Approximately Counting Embeddings into Random Graphs

Abstract: Let H be a graph, and let C_H(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating C_H(G). Previous results cover only a few specific instances of this general problem, for example, the case when H has degree at most one (monomer-dimer problem). In this paper, we present the first general subcase of the subgraph isomorphism counting problem which is almost always efficiently approximable. The results rely on a new graph decomposition technique. Informally, the decomposition is a labeling of the vertices such that every edge is between vertices with different labels and for every vertex all neighbors with a higher label have identical labels. The labeling implicitly generates a sequence of bipartite graphs which permits us to break the problem of counting embeddings of large subgraphs into that of counting embeddings of small subgraphs. Using this method, we present a simple randomized algorithm for the counting problem. For all decomposable graphs H and all graphs G, the algorithm is an unbiased estimator. Furthermore, for all graphs H having a decomposition where each of the bipartite graphs generated is small and almost all graphs G, the algorithm is a fully polynomial randomized approximation scheme. We show that the graph classes of H for which we obtain a fully polynomial randomized approximation scheme for almost all G includes graphs of degree at most two, bounded-degree forests, bounded-length grid graphs, subdivision of bounded-degree graphs, and major subclasses of outerplanar graphs, series-parallel graphs and planar graphs, whereas unbounded-length grid graphs are excluded.


Triangulation of Simple 3D Shapes with Well-Centered Tetrahedra

Abstract: A completely well-centered tetrahedral mesh is a triangulation of a three dimensional domain in which every tetrahedron and every triangle contains its circumcenter in its interior. Such meshes have applications in scientific computing and other fields. We show how to triangulate simple domains using completely well-centered tetrahedra. The domains we consider here are space, infinite slab, infinite rectangular prism, cube and regular tetrahedron. We also demonstrate single tetrahedra with various combinations of the properties of dihedral acuteness, 2-well-centeredness and 3-well-centeredness.


Development of Hybrid Intelligent Systems and their Applications from Engineering Systems to Complex Systems

Abstract: In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topic of this spacious skeleton. Upon this clue, we organize different algorithms involved a few prominent intelligent computing and approximate reasoning methods such as self organizing feature map (SOM)[9], Neuro- Fuzzy Inference System[10], Rough Set Theory (RST)[11], collaborative clustering, Genetic Algorithm and Ant Colony System. Upon this, we have employed our algorithms on the several engineering systems, especially emerged systems in Civil and Mineral processing. In other process, we investigated how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect mapping among finical systems and eventual market fluctuations with MACIPS. In the following sections, we will mention the main topics of the suggested proposal, briefly Details of the proposed algorithms can be found in the references.


Existence of a polyhedron which does not have a non-overlapping pseudo-edge unfolding

Abstract: There exists a surface of a convex polyhedron P and a partition L of P into geodesic convex polygons such that there are no connected "edge" unfoldings of P without self-intersections (whose spanning tree is a subset of the edge skeleton of L).


Ad-hoc Limited Scale-Free Models for Unstructured Peer-to-Peer Networks

Abstract: Several protocol efficiency metrics (e.g., scalability, search success rate, routing reachability and stability) depend on the capability of preserving structure even over the churn caused by the ad-hoc nodes joining or leaving the network. Preserving the structure becomes more prohibitive due to the distributed and potentially uncooperative nature of such networks, as in the peer-to-peer (P2P) networks. Thus, most practical solutions involve unstructured approaches while attempting to maintain the structure at various levels of protocol stack. The primary focus of this paper is to investigate construction and maintenance of scale-free topologies in a distributed manner without requiring global topology information at the time when nodes join or leave. We consider the uncooperative behavior of peers by limiting the number of neighbors to a pre-defined hard cutoff value (i.e., no peer is a major hub), and the ad-hoc behavior of peers by rewiring the neighbors of nodes leaving the network. We also investigate the effect of these hard cutoffs and rewiring of ad-hoc nodes on the P2P search efficiency.


Logical Reasoning for Higher-Order Functions with Local State

Abstract: We introduce an extension of Hoare logic for call-by-value higher-order functions with ML-like local reference generation. Local references may be generated dynamically and exported outside their scope, may store higher-order functions and may be used to construct complex mutable data structures. This primitive is captured logically using a predicate asserting reachability of a reference name from a possibly higher-order datum and quantifiers over hidden references. We explore the logic's descriptive and reasoning power with non-trivial programming examples combining higher-order procedures and dynamically generated local state. Axioms for reachability and local invariant play a central role for reasoning about the examples.


Proposition of a full deterministic medium access method for wireless network in a robotic application

Abstract: Today, many network applications require shorter react time. Robotic field is an excellent example of these needs: robot react time has a direct effect on its task's complexity. Here, we propose a full deterministic medium access method for a wireless robotic application. This contribution is based on some low-power wireless personal area networks, like ZigBee standard. Indeed, ZigBee has identified limits with Quality of Service due to non-determinist medium access and probable collisions during medium reservation requests. In this paper, two major improvements are proposed: an efficient polling of the star nodes and a temporal deterministic distribution of peer-to-peer messages. This new MAC protocol with no collision offers some QoS faculties.


The computability path ordering: the end of a quest

Abstract: In this paper, we first briefly survey automated termination proof methods for higher-order calculi. We then concentrate on the higher-order recursive path ordering, for which we provide an improved definition, the Computability Path Ordering. This new definition appears indeed to capture the essence of computability arguments \`a la Tait and Girard, therefore explaining the name of the improved ordering.


A Data-Parallel Algorithm to Reliably Solve Systems of Nonlinear Equations

Abstract: Numerical methods based on interval arithmetic are efficient means to reliably solve nonlinear systems of equations. Algorithm bc3revise is an interval method that tightens variables' domains by enforcing a property called box consistency. It has been successfully used on difficult problems whose solving eluded traditional numerical methods. We present a new algorithm to enforce box consistency that is simpler than bc3revise, faster, and easily data parallelizable. A parallel implementation with Intel SSE2 SIMD instructions shows that an increase in performance of up to an order of magnitude and more is achievable.


Prototyping and Performance Analysis of a QoS MAC Layer for Industrial Wireless Network

Abstract: Today's industrial sensor networks require strong reliability and guarantees on messages delivery. These needs are even more important in real time applications like control/command, such as robotic wireless communications where strong temporal constraints are critical. For these reasons, classical random-based Medium Access Control (MAC) protocols present a non-null frame collision probability. In this paper we present an original full deterministic MAC-layer for industrial wireless network and its performance evaluation thanks to the development of a material prototype.


Proposition and validation of an original MAC layer with simultaneous medium accesses for low latency wireless control/command applications

Abstract: Control/command processes require a transmission system with some characteristics like high reliability, low latency and strong guarantees on messages delivery. Concerning wire networks, field buses technologies like FIP offer this kind of service (periodic tasks, real time constraints...). Unfortunately, few wireless technologies can propose a communication system which respects such constraints. Indeed, wireless transmissions must deal with medium characteristics which make impossible the direct translation of mechanisms used with wire networks. The purpose of this paper is to present an original Medium Access Control (MAC) layer for a real time Low Power-Wireless Personal Area Network (LP-WPAN). The proposed MAC-layer has been validated by several complementary methods; in this paper, we focus on the specific Simultaneous Guaranteed Time Slot (SGTS) part.


Frequency of Correctness versus Average-Case Polynomial Time and Generalized Juntas

Abstract: We prove that every distributional problem solvable in polynomial time on the average with respect to the uniform distribution has a frequently self-knowingly correct polynomial-time algorithm. We also study some features of probability weight of correctness with respect to generalizations of Procaccia and Rosenschein's junta distributions [PR07b].


A chain dictionary method for Word Sense Disambiguation and applications

Abstract: A large class of unsupervised algorithms for Word Sense Disambiguation (WSD) is that of dictionary-based methods. Various algorithms have as the root Lesk's algorithm, which exploits the sense definitions in the dictionary directly. Our approach uses the lexical base WordNet for a new algorithm originated in Lesk's, namely "chain algorithm for disambiguation of all words", CHAD. We show how translation from a language into another one and also text entailment verification could be accomplished by this disambiguation.


Data-Oblivious Stream Productivity

Abstract: We are concerned with demonstrating productivity of specifications of infinite streams of data, based on orthogonal rewrite rules. In general, this property is undecidable, but for restricted formats computable sufficient conditions can be obtained. The usual analysis disregards the identity of data, thus leading to approaches that we call data-oblivious. We present a method that is provably optimal among all such data-oblivious approaches. This means that in order to improve on the algorithm in this paper one has to proceed in a data-aware fashion.


Biased Range Trees

Abstract: A data structure, called a biased range tree, is presented that preprocesses a set S of n points in R^2 and a query distribution D for 2-sided orthogonal range counting queries. The expected query time for this data structure, when queries are drawn according to D, matches, to within a constant factor, that of the optimal decision tree for S and D. The memory and preprocessing requirements of the data structure are O(n log n).


A distributed algorithm for computing and updating the process number of a forest

Abstract: In this paper, we present a distributed algorithm to compute various parameters of a tree such as the process number, the edge search number or the node search number and so the pathwidth. This algorithm requires n steps, an overall computation time of O(n log(n)), and n messages of size log_3(n)+3. We then propose a distributed algorithm to update the process number (or the node search number, or the edge search number) of each component of a forest after adding or deleting an edge. This second algorithm requires O(D) steps, an overall computation time of O(D log(n)), and O(D) messages of size log_3(n)+3, where D is the diameter of the modified connected component. Finally, we show how to extend our algorithms to trees and forests of unknown size using messages of less than 2a+4+e bits, where a is the parameter to be determined and e=1 for updates algorithms.


