, i.e. it uses {\em spatial correlation decay} to compute {\em deterministically} marginals of {\em Gibbs distribution}. We develop a scheme whose accuracy depends on {\em non-reconstruction} of the colourings of $G(n,d/n)$, rather than {\em uniqueness} that are required in previous works. This leaves open the possibility for our schema to be sufficiently accurate even for $k<d$. The set up for establishing correlation decay is as follows: Given $G(n,d/n)$, we alter the graph structure in some specific region $\Lambda$ of the graph by deleting edges between vertices of $\Lambda$. Then we show that the effect of this change on the marginals of Gibbs distribution, diminishes as we move away from $\Lambda$. Our approach is novel and suggests a new context for the study of deterministic counting algorithms.


Practical Rate and Route Adaptation with Efficient Link Quality Estimation for IEEE 802.11b/g Multi-Hop Networks

Abstract: Accurate and fast packet delivery rate (PDR) estimation, used in evaluating wireless link quality, is a prerequisite to increase the performance of mobile, multi-hop and multi-rate wireless ad hoc networks. Unfortunately, contemporary PDR estimation methods, i.e. beacon-based packet counting in Estimated Transmission Time and Expected Transmission Count metrics, have unsatisfactory performance. Therefore, in this paper we propose a novel PDR estimation method based on SNR profiles. We classify all possible link quality estimation methods and compare them analytically against our design. Results show that it leads to a more efficient link quality estimation. Further investigations with the prototype implementation of our method in IEEE 802.11b/g testbeds reveal that the accuracy of PDR estimation in mobile scenarios can be improved up to 50% in comparison to generic packet-based PDR. Experiments with the same prototype on link and routing layers for different measurement scenarios show that it leads to a better rate adaptation and route selection in the form of end-to-end throughput increase compared to traditional packet counting methods.


Finding Induced Subgraphs via Minimal Triangulations

Abstract: Potential maximal cliques and minimal separators are combinatorial objects which were introduced and studied in the realm of minimal triangulations problems including Minimum Fill-in and Treewidth. We discover unexpected applications of these notions to the field of moderate exponential algorithms. In particular, we show that given an n-vertex graph G together with its set of potential maximal cliques Pi_G, and an integer t, it is possible in time |Pi_G| * n^(O(t)) to find a maximum induced subgraph of treewidth t in G; and for a given graph F of treewidth t, to decide if G contains an induced subgraph isomorphic to F. Combined with an improved algorithm enumerating all potential maximal cliques in time O(1.734601^n), this yields that both problems are solvable in time 1.734601^n * n^(O(t)).


Wiretapping a hidden network

Abstract: We consider the problem of maximizing the probability of hitting a strategically chosen hidden virtual network by placing a wiretap on a single link of a communication network. This can be seen as a two-player win-lose (zero-sum) game that we call the wiretap game. The value of this game is the greatest probability that the wiretapper can secure for hitting the virtual network. The value is shown to equal the reciprocal of the strength of the underlying graph. We efficiently compute a unique partition of the edges of the graph, called the prime-partition, and find the set of pure strategies of the hider that are best responses against every maxmin strategy of the wiretapper. Using these special pure strategies of the hider, which we call omni-connected-spanning-subgraphs, we define a partial order on the elements of the prime-partition. From the partial order, we obtain a linear number of simple two-variable inequalities that define the maxmin-polytope, and a characterization of its extreme points. Our definition of the partial order allows us to find all equilibrium strategies of the wiretapper that minimize the number of pure best responses of the hider. Among these strategies, we efficiently compute the unique strategy that maximizes the least punishment that the hider incurs for playing a pure strategy that is not a best response. Finally, we show that this unique strategy is the nucleolus of the recently studied simple cooperative spanning connectivity game.


The Remote Point Problem, Small Bias Space, and Expanding Generator Sets

Abstract: Using $\epsilon$-bias spaces over $F_2$, we show that the Remote Point Problem (RPP), introduced by Alon et al [APY09], has an $NC^2$ algorithm (achieving the same parameters as [APY09]). We study a generalization of the Remote Point Problem to groups: we replace $F^n$ by $G^n$ for an arbitrary fixed group $G$. When $G$ is Abelian, we give an $NC^2$ algorithm for RPP, again using $\epsilon$-bias spaces. For nonabelian $G$, we give a deterministic polynomial-time algorithm for RPP. We also show the connection to construction of expanding generator sets for the group $G^n$. All our algorithms for the RPP achieve essentially the same parameters as [APY09].


Quasi-Proportional Mechanisms: Prior-free Revenue Maximization

Abstract: Inspired by Internet ad auction applications, we study the problem of allocating a single item via an auction when bidders place very different values on the item. We formulate this as the problem of prior-free auction and focus on designing a simple mechanism that always allocates the item. Rather than designing sophisticated pricing methods like prior literature, we design better allocation methods. In particular, we propose quasi-proportional allocation methods in which the probability that an item is allocated to a bidder depends (quasi-proportionally) on the bids. We prove that corresponding games for both all-pay and winners-pay quasi-proportional mechanisms admit pure Nash equilibria and this equilibrium is unique. We also give an algorithm to compute this equilibrium in polynomial time. Further, we show that the revenue of the auctioneer is promisingly high compared to the ultimate, i.e., the highest value of any of the bidders, and show bounds on the revenue of equilibria both analytically, as well as using experiments for specific quasi-proportional functions. This is the first known revenue analysis for these natural mechanisms (including the special case of proportional mechanism which is common in network resource allocation problems).


A Universal Crease Pattern for Folding Orthogonal Shapes

Abstract: We present a universal crease pattern--known in geometry as the tetrakis tiling and in origami as box pleating--that can fold into any object made up of unit cubes joined face-to-face (polycubes). More precisely, there is one universal finite crease pattern for each number n of unit cubes that need to be folded. This result contrasts previous universality results for origami, which require a different crease pattern for each target object, and confirms intuition in the origami community that box pleating is a powerful design technique.


Formal Verification of Full-Wave Rectifier: A Case Study

Abstract: We present a case study of formal verification of full-wave rectifier for analog and mixed signal designs. We have used the Checkmate tool from CMU [1], which is a public domain formal verification tool for hybrid systems. Due to the restriction imposed by Checkmate it necessitates to make the changes in the Checkmate implementation to implement the complex and non-linear system. Full-wave rectifier has been implemented by using the Checkmate custom blocks and the Simulink blocks from MATLAB from Math works. After establishing the required changes in the Checkmate implementation we are able to efficiently verify the safety properties of the full-wave rectifier.


