How really effective are Multimodal Hints in enhancing Visual Target Spotting? Some evidence from a usability study

Abstract: The main aim of the work presented here is to contribute to computer science advances in the multimodal usability area, in-as-much as it addresses one of the major issues relating to the generation of effective oral system messages: how to design messages which effectively help users to locate specific graphical objects in information visualisations? An experimental study was carried out to determine whether oral messages including coarse information on the locations of graphical objects on the current display may facilitate target detection tasks sufficiently for making it worth while to integrate such messages in GUIs. The display spatial layout varied in order to test the influence of visual presentation structure on the contribution of these messages to facilitating visual search on crowded displays. Finally, three levels of task difficulty were defined, based mainly on the target visual complexity and the number of distractors in the scene. The findings suggest that spatial information messages improve participants' visual search performances significantly; they are more appropriate to radial structures than to matrix, random and elleptic structures; and, they are particularly useful for performing difficult visual search tasks.


Ambient Multimodality: an Asset for Developing Universal Access to the Information Society

Abstract: The paper tries to point out the benefits that can be derived from research advances in the implementation of concepts such as ambient intelligence (AmI) and ubiquitous or pervasive computing for promoting Universal Access (UA) to the Information Society, that is, for contributing to enable everybody, especially Physically Disabled (PD) people, to have easy access to all computing resources and information services that the coming worldwide Information Society will soon make available to the general public. Following definitions of basic concepts relating to multimodal interaction, the significant contribution of multimodality to developing UA is briefly argued. Then, a short state of the art in AmI research is presented. In the last section we bring out the potential contribution of advances in AmI research and technology to the improvement of computer access for PD people. This claim is supported by the following observations: (i) most projects aiming at implementing AmI focus on the design of new interaction modalities and flexible multimodal user interfaces which may facilitate PD users' computer access ; (ii) targeted applications will support users in a wide range of daily activities which will be performed simultaneously with supporting computing tasks; therefore, users will be placed in contexts where they will be confronted with similar difficulties to those encountered by PD users; (iii) AmI applications being intended for the general public, a wide range of new interaction devices and flexible processing software will be available, making it possible to provide PD users with human-computer facilities tailored to their specific needs at reasonable expense..


HORPO with Computability Closure : A Reconstruction

Abstract: This paper provides a new, decidable definition of the higher- order recursive path ordering in which type comparisons are made only when needed, therefore eliminating the need for the computability clo- sure, and bound variables are handled explicitly, making it possible to handle recursors for arbitrary strictly positive inductive types.


Parametric stiffness analysis of the Orthoglide

Abstract: This paper presents a parametric stiffness analysis of the Orthoglide. A compliant modeling and a symbolic expression of the stiffness matrix are conducted. This allows a simple systematic analysis of the influence of the geometric design parameters and to quickly identify the critical link parameters. Our symbolic model is used to display the stiffest areas of the workspace for a specific machining task. Our approach can be applied to any parallel manipulator for which stiffness is a critical issue.


Kinematics and Workspace Analysis of a Three-Axis Parallel Manipulator: the Orthoglide

Abstract: The paper addresses kinematic and geometrical aspects of the Orthoglide, a three-DOF parallel mechanism. This machine consists of three fixed linear joints, which are mounted orthogonally, three identical legs and a mobile platform, which moves in the Cartesian x-y-z space with fixed orientation. New solutions to solve inverse/direct kinematics are proposed and we perform a detailed workspace and singularity analysis, taking into account specific joint limit constraints.


Recursive Structure and Bandwidth of Hales-Numbered Hypercube

Abstract: The Hales numbered $n$-dimensional hypercube and the corresponding adjacency matrix exhibit interesting recursive structures in $n$. These structures lead to a very simple proof of the well-known bandwidth formula for hypercube, whose proof was thought to be surprisingly difficult. A related problem called hypercube antibandwidth, for which Harper proposed an algorithm, is also reexamined in the light of the above recursive structures, and a close form solution is found.


Relative-Error CUR Matrix Decompositions

Abstract: Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus difficult to interpret in terms of the original features of the input data. In this paper, we propose and study matrix approximations that are explicitly expressed in terms of a small number of columns and/or rows of the data matrix, and thereby more amenable to interpretation in terms of the original data. Our main algorithmic results are two randomized algorithms which take as input an $m \times n$ matrix $A$ and a rank parameter $k$. In our first algorithm, $C$ is chosen, and we let $A'=CC^+A$, where $C^+$ is the Moore-Penrose generalized inverse of $C$. In our second algorithm $C$, $U$, $R$ are chosen, and we let $A'=CUR$. ($C$ and $R$ are matrices that consist of actual columns and rows, respectively, of $A$, and $U$ is a generalized inverse of their intersection.) For each algorithm, we show that with probability at least $1-\delta$: $$ ||A-A'||_F \leq (1+\epsilon) ||A-A_k||_F, $$ where $A_k$ is the ``best'' rank-$k$ approximation provided by truncating the singular value decomposition (SVD) of $A$. The number of columns of $C$ and rows of $R$ is a low-degree polynomial in $k$, $1/\epsilon$, and $\log(1/\delta)$. Our two algorithms are the first polynomial time algorithms for such low-rank matrix approximations that come with relative-error guarantees; previously, in some cases, it was not even known whether such matrix decompositions exist. Both of our algorithms are simple, they take time of the order needed to approximately compute the top $k$ singular vectors of $A$, and they use a novel, intuitive sampling method called ``subspace sampling.''


Verified Real Number Calculations: A Library for Interval Arithmetic

Abstract: Real number calculations on elementary functions are remarkably difficult to handle in mechanical proofs. In this paper, we show how these calculations can be performed within a theorem prover or proof assistant in a convenient and highly automated as well as interactive way. First, we formally establish upper and lower bounds for elementary functions. Then, based on these bounds, we develop a rational interval arithmetic where real number calculations take place in an algebraic setting. In order to reduce the dependency effect of interval arithmetic, we integrate two techniques: interval splitting and taylor series expansions. This pragmatic approach has been developed, and formally verified, in a theorem prover. The formal development also includes a set of customizable strategies to automate proofs involving explicit calculations over real numbers. Our ultimate goal is to provide guaranteed proofs of numerical properties with minimal human theorem-prover interaction.


Formally Verified Argument Reduction with a Fused-Multiply-Add

Abstract: Cody & Waite argument reduction technique works perfectly for reasonably large arguments but as the input grows there are no bit left to approximate the constant with enough accuracy. Under mild assumptions, we show that the result computed with a fused-multiply-add provides a fully accurate result for many possible values of the input with a constant almost accurate to the full working precision. We also present an algorithm for a fully accurate second reduction step to reach double full accuracy (all the significand bits of two numbers are significant) even in the worst cases of argument reduction. Our work recalls the common algorithms and presents proofs of correctness. All the proofs are formally verified using the Coq automatic proof checker.


Parametric Stiffness Analysis of the Orthoglide

Abstract: This paper presents a parametric stiffness analysis of the Orthoglide, a 3-DOF translational Parallel Kinematic Machine. First, a compliant modeling of the Orthoglide is conducted based on an existing method. Then stiffness matrix is symbolically computed. This allows one to easily study the influence of the geometric design parameters on the matrix elements. Critical links are displayed. Cutting forces are then modeled so that static displacements of the Orthoglide tool during slot milling are symbolically computed. Influence of the geometric design parameters on the static displacements is checked as well. Other machining operations can be modeled. This parametric stiffness analysis can be applied to any parallel manipulator for which stiffness is a critical issue.


Searching for a dangerous host: randomized vs. deterministic

Abstract: A Black Hole is an harmful host in a network that destroys incoming agents without leaving any trace of such event. The problem of locating the black hole in a network through a team of agent coordinated by a common protocol is usually referred in literature as the Black Hole Search problem (or BHS for brevity) and it is a consolidated research topic in the area of distributed algorithms. The aim of this paper is to extend the results for BHS by considering more general (and hence harder) classes of dangerous host. In particular we introduce rB-hole as a probabilistic generalization of the Black Hole, in which the destruction of an incoming agent is a purely random event happening with some fixed probability (like flipping a biased coin). The main result we present is that if we tolerate an arbitrarily small error probability in the result then the rB-hole Search problem, or RBS, is not harder than the usual BHS. We establish this result in two different communication model, specifically both in presence or absence of whiteboards non-located at the homebase. The core of our methods is a general reduction tool for transforming algorithms for the black hole into algorithms for the rB-hole.


Plate-forme Magicien d'Oz pour l'\'etude de l'apport des ACAs \`a l'interaction

Abstract: In order to evaluate the contribution of Embodied (Animated) Conversational Agents (ECAs) to the effectiveness and usability of human-computer interaction, we developed a software platform meant to collect usage data. This platform, which implements the wizard of Oz paradigm, makes it possible to simulate user interfaces integrating ACAs for any Windows software application. It can also save and "replay" a rich interaction trace including user and system events, screen captures, users' speech and eye fixations. This platform has been used to assess users' subjective judgements and reactions to a multimodal online help system meant to facilitate the use of software for the general public (Flash). The online help system is embodied using a 3D talking head (developed by FT R&D) which "says" oral help messages illustrated with Flash screen copies.


