Searching the Nodes of a Graph: Theory and Algorithms

Abstract: One or more searchers must capture an invisible evader hiding in the nodes of a graph. We study this graph search problem; we emphasize that we study the capture of a node-located evader, which has received less attention than edge search. We show that in general graphs the problem of node search is easier than that of edge search (however node search is NP-complete, just like edge search). We concentrate on the internal monotone connected (IMC) node search of trees and show that it is essentially equivalent to IMC edge search. For IMC node search on general graphs we present a new algorithm: GSST (Guaranteed Search by Spanning Tree) which clears the graph G by performing all its clearing moves along a spanning tree T of G. We prove the existence of probabilistically complete variants of GSST. Our experiments also indicate that GSST can efficiently node-clear large graphs given only a small running time. An implementation of GSST is also provided and made publicly available.


Learning Nonlinear Dynamic Models

Abstract: We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory showing this new approach is consistent for models with long range structure, and apply the approach to motion capture and high-dimensional video data, yielding results superior to standard alternatives.


Interpretations of the Web of Data

Abstract: The emerging Web of Data utilizes the web infrastructure to represent and interrelate data. The foundational standards of the Web of Data include the Uniform Resource Identifier (URI) and the Resource Description Framework (RDF). URIs are used to identify resources and RDF is used to relate resources. While RDF has been posited as a logic language designed specifically for knowledge representation and reasoning, it is more generally useful if it can conveniently support other models of computing. In order to realize the Web of Data as a general-purpose medium for storing and processing the world's data, it is necessary to separate RDF from its logic language legacy and frame it simply as a data model. Moreover, there is significant advantage in seeing the Semantic Web as a particular interpretation of the Web of Data that is focused specifically on knowledge representation and reasoning. By doing so, other interpretations of the Web of Data are exposed that realize RDF in different capacities and in support of different computing models.


Auctions with Online Supply

Abstract: We study the problem of selling identical goods to n unit-demand bidders in a setting in which the total supply of goods is unknown to the mechanism. Items arrive dynamically, and the seller must make the allocation and payment decisions online with the goal of maximizing social welfare. We consider two models of unknown supply: the adversarial supply model, in which the mechanism must produce a welfare guarantee for any arbitrary supply, and the stochastic supply model, in which supply is drawn from a distribution known to the mechanism, and the mechanism need only provide a welfare guarantee in expectation. Our main result is a separation between these two models. We show that all truthful mechanisms, even randomized, achieve a diminishing fraction of the optimal social welfare (namely, no better than a Omega(loglog n) approximation) in the adversarial setting. In sharp contrast, in the stochastic model, under a standard monotone hazard-rate condition, we present a truthful mechanism that achieves a constant approximation. We show that the monotone hazard rate condition is necessary, and also characterize a natural subclass of truthful mechanisms in our setting, the set of online-envy-free mechanisms. All of the mechanisms we present fall into this class, and we prove almost optimal lower bounds for such mechanisms. Since auctions with unknown supply are regularly run in many online-advertising settings, our main results emphasize the importance of considering distributional information in the design of auctions in such environments.


A Type System for Parallel Components

Abstract: The # component model was proposed to improve the practice of parallel programming. This paper introduces a type system for # programming systems, aiming to lift the abstraction and safety of programming for parallel computing architectures by introducing a notion of abstract component based on universal and existential bounded quantification. Issues about the implementation of such type system in HPE, a # programming system, are also discussed.


Gradient Clock Synchronization using Reference Broadcasts

Abstract: In this paper we suggest a method by which reference broadcast synchronization (RBS), and other methods of estimating clock values, can be incorporated in standard clock synchronization algorithms to improve synchronization quality. We advocate a logical separation of the task of estimating the clock values of other nodes in the network from the task of using these estimates to output a logical clock value. The separation is achieved by means of a virtual estimate graph, overlaid on top of the real network graph, which represents the information various nodes can obtain about each other. RBS estimates are represented in the estimate graph as edges between nodes at distance 2 from each other in the original network graph. A clock synchronization algorithm then operates on the estimate graph as though it were the original network. To illustrate the merits of this approach, we modify a recent optimal gradient clock synchronization algorithm to work in this setting. The modified algorithm transparently takes advantage of RBS estimates and any other means by which nodes can estimate each others' clock values.


A semantical approach to equilibria and rationality

Abstract: Game theoretic equilibria are mathematical expressions of rationality. Rational agents are used to model not only humans and their software representatives, but also organisms, populations, species and genes, interacting with each other and with the environment. Rational behaviors are achieved not only through conscious reasoning, but also through spontaneous stabilization at equilibrium points. Formal theories of rationality are usually guided by informal intuitions, which are acquired by observing some concrete economic, biological, or network processes. Treating such processes as instances of computation, we reconstruct and refine some basic notions of equilibrium and rationality from the some basic structures of computation. It is, of course, well known that equilibria arise as fixed points; the point is that semantics of computation of fixed points seems to be providing novel methods, algebraic and coalgebraic, for reasoning about them.


Two hierarchies of spline interpolations. Practical algorithms for multivariate higher order splines

Abstract: A systematic construction of higher order splines using two hierarchies of polynomials is presented. Explicit instructions on how to implement one of these hierarchies are given. The results are limited to interpolations on regular, rectangular grids, but an approach to other types of grids is also discussed.


Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

Abstract: The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (seaside), Bastia (seaside) and Corte (average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places with different geographical features: Corte, a mountainous region and Bastia, a coastal region. On daily horizon, the relocation has implied fewer errors than a naive prediction method based on the persistence (RMSE=1468 Vs 1383Wh/m2 to Bastia and 1325 Vs 1213Wh/m2 to Corte). On hourly case, the results were still satisfactory, and widely better than persistence (RMSE=138.8 Vs 109.3 Wh/m2 to Bastia and 135.1 Vs 114.7 Wh/m2 to Corte). The last experiment was to evaluate the accuracy of our simulator on a PV power grid localized at 10 km from the station of Ajaccio. We got errors very suitable (nRMSE=27.9%, RMSE=99.0 W.h) compared to those obtained with the persistence (nRMSE=42.2%, RMSE=149.7 W.h).


On the Expected Maximum Degree of Gabriel and Yao Graphs

Abstract: Motivated by applications of Gabriel graphs and Yao graphs in wireless ad-hoc networks, we show that the maximal degree of a random Gabriel graph or Yao graph defined on $n$ points drawn uniformly at random from a unit square grows as $\Theta (\log n / \log \log n)$ in probability.


Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in Symmetric Cournot Games

Abstract: We use co-evolutionary genetic algorithms to model the players' learning process in several Cournot models, and evaluate them in terms of their convergence to the Nash Equilibrium. The "social-learning" versions of the two co-evolutionary algorithms we introduce, establish Nash Equilibrium in those models, in contrast to the "individual learning" versions which, as we see here, do not imply the convergence of the players' strategies to the Nash outcome. When players use "canonical co-evolutionary genetic algorithms" as learning algorithms, the process of the game is an ergodic Markov Chain, and therefore we analyze simulation results using both the relevant methodology and more general statistical tests, to find that in the "social" case, states leading to NE play are highly frequent at the stationary distribution of the chain, in contrast to the "individual learning" case, when NE is not reached at all in our simulations; to find that the expected Hamming distance of the states at the limiting distribution from the "NE state" is significantly smaller in the "social" than in the "individual learning case"; to estimate the expected time that the "social" algorithms need to get to the "NE state" and verify their robustness and finally to show that a large fraction of the games played are indeed at the Nash Equilibrium.


Lindstrom theorems for fragments of first-order logic

Abstract: Lindstr\"om theorems characterize logics in terms of model-theoretic conditions such as Compactness and the L\"owenheim-Skolem property. Most existing characterizations of this kind concern extensions of first-order logic. But on the other hand, many logics relevant to computer science are fragments or extensions of fragments of first-order logic, e.g., k-variable logics and various modal logics. Finding Lindstr\"om theorems for these languages can be challenging, as most known techniques rely on coding arguments that seem to require the full expressive power of first-order logic. In this paper, we provide Lindstr\"om theorems for several fragments of first-order logic, including the k-variable fragments for k>2, Tarski's relation algebra, graded modal logic, and the binary guarded fragment. We use two different proof techniques. One is a modification of the original Lindstr\"om proof. The other involves the modal concepts of bisimulation, tree unraveling, and finite depth. Our results also imply semantic preservation theorems.


Towards Barter Double Auction as Model for Bilateral Social Cooperations

Abstract: The idea of this paper is an advanced game concept. This concept is expected to model non-monetary bilateral cooperations between self-interested agents. Such non-monetary cases are social cooperations like allocation of high level jobs or sexual relationships among humans. In a barter double auction, there is a big amount of agents. Every agent has a vector of parameters which specifies his demand and a vector which specifies his offer. Two agents can achieve a commitment through barter exchange. The subjective satisfaction level (a number between 0% and 100%) of an agent is as high as small is the distance between his demand and the accepted offer. This paper introduces some facets of this complex game concept.


A formal proof of the four color theorem

Abstract: A formal proof has not been found for the four color theorem since 1852 when Francis Guthrie first conjectured the four color theorem. Why? A bad idea, we think, directed people to a rough road. Using a similar method to that for the formal proof of the five color theorem, a formal proof is proposed in this paper of the four color theorem, namely, every planar graph is four-colorable. The formal proof proposed can also be regarded as an algorithm to color a planar graph using four colors so that no two adjacent vertices receive the same color.