PetRBF--A parallel O(N) algorithm for radial basis function interpolation

Abstract: We have developed a parallel algorithm for radial basis function (RBF) interpolation that exhibits O(N) complexity,requires O(N) storage, and scales excellently up to a thousand processes. The algorithm uses a GMRES iterative solver with a restricted additive Schwarz method (RASM) as a preconditioner and a fast matrix-vector algorithm. Previous fast RBF methods, --,achieving at most O(NlogN) complexity,--, were developed using multiquadric and polyharmonic basis functions. In contrast, the present method uses Gaussians with a small variance (a common choice in particle methods for fluid simulation, our main target application). The fast decay of the Gaussian basis function allows rapid convergence of the iterative solver even when the subdomains in the RASM are very small. The present method was implemented in parallel using the PETSc library (developer version). Numerical experiments demonstrate its capability in problems of RBF interpolation with more than 50 million data points, timing at 106 seconds (19 iterations for an error tolerance of 10^-15 on 1024 processors of a Blue Gene/L (700 MHz PowerPC processors). The parallel code is freely available in the open-source model.


Through-Wall Tracking Using Variance-Based Radio Tomography Networks

Abstract: This paper presents a new method for imaging, localizing, and tracking motion behind walls in real-time. The method takes advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network. Using a multipath channel model, we show that the signal strength on a wireless link is largely dependent on the power contained in multipath components that travel through space containing moving objects. A statistical model relating variance to spatial locations of movement is presented and used as a framework for the estimation of a motion image. From the motion image, the Kalman filter is applied to recursively track the coordinates of a moving target. Experimental results for a 34-node through-wall imaging and tracking system over a 780 square foot area are presented.


Information tracking approach to segmentation of ultrasound imagery of prostate

Abstract: The size and geometry of the prostate are known to be pivotal quantities used by clinicians to assess the condition of the gland during prostate cancer screening. As an alternative to palpation, an increasing number of methods for estimation of the above-mentioned quantities are based on using imagery data of prostate. The necessity to process large volumes of such data creates a need for automatic segmentation tools which would allow the estimation to be carried out with maximum accuracy and efficiency. In particular, the use of transrectal ultrasound (TRUS) imaging in prostate cancer screening seems to be becoming a standard clinical practice due to the high benefit-to-cost ratio of this imaging modality. Unfortunately, the segmentation of TRUS images is still hampered by relatively low contrast and reduced SNR of the images, thereby requiring the segmentation algorithms to incorporate prior knowledge about the geometry of the gland. In this paper, a novel approach to the problem of segmenting the TRUS images is described. The proposed approach is based on the concept of distribution tracking, which provides a unified framework for modeling and fusing image-related and morphological features of the prostate. Moreover, the same framework allows the segmentation to be regularized via using a new type of "weak" shape priors, which minimally bias the estimation procedure, while rendering the latter stable and robust.


Iterative Shrinkage Approach to Restoration of Optical Imagery

Abstract: The problem of reconstruction of digital images from their degraded measurements is regarded as a problem of central importance in various fields of engineering and imaging sciences. In such cases, the degradation is typically caused by the resolution limitations of an imaging device in use and/or by the destructive influence of measurement noise. Specifically, when the noise obeys a Poisson probability law, standard approaches to the problem of image reconstruction are based on using fixed-point algorithms which follow the methodology first proposed by Richardson and Lucy. The practice of using these methods, however, shows that their convergence properties tend to deteriorate at relatively high noise levels. Accordingly, in the present paper, a novel method for de-noising and/or de-blurring of digital images corrupted by Poisson noise is introduced. The proposed method is derived under the assumption that the image of interest can be sparsely represented in the domain of a linear transform. Consequently, a shrinkage-based iterative procedure is proposed, which guarantees the solution to converge to the global maximizer of an associated maximum-a-posteriori criterion. It is shown in a series of both computer-simulated and real-life experiments that the proposed method outperforms a number of existing alternatives in terms of stability, precision, and computational efficiency.


Proceedings Fourth Athens Colloquium on Algorithms and Complexity

Abstract: ACAC 2009 is organized by the Athens University of Economics and Business (AUEB) and it is the fourth in a series of meetings that aim to bring together researchers working on all areas of the theory of algorithms and computational complexity. These meetings are expected to serve as a lively forum for presenting results that are in a preliminary stage or have been recently presented in some major conference. For the first time this year all submitted papers were reviewed and ACAC also offered to the authors the choice of publishing their contribution (provided it has not been published anywhere else before) with the post-proceedings of EPTCS (Electronic Proceedings in Theoretical Computer Science).


Clique and Vertex Cover are solvable in polynomial time if the input structure is ordered and contains a successor predicate

Abstract: In this manuscript, assuming that Graedel's 1991 results are correct (which implies that bounds on the solution values for optimization problems can be expressed in existential second order logic where the first order part is universal Horn), I will show that Clique and Vertex Cover can be solved in polynomial time if the input structure is ordered and contains a successor predicate. In the last section, we will argue about the validity of Graedel's 1991 results. Update: Manuscript withdrawn, because results are incorrect. If phi = phi_1 AND phi_2, and phi is a Horn formula, it does NOT mean that both phi_1 and phi_2 are Horn formulae. Furthermore, the cardinality constraint CANNOT be expressed as a universal Horn sentence in ESO (NOT even when the structure is ordered).


Differential Privacy via Wavelet Transforms

Abstract: Privacy preserving data publishing has attracted considerable research interest in recent years. Among the existing solutions, {\em $\epsilon$-differential privacy} provides one of the strongest privacy guarantees. Existing data publishing methods that achieve $\epsilon$-differential privacy, however, offer little data utility. In particular, if the output dataset is used to answer count queries, the noise in the query answers can be proportional to the number of tuples in the data, which renders the results useless. In this paper, we develop a data publishing technique that ensures $\epsilon$-differential privacy while providing accurate answers for {\em range-count queries}, i.e., count queries where the predicate on each attribute is a range. The core of our solution is a framework that applies {\em wavelet transforms} on the data before adding noise to it. We present instantiations of the proposed framework for both ordinal and nominal data, and we provide a theoretical analysis on their privacy and utility guarantees. In an extensive experimental study on both real and synthetic data, we show the effectiveness and efficiency of our solution.