Interfaces adaptatives Adaptation dynamique \`a l'utilisateur courant

Abstract: We present a survey of recent research studies of the implementation of adaptive user models in human-computer interaction. A classification of research directions on adaptive user interfaces is first proposed; it takes account of the user characteristics that are modelled, the distribution of initiative and control of the system evolution between user and system, and the role of dynamic adaptation. Then, a few representative research studies are briefly presented to illustrate this classification. In the conclusion, some major issues regarding the utility and usability of adaptive user interfaces and the design of an appropriate methodology for assessing the ergonomic quality of this new form of interaction are mentioned.


Design Strategies for the Geometric Synthesis of Orthoglide-type Mechanisms

Abstract: The paper addresses the geometric synthesis of Orthoglide-type mechanism, a family of 3-DOF parallel manipulators for rapid machining applications, which combine advantages of both serial mechanisms and parallel kinematic architectures. These manipulators possess quasi-isotropic kinematic performances and are made up of three actuated fixed prismatic joints, which are mutually orthogonal and connected to a mobile platform via three parallelogram chains. The platform moves in the Cartesian space with fixed orientation, similar to conventional XYZ-machine. Three strategies have been proposed to define the Orthoglide geometric parameters (manipulator link lengths and actuated joint limits) as functions of a cubic workspace size and dextrous properties expressed by bounds on the velocity transmission factors, manipulability or the Jacobian condition number. Low inertia and intrinsic stiffness have been set as additional design goals expressed by the minimal link length requirement. For each design strategy, analytical expressions for computing the Orthoglide parameters are proposed. It is showed that the proposed strategies yield Pareto-optimal solutions, which differ by the kinematic performances outside the prescribed Cartesian cube (but within the workspace bounded by the actuated joint limits). The proposed technique is illustrated with numerical examples for the Orthoglide prototype design.


An Exhaustive Study of the Workspaces Tolopogies of all 3R Orthogonal Manipulators with Geometric Simplifications

Abstract: This paper proposes a classification of three-revolute orthogonal manipulators that have at least one of their DH parameters equal to zero. This classification is based on the topology of their workspace. The workspace is characterized in a half-cross section by the singular curves. The workspace topology is defined by the number of cusps and nodes that appear on these singular curves. The manipulators are classified into different types with similar kinematic properties. Each type is evaluated according to interesting kinematic properties such as, whether the workspace is fully reachable with four inverse kinematic solutions or not, the existence of voids, and the feasibility of continuous trajectories in the workspace. It is found that several orthogonal manipulators have a "well-connected" workspace, that is, their workspace is fully accessible with four inverse kinematic solutions and any continuous trajectory is feasible. This result is of interest for the design of alternative manipulator geometries.


A Non Parametric Model for the Forecasting of the Venezuelan Oil Prices

Abstract: A neural net model for forecasting the prices of Venezuelan crude oil is proposed. The inputs of the neural net are selected by reference to a dynamic system model of oil prices by Mashayekhi (1995, 2001) and its performance is evaluated using two criteria: the Excess Profitability test by Anatoliev and Gerko (2005) and the characteristics of the equity curve generated by a trading strategy based on the neural net predictions. ----- Se introduce aqui un modelo no parametrico para pronosticar los precios del petroleo Venezolano cuyos insumos son seleccionados en base a un sistema dinamico que explica los precios en terminos de dichos insumos. Se describe el proceso de recoleccion y pre-procesamiento de datos y la corrida de la red y se evaluan sus pronosticos a traves de un test estadistico de predictibilidad y de las caracteristicas del Equity Curve inducido por la estrategia de compraventa bursatil generada por dichos pronosticos.


The Isoconditioning Loci of Planar Three-DOF Parallel Manipulators

Abstract: The subject of this paper is a special class of three-degree-of-freedom parallel manipulators. The singular configurations of the two Jacobian matrices are first studied. The isotropic configurations are then found based on the characteristic length of this manipulator. The isoconditioning loci for the Jacobian matrices are plotted to define a global performance index allowing the comparison of the different working modes. The index thus resulting is compared with the Cartesian workspace surface and the average of the condition number.


Kinematic analysis of the 3-RPR parallel manipulator

Abstract: The aim of this paper is the kinematic study of a 3-RPR planar parallel manipulator where the three fixed revolute joints are actuated. The direct and inverse kinematic problem as well as the singular configuration is characterized. On parallel singular configurations, the motion produce by the mobile platform can be compared to the Reuleaux straight-line mechanism.


Working and Assembly Modes of the Agile Eye

Abstract: This paper deals with the in-depth kinematic analysis of a special spherical parallel wrist, called the Agile Eye. The Agile Eye is a three-legged spherical parallel robot with revolute joints in which all pairs of adjacent joint axes are orthogonal. Its most peculiar feature, demonstrated in this paper for the first time, is that its (orientation) workspace is unlimited and flawed only by six singularity curves (rather than surfaces). Furthermore, these curves correspond to self-motions of the mobile platform. This paper also demonstrates that, unlike for any other such complex spatial robots, the four solutions to the direct kinematics of the Agile Eye (assembly modes) have a simple geometric relationship with the eight solutions to the inverse kinematics (working modes).


A course on Combinatorial Algorithms

Abstract: The paper presents a course on Combinatorial Algorithms that is based on the drafts of the author that he used while teaching the course in the Department of Informatics and Applied Mathematics of Yerevan State University, Armenia from February 2007 to June 2007.


Graph Isomorphism is PSPACE-complete

Abstract: Combining the the results of A.R. Meyer and L.J. Stockmeyer "The Equivalence Problem for Regular Expressions with Squaring Requires Exponential Space", and K.S. Booth "Isomorphism testing for graphs, semigroups, and finite automata are polynomiamlly equivalent problems" shows that graph isomorphism is PSPACE-complete.


Aides en ligne \`a l'utilisation de logiciels grand public : probl\`emes sp\'ecifiques de conception et solutions potentielles

Abstract: The observation that novice users seldom consult online help was made over twenty years ago. This observation still holds nowadays, although online help to the use of software for the general public has greatly improved in usability during this period. The paper first demonstrates the necessity of online help to the use of new software whatever the transparency of the user interface, as whether online help systems are meant to compensate for interface design weaknesses or actually do provide necessary assistance to the discovery of a new software package functionalities is still an unsolved issue. The discussion relies on results of empirical and experimental studies and theoretical arguments. In the second part, we analyse the specific difficulties raised by the design of effective online help systems for current software intended for the general public so as to try and understand the reluctance of novice users to use online help. In the last part, we present and discuss the possible contributions of various approaches to solving this issue. Recent interaction paradigms and techniques are considered, such as, static and dynamic personalisation, contextual online help and new forms of multimodality.


On the complexity of nonnegative matrix factorization

Abstract: Nonnegative matrix factorization (NMF) has become a prominent technique for the analysis of image databases, text databases and other information retrieval and clustering applications. In this report, we define an exact version of NMF. Then we establish several results about exact NMF: (1) that it is equivalent to a problem in polyhedral combinatorics; (2) that it is NP-hard; and (3) that a polynomial-time local search heuristic exists.


Raising a Hardness Result

Abstract: This article presents a technique for proving problems hard for classes of the polynomial hierarchy or for PSPACE. The rationale of this technique is that some problem restrictions are able to simulate existential or universal quantifiers. If this is the case, reductions from Quantified Boolean Formulae (QBF) to these restrictions can be transformed into reductions from QBFs having one more quantifier in the front. This means that a proof of hardness of a problem at level n in the polynomial hierarchy can be split into n separate proofs, which may be simpler than a proof directly showing a reduction from a class of QBFs to the considered problem.


Optimal Per-Edge Processing Times in the Semi-Streaming Model

Abstract: We present semi-streaming algorithms for basic graph problems that have optimal per-edge processing times and therefore surpass all previous semi-streaming algorithms for these tasks. The semi-streaming model, which is appropriate when dealing with massive graphs, forbids random access to the input and restricts the memory to O(n*polylog n) bits. Particularly, the formerly best per-edge processing times for finding the connected components and a bipartition are O(alpha(n)), for determining k-vertex and k-edge connectivity O(k^2n) and O(n*log n) respectively for any constant k and for computing a minimum spanning forest O(log n). All these time bounds we reduce to O(1). Every presented algorithm determines a solution asymptotically as fast as the best corresponding algorithm up to date in the classical RAM model, which therefore cannot convert the advantage of unlimited memory and random access into superior computing times for these problems.


Pattern Matching in Trees and Strings

Abstract: We study the design of efficient algorithms for combinatorial pattern matching. More concretely, we study algorithms for tree matching, string matching, and string matching in compressed texts.


2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

Abstract: When Kurt Goedel layed the foundations of theoretical computer science in 1931, he also introduced essential concepts of the theory of Artificial Intelligence (AI). Although much of subsequent AI research has focused on heuristics, which still play a major role in many practical AI applications, in the new millennium AI theory has finally become a full-fledged formal science, with important optimality results for embodied agents living in unknown environments, obtained through a combination of theory a la Goedel and probability theory. Here we look back at important milestones of AI history, mention essential recent results, and speculate about what we may expect from the next 25 years, emphasizing the significance of the ongoing dramatic hardware speedups, and discussing Goedel-inspired, self-referential, self-improving universal problem solvers.