A Process Algebra Software Engineering Environment

Abstract: In previous work we described how the process algebra based language PSF can be used in software engineering, using the ToolBus, a coordination architecture also based on process algebra, as implementation model. In this article we summarize that work and describe the software development process more formally by presenting the tools we use in this process in a CASE setting, leading to the PSF-ToolBus software engineering environment. We generalize the refine step in this environment towards a process algebra based software engineering workbench of which several instances can be combined to form an environment.


A logic with temporally accessible iteration

Abstract: Deficiency in expressive power of the first-order logic has led to developing its numerous extensions by fixed point operators, such as Least Fixed-Point (LFP), inflationary fixed-point (IFP), partial fixed-point (PFP), etc. These logics have been extensively studied in finite model theory, database theory, descriptive complexity. In this paper we introduce unifying framework, the logic with iteration operator, in which iteration steps may be accessed by temporal logic formulae. We show that proposed logic FO+TAI subsumes all mentioned fixed point extensions as well as many other fixed point logics as natural fragments. On the other hand we show that over finite structures FO+TAI is no more expressive than FO+PFP. Further we show that adding the same machinery to the logic of monotone inductions (FO+LFP) does not increase its expressive power either.


MultiKulti Algorithm: Migrating the Most Different Genotypes in an Island Model

Abstract: Migration policies in distributed evolutionary algorithms has not been an active research area until recently. However, in the same way as operators have an impact on performance, the choice of migrants is due to have an impact too. In this paper we propose a new policy (named multikulti) for choosing the individuals that are going to be sent to other nodes, based on multiculturality: the individual sent should be as different as possible to the receiving population. We have checked this policy on different discrete optimization problems, and found that, in average or in median, this policy outperforms classical ones like sending the best or a random individual.


Learning Graph Matching

Abstract: As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. Many formulations of this problem can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility and a quadratic term encodes edge compatibility. The main research focus in this theme is about designing efficient algorithms for approximately solving the quadratic assignment problem, since it is NP-hard. In this paper we turn our attention to a different question: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the `labels' are matches between them. Our experimental results reveal that learning can substantially improve the performance of standard graph matching algorithms. In particular, we find that simple linear assignment with such a learning scheme outperforms Graduated Assignment with bistochastic normalisation, a state-of-the-art quadratic assignment relaxation algorithm.


Strategy Iteration using Non-Deterministic Strategies for Solving Parity Games

Abstract: This article extends the idea of solving parity games by strategy iteration to non-deterministic strategies: In a non-deterministic strategy a player restricts himself to some non-empty subset of possible actions at a given node, instead of limiting himself to exactly one action. We show that a strategy-improvement algorithm by by Bjoerklund, Sandberg, and Vorobyov can easily be adapted to the more general setting of non-deterministic strategies. Further, we show that applying the heuristic of "all profitable switches" leads to choosing a "locally optimal" successor strategy in the setting of non-deterministic strategies, thereby obtaining an easy proof of an algorithm by Schewe. In contrast to the algorithm by Bjoerklund et al., we present our algorithm directly for parity games which allows us to compare it to the algorithm by Jurdzinski and Voege: We show that the valuations used in both algorithm coincide on parity game arenas in which one player can "surrender". Thus, our algorithm can also be seen as a generalization of the one by Jurdzinski and Voege to non-deterministic strategies. Finally, using non-deterministic strategies allows us to show that the number of improvement steps is bound from above by O(1.724^n). For strategy-improvement algorithms, this bound was previously only known to be attainable by using randomization.


On the Optimization of the IEEE 802.11 DCF: A Cross-Layer Perspective

Abstract: This paper is focused on the problem of optimizing the aggregate throughput of the Distributed Coordination Function (DCF) employing the basic access mechanism at the data link layer of IEEE 802.11 protocols. In order to broaden the applicability of the proposed analysis, we consider general operating conditions accounting for both non-saturated and saturated traffic in the presence of transmission channel errors, as exemplified by the packet error rate $P_e$. The main clue of this work stems from the relation that links the aggregate throughput of the network to the packet rate $\lambda$ of the contending stations. In particular, we show that the aggregate throughput $S(\lambda)$ presents two clearly distinct operating regions that depend on the actual value of the packet rate $\lambda$ with respect to a critical value $\lambda_c$, theoretically derived in this work. The behavior of $S(\lambda)$ paves the way to a cross-layer optimization algorithm, which proved to be effective for maximizing the aggregate throughput in a variety of network operating conditions. A nice consequence of the proposed optimization framework relies on the fact that the aggregate throughput can be predicted quite accurately with a simple, yet effective, closed-form expression, which is also derived in the article. Finally, theoretical and simulation results are presented throughout the work in order to unveil, as well as verify, the key ideas.


Neural networks in 3D medical scan visualization

Abstract: For medical volume visualization, one of the most important tasks is to reveal clinically relevant details from the 3D scan (CT, MRI ...), e.g. the coronary arteries, without obscuring them with less significant parts. These volume datasets contain different materials which are difficult to extract and visualize with 1D transfer functions based solely on the attenuation coefficient. Multi-dimensional transfer functions allow a much more precise classification of data which makes it easier to separate different surfaces from each other. Unfortunately, setting up multi-dimensional transfer functions can become a fairly complex task, generally accomplished by trial and error. This paper explains neural networks, and then presents an efficient way to speed up visualization process by semi-automatic transfer function generation. We describe how to use neural networks to detect distinctive features shown in the 2D histogram of the volume data and how to use this information for data classification.


The Kleene-Rosser Paradox, The Liar's Paradox & A Fuzzy Logic Programming Paradox Imply SAT is (NOT) NP-complete

Abstract: After examining the {\bf P} versus {\bf NP} problem against the Kleene-Rosser paradox of the $\lambda$-calculus [94], it was found that it represents a counter-example to NP-completeness. We prove that it contradicts the proof of Cook's theorem. A logical formalization of the liar's paradox leads to the same result. This formalization of the liar's paradox into a computable form is a 2-valued instance of a fuzzy logic programming paradox discovered in the system of [90]. Three proofs that show that {\bf SAT} is (NOT) NP-complete are presented. The counter-example classes to NP-completeness are also counter-examples to Fagin's theorem [36] and the Immermann-Vardi theorem [89,110], the fundamental results of descriptive complexity. All these results show that {\bf ZF$\not$C} is inconsistent.


Multi Site Coordination using a Multi-Agent System

Abstract: A new approach of coordination of decisions in a multi site system is proposed. It is based this approach on a multi-agent concept and on the principle of distributed network of enterprises. For this purpose, each enterprise is defined as autonomous and performs simultaneously at the local and global levels. The basic component of our approach is a so-called Virtual Enterprise Node (VEN), where the enterprise network is represented as a set of tiers (like in a product breakdown structure). Within the network, each partner constitutes a VEN, which is in contact with several customers and suppliers. Exchanges between the VENs ensure the autonomy of decision, and guarantiee the consistency of information and material flows. Only two complementary VEN agents are necessary: one for external interactions, the Negotiator Agent (NA) and one for the planning of internal decisions, the Planner Agent (PA). If supply problems occur in the network, two other agents are defined: the Tier Negotiator Agent (TNA) working at the tier level only and the Supply Chain Mediator Agent (SCMA) working at the level of the enterprise network. These two agents are only active when the perturbation occurs. Otherwise, the VENs process the flow of information alone. With this new approach, managing enterprise network becomes much more transparent and looks like managing a simple enterprise in the network. The use of a Multi-Agent System (MAS) allows physical distribution of the decisional system, and procures a heterarchical organization structure with a decentralized control that guaranties the autonomy of each entity and the flexibility of the network.


Multi-agents architecture for supply chain management

Abstract: The purpose of this paper is to propose a new approach for the supply chain management. This approach is based on the virtual enterprise paradigm and the used of multi-agent concept. Each entity (like enterprise) is autonomous and must perform local and global goals in relation with its environment. The base component of our approach is a Virtual Enterprise Node (VEN). The supply chain is viewed as a set of tiers (corresponding to the levels of production), in which each partner of the supply chain (VEN) is in relation with several customers and suppliers. Each VEN belongs to one tier. The main customer gives global objectives (quantity, cost and delay) to the supply chain. The Mediator Agent (MA) is in charge to manage the supply chain in order to respect those objectives as global level. Those objectives are taking over to Negotiator Agent at the tier level (NAT). These two agents are only active if a perturbation occurs; otherwise information flows are only exchange between VENs. This architecture allows supply chains management which is completely transparent seen from simple enterprise of the supply chain. The used of Multi-Agent System (MAS) allows physical distribution of the decisional system. Moreover, the hierarchical organizational structure with a decentralized control guaranties, in the same time, the autonomy of each entity and the whole flexibility.


Compound Node-Kayles on Paths

Abstract: In his celebrated book "On Number and Games" (Academic Press, New-York, 1976), J.H. Conway introduced twelve versions of compound games. We analyze these twelve versions for the Node-Kayles game on paths. For usual disjunctive compound, Node-Kayles has been solved for a long time under normal play, while it is still unsolved under mis\`ere play. We thus focus on the ten remaining versions, leaving only one of them unsolved.