Prostate Biopsy Assistance System with Gland Deformation Estimation for Enhanced Precision

Abstract: Computer-assisted prostate biopsies became a very active research area during the last years. Prostate tracking makes it possi- ble to overcome several drawbacks of the current standard transrectal ultrasound (TRUS) biopsy procedure, namely the insufficient targeting accuracy which may lead to a biopsy distribution of poor quality, the very approximate knowledge about the actual location of the sampled tissues which makes it difficult to implement focal therapy strategies based on biopsy results, and finally the difficulty to precisely reach non-ultrasound (US) targets stemming from different modalities, statistical atlases or previous biopsy series. The prostate tracking systems presented so far are limited to rigid transformation tracking. However, the gland can get considerably deformed during the intervention because of US probe pres- sure and patient movements. We propose to use 3D US combined with image-based elastic registration to estimate these deformations. A fast elastic registration algorithm that copes with the frequently occurring US shadows is presented. A patient cohort study was performed, which yielded a statistically significant in-vivo accuracy of 0.83+-0.54mm.


GPU sample sort

Abstract: In this paper, we present the design of a sample sort algorithm for manycore GPUs. Despite being one of the most efficient comparison-based sorting algorithms for distributed memory architectures its performance on GPUs was previously unknown. For uniformly distributed keys our sample sort is at least 25% and on average 68% faster than the best comparison-based sorting algorithm, GPU Thrust merge sort, and on average more than 2 times faster than GPU quicksort. Moreover, for 64-bit integer keys it is at least 63% and on average 2 times faster than the highly optimized GPU Thrust radix sort that directly manipulates the binary representation of keys. Our implementation is robust to different distributions and entropy levels of keys and scales almost linearly with the input size. These results indicate that multi-way techniques in general and sample sort in particular achieve substantially better performance than two-way merge sort and quicksort.


Linear Complementarity Algorithms for Infinite Games

Abstract: The performance of two pivoting algorithms, due to Lemke and Cottle and Dantzig, is studied on linear complementarity problems (LCPs) that arise from infinite games, such as parity, average-reward, and discounted games. The algorithms have not been previously studied in the context of infinite games, and they offer alternatives to the classical strategy-improvement algorithms. The two algorithms are described purely in terms of discounted games, thus bypassing the reduction from the games to LCPs, and hence facilitating a better understanding of the algorithms when applied to games. A family of parity games is given, on which both algorithms run in exponential time, indicating that in the worst case they perform no better for parity, average-reward, or discounted games than they do for general P-matrix LCPs.


Approximating Loops in a Shortest Homology Basis from Point Data

Abstract: Inference of topological and geometric attributes of a hidden manifold from its point data is a fundamental problem arising in many scientific studies and engineering applications. In this paper we present an algorithm to compute a set of loops from a point data that presumably sample a smooth manifold $M\subset \mathbb{R}^d$. These loops approximate a {\em shortest} basis of the one dimensional homology group $H_1(M)$ over coefficients in finite field $\mathbb{Z}_2$. Previous results addressed the issue of computing the rank of the homology groups from point data, but there is no result on approximating the shortest basis of a manifold from its point sample. In arriving our result, we also present a polynomial time algorithm for computing a shortest basis of $H_1(K)$ for any finite {\em simplicial complex} $K$ whose edges have non-negative weights.


Improvements of the 3D images captured with Time-of-Flight cameras

Abstract: 3D Time-of-Flight camera's images are affected by errors due to the diffuse (indirect) light and to the flare light. The presented method improves the 3D image reducing the distance's errors to dark surface objects. This is achieved by placing one or two contrast tags in the scene at different distances from the ToF camera. The white and black parts of the tags are situated at the same distance to the camera but the distances measured by the camera are different. This difference is used to compute a correction vector. The distance to black surfaces is corrected by subtracting this vector from the captured vector image.


Beyond Equilibria: Mechanisms for Repeated Combinatorial Auctions

Abstract: We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. We consider models of agent behaviour in which they either apply common learning techniques to minimize the regret of their bidding strategies, or apply short-sighted best-response strategies. We ask: when can a black-box approximation algorithm for the base auction problem be converted into a mechanism that approximately preserves the original algorithm's approximation factor on average over many iterations? We present a general reduction for a broad class of algorithms when agents minimize external regret. We also present a new mechanism for the combinatorial auction problem that attains an $O(\sqrt{m})$ approximation on average when agents apply best-response dynamics.


Partition Arguments in Multiparty Communication Complexity

Abstract: Consider the "Number in Hand" multiparty communication complexity model, where k players holding inputs x_1,...,x_k in {0,1}^n communicate to compute the value f(x_1,...,x_k) of a function f known to all of them. The main lower bound technique for the communication complexity of such problems is that of partition arguments: partition the k players into two disjoint sets of players and find a lower bound for the induced two-party communication complexity problem. In this paper, we study the power of partition arguments. Our two main results are very different in nature: (i) For randomized communication complexity, we show that partition arguments may yield bounds that are exponentially far from the true communication complexity. Specifically, we prove that there exists a 3-argument function f whose communication complexity is Omega(n), while partition arguments can only yield an Omega(log n) lower bound. The same holds for nondeterministic communication complexity. (ii) For deterministic communication complexity, we prove that finding significant gaps between the true communication complexity and the best lower bound that can be obtained via partition arguments, would imply progress on a generalized version of the "log-rank conjecture" in communication complexity. We conclude with two results on the multiparty "fooling set technique", another method for obtaining communication complexity lower bounds.


Algorithms for finding dispensable variables

Abstract: This short note reviews briefly three algorithms for finding the set of dispensable variables of a boolean formula. The presentation is light on proofs and heavy on intuitions.


Improved Hardness of Approximation for Stackelberg Shortest-Path Pricing

Abstract: We consider the Stackelberg shortest-path pricing problem, which is defined as follows. Given a graph G with fixed-cost and pricable edges and two distinct vertices s and t, we may assign prices to the pricable edges. Based on the predefined fixed costs and our prices, a customer purchases a cheapest s-t-path in G and we receive payment equal to the sum of prices of pricable edges belonging to the path. Our goal is to find prices maximizing the payment received from the customer. While Stackelberg shortest-path pricing was known to be APX-hard before, we provide the first explicit approximation threshold and prove hardness of approximation within 2-o(1).