Sensitivity Analysis of the Orthoglide, a 3-DOF Translational Parallel Kinematic Machine

Abstract: This paper presents a sensitivity analysis of the Orthoglide, a 3-DOF translational Parallel Kinematic Machine. Two complementary methods are developed to analyze its sensitivity to its dimensional and angular variations. First, a linkage kinematic analysis method is used to have a rough idea of the influence of the dimensional variations on the location of the end-effector. Besides, this method shows that variations in the design parameters of the same type from one leg to the other have the same influence on the end-effector. However, this method does not take into account the variations in the parallelograms. Thus, a differential vector method is used to study the influence of the dimensional and angular variations in the parts of the manipulator on the position and orientation of the end-effector, and particularly the influence of the variations in the parallelograms. It turns out that the kinematic isotropic configuration of the manipulator is the least sensitive one to its dimensional and angular variations. On the contrary, the closest configurations to its kinematic singular configurations are the most sensitive ones to geometrical variations.


A system for the simulation of simultaneous moves between two noncolocational players

Abstract: We describe a new system for the simulation of simultaneous moves between noncolocational players. This has applications in the burgeoning Rock-Paper-Scissors by mail movement.


Type-IV DCT, DST, and MDCT algorithms with reduced numbers of arithmetic operations

Abstract: We present algorithms for the type-IV discrete cosine transform (DCT-IV) and discrete sine transform (DST-IV), as well as for the modified discrete cosine transform (MDCT) and its inverse, that achieve a lower count of real multiplications and additions than previously published algorithms, without sacrificing numerical accuracy. Asymptotically, the operation count is reduced from ~2NlogN to ~(17/9)NlogN for a power-of-two transform size N, and the exact count is strictly lowered for all N > 4. These results are derived by considering the DCT to be a special case of a DFT of length 8N, with certain symmetries, and then pruning redundant operations from a recent improved fast Fourier transform algorithm (based on a recursive rescaling of the conjugate-pair split radix algorithm). The improved algorithms for DST-IV and MDCT follow immediately from the improved count for the DCT-IV.


The road coloring problem

Abstract: The synchronizing word of deterministic automaton is a word in the alphabet of colors (considered as letters) of its edges that maps the automaton to a single state. A coloring of edges of a directed graph is synchronizing if the coloring turns the graph into deterministic finite automaton possessing a synchronizing word. The road coloring problem is a problem of synchronizing coloring of directed finite strongly connected graph with constant outdegree of all its vertices if the greatest common divisor of lengths of all its cycles is one. The problem was posed by Adler, Goodwyn and Weiss over 30 years ago and evoked a noticeable interest among the specialists in theory of graphs, deterministic automata and symbolic dynamics. The problem is described even in "Wikipedia" - the popular Internet Encyclopedia. The positive solution of the road coloring problem is presented.


On Ultrametric Algorithmic Information

Abstract: How best to quantify the information of an object, whether natural or artifact, is a problem of wide interest. A related problem is the computability of an object. We present practical examples of a new way to address this problem. By giving an appropriate representation to our objects, based on a hierarchical coding of information, we exemplify how it is remarkably easy to compute complex objects. Our algorithmic complexity is related to the length of the class of objects, rather than to the length of the object.


Untangling a Planar Graph

Abstract: A straight-line drawing $\delta$ of a planar graph $G$ need not be plane, but can be made so by \emph{untangling} it, that is, by moving some of the vertices of $G$. Let shift$(G,\delta)$ denote the minimum number of vertices that need to be moved to untangle $\delta$. We show that shift$(G,\delta)$ is NP-hard to compute and to approximate. Our hardness results extend to a version of \textsc{1BendPointSetEmbeddability}, a well-known graph-drawing problem. Further we define fix$(G,\delta)=n-shift(G,\delta)$ to be the maximum number of vertices of a planar $n$-vertex graph $G$ that can be fixed when untangling $\delta$. We give an algorithm that fixes at least $\sqrt{((\log n)-1)/\log \log n}$ vertices when untangling a drawing of an $n$-vertex graph $G$. If $G$ is outerplanar, the same algorithm fixes at least $\sqrt{n/2}$ vertices. On the other hand we construct, for arbitrarily large $n$, an $n$-vertex planar graph $G$ and a drawing $\delta_G$ of $G$ with fix$(G,\delta_G) \le \sqrt{n-2}+1$ and an $n$-vertex outerplanar graph $H$ and a drawing $\delta_H$ of $H$ with fix$(H,\delta_H) \le 2 \sqrt{n-1}+1$. Thus our algorithm is asymptotically worst-case optimal for outerplanar graphs.


Effective Generation of Subjectively Random Binary Sequences

Abstract: We present an algorithm for effectively generating binary sequences which would be rated by people as highly likely to have been generated by a random process, such as flipping a fair coin.


Capacity constraints and the inevitability of mediators in adword auctions

Abstract: One natural constraint in the sponsored search advertising framework arises from the fact that there is a limit on the number of available slots, especially for the popular keywords, and as a result, a significant pool of advertisers are left out. We study the emergence of diversification in the adword market triggered by such capacity constraints in the sense that new market mechanisms, as well as, new for-profit agents are likely to emerge to combat or to make profit from the opportunities created by shortages in ad-space inventory. We propose a model where the additional capacity is provided by for-profit agents (or, mediators), who compete for slots in the original auction, draw traffic, and run their own sub-auctions. The quality of the additional capacity provided by a mediator is measured by its {\it fitness} factor. We compute revenues and payoffs for all the different parties at a {\it symmetric Nash equilibrium} (SNE) when the mediator-based model is operated by a mechanism currently being used by Google and Yahoo!, and then compare these numbers with those obtained at a corresponding SNE for the same mechanism, but without any mediators involved in the auctions. Such calculations allow us to determine the value of the additional capacity. Our results show that the revenue of the auctioneer, as well as the social value (i.e. efficiency), always increase when mediators are involved; moreover even the payoffs of {\em all} the bidders will increase if the mediator has a high enough fitness. Thus, our analysis indicates that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of agents and mechanisms to coexist.


Brief encounter networks

Abstract: Many complex human and natural phenomena can usefully be represented as networks describing the relationships between individuals. While these relationships are typically intermittent, previous research has used network representations that aggregate the relationships at discrete intervals. However, such an aggregation discards important temporal information, thus inhibiting our understanding of the networks dynamic behaviour and evolution. We have recorded patterns of human urban encounter using Bluetooth technology thus retaining the temporal properties of this network. Here we show how this temporal information influences the structural properties of the network. We show that the temporal properties of human urban encounter are scale-free, leading to an overwhelming proportion of brief encounters between individuals. While previous research has shown preferential attachment to result in scale-free connectivity in aggregated network data, we found that scale-free connectivity results from the temporal properties of the network. In addition, we show that brief encounters act as weak social ties in the diffusion of non-expiring information, yet persistent encounters provide the means for sustaining time-expiring information through a network.


Solution of moving-boundary problems by the spectral element method

Abstract: This paper describes a novel numerical model aiming at solving moving-boundary problems such as free-surface flows or fluid-structure interaction. This model uses a moving-grid technique to solve the Navier--Stokes equations expressed in the arbitrary Lagrangian--Eulerian kinematics. The discretization in space is based on the spectral element method. The coupling of the fluid equations and the moving-grid equations is essentially done through the conditions on the moving boundaries. Two- and three-dimensional simulations are presented: translation and rotation of a cylinder in a fluid, and large-amplitude sloshing in a rectangular tank. The accuracy and robustness of the present numerical model is studied and discussed.


Relationship between clustering and algorithmic phase transitions in the random k-XORSAT model and its NP-complete extensions

Abstract: We study the performances of stochastic heuristic search algorithms on Uniquely Extendible Constraint Satisfaction Problems with random inputs. We show that, for any heuristic preserving the Poissonian nature of the underlying instance, the (heuristic-dependent) largest ratio $\alpha_a$ of constraints per variables for which a search algorithm is likely to find solutions is smaller than the critical ratio $\alpha_d$ above which solutions are clustered and highly correlated. In addition we show that the clustering ratio can be reached when the number k of variables per constraints goes to infinity by the so-called Generalized Unit Clause heuristic.


An Integrated Simulation System for Human Factors Study

Abstract: It has been reported that virtual reality can be a useful tool for ergonomics study. The proposed integrated simulation system aims at measuring operator's performance in an interactive way for 2D control panel design. By incorporating some sophisticated virtual reality hardware/software, the system allows natural human-system and/or human-human interaction in a simulated virtual environment; enables dynamic objective measurement of human performance; and evaluates the quality of the system design in human factors perspective based on the measurement. It can also be for operation training for some 2D control panels.


A DH-parameter based condition for 3R orthogonal manipulators to have 4 distinct inverse kinematic solutions

Abstract: Positioning 3R manipulators may have two or four inverse kinematic solutions (IKS). This paper derives a necessary and sufficient condition for 3R positioning manipulators with orthogonal joint axes to have four distinct IKS. We show that the transition between manipulators with 2 and 4 IKS is defined by the set of manipulators with a quadruple root of their inverse kinematics. The resulting condition is explicit and states that the last link length of the manipulator must be greater than a quantity that depends on three of its remaining DH-parameters. This result is of interest for the design of new manipulators.