On the stability of bubble functions and a stabilized mixed finite element formulation for the Stokes problem

Abstract: In this paper we investigate the relationship between stabilized and enriched finite element formulations for the Stokes problem. We also present a new stabilized mixed formulation for which the stability parameter is derived purely by the method of weighted residuals. This new formulation allows equal order interpolation for the velocity and pressure fields. Finally, we show by counterexample that a direct equivalence between subgrid-based stabilized finite element methods and Galerkin methods enriched by bubble functions cannot be constructed for quadrilateral and hexahedral elements using standard bubble functions.


Using rational numbers to key nested sets

Abstract: This report details the generation and use of tree node ordering keys in a single relational database table. The keys for each node are calculated from the keys of its parent, in such a way that the sort order places every node in the tree before all of its descendants and after all siblings having a lower index. The calculation from parent keys to child keys is simple, and reversible in the sense that the keys of every ancestor of a node can be calculated from that node's keys without having to consult the database. Proofs of the above properties of the key encoding process and of its correspondence to a finite continued fraction form are provided.


Algorithmic Based Fault Tolerance Applied to High Performance Computing

Abstract: We present a new approach to fault tolerance for High Performance Computing system. Our approach is based on a careful adaptation of the Algorithmic Based Fault Tolerance technique (Huang and Abraham, 1984) to the need of parallel distributed computation. We obtain a strongly scalable mechanism for fault tolerance. We can also detect and correct errors (bit-flip) on the fly of a computation. To assess the viability of our approach, we have developed a fault tolerant matrix-matrix multiplication subroutine and we propose some models to predict its running time. Our parallel fault-tolerant matrix-matrix multiplication scores 1.4 TFLOPS on 484 processors (cluster jacquard.nersc.gov) and returns a correct result while one process failure has happened. This represents 65% of the machine peak efficiency and less than 12% overhead with respect to the fastest failure-free implementation. We predict (and have observed) that, as we increase the processor count, the overhead of the fault tolerance drops significantly.


TRANS-Net: an Efficient Peer-to-Peer Overlay Network Based on a Full Transposition Graph

Abstract: In this paper we propose a new practical P2P system based on a full transposition network topology named TRANS-Net. Full transposition networks achieve higher fault-tolerance and lower congestion among the class of transposition networks. TRANS-Net provides an efficient lookup service i.e. k hops with high probability, where k satisfies Theta(log_n m) less than k less than Theta(log_2 m), where m denotes the number of system nodes and n is a system parameter related to the maximum number that m can take (up to n!). Experiments show that the look-up performance achieves the lower limit of the complexity relation. TRANS-Net also preserves data locality and provides efficient look-up performance for complex queries such as multi-dimensional queries.


A Computer Verified Theory of Compact Sets

Abstract: Compact sets in constructive mathematics capture our intuition of what computable subsets of the plane (or any other complete metric space) ought to be. A good representation of compact sets provides an efficient means of creating and displaying images with a computer. In this paper, I build upon existing work about complete metric spaces to define compact sets as the completion of the space of finite sets under the Hausdorff metric. This definition allowed me to quickly develop a computer verified theory of compact sets. I applied this theory to compute provably correct plots of uniformly continuous functions.


MOHCS: Towards Mining Overlapping Highly Connected Subgraphs

Abstract: Many networks in real-life typically contain parts in which some nodes are more highly connected to each other than the other nodes of the network. The collection of such nodes are usually called clusters, communities, cohesive groups or modules. In graph terminology, it is called highly connected graph. In this paper, we first prove some properties related to highly connected graph. Based on these properties, we then redefine the highly connected subgraph which results in an algorithm that determines whether a given graph is highly connected in linear time. Then we present a computationally efficient algorithm, called MOHCS, for mining overlapping highly connected subgraphs. We have evaluated experimentally the performance of MOHCS using real and synthetic data sets from computer-generated graph and yeast protein network. Our results show that MOHCS is effective and reliable in finding overlapping highly connected subgraphs. Keywords-component; Highly connected subgraph, clustering algorithms, minimum cut, minimum degree


Local Search Heuristics For The Multidimensional Assignment Problem

Abstract: The Multidimensional Assignment Problem (MAP) (abbreviated s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s also have a large number of applications. We consider several known neighborhoods, generalize them and propose some new ones. The heuristics are evaluated both theoretically and experimentally and dominating algorithms are selected. We also demonstrate a combination of two neighborhoods may yield a heuristics which is superior to both of its components.


On Computing the Vertex Centroid of a Polyhedron

Abstract: Let $\mathcal{P}$ be an $\mathcal{H}$-polytope in $\mathbb{R}^d$ with vertex set $V$. The vertex centroid is defined as the average of the vertices in $V$. We prove that computing the vertex centroid of an $\mathcal{H}$-polytope is #P-hard. Moreover, we show that even just checking whether the vertex centroid lies in a given halfspace is already #P-hard for $\mathcal{H}$-polytopes. We also consider the problem of approximating the vertex centroid by finding a point within an $\epsilon$ distance from it and prove this problem to be #P-easy by showing that given an oracle for counting the number of vertices of an $\mathcal{H}$-polytope, one can approximate the vertex centroid in polynomial time. We also show that any algorithm approximating the vertex centroid to \emph{any} ``sufficiently'' non-trivial (for example constant) distance, can be used to construct a fully polynomial approximation scheme for approximating the centroid and also an output-sensitive polynomial algorithm for the Vertex Enumeration problem. Finally, we show that for unbounded polyhedra the vertex centroid can not be approximated to a distance of $d^{{1/2}-\delta}$ for any fixed constant $\delta>0$.


Stabilizing Tiny Interaction Protocols

Abstract: In this paper we present the self-stabilizing implementation of a class of token based algorithms. In the current work we only consider interactions between weak nodes. They are uniform, they do not have unique identifiers, are static and their interactions are restricted to a subset of nodes called neighbours. While interacting, a pair of neighbouring nodes may create mobile agents (that materialize in the current work the token abstraction) that perform traversals of the network and accelerate the system stabilization. In this work we only explore the power of oblivious stateless agents. Our work shows that the agent paradigm is an elegant distributed tool for achieving self-stabilization in Tiny Interaction Protocols (TIP). Nevertheless, in order to reach the full power of classical self-stabilizing algorithms more complex classes of agents have to be considered (e.g. agents with memory, identifiers or communication skills). Interestingly, our work proposes for the first time a model that unifies the recent studies in mobile robots(agents) that evolve in a discrete space and the already established population protocols paradigm.


"Minesweeper" and spectrum of discrete Laplacians

Abstract: The paper is devoted to a problem inspired by the "Minesweeper" computer game. It is shown that certain configurations of open cells guarantee the existence and the uniqueness of solution. Mathematically the problem is reduced to some spectral properties of discrete differential operators. It is shown how the uniqueness can be used to create a new game which preserves the spirit of "Minesweeper" but does not require a computer.


Consistent Newton-Raphson vs. fixed-point for variational multiscale formulations for incompressible Navier-Stokes

Abstract: The following paper compares a consistent Newton-Raphson and fixed-point iteration based solution strategy for a variational multiscale finite element formulation for incompressible Navier-Stokes. The main contributions of this work include a consistent linearization of the Navier-Stokes equations, which provides an avenue for advanced algorithms that require origins in a consistent method. We also present a comparison between formulations that differ only in their linearization, but maintain all other equivalences. Using the variational multiscale concept, we construct a stabilized formulation (that may be considered an extension of the MINI element to nonlinear Navier-Stokes). We then linearize the problem using fixed-point iteration and by deriving a consistent tangent matrix for the update equation to obtain the solution via Newton-Raphson iterations. We show that the consistent formulation converges in fewer iterations, as expected, for several test problems. We also show that the consistent formulation converges for problems for which fixed-point iteration diverges. We present the results of both methods for problems of Reynold's number up to 5000.


In Pursuit of Spreadsheet Excellence

Abstract: The first fully-documented study into the quantitative impact of errors in operational spreadsheets identified an interesting anomaly. One of the five participating organisations involved in the study contributed a set of five spreadsheets of such quality that they set the organisation apart in a statistical sense. This virtuoso performance gave rise to a simple sampling test - The Clean Sheet Test - which can be used to objectively evaluate if an organisation is in control of the spreadsheets it is using in important processes such as financial reporting.


Statistical Learning of Arbitrary Computable Classifiers

Abstract: Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest is the sample complexity: the number of samples required to learn to a specified level of accuracy. Here we consider learning over the set of all computable labeling functions. Since the VC-dimension is infinite and a priori (uniform) bounds on the number of samples are impossible, we let the learning algorithm decide when it has seen sufficient samples to have learned. We first show that learning in this setting is indeed possible, and develop a learning algorithm. We then show, however, that bounding sample complexity independently of the distribution is impossible. Notably, this impossibility is entirely due to the requirement that the learning algorithm be computable, and not due to the statistical nature of the problem.