Finding Associations and Computing Similarity via Biased Pair Sampling

Abstract: This version is ***superseded*** by a full version that can be found at http://www.itu.dk/people/pagh/papers/mining-jour.pdf, which contains stronger theoretical results and fixes a mistake in the reporting of experiments. Abstract: Sampling-based methods have previously been proposed for the problem of finding interesting associations in data, even for low-support items. While these methods do not guarantee precise results, they can be vastly more efficient than approaches that rely on exact counting. However, for many similarity measures no such methods have been known. In this paper we show how a wide variety of measures can be supported by a simple biased sampling method. The method also extends to find high-confidence association rules. We demonstrate theoretically that our method is superior to exact methods when the threshold for "interesting similarity/confidence" is above the average pairwise similarity/confidence, and the average support is not too low. Our method is particularly good when transactions contain many items. We confirm in experiments on standard association mining benchmarks that this gives a significant speedup on real data sets (sometimes much larger than the theoretical guarantees). Reductions in computation time of over an order of magnitude, and significant savings in space, are observed.


Criticisms of modelling packet traffic using long-range dependence

Abstract: This paper criticises the notion that long-range dependence is an important contributor to the queuing behaviour of real Internet traffic. The idea is questioned in two different ways. Firstly, a class of models used to simulate Internet traffic is shown to have important theoretical flaws. It is shown that this behaviour is inconsistent with the behaviour of real traffic traces. Secondly, the notion that long-range correlations significantly affects the queuing performance of traffic is investigated by destroying those correlations in real traffic traces (by reordering). It is shown that the longer ranges of correlations are not important except in one case with an extremely high load.


Analysis, Design and Simulation of a New System for Internet Multimedia Transmission Guarantee

Abstract: QoS is a very important issue for multimedia communication systems. In this paper, a new system that reinstalls the relation between the QoS elements (RSVP, routing protocol, sender, and receiver) during the multimedia transmission is proposed, then an alternative path is created in case of original multimedia path failure. The suggested system considers the resulting problems that may be faced within and after the creation of rerouting path. Finally, the proposed system is simulated using OPNET 11.5 simulation package. Simulation results show that our proposed system outperforms the old one in terms of QoS parameters like packet loss and delay jitter.


Web-enabling Cache Daemon for Complex Data

Abstract: One of the most common basic techniques for improving the performance of web applications is caching frequently accessed data in fast data stores, colloquially known as cache daemons. In this paper we present a cache daemon suitable for storing complex data while maintaining fine-grained control over data storage, retrieval and expiry. Data manipulation in this cache daemon is performed via standard SQL statements so we call it SQLcached. It is a practical, usable solution already implemented in several large web sites.


Hierarchical Approach for Key Management in Mobile Ad hoc Networks

Abstract: Mobile Ad-hoc Network (MANET) is a collection of autonomous nodes or terminals which communicate with each other by forming a multi-hop radio network and maintaining connectivity in a decentralized manner. The conventional security solutions to provide key management through accessing trusted authorities or centralized servers are infeasible for this new environment since mobile ad hoc networks are characterized by the absence of any infrastructure, frequent mobility, and wireless links. We propose a hierarchical group key management scheme that is hierarchical and fully distributed with no central authority and uses a simple rekeying procedure which is suitable for large and high mobility mobile ad hoc networks. The rekeying procedure requires only one round in our scheme and Chinese Remainder Theorem Diffie Hellman Group Diffie Hellmann and Burmester and Desmedt it is a constant 3 whereas in other schemes such as Distributed Logical Key Hierarchy and Distributed One Way Function Trees, it depends on the number of members. We reduce the energy consumption during communication of the keying materials by reducing the number of bits in the rekeying message. We show through analysis and simulations that our scheme has less computation, communication and energy consumption compared to the existing schemes.


Hypergraphic LP Relaxations for Steiner Trees

Abstract: We investigate hypergraphic LP relaxations for the Steiner tree problem, primarily the partition LP relaxation introduced by Koenemann et al. [Math. Programming, 2009]. Specifically, we are interested in proving upper bounds on the integrality gap of this LP, and studying its relation to other linear relaxations. Our results are the following. Structural results: We extend the technique of uncrossing, usually applied to families of sets, to families of partitions. As a consequence we show that any basic feasible solution to the partition LP formulation has sparse support. Although the number of variables could be exponential, the number of positive variables is at most the number of terminals. Relations with other relaxations: We show the equivalence of the partition LP relaxation with other known hypergraphic relaxations. We also show that these hypergraphic relaxations are equivalent to the well studied bidirected cut relaxation, if the instance is quasibipartite. Integrality gap upper bounds: We show an upper bound of sqrt(3) ~ 1.729 on the integrality gap of these hypergraph relaxations in general graphs. In the special case of uniformly quasibipartite instances, we show an improved upper bound of 73/60 ~ 1.216. By our equivalence theorem, the latter result implies an improved upper bound for the bidirected cut relaxation as well.


On Finding Ordinary or Monochromatic Intersection Points

Abstract: An algorithm is demonstrated that finds an ordinary intersection in an arrangement of $n$ lines in $\mathbb{R}^2$, not all parallel and not all passing through a common point, in time $O(n \log{n})$. The algorithm is then extended to find an ordinary intersection among an arrangement of hyperplanes in $\mathbb{R}^d$, no $d$ passing through a line and not all passing through the same point, again, in time $O(n \log{n})$. Two additional algorithms are provided that find an ordinary or monochromatic intersection, respectively, in an arrangement of pseudolines in time $O(n^2)$.


An Analysis of Energy Consumption on ACK plus Rate Packet in Rate Based Transport Protocol

Abstract: Rate based transport protocol determines the rate of data transmission between the sender and receiver and then sends the data according to that rate. To notify the rate to the sender, the receiver sends ACKplusRate packet based on epoch timer expiry. In this paper, through detailed arguments and simulation it is shown that the transmission of ACKplusRate packet based on epoch timer expiry consumes more energy in network with low mobility. To overcome this problem, a new technique called Dynamic Rate Feedback (DRF) is proposed. DRF sends ACKplusRate whenever there is a change in rate of (plus or minus) 25 percent than the previous rate. Based on ns2 simulation DRF is compared with a reliable transport protocol for ad hoc network (ATP)


A New Fuzzy Approach for Dynamic Load Balancing Algorithm

Abstract: Load balancing is the process of improving the Performance of a parallel and distributed system through is distribution of load among the processors [1-2]. Most of the previous work in load balancing and distributed decision making in general, do not effectively take into account the uncertainty and inconsistency in state information but in fuzzy logic, we have advantage of using crisps inputs. In this paper, we present a new approach for implementing dynamic load balancing algorithm with fuzzy logic, which can face to uncertainty and inconsistency of previous algorithms, further more our algorithm shows better response time than round robin and randomize algorithm respectively 30.84 percent and 45.45 percent.