Where are the really hard manipulation problems? The phase transition in manipulating the veto rule

Abstract: Voting is a simple mechanism to aggregate the preferences of agents. Many voting rules have been shown to be NP-hard to manipulate. However, a number of recent theoretical results suggest that this complexity may only be in the worst-case since manipulation is often easy in practice. In this paper, we show that empirical studies are useful in improving our understanding of this issue. We demonstrate that there is a smooth transition in the probability that a coalition can elect a desired candidate using the veto rule as the size of the manipulating coalition increases. We show that a rescaled probability curve displays a simple and universal form independent of the size of the problem. We argue that manipulation of the veto rule is asymptotically easy for many independent and identically distributed votes even when the coalition of manipulators is critical in size. Based on this argument, we identify a situation in which manipulation is computationally hard. This is when votes are highly correlated and the election is "hung". We show, however, that even a single uncorrelated voter is enough to make manipulation easy again.


Decompositions of All Different, Global Cardinality and Related Constraints

Abstract: We show that some common and important global constraints like ALL-DIFFERENT and GCC can be decomposed into simple arithmetic constraints on which we achieve bound or range consistency, and in some cases even greater pruning. These decompositions can be easily added to new solvers. They also provide other constraints with access to the state of the propagator by sharing of variables. Such sharing can be used to improve propagation between constraints. We report experiments with our decomposition in a pseudo-Boolean solver.


Circuit Complexity and Decompositions of Global Constraints

Abstract: We show that tools from circuit complexity can be used to study decompositions of global constraints. In particular, we study decompositions of global constraints into conjunctive normal form with the property that unit propagation on the decomposition enforces the same level of consistency as a specialized propagation algorithm. We prove that a constraint propagator has a a polynomial size decomposition if and only if it can be computed by a polynomial size monotone Boolean circuit. Lower bounds on the size of monotone Boolean circuits thus translate to lower bounds on the size of decompositions of global constraints. For instance, we prove that there is no polynomial sized decomposition of the domain consistency propagator for the ALLDIFFERENT constraint.


Scenario-based Stochastic Constraint Programming

Abstract: To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number of important dimensions (e.g. to multiple chance constraints and to a range of new objectives). We also provide a new (but equivalent) semantics based on scenarios. Using this semantics, we can compile stochastic constraint programs down into conventional (nonstochastic) constraint programs. This allows us to exploit the full power of existing constraint solvers. We have implemented this framework for decision making under uncertainty in stochastic OPL, a language which is based on the OPL constraint modelling language [Hentenryck et al., 1999]. To illustrate the potential of this framework, we model a wide range of problems in areas as diverse as finance, agriculture and production.


Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques

Abstract: Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all three kinds of information. We therefore propose a framework, based on both CP-nets and soft constraints, that handles both hard and soft constraints as well as conditional preferences efficiently and uniformly. We study the complexity of testing the consistency of preference statements, and show how soft constraints can faithfully approximate the semantics of conditional preference statements whilst improving the computational complexity


Multiset Ordering Constraints

Abstract: We identify a new and important global (or non-binary) constraint. This constraint ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered. This constraint is useful for a number of different applications including breaking symmetry and fuzzy constraint satisfaction. We propose and implement an efficient linear time algorithm for enforcing generalised arc consistency on such a multiset ordering constraint. Experimental results on several problem domains show considerable promise.


On the complexity of identifying Head Elementary Set Free programs

Abstract: Head-elementary-set-free programs were proposed in (Gebser et al. 2007) and shown to generalize over head-cycle-free programs while retaining their nice properties. It was left as an open problem in (Gebser et al. 2007) to establish the complexity of identifying head-elementary-set-free programs. This note solves the open problem, by showing that the problem is complete for co-NP.


Some Results On Convex Greedy Embedding Conjecture for 3-Connected Planar Graphs

Abstract: A greedy embedding of a graph $G = (V,E)$ into a metric space $(X,d)$ is a function $x : V(G) \to X$ such that in the embedding for every pair of non-adjacent vertices $x(s), x(t)$ there exists another vertex $x(u)$ adjacent to $x(s)$ which is closer to $x(t)$ than $x(s)$. This notion of greedy embedding was defined by Papadimitriou and Ratajczak (Theor. Comput. Sci. 2005), where authors conjectured that every 3-connected planar graph has a greedy embedding (possibly planar and convex) in the Euclidean plane. Recently, greedy embedding conjecture has been proved by Leighton and Moitra (FOCS 2008). However, their algorithm do not result in a drawing that is planar and convex for all 3-connected planar graph in the Euclidean plane. In this work we consider the planar convex greedy embedding conjecture and make some progress. We derive a new characterization of planar convex greedy embedding that given a 3-connected planar graph $G = (V,E)$, an embedding $x: V \to \bbbr^2$ of $G$ is a planar convex greedy embedding if and only if, in the embedding $x$, weight of the maximum weight spanning tree ($T$) and weight of the minimum weight spanning tree ($\func{MST}$) satisfies $\WT(T)/\WT(\func{MST}) \leq (\card{V}-1)^{1 - \delta}$, for some $0 < \delta \leq 1$.


Tag Clouds for Displaying Semantics: The Case of Filmscripts

Abstract: We relate tag clouds to other forms of visualization, including planar or reduced dimensionality mapping, and Kohonen self-organizing maps. Using a modified tag cloud visualization, we incorporate other information into it, including text sequence and most pertinent words. Our notion of word pertinence goes beyond just word frequency and instead takes a word in a mathematical sense as located at the average of all of its pairwise relationships. We capture semantics through context, taken as all pairwise relationships. Our domain of application is that of filmscript analysis. The analysis of filmscripts, always important for cinema, is experiencing a major gain in importance in the context of television. Our objective in this work is to visualize the semantics of filmscript, and beyond filmscript any other partially structured, time-ordered, sequence of text segments. In particular we develop an innovative approach to plot characterization.


Swap Bribery

Abstract: In voting theory, bribery is a form of manipulative behavior in which an external actor (the briber) offers to pay the voters to change their votes in order to get her preferred candidate elected. We investigate a model of bribery where the price of each vote depends on the amount of change that the voter is asked to implement. Specifically, in our model the briber can change a voter's preference list by paying for a sequence of swaps of consecutive candidates. Each swap may have a different price; the price of a bribery is the sum of the prices of all swaps that it involves. We prove complexity results for this model, which we call swap bribery, for a broad class of election systems, including variants of approval and k-approval, Borda, Copeland, and maximin.


SuperNOVA: a novel algorithm for graph automorphism calculations

Abstract: The graph isomorphism problem is of practical importance, as well as being a theoretical curiosity in computational complexity theory in that it is not known whether it is $NP$-complete or $P$. However, for many graphs, the problem is tractable, and related to the problem of finding the automorphism group of the graph. Perhaps the most well known state-of-the art implementation for finding the automorphism group is Nauty. However, Nauty is particularly susceptible to poor performance on star configurations, where the spokes of the star are isomorphic with each other. In this work, I present an algorithm that explodes these star configurations, reducing the problem to a sequence of simpler automorphism group calculations.


FTOS-Verify: Analysis and Verification of Non-Functional Properties for Fault-Tolerant Systems

Abstract: The focus of the tool FTOS is to alleviate designers' burden by offering code generation for non-functional aspects including fault-tolerance mechanisms. One crucial aspect in this context is to ensure that user-selected mechanisms for the system model are sufficient to resist faults as specified in the underlying fault hypothesis. In this paper, formal approaches in verification are proposed to assist the claim. We first raise the precision of FTOS into pure mathematical constructs, and formulate the deterministic assumption, which is necessary as an extension of Giotto-like systems (e.g., FTOS) to equip with fault-tolerance abilities. We show that local properties of a system with the deterministic assumption will be preserved in a modified synchronous system used as the verification model. This enables the use of techniques known from hardware verification. As for implementation, we develop a prototype tool called FTOS-Verify, deploy it as an Eclipse add-on for FTOS, and conduct several case studies.


Modeling and Verification for Timing Satisfaction of Fault-Tolerant Systems with Finiteness

Abstract: The increasing use of model-based tools enables further use of formal verification techniques in the context of distributed real-time systems. To avoid state explosion, it is necessary to construct verification models that focus on the aspects under consideration. In this paper, we discuss how we construct a verification model for timing analysis in distributed real-time systems. We (1) give observations concerning restrictions of timed automata to model these systems, (2) formulate mathematical representations on how to perform model-to-model transformation to derive verification models from system models, and (3) propose some theoretical criteria how to reduce the model size. The latter is in particular important, as for the verification of complex systems, an efficient model reflecting the properties of the system under consideration is equally important to the verification algorithm itself. Finally, we present an extension of the model-based development tool FTOS, designed to develop fault-tolerant systems, to demonstrate %the benefits of our approach.


A New Solution to the Relative Orientation Problem using only 3 Points and the Vertical Direction

Abstract: This paper presents a new method to recover the relative pose between two images, using three points and the vertical direction information. The vertical direction can be determined in two ways: 1- using direct physical measurement like IMU (inertial measurement unit), 2- using vertical vanishing point. This knowledge of the vertical direction solves 2 unknowns among the 3 parameters of the relative rotation, so that only 3 homologous points are requested to position a couple of images. Rewriting the coplanarity equations leads to a simpler solution. The remaining unknowns resolution is performed by an algebraic method using Grobner bases. The elements necessary to build a specific algebraic solver are given in this paper, allowing for a real-time implementation. The results on real and synthetic data show the efficiency of this method.


Optimal byzantine resilient convergence in oblivious robot networks

Abstract: Given a set of robots with arbitrary initial location and no agreement on a global coordinate system, convergence requires that all robots asymptotically approach the exact same, but unknown beforehand, location. Robots are oblivious-- they do not recall the past computations -- and are allowed to move in a one-dimensional space. Additionally, robots cannot communicate directly, instead they obtain system related information only via visual sensors. We draw a connection between the convergence problem in robot networks, and the distributed \emph{approximate agreement} problem (that requires correct processes to decide, for some constant $\epsilon$, values distance $\epsilon$ apart and within the range of initial proposed values). Surprisingly, even though specifications are similar, the convergence implementation in robot networks requires specific assumptions about synchrony and Byzantine resilience. In more details, we prove necessary and sufficient conditions for the convergence of mobile robots despite a subset of them being Byzantine (i.e. they can exhibit arbitrary behavior). Additionally, we propose a deterministic convergence algorithm for robot networks and analyze its correctness and complexity in various synchrony settings. The proposed algorithm tolerates f Byzantine robots for (2f+1)-sized robot networks in fully synchronous networks, (3f+1)-sized in semi-synchronous networks. These bounds are optimal for the class of cautious algorithms, which guarantee that correct robots always move inside the range of positions of the correct robots.


Continued Fraction Expansion of Real Roots of Polynomial Systems

Abstract: We present a new algorithm for isolating the real roots of a system of multivariate polynomials, given in the monomial basis. It is inspired by existing subdivision methods in the Bernstein basis; it can be seen as generalization of the univariate continued fraction algorithm or alternatively as a fully analog of Bernstein subdivision in the monomial basis. The representation of the subdivided domains is done through homographies, which allows us to use only integer arithmetic and to treat efficiently unbounded regions. We use univariate bounding functions, projection and preconditionning techniques to reduce the domain of search. The resulting boxes have optimized rational coordinates, corresponding to the first terms of the continued fraction expansion of the real roots. An extension of Vincent's theorem to multivariate polynomials is proved and used for the termination of the algorithm. New complexity bounds are provided for a simplified version of the algorithm. Examples computed with a preliminary C++ implementation illustrate the approach.


A Physical Model of Wireless Network

Abstract: Using an approach developed in physics, we propose a new framework for the study of cellular networks. The key idea of the physical network model we propose is to replace the discrete base stations (BS) entities by a continuum of transmitters which are spatially distributed in the network. This allows us to establish a closed form formula of the other-cell downlink interference factor f, as a function of the location of the mobile. We define here f as the ratio of outer cell received power (i.e. the power received from other cells) to the inner cell received power. This physical model allows calculating the influence of interference on any mobile in a cell, whatever its position. Results obtained with that closed-form formula are close to the ones obtained by simulations using a traditional hexagonal network model. Since the physical model allows to establish a closed form formula of the interference factor, it allows to do analytical studies of wireless networks such as outage probability, quality of service, capacity.


Transfer Learning Using Feature Selection

Abstract: We present three related ways of using Transfer Learning to improve feature selection. The three methods address different problems, and hence share different kinds of information between tasks or feature classes, but all three are based on the information theoretic Minimum Description Length (MDL) principle and share the same underlying Bayesian interpretation. The first method, MIC, applies when predictive models are to be built simultaneously for multiple tasks (``simultaneous transfer'') that share the same set of features. MIC allows each feature to be added to none, some, or all of the task models and is most beneficial for selecting a small set of predictive features from a large pool of features, as is common in genomic and biological datasets. Our second method, TPC (Three Part Coding), uses a similar methodology for the case when the features can be divided into feature classes. Our third method, Transfer-TPC, addresses the ``sequential transfer'' problem in which the task to which we want to transfer knowledge may not be known in advance and may have different amounts of data than the other tasks. Transfer-TPC is most beneficial when we want to transfer knowledge between tasks which have unequal amounts of labeled data, for example the data for disambiguating the senses of different verbs. We demonstrate the effectiveness of these approaches with experimental results on real world data pertaining to genomics and to Word Sense Disambiguation (WSD).


Normalized Web Distance and Word Similarity

Abstract: There is a great deal of work in cognitive psychology, linguistics, and computer science, about using word (or phrase) frequencies in context in text corpora to develop measures for word similarity or word association, going back to at least the 1960s. The goal of this chapter is to introduce the normalizedis a general way to tap the amorphous low-grade knowledge available for free on the Internet, typed in by local users aiming at personal gratification of diverse objectives, and yet globally achieving what is effectively the largest semantic electronic database in the world. Moreover, this database is available for all by using any search engine that can return aggregate page-count estimates for a large range of search-queries. In the paper introducing the NWD it was called `normalized Google distance (NGD),' but since Google doesn't allow computer searches anymore, we opt for the more neutral and descriptive NWD. web distance (NWD) method to determine similarity between words and phrases. It


A 4/3-competitive randomized algorithm for online scheduling of packets with agreeable deadlines

Abstract: In 2005 Li et al. gave a phi-competitive deterministic online algorithm for scheduling of packets with agreeable deadlines with a very interesting analysis. This is known to be optimal due to a lower bound by Hajek. We claim that the algorithm by Li et al. can be slightly simplified, while retaining its competitive ratio. Then we introduce randomness to the modified algorithm and argue that the competitive ratio against oblivious adversary is at most 4/3. Note that this still leaves a gap between the best known lower bound of 5/4 by Chin et al. for randomised algorithms against oblivious adversary.


Orthomodular lattices, Foulis Semigroups and Dagger Kernel Categories

Abstract: This paper is a sequel to arXiv:0902.2355 and continues the study of quantum logic via dagger kernel categories. It develops the relation between these categories and both orthomodular lattices and Foulis semigroups. The relation between the latter two notions has been uncovered in the 1960s. The current categorical perspective gives a broader context and reconstructs this relationship between orthomodular lattices and Foulis semigroups as special instance.


Online Stochastic Matching: Beating 1-1/e

Abstract: We study the online stochastic bipartite matching problem, in a form motivated by display ad allocation on the Internet. In the online, but adversarial case, the celebrated result of Karp, Vazirani and Vazirani gives an approximation ratio of $1-1/e$. In the online, stochastic case when nodes are drawn repeatedly from a known distribution, the greedy algorithm matches this approximation ratio, but still, no algorithm is known that beats the $1 - 1/e$ bound. Our main result is a 0.67-approximation online algorithm for stochastic bipartite matching, breaking this $1 - {1/e}$ barrier. Furthermore, we show that no online algorithm can produce a $1-\epsilon$ approximation for an arbitrarily small $\epsilon$ for this problem. We employ a novel application of the idea of the power of two choices from load balancing: we compute two disjoint solutions to the expected instance, and use both of them in the online algorithm in a prescribed preference order. To identify these two disjoint solutions, we solve a max flow problem in a boosted flow graph, and then carefully decompose this maximum flow to two edge-disjoint (near-)matchings. These two offline solutions are used to characterize an upper bound for the optimum in any scenario. This is done by identifying a cut whose value we can bound under the arrival distribution.


Faster estimation of the correlation fractal dimension using box-counting

Abstract: Fractal dimension is widely adopted in spatial databases and data mining, among others as a measure of dataset skewness. State-of-the-art algorithms for estimating the fractal dimension exhibit linear runtime complexity whether based on box-counting or approximation schemes. In this paper, we revisit a correlation fractal dimension estimation algorithm that redundantly rescans the dataset and, extending that work, we propose another linear, yet faster and as accurate method, which completes in a single pass.


Distributed Discovery of Large Near-Cliques

Abstract: Given an undirected graph and $0\le\epsilon\le1$, a set of nodes is called $\epsilon$-near clique if all but an $\epsilon$ fraction of the pairs of nodes in the set have a link between them. In this paper we present a fast synchronous network algorithm that uses small messages and finds a near-clique. Specifically, we present a constant-time algorithm that finds, with constant probability of success, a linear size $\epsilon$-near clique if there exists an $\epsilon^3$-near clique of linear size in the graph. The algorithm uses messages of $O(\log n)$ bits. The failure probability can be reduced to $n^{-\Omega(1)}$ in $O(\log n)$ time, and the algorithm also works if the graph contains a clique of size $\Omega(n/\log^{\alpha}\log n)$ for some $\alpha \in (0,1)$.


Google matrix, dynamical attractors and Ulam networks

Abstract: We study the properties of the Google matrix generated by a coarse-grained Perron-Frobenius operator of the Chirikov typical map with dissipation. The finite size matrix approximant of this operator is constructed by the Ulam method. This method applied to the simple dynamical model creates the directed Ulam networks with approximate scale-free scaling and characteristics being rather similar to those of the World Wide Web. The simple dynamical attractors play here the role of popular web sites with a strong concentration of PageRank. A variation of the Google parameter $\alpha$ or other parameters of the dynamical map can drive the PageRank of the Google matrix to a delocalized phase with a strange attractor where the Google search becomes inefficient.


Answers to Questions Formulated in the Paper "On States Observability in Deterministic Finite Automata"

Abstract: This paper gives answers to questions formulated as open in the paper "On State Observability in Deterministic Finite Automata" by A. Mateescu and Gh. Paun. Specifically, it demonstrates that for all k >= 2, the families of regular languages acceptable by deterministic finite automata with no more than k semi-observable states, denoted by Tk, are anti-AFL's, and that the family T1 differs in the closure property under Kleene +.


The Usefulness of Multilevel Hash Tables with Multiple Hash Functions in Large Databases

Abstract: In this work, attempt is made to select three good hash functions which uniformly distribute hash values that permute their internal states and allow the input bits to generate different output bits. These functions are used in different levels of hash tables that are coded in Java Programming Language and a quite number of data records serve as primary data for testing the performances. The result shows that the two-level hash tables with three different hash functions give a superior performance over one-level hash table with two hash functions or zero-level hash table with one function in term of reducing the conflict keys and quick lookup for a particular element. The result assists to reduce the complexity of join operation in query language from O(n2) to O(1) by placing larger query result, if any, in multilevel hash tables with multiple hash functions and generate shorter query result.


Multimedia Aplication for Solving a Sudoku Game

Abstract: This article explains the way in which, with the help of Action Script 3 in combination with Flash, a method of solving Sudoku game was implemented, through searching for the certain numbers and after that trying to guess for the squares where there are two possible numbers.


Development and Optimization of a Multimedia Product

Abstract: This article presents a new concept of a multimedia interactive product. It is a multiuser versatile platform that can be used for different purposes. The first implementation of the platform is a multiplayer game called Texas Hold 'em, which is a very popular community card game. The paper shows the product's multimedia structure where Hardware and Software work together in creating a realistic feeling for the users.


Strong Dependencies between Software Components

Abstract: Component-based systems often describe context requirements in terms of explicit inter-component dependencies. Studying large instances of such systems?such as free and open source software (FOSS) distributions?in terms of declared dependencies between packages is appealing. It is however also misleading when the language to express dependencies is as expressive as boolean formulae, which is often the case. In such settings, a more appropriate notion of component dependency exists: strong dependency. This paper introduces such notion as a first step towards modeling semantic, rather then syntactic, inter-component relationships. Furthermore, a notion of component sensitivity is derived from strong dependencies, with ap- plications to quality assurance and to the evaluation of upgrade risks. An empirical study of strong dependencies and sensitivity is presented, in the context of one of the largest, freely available, component-based system.


The Convergence of Bird Flocking

Abstract: We bound the time it takes for a group of birds to reach steady state in a standard flocking model. We prove that (i) within single exponential time fragmentation ceases and each bird settles on a fixed flying direction; (ii) the flocking network converges only after a number of steps that is an iterated exponential of height logarithmic in the number of birds. We also prove the highly surprising result that this bound is optimal. The model directs the birds to adjust their velocities repeatedly by averaging them with their neighbors within a fixed radius. The model is deterministic, but we show that it can tolerate a reasonable amount of stochastic or even adversarial noise. Our methods are highly general and we speculate that the results extend to a wider class of models based on undirected flocking networks, whether defined metrically or topologically. This work introduces new techniques of broader interest, including the "flight net," the "iterated spectral shift," and a certain "residue-clearing" argument in circuit complexity.


Execution Time of lambda-Terms via Denotational Semantics and Intersection Types

Abstract: The multiset based relational model of linear logic induces a semantics of the type free lambda-calculus, which corresponds to a non-idempotent intersection type system, System R. We prove that, in System R, the size of the type derivations and the size of the types are closely related to the execution time of lambda-terms in a particular environment machine, Krivine's machine.


Mathematical Models in Danube Water Quality

Abstract: The mathematical shaping in the study of water quality has become a branch of environmental engineering. The comprehension and effective application of mathematical models in studying environmental phenomena keep up with the results in the domain of mathematics and the development of specialized software as well. Integrated software programs simulate and predict extreme events, propose solutions, analyzing and processing data in due time. This paper presents a browsing through some mathematical categories of processing the statistical data, examples and their analysis concerning the degree of water pollution downstream the river Danube.


On expressive power and class invariance

Abstract: In computer science, various logical languages are defined to analyze properties of systems. One way to pinpoint the essential differences between those logics is to compare their expressivity in terms of distinguishing power and expressive power. In this paper, we study those two concepts by regarding the latter notion as the former lifted to classes of models. We show some general results on lifting an invariance relation on models to one on classes of models, such that when the former corresponds to the distinguishing power of a logic, the latter corresponds to its expressive power, given certain compactness requirements. In particular, we introduce the notion of class bisimulation to capture the expressive power of modal logics. We demonstrate the application of our results by revisiting modal definability with our new insights.


Automating Quantified Multimodal Logics in Simple Type Theory -- A Case Study

Abstract: In a case study we investigate whether off the shelf higher-order theorem provers and model generators can be employed to automate reasoning in and about quantified multimodal logics. In our experiments we exploit the new TPTP infrastructure for classical higher-order logic.


Information Modeling for a Dynamic Representation of an Emergency Situation

Abstract: In this paper we propose an approach to build a decision support system that can help emergency planners and responders to detect and manage emergency situations. The internal mechanism of the system is independent from the treated application. Therefore, we think the system may be used or adapted easily to different case studies. We focus here on a first step in the decision-support process which concerns the modeling of information issued from the perceived environment and their representation dynamically using a multiagent system. This modeling was applied on the RoboCupRescue Simulation System. An implementation and some results are presented here.


Limits of Educational Soft "GeoGebra" in a Critical Constructive Review

Abstract: Mathematical educational soft explore, investigating in a dynamical way, some algebraically, geometrically problems, the expected results being used to involve a lot of mathematical results. One such software soft is GeoGebra. The software is free and multi-platform dynamic mathematics software for learning and teaching, awards in Europe and the USA. This paper describes some critical but constructive investigation using the platform for graph functions and dynamic geometry.


Proposition d'une methode de qualification et de selection d'un logiciel d'analyse et de suivi du referencement dans les moteurs de recherche

Abstract: In order to measure website visibility in search engines, there are softwares for analytics and referencing follow-up. They permit to quantify website's efficacity of referencing and optimize its positionning in search engines. With regard to search engines' algorithms' evolution and centralization of Key Performance Indicators for Marketing decision making, it becomes hard to find solutions to effectively lead a lot of projects for referencing. That's why we have built a methodology in order compare, evaluate and choose a software for analytics and referencing follow-up in search engines.


Reverse nearest neighbor queries in fixed dimension

Abstract: Reverse nearest neighbor queries are defined as follows: Given an input point-set P, and a query point q, find all the points p in P whose nearest point in P U {q} \ {p} is q. We give a data structure to answer reverse nearest neighbor queries in fixed-dimensional Euclidean space. Our data structure uses O(n) space, its preprocessing time is O(n log n), and its query time is O(log n).


Approximation Algorithms for the Traveling Repairman and Speeding Deliveryman Problems

Abstract: Constant-factor, polynomial-time approximation algorithms are presented for two variations of the traveling salesman problem with time windows. In the first variation, the traveling repairman problem, the goal is to find a tour that visits the maximum possible number of locations during their time windows. In the second variation, the speeding deliveryman problem, the goal is to find a tour that uses the minimum possible speedup to visit all locations during their time windows. For both variations, the time windows are of unit length, and the distance metric is based on a weighted, undirected graph. Algorithms with improved approximation ratios are given for the case when the input is defined on a tree rather than a general graph. The algorithms are also extended to handle time windows whose lengths fall in any bounded range.


Analysis of Sorting Algorithms by Kolmogorov Complexity (A Survey)

Abstract: Recently, many results on the computational complexity of sorting algorithms were obtained using Kolmogorov complexity (the incompressibility method). Especially, the usually hard average-case analysis is ammenable to this method. Here we survey such results about Bubblesort, Heapsort, Shellsort, Dobosiewicz-sort, Shakersort, and sorting with stacks and queues in sequential or parallel mode. Especially in the case of Shellsort the uses of Kolmogorov complexity surprisingly easily resolved problems that had stayed open for a long time despite strenuous attacks.


Bounding the Sum of Square Roots via Lattice Reduction

Abstract: Let $k$ and $n$ be positive integers. Define $R(n,k)$ to be the minimum positive value of $$ | e_i \sqrt{s_1} + e_2 \sqrt{s_2} + ... + e_k \sqrt{s_k} -t | $$ where $ s_1, s_2, ..., s_k$ are positive integers no larger than $n$, $t$ is an integer and $e_i\in \{1,0, -1\}$ for all $1\leq i\leq k$. It is important in computational geometry to determine a good lower and upper bound of $ R(n,k)$. In this paper we show that this problem is closely related to the shortest vector problem in certain integral lattices and present an algorithm to find lower bounds based on lattice reduction algorithms. Although we can only prove an exponential time upper bound for the algorithm, it is efficient for large $k$ when an exhaustive search for the minimum value is clearly infeasible. It produces lower bounds much better than the root separation technique does. Based on numerical data, we formulate a conjecture on the length of the shortest nonzero vector in the lattice, whose validation implies that our algorithm runs in polynomial time and the problem of comparing two sums of square roots of small integers can be solved in polynomial time. As a side result, we obtain constructive upper bounds for $R(n,k)$ when $ n$ is much smaller than $2^{2k}$.


Confluence Results for a Quantum Lambda Calculus with Measurements

Abstract: A strong confluence result for Q*, a quantum lambda-calculus with measurements, is proved. More precisely, confluence is shown to hold both for finite and infinite computations. The technique used in the confluence proof is syntactical but innovative. This makes Q* different from similar quantum lambda calculi, which are either measurement-free or provided with a reduction strategy.


Weak Evolvability Equals Strong Evolvability

Abstract: An updated version will be uploaded later.


Generic Unpacking of Self-modifying, Aggressive, Packed Binary Programs

Abstract: Nowadays most of the malware applications are either packed or protected. This techniques are applied especially to evade signature based detectors and also to complicate the job of reverse engineers or security analysts. The time one must spend on unpacking or decrypting malware layers is often very long and in fact remains the most complicated task in the overall process of malware analysis. In this report author proposes MmmBop as a relatively new concept of using dynamic binary instrumentation techniques for unpacking and bypassing detection by self-modifying and highly aggressive packed binary code. MmmBop is able to deal with most of the known and unknown packing algorithms and it is also suitable to successfully bypass most of currently used anti-reversing tricks. This framework does not depend on any other 3rd party software and it is developed entirely in user mode (ring3). MmmBop supports the IA-32 architecture and it is targeted for Microsoft Windows XP, some of the further deliberations will be referring directly to this operating system.


Mod\'elisation des facteurs influen\c{c}ant la performance de la cha\^ine logistique

Abstract: Improvement of industrial performance such as cost, lead-time, adaptability, variety and traceability is the major finality of companies. At this need corresponds the necessity to collaborate and to strengthen their coordination mechanisms. Information exchange becomes then a strategic question: what is the nature of the information that can be shared with customers and suppliers? Which impact on the performance of a company is expectable? What about the performance of the whole supply chain? It is essential for a company to identify the information whose exchange contributes to its performance and to control its information flows. This study aims to release from the literature the main tendencies of collaboration practices and information exchanges leading to the performance and to propose a model of hypothesis gathering these practices.


About raising and handling exceptions

Abstract: This paper presents a unified framework for dealing with a deduction system and a denotational semantics of exceptions. It is based on the fact that handling exceptions can be seen as a kind of generalized case distinction. This point of view on exceptions has been introduced in 2004, it is based on the notion of diagrammatic logic, which assumes some familiarity with category theory. Extensive sums of types can be used for dealing with case distinctions. The aim of this new paper is to focus on the role of generalized extensivity property for dealing with exceptions. Moreover, the presentation of this paper makes only a restricted use of category theory.


Iterative Methods for Systems' Solving - a C# approach

Abstract: This work wishes to support various mathematical issues concerning the iterative methods with the help of new programming languages. We consider a way to show how problems in math have an answer by using different academic resources and different thoughts. Here we treat methods like Gauss-Seidel's, Cramer's and Gauss-Jordan's.


Considerations on Construction Ontologies

Abstract: The paper proposes an analysis on some existent ontologies, in order to point out ways to resolve semantic heterogeneity in information systems. Authors are highlighting the tasks in a Knowledge Acquisiton System and identifying aspects related to the addition of new information to an intelligent system. A solution is proposed, as a combination of ontology reasoning services and natural languages generation. A multi-agent system will be conceived with an extractor agent, a reasoner agent and a competence management agent.


XML Technologies in Computer Assisted Learning and Testing Systems

Abstract: The learning and assessment activities have undergone major changes due to the development of modern technologies. The computer-assisted learning and testing has proven a number of advantages in the development of modern educational system. The paper suggests a solution for the computer-assisted testing, which uses XML technologies, a solution that could make the basis for developing a learning computer-assisted system.


Techniques for Securing Data Exchange between a Database Server and a Client Program

Abstract: The goal of the presented work is to illustrate a method by which the data exchange between a standalone computer software and a shared database server can be protected of unauthorized interceptation of the traffic in Internet network, a transport network for data managed by those two systems, interceptation by which an attacker could gain illegetimate access to the database, threatening this way the data integrity and compromising the database.


Designing a Framework to Develop WEB Graphical Interfaces for ORACLE Databases - Web Dialog

Abstract: The present article aims to describe a project consisting in designing a framework of applications used to create graphical interfaces with an Oracle distributed database. The development of the project supposed the use of the latest technologies: database Oracle server, Tomcat web server, JDBC (Java library used for accessing a database), JSP and Tag Library (for the development of graphical interfaces).


Indexing Research Papers in Open Access Databases

Abstract: This paper synthesizes the actions performed in order to transform a classic scientific research journal - 'Annals. Computer Science Series' - available only in printed form until 2008, into a modern e-journal with free access to the full text of the articles. For achieving this goal, the research papers have been included in various article databases, portals and library catalogs which offered a high visibility to the journal.


The Effectiveness of Computer Assisted Classes for English as a Second Language

Abstract: The present study aims to evaluate the efficiency of the computer assisted English classes and to emphasize the necessity of developing sound methodological strategies adjusted to the new technology. It also present the benefits of using the computer in the pre-school and elementary school classes, highlighted by a report on the comparative observation of four groups of children studying English in a computer assisted environment.


Straight-line instruction sequence completeness for total calculation on cancellation meadows

Abstract: A combination of program algebra with the theory of meadows is designed leading to a theory of computation in algebraic structures which use in addition to a zero test and copying instructions the instruction set $\{x \Leftarrow 0, x \Leftarrow 1, x\Leftarrow -x, x\Leftarrow x^{-1}, x\Leftarrow x+y, x\Leftarrow x\cdot y\}$. It is proven that total functions on cancellation meadows can be computed by straight-line programs using at most 5 auxiliary variables. A similar result is obtained for signed meadows.


Athos - The C# GUI Generator

Abstract: This application comes to help software architects and developers during the long process between user's stories, designing the application's structure and actually coding it.


A Logic Programming Approach to Activity Recognition

Abstract: We have been developing a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities detected on video frames. The output of our system is a set of recognised long-term activities, which are pre-defined temporal combinations of short-term activities. The constraints on the short-term activities that, if satisfied, lead to the recognition of a long-term activity, are expressed using a dialect of the Event Calculus. We illustrate the expressiveness of the dialect by showing the representation of several typical complex activities. Furthermore, we present a detailed evaluation of the system through experimentation on a benchmark dataset of surveillance videos.


CoPhIR: a Test Collection for Content-Based Image Retrieval

Abstract: The scalability, as well as the effectiveness, of the different Content-based Image Retrieval (CBIR) approaches proposed in literature, is today an important research issue. Given the wealth of images on the Web, CBIR systems must in fact leap towards Web-scale datasets. In this paper, we report on our experience in building a test collection of 100 million images, with the corresponding descriptive features, to be used in experimenting new scalable techniques for similarity searching, and comparing their results. In the context of the SAPIR (Search on Audio-visual content using Peer-to-peer Information Retrieval) European project, we had to experiment our distributed similarity searching technology on a realistic data set. Therefore, since no large-scale collection was available for research purposes, we had to tackle the non-trivial process of image crawling and descriptive feature extraction (we used five MPEG-7 features) using the European EGEE computer GRID. The result of this effort is CoPhIR, the first CBIR test collection of such scale. CoPhIR is now open to the research community for experiments and comparisons, and access to the collection was already granted to more than 50 research groups worldwide.


Mining Generalized Patterns from Large Databases using Ontologies

Abstract: Formal Concept Analysis (FCA) is a mathematical theory based on the formalization of the notions of concept and concept hierarchies. It has been successfully applied to several Computer Science fields such as data mining,software engineering, and knowledge engineering, and in many domains like medicine, psychology, linguistics and ecology. For instance, it has been exploited for the design, mapping and refinement of ontologies. In this paper, we show how FCA can benefit from a given domain ontology by analyzing the impact of a taxonomy (on objects and/or attributes) on the resulting concept lattice. We willmainly concentrate on the usage of a taxonomy to extract generalized patterns (i.e., knowledge generated from data when elements of a given domain ontology are used) in the form of concepts and rules, and improve navigation through these patterns. To that end, we analyze three generalization cases and show their impact on the size of the generalized pattern set. Different scenarios of simultaneous generalizations on both objects and attributes are also discussed


Reengineering PDF-Based Documents Targeting Complex Software Specifications

Abstract: This article aims at reengineering of PDF-based complex documents, where specifications of the Object Management Group (OMG) are our initial targets. Our motivation is that such specifications are dense and intricate to use, and tend to have complicated structures. Our objective is therefore to create an approach that allows us to reengineer PDF-based documents, and to illustrate how to make more usable versions of electronic documents (such as specifications, technical books, etc) so that end users to have a better experience with them. The first step was to extract the logical structure of the document in a meaningful XML format for subsequent processing. Our initial assumption was that, many key concepts of a document are expressed in this structure. In the next phase, we created a multilayer hypertext version of the document to facilitate browsing and navigating. Although we initially focused on OMG software specifications, we chose a general approach for different phases of our work including format conversions, logical structure extraction, text extraction, multilayer hypertext generation, and concept exploration. As a consequence, we can process other complex documents to achieve our goals.


A fast algorithm for computing minimal-norm solutions to underdetermined systems of linear equations

Abstract: We introduce a randomized algorithm for computing the minimal-norm solution to an underdetermined system of linear equations. Given an arbitrary full-rank m x n matrix A with m<n, any m x 1 vector b, and any positive real number epsilon less than 1, the procedure computes an n x 1 vector x approximating to relative precision epsilon or better the n x 1 vector p of minimal Euclidean norm satisfying Ap=b. The algorithm typically requires O(mn log(sqrt(n)/epsilon) + m**3) floating-point operations, generally less than the O(m**2 n) required by the classical schemes based on QR-decompositions or bidiagonalization. We present several numerical examples illustrating the performance of the algorithm.


Optimizing XML Compression

Abstract: The eXtensible Markup Language (XML) provides a powerful and flexible means of encoding and exchanging data. As it turns out, its main advantage as an encoding format (namely, its requirement that all open and close markup tags are present and properly balanced) yield also one of its main disadvantages: verbosity. XML-conscious compression techniques seek to overcome this drawback. Many of these techniques first separate XML structure from the document content, and then compress each independently. Further compression gains can be realized by identifying and compressing together document content that is highly similar, thereby amortizing the storage costs of auxiliary information required by the chosen compression algorithm. Additionally, the proper choice of compression algorithm is an important factor not only for the achievable compression gain, but also for access performance. Hence, choosing a compression configuration that optimizes compression gain requires one to determine (1) a partitioning strategy for document content, and (2) the best available compression algorithm to apply to each set within this partition. In this paper, we show that finding an optimal compression configuration with respect to compression gain is an NP-hard optimization problem. This problem remains intractable even if one considers a single compression algorithm for all content. We also describe an approximation algorithm for selecting a partitioning strategy for document content based on the branch-and-bound paradigm.


Variational structure of the optimal artificial diffusion method for the advection-diffusion equation

Abstract: In this research note we provide a variational basis for the optimal artificial diffusion method, which has been a cornerstone in developing many stabilized methods. The optimal artificial diffusion method produces exact nodal solutions when applied to one-dimensional problems with constant coefficients and forcing function. We first present a variational principle for a multi-dimensional advective-diffusive system, and then derive a new stable weak formulation. When applied to one-dimensional problems with constant coefficients and forcing function, this resulting weak formulation will be equivalent to the optimal artificial diffusion method. We present representative numerical results to corroborate our theoretical findings.


Representations of Stream Processors Using Nested Fixed Points

Abstract: We define representations of continuous functions on infinite streams of discrete values, both in the case of discrete-valued functions, and in the case of stream-valued functions. We define also an operation on the representations of two continuous functions between streams that yields a representation of their composite. In the case of discrete-valued functions, the representatives are well-founded (finite-path) trees of a certain kind. The underlying idea can be traced back to Brouwer's justification of bar-induction, or to Kreisel and Troelstra's elimination of choice-sequences. In the case of stream-valued functions, the representatives are non-wellfounded trees pieced together in a coinductive fashion from well-founded trees. The definition requires an alternating fixpoint construction of some ubiquity.


A Survey on Cross-Site Scripting Attacks

Abstract: Web applications are becoming truly pervasive in all kinds of business models and organizations. Today, most critical systems such as those related to health care, banking, or even emergency response, are relying on these applications. They must therefore include, in addition to the expected value offered to their users, reliable mechanisms to ensure their security. In this paper, we focus on the specific problem of cross-site scripting attacks against web applications. We present a study of this kind of attacks, and survey current approaches for their prevention. Applicability and limitations of each proposal are also discussed.


Informatics Issues Used in the Production Dashboard

Abstract: The aim of this paper is to present some computer aspects regarding the implementation and the employing of a dashboard in relation to the production activity. The paper begins with the theoretical presentation of the managerial perspective regarding the necessity of using the dashboard. The main functions of the dashboard in the production activity and the way it is employed are presented in the second part of the paper.


Derivation of UML Based Performance Models for Design Assessment in a Reuse Based Software Development Approach

Abstract: Reuse-based software development provides an opportunity for better quality and increased productivity in the software products. One of the most critical aspects of the quality of a software system is its performance. The systematic application of software performance engineering techniques throughout the development process can help to identify design alternatives that preserve desirable qualities such as extensibility and reusability while meeting performance objectives. In the present scenario, most of the performance failures are due to a lack of consideration of performance issues early in the development process, especially in the design phase. These performance failures results in damaged customer relations, lost productivity for users, cost overruns due to tuning or redesign, and missed market windows. In this paper, we propose UML based Performance Models for design assessment in a reuse based software development scenario.


Computer Based Interpretation of the Students' Evaluation of the Teaching Staff

Abstract: The goal of this paper is to offer a full support for universities and quality assessment committees in retrieving the feedback from their students regarding to their teaching staff. The computer based application presented before ([Cri07]) collects data from the students. Another part of the application, presented in this paper, processes this data and presents the statistical results concerning each teacher.


Flexible frontiers for text division into rows

Abstract: This paper presents an original solution for flexible hand-written text division into rows. Unlike the standard procedure, the proposed method avoids the isolated characters extensions amputation and reduces the recognition error rate in the final stage.


Aspects Regarding Operations with Fuzzy Processes

Abstract: This paper introduces the notion of fuzzy process as a formalism for the idea of fuzzy contact between a device and its environment. The notions of absolute correctness and relative correctness are defined. In order to work with concurrency it has been built an approach to manipulate the interactive processes as a single process and the resulted behavior has been observed.


On Some Manipulations with Fuzzy Processes

Abstract: The paper starts from the observation on the complexity of the manipulation of fuzzy processes that increases very rapidly with the extents of the processes representation. Therefore, a productive approach is to divide the problem into smaller parts, treated separately and then the results combined. Some algebraic results obtained by the authors are presented.


On the Convex Feasibility Problem

Abstract: The convergence of the projection algorithm for solving the convex feasibility problem for a family of closed convex sets, is in connection with the regularity properties of the family. In the paper [18] are pointed out four cases of such a family depending of the two characteristics: the emptiness and boudedness of the intersection of the family. The case four (the interior of the intersection is empty and the intersection itself is bounded) is unsolved. In this paper we give a (partial) answer for the case four: in the case of two closed convex sets in R3 the regularity property holds.


Divide and Conquer: Partitioning Online Social Networks

Abstract: Online Social Networks (OSNs) have exploded in terms of scale and scope over the last few years. The unprecedented growth of these networks present challenges in terms of system design and maintenance. One way to cope with this is by partitioning such large networks and assigning these partitions to different machines. However, social networks possess unique properties that make the partitioning problem non-trivial. The main contribution of this paper is to understand different properties of social networks and how these properties can guide the choice of a partitioning algorithm. Using large scale measurements representing real OSNs, we first characterize different properties of social networks, and then we evaluate qualitatively different partitioning methods that cover the design space. We expose different trade-offs involved and understand them in light of properties of social networks. We show that a judicious choice of a partitioning scheme can help improve performance.


Improved Approximation Algorithms for Segment Minimization in Intensity Modulated Radiation Therapy

Abstract: he segment minimization problem consists of finding the smallest set of integer matrices that sum to a given intensity matrix, such that each summand has only one non-zero value, and the non-zeroes in each row are consecutive. This has direct applications in intensity-modulated radiation therapy, an effective form of cancer treatment. We develop three approximation algorithms for matrices with arbitrarily many rows. Our first two algorithms improve the approximation factor from the previous best of $1+\log_2 h $ to (roughly) $3/2 \cdot (1+\log_3 h)$ and $11/6\cdot(1+\log_4{h})$, respectively, where $h$ is the largest entry in the intensity matrix. We illustrate the limitations of the specific approach used to obtain these two algorithms by proving a lower bound of $\frac{(2b-2)}{b}\cdot\log_b{h} + \frac{1}{b}$ on the approximation guarantee. Our third algorithm improves the approximation factor from $2 \cdot (\log D+1)$ to $24/13 \cdot (\log D+1)$, where $D$ is (roughly) the largest difference between consecutive elements of a row of the intensity matrix. Finally, experimentation with these algorithms shows that they perform well with respect to the optimum and outperform other approximation algorithms on 77% of the 122 test cases we consider, which include both real world and synthetic data.


Towards Automated Deduction in Blackmail Case Analysis with Forensic Lucid

Abstract: This work-in-progress focuses on the refinement of application of the intensional logic to cyberforensic analysis and its benefits are compared with the finite-state automata approach. This work extends the use of the scientific intensional programming paradigm onto modeling and implementation of a cyberforensics investigation process with the backtrace of event reconstruction, modeling the evidence as multidimensional hierarchical contexts, and proving or disproving the claims with it in the intensional manner of evaluation. This is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in the related works. As a base implementation language model we use in this approach is a new dialect of the Lucid programming language, that we call Forensic Lucid and in this paper we focus on defining hierarchical contexts based on the intensional logic for the evaluation of cyberforensic expressions.


A Minimum Description Length Approach to Multitask Feature Selection

Abstract: Many regression problems involve not one but several response variables (y's). Often the responses are suspected to share a common underlying structure, in which case it may be advantageous to share information across them; this is known as multitask learning. As a special case, we can use multiple responses to better identify shared predictive features -- a project we might call multitask feature selection. This thesis is organized as follows. Section 1 introduces feature selection for regression, focusing on ell_0 regularization methods and their interpretation within a Minimum Description Length (MDL) framework. Section 2 proposes a novel extension of MDL feature selection to the multitask setting. The approach, called the "Multiple Inclusion Criterion" (MIC), is designed to borrow information across regression tasks by more easily selecting features that are associated with multiple responses. We show in experiments on synthetic and real biological data sets that MIC can reduce prediction error in settings where features are at least partially shared across responses. Section 3 surveys hypothesis testing by regression with a single response, focusing on the parallel between the standard Bonferroni correction and an MDL approach. Mirroring the ideas in Section 2, Section 4 proposes a novel MIC approach to hypothesis testing with multiple responses and shows that on synthetic data with significant sharing of features across responses, MIC sometimes outperforms standard FDR-controlling methods in terms of finding true positives for a given level of false positives. Section 5 concludes.


Managing Distributed MARF with SNMP

Abstract: The scope of this project's work focuses on the research and prototyping of the extension of the Distributed MARF such that its services can be managed through the most popular management protocol familiarly, SNMP. The rationale behind SNMP vs. MARF's proprietary management protocols, is that can be integrated with the use of common network service and device management, so the administrators can manage MARF nodes via a already familiar protocol, as well as monitor their performance, gather statistics, set desired configuration, etc. perhaps using the same management tools they've been using for other network devices and application servers.


The cost of being co-Buchi is nonlinear

Abstract: It is well known, and easy to see, that not each nondeterministic Buchi automaton on infinite words can be simulated by a nondeterministic co-Buchi automaton. We show that in the cases when such a simulation is possible, the number of states needed for it can grow nonlinearly. More precisely, we show a sequence of - as we believe, simple and elegant - languages which witness the existence of a nondeterministic Buchi automaton with n states, which can be simulated by a nondeterministic co-Buchi automaton, but cannot be simulated by any nondeterministic co-Buchi automaton with less than c*n^{7/6} states for some constant c. This improves on the best previously known lower bound of 3(n-1)/2.


Reverse method for labeling the information from semi-structured web pages

Abstract: We propose a new technique to infer the structure and extract the tokens of data from the semi-structured web sources which are generated using a consistent template or layout with some implicit regularities. The attributes are extracted and labeled reversely from the region of interest of targeted contents. This is in contrast with the existing techniques which always generate the trees from the root. We argue and show that our technique is simpler, more accurate and effective especially to detect the changes of the templates of targeted web pages.


Inventory competition in a multi channel distribution system: The Nash and Stackelberg game

Abstract: This paper investigates inventory management in a multi channel distribution system consisting of one manufacturer and an arbitrary number of retailers that face stochastic demand. Existence of the pure Nash equilibrium is proved and parameter restriction which implies uniqueness of it is derived. Also the Stackelberg game where the manufacturer plays a roll as a leader is discussed. Under specified parameter restrictions which guarantee profitability, sufficient condition for uniqueness of Stackelberg equilibrium is obtained. In addition comparison with simultaneous move game is made. The result shows that when whole prices are equal to production cost, manufacturer carries more inventory than simultaneous move game. Keywords: Inventory management, Substitution, Nash equilibrium, Stackelberg equilibrium.


Mitigating the ICA Attack against Rotation Based Transformation for Privacy Preserving Clustering

Abstract: The rotation based transformation (RBT) for privacy preserving data mining (PPDM) is vulnerable to the independent component analysis (ICA) attack. This paper introduces a modified multiple rotation based transformation (MRBT) technique for special mining applications mitigating the ICA attack while maintaining the advantages of the RBT.


A Survey of Tree Convex Sets Test

Abstract: Tree convex sets refer to a collection of sets such that each set in the collection is a subtree of a tree whose nodes are the elements of these sets. They extend the concept of row convex sets each of which is an interval over a total ordering of the elements of those sets. They have been applied to identify tractable Constraint Satisfaction Problems and Combinatorial Auction Problems. Recently, polynomial algorithms have been proposed to recognize tree convex sets. In this paper, we review the materials that are the key to a linear recognition algorithm.


Equations of States in Statistical Learning for a Nonparametrizable and Regular Case

Abstract: Many learning machines that have hierarchical structure or hidden variables are now being used in information science, artificial intelligence, and bioinformatics. However, several learning machines used in such fields are not regular but singular statistical models, hence their generalization performance is still left unknown. To overcome these problems, in the previous papers, we proved new equations in statistical learning, by which we can estimate the Bayes generalization loss from the Bayes training loss and the functional variance, on the condition that the true distribution is a singularity contained in a learning machine. In this paper, we prove that the same equations hold even if a true distribution is not contained in a parametric model. Also we prove that, the proposed equations in a regular case are asymptotically equivalent to the Takeuchi information criterion. Therefore, the proposed equations are always applicable without any condition on the unknown true distribution.


Solving $k$-Nearest Neighbor Problem on Multiple Graphics Processors

Abstract: The recommendation system is a software system to predict customers' unknown preferences from known preferences. In the recommendation system, customers' preferences are encoded into vectors, and finding the nearest vectors to each vector is an essential part. This vector-searching part of the problem is called a $k$-nearest neighbor problem. We give an effective algorithm to solve this problem on multiple graphics processor units (GPUs). Our algorithm consists of two parts: an $N$-body problem and a partial sort. For a algorithm of the $N$-body problem, we applied the idea of a known algorithm for the $N$-body problem in physics, although another trick is need to overcome the problem of small sized shared memory. For the partial sort, we give a novel GPU algorithm which is effective for small $k$. In our partial sort algorithm, a heap is accessed in parallel by threads with a low cost of synchronization. Both of these two parts of our algorithm utilize maximal power of coalesced memory access, so that a full bandwidth is achieved. By an experiment, we show that when the size of the problem is large, an implementation of the algorithm on two GPUs runs more than 330 times faster than a single core implementation on a latest CPU. We also show that our algorithm scales well with respect to the number of GPUs.


Multi-Linear cryptanalysis in Power Analysis Attacks MLPA

Abstract: Power analysis attacks against embedded secret key cryptosystems are widely studied since the seminal paper of Paul Kocher, Joshua Ja, and Benjamin Jun in 1998 where has been introduced the powerful Differential Power Analysis. The strength of DPA is such that it became necessary to develop sound and efficient countermeasures. Nowadays embedded cryptographic primitives usually integrate one or several of these countermeasures (e.g. masking techniques, asynchronous designs, balanced dynamic dual-rail gates designs, noise adding, power consumption smoothing, etc. ...). This document presents a simple, yet interesting, countermeasure to DPA and HO-DPA attacks, called brutal countermeasure and new power analysis attacks using multi-linear approximations (MLPA attacks) based on very recent and still unpublished results of Tavernier et al..


Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

Abstract: In this paper, we study the problem of processing continuous range queries in a hierarchical wireless sensor network. Contrasted with the traditional approach of building networks in a "flat" structure using sensor devices of the same capability, the hierarchical approach deploys devices of higher capability in a higher tier, i.e., a tier closer to the server. While query processing in flat sensor networks has been widely studied, the study on query processing in hierarchical sensor networks has been inadequate. In wireless sensor networks, the main costs that should be considered are the energy for sending data and the storage for storing queries. There is a trade-off between these two costs. Based on this, we first propose a progressive processing method that effectively processes a large number of continuous range queries in hierarchical sensor networks. The proposed method uses the query merging technique proposed by Xiang et al. as the basis and additionally considers the trade-off between the two costs. More specifically, it works toward reducing the storage cost at lower-tier nodes by merging more queries, and toward reducing the energy cost at higher-tier nodes by merging fewer queries (thereby reducing "false alarms"). We then present how to build a hierarchical sensor network that is optimal with respect to the weighted sum of the two costs. It allows for a cost-based systematic control of the trade-off based on the relative importance between the storage and energy in a given network environment and application. Experimental results show that the proposed method achieves a near-optimal control between the storage and energy and reduces the cost by 0.989~84.995 times compared with the cost achieved using the flat (i.e., non-hierarchical) setup as in the work by Xiang et al.


MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

Abstract: In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.


Microcontroller based distributed and networked control system for public cluster

Abstract: We present the architecture and application of the distributed control in public cluster, a parallel machine which is open for public access. Following the nature of public cluster, the integrated distributed control system is fully accessible through network using a user-friendly web interface. The system is intended mainly to control the power of each node in a block of parallel computers provided to certain users. This is especially important to extend the life-time of related hardwares, and to reduce the whole running and maintainance costs. The system consists of two parts : the master- and node-controllers, and both are connected each other through RS-485 interface. Each node-controller is assigned with a unique address to distinguish each of them. We also discuss briefly the implementation of the system at the LIPI Public Cluster.


Rivisiting Token/Bucket Algorithms in New Applications

Abstract: We consider a somehow peculiar Token/Bucket problem which at first sight looks confusing and difficult to solve. The winning approach to solve the problem consists in going back to the simple and traditional methods to solve computer science problems like the one taught to us by Knuth. Somehow the main trick is to be able to specify clearly what needs to be achieved, and then the solution, even if complex, appears almost by itself.


Towards a Centralized Scheduling Framework for Communication Flows in Distributed Systems

Abstract: The overall performance of a distributed system is highly dependent on the communication efficiency of the system. Although network resources (links, bandwidth) are becoming increasingly more available, the communication performance of data transfers involving large volumes of data does not necessarily improve at the same rate. This is due to the inefficient usage of the available network resources. A solution to this problem consists of data transfer scheduling techniques, which manage and allocate the network resources in an efficient manner. In this paper we present several online and offline data transfer optimization techniques, in the context of a centrally controlled distributed system.


Offline Algorithms for Several Network Design, Clustering and QoS Optimization Problems

Abstract: In this paper we address several network design, clustering and Quality of Service (QoS) optimization problems and present novel, efficient, offline algorithms which compute optimal or near-optimal solutions. The QoS optimization problems consist of reliability improvement (by computing backup shortest paths) and network link upgrades (in order to reduce the latency on several paths). The network design problems consist of determining small diameter networks, as well as very well connected and regular network topologies. The network clustering problems consider only the restricted model of static and mobile path networks, for which we were able to develop optimal algorithms.


Data Distribution Optimization using Offline Algorithms and a Peer-to-Peer Small Diameter Tree Architecture with Bounded Node Degrees

Abstract: Multicast data transfers occur in many distributed systems and applications (e.g. IPTV, Grids, content delivery networks). Because of this, efficient multicast data distribution optimization techniques are required. In the first part of this paper we present a small diameter, bounded degree, collaborative peer-to-peer multicast tree architecture, which supports dynamic node arrivals and departures making local decisions only. The architecture is fault tolerant and, at low arrival and departure rates, converges towards a theoretically optimal structure. In the second part of the paper we consider several offline data distribution optimization problems, for which we present novel and time-efficient algorithmic solutions.


Observational Equivalence and Full Abstraction in the Symmetric Interaction Combinators

Abstract: The symmetric interaction combinators are an equally expressive variant of Lafont's interaction combinators. They are a graph-rewriting model of deterministic computation. We define two notions of observational equivalence for them, analogous to normal form and head normal form equivalence in the lambda-calculus. Then, we prove a full abstraction result for each of the two equivalences. This is obtained by interpreting nets as certain subsets of the Cantor space, called edifices, which play the same role as Boehm trees in the theory of the lambda-calculus.


Curse of Dimensionality in Pivot-based Indexes

Abstract: We offer a theoretical validation of the curse of dimensionality in the pivot-based indexing of datasets for similarity search, by proving, in the framework of statistical learning, that in high dimensions no pivot-based indexing scheme can essentially outperform the linear scan. A study of the asymptotic performance of pivot-based indexing schemes is performed on a sequence of datasets modeled as samples $X_d$ picked in i.i.d. fashion from metric spaces $\Omega_d$. We allow the size of the dataset $n=n_d$ to be such that $d$, the ``dimension'', is superlogarithmic but subpolynomial in $n$. The number of pivots is allowed to grow as $o(n/d)$. We pick the least restrictive cost model of similarity search where we count each distance calculation as a single computation and disregard the rest. We demonstrate that if the intrinsic dimension of the spaces $\Omega_d$ in the sense of concentration of measure phenomenon is $O(d)$, then the performance of similarity search pivot-based indexes is asymptotically linear in $n$.


A New Upper Bound on 2D Online Bin Packing

Abstract: The 2D Online Bin Packing is a fundamental problem in Computer Science and the determination of its asymptotic competitive ratio has attracted great research attention. In a long series of papers, the lower bound of this ratio has been improved from 1.808, 1.856 to 1.907 and its upper bound reduced from 3.25, 3.0625, 2.8596, 2.7834 to 2.66013. In this paper, we rewrite the upper bound record to 2.5545. Our idea for the improvement is as follows. In SODA 2002 \cite{SS03}, Seiden and van Stee proposed an elegant algorithm called $H \otimes B$, comprised of the {\em Harmonic algorithm} $H$ and the {\em Improved Harmonic algorithm} $B$, for the two-dimensional online bin packing problem and proved that the algorithm has an asymptotic competitive ratio of at most 2.66013. Since the best known online algorithm for one-dimensional bin packing is the {\em Super Harmonic algorithm} \cite{S02}, a natural question to ask is: could a better upper bound be achieved by using the Super Harmonic algorithm instead of the Improved Harmonic algorithm? However, as mentioned in \cite{SS03}, the previous analysis framework does not work. In this paper, we give a positive answer for the above question. A new upper bound of 2.5545 is obtained for 2-dimensional online bin packing. The main idea is to develop new weighting functions for the Super Harmonic algorithm and propose new techniques to bound the total weight in a rectangular bin.


Computing the tree number of a cut-outerplanar graph

Abstract: While the notion of arboricity of a graph is well-known in graph theory, very few results are dedicated to the minimal number of trees covering the edges of a graph, called the tree number of a graph.


A Mixed-Fractal Model for Network Traffic

Abstract: In this short paper, we propose a new multi-fractal flow model, aiming to provide a possible explanation for the crossover phenomena that appear in the estimation of Hurst exponent for network traffic. It is shown that crossover occurs if the network flow consists of several components with different Hurst components. Our results indicate that this model might be useful in network traffic modeling and simulation.


Methodologies for Analyzing Equilibria in Wireless Games

Abstract: Under certain assumptions in terms of information and models, equilibria correspond to possible stable outcomes in conflicting or cooperative scenarios where rational entities interact. For wireless engineers, it is of paramount importance to be able to predict and even ensure such states at which the network will effectively operate. In this article, we provide non-exhaustive methodologies for characterizing equilibria in wireless games in terms of existence, uniqueness, selection, and efficiency.


An optimal linear separator for the Sonar Signals Classification task

Abstract: The problem of classifying sonar signals from rocks and mines first studied by Gorman and Sejnowski has become a benchmark against which many learning algorithms have been tested. We show that both the training set and the test set of this benchmark are linearly separable, although with different hyperplanes. Moreover, the complete set of learning and test patterns together, is also linearly separable. We give the weights that separate these sets, which may be used to compare results found by other algorithms.


A stabilized finite element formulation of non-smooth contact

Abstract: The computational modeling of many engineering problems using the Finite Element method involves the modeling of two or more bodies that meet through an interface. The interface can be physical, as in multi-physics and contact problems, or purely numerical, as in the coupling of non-conforming meshes. The most critical part of the modeling process is to ensure geometric compatibility and a complete transfer of surface tractions between the different components at the connecting interfaces. Popular contact modeling techniques rely on geometric projections to detect and resolve overlapping or mass interpenetration between two or more contacting bodies. Such approaches have been shown to have two major drawbacks: they are not suitable for contact at highly nonlinear surfaces and sharp corners where smooth normal projections are not feasible, and they fail to guarantee a complete and accurate transfer of pressure across the interface. This dissertation presents a novel formulation for the modeling of contact problems that possesses the ability to resolve complicated contact scenarios effectively, while being simpler to implement and more widely applicable than currently available methods. We show that the formulation boils down to a node-to-surface gap function that works effectively for non-smooth contact. The numerical implementation using the midpoint rule shows the need to guarantee the conservation of the total energy during impact, for which a Lagrange multiplier method is used. We propose a local enrichment of the interface and a simple stabilization procedure based on the discontinuous Galerkin method to guarantee an accurate transfer of the pressure field. The result is a robust interface formulation for contact problems and the coupling of non-conforming meshes.


An Axiomatic Theory of Fairness in Network Resource Allocation

Abstract: We present a set of five axioms for fairness measures in resource allocation. A family of fairness measures satisfying the axioms is constructed. Well-known notions such as alpha-fairness, Jain's index, and entropy are shown to be special cases. Properties of fairness measures satisfying the axioms are proven, including Schur-concavity. Among the engineering implications is a generalized Jain's index that tunes the resolution of the fairness measure, a new understanding of alpha-fair utility functions, and an interpretation of "larger alpha is more fair". We also construct an alternative set of four axioms to capture efficiency objectives and feasibility constraints.


On lines and Joints

Abstract: Let $L$ be a set of $n$ lines in $\reals^d$, for $d\ge 3$. A {\em joint} of $L$ is a point incident to at least $d$ lines of $L$, not all in a common hyperplane. Using a very simple algebraic proof technique, we show that the maximum possible number of joints of $L$ is $\Theta(n^{d/(d-1)})$. For $d=3$, this is a considerable simplification of the orignal algebraic proof of Guth and Katz~\cite{GK}, and of the follow-up simpler proof of Elekes et al. \cite{EKS}.


Optimal Byzantine Resilient Convergence in Asynchronous Robot Networks

Abstract: We propose the first deterministic algorithm that tolerates up to $f$ byzantine faults in $3f+1$-sized networks and performs in the asynchronous CORDA model. Our solution matches the previously established lower bound for the semi-synchronous ATOM model on the number of tolerated Byzantine robots. Our algorithm works under bounded scheduling assumptions for oblivious robots moving in a uni-dimensional space.


Quality assessment of the MPEG-4 scalable video CODEC

Abstract: In this paper, the performance of the emerging MPEG-4 SVC CODEC is evaluated. In the first part, a brief introduction on the subject of quality assessment and the development of the MPEG-4 SVC CODEC is given. After that, the used test methodologies are described in detail, followed by an explanation of the actual test scenarios. The main part of this work concentrates on the performance analysis of the MPEG-4 SVC CODEC - both objective and subjective.