Design and Analysis of an Asynchronous Zero Collision MAC Protocol

Abstract: This paper proposes and analyzes a distributed MAC protocol that achieves zero collision with no control message exchange nor synchronization. ZC (ZeroCollision) is neither reservation-based nor dynamic TDMA; the protocol supports variable-length packets and does not lose efficiency when some of the stations do not transmit. At the same time, ZC is not a CSMA; in its steady state, it is completely collision-free. The stations transmit repeatedly in a round-robin order once the convergence state is reached. If some stations skip their turn, their transmissions are replaced by idle $20 \mu$-second mini-slots that enable the other stations to keep track of their order. Because of its short medium access delay and its efficiency, the protocol supports both real-time and elastic applications. The protocol allows for nodes leaving and joining the network; it can allocate more throughput to specific nodes (such as an access point). The protocol is robust against carrier sensing errors or clock drift. While collision avoidance is guaranteed in a single collision domain, it is not the case in a multiple collision one. However, experiments show ZC supports a comparable amount of goodput to CSMA in a multiple collision domain environment. The paper presents an analysis and extensive simulations of the protocol, confirming that ZC outperforms both CSMA and TDMA at high and low load.


Round Trip Time Prediction Using the Symbolic Function Network Approach

Abstract: In this paper, we develop a novel approach to model the Internet round trip time using a recently proposed symbolic type neural network model called symbolic function network. The developed predictor is shown to have good generalization performance and simple representation compared to the multilayer perceptron based predictors.


Approximating Multi-Criteria Max-TSP

Abstract: We present randomized approximation algorithms for multi-criteria Max-TSP. For Max-STSP with k > 1 objective functions, we obtain an approximation ratio of $1/k - \eps$ for arbitrarily small $\eps > 0$. For Max-ATSP with k objective functions, we obtain an approximation ratio of $1/(k+1) - \eps$.


Atlas-Based Prostate Segmentation Using an Hybrid Registration

Abstract: Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.


How Is Meaning Grounded in Dictionary Definitions?

Abstract: Meaning cannot be based on dictionary definitions all the way down: at some point the circularity of definitions must be broken in some way, by grounding the meanings of certain words in sensorimotor categories learned from experience or shaped by evolution. This is the "symbol grounding problem." We introduce the concept of a reachable set -- a larger vocabulary whose meanings can be learned from a smaller vocabulary through definition alone, as long as the meanings of the smaller vocabulary are themselves already grounded. We provide simple algorithms to compute reachable sets for any given dictionary.


Cross-concordances: terminology mapping and its effectiveness for information retrieval

Abstract: The German Federal Ministry for Education and Research funded a major terminology mapping initiative, which found its conclusion in 2007. The task of this terminology mapping initiative was to organize, create and manage 'cross-concordances' between controlled vocabularies (thesauri, classification systems, subject heading lists) centred around the social sciences but quickly extending to other subject areas. 64 crosswalks with more than 500,000 relations were established. In the final phase of the project, a major evaluation effort to test and measure the effectiveness of the vocabulary mappings in an information system environment was conducted. The paper reports on the cross-concordance work and evaluation results.


Computational Approaches to Measuring the Similarity of Short Contexts : A Review of Applications and Methods

Abstract: Measuring the similarity of short written contexts is a fundamental problem in Natural Language Processing. This article provides a unifying framework by which short context problems can be categorized both by their intended application and proposed solution. The goal is to show that various problems and methodologies that appear quite different on the surface are in fact very closely related. The axes by which these categorizations are made include the format of the contexts (headed versus headless), the way in which the contexts are to be measured (first-order versus second-order similarity), and the information used to represent the features in the contexts (micro versus macro views). The unifying thread that binds together many short context applications and methods is the fact that similarity decisions must be made between contexts that share few (if any) words in common.


Optimal Scheduling of File Transfers with Divisible Sizes on Multiple Disjoint Paths

Abstract: In this paper I investigate several offline and online data transfer scheduling problems and propose efficient algorithms and techniques for addressing them. In the offline case, I present a novel, heuristic, algorithm for scheduling files with divisible sizes on multiple disjoint paths, in order to maximize the total profit (the problem is equivalent to the multiple knapsack problem with divisible item sizes). I then consider a cost optimization problem for transferring a sequence of identical files, subject to time constraints imposed by the data transfer providers. For the online case I propose an algorithmic framework based on the block partitioning method, which can speed up the process of resource allocation and reservation.


Separability in the Ambient Logic

Abstract: The \it{Ambient Logic} (AL) has been proposed for expressing properties of process mobility in the calculus of Mobile Ambients (MA), and as a basis for query languages on semistructured data. We study some basic questions concerning the discriminating power of AL, focusing on the equivalence on processes induced by the logic $(=_L>)$. As underlying calculi besides MA we consider a subcalculus in which an image-finiteness condition holds and that we prove to be Turing complete. Synchronous variants of these calculi are studied as well. In these calculi, we provide two operational characterisations of $_=L$: a coinductive one (as a form of bisimilarity) and an inductive one (based on structual properties of processes). After showing $_=L$ to be stricly finer than barbed congruence, we establish axiomatisations of $_=L$ on the subcalculus of MA (both the asynchronous and the synchronous version), enabling us to relate $_=L$ to structural congruence. We also present some (un)decidability results that are related to the above separation properties for AL: the undecidability of $_=L$ on MA and its decidability on the subcalculus.


Conceptualization of seeded region growing by pixels aggregation. Part 1: the framework

Abstract: Adams and Bishop have proposed in 1994 a novel region growing algorithm called seeded region growing by pixels aggregation (SRGPA). This paper introduces a framework to implement an algorithm using SRGPA. This framework is built around two concepts: localization and organization of applied action. This conceptualization gives a quick implementation of algorithms, a direct translation between the mathematical idea and the numerical implementation, and an improvement of algorithms efficiency.


Conceptualization of seeded region growing by pixels aggregation. Part 2: how to localize a final partition invariant about the seeded region initialisation order

Abstract: In the previous paper, we have conceptualized the localization and the organization of seeded region growing by pixels aggregation (SRGPA) but we do not give the issue when there is a collision between two distinct regions during the growing process. In this paper, we propose two implementations to manage two classical growing processes: one without a boundary region region to divide the other regions and another with. Unfortunately, as noticed by Mehnert and Jakway (1997), this partition depends on the seeded region initialisation order (SRIO). We propose a growing process, invariant about SRIO such as the boundary region is the set of ambiguous pixels.


Conceptualization of seeded region growing by pixels aggregation. Part 3: a wide range of algorithms

Abstract: In the two previous papers of this serie, we have created a library, called Population, dedicated to seeded region growing by pixels aggregation and we have proposed different growing processes to get a partition with or without a boundary region to divide the other regions or to get a partition invariant about the seeded region initialisation order. Using this work, we implement some algorithms belonging to the field of SRGPA using this library and these growing processes.


Conceptualization of seeded region growing by pixels aggregation. Part 4: Simple, generic and robust extraction of grains in granular materials obtained by X-ray tomography

Abstract: This paper proposes a simple, generic and robust method to extract the grains from experimental tridimensionnal images of granular materials obtained by X-ray tomography. This extraction has two steps: segmentation and splitting. For the segmentation step, if there is a sufficient contrast between the different components, a classical threshold procedure followed by a succession of morphological filters can be applied. If not, and if the boundary needs to be localized precisely, a watershed transformation controlled by labels is applied. The basement of this transformation is to localize a label included in the component and another label in the component complementary. A "soft" threshold following by an opening is applied on the initial image to localize a label in a component. For any segmentation procedure, the visualisation shows a problem: some groups of two grains, close one to each other, become connected. So if a classical cluster procedure is applied on the segmented binary image, these numerical connected grains are considered as a single grain. To overcome this problem, we applied a procedure introduced by L. Vincent in 1993. This grains extraction is tested for various complexes porous media and granular material, to predict various properties (diffusion, electrical conductivity, deformation field) in a good agreement with experiment data.


A stabilized finite element formulation for advection-diffusion using the generalized finite element framework

Abstract: The following work presents a generalized (extended) finite element formulation for the advection-diffusion equation. Using enrichment functions that represent the exponential nature of the exact solution, smooth numerical solutions are obtained for problems with steep gradients and high Peclet numbers (up to Pe = 25) in one and two-dimensions. As opposed to traditional stabilized methods that require the construction of stability parameters and stabilization terms, the present work avoids numerical instabilities by improving the classical Galerkin solution with an enrichment function. To contextualize this method among other stabilized methods, we show by decomposition of the solution (in a multiscale manner) an equivalence to both Galerkin/least-squares type methods and those that use bubble functions. This work also presents a strategy for constructing the enrichment function for problems with complex geometries by employing a global-local approach.


Design, Development and Testing of Underwater Vehicles: ITB Experience

Abstract: The last decade has witnessed increasing worldwide interest in the research of underwater robotics with particular focus on the area of autonomous underwater vehicles (AUVs). The underwater robotics technology has enabled human to access the depth of the ocean to conduct environmental surveys, resources mapping as well as scientific and military missions. This capability is especially valuable for countries with major water or oceanic resources. As an archipelagic nation with more than 13,000 islands, Indonesia has one of the most abundant living and non-organic oceanic resources. The needs for the mapping, exploration, and environmental preservation of the vast marine resources are therefore imperative. The challenge of the deep water exploration has been the complex issues associated with hazardous and unstructured undersea and sea-bed environments. The paper reports the design, development and testing efforts of underwater vehicle that have been conducted at Institut Teknologi Bandung. Key technology areas have been identified and step-by-step development is presented in conjunction with the need to meet the challenge of underwater vehicle operation. A number of future research directions are also highlighted.


