Counting Triangulations of Planar Point Sets

Abstract: We study the maximal number of triangulations that a planar set of $n$ points can have, and show that it is at most $30^n$. This new bound is achieved by a careful optimization of the charging scheme of Sharir and Welzl (2006), which has led to the previous best upper bound of $43^n$ for the problem. Moreover, this new bound is useful for bounding the number of other types of planar (i.e., crossing-free) straight-line graphs on a given point set. Specifically, we derive new upper bounds for the number of planar graphs ($o(239.4^n)$), spanning cycles ($O(70.21^n)$), and spanning trees ($160^n$).


A Minimal Periods Algorithm with Applications

Abstract: Kosaraju in ``Computation of squares in a string'' briefly described a linear-time algorithm for computing the minimal squares starting at each position in a word. Using the same construction of suffix trees, we generalize his result and describe in detail how to compute in O(k|w|)-time the minimal k-th power, with period of length larger than s, starting at each position in a word w for arbitrary exponent $k\geq2$ and integer $s\geq0$. We provide the complete proof of correctness of the algorithm, which is somehow not completely clear in Kosaraju's original paper. The algorithm can be used as a sub-routine to detect certain types of pseudo-patterns in words, which is our original intention to study the generalization.


Bounded Independence Fools Degree-2 Threshold Functions

Abstract: Let x be a random vector coming from any k-wise independent distribution over {-1,1}^n. For an n-variate degree-2 polynomial p, we prove that E[sgn(p(x))] is determined up to an additive epsilon for k = poly(1/epsilon). This answers an open question of Diakonikolas et al. (FOCS 2009). Using standard constructions of k-wise independent distributions, we obtain a broad class of explicit generators that epsilon-fool the class of degree-2 threshold functions with seed length log(n)*poly(1/epsilon). Our approach is quite robust: it easily extends to yield that the intersection of any constant number of degree-2 threshold functions is epsilon-fooled by poly(1/epsilon)-wise independence. Our results also hold if the entries of x are k-wise independent standard normals, implying for example that bounded independence derandomizes the Goemans-Williamson hyperplane rounding scheme. To achieve our results, we introduce a technique we dub multivariate FT-mollification, a generalization of the univariate form introduced by Kane et al. (SODA 2010) in the context of streaming algorithms. Along the way we prove a generalized hypercontractive inequality for quadratic forms which takes the operator norm of the associated matrix into account. These techniques may be of independent interest.


Dense-choice Counter Machines revisited

Abstract: This paper clarifies the picture about Dense-choice Counter Machines, which have been less studied than (discrete) Counter Machines. We revisit the definition of "Dense Counter Machines" so that it now extends (discrete) Counter Machines, and we provide new undecidability and decidability results. Using the first-order additive mixed theory of reals and integers, we give a logical characterization of the sets of configurations reachable by reversal-bounded Dense-choice Counter Machines.


Flare: Architecture for rapid and easy development of Internet-based Applications

Abstract: We propose an architecture, Flare, that is a structured and easy way to develop applications rapidly, in a multitude of languages, which make use of online storage of data and management of users. The architecture eliminates the need for server-side programming in most cases, creation and management of online database storage servers, re-creation of user management schemes and writing a lot of unnecessary code for accessing different web-based services using their APIs. A Web API provides a common API for various web-based services like Blogger [2], Wordpress, MSN Live, Facebook [3] etc. Access Libraries provided for major programming languages and platforms make it easy to develop applications using the Flare Web Service. We demonstrate a simple micro-blogging service developed using these APIs in two modes: a graphical browser-based mode, and a command-line mode in C++, which provide two different interfaces to the same account and data.


Proceedings International Workshop on Verification of Infinite-State Systems

Abstract: This volume contains the proceedings of the 11th International Workshop on Verification of Infinite-State Systems (INFINITY 2009). The workshop was held in Bologna, Italy on August 31, 2009, as a satellite event to the 20th International Conference on Concurrency Theory (CONCUR 2009). The aim of the INFINITY workshop is to provide a forum for researchers interested in the development of formal methods and algorithmic techniques for the analysis of systems with infinitely many states, and their application in automated verification of complex software and hardware systems.


PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

Abstract: High-performance computing has recently seen a surge of interest in heterogeneous systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices offer tremendous potential for performance and efficiency in important large-scale applications of computational science. However, exploiting this potential can be challenging, as one must adapt to the specialized and rapidly evolving computing environment currently exhibited by GPUs. One way of addressing this challenge is to embrace better techniques and develop tools tailored to their needs. This article presents one simple technique, GPU run-time code generation (RTCG), along with PyCUDA and PyOpenCL, two open-source toolkits that support this technique. In introducing PyCUDA and PyOpenCL, this article proposes the combination of a dynamic, high-level scripting language with the massive performance of a GPU as a compelling two-tiered computing platform, potentially offering significant performance and productivity advantages over conventional single-tier, static systems. The concept of RTCG is simple and easily implemented using existing, robust infrastructure. Nonetheless it is powerful enough to support (and encourage) the creation of custom application-specific tools by its users. The premise of the paper is illustrated by a wide range of examples where the technique has been applied with considerable success.


Polynomial Threshold Functions: Structure, Approximation and Pseudorandomness

Abstract: We study the computational power of polynomial threshold functions, that is, threshold functions of real polynomials over the boolean cube. We provide two new results bounding the computational power of this model. Our first result shows that low-degree polynomial threshold functions cannot approximate any function with many influential variables. We provide a couple of examples where this technique yields tight approximation bounds. Our second result relates to constructing pseudorandom generators fooling low-degree polynomial threshold functions. This problem has received attention recently, where Diakonikolas et al proved that $k$-wise independence suffices to fool linear threshold functions. We prove that any low-degree polynomial threshold function, which can be represented as a function of a small number of linear threshold functions, can also be fooled by $k$-wise independence. We view this as an important step towards fooling general polynomial threshold functions, and we discuss a plausible approach achieving this goal based on our techniques. Our results combine tools from real approximation theory, hyper-contractive inequalities and probabilistic methods. In particular, we develop several new tools in approximation theory which may be of independent interest.