Do oral messages help visual search?

Abstract: A preliminary experimental study is presented, that aims at eliciting the contribution of oral messages to facilitating visual search tasks on crowded visual displays. Results of quantitative and qualitative analyses suggest that appropriate verbal messages can improve both target selection time and accuracy. In particular, multimodal messages including a visual presentation of the isolated target together with absolute spatial oral information on its location in the displayed scene seem most effective. These messages also got top-ranking ratings from most subjects.


Oral messages improve visual search

Abstract: Input multimodality combining speech and hand gestures has motivated numerous usability studies. Contrastingly, issues relating to the design and ergonomic evaluation of multimodal output messages combining speech with visual modalities have not yet been addressed extensively. The experimental study presented here addresses one of these issues. Its aim is to assess the actual efficiency and usability of oral system messages including brief spatial information for helping users to locate objects on crowded displays rapidly. Target presentation mode, scene spatial structure and task difficulty were chosen as independent variables. Two conditions were defined: the visual target presentation mode (VP condition) and the multimodal target presentation mode (MP condition). Each participant carried out two blocks of visual search tasks (120 tasks per block, and one block per condition). Scene target presentation mode, scene structure and task difficulty were found to be significant factors. Multimodal target presentation proved to be more efficient than visual target presentation. In addition, participants expressed very positive judgments on multimodal target presentations which were preferred to visual presentations by a majority of participants. Besides, the contribution of spatial messages to visual search speed and accuracy was influenced by scene spatial structure and task difficulty: (i) messages improved search efficiency to a lesser extent for 2D array layouts than for some other symmetrical layouts, although the use of 2D arrays for displaying pictures is currently prevailing; (ii) message usefulness increased with task difficulty. Most of these results are statistically significant.


A Generic Approach to Coalition Formation

Abstract: We propose an abstract approach to coalition formation that focuses on simple merge and split rules transforming partitions of a group of players. We identify conditions under which every iteration of these rules yields a unique partition. The main conceptual tool is a specific notion of a stable partition. The results are parametrized by a preference relation between partitions of a group of players and naturally apply to coalitional TU-games, hedonic games and exchange economy games.


Logic Column 19: Symbolic Model Checking for Temporal-Epistemic Logics

Abstract: This article surveys some of the recent work in verification of temporal epistemic logic via symbolic model checking, focusing on OBDD-based and SAT-based approaches for epistemic logics built on discrete and real-time branching time temporal logics.


Filtering Additive Measurement Noise with Maximum Entropy in the Mean

Abstract: The purpose of this note is to show how the method of maximum entropy in the mean (MEM) may be used to improve parametric estimation when the measurements are corrupted by large level of noise. The method is developed in the context on a concrete example: that of estimation of the parameter in an exponential distribution. We compare the performance of our method with the bayesian and maximum likelihood approaches.


Competition in Wireless Systems via Bayesian Interference Games

Abstract: We study competition between wireless devices with incomplete information about their opponents. We model such interactions as Bayesian interference games. Each wireless device selects a power profile over the entire available bandwidth to maximize its data rate. Such competitive models represent situations in which several wireless devices share spectrum without any central authority or coordinated protocol. In contrast to games where devices have complete information about their opponents, we consider scenarios where the devices are unaware of the interference they cause to other devices. Such games, which are modeled as Bayesian games, can exhibit significantly different equilibria. We first consider a simple scenario of simultaneous move games, where we show that the unique Bayes-Nash equilibrium is where both devices spread their power equally across the entire bandwidth. We then extend this model to a two-tiered spectrum sharing case where users act sequentially. Here one of the devices, called the primary user, is the owner of the spectrum and it selects its power profile first. The second device (called the secondary user) then responds by choosing a power profile to maximize its Shannon capacity. In such sequential move games, we show that there exist equilibria in which the primary user obtains a higher data rate by using only a part of the bandwidth. In a repeated Bayesian interference game, we show the existence of reputation effects: an informed primary user can bluff to prevent spectrum usage by a secondary user who suffers from lack of information about the channel gains. The resulting equilibrium can be highly inefficient, suggesting that competitive spectrum sharing is highly suboptimal.


Abstract: In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision. Since the revision of quantitative as well as qualitative belief assignment given the occurrence of a new event (the conditioning constraint) can be done in many possible ways, we present here only what we consider as the most appealing Qualitative Belief Conditioning Rules (QBCR) which allow to revise the belief directly with words and linguistic labels and thus avoids the introduction of ad-hoc translations of quantitative beliefs into quantitative ones for solving the problem.


On Faster Integer Calculations using Non-Arithmetic Primitives

Abstract: The unit cost model is both convenient and largely realistic for describing integer decision algorithms over (+,*). Additional operations like division with remainder or bitwise conjunction, although equally supported by computing hardware, may lead to a considerable drop in complexity. We show a variety of concrete problems to benefit from such NON-arithmetic primitives by presenting and analyzing corresponding fast algorithms.


Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

Abstract: I postulate that human or other intelligent agents function or should function as follows. They store all sensory observations as they come - the data is holy. At any time, given some agent's current coding capabilities, part of the data is compressible by a short and hopefully fast program / description / explanation / world model. In the agent's subjective eyes, such data is more regular and more "beautiful" than other data. It is well-known that knowledge of regularity and repeatability may improve the agent's ability to plan actions leading to external rewards. In absence of such rewards, however, known beauty is boring. Then "interestingness" becomes the first derivative of subjective beauty: as the learning agent improves its compression algorithm, formerly apparently random data parts become subjectively more regular and beautiful. Such progress in compressibility is measured and maximized by the curiosity drive: create action sequences that extend the observation history and yield previously unknown / unpredictable but quickly learnable algorithmic regularity. We discuss how all of the above can be naturally implemented on computers, through an extension of passive unsupervised learning to the case of active data selection: we reward a general reinforcement learner (with access to the adaptive compressor) for actions that improve the subjective compressibility of the growing data. An unusually large breakthrough in compressibility deserves the name "discovery". The "creativity" of artists, dancers, musicians, pure mathematicians can be viewed as a by-product of this principle. Several qualitative examples support this hypothesis.


On the Complexity of Protein Local Structure Alignment Under the Discrete Fr\'echet Distance

Abstract: We show that given $m$ proteins (or protein backbones, which are modeled as 3D polygonal chains each of length O(n)) the problem of protein local structure alignment under the discrete Fr\'{e}chet distance is as hard as Independent Set. So the problem does not admit any approximation of factor $n^{1-\epsilon}$. This is the strongest negative result regarding the protein local structure alignment problem. On the other hand, if $m$ is a constant, then the problem can be solved in polygnomial time.


Designing a Virtual Manikin Animation Framework Aimed at Virtual Prototyping

Abstract: In the industry, numerous commercial packages provide tools to introduce, and analyse human behaviour in the product's environment (for maintenance, ergonomics...), thanks to Virtual Humans. We will focus on control. Thanks to algorithms newly introduced in recent research papers, we think we can provide an implementation, which even widens, and simplifies the animation capacities of virtual manikins. In order to do so, we are going to express the industrial expectations as for Virtual Humans, without considering feasibility (not to bias the issue). The second part will show that no commercial application provides the tools that perfectly meet the needs. Thus we propose a new animation framework that better answers the problem. Our contribution is the integration - driven by need ~ of available new scientific techniques to animate Virtual Humans, in a new control scheme that better answers industrial expectations.


Geometric Complexity Theory: Introduction

Abstract: These are lectures notes for the introductory graduate courses on geometric complexity theory (GCT) in the computer science department, the university of Chicago. Part I consists of the lecture notes for the course given by the first author in the spring quarter, 2007. It gives introduction to the basic structure of GCT. Part II consists of the lecture notes for the course given by the second author in the spring quarter, 2003. It gives introduction to invariant theory with a view towards GCT. No background in algebraic geometry or representation theory is assumed. These lecture notes in conjunction with the article \cite{GCTflip1}, which describes in detail the basic plan of GCT based on the principle called the flip, should provide a high level picture of GCT assuming familiarity with only basic notions of algebra, such as groups, rings, fields etc.


On P vs. NP, Geometric Complexity Theory, and the Flip I: a high level view

Abstract: Geometric complexity theory (GCT) is an approach to the $P$ vs. $NP$ and related problems through algebraic geometry and representation theory. This article gives a high-level exposition of the basic plan of GCT based on the principle, called the flip, without assuming any background in algebraic geometry or representation theory.


Geometric Complexity Theory VII: Nonstandard quantum group for the plethysm problem

Abstract: This article describes a {\em nonstandard} quantum group that may be used to derive a positive formula for the plethysm problem, just as the standard (Drinfeld-Jimbo) quantum group can be used to derive the positive Littlewood-Richardson rule for arbitrary complex semisimple Lie groups. The sequel \cite{GCT8} gives conjecturally correct algorithms to construct canonical bases of the coordinate rings of these nonstandard quantum groups and canonical bases of the dually paired nonstandard deformations of the symmetric group algebra. A positive $#P$-formula for the plethysm constant follows from the conjectural properties of these canonical bases and the duality and reciprocity conjectures herein.