Linear Parameter Varying Model Identification for Control of Rotorcraft-based UAV

Abstract: A rotorcraft-based unmanned aerial vehicle exhibits more complex properties compared to its full-size counterparts due to its increased sensitivity to control inputs and disturbances and higher bandwidth of its dynamics. As an aerial vehicle with vertical take-off and landing capability, the helicopter specifically poses a difficult problem of transition between forward flight and unstable hover and vice versa. The LPV control technique explicitly takes into account the change in performance due to the real-time parameter variations. The technique therefore theoretically guarantees the performance and robustness over the entire operating envelope. In this study, we investigate a new approach implementing model identification for use in the LPV control framework. The identification scheme employs recursive least square technique implemented on the LPV system represented by dynamics of helicopter during a transition. The airspeed as the scheduling of parameter trajectory is not assumed to vary slowly. The exclusion of slow parameter change requirement allows for the application of the algorithm for aggressive maneuvering capability without the need of expensive computation. The technique is tested numerically and will be validated in the autonomous flight of a small scale helicopter.


Data linkage dynamics with shedding

Abstract: We study shedding in the setting of data linkage dynamics, a simple model of computation that bears on the use of dynamic data structures in programming. Shedding is complementary to garbage collection. With shedding, each time a link to a data object is updated by a program, it is determined whether or not the link will possibly be used once again by the program, and if not the link is automatically removed. Thus, everything is made garbage as soon as it can be viewed as garbage. By that, the effectiveness of garbage collection becomes maximal.


A comparison of two approaches for polynomial time algorithms computing basic graph parameters

Abstract: In this paper we compare and illustrate the algorithmic use of graphs of bounded tree-width and graphs of bounded clique-width. For this purpose we give polynomial time algorithms for computing the four basic graph parameters independence number, clique number, chromatic number, and clique covering number on a given tree structure of graphs of bounded tree-width and graphs of bounded clique-width in polynomial time. We also present linear time algorithms for computing the latter four basic graph parameters on trees, i.e. graphs of tree-width 1, and on co-graphs, i.e. graphs of clique-width at most 2.


Complexity of Hybrid Logics over Transitive Frames

Abstract: This paper examines the complexity of hybrid logics over transitive frames, transitive trees, and linear frames. We show that satisfiability over transitive frames for the hybrid language extended with the downarrow operator is NEXPTIME-complete. This is in contrast to undecidability of satisfiability over arbitrary frames for this language (Areces, Blackburn, Marx 1999). It is also shown that adding the @ operator or the past modality leads to undecidability over transitive frames. This is again in contrast to the case of transitive trees and linear frames, where we show these languages to be nonelementarily decidable. Moreover, we establish 2EXPTIME and EXPTIME upper bounds for satisfiability over transitive frames and transitive trees, respectively, for the hybrid Until/Since language. An EXPTIME lower bound is shown to hold for the modal Until language over both frame classes.


Agnostically Learning Juntas from Random Walks

Abstract: We prove that the class of functions g:{-1,+1}^n -> {-1,+1} that only depend on an unknown subset of k<<n variables (so-called k-juntas) is agnostically learnable from a random walk in time polynomial in n, 2^{k^2}, epsilon^{-k}, and log(1/delta). In other words, there is an algorithm with the claimed running time that, given epsilon, delta > 0 and access to a random walk on {-1,+1}^n labeled by an arbitrary function f:{-1,+1}^n -> {-1,+1}, finds with probability at least 1-delta a k-junta that is (opt(f)+epsilon)-close to f, where opt(f) denotes the distance of a closest k-junta to f.


Localized Spanners for Wireless Networks

Abstract: We present a new efficient localized algorithm to construct, for any given quasi-unit disk graph G=(V,E) and any e > 0, a (1+e)-spanner for G of maximum degree O(1) and total weight O(w(MST)), where w(MST) denotes the weight of a minimum spanning tree for V. We further show that similar localized techniques can be used to construct, for a given unit disk graph G = (V, E), a planar Cdel(1+e)(1+pi/2)-spanner for G of maximum degree O(1) and total weight O(w(MST)). Here Cdel denotes the stretch factor of the unit Delaunay triangulation for V. Both constructions can be completed in O(1) communication rounds, and require each node to know its own coordinates.


Implementation for blow up of tornado-type solutions for complex version of 3D Navier-Stokes system

Abstract: We consider Cauchy problem for Fourier transformation of 3-dimensional Navier-Stokes system with zero external force. Using initial data purposed by Dong Li and Ya.G.Sinai we implement self-similar regime producing fast growing behavior of the energy of solution while time tends to critical value.


An Efficient Algorithm for 2D Euclidean 2-Center with Outliers

Abstract: For a set P of n points in R^2, the Euclidean 2-center problem computes a pair of congruent disks of the minimal radius that cover P. We extend this to the (2,k)-center problem where we compute the minimal radius pair of congruent disks to cover n-k points of P. We present a randomized algorithm with O(n k^7 log^3 n) expected running time for the (2,k)-center problem. We also study the (p,k)-center problem in R}^2 under the \ell_\infty-metric. We give solutions for p=4 in O(k^{O(1)} n log n) time and for p=5 in O(k^{O(1)} n log^5 n) time.


On Sequences with Non-Learnable Subsequences

Abstract: The remarkable results of Foster and Vohra was a starting point for a series of papers which show that any sequence of outcomes can be learned (with no prior knowledge) using some universal randomized forecasting algorithm and forecast-dependent checking rules. We show that for the class of all computationally efficient outcome-forecast-based checking rules, this property is violated. Moreover, we present a probabilistic algorithm generating with probability close to one a sequence with a subsequence which simultaneously miscalibrates all partially weakly computable randomized forecasting algorithms. %subsequences non-learnable by each randomized algorithm. According to the Dawid's prequential framework we consider partial recursive randomized algorithms.


Approximability and parameterized complexity of minmax values

Abstract: We consider approximating the minmax value of a multi-player game in strategic form. Tightening recent bounds by Borgs et al., we observe that approximating the value with a precision of epsilon log n digits (for any constant epsilon>0 is NP-hard, where n is the size of the game. On the other hand, approximating the value with a precision of c log log n digits (for any constant c >= 1) can be done in quasi-polynomial time. We consider the parameterized complexity of the problem, with the parameter being the number of pure strategies k of the player for which the minmax value is computed. We show that if there are three players, k=2 and there are only two possible rational payoffs, the minmax value is a rational number and can be computed exactly in linear time. In the general case, we show that the value can be approximated with any polynomial number of digits of accuracy in time n^(O(k)). On the other hand, we show that minmax value approximation is W[1]-hard and hence not likely to be fixed parameter tractable. Concretely, we show that if k-CLIQUE requires time n^(Omega(k)) then so does minmax value computation.


Space Efficient Multi-Dimensional Range Reporting

Abstract: We present a data structure that supports three-dimensional range reporting queries in $O(\log \log U + (\log \log n)^3+k)$ time and uses $O(n\log^{1+\eps} n)$ space, where $U$ is the size of the universe, $k$ is the number of points in the answer,and $\eps$ is an arbitrary constant. This result improves over the data structure of Alstrup, Brodal, and Rauhe (FOCS 2000) that uses $O(n\log^{1+\eps} n)$ space and supports queries in $O(\log n+k)$ time,the data structure of Nekrich (SoCG'07) that uses $O(n\log^{3} n)$ space and supports queries in $O(\log \log U + (\log \log n)^2 + k)$ time, and the data structure of Afshani (ESA'08) that uses $O(n\log^{3} n)$ space and also supports queries in $O(\log \log U + (\log \log n)^2 + k)$ time but relies on randomization during the preprocessing stage. Our result allows us to significantly reduce the space usage of the fastest previously known static and incremental $d$-dimensional data structures, $d\geq 3$, at a cost of increasing the query time by a negligible $O(\log \log n)$ factor.


The 1-fixed-endpoint Path Cover Problem is Polynomial on Interval Graph

Abstract: We consider a variant of the path cover problem, namely, the $k$-fixed-endpoint path cover problem, or kPC for short, on interval graphs. Given a graph $G$ and a subset $\mathcal{T}$ of $k$ vertices of $V(G)$, a $k$-fixed-endpoint path cover of $G$ with respect to $\mathcal{T}$ is a set of vertex-disjoint paths $\mathcal{P}$ that covers the vertices of $G$ such that the $k$ vertices of $\mathcal{T}$ are all endpoints of the paths in $\mathcal{P}$. The kPC problem is to find a $k$-fixed-endpoint path cover of $G$ of minimum cardinality; note that, if $\mathcal{T}$ is empty the stated problem coincides with the classical path cover problem. In this paper, we study the 1-fixed-endpoint path cover problem on interval graphs, or 1PC for short, generalizing the 1HP problem which has been proved to be NP-complete even for small classes of graphs. Motivated by a work of Damaschke, where he left both 1HP and 2HP problems open for the class of interval graphs, we show that the 1PC problem can be solved in polynomial time on the class of interval graphs. The proposed algorithm is simple, runs in $O(n^2)$ time, requires linear space, and also enables us to solve the 1HP problem on interval graphs within the same time and space complexity.


Prediction with Expert Advice in Games with Unbounded One-Step Gains

Abstract: The games of prediction with expert advice are considered in this paper. We present some modification of Kalai and Vempala algorithm of following the perturbed leader for the case of unrestrictedly large one-step gains. We show that in general case the cumulative gain of any probabilistic prediction algorithm can be much worse than the gain of some expert of the pool. Nevertheless, we give the lower bound for this cumulative gain in general case and construct a universal algorithm which has the optimal performance; we also prove that in case when one-step gains of experts of the pool have ``limited deviations'' the performance of our algorithm is close to the performance of the best expert.