Towards a Dichotomy for the Possible Winner Problem in Elections Based on Scoring Rules

Abstract: To make a joint decision, agents (or voters) are often required to provide their preferences as linear orders. To determine a winner, the given linear orders can be aggregated according to a voting protocol. However, in realistic settings, the voters may often only provide partial orders. This directly leads to the Possible Winner problem that asks, given a set of partial votes, whether a distinguished candidate can still become a winner. In this work, we consider the computational complexity of Possible Winner for the broad class of voting protocols defined by scoring rules. A scoring rule provides a score value for every position which a candidate can have in a linear order. Prominent examples include plurality, k-approval, and Borda. Generalizing previous NP-hardness results for some special cases, we settle the computational complexity for all but one scoring rule. More precisely, for an unbounded number of candidates and unweighted voters, we show that Possible Winner is NP-complete for all pure scoring rules except plurality, veto, and the scoring rule defined by the scoring vector (2,1,...,1,0), while it is solvable in polynomial time for plurality and veto.


Estimating Network Link Characteristics using Packet-Pair Dispersion: A Discrete Time Queueing Theoretic View

Abstract: Packet-dispersion based measurement tools insert pairs of probe packets with a known separation into the network for transmission over a unicast path or a multicast tree. Samples of the separation between the probe pairs at the destination(s) are observed. Heuristic techniques are then used by these tools to estimate the path characteristics from the observations. In this paper we present a queueing theoretic setting for packet-dispersion based probing. Analogous to network tomography, we develop techniques to estimate the parameters of the arrival process to the individual links from the samples of the output separations, i.e., from the end-to-end measurements. The links are modeled as independent discrete time queues with i.i.d. arrivals. We first obtain an algorithm to obtain the (joint) distribution of the separation between the probes at the destination(s) for a given distribution of the spacing at the input. The parameter estimates of the arrival process are obtained as the minimizer of a cost function between the empirical and calculated distributions. We also carry out extensive simulations and numerical experiments to study the performance of the estimation algorithm under the fairly `harsh' conditions of non stationarity of the arrival process. We find that the estimations work fairly well for two queues in series and for multicast.


Noise Speech wavelet analyzing in special time ranges

Abstract: Speech analyzing in special periods of time has been presented in this paper. One of the most important periods in signal processing is near to Zero. By this paper, we analyze noise speech signals when these signals are near to Zero. Our strategy is defining some subfunctions and compress histograms when a noise speech signal is in a special period. It can be so useful for wavelet signal processing and spoken systems analyzing.


X-Learn: An XML-Based, Multi-agent System for Supporting "User-Device" Adaptive E-learning

Abstract: In this paper we present X-Learn, an XML-based, multi-agent system for supporting "user-device" adaptive e-learning. X-Learn is characterized by the following features: (i) it is highly subjective, since it handles quite a rich and detailed user profile that plays a key role during the learning activities; (ii) it is dynamic and flexible, i.e., it is capable of reacting to variations of exigencies and objectives; (iii) it is device-adaptive, since it decides the learning objects to present to the user on the basis of the device she/he is currently exploiting; (iv) it is generic, i.e., it is capable of operating in a large variety of learning contexts; (v) it is XML based, since it exploits many facilities of XML technology for handling and exchanging information connected to e-learning activities. The paper reports also various experimental results as well as a comparison between X-Learn and other related e-learning management systems already presented in the literature.


"Almost automatic" and semantic integration of XML Schemas at various "severity" levels

Abstract: This paper presents a novel approach for the integration of a set of XML Schemas. The proposed approach is specialized for XML, is almost automatic, semantic and "light". As a further, original, peculiarity, it is parametric w.r.t. a "severity" level against which the integration task is performed. The paper describes the approach in all details, illustrates various theoretical results, presents the experiments we have performed for testing it and, finally, compares it with various related approaches already proposed in the literature.


AnAmeter: The First Steps to Evaluating Adaptation

Abstract: This paper presents the online AnAmeter framework that helps characterize the different types of adaptations a system features by helping the evaluator fill in a simple form. The provided information is then processed to obtain a quantitative evaluation of three parameters called global, semi-global and local adaptation degrees. By characterizing and quantifying adaptation, AnAmeter provides the first steps towards the evaluation of the quality of a system's adaptation. AnAmeter is an open tool available as freeware on the web and has been applied to a selection of well known systems. To build this evaluation grid we also collected a number of systems that cover the full range of adaptation types.


Deciding Regularity of the Set of Instances of a Set of Terms with Regular Constraints is EXPTIME-Complete

Abstract: Finite-state tree automata are a well studied formalism for representing term languages. This paper studies the problem of determining the regularity of the set of instances of a finite set of terms with variables, where each variable is restricted to instantiations of a regular set given by a tree automaton. The problem was recently proved decidable, but with an unknown complexity. Here, the exact complexity of the problem is determined by proving EXPTIME-completeness. The main contribution is a new, exponential time algorithm that performs various exponential transformations on the involved terms and tree automata, and decides regularity by analyzing formulas over inequality and height predicates.


Manipulability of Single Transferable Vote

Abstract: For many voting rules, it is NP-hard to compute a successful manipulation. However, NP-hardness only bounds the worst-case complexity. Recent theoretical results suggest that manipulation may often be easy in practice. We study empirically the cost of manipulating the single transferable vote (STV) rule. This was one of the first rules shown to be NP-hard to manipulate. It also appears to be one of the harder rules to manipulate since it involves multiple rounds and since, unlike many other rules, it is NP-hard for a single agent to manipulate without weights on the votes or uncertainty about how the other agents have voted. In almost every election in our experiments, it was easy to compute how a single agent could manipulate the election or to prove that manipulation by a single agent was impossible. It remains an interesting open question if manipulation by a coalition of agents is hard to compute in practice.


Applications of the Dynamic Distance Potential Field Method

Abstract: Recently the dynamic distance potential field (DDPF) was introduced as a computationally efficient method to make agents in a simulation of pedestrians move rather on the quickest path than the shortest. It can be considered to be an estimated-remaining-journey-time-based one-shot dynamic assignment method for pedestrian route choice on the operational level of dynamics. In this contribution the method is shortly introduced and the effect of the method on RiMEA's test case 11 is investigated.