Geometric Complexity Theory VIII: On canonical bases for the nonstandard quantum groups

Abstract: This article gives conjecturally correct algorithms to construct canonical bases of the irreducible polynomial representations and the matrix coordinate rings of the nonstandard quantum groups in GCT4 and GCT7, and canonical bases of the dually paired nonstandard deformations of the symmetric group algebra therein. These are generalizations of the canonical bases of the irreducible polynomial representations and the matrix coordinate ring of the standard quantum group, as constructed by Kashiwara and Lusztig, and the Kazhdan-Lusztig basis of the Hecke algebra. A positive ($#P$-) formula for the well-known plethysm constants follows from their conjectural properties and the duality and reciprocity conjectures in \cite{GCT7}.


Liquid State Machines in Adbiatic Quantum Computers for General Computation

Abstract: Major mistakes do not read


Open Access does not increase citations for research articles from The Astrophysical Journal

Abstract: We demonstrate conclusively that there is no "Open Access Advantage" for papers from the Astrophysical Journal. The two to one citation advantage enjoyed by papers deposited in the arXiv e-print server is due entirely to the nature and timing of the deposited papers. This may have implications for other disciplines.


A Greedy Randomized Adaptive Search Procedure for Technicians and Interventions Scheduling for Telecommunications

Abstract: The subject of the 5th challenge proposed by the French Society of Operations Research and Decision Analysis (ROADEF) consists in scheduling technicians and interventions for telecommunications (http://www.g-scop.inpg.fr/ChallengeROADEF2007/ or http://www.roadef.org/). We detail the algorithm we proposed for this challenge which is a Greedy Randomized Adaptative Search Procedure (GRASP). Computational results led us to the 1st position in the Junior category and to the 4th position in All category of the Challenge ROADEF 2007.


A New Distributed Topology Control Algorithm for Wireless Environments with Non-Uniform Path Loss and Multipath Propagation

Abstract: Each node in a wireless multi-hop network can adjust the power level at which it transmits and thus change the topology of the network to save energy by choosing the neighbors with which it directly communicates. Many previous algorithms for distributed topology control have assumed an ability at each node to deduce some location-based information such as the direction and the distance of its neighbor nodes with respect to itself. Such a deduction of location-based information, however, cannot be relied upon in real environments where the path loss exponents vary greatly leading to significant errors in distance estimates. Also, multipath effects may result in different signal paths with different loss characteristics, and none of these paths may be line-of-sight, making it difficult to estimate the direction of a neighboring node. In this paper, we present Step Topology Control (STC), a simple distributed topology control algorithm which reduces energy consumption while preserving the connectivity of a heterogeneous sensor network without use of any location-based information. We show that the STC algorithm achieves the same or better order of communication and computational complexity when compared to other known algorithms that also preserve connectivity without the use of location-based information. We also present a detailed simulation-based comparative analysis of the energy savings and interference reduction achieved by the algorithms. The results show that, in spite of not incurring a higher communication or computational complexity, the STC algorithm performs better than other algorithms in uniform wireless environments and especially better when path loss characteristics are non-uniform.


The Induced Bounded-Degree Subgraph Problem and Stream Control in MIMO Networks

Abstract: In this report, we consider maximal solutions to the induced bounded-degree subgraph problem and relate it to issues concerning stream control in multiple-input multiple-output (MIMO) networks. We present a new distributed algorithm that completes in logarithmic time with high probability and is guaranteed to complete in linear time. We conclude the report with simulation results that address the effectiveness of stream control and the relative impact of receiver overloading and flexible interference suppression.


Computational performance of a parallelized high-order spectral and mortar element toolbox

Abstract: In this paper, a comprehensive performance review of a MPI-based high-order spectral and mortar element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed and compared to predictions given by a heuristic model, the so-called Gamma model. A tailor-made CFD computation benchmark case is introduced and used to carry out this review, stressing the particular interest for commodity clusters. Conclusions are drawn from this extensive series of analyses and modeling leading to specific recommendations concerning such toolbox development and parallel implementation.


A Sudoku Game for People with Motor Impairments

Abstract: Computer games are motivating and beneficial in learning different educational skills. Most people use their fingers, hands, and arms when using a computer game. However, for people with motor disabilities this task can be a barrier. We present a new Sudoku game for people whose motion is impaired, called Sudoku 4ALL. With this special interface a person can control the game with the voice or with a single switch. Our research aims to cautiously search for issues that might be appropriate for computational support and to build enabling technologies that increase individuals' functional independence in a game environment.


On the Protocol Composition Logic PCL

Abstract: A recent development in formal security protocol analysis is the Protocol Composition Logic (PCL). We identify a number of problems with this logic as well as with extensions of the logic, as defined in [DDMP05,HSD+05,He05,Dat05,Der06,DDMR07]. The identified problems imply strong restrictions on the scope of PCL, and imply that some currently claimed PCL proofs cannot be proven within the logic, or make use of unsound axioms. Where possible, we propose solutions for these problems.


Multi-Sensor Fusion Method using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching

Abstract: This paper presents a multi-sensor fusion strategy for a novel road-matching method designed to support real-time navigational features within advanced driving-assistance systems. Managing multihypotheses is a useful strategy for the road-matching problem. The multi-sensor fusion and multi-modal estimation are realized using Dynamical Bayesian Network. Experimental results, using data from Antilock Braking System (ABS) sensors, a differential Global Positioning System (GPS) receiver and an accurate digital roadmap, illustrate the performances of this approach, especially in ambiguous situations.


An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation

Abstract: Monotonicity is a simple yet significant qualitative characteristic. We consider the problem of segmenting a sequence in up to K segments. We want segments to be as monotonic as possible and to alternate signs. We propose a quality metric for this problem using the l_inf norm, and we present an optimal linear time algorithm based on novel formalism. Moreover, given a precomputation in time O(n log n) consisting of a labeling of all extrema, we compute any optimal segmentation in constant time. We compare experimentally its performance to two piecewise linear segmentation heuristics (top-down and bottom-up). We show that our algorithm is faster and more accurate. Applications include pattern recognition and qualitative modeling.


Using RDF to Model the Structure and Process of Systems

Abstract: Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of $10^9$ edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.


An efficient algorithm finds noticeable trends and examples concerning the \v{C}erny conjecture

Abstract: A word w is called synchronizing (recurrent, reset, directed) word of a deterministic finite automaton (DFA) if w sends all states of the automaton on a unique state. Jan Cerny had found in 1964 a sequence of n-state complete DFA with shortest synchronizing word of length (n-1)^2. He had conjectured that it is an upper bound for the length of the shortest synchronizing word for any $n$-state complete DFA. The examples of DFA with shortest synchronizing word of length (n-1)^2 are relatively rare. To the Cerny sequence were added in all examples of Cerny, Piricka and Rosenauerova (1971), of Kari (2001) and of Roman (2004). By help of a program based on some effective algorithms, a wide class of automata of size less than 11 was checked. The order of the algorithm finding synchronizing word is quadratic for overwhelming majority of known to date automata. Some new examples of n-state DFA with minimal synchronizing word of length (n-1)^2 were discovered. The program recognized some remarkable trends concerning the length of the minimal synchronizing word. http://www.cs.biu.ac.il/~trakht/Testas.html


The P versus NP Brief

Abstract: This paper discusses why P and NP are likely to be different. It analyses the essence of the concepts and points out that P and NP might be diverse by sheer definition. It also speculates that P and NP may be unequal due to natural laws.


Efficient Algorithms for Node Disjoint Subgraph Homeomorphism Determination

Abstract: Recently, great efforts have been dedicated to researches on the management of large scale graph based data such as WWW, social networks, biological networks. In the study of graph based data management, node disjoint subgraph homeomorphism relation between graphs is more suitable than (sub)graph isomorphism in many cases, especially in those cases that node skipping and node mismatching are allowed. However, no efficient node disjoint subgraph homeomorphism determination (ndSHD) algorithms have been available. In this paper, we propose two computationally efficient ndSHD algorithms based on state spaces searching with backtracking, which employ many heuristics to prune the search spaces. Experimental results on synthetic data sets show that the proposed algorithms are efficient, require relative little time in most of the testing cases, can scale to large or dense graphs, and can accommodate to more complex fuzzy matching cases.


A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures

Abstract: As multicore systems continue to gain ground in the High Performance Computing world, linear algebra algorithms have to be reformulated or new algorithms have to be developed in order to take advantage of the architectural features on these new processors. Fine grain parallelism becomes a major requirement and introduces the necessity of loose synchronization in the parallel execution of an operation. This paper presents an algorithm for the Cholesky, LU and QR factorization where the operations can be represented as a sequence of small tasks that operate on square blocks of data. These tasks can be dynamically scheduled for execution based on the dependencies among them and on the availability of computational resources. This may result in an out of order execution of the tasks which will completely hide the presence of intrinsically sequential tasks in the factorization. Performance comparisons are presented with the LAPACK algorithms where parallelism can only be exploited at the level of the BLAS operations and vendor implementations.