Post-Processing of Discovered Association Rules Using Ontologies

Abstract: In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. In this paper we propose a new approach to prune and filter discovered rules. Using Domain Ontologies, we strengthen the integration of user knowledge in the post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task. On the one hand, we represent user domain knowledge using a Domain Ontology over database. On the other hand, a novel technique is suggested to prune and to filter discovered rules. The proposed framework was applied successfully over the client database provided by Nantes Habitat.


Supporting Lock-Free Composition of Concurrent Data Objects

Abstract: Lock-free data objects offer several advantages over their blocking counterparts, such as being immune to deadlocks and convoying and, more importantly, being highly concurrent. But they share a common disadvantage in that the operations they provide are difficult to compose into larger atomic operations while still guaranteeing lock-freedom. We present a lock-free methodology for composing highly concurrent linearizable objects together by unifying their linearization points. This makes it possible to relatively easily introduce atomic lock-free move operations to a wide range of concurrent objects. Experimental evaluation has shown that the operations originally supported by the data objects keep their performance behavior under our methodology.


The averaging trick and the Cerny conjecture

Abstract: The results of several papers concerning the \v{C}ern\'y conjecture are deduced as consequences of a simple idea that I call the averaging trick. This idea is implicitly used in the literature, but no attempt was made to formalize the proof scheme axiomatically. Instead, authors axiomatized classes of automata to which it applies.


Stackelberg Pricing is Hard to Approximate within $2-\epsilon$

Abstract: Stackelberg Pricing Games is a two-level combinatorial pricing problem studied in the Economics, Operation Research, and Computer Science communities. In this paper, we consider the decade-old shortest path version of this problem which is the first and most studied problem in this family. The game is played on a graph (representing a network) consisting of {\em fixed cost} edges and {\em pricable} or {\em variable cost} edges. The fixed cost edges already have some fixed price (representing the competitor's prices). Our task is to choose prices for the variable cost edges. After that, a client will buy the cheapest path from a node $s$ to a node $t$, using any combination of fixed cost and variable cost edges. The goal is to maximize the revenue on variable cost edges. In this paper, we show that the problem is hard to approximate within $2-\epsilon$, improving the previous \APX-hardness result by Joret [to appear in {\em Networks}]. Our technique combines the existing ideas with a new insight into the price structure and its relation to the hardness of the instances.


Exact Covers via Determinants

Abstract: Given a k-uniform hypergraph on n vertices, partitioned in k equal parts such that every hyperedge includes one vertex from each part, the k-dimensional matching problem asks whether there is a disjoint collection of the hyperedges which covers all vertices. We show it can be solved by a randomized polynomial space algorithm in time O*(2^(n(k-2)/k)). The O*() notation hides factors polynomial in n and k. When we drop the partition constraint and permit arbitrary hyperedges of cardinality k, we obtain the exact cover by k-sets problem. We show it can be solved by a randomized polynomial space algorithm in time O*(c_k^n), where c_3=1.496, c_4=1.642, c_5=1.721, and provide a general bound for larger k. Both results substantially improve on the previous best algorithms for these problems, especially for small k, and follow from the new observation that Lovasz' perfect matching detection via determinants (1979) admits an embedding in the recently proposed inclusion-exclusion counting scheme for set covers, despite its inability to count the perfect matchings.


From Requirements to code: an Architecture-centric Approach for producing Quality Systems

Abstract: When engineering complex and distributed software and hardware systems (increasingly used in many sectors, such as manufacturing, aerospace, transportation, communication, energy, and health-care), quality has become a big issue, since failures can have economics consequences and can also endanger human life. Model-based specifications of a component-based system permit to explicitly model the structure and behaviour of components and their integration. In particular Software Architectures (SA) has been advocated as an effective means to produce quality systems. In this chapter by combining different technologies and tools for analysis and development, we propose an architecture-centric model-driven approach to validate required properties and to generate the system code. Functional requirements are elicited and used for identifying expected properties the architecture shall express. The architectural compliance to the properties is formally demonstrated, and the produced architectural model is used to automatically generate the Java code. Suitable transformations assure that the code is conforming to both structural and behavioural SA constraints. This chapter describes the process and discusses how some existing tools and languages can be exploited to support the approach.


Improved Analysis of a Max Cut Algorithm Based on Spectral Partitioning

Abstract: Trevisan [SICOMP 2012] presented an algorithm for Max-Cut based on spectral partitioning techniques. This is the first algorithm for Max-Cut with an approximation guarantee strictly larger than 1/2 that is not based on semidefinite programming. Trevisan showed that its approximation ratio is of at least 0.531. In this paper we improve this bound up to 0.614247. We also define and extend this result for the more general Maximum Colored Cut problem.


Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Abstract: Graphics processing units (GPUs) are gaining widespread use in computational chemistry and other scientific simulation contexts because of their huge performance advantages relative to conventional CPUs. However, the reliability of GPUs in error-intolerant applications is largely unproven. In particular, a lack of error checking and correcting (ECC) capability in the memory subsystems of graphics cards has been cited as a hindrance to the acceptance of GPUs as high-performance coprocessors, but the impact of this design has not been previously quantified. In this article we present MemtestG80, our software for assessing memory error rates on NVIDIA G80 and GT200-architecture-based graphics cards. Furthermore, we present the results of a large-scale assessment of GPU error rate, conducted by running MemtestG80 on over 20,000 hosts on the Folding@home distributed computing network. Our control experiments on consumer-grade and dedicated-GPGPU hardware in a controlled environment found no errors. However, our survey over cards on Folding@home finds that, in their installed environments, two-thirds of tested GPUs exhibit a detectable, pattern-sensitive rate of memory soft errors. We demonstrate that these errors persist after controlling for overclocking and environmental proxies for temperature, but depend strongly on board architecture.


Ranking via Arrow-Debreu Equilibrium

Abstract: In this paper, we establish a connection between ranking theory and general equilibrium theory. First of all, we show that the ranking vector of PageRank or Invariant method is precisely the equilibrium of a special Cobb-Douglas market. This gives a natural economic interpretation for the PageRank or Invariant method. Furthermore, we propose a new ranking method, the CES ranking, which is minimally fair, strictly monotone and invariant to reference intensity, but not uniform or weakly additive.