Evolutionary estimation of a Coupled Markov Chain credit risk model

Abstract: There exists a range of different models for estimating and simulating credit risk transitions to optimally manage credit risk portfolios and products. In this chapter we present a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. As the likelihood of the model turns out to be a non-convex function of the parameters to be estimated, we apply heuristics to find the ML estimators. To this extent, we outline the model and its likelihood function, and present both a Particle Swarm Optimization algorithm, as well as an Evolutionary Optimization algorithm to maximize the likelihood function. Numerical results are shown which suggest a further application of evolutionary optimization techniques for credit risk management.


Continuous Verification of Large Embedded Software using SMT-Based Bounded Model Checking

Abstract: The complexity of software in embedded systems has increased significantly over the last years so that software verification now plays an important role in ensuring the overall product quality. In this context, SAT-based bounded model checking has been successfully applied to discover subtle errors, but for larger applications, it often suffers from the state space explosion problem. This paper describes a new approach called continuous verification to detect design errors as quickly as possible by looking at the Software Configuration Management (SCM) system and by combining dynamic and static verification to reduce the state space to be explored. We also give a set of encodings that provide accurate support for program verification and use different background theories in order to improve scalability and precision in a completely automatic way. A case study from the telecommunications domain shows that the proposed approach improves the error-detection capability and reduces the overall verification time by up to 50%.


Graph rewriting with polarized cloning

Abstract: We tackle the problem of graph transformation with a particular focus on node cloning. We propose a new approach to graph rewriting where nodes can be cloned zero, one or more times. A node can be cloned together with all its incident edges, with only its outgoing edges, with only its incoming edges or with none of its incident edges. We thus subsume previous works such as the sesqui-pushout, the heterogeneous pushout and the adaptive star grammars approaches. A rewrite rule is defined as a span where the right-hand and left-hand sides are graphs while the interface is a polarized graph. A polarized graph is a graph endowed with some annotations on nodes. The way a node is cloned is indicated by its polarization annotation. We use these annotations for designing graph transformation with polarized cloning. We show how a clone of a node can be built according to the different possible polarizations and define a rewrite step as a final pullback complement followed by a pushout. This is called the polarized sesqui-pushout approach. We also provide an algorithmic presentation of the proposed graph transformation with polarized cloning.


Capturing Polynomial Time on Interval Graphs

Abstract: We prove a characterization of all polynomial-time computable queries on the class of interval graphs by sentences of fixed-point logic with counting. More precisely, it is shown that on the class of unordered interval graphs, any query is polynomial-time computable if and only if it is definable in fixed-point logic with counting. This result is one of the first establishing the capturing of polynomial time on a graph class which is defined by forbidden induced subgraphs. For this, we define a canonical form of interval graphs using a type of modular decomposition, which is different from the method of tree decomposition that is used in most known capturing results for other graph classes, specifically those defined by forbidden minors. The method might also be of independent interest for its conceptual simplicity. Furthermore, it is shown that fixed-point logic with counting is not expressive enough to capture polynomial time on the classes of chordal graphs or incomparability graphs.


Delay Bounds for Networks with Heavy-Tailed and Self-Similar Traffic

Abstract: We provide upper bounds on the end-to-end backlog and delay in a network with heavy-tailed and self-similar traffic. The analysis follows a network calculus approach where traffic is characterized by envelope functions and service is described by service curves. A key contribution of this paper is the derivation of a probabilistic sample path bound for heavy-tailed self-similar arrival processes, which is enabled by a suitable envelope characterization, referred to as `htss envelope'. We derive a heavy-tailed service curve for an entire network path when the service at each node on the path is characterized by heavy-tailed service curves. We obtain backlog and delay bounds for traffic that is characterized by an htss envelope and receives service given by a heavy-tailed service curve. The derived performance bounds are non-asymptotic in that they do not assume a steady-state, large buffer, or many sources regime. We also explore the scale of growth of delays as a function of the length of the path. The appendix contains an analysis for self-similar traffic with a Gaussian tail distribution.


A Semantic Grid Oriented to E-Tourism

Abstract: With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.


Randomized Interior Point methods for Sampling and Optimization

Abstract: We present a Markov chain (Dikin walk) for sampling from a convex body equipped with a self-concordant barrier, whose mixing time from a "central point" is strongly polynomial in the description of the convex set. The mixing time of this chain is invariant under affine transformations of the convex set, thus eliminating the need for first placing the body in an isotropic position. This recovers and extends previous results of from polytopes to more general convex sets. On every convex set of dimension $n$, there exists a self-concordant barrier whose "complexity" is polynomially bounded. Consequently, a rapidly mixing Markov chain of the kind we describe can be defined on any convex set. We use these results to design an algorithm consisting of a single random walk for optimizing a linear function on a convex set. We show that this random walk reaches an approximately optimal point in polynomial time with high probability and that the corresponding objective values converge with probability 1 to the optimal objective value as the number of steps tends to infinity. One technical contribution is a family of lower bounds for the isoperimetric constants of (weighted) Riemannian manifolds on which, interior point methods perform a kind of steepest descent. Using results of Barthe \cite{barthe} and Bobkov and Houdr\'e, on the isoperimetry of products of (weighted) Riemannian manifolds, we obtain sharper upper bounds on the mixing time of Dikin walk on products of convex sets than the bounds obtained from a direct application of the Localization Lemma, on which, since (Lov\'asz and Simonovits), the analyses of all random walks on convex sets have relied.


Making the road by searching - A search engine based on Swarm Information Foraging

Abstract: Search engines are nowadays one of the most important entry points for Internet users and a central tool to solve most of their information needs. Still, there exist a substantial amount of users' searches which obtain unsatisfactory results. Needless to say, several lines of research aim to increase the relevancy of the results users retrieve. In this paper the authors frame this problem within the much broader (and older) one of information overload. They argue that users' dissatisfaction with search engines is a currently common manifestation of such a problem, and propose a different angle from which to tackle with it. As it will be discussed, their approach shares goals with a current hot research topic (namely, learning to rank for information retrieval) but, unlike the techniques commonly applied in that field, their technique cannot be exactly considered machine learning and, additionally, it can be used to change the search engine's response in real-time, driven by the users behavior. Their proposal adapts concepts from Swarm Intelligence (in particular, Ant Algorithms) from an Information Foraging point of view. It will be shown that the technique is not only feasible, but also an elegant solution to the stated problem; what's more, it achieves promising results, both increasing the performance of a major search engine for informational queries, and substantially reducing the time users require to answer complex information needs.