Computationally Efficient Estimators for Dimension Reductions Using Stable Random Projections

Abstract: The method of stable random projections is a tool for efficiently computing the $l_\alpha$ distances using low memory, where $0<\alpha \leq 2$ is a tuning parameter. The method boils down to a statistical estimation task and various estimators have been proposed, based on the geometric mean, the harmonic mean, and the fractional power etc. This study proposes the optimal quantile estimator, whose main operation is selecting, which is considerably less expensive than taking fractional power, the main operation in previous estimators. Our experiments report that the optimal quantile estimator is nearly one order of magnitude more computationally efficient than previous estimators. For large-scale learning tasks in which storing and computing pairwise distances is a serious bottleneck, this estimator should be desirable. In addition to its computational advantages, the optimal quantile estimator exhibits nice theoretical properties. It is more accurate than previous estimators when $\alpha>1$. We derive its theoretical error bounds and establish the explicit (i.e., no hidden constants) sample complexity bound.


On Approximating the Lp Distances for p>2

Abstract: Applications in machine learning and data mining require computing pairwise Lp distances in a data matrix A. For massive high-dimensional data, computing all pairwise distances of A can be infeasible. In fact, even storing A or all pairwise distances of A in the memory may be also infeasible. This paper proposes a simple method for p = 2, 4, 6, ... We first decompose the l_p (where p is even) distances into a sum of 2 marginal norms and p-1 ``inner products'' at different orders. Then we apply normal or sub-Gaussian random projections to approximate the resultant ``inner products,'' assuming that the marginal norms can be computed exactly by a linear scan. We propose two strategies for applying random projections. The basic projection strategy requires only one projection matrix but it is more difficult to analyze, while the alternative projection strategy requires p-1 projection matrices but its theoretical analysis is much easier. In terms of the accuracy, at least for p=4, the basic strategy is always more accurate than the alternative strategy if the data are non-negative, which is common in reality.


On empirical meaning of randomness with respect to a real parameter

Abstract: We study the empirical meaning of randomness with respect to a family of probability distributions $P_\theta$, where $\theta$ is a real parameter, using algorithmic randomness theory. In the case when for a computable probability distribution $P_\theta$ an effectively strongly consistent estimate exists, we show that the Levin's a priory semicomputable semimeasure of the set of all $P_\theta$-random sequences is positive if and only if the parameter $\theta$ is a computable real number. The different methods for generating ``meaningful'' $P_\theta$-random sequences with noncomputable $\theta$ are discussed.


The model of quantum evolution

Abstract: This paper has been withdrawn by the author due to extremely unscientific errors.


WiPal: Efficient Offline Merging of IEEE 802.11 Traces

Abstract: Merging wireless traces is a fundamental step in measurement-based studies involving multiple packet sniffers. Existing merging tools either require a wired infrastructure or are limited in their usability. We propose WiPal, an offline merging tool for IEEE 802.11 traces that has been designed to be efficient and simple to use. WiPal is flexible in the sense that it does not require any specific services, neither from monitors (like synchronization, access to a wired network, or embedding specific software) nor from its software environment (e.g. an SQL server). We present WiPal's operation and show how its features - notably, its modular design - improve both ease of use and efficiency. Experiments on real traces show that WiPal is an order of magnitude faster than other tools providing the same features. To our knowledge, WiPal is the only offline trace merger that can be used by the research community in a straightforward fashion.


Interpolation in local theory extensions

Abstract: In this paper we study interpolation in local extensions of a base theory. We identify situations in which it is possible to obtain interpolants in a hierarchical manner, by using a prover and a procedure for generating interpolants in the base theory as black-boxes. We present several examples of theory extensions in which interpolants can be computed this way, and discuss applications in verification, knowledge representation, and modular reasoning in combinations of local theories.


SP2Bench: A SPARQL Performance Benchmark

Abstract: Recently, the SPARQL query language for RDF has reached the W3C recommendation status. In response to this emerging standard, the database community is currently exploring efficient storage techniques for RDF data and evaluation strategies for SPARQL queries. A meaningful analysis and comparison of these approaches necessitates a comprehensive and universal benchmark platform. To this end, we have developed SP^2Bench, a publicly available, language-specific SPARQL performance benchmark. SP^2Bench is settled in the DBLP scenario and comprises both a data generator for creating arbitrarily large DBLP-like documents and a set of carefully designed benchmark queries. The generated documents mirror key characteristics and social-world distributions encountered in the original DBLP data set, while the queries implement meaningful requests on top of this data, covering a variety of SPARQL operator constellations and RDF access patterns. As a proof of concept, we apply SP^2Bench to existing engines and discuss their strengths and weaknesses that follow immediately from the benchmark results.


The Heap Lambda Machine

Abstract: This paper introduces a new machine architecture for evaluating lambda expressions using the normal-order reduction, which guarantees that every lambda expression will be evaluated if the expression has its normal form and the system has enough memory. The architecture considered here operates using heap memory only. Lambda expressions are represented as graphs, and all algorithms used in the processing unit of this machine are non-recursive.


An Algebraic Approach for the MIMO Control of Small Scale Helicopter

Abstract: The control of small-scale helicopter is a MIMO problem. To use of classical control approach to formally solve a MIMO problem, one needs to come up with multidimensional Root Locus diagram to tune the control parameters. The problem with the required dimension of the RL diagram for MIMO design has forced the design procedure of classical approach to be conducted in cascaded multi-loop SISO system starting from the innermost loop outward. To implement this control approach for a helicopter, a pitch and roll attitude control system is often subordinated to a, respectively, longitudinal and lateral velocity control system in a nested architecture. The requirement for this technique to work is that the inner attitude control loop must have a higher bandwidth than the outer velocity control loop which is not the case for high performance mini helicopter. To address the above problems, an algebraic design approach is proposed in this work. The designed control using s-CDM approach is demonstrated for hovering control of small-scale helicopter simultaneously subjected to plant parameter uncertainties and wind disturbances.


Structural Damage Detection Using Randomized Trained Neural Networks

Abstract: A computationally method on damage detection problems in structures was conducted using neural networks. The problem that is considered in this works consists of estimating the existence, location and extent of stiffness reduction in structure which is indicated by the changes of the structural static parameters such as deflection and strain. The neural network was trained to recognize the behaviour of static parameter of the undamaged structure as well as of the structure with various possible damage extent and location which were modelled as random states. The proposed techniques were applied to detect damage in a simply supported beam. The structure was analyzed using finite-element-method (FEM) and the damage identification was conducted by a back-propagation neural network using the change of the structural strain and displacement. The results showed that using proposed method the strain is more efficient for identification of damage than the displacement.


A Fixed-Parameter Algorithm for Random Instances of Weighted d-CNF Satisfiability

Abstract: We study random instances of the weighted $d$-CNF satisfiability problem (WEIGHTED $d$-SAT), a generic W[1]-complete problem. A random instance of the problem consists of a fixed parameter $k$ and a random $d$-CNF formula $\weicnf{n}{p}{k, d}$ generated as follows: for each subset of $d$ variables and with probability $p$, a clause over the $d$ variables is selected uniformly at random from among the $2^d - 1$ clauses that contain at least one negated literals. We show that random instances of WEIGHTED $d$-SAT can be solved in $O(k^2n + n^{O(1)})$-time with high probability, indicating that typical instances of WEIGHTED $d$-SAT under this instance distribution are fixed-parameter tractable. The result also hold for random instances from the model $\weicnf{n}{p}{k,d}(d')$ where clauses containing less than $d' (1 < d' < d)$ negated literals are forbidden, and for random instances of the renormalized (miniaturized) version of WEIGHTED $d$-SAT in certain range of the random model's parameter $p(n)$. This, together with our previous results on the threshold behavior and the resolution complexity of unsatisfiable instances of $\weicnf{n}{p}{k, d}$, provides an almost complete characterization of the typical-case behavior of random instances of WEIGHTED $d$-SAT.


Sparse Online Learning via Truncated Gradient

Abstract: We propose a general method called truncated gradient to induce sparsity in the weights of online learning algorithms with convex loss functions. This method has several essential properties: The degree of sparsity is continuous -- a parameter controls the rate of sparsification from no sparsification to total sparsification. The approach is theoretically motivated, and an instance of it can be regarded as an online counterpart of the popular $L_1$-regularization method in the batch setting. We prove that small rates of sparsification result in only small additional regret with respect to typical online learning guarantees. The approach works well empirically. We apply the approach to several datasets and find that for datasets with large numbers of features, substantial sparsity is discoverable.


On the Throughput Allocation for Proportional Fairness in Multirate IEEE 802.11 DCF

Abstract: This paper presents a modified proportional fairness (PF) criterion suitable for mitigating the \textit{rate anomaly} problem of multirate IEEE 802.11 Wireless LANs employing the mandatory Distributed Coordination Function (DCF) option. Compared to the widely adopted assumption of saturated network, the proposed criterion can be applied to general networks whereby the contending stations are characterized by specific packet arrival rates, $\lambda_s$, and transmission rates $R_d^{s}$. The throughput allocation resulting from the proposed algorithm is able to greatly increase the aggregate throughput of the DCF while ensuring fairness levels among the stations of the same order of the ones available with the classical PF criterion. Put simply, each station is allocated a throughput that depends on a suitable normalization of its packet rate, which, to some extent, measures the frequency by which the station tries to gain access to the channel. Simulation results are presented for some sample scenarios, confirming the effectiveness of the proposed criterion.