A Note On Higher Order Grammar

Abstract: Both syntax-phonology and syntax-semantics interfaces in Higher Order Grammar (HOG) are expressed as axiomatic theories in higher-order logic (HOL), i.e. a language is defined entirely in terms of provability in the single logical system. An important implication of this elegant architecture is that the meaning of a valid expression turns out to be represented not by a single, nor even by a few "discrete" terms (in case of ambiguity), but by a "continuous" set of logically equivalent terms. The note is devoted to precise formulation and proof of this observation.


Combining Approximation Algorithms for the Prize-Collecting TSP

Abstract: We present a 1.91457-approximation algorithm for the prize-collecting travelling salesman problem. This is obtained by combining a randomized variant of a rounding algorithm of Bienstock et al. and a primal-dual algorithm of Goemans and Williamson.


Algorithmic Meta-Theorems for Graphs of Bounded Vertex Cover

Abstract: Possibly the most famous algorithmic meta-theorem is Courcelle's theorem, which states that all MSO-expressible graph properties are decidable in linear time for graphs of bounded treewidth. Unfortunately, the running time's dependence on the MSO formula describing the problem is in general a tower of exponentials of unbounded height, and there exist lower bounds proving that this cannot be improved even if we restrict ourselves to deciding FO logic on trees. In this paper we attempt to circumvent these lower bounds by focusing on a subclass of bounded treewidth graphs, the graphs of bounded vertex cover. By using a technique different from the standard decomposition and dynamic programming technique of treewidth we prove that in this case the running time implied by Courcelle's theorem can be improved dramatically, from non-elementary to doubly and singly exponential for MSO and FO logic respectively. Our technique relies on a new graph width measure we introduce, for which we show some additional results that may indicate that it is of independent interest. We also prove lower bound results which show that our upper bounds cannot be improved significantly, under widely believed complexity assumptions. Our work answers an open problem posed by Michael Fellows.


Towards a Grid Platform for Scientific Workflows Management

Abstract: Workflow management systems allow the users to develop complex applications at a higher level, by orchestrating functional components without handling the implementation details. Although a wide range of workflow engines are developed in enterprise environments, the open source engines available for scientific applications lack some functionalities or are too difficult to use for non-specialists. Our purpose is to develop a workflow management platform for distributed systems, that will provide features like an intuitive way to describe workflows, efficient data handling mechanisms and flexible fault tolerance support. We introduce here an architectural model for the workflow platform, based on the ActiveBPEL workflow engine, which we propose to augment with an additional set of components.


Digital Business Ecosystems: Natural Science Paradigms

Abstract: A primary motivation for research in Digital Ecosystems is the desire to exploit the self-organising properties of natural ecosystems. Ecosystems arc thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the biological processes that contribute to these properties have not been made explicit in Digital Ecosystem research. Here, we introduce how biological properties contribute to the self-organising features of natural ecosystems. These properties include populations of evolving agents, a complex dynamic environment, and spatial distributions which generate local interactions. The potential for exploiting these properties in artificial systems is then considered.


Transmission line inspires a new distributed algorithm to solve linear system of circuit

Abstract: Transmission line, or wire, is always troublesome to integrated circuits designers, but it could be helpful to parallel computing researchers. This paper proposes the Virtual Transmission Method (VTM), which is a new distributed and stationary iterative algorithm to solve the linear system extracted from circuit. It tears the circuit by virtual transmission lines to achieve distributed computing. For the symmetric positive definite (SPD) linear system, VTM is proved to be convergent. For the unsymmetrical linear system, numerical experiments show that VTM is possible to achieve better convergence property than the traditional stationary algorithms. VTM could be accelerated by some preconditioning techniques, and the convergence speed of VTM is fast when its preconditioner is properly chosen.


Variable sigma Gaussian processes: An expectation propagation perspective

Abstract: Gaussian processes (GPs) provide a probabilistic nonparametric representation of functions in regression, classification, and other problems. Unfortunately, exact learning with GPs is intractable for large datasets. A variety of approximate GP methods have been proposed that essentially map the large dataset into a small set of basis points. The most advanced of these, the variable-sigma GP (VSGP) (Walder et al., 2008), allows each basis point to have its own length scale. However, VSGP was only derived for regression. We describe how VSGP can be applied to classification and other problems, by deriving it as an expectation propagation algorithm. In this view, sparse GP approximations correspond to a KL-projection of the true posterior onto a compact exponential family of GPs. VSGP constitutes one such family, and we show how to enlarge this family to get additional accuracy. In particular, we show that endowing each basis point with its own full covariance matrix provides a significant increase in approximation power.


Computing of Applied Digital Ecosystems

Abstract: A primary motivation for our research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. Here, we discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems, Service-Oriented Architectures, and distributed evolutionary computing. The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, considering the self-organised diversity of its evolving agent populations relative to the user request behaviour.


Self-similarity properties in a queuing network model

Abstract: In this paper a model of subscriber telephone network based on the concept of cellular automata is elaborated. Some fractal properties inherent in the model are revealed that vary depending on parameters assigning its operation rules. The main advantage of the model in question is its compatibility with algorithmic methods - a finite set of formal rules, assigned on a finite set of elements (cells), allows precise realization in the form of algorithms.


Robust Failure Detection Architecture for Large Scale Distributed Systems

Abstract: Failure detection is a fundamental building block for ensuring fault tolerance in large scale distributed systems. There are lots of approaches and implementations in failure detectors. Providing flexible failure detection in off-the-shelf distributed systems is difficult. In this paper we present an innovative solution to this problem. Our approach is based on adaptive, decentralized failure detectors, capable of working asynchronous and independent on the application flow. The proposed solution considers an architecture for the failure detectors, based on clustering, the use of a gossip-based algorithm for detection at local level and the use of a hierarchical structure among clusters of detectors along which traffic is channeled. The solution can scale to a large number of nodes, considers the QoS requirements of both applications and resources, and includes fault tolerance and system orchestration mechanisms, added in order to asses the reliability and availability of distributed systems.


Co-Channel Interference Cancellation in OFDM Networks using Coordinated Symbol Repetition and Soft Decision MLE CCI Canceler

Abstract: In this paper, a new scheme of downlink co-channel interference (CCI) cancellation in OFDM cellular networks is introduced for users at the cell-edge. Coordinated symbol transmission between base stations (BS) is operated where the same symbol is transmitted from different BS on different sub-carriers. At the mobile station (MS) receiver, we introduce a soft decision maximum likelihood CCI canceler and a modified maximum ratio combining (M-MRC) to obtain an estimate of the transmitted symbols. Weights used in the combining method are derived from the channels coefficients between the cooperated BS and the MS. Simulations show that the proposed scheme works well under frequency-selective channels and frequency non-selective channels. A gain of 9 dB and 6 dB in SIR is obtained under multipath fading and flat-fading channels, respectively.