Extending Firewall Session Table to Accelerate NAT, QoS Classification and Routing

Abstract: security and QoS are the two most precious objectives for network systems to be attained. Unfortunately, they are in conflict, while QoS tries to minimize processing delay, strong security protection requires more processing time and cause packet delay. This article is a step towards resolving this conflict by extending the firewall session table to accelerate NAT, QoS classification, and routing processing time while providing the same level of security protection. Index Terms ? stateful packet filtering; firewall; session/state table; QoS; NAT; Routing.


Q-ESP: a QoS-compliant Security Protocol to enrich IPSec Framework

Abstract: IPSec is a protocol that allows to make secure connections between branch offices and allows secure VPN accesses. However, the efforts to improve IPSec are still under way; one aspect of this improvement is to take Quality of Service (QoS) requirements into account. QoS is the ability of the network to provide a service at an assured service level while optimizing the global usage of network resources. The QoS level that a flow receives depends on a six-bit identifier in the IP header; the so-called Differentiated Services code point (DSCP). Basically, Multi-Field classifiers classify a packet by inspecting IP/TCP headers, to decide how the packet should be processed. The current IPSec standard does hardly offer any guidance to do this, because the existing IPSec ESP security protocol hides much of this information in its encrypted payloads, preventing network control devices such as routers and switches from utilizing this information in performing classification appropriately. To solve this problem, we propose a QoS-friendly Encapsulated Security Payload (Q-ESP) as a new IPSec security protocol that provides both security and QoS supports. We also present our NetBSD kernel-based implementation as well as our evaluation results of Q-ESP.


About a new splitting for the algorithmic study of the tilings $\{p,q\}$ of the hyperbolic plane when $q$ is odd

Abstract: In this paper, we remind previous results about the tilings $\{p,q\}$ of the hyperbolic plane. We introduce two new ways to split the hyperbolic plane in order to algorithmically construct the tilings $\{p,q\}$ when $q$ is odd.


Efficient Local Unfolding with Ancestor Stacks

Abstract: The most successful unfolding rules used nowadays in the partial evaluation of logic programs are based on well quasi orders (wqo) applied over (covering) ancestors, i.e., a subsequence of the atoms selected during a derivation. Ancestor (sub)sequences are used to increase the specialization power of unfolding while still guaranteeing termination and also to reduce the number of atoms for which the wqo has to be checked. Unfortunately, maintaining the structure of the ancestor relation during unfolding introduces significant overhead. We propose an efficient, practical local unfolding rule based on the notion of covering ancestors which can be used in combination with a wqo and allows a stack-based implementation without losing any opportunities for specialization. Using our technique, certain non-leftmost unfoldings are allowed as long as local unfolding is performed, i.e., we cover depth-first strategies.


A computational definition of the notion of vectorial space

Abstract: We usually define an algebraic structure by a set, some operations defined on this set and some propositions that the algebraic structure must validate. In some cases, we can replace these propositions by an algorithm on terms constructed upon these operations that the algebraic structure must validate. We show in this note that this is the case for the notions of vectorial space and bilinear operation. KEYWORDS: Rewrite system, vector space, bilinear operation, tensorial product, semantics, quantum programming languages, probabilistic programming languages.


On convexification of polygons by pops

Abstract: Given a polygon $P$ in the plane, a {\em pop} operation is the reflection of a vertex with respect to the line through its adjacent vertices. We define a family of alternating polygons, and show that any polygon from this family cannot be convexified by pop operations. This family contains simple, as well as non-simple (i.e., self-intersecting) polygons, as desired. We thereby answer in the negative an open problem posed by Demaine and O'Rourke \cite[Open Problem 5.3]{DO07}.


The Impact of Exponential Utility Costs in Bottleneck Routing Games

Abstract: We study bottleneck routing games where the social cost is determined by the worst congestion on any edge in the network. Bottleneck games have been studied in the literature by having the player's utility costs to be determined by the worst congested edge in their paths. However, the Nash equilibria of such games are inefficient since the price of anarchy can be very high with respect to the parameters of the game. In order to obtain smaller price of anarchy we explore {\em exponential bottleneck games} where the utility costs of the players are exponential functions on the congestion of the edges in their paths. We find that exponential bottleneck games are very efficient giving a poly-log bound on the price of anarchy: O(log L log |E|), where L is the largest path length in the players strategy sets and E is the set of edges in the graph.


Folksonomic Tag Clouds as an Aid to Content Indexing

Abstract: Social tagging systems have recently developed as a popular method of data organisation on the Internet. These systems allow users to organise their content in a way that makes sense to them, rather than forcing them to use a pre-determined and rigid set of categorisations. These folksonomies provide well populated sources of unstructured tags describing web resources which could potentially be used as semantic index terms for these resources. However getting people to agree on what tags best describe a resource is a difficult problem, therefore any feature which increases the consistency and stability of terms chosen would be extremely beneficial. We investigate how the provision of a tag cloud, a weighted list of terms commonly used to assist in browsing a folksonomy, during the tagging process itself influences the tags produced and how difficult the user perceived the task to be. We show that illustrating the most popular tags to users assists in the tagging process and encourages a stable and consistent folksonomy to form.


Network congestion control using NetFlow

Abstract: The goal of congestion control is to avoid congestion in network elements. A network element is congested if it is being offered more traffic than it can process. To detect such situations and to neutralize them we should monitor traffic in the network. In this paper, we propose using Cisco's NetFlow technology, which allows collecting statistics about traffic in the network by generating special NetFlow packets. Cisco's routers can send NetFlow packets to a special node, so we can collect these packets, analyze its content and detect network congestion. We use Cisco's feature as example, some other vendors (Juniper, 3COM, Alcatel, etc.) provide similar features for their routers. We also consider a simple system, which collects statistical information about network elements, determines overloaded elements and identifies flows, which congest them.


From Self-Interpreters to Normalization by Evaluation

Abstract: We characterize normalization by evaluation as the composition of a self-interpreter with a self-reducer using a special representation scheme, in the sense of Mogensen (1992). We do so by deriving in a systematic way an untyped normalization by evaluation algorithm from a standard interpreter for the ?-calculus. The derived algorithm is not novel and indeed other published algorithms may be obtained in the same manner through appropriate adaptations to the representation scheme.