Challenging More Updates: Towards Anonymous Re-publication of Fully Dynamic Datasets

Abstract: Most existing anonymization work has been done on static datasets, which have no update and need only one-time publication. Recent studies consider anonymizing dynamic datasets with external updates: the datasets are updated with record insertions and/or deletions. This paper addresses a new problem: anonymous re-publication of datasets with internal updates, where the attribute values of each record are dynamically updated. This is an important and challenging problem for attribute values of records are updating frequently in practice and existing methods are unable to deal with such a situation. We initiate a formal study of anonymous re-publication of dynamic datasets with internal updates, and show the invalidation of existing methods. We introduce theoretical definition and analysis of dynamic datasets, and present a general privacy disclosure framework that is applicable to all anonymous re-publication problems. We propose a new counterfeited generalization principle alled m-Distinct to effectively anonymize datasets with both external updates and internal updates. We also develop an algorithm to generalize datasets to meet m-Distinct. The experiments conducted on real-world data demonstrate the effectiveness of the proposed solution.


Linear Time Algorithms for Finding a Dominating Set of Fixed Size in Degenerated Graphs

Abstract: There is substantial literature dealing with fixed parameter algorithms for the dominating set problem on various families of graphs. In this paper, we give a $k^{O(dk)} n$ time algorithm for finding a dominating set of size at most $k$ in a $d$-degenerated graph with $n$ vertices. This proves that the dominating set problem is fixed-parameter tractable for degenerated graphs. For graphs that do not contain $K_h$ as a topological minor, we give an improved algorithm for the problem with running time $(O(h))^{hk} n$. For graphs which are $K_h$-minor-free, the running time is further reduced to $(O(\log h))^{hk/2} n$. Fixed-parameter tractable algorithms that are linear in the number of vertices of the graph were previously known only for planar graphs. For the families of graphs discussed above, the problem of finding an induced cycle of a given length is also addressed. For every fixed $H$ and $k$, we show that if an $H$-minor-free graph $G$ with $n$ vertices contains an induced cycle of size $k$, then such a cycle can be found in O(n) expected time as well as in $O(n \log n)$ worst-case time. Some results are stated concerning the (im)possibility of establishing linear time algorithms for the more general family of degenerated graphs.


Concept-Oriented Programming

Abstract: Object-oriented programming (OOP) is aimed at describing the structure and behaviour of objects by hiding the mechanism of their representation and access in primitive references. In this article we describe an approach, called concept-oriented programming (COP), which focuses on modelling references assuming that they also possess application-specific structure and behaviour accounting for a great deal or even most of the overall program complexity. References in COP are completely legalized and get the same status as objects while the functions are distributed among both objects and references. In order to support this design we introduce a new programming construct, called concept, which generalizes conventional classes and concept inclusion relation generalizing class inheritance. The main advantage of COP is that it allows programmers to describe two sides of any program: explicitly used functions of objects and intermediate functionality of references having cross-cutting nature and executed implicitly behind the scenes during object access.


Nested Ordered Sets and their Use for Data Modelling

Abstract: In this paper we present a new approach to data modelling, called the concept-oriented model (CoM), and describe its main features and characteristics including data semantics and operations. The distinguishing feature of this model is that it is based on the formalism of nested ordered sets where any element participates in two structures simultaneously: hierarchical (nested) and multi-dimensional (ordered). An element of the model is postulated to consist of two parts, called identity and entity, and the whole approach can be naturally broken into two branches: identity modelling and entity modelling. We also propose a new query language with the main construct, called concept, defined as a pair of two classes: identity class and entity class. We describe how its operations of projection, de-projection and product can be used to solve typical data modelling tasks.


Locality and Bounding-Box Quality of Two-Dimensional Space-Filling Curves

Abstract: Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different space-filling curves are for this purpose. We give general lower bounds on the bounding-box quality measures and on locality according to Gotsman and Lindenbaum for a large class of space-filling curves. We describe a generic algorithm to approximate these and similar quality measures for any given curve. Using our algorithm we find good approximations of the locality and the bounding-box quality of several known and new space-filling curves. Surprisingly, some curves with relatively bad locality by Gotsman and Lindenbaum's measure, have good bounding-box quality, while the curve with the best-known locality has relatively bad bounding-box quality.


AMS Without 4-Wise Independence on Product Domains

Abstract: In their seminal work, Alon, Matias, and Szegedy introduced several sketching techniques, including showing that 4-wise independence is sufficient to obtain good approximations of the second frequency moment. In this work, we show that their sketching technique can be extended to product domains $[n]^k$ by using the product of 4-wise independent functions on $[n]$. Our work extends that of Indyk and McGregor, who showed the result for $k = 2$. Their primary motivation was the problem of identifying correlations in data streams. In their model, a stream of pairs $(i,j) \in [n]^2$ arrive, giving a joint distribution $(X,Y)$, and they find approximation algorithms for how close the joint distribution is to the product of the marginal distributions under various metrics, which naturally corresponds to how close $X$ and $Y$ are to being independent. By using our technique, we obtain a new result for the problem of approximating the $\ell_2$ distance between the joint distribution and the product of the marginal distributions for $k$-ary vectors, instead of just pairs, in a single pass. Our analysis gives a randomized algorithm that is a $(1 \pm \epsilon)$ approximation (with probability $1-\delta$) that requires space logarithmic in $n$ and $m$ and proportional to $3^k$.


A new Hedging algorithm and its application to inferring latent random variables

Abstract: We present a new online learning algorithm for cumulative discounted gain. This learning algorithm does not use exponential weights on the experts. Instead, it uses a weighting scheme that depends on the regret of the master algorithm relative to the experts. In particular, experts whose discounted cumulative gain is smaller (worse) than that of the master algorithm receive zero weight. We also sketch how a regret-based algorithm can be used as an alternative to Bayesian averaging in the context of inferring latent random variables.


On stars and Steiner stars. II

Abstract: A {\em Steiner star} for a set $P$ of $n$ points in $\RR^d$ connects an arbitrary center point to all points of $P$, while a {\em star} connects a point $p\in P$ to the remaining $n-1$ points of $P$. All connections are realized by straight line segments. Fekete and Meijer showed that the minimum star is at most $\sqrt{2}$ times longer than the minimum Steiner star for any finite point configuration in $\RR^d$. The maximum ratio between them, over all finite point configurations in $\RR^d$, is called the {\em star Steiner ratio} in $\RR^d$. It is conjectured that this ratio is $4/\pi = 1.2732...$ in the plane and $4/3=1.3333...$ in three dimensions. Here we give upper bounds of 1.3631 in the plane, and 1.3833 in 3-space, thereby substantially improving recent upper bounds of 1.3999, and $\sqrt{2}-10^{-4}$, respectively. Our results also imply improved bounds on the maximum ratios between the minimum star and the maximum matching in two and three dimensions.


Termination of lambda-calculus with the extra Call-By-Value rule known as assoc

Abstract: In this paper we prove that any lambda-term that is strongly normalising for beta-reduction is also strongly normalising for beta,assoc-reduction. assoc is a call-by-value rule that has been used in works by Moggi, Joachimsky, Espirito Santo and others. The result has often been justified with incomplete or incorrect proofs. Here we give one in full details.


Conception et Evaluation de XQuery dans une architecture de m\'ediation "Tout-XML"

Abstract: XML has emerged as the leading language for representing and exchanging data not only on the Web, but also in general in the enterprise. XQuery is emerging as the standard query language for XML. Thus, tools are required to mediate between XML queries and heterogeneous data sources to integrate data in XML. This paper presents the XMedia mediator, a unique tool for integrating and querying disparate heterogeneous information as unified XML views. It describes the mediator architecture and focuses on the unique distributed query processing technology implemented in this component. Query evaluation is based on an original XML algebra simply extending classical operators to process tuples of tree elements. Further, we present a set of performance evaluation on a relational benchmark, which leads to discuss possible performance enhancements.


Interpr\'etation vague des contraintes structurelles pour la RI dans des corpus de documents XML - \'Evaluation d'une m\'ethode approch\'ee de RI structur\'ee

Abstract: We propose specific data structures designed to the indexing and retrieval of information elements in heterogeneous XML data bases. The indexing scheme is well suited to the management of various contextual searches, expressed either at a structural level or at an information content level. The approximate search mechanisms are based on a modified Levenshtein editing distance and information fusion heuristics. The implementation described highlights the mixing of structured information presented as field/value instances and free text elements. The retrieval performances of the proposed approach are evaluated within the INEX 2005 evaluation campaign. The evaluation results rank the proposed approach among the best evaluated XML IR systems for the VVCAS task.


Game Refinement Relations and Metrics

Abstract: We consider two-player games played over finite state spaces for an infinite number of rounds. At each state, the players simultaneously choose moves; the moves determine a successor state. It is often advantageous for players to choose probability distributions over moves, rather than single moves. Given a goal, for example, reach a target state, the question of winning is thus a probabilistic one: what is the maximal probability of winning from a given state? On these game structures, two fundamental notions are those of equivalences and metrics. Given a set of winning conditions, two states are equivalent if the players can win the same games with the same probability from both states. Metrics provide a bound on the difference in the probabilities of winning across states, capturing a quantitative notion of state similarity. We introduce equivalences and metrics for two-player game structures, and we show that they characterize the difference in probability of winning games whose goals are expressed in the quantitative mu-calculus. The quantitative mu-calculus can express a large set of goals, including reachability, safety, and omega-regular properties. Thus, we claim that our relations and metrics provide the canonical extensions to games, of the classical notion of bisimulation for transition systems. We develop our results both for equivalences and metrics, which generalize bisimulation, and for asymmetrical versions, which generalize simulation.