A methodology for semi-automatic classification schema building

Abstract: This paper describe a methodology for semi-automatic classification schema definition (a classification schema is a taxonomy of categories useful for automatic document classification). The methodology is based on: (i) an extensional approach useful to create a typology starting from a document base, and (ii) an intensional approach to build the classification schema starting from the typology. The extensional approach uses clustering techniques to group together documents on the basis of a similarity measure, whereas the intensional approach uses different operations (aggregation, reduction, generalization specialization) to define classes. keywords: ontology, classification schema, fundamentum divisionis, cluster analysis classification task.


A Framework for Specifying, Prototyping, and Reasoning about Computational Systems

Abstract: This thesis concerns the development of a framework that facilitates the design and analysis of formal systems. Specifically, this framework provides a specification language which supports the concise and direct description of formal systems, a mechanism for animating the specification language thereby producing prototypes of encoded systems, and a logic for proving properties of specifications and therefore of the systems they encode. A defining characteristic of the proposed framework is that it is based on two separate but closely intertwined logics: a specification logic that facilitates the description of computational structure and another logic that exploits the special characteristics of the specification logic to support reasoning about the computational behavior of systems that are described using it. Both logics embody a natural treatment of binding structure by using the lambda-calculus as a means for representing objects and by incorporating special mechanisms for working with such structure. By using this technique, they lift the treatment of binding from the object language into the domain of the relevant meta logic, thereby allowing the specification or analysis components to focus on the more essential logical aspects of the systems that are encoded. The primary contributions of these thesis are the development of a rich meta-logic called G with capabilities for sophisticated reasoning that includes induction and co-induction over high-level specifications of computations and with an associated cut-elimination result; an interactive reasoning system called Abella based on G; and several reasoning examples which demonstrate the expressiveness and naturalness of both G and Abella.


Local negative circuits and fixed points in Boolean networks

Abstract: To each Boolean function F from {0,1}^n to itself and each point x in {0,1}^n, we associate the signed directed graph G_F(x) of order n that contains a positive (resp. negative) arc from j to i if the partial derivative of f_i with respect of x_j is positive (resp. negative) at point x. We then focus on the following open problem: Is the absence of a negative circuit in G_F(x) for all x in {0,1}^n a sufficient condition for F to have at least one fixed point? As main result, we settle this problem under the additional condition that, for all x in {0,1}^n, the out-degree of each vertex of G_F(x) is at most one.


The Knapsack Problem with Neighbour Constraints

Abstract: We study a constrained version of the knapsack problem in which dependencies between items are given by the adjacencies of a graph. In the 1-neighbour knapsack problem, an item can be selected only if at least one of its neighbours is also selected. In the all-neighbours knapsack problem, an item can be selected only if all its neighbours are also selected. We give approximation algorithms and hardness results when the nodes have both uniform and arbitrary weight and profit functions, and when the dependency graph is directed and undirected.


A Survey of Biometric keystroke Dynamics: Approaches, Security and Challenges

Abstract: Biometrics technologies are gaining popularity today since they provide more reliable and efficient means of authentication and verification. Keystroke Dynamics is one of the famous biometric technologies, which will try to identify the authenticity of a user when the user is working via a keyboard. The authentication process is done by observing the change in the typing pattern of the user. A comprehensive survey of the existing keystroke dynamics methods, metrics, different approaches are given in this study. This paper also discusses about the various security issues and challenges faced by keystroke dynamics.


Performance Evaluation of Wimax Physical Layer under Adaptive Modulation Techniques and Communication Channels

Abstract: Wimax (Worldwide Interoperability for Microwave Access) is a promising technology which can offer high speed voice, video and data service up to the customer end. The aim of this paper is the performance evaluation of an Wimax system under different combinations of digital modulation (BPSK, QPSK, 4 QAM and 16 QAM) and different communication channels AWGN and fading channels (Rayleigh and Rician). And the Wimax system incorporates Reed Solomon (RS) encoder with Convolutional encoder with half and two third rated codes in FEC channel coding. The simulation results of estimated Bit Error Rate (BER) displays that the implementation of interleaved RS code (255, 239, 8) with two third rated Convolutional code under BPSK modulation technique is highly effective to combat in the Wimax communication system. To complete this performance analysis in Wimax based systems, a segment of audio signal is used for analysis. The transmitted audio message is found to have retrieved effectively under noisy situation.


Optimal deterministic ring exploration with oblivious asynchronous robots

Abstract: We consider the problem of exploring an anonymous unoriented ring of size $n$ by $k$ identical, oblivious, asynchronous mobile robots, that are unable to communicate, yet have the ability to sense their environment and take decisions based on their local view. Previous works in this weak scenario prove that $k$ must not divide $n$ for a deterministic solution to exist. Also, it is known that the minimum number of robots (either deterministic or probabilistic) to explore a ring of size $n$ is 4. An upper bound of 17 robots holds in the deterministic case while 4 probabilistic robots are sufficient. In this paper, we close the complexity gap in the deterministic setting, by proving that no deterministic exploration is feasible with less than five robots whenever the size of the ring is even, and that five robots are sufficient for any $n$ that is coprime with five. Our protocol completes exploration in O(n) robot moves, which is also optimal.


Design of asynchronous supervisors

Abstract: One of the main drawbacks while implementing the interaction between a plant and a supervisor, synthesised by the supervisory control theory of \citeauthor{RW:1987}, is the inexact synchronisation. \citeauthor{balemiphdt} was the first to consider this problem, and the solutions given in his PhD thesis were in the domain of automata theory. Our goal is to address the issue of inexact synchronisation in a process algebra setting, because we get concepts like modularity and abstraction for free, which are useful to further analyze the synthesised system. In this paper, we propose four methods to check a closed loop system in an asynchronous setting such that it is branching bisimilar to the modified (asynchronous) closed loop system. We modify a given closed loop system by introducing buffers either in the plant models, the supervisor models, or the output channels of both supervisor and plant models, or in the input channels of both supervisor and plant models. A notion of desynchronisable closed loop system is introduced, which is a class of synchronous closed loop systems such that they are branching bisimilar to their corresponding asynchronous versions. Finally we study different case studies in an asynchronous setting and then try to summarise the observations (or conditions) which will be helpful in order to formulate a theory of desynchronisable closed loop systems.