Introduction to Bioinformatics

Abstract: Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling of biological phenomena, and development of algorithms and statistics. This article presents an introduction to bioinformatics


Secure Multidimensional Queries in Tiered Sensor Networks

Abstract: In this paper, aiming at securing range query, top-k query, and skyline query in tiered sensor networks, we propose the Secure Range Query (SRQ), Secure Top-$k$ Query (STQ), and Secure Skyline Query (SSQ) schemes, respectively. In particular, SRQ, by using our proposed \emph{prime aggregation} technique, has the lowest communication overhead among prior works, while STQ and SSQ, to our knowledge, are the first proposals in tiered sensor networks for securing top-$k$ and skyline queries, respectively. Moreover, the relatively unexplored issue of the security impact of sensor node compromises on multidimensional queries is studied; two attacks incurred from the sensor node compromises, \emph{collusion attack} and \emph{false-incrimination attack}, are investigated in this paper. After developing a novel technique called \emph{subtree sampling}, we also explore methods of efficiently mitigating the threat of sensor node compromises. Performance analyses regarding the probability for detecting incomplete query-results and communication cost of the proposed schemes are also studied.


Constrained Function Based En-Route Filtering for Sensor Networks

Abstract: Sensor networks are vulnerable to \emph{false data injection attack} and \emph{path-based DoS} (PDoS) attack. While conventional authentication schemes are insufficient for solving these security conflicts, an \emph{en-route filtering} scheme acts as a defense against these two attacks. To construct an efficient en-route filtering scheme, this paper first presents a Constrained Function based message Authentication (CFA) scheme, which can be thought of as a hash function directly supporting the en-route filtering functionality. Together with the \emph{redundancy property} of sensor networks, which means that an event can be simultaneously observed by multiple sensor nodes, the devised CFA scheme is used to construct a CFA-based en-route filtering (CFAEF) scheme. In contrast to most of the existing methods, which rely on complicated security associations among sensor nodes, our design, which directly exploits an en-route filtering hash function, appears to be novel. We examine the CFA and CFAEF schemes from both the theoretical and numerical aspects to demonstrate their efficiency and effectiveness.


Towards Industrialized Conception and Production of Serious Games

Abstract: Serious Games (SGs) have experienced a tremendous outburst these last years. Video game companies have been producing fun, user-friendly SGs, but their educational value has yet to be proven. Meanwhile, cognition research scientist have been developing SGs in such a way as to guarantee an educational gain, but the fun and attractive characteristics featured often would not meet the public's expectations. The ideal SG must combine these two aspects while still being economically viable. In this article, we propose a production chain model to efficiently conceive and produce SGs that are certified for their educational gain and fun qualities. Each step of this chain will be described along with the human actors, the tools and the documents that intervene.


The Importance, Design and Implementation of a Middleware for Networked Control Systems

Abstract: Due to the advancement of computing and communication technology, networked control systems may soon become prevalent in many control applications. While the capability of employing the communication network in the control loop certainly provides many benefits, it also raises several challenges which need to be overcome to utilize the benefits. In this chapter, we focus on one major challenge: a middleware framework that enables a networked control system to be implemented. Indeed our thesis is that a middleware for networked control sys important for the future of networked control systems. We discuss the fundamental issues which need to be considered in the design and development of an appropriate middleware for networked control systems. We describe \emph{Etherware}, a middleware for networked control system which has been developed at the University of Illinois, as an example of such a middleware framework, to illustrate how these issues can be addressed in the design of a middleware. Using a networked inverted pendulum control system as an example, we demonstrate the powerful capabilities provided by Etherware for a networked control system.


Evaluation of Anonymized ONS Queries

Abstract: Electronic Product Code (EPC) is the basis of a pervasive infrastructure for the automatic identification of objects on supply chain applications (e.g., pharmaceutical or military applications). This infrastructure relies on the use of the (1) Radio Frequency Identification (RFID) technology to tag objects in motion and (2) distributed services providing information about objects via the Internet. A lookup service, called the Object Name Service (ONS) and based on the use of the Domain Name System (DNS), can be publicly accessed by EPC applications looking for information associated with tagged objects. Privacy issues may affect corporate infrastructures based on EPC technologies if their lookup service is not properly protected. A possible solution to mitigate these issues is the use of online anonymity. We present an evaluation experiment that compares the of use of Tor (The second generation Onion Router) on a global ONS/DNS setup, with respect to benefits, limitations, and latency.


Markovian Network Interdiction and the Four Color Theorem

Abstract: The Unreactive Markovian Evader Interdiction Problem (UME) asks to optimally place sensors on a network to detect Markovian motion by one or more "evaders". It was previously proved that finding the optimal sensor placement is NP-hard if the number of evaders is unbounded. Here we show that the problem is NP-hard with just 2 evaders using a connection to coloring of planar graphs. The results suggest that approximation algorithms are needed even in applications where the number of evaders is small. It remains an open problem to determine the complexity of the 1-evader case or to devise efficient algorithms.


Structural Consistency: Enabling XML Keyword Search to Eliminate Spurious Results Consistently

Abstract: XML keyword search is a user-friendly way to query XML data using only keywords. In XML keyword search, to achieve high precision without sacrificing recall, it is important to remove spurious results not intended by the user. Efforts to eliminate spurious results have enjoyed some success by using the concepts of LCA or its variants, SLCA and MLCA. However, existing methods still could find many spurious results. The fundamental cause for the occurrence of spurious results is that the existing methods try to eliminate spurious results locally without global examination of all the query results and, accordingly, some spurious results are not consistently eliminated. In this paper, we propose a novel keyword search method that removes spurious results consistently by exploiting the new concept of structural consistency.


Scheduling Sensors for Guaranteed Sparse Coverage

Abstract: Sensor networks are particularly applicable to the tracking of objects in motion. For such applications, it may not necessary that the whole region be covered by sensors as long as the uncovered region is not too large. This notion has been formalized by Balasubramanian et.al. as the problem of $\kappa$-weak coverage. This model of coverage provides guarantees about the regions in which the objects may move undetected. In this paper, we analyse the theoretical aspects of the problem and provide guarantees about the lifetime achievable. We introduce a number of practical algorithms and analyse their significance. The main contribution is a novel linear programming based algorithm which provides near-optimal lifetime. Through extensive experimentation, we analyse the performance of these algorithms based on several parameters defined.