Finding Large Clique Minors is Hard

Abstract: We prove that it is NP-complete, given a graph G and a parameter h, to determine whether G contains a complete graph K_h as a minor.


Automatic Metadata Generation using Associative Networks

Abstract: In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset.


Quantitative Paradigm of Software Reliability as Content Relevance

Abstract: This paper presents a quantitative approach to software reliability and content relevance definitions validated by the systems' potential reliability law.Thus it is argued for the unified math nature or quantitative paradigm of software reliability and content relevance.


Graph Kernels

Abstract: We present a unified framework to study graph kernels, special cases of which include the random walk graph kernel \citep{GaeFlaWro03,BorOngSchVisetal05}, marginalized graph kernel \citep{KasTsuIno03,KasTsuIno04,MahUedAkuPeretal04}, and geometric kernel on graphs \citep{Gaertner02}. Through extensions of linear algebra to Reproducing Kernel Hilbert Spaces (RKHS) and reduction to a Sylvester equation, we construct an algorithm that improves the time complexity of kernel computation from $O(n^6)$ to $O(n^3)$. When the graphs are sparse, conjugate gradient solvers or fixed-point iterations bring our algorithm into the sub-cubic domain. Experiments on graphs from bioinformatics and other application domains show that it is often more than a thousand times faster than previous approaches. We then explore connections between diffusion kernels \citep{KonLaf02}, regularization on graphs \citep{SmoKon03}, and graph kernels, and use these connections to propose new graph kernels. Finally, we show that rational kernels \citep{CorHafMoh02,CorHafMoh03,CorHafMoh04} when specialized to graphs reduce to the random walk graph kernel.


The Dynamics of Probabilistic Population Protocols

Abstract: We study here the dynamics (and stability) of Probabilistic Population Protocols, via the differential equations approach. We provide a quite general model and we show that it includes the model of Angluin et. al. in the case of very large populations. For the general model we give a sufficient condition for stability that can be checked in polynomial time. We also study two interesting subcases: (a) protocols whose specifications (in our terms) are configuration independent. We show that they are always stable and that their eventual subpopulation percentages are actually a Markov Chain stationary distribution. (b) protocols that have dynamics resembling virus spread. We show that their dynamics are actually similar to the well-known Replicator Dynamics of Evolutionary Games. We also provide a sufficient condition for stability in this case.


Increase of Software Safety

Abstract: New model of software safety is offered. Distribution of mistakes in program on stages of life cycle is researched. Study of ways of increase of reliability of software at help simulation program is leaded.


Range Medians

Abstract: We study a generalization of the classical median finding problem to batched query case: given an array of unsorted $n$ items and $k$ (not necessarily disjoint) intervals in the array, the goal is to determine the median in {\em each} of the intervals in the array. We give an algorithm that uses $O(n\log n + k\log k \log n)$ comparisons and show a lower bound of $\Omega(n\log k)$ comparisons for this problem. This is optimal for $k=O(n/\log n)$.


About the creation of a parallel bilingual corpora of web-publications

Abstract: The algorithm of the creation texts parallel corpora was presented. The algorithm is based on the use of "key words" in text documents, and on the means of their automated translation. Key words were singled out by means of using Russian and Ukrainian morphological dictionaries, as well as dictionaries of the translation of nouns for the Russian and Ukrainianlanguages. Besides, to calculate the weights of the terms in the documents, empiric-statistic rules were used. The algorithm under consideration was realized in the form of a program complex, integrated into the content-monitoring InfoStream system. As a result, a parallel bilingual corpora of web-publications containing about 30 thousand documents, was created


Wireless Broadcast with Network Coding in Mobile Ad-Hoc Networks: DRAGONCAST

Abstract: Network coding is a recently proposed method for transmitting data, which has been shown to have potential to improve wireless network performance. We study network coding for one specific case of multicast, broadcasting, from one source to all nodes of the network. We use network coding as a loss tolerant, energy-efficient, method for broadcast. Our emphasis is on mobile networks. Our contribution is the proposal of DRAGONCAST, a protocol to perform network coding in such a dynamically evolving environment. It is based on three building blocks: a method to permit real-time decoding of network coding, a method to adjust the network coding transmission rates, and a method for ensuring the termination of the broadcast. The performance and behavior of the method are explored experimentally by simulations; they illustrate the excellent performance of the protocol.


On the complexity of finding a sun in a graph

Abstract: The sun is the graph obtained from a cycle of length even and at least six by adding edges to make the even-indexed vertices pairwise adjacent. Suns play an important role in the study of strongly chordal graphs. A graph is chordal if it does not contain an induced cycle of length at least four. A graph is strongly chordal if it is chordal and every even cycle has a chord joining vertices whose distance on the cycle is odd. Farber proved that a graph is strongly chordal if and only if it is chordal and contains no induced suns. There are well known polynomial-time algorithms for recognizing a sun in a chordal graph. Recently, polynomial-time algorithms for finding a sun for a larger class of graphs, the so-called HHD-free graphs, have been discovered. In this paper, we prove the problem of deciding whether an arbitrary graph contains a sun in NP-complete.


Research report: State complexity of operations on two-way quantum finite automata

Abstract: This paper deals with the size complexity of minimal {\it two-way quantum finite automata} (2qfa's) necessary for operations to perform on all inputs of each fixed length. Such a complexity measure, known as state complexity of operations, is useful in measuring how much information is necessary to convert languages. We focus on intersection, union, reversals, and catenation operations and show some upper bounds of state complexity of operations on 2qfa's. Also, we present a number of non-regular languages and prove that these languages can be accepted by 2qfa's with one-sided error probabilities within linear time. Notably, these examples show that our bounds obtained for these operations are not tight, and therefore worth improving. We give an instance to show that the upper bound of the state number for the simulation of one-way deterministic finite automata by two-way reversible finite automata is not tight in general.


Improved bounds and new techniques for Davenport-Schinzel sequences and their generalizations

Abstract: Let lambda_s(n) denote the maximum length of a Davenport-Schinzel sequence of order s on n symbols. For s=3 it is known that lambda_3(n) = Theta(n alpha(n)) (Hart and Sharir, 1986). For general s>=4 there are almost-tight upper and lower bounds, both of the form n * 2^poly(alpha(n)) (Agarwal, Sharir, and Shor, 1989). Our first result is an improvement of the upper-bound technique of Agarwal et al. We obtain improved upper bounds for s>=6, which are tight for even s up to lower-order terms in the exponent. More importantly, we also present a new technique for deriving upper bounds for lambda_s(n). With this new technique we: (1) re-derive the upper bound of lambda_3(n) <= 2n alpha(n) + O(n sqrt alpha(n)) (first shown by Klazar, 1999); (2) re-derive our own new upper bounds for general s; and (3) obtain improved upper bounds for the generalized Davenport-Schinzel sequences considered by Adamec, Klazar, and Valtr (1992). Regarding lower bounds, we show that lambda_3(n) >= 2n alpha(n) - O(n), and therefore, the coefficient 2 is tight. We also present a simpler version of the construction of Agarwal, Sharir, and Shor that achieves the known lower bounds for even s>=4.


Decomposition of Multiple Coverings into More Parts

Abstract: We prove that for every centrally symmetric convex polygon Q, there exists a constant alpha such that any alpha*k-fold covering of the plane by translates of Q can be decomposed into k coverings. This improves on a quadratic upper bound proved by Pach and Toth (SoCG'07). The question is motivated by a sensor network problem, in which a region has to be monitored by sensors with limited battery lifetime.


Lightweight Security for Network Coding

Abstract: Under the emerging network coding paradigm, intermediate nodes in the network are allowed not only to store and forward packets but also to process and mix different data flows. We propose a low-complexity cryptographic scheme that exploits the inherent security provided by random linear network coding and offers the advantage of reduced overhead in comparison to traditional end-to-end encryption of the entire data. Confidentiality is achieved by protecting (or "locking") the source coefficients required to decode the encoded data, without preventing intermediate nodes from running their standard network coding operations. Our scheme can be easily combined with existing techniques that counter active attacks.


Asymptotic Mean Time To Failure and Higher Moments for Large, Recursive Networks

Abstract: This paper deals with asymptotic expressions of the Mean Time To Failure (MTTF) and higher moments for large, recursive, and non-repairable systems in the context of two-terminal reliability. Our aim is to extend the well-known results of the series and parallel cases. We first consider several exactly solvable configurations of identical components with exponential failure-time distribution functions to illustrate different (logarithmic or power-law) behaviors as the size of the system, indexed by an integer n, increases. The general case is then addressed: it provides a simple interpretation of the origin of the power-law exponent and an efficient asymptotic expression for the total reliability of large, recursive systems. Finally, we assess the influence of the non-exponential character of the component reliability on the n-dependence of the MTTF.


Belief decision support and reject for textured images characterization

Abstract: The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can have more than one texture. These considerations allows us to develop a belief decision model permitting to reject an area as unlearning and to decide on unions and intersections of learning classes. The proposed approach finds all its justification in an application of seabed characterization from sonar images, which contributes to an illustration.