Bidding for Representative Allocations for Display Advertising

Abstract: Display advertising has traditionally been sold via guaranteed contracts -- a guaranteed contract is a deal between a publisher and an advertiser to allocate a certain number of impressions over a certain period, for a pre-specified price per impression. However, as spot markets for display ads, such as the RightMedia Exchange, have grown in prominence, the selection of advertisements to show on a given page is increasingly being chosen based on price, using an auction. As the number of participants in the exchange grows, the price of an impressions becomes a signal of its value. This correlation between price and value means that a seller implementing the contract through bidding should offer the contract buyer a range of prices, and not just the cheapest impressions necessary to fulfill its demand. Implementing a contract using a range of prices, is akin to creating a mutual fund of advertising impressions, and requires {\em randomized bidding}. We characterize what allocations can be implemented with randomized bidding, namely those where the desired share obtained at each price is a non-increasing function of price. In addition, we provide a full characterization of when a set of campaigns are compatible and how to implement them with randomized bidding strategies.


Reduced-Rank Hidden Markov Models

Abstract: We introduce the Reduced-Rank Hidden Markov Model (RR-HMM), a generalization of HMMs that can model smooth state evolution as in Linear Dynamical Systems (LDSs) as well as non-log-concave predictive distributions as in continuous-observation HMMs. RR-HMMs assume an m-dimensional latent state and n discrete observations, with a transition matrix of rank k <= m. This implies the dynamics evolve in a k-dimensional subspace, while the shape of the set of predictive distributions is determined by m. Latent state belief is represented with a k-dimensional state vector and inference is carried out entirely in R^k, making RR-HMMs as computationally efficient as k-state HMMs yet more expressive. To learn RR-HMMs, we relax the assumptions of a recently proposed spectral learning algorithm for HMMs (Hsu, Kakade and Zhang 2009) and apply it to learn k-dimensional observable representations of rank-k RR-HMMs. The algorithm is consistent and free of local optima, and we extend its performance guarantees to cover the RR-HMM case. We show how this algorithm can be used in conjunction with a kernel density estimator to efficiently model high-dimensional multivariate continuous data. We also relax the assumption that single observations are sufficient to disambiguate state, and extend the algorithm accordingly. Experiments on synthetic data and a toy video, as well as on a difficult robot vision modeling problem, yield accurate models that compare favorably with standard alternatives in simulation quality and prediction capability.


Social Networks and Stable Matchings in the Job Market

Abstract: For most people, social contacts play an integral part in finding a new job. As observed by Granovetter's seminal study, the proportion of jobs obtained through social contacts is usually large compared to those obtained through postings or agencies. At the same time, job markets are a natural example of two-sided matching markets. An important solution concept in such markets is that of stable matchings, and the use of the celebrated Gale-Shapley algorithm to compute them. So far, the literature has evolved separately, either focusing on the implications of information flowing through a social network, or on developing a mathematical theory of job markets through the use of two-sided matching techniques. In this paper we provide a model of the job market that brings both aspects of job markets together. To model the social scientists' observations, we assume that workers learn only about positions in firms through social contacts. Given that information structure, we study both static properties of what we call locally stable matchings (i.e., stable matchings subject to informational constraints given by a social network) and dynamic properties through a reinterpretation of Gale-Shapley's algorithm as myopic best response dynamics. We prove that, in general, the set of locally stable matching strictly contains that of stable matchings and it is in fact NP-complete to determine if they are identical. We also show that the lattice structure of stable matchings is in general absent. Finally, we focus on myopic best response dynamics inspired by the Gale-Shapley algorithm. We study the efficiency loss due to the informational constraints, providing both lower and upper bounds.


Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison

Abstract: We consider a problem of significant practical importance, namely, the reconstruction of a low-rank data matrix from a small subset of its entries. This problem appears in many areas such as collaborative filtering, computer vision and wireless sensor networks. In this paper, we focus on the matrix completion problem in the case when the observed samples are corrupted by noise. We compare the performance of three state-of-the-art matrix completion algorithms (OptSpace, ADMiRA and FPCA) on a single simulation platform and present numerical results. We show that in practice these efficient algorithms can be used to reconstruct real data matrices, as well as randomly generated matrices, accurately.


On Metric Skyline Processing by PM-tree

Abstract: The task of similarity search in multimedia databases is usually accomplished by range or k nearest neighbor queries. However, the expressing power of these "single-example" queries fails when the user's delicate query intent is not available as a single example. Recently, the well-known skyline operator was reused in metric similarity search as a "multi-example" query type. When applied on a multi-dimensional database (i.e., on a multi-attribute table), the traditional skyline operator selects all database objects that are not dominated by other objects. The metric skyline query adopts the skyline operator such that the multiple attributes are represented by distances (similarities) to multiple query examples. Hence, we can view the metric skyline as a set of representative database objects which are as similar to all the examples as possible and, simultaneously, are semantically distinct. In this paper we propose a technique of processing the metric skyline query by use of PM-tree, while we show that our technique significantly outperforms the original M-tree based implementation in both time and space costs. In experiments we also evaluate the partial metric skyline processing, where only a controlled number of skyline objects is retrieved.


Pessimistic Testing

Abstract: We propose a new approach to testing conformance to a nondeterministic specification, in which testing proceeds only as long as increased test coverage is guaranteed.


Building upon Fast Multipole Methods to Detect and Model Organizations

Abstract: Many models in natural and social sciences are comprised of sets of inter-acting entities whose intensity of interaction decreases with distance. This often leads to structures of interest in these models composed of dense packs of entities. Fast Multipole Methods are a family of methods developed to help with the calculation of a number of computable models such as described above. We propose a method that builds upon FMM to detect and model the dense structures of these systems.


A Formally Specified Type System and Operational Semantics for Higher-Order Procedural Variables

Abstract: We formally specified the type system and operational semantics of LOOPw with Ott and Isabelle/HOL proof assistant. Moreover, both the type system and the semantics of LOOPw have been tested using Isabelle/HOL program extraction facility for inductively defined relations. In particular, the program that computes the Ackermann function type checks and behaves as expected. The main difference (apart from the choice of an Ada-like concrete syntax) with LOOPw comes from the treatment of parameter passing. Indeed, since Ott does not currently fully support alpha-conversion, we rephrased the operational semantics with explicit aliasing in order to implement the out parameter passing mode.