Circuit Lower Bounds, Help Functions, and the Remote Point Problem

Abstract: We investigate the power of Algebraic Branching Programs (ABPs) augmented with help polynomials, and constant-depth Boolean circuits augmented with help functions. We relate the problem of proving explicit lower bounds in both these models to the Remote Point Problem (introduced by Alon, Panigrahy, and Yekhanin (RANDOM '09)). More precisely, proving lower bounds for ABPs with help polynomials is related to the Remote Point Problem w.r.t. the rank metric, and for constant-depth circuits with help functions it is related to the Remote Point Problem w.r.t. the Hamming metric. For algebraic branching programs with help polynomials with some degree restrictions we show exponential size lower bounds for explicit polynomials.


Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View

Abstract: Relay selection for cooperative communications promises significant performance improvements, and is, therefore, attracting considerable attention. While several criteria have been proposed for selecting one or more relays, distributed mechanisms that perform the selection have received relatively less attention. In this paper, we develop a novel, yet simple, asymptotic analysis of a splitting-based multiple access selection algorithm to find the single best relay. The analysis leads to simpler and alternate expressions for the average number of slots required to find the best user. By introducing a new `contention load' parameter, the analysis shows that the parameter settings used in the existing literature can be improved upon. New and simple bounds are also derived. Furthermore, we propose a new algorithm that addresses the general problem of selecting the best $Q \ge 1$ relays, and analyze and optimize it. Even for a large number of relays, the algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. We also propose a new and simple scheme for the practically relevant case of discrete metrics. Altogether, our results develop a unifying perspective about the general problem of distributed selection in cooperative systems and several other multi-node systems.


Hitting Diamonds and Growing Cacti

Abstract: We consider the following NP-hard problem: in a weighted graph, find a minimum cost set of vertices whose removal leaves a graph in which no two cycles share an edge. We obtain a constant-factor approximation algorithm, based on the primal-dual method. Moreover, we show that the integrality gap of the natural LP relaxation of the problem is \Theta(\log n), where n denotes the number of vertices in the graph.


Automated Proofs in Geometry : Computing Upper Bounds for the Heilbronn Problem for Triangles

Abstract: We propose a method for computing upper bounds for the Heilbronn problem for triangles.


Ptolemaic Indexing

Abstract: This paper discusses a new family of bounds for use in similarity search, related to those used in metric indexing, but based on Ptolemy's inequality, rather than the metric axioms. Ptolemy's inequality holds for the well-known Euclidean distance, but is also shown here to hold for quadratic form metrics in general, with Mahalanobis distance as an important special case. The inequality is examined empirically on both synthetic and real-world data sets and is also found to hold approximately, with a very low degree of error, for important distances such as the angular pseudometric and several Lp norms. Indexing experiments demonstrate a highly increased filtering power compared to existing, triangular methods. It is also shown that combining the Ptolemaic and triangular filtering can lead to better results than using either approach on its own.


Bio-inspired speed detection and discrimination

Abstract: In the field of computer vision, a crucial task is the detection of motion (also called optical flow extraction). This operation allows analysis such as 3D reconstruction, feature tracking, time-to-collision and novelty detection among others. Most of the optical flow extraction techniques work within a finite range of speeds. Usually, the range of detection is extended towards higher speeds by combining some multiscale information in a serial architecture. This serial multi-scale approach suffers from the problem of error propagation related to the number of scales used in the algorithm. On the other hand, biological experiments show that human motion perception seems to follow a parallel multiscale scheme. In this work we present a bio-inspired parallel architecture to perform detection of motion, providing a wide range of operation and avoiding error propagation associated with the serial architecture. To test our algorithm, we perform relative error comparisons between both classical and proposed techniques, showing that the parallel architecture is able to achieve motion detection with results similar to the serial approach.


Introduction to Distributed Systems

Abstract: Computing has passed through many transformations since the birth of the first computing machines. Developments in technology have resulted in the availability of fast and inexpensive processors, and progresses in communication technology have resulted in the availability of lucrative and highly proficient computer networks. Among these, the centralized networks have one component that is shared by users all the time. All resources are accessible, but there is a single point of control as well as a single point of failure. The integration of computer and networking technologies gave birth to new paradigm of computing called distributed computing in the late 1970s. Distributed computing has changed the face of computing and offered quick and precise solutions for a variety of complex problems for different fields. Nowadays, we are fully engrossed by the information age, and expending more time communicating and gathering information through the Internet. The Internet keeps on progressing along more than a few magnitudes, abiding end systems increasingly to communicate in more and more different ways. Over the years, several methods have evolved to enable these developments, ranging from simplistic data sharing to advanced systems supporting a multitude of services. This article provides an overview of distributed computing systems. The definition, architecture, characteristics of distributed systems and the various distributed computing fallacies are discussed in the beginning. Finally, discusses client/server computing, World Wide Web and types of distributed systems.


Designing fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images

Abstract: We propose a novel scheme for designing fuzzy rule based classifier. An SOFM based method is used for generating a set of prototypes which is used to generate a set of fuzzy rules. Each rule represents a region in the feature space that we call the context of the rule. The rules are tuned with respect to their context. We justified that the reasoning scheme may be different in different context leading to context sensitive inferencing. To realize context sensitive inferencing we used a softmin operator with a tunable parameter. The proposed scheme is tested on several multispectral satellite image data sets and the performance is found to be much better than the results reported in the literature.


Land cover classification using fuzzy rules and aggregation of contextual information through evidence theory

Abstract: Land cover classification using multispectral satellite image is a very challenging task with numerous practical applications. We propose a multi-stage classifier that involves fuzzy rule extraction from the training data and then generation of a possibilistic label vector for each pixel using the fuzzy rule base. To exploit the spatial correlation of land cover types we propose four different information aggregation methods which use the possibilistic class label of a pixel and those of its eight spatial neighbors for making the final classification decision. Three of the aggregation methods use Dempster-Shafer theory of evidence while the remaining one is modeled after the fuzzy k-NN rule. The proposed methods are tested with two benchmark seven channel satellite images and the results are found to be quite satisfactory. They are also compared with a Markov random field (MRF) model-based contextual classification method and found to perform consistently better.