A proof of strong normalisation using domain theory

Abstract: Ulrich Berger presented a powerful proof of strong normalisation using domains, in particular it simplifies significantly Tait's proof of strong normalisation of Spector's bar recursion. The main contribution of this paper is to show that, using ideas from intersection types and Martin-Lof's domain interpretation of type theory one can in turn simplify further U. Berger's argument. We build a domain model for an untyped programming language where U. Berger has an interpretation only for typed terms or alternatively has an interpretation for untyped terms but need an extra condition to deduce strong normalisation. As a main application, we show that Martin-L\"{o}f dependent type theory extended with a program for Spector double negation shift.


Unfolding Restricted Convex Caps

Abstract: This paper details an algorithm for unfolding a class of convex polyhedra, where each polyhedron in the class consists of a convex cap over a rectangular base, with several restrictions: the cap's faces are quadrilaterals, with vertices over an underlying integer lattice, and such that the cap convexity is ``radially monotone,'' a type of smoothness constraint. Extensions of Cauchy's arm lemma are used in the proof of non-overlap.


Efficient Tabling Mechanisms for Transaction Logic Programs

Abstract: In this paper we present efficient evaluation algorithms for the Horn Transaction Logic (a generalization of the regular Horn logic programs with state updates). We present two complementary methods for optimizing the implementation of Transaction Logic. The first method is based on tabling and we modified the proof theory to table calls and answers on states (practically, equivalent to dynamic programming). The call-answer table is indexed on the call and a signature of the state in which the call was made. The answer columns contain the answer unification and a signature of the state after the call was executed. The states are signed efficiently using a technique based on tries and counting. The second method is based on incremental evaluation and it applies when the data oracle contains derived relations. The deletions and insertions (executed in the transaction oracle) change the state of the database. Using the heuristic of inertia (only a part of the state changes in response to elementary updates), most of the time it is cheaper to compute only the changes in the state than to recompute the entire state from scratch. The two methods are complementary by the fact that the first method optimizes the evaluation when a call is repeated in the same state, and the second method optimizes the evaluation of a new state when a call-state pair is not found by the tabling mechanism (i.e. the first method). The proof theory of Transaction Logic with the application of tabling and incremental evaluation is sound and complete with respect to its model theory.


Enrichment of Qualitative Beliefs for Reasoning under Uncertainty

Abstract: This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels. In this work, two possible enrichments (quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication, division, etc) for dealing with them are proposed and explained. We denote them $qe$-operators, $qe$ standing for "qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative operators ($q$-operators) proposed recently in the Dezert-Smarandache Theory of plausible and paradoxist reasoning (DSmT). $q$-operators are also justified in details in this paper. The quantitative enrichment of linguistic label is a numerical supporting degree in $[0,\infty)$, while the qualitative enrichment takes its values in a finite ordered set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected more close with what human experts can easily provide when expressing linguistic labels with supporting degrees. Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done.


Experiments with small helicopter automated landings at unusual attitudes

Abstract: This paper describes a set of experiments involving small helicopters landing automated landing at unusual attitudes. By leveraging the increased agility of small air vehicles, we show that it is possible to automatically land a small helicopter on surfaces pitched at angles up to 60 degrees. Such maneuvers require considerable agility from the vehicle and its avionics system, and they pose significant technical and safety challenges. Our work builds upon previous activities in human-inspired, high-agility flight for small rotorcraft. However, it was not possible to leverage manual flight test data to extract landing maneuvers due to stringent attitude and position control requirements. Availability of low-cost, local navigation systems requiring no on-board instrumentation has proven particularly important for these experiments to be successful.


Variational local structure estimation for image super-resolution

Abstract: Super-resolution is an important but difficult problem in image/video processing. If a video sequence or some training set other than the given low-resolution image is available, this kind of extra information can greatly aid in the reconstruction of the high-resolution image. The problem is substantially more difficult with only a single low-resolution image on hand. The image reconstruction methods designed primarily for denoising is insufficient for super-resolution problem in the sense that it tends to oversmooth images with essentially no noise. We propose a new adaptive linear interpolation method based on variational method and inspired by local linear embedding (LLE). The experimental result shows that our method avoids the problem of oversmoothing and preserves image structures well.


Overlap-free words and spectra of matrices

Abstract: Overlap-free words are words over the binary alphabet $A=\{a, b\}$ that do not contain factors of the form $xvxvx$, where $x \in A$ and $v \in A^*$. We analyze the asymptotic growth of the number $u_n$ of overlap-free words of length $n$ as $ n \to \infty$. We obtain explicit formulas for the minimal and maximal rates of growth of $u_n$ in terms of spectral characteristics (the lower spectral radius and the joint spectral radius) of certain sets of matrices of dimension $20 \times 20$. Using these descriptions we provide new estimates of the rates of growth that are within 0.4% and $0.03 %$ of their exact values. The best previously known bounds were within 11% and 3% respectively. We then prove that the value of $u_n$ actually has the same rate of growth for ``almost all'' natural numbers $n$. This ``average'' growth is distinct from the maximal and minimal rates and can also be expressed in terms of a spectral quantity (the Lyapunov exponent). We use this expression to estimate it. In order to obtain our estimates, we introduce new algorithms to compute spectral characteristics of sets of matrices. These algorithms can be used in other contexts and are of independent interest.


Bandwidth selection for kernel estimation in mixed multi-dimensional spaces

Abstract: Kernel estimation techniques, such as mean shift, suffer from one major drawback: the kernel bandwidth selection. The bandwidth can be fixed for all the data set or can vary at each points. Automatic bandwidth selection becomes a real challenge in case of multidimensional heterogeneous features. This paper presents a solution to this problem. It is an extension of \cite{Comaniciu03a} which was based on the fundamental property of normal distributions regarding the bias of the normalized density gradient. The selection is done iteratively for each type of features, by looking for the stability of local bandwidth estimates across a predefined range of bandwidths. A pseudo balloon mean shift filtering and partitioning are introduced. The validity of the method is demonstrated in the context of color image segmentation based on a 5-dimensional space.


Speeding up Simplification of Polygonal Curves using Nested Approximations

Abstract: We develop a multiresolution approach to the problem of polygonal curve approximation. We show theoretically and experimentally that, if the simplification algorithm A used between any two successive levels of resolution satisfies some conditions, the multiresolution algorithm MR will have a complexity lower than the complexity of A. In particular, we show that if A has a O(N2/K) complexity (the complexity of a reduced search dynamic solution approach), where N and K are respectively the initial and the final number of segments, the complexity of MR is in O(N).We experimentally compare the outcomes of MR with those of the optimal "full search" dynamic programming solution and of classical merge and split approaches. The experimental evaluations confirm the theoretical derivations and show that the proposed approach evaluated on 2D coastal maps either shows a lower complexity or provides polygonal approximations closer to the initial curves.


Connecting Polygonizations via Stretches and Twangs

Abstract: We show that the space of polygonizations of a fixed planar point set S of n points is connected by O(n^2) ``moves'' between simple polygons. Each move is composed of a sequence of atomic moves called ``stretches'' and ``twangs''. These atomic moves walk between weakly simple ``polygonal wraps'' of S. These moves show promise to serve as a basis for generating random polygons.


Distribution of PageRank Mass Among Principle Components of the Web

Abstract: We study the PageRank mass of principal components in a bow-tie Web Graph, as a function of the damping factor c. Using a singular perturbation approach, we show that the PageRank share of IN and SCC components remains high even for very large values of the damping factor, in spite of the fact that it drops to zero when c goes to one. However, a detailed study of the OUT component reveals the presence ``dead-ends'' (small groups of pages linking only to each other) that receive an unfairly high ranking when c is close to one. We argue that this problem can be mitigated by choosing c as small as 1/2.


Toward Psycho-robots

Abstract: We try to perform geometrization of psychology by representing mental states, <<ideas>>, by points of a metric space, <<mental space>>. Evolution of ideas is described by dynamical systems in metric mental space. We apply the mental space approach for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1-4, we consider cognitive systems with increasing complexity of psychological behavior determined by structure of flows of ideas. Since our models are in fact models of the AI-type, one immediately recognizes that they can be used for creation of AI-systems, which we call psycho-robots, exhibiting important elements of human psyche. Creation of such psycho-robots may be useful improvement of domestic robots. At the moment domestic robots are merely simple working devices (e.g. vacuum cleaners or lawn mowers) . However, in future one can expect demand in systems which be able not only perform simple work tasks, but would have elements of human self-developing psyche. Such AI-psyche could play an important role both in relations between psycho-robots and their owners as well as between psycho-robots. Since the presence of a huge numbers of psycho-complexes is an essential characteristic of human psychology, it would be interesting to model them in the AI-framework.


Bregman Voronoi Diagrams: Properties, Algorithms and Applications

Abstract: The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define many variants of Voronoi diagrams depending on the class of objects, the distance functions and the embedding space. In this paper, we investigate a framework for defining and building Voronoi diagrams for a broad class of distance functions called Bregman divergences. Bregman divergences include not only the traditional (squared) Euclidean distance but also various divergence measures based on entropic functions. Accordingly, Bregman Voronoi diagrams allow to define information-theoretic Voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. We define several types of Bregman diagrams, establish correspondences between those diagrams (using the Legendre transformation), and show how to compute them efficiently. We also introduce extensions of these diagrams, e.g. k-order and k-bag Bregman Voronoi diagrams, and introduce Bregman triangulations of a set of points and their connexion with Bregman Voronoi diagrams. We show that these triangulations capture many of the properties of the celebrated Delaunay triangulation. Finally, we give some applications of Bregman Voronoi diagrams which are of interest in the context of computational geometry and machine learning.