Interval edge colorings of some products of graphs

Abstract: An edge coloring of a graph $G$ with colors $1,2,\ldots ,t$ is called an interval $t$-coloring if for each $i\in \{1,2,\ldots,t\}$ there is at least one edge of $G$ colored by $i$, and the colors of edges incident to any vertex of $G$ are distinct and form an interval of integers. A graph $G$ is interval colorable, if there is an integer $t\geq 1$ for which $G$ has an interval $t$-coloring. Let $\mathfrak{N}$ be the set of all interval colorable graphs. In 2004 Kubale and Giaro showed that if $G,H\in \mathfrak{N}$, then the Cartesian product of these graphs belongs to $\mathfrak{N}$. Also, they formulated a similar problem for the lexicographic product as an open problem. In this paper we first show that if $G\in \mathfrak{N}$, then $G[nK_{1}]\in \mathfrak{N}$ for any $n\in \mathbf{N}$. Furthermore, we show that if $G,H\in \mathfrak{N}$ and $H$ is a regular graph, then strong and lexicographic products of graphs $G,H$ belong to $\mathfrak{N}$. We also prove that tensor and strong tensor products of graphs $G,H$ belong to $\mathfrak{N}$ if $G\in \mathfrak{N}$ and $H$ is a regular graph.


Computation- and Space-Efficient Implementation of SSA

Abstract: The computational complexity of different steps of the basic SSA is discussed. It is shown that the use of the general-purpose "blackbox" routines (e.g. found in packages like LAPACK) leads to huge waste of time resources since the special Hankel structure of the trajectory matrix is not taken into account. We outline several state-of-the-art algorithms (for example, Lanczos-based truncated SVD) which can be modified to exploit the structure of the trajectory matrix. The key components here are hankel matrix-vector multiplication and hankelization operator. We show that both can be computed efficiently by the means of Fast Fourier Transform. The use of these methods yields the reduction of the worst-case computational complexity from O(N^3) to O(k N log(N)), where N is series length and k is the number of eigentriples desired.


Improved Algorithm for Degree Bounded Survivable Network Design Problem

Abstract: We consider the Degree-Bounded Survivable Network Design Problem: the objective is to find a minimum cost subgraph satisfying the given connectivity requirements as well as the degree bounds on the vertices. If we denote the upper bound on the degree of a vertex v by b(v), then we present an algorithm that finds a solution whose cost is at most twice the cost of the optimal solution while the degree of a degree constrained vertex v is at most 2b(v) + 2. This improves upon the results of Lau and Singh and that of Lau, Naor, Salavatipour and Singh.


A tight upper bound on the (2,1)-total labeling number of outerplanar graphs

Abstract: A $(2,1)$-total labeling of a graph $G$ is an assignment $f$ from the vertex set $V(G)$ and the edge set $E(G)$ to the set $\{0,1,...,k\}$ of nonnegative integers such that $|f(x)-f(y)|\ge 2$ if $x$ is a vertex and $y$ is an edge incident to $x$, and $|f(x)-f(y)|\ge 1$ if $x$ and $y$ are a pair of adjacent vertices or a pair of adjacent edges, for all $x$ and $y$ in $V(G)\cup E(G)$. The $(2,1)$-total labeling number $\lambda^T_2(G)$ of a graph $G$ is defined as the minimum $k$ among all possible assignments. In [D. Chen and W. Wang. (2,1)-Total labelling of outerplanar graphs. Discr. Appl. Math. 155, 2585--2593 (2007)], Chen and Wang conjectured that all outerplanar graphs $G$ satisfy $\lambda^T_2(G) \leq \Delta(G)+2$, where $\Delta(G)$ is the maximum degree of $G$, while they also showed that it is true for $G$ with $\Delta(G)\geq 5$. In this paper, we solve their conjecture completely, by proving that $\lambda^T_2(G) \leq \Delta(G)+2$ even in the case of $\Delta(G)\leq 4 $.


G3 : GENESIS software envrionment update

Abstract: GENESIS3 is the new version of the GENESIS software environment for musical creation by means of mass-interaction physics network modeling. It was designed, and developed from scratch, in hindsight of more than 10 years working on and using the previous version. We take the opportunity of this birth to provide in this article (1) an analysis of the peculiarities in GENESIS, aiming at highlighting its core ?software paradigm?; and (2) an update on the features of the new version as compared to the last.


A graph polynomial for independent sets of bipartite graphs

Abstract: We introduce a new graph polynomial that encodes interesting properties of graphs, for example, the number of matchings and the number of perfect matchings. Most importantly, for bipartite graphs the polynomial encodes the number of independent sets (#BIS). We analyze the complexity of exact evaluation of the polynomial at rational points and show that for most points exact evaluation is #P-hard (assuming the generalized Riemann hypothesis) and for the rest of the points exact evaluation is trivial. We conjecture that a natural Markov chain can be used to approximately evaluate the polynomial for a range of parameters. The conjecture, if true, would imply an approximate counting algorithm for #BIS, a problem shown, by [Dyer et al. 2004], to be complete (with respect to, so called, AP-reductions) for a rich logically defined sub-class of #P. We give a mild support for our conjecture by proving that the Markov chain is rapidly mixing on trees. As a by-product we show that the "single bond flip" Markov chain for the random cluster model is rapidly mixing on constant tree-width graphs.


Covering of ordinals

Abstract: The paper focuses on the structure of fundamental sequences of ordinals smaller than $\epsilon_0$. A first result is the construction of a monadic second-order formula identifying a given structure, whereas such a formula cannot exist for ordinals themselves. The structures are precisely classified in the pushdown hierarchy. Ordinals are also located in the hierarchy, and a direct presentation is given.


O-Minimal Hybrid Reachability Games

Abstract: In this paper, we consider reachability games over general hybrid systems, and distinguish between two possible observation frameworks for those games: either the precise dynamics of the system is seen by the players (this is the perfect observation framework), or only the starting point and the delays are known by the players (this is the partial observation framework). In the first more classical framework, we show that time-abstract bisimulation is not adequate for solving this problem, although it is sufficient in the case of timed automata . That is why we consider an other equivalence, namely the suffix equivalence based on the encoding of trajectories through words. We show that this suffix equivalence is in general a correct abstraction for games. We apply this result to o-minimal hybrid systems, and get decidability and computability results in this framework. For the second framework which assumes a partial observation of the dynamics of the system, we propose another abstraction, called the superword encoding, which is suitable to solve the games under that assumption. In that framework, we also provide decidability and computability results.


Statistical exponential families: A digest with flash cards

Abstract: This document describes concisely the ubiquitous class of exponential family distributions met in statistics. The first part recalls definitions and summarizes main properties and duality with Bregman divergences (all proofs are skipped). The second part lists decompositions and related formula of common exponential family distributions. We recall the Fisher-Rao-Riemannian geometries and the dual affine connection information geometries of statistical manifolds. It is intended to maintain and update this document and catalog by adding new distribution items.


Non-photorealistic image processing: an Impressionist rendering

Abstract: The paper describes an image processing for a non-photorealistic rendering. The algorithm is based on a random choice of a set of pixels from those ot the original image and substitution of them with colour spots. An iterative procedure is applied to cover, at a desired level, the canvas. The resulting effect mimics the impressionist painting and Pointillism.


Efficient Higher Order Derivatives of Objective Functions Composed of Matrix Operations

Abstract: This paper is concerned with the efficient evaluation of higher-order derivatives of functions $f$ that are composed of matrix operations. I.e., we want to compute the $D$-th derivative tensor $\nabla^D f(X) \in \mathbb R^{N^D}$, where $f:\mathbb R^{N} \to \mathbb R$ is given as an algorithm that consists of many matrix operations. We propose a method that is a combination of two well-known techniques from Algorithmic Differentiation (AD): univariate Taylor propagation on scalars (UTPS) and first-order forward and reverse on matrices. The combination leads to a technique that we would like to call univariate Taylor propagation on matrices (UTPM). The method inherits many desirable properties: It is easy to implement, it is very efficient and it returns not only $\nabla^D f$ but yields in the process also the derivatives $\nabla^d f$ for $d \leq D$. As performance test we compute the gradient $\nabla f(X)$ % and the Hessian $\nabla_A^2 f(A)$ by a combination of forward and reverse mode of $f(X) = \trace (X^{-1})$ in the reverse mode of AD for $X \in \mathbb R^{n \times n}$. We observe a speedup of about 100 compared to UTPS. Due to the nature of the method, the memory footprint is also small and therefore can be used to differentiate functions that are not accessible by standard methods due to limited physical memory.


Shortest Paths in Planar Graphs with Real Lengths in $O(n\log^2n/\log\log n)$ Time

Abstract: Given an $n$-vertex planar directed graph with real edge lengths and with no negative cycles, we show how to compute single-source shortest path distances in the graph in $O(n\log^2n/\log\log n)$ time with O(n) space. This is an improvement of a recent time bound of $O(n\log^2n)$ by Klein et al.


Efficient Fully-Compressed Sequence Representations

Abstract: We present a data structure that stores a sequence $s[1..n]$ over alphabet $[1..\sigma]$ in $n\Ho(s) + o(n)(\Ho(s){+}1)$ bits, where $\Ho(s)$ is the zero-order entropy of $s$. This structure supports the queries \access, \rank\ and \select, which are fundamental building blocks for many other compressed data structures, in worst-case time $\Oh{\lg\lg\sigma}$ and average time $\Oh{\lg \Ho(s)}$. The worst-case complexity matches the best previous results, yet these had been achieved with data structures using $n\Ho(s)+o(n\lg\sigma)$ bits. On highly compressible sequences the $o(n\lg\sigma)$ bits of the redundancy may be significant compared to the the $n\Ho(s)$ bits that encode the data. Our representation, instead, compresses the redundancy as well. Moreover, our average-case complexity is unprecedented. Our technique is based on partitioning the alphabet into characters of similar frequency. The subsequence corresponding to each group can then be encoded using fast uncompressed representations without harming the overall compression ratios, even in the redundancy. The result also improves upon the best current compressed representations of several other data structures. For example, we achieve $(i)$ compressed redundancy, retaining the best time complexities, for the smallest existing full-text self-indexes; $(ii)$ compressed permutations $\pi$ with times for $\pi()$ and $\pii()$ improved to loglogarithmic; and $(iii)$ the first compressed representation of dynamic collections of disjoint sets. We also point out various applications to inverted indexes, suffix arrays, binary relations, and data compressors. ...


New Solutions to the Firing Squad Synchronization Problems for Neural and Hyperdag P Systems

Abstract: We propose two uniform solutions to an open question: the Firing Squad Synchronization Problem (FSSP), for hyperdag and symmetric neural P systems, with anonymous cells. Our solutions take e_c+5 and 6e_c+7 steps, respectively, where e_c is the eccentricity of the commander cell of the dag or digraph underlying these P systems. The first and fast solution is based on a novel proposal, which dynamically extends P systems with mobile channels. The second solution is substantially longer, but is solely based on classical rules and static channels. In contrast to the previous solutions, which work for tree-based P systems, our solutions synchronize to any subset of the underlying digraph; and do not require membrane polarizations or conditional rules, but require states, as typically used in hyperdag and neural P systems.


Drip and Mate Operations Acting in Test Tube Systems and Tissue-like P systems

Abstract: The operations drip and mate considered in (mem)brane computing resemble the operations cut and recombination well known from DNA computing. We here consider sets of vesicles with multisets of objects on their outside membrane interacting by drip and mate in two different setups: in test tube systems, the vesicles may pass from one tube to another one provided they fulfill specific constraints; in tissue-like P systems, the vesicles are immediately passed to specified cells after having undergone a drip or mate operation. In both variants, computational completeness can be obtained, yet with different constraints for the drip and mate operations.


Dependencies and Simultaneity in Membrane Systems

Abstract: Membrane system computations proceed in a synchronous fashion: at each step all the applicable rules are actually applied. Hence each step depends on the previous one. This coarse view can be refined by looking at the dependencies among rule occurrences, by recording, for an object, which was the a rule that produced it and subsequently (in a later step), which was the a rule that consumed it. In this paper we propose a way to look also at the other main ingredient in membrane system computations, namely the simultaneity in the rule applications. This is achieved using zero-safe nets that allows to synchronize transitions, i.e., rule occurrences. Zero-safe nets can be unfolded into occurrence nets in a classical way, and to this unfolding an event structure can be associated. The capability of capturing simultaneity of zero-safe nets is transferred on the level of event structure by adding a way to express which events occur simultaneously.


Querying Two