A complete proof of The Graceful Tree Conjecture using the concept of Edge Degree

Abstract: We show the Graceful Tree Conjecture holds.


Otiy: Loactors tracking nodes

Abstract: We propose Otiy, a node-centric location service that limits the impact of location updates generate by mobile nodes in IEEE802.11-based wireless mesh networks. Existing location services use node identifiers to determine the locator (aka anchor) that is responsible for keeping track of a node's location. Such a strategy can be inefficient because: (i) identifiers give no clue on the node's mobility and (ii) locators can be far from the source/destination shortest path, which increases both location delays and bandwidth consumption. To solve these issues, Otiy introduces a new strategy that identifies nodes to play the role of locators based on the likelihood of a destination to be close to these nodes- i.e., locators are identified depending on the mobility pattern of nodes. Otiy relies on the cyclic mobility patterns of nodes and creates a slotted agenda composed of a set of predicted locations, defined according to the past and present patterns of mobility. Correspondent nodes fetch this agenda only once and use it as a reference for identifying which locators are responsible for the node at different points in time. Over a period of about one year, the weekly proportion of nodes having at least 50% of exact location predictions is in average about 75%. This proportion increases by 10% when nodes also consider their closeness to the locator from only what they know about the network.


Bootstrapping Deep Lexical Resources: Resources for Courses

Abstract: We propose a range of deep lexical acquisition methods which make use of morphological, syntactic and ontological language resources to model word similarity and bootstrap from a seed lexicon. The different methods are deployed in learning lexical items for a precision grammar, and shown to each have strengths and weaknesses over different word classes. A particular focus of this paper is the relative accessibility of different language resource types, and predicted ``bang for the buck'' associated with each in deep lexical acquisition applications.


Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels

Abstract: In this paper we propose and analyze a distributed algorithm for achieving globally optimal decisions, either estimation or detection, through a self-synchronization mechanism among linearly coupled integrators initialized with local measurements. We model the interaction among the nodes as a directed graph with weights (possibly) dependent on the radio channels and we pose special attention to the effect of the propagation delay occurring in the exchange of data among sensors, as a function of the network geometry. We derive necessary and sufficient conditions for the proposed system to reach a consensus on globally optimal decision statistics. One of the major results proved in this work is that a consensus is reached with exponential convergence speed for any bounded delay condition if and only if the directed graph is quasi-strongly connected. We provide a closed form expression for the global consensus, showing that the effect of delays is, in general, the introduction of a bias in the final decision. Finally, we exploit our closed form expression to devise a double-step consensus mechanism able to provide an unbiased estimate with minimum extra complexity, without the need to know or estimate the channel parameters.


Learning for Dynamic Bidding in Cognitive Radio Resources

Abstract: In this paper, we model the various wireless users in a cognitive radio network as a collection of selfish, autonomous agents that strategically interact in order to acquire the dynamically available spectrum opportunities. Our main focus is on developing solutions for wireless users to successfully compete with each other for the limited and time-varying spectrum opportunities, given the experienced dynamics in the wireless network. We categorize these dynamics into two types: one is the disturbance due to the environment (e.g. wireless channel conditions, source traffic characteristics, etc.) and the other is the impact caused by competing users. To analyze the interactions among users given the environment disturbance, we propose a general stochastic framework for modeling how the competition among users for spectrum opportunities evolves over time. At each stage of the dynamic resource allocation, a central spectrum moderator auctions the available resources and the users strategically bid for the required resources. The joint bid actions affect the resource allocation and hence, the rewards and future strategies of all users. Based on the observed resource allocation and corresponding rewards from previous allocations, we propose a best response learning algorithm that can be deployed by wireless users to improve their bidding policy at each stage. The simulation results show that by deploying the proposed best response learning algorithm, the wireless users can significantly improve their own performance in terms of both the packet loss rate and the incurred cost for the used resources.


Autoencoder, Principal Component Analysis and Support Vector Regression for Data Imputation

Abstract: Data collection often results in records that have missing values or variables. This investigation compares 3 different data imputation models and identifies their merits by using accuracy measures. Autoencoder Neural Networks, Principal components and Support Vector regression are used for prediction and combined with a genetic algorithm to then impute missing variables. The use of PCA improves the overall performance of the autoencoder network while the use of support vector regression shows promising potential for future investigation. Accuracies of up to 97.4 % on imputation of some of the variables were achieved.


H-Decompositions

Abstract: We show that for all graphs H of size n, the complete graph $K_{2n+1}$ has an $H$-decomposition.


On Frequency Optimisation for Power Saving in WSNs: Finding Optimum Hardware Timers Frequencies

Abstract: Wireless Sensor Networks research and demand are now in full expansion, since people came to understand these are the key to a large number of issues in industry, commerce, home automation, healthcare, agriculture and environment, monitoring, public safety etc. One of the most challenging research problems in sensor networks research is power awareness and power-saving techniques. In this master's thesis, we have studied one particular power-saving technique, i.e. frequency scaling. In particular, we analysed the close relationship between clock frequencies in a microcontroller and several types of constraints imposed on these frequencies, e.g. by other components of the microcontroller, by protocol specifications, by external factors etc. Among these constraints, we were especially interested in the ones imposed by the timer service and by the serial ports' transmission rates. Our efforts resulted in a microcontroller configuration management tool which aims at assisting application programmers in choosing microcontroller configurations, in function of the particular needs and constraints of their application.


Non-Blocking Signature of very large SOAP Messages

Abstract: Data transfer and staging services are common components in Grid-based, or more generally, in service-oriented applications. Security mechanisms play a central role in such services, especially when they are deployed in sensitive application fields like e-health. The adoption of WS-Security and related standards to SOAP-based transfer services is, however, problematic as a straightforward adoption of SOAP with MTOM introduces considerable inefficiencies in the signature generation process when large data sets are involved. This paper proposes a non-blocking, signature generation approach enabling a stream-like processing with considerable performance enhancements.


An algorithm for solving the Independent Set problem

Abstract: This paper has been withdrawn by the author, due an error in claim 1.


Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-hop Relay Networks

Abstract: We study a pricing game in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. In this game, each node (1) announces pricing functions which specify the payments it demands from its respective customers depending on the amount of traffic they route to it and (2) allocates the total traffic it receives to its service providers. The profit of a node is the difference between the revenue earned from servicing others and the cost of using others' services. We show that the socially optimal routing of such a game can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its pricing functions or routing decision. On the other hand, there may also exist inefficient equilibria. We characterize the loss of efficiency by deriving the price of anarchy at inefficient equilibria. We show that the price of anarchy is finite for oligopolies with concave marginal cost functions, while it is infinite for general topologies and cost functions.


Triangulating the Real Projective Plane

Abstract: We consider the problem of computing a triangulation of the real projective plane P2, given a finite point set S={p1, p2,..., pn} as input. We prove that a triangulation of P2 always exists if at least six points in S are in general position, i.e., no three of them are collinear. We also design an algorithm for triangulating P2 if this necessary condition holds. As far as we know, this is the first computational result on the real projective plane.


Incremental Satisfiability and Implication for UTVPI Constraints

Abstract: Unit two-variable-per-inequality (UTVPI) constraints form one of the largest class of integer constraints which are polynomial time solvable (unless P=NP). There is considerable interest in their use for constraint solving, abstract interpretation, spatial databases, and theorem proving. In this paper we develop a new incremental algorithm for UTVPI constraint satisfaction and implication checking that requires O(m + n log n + p) time and O(n+m+p) space to incrementally check satisfiability of m UTVPI constraints on n variables and check implication of p UTVPI constraints.


Supervised learning on graphs of spatio-temporal similarity in satellite image sequences

Abstract: High resolution satellite image sequences are multidimensional signals composed of spatio-temporal patterns associated to numerous and various phenomena. Bayesian methods have been previously proposed in (Heas and Datcu, 2005) to code the information contained in satellite image sequences in a graph representation using Bayesian methods. Based on such a representation, this paper further presents a supervised learning methodology of semantics associated to spatio-temporal patterns occurring in satellite image sequences. It enables the recognition and the probabilistic retrieval of similar events. Indeed, graphs are attached to statistical models for spatio-temporal processes, which at their turn describe physical changes in the observed scene. Therefore, we adjust a parametric model evaluating similarity types between graph patterns in order to represent user-specific semantics attached to spatio-temporal phenomena. The learning step is performed by the incremental definition of similarity types via user-provided spatio-temporal pattern examples attached to positive or/and negative semantics. From these examples, probabilities are inferred using a Bayesian network and a Dirichlet model. This enables to links user interest to a specific similarity model between graph patterns. According to the current state of learning, semantic posterior probabilities are updated for all possible graph patterns so that similar spatio-temporal phenomena can be recognized and retrieved from the image sequence. Few experiments performed on a multi-spectral SPOT image sequence illustrate the proposed spatio-temporal recognition method.


Query Evaluation in P2P Systems of Taxonomy-based Sources: Algorithms, Complexity, and Optimizations

Abstract: In this study, we address the problem of answering queries over a peer-to-peer system of taxonomy-based sources. A taxonomy states subsumption relationships between negation-free DNF formulas on terms and negation-free conjunctions of terms. To the end of laying the foundations of our study, we first consider the centralized case, deriving the complexity of the decision problem and of query evaluation. We conclude by presenting an algorithm that is efficient in data complexity and is based on hypergraphs. More expressive forms of taxonomies are also investigated, which however lead to intractability. We then move to the distributed case, and introduce a logical model of a network of taxonomy-based sources. On such network, a distributed version of the centralized algorithm is then presented, based on a message passing paradigm, and its correctness is proved. We finally discuss optimization issues, and relate our work to the literature.


Series which are both max-plus and min-plus rational are unambiguous

Abstract: Consider partial maps from the free monoid into the field of real numbers with a rational domain. We show that two families of such series are actually the same: the unambiguous rational series on the one hand, and the max-plus and min-plus rational series on the other hand. The decidability of equality was known to hold in both families with different proofs, so the above unifies the picture. We give an effective procedure to build an unambiguous automaton from a max-plus automaton and a min-plus one that recognize the same series.


Mistake Analyses on Proof about Perfect Secrecy of One-time-pad

Abstract: This paper has been withdrawn


Weighted Matching in the Semi-Streaming Model

Abstract: We reduce the best known approximation ratio for finding a weighted matching of a graph using a one-pass semi-streaming algorithm from 5.828 to 5.585. The semi-streaming model forbids random access to the input and restricts the memory to O(n*polylog(n)) bits. It was introduced by Muthukrishnan in 2003 and is appropriate when dealing with massive graphs.


Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps

Abstract: In many real world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable sensible comparison between observations. Kohonen's Self-Organizing Map (SOM) has been adapted to data described only through their dissimilarity matrix. This algorithm provides both non linear projection and clustering of non vector data. Unfortunately, the algorithm suffers from a high cost that makes it quite difficult to use with voluminous data sets. In this paper, we propose a new algorithm that provides an important reduction of the theoretical cost of the dissimilarity SOM without changing its outcome (the results are exactly the same as the ones obtained with the original algorithm). Moreover, we introduce implementation methods that result in very short running times. Improvements deduced from the theoretical cost model are validated on simulated and real world data (a word list clustering problem). We also demonstrate that the proposed implementation methods reduce by a factor up to 3 the running time of the fast algorithm over a standard implementation.


Design of moveable and resizable graphics

Abstract: We are communicating with computers on two different levels. On upper level we have a very flexible system of windows: we can move them, resize, overlap or put side by side. At any moment we decide what would be the best view and reorganize the whole view easily. Then we start any application, go to the inner level, and everything changes. Here we are stripped of all the flexibility and can work only inside the scenario, developed by the designer of the program. Interface will allow us to change some tiny details, but in general everything is fixed: graphics is neither moveable, nor resizable, and the same with controls. Author designed an extremely powerful mechanism of turning graphical objects and controls into moveable and resizable. This can not only significantly improve the existing applications, but this will bring the applications to another level. (To estimate the possible difference, try to imagine the Windows system without its flexibility and compare it with the current one.) This article explains in details the construction and use of moveable and resizable graphical objects.


A New Lower Bound on Guard Placement for Wireless Localization

Abstract: The problem of wireless localization asks to place and orient stations in the plane, each of which broadcasts a unique key within a fixed angular range, so that each point in the plane can determine whether it is inside or outside a given polygonal region. The primary goal is to minimize the number of stations. In this paper we establish a lower bound of 2n/3 - 1 stations for polygons in general position, for the case in which the placement of stations is restricted to polygon vertices, improving upon the existing n/2 lower bound.


Une adaptation des cartes auto-organisatrices pour des donn\'ees d\'ecrites par un tableau de dissimilarit\'es

Abstract: Many data analysis methods cannot be applied to data that are not represented by a fixed number of real values, whereas most of real world observations are not readily available in such a format. Vector based data analysis methods have therefore to be adapted in order to be used with non standard complex data. A flexible and general solution for this adaptation is to use a (dis)similarity measure. Indeed, thanks to expert knowledge on the studied data, it is generally possible to define a measure that can be used to make pairwise comparison between observations. General data analysis methods are then obtained by adapting existing methods to (dis)similarity matrices. In this article, we propose an adaptation of Kohonen's Self Organizing Map (SOM) to (dis)similarity data. The proposed algorithm is an adapted version of the vector based batch SOM. The method is validated on real world data: we provide an analysis of the usage patterns of the web site of the Institut National de Recherche en Informatique et Automatique, constructed thanks to web log mining method.


Self-organizing maps and symbolic data

Abstract: In data analysis new forms of complex data have to be considered like for example (symbolic data, functional data, web data, trees, SQL query and multimedia data, ...). In this context classical data analysis for knowledge discovery based on calculating the center of gravity can not be used because input are not $\mathbb{R}^p$ vectors. In this paper, we present an application on real world symbolic data using the self-organizing map. To this end, we propose an extension of the self-organizing map that can handle symbolic data.


An extension of a result concerning convex geometric graphs

Abstract: We show a general result known as the Erdos_Sos Conjecture: if $E(G)>{1/2}(k-1)n$ where $G$ has order $n$ then $G$ contains every tree of order $k+1$ as a subgraph.


Representation of Functional Data in Neural Networks

Abstract: Functional Data Analysis (FDA) is an extension of traditional data analysis to functional data, for example spectra, temporal series, spatio-temporal images, gesture recognition data, etc. Functional data are rarely known in practice; usually a regular or irregular sampling is known. For this reason, some processing is needed in order to benefit from the smooth character of functional data in the analysis methods. This paper shows how to extend the Radial-Basis Function Networks (RBFN) and Multi-Layer Perceptron (MLP) models to functional data inputs, in particular when the latter are known through lists of input-output pairs. Various possibilities for functional processing are discussed, including the projection on smooth bases, Functional Principal Component Analysis, functional centering and reduction, and the use of differential operators. It is shown how to incorporate these functional processing into the RBFN and MLP models. The functional approach is illustrated on a benchmark of spectrometric data analysis.


Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis

Abstract: In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally show on simulated and real world data that the proposed model performs in a very satisfactory way.


Static Deadlock Detection in MPI Synchronization Communication

Abstract: It is very common to use dynamic methods to detect deadlocks in MPI programs for the reason that static methods have some restrictions. To guarantee high reliability of some important MPI-based application software, a model of MPI synchronization communication is abstracted and a type of static method is devised to examine deadlocks in such modes. The model has three forms with different complexity: sequential model, single-loop model and nested-loop model. Sequential model is a base for all models. Single-loop model must be treated with a special type of equation group and nested-loop model extends the methods for the other two models. A standard Java-based software framework originated from these methods is constructed for determining whether MPI programs are free from synchronization communication deadlocks. Our practice shows the software framework is better than those tools using dynamic methods because it can dig out all synchronization communication deadlocks before an MPI-based program goes into running.


Deadlock Detection in Basic Models of MPI Synchronization Communication Programs

Abstract: A model of MPI synchronization communication programs is presented and its three basic simplified models are also defined. A series of theorems and methods for deciding whether deadlocks will occur among the three models are given and proved strictly. These theories and methods for simple models' deadlock detection are the necessary base for real MPI program deadlock detection. The methods are based on a static analysis through programs and with runtime detection in necessary cases and they are able to determine before compiling whether it will be deadlocked for two of the three basic models. For another model, some deadlock cases can be found before compiling and others at runtime. Our theorems can be used to prove the correctness of currently popular MPI program deadlock detection algorithms. Our methods may decrease codes that those algorithms need to change to MPI source or profiling interface and may detects deadlocks ahead of program execution, thus the overheads can be reduced greatly.


Algorithm of Static Deadlock Detection in MPI Synchronization Communication Sequential Model

Abstract: Detecting deadlocks in MPI synchronization communication programs is very difficult and need building program models. All complex models are based on sequential models. The sequential model is mapped into a set of character strings and its deadlock detection problem is translated into an equivalent multi-queue string matching problem. An algorithm is devised and implemented to statically detect deadlocks in sequential models of MPI synchronization communication programs. The time and space complexity of the algorithm is O(n) where n is the amount of message in model. The algorithm is better than usual circle-detection methods and can adapt well to dynamic message stream.


Research Paper on Transaction-Oriented Simulation In Ad Hoc Grids

Abstract: This paper analyses the requirements of performing parallel transaction-oriented simulations with a special focus on the space-parallel approach and discrete event simulation synchronisation algorithms that are suitable for transaction-oriented simulation and the target environment of Ad Hoc Grids. To demonstrate the findings a Java-based parallel transaction-oriented simulator for the simulation language GPSS/H is implemented on the basis of the most promising Shock Resistant Time Warp synchronisation algorithm and using the Grid framework ProActive. The validation of this parallel simulator shows that the Shock Resistant Time Warp algorithm can successfully reduce the number of rolled back Transaction moves but it also reveals circumstances in which the Shock Resistant Time Warp algorithm can be outperformed by the normal Time Warp algorithm. The conclusion of this paper suggests possible improvements to the Shock Resistant Time Warp algorithm to avoid such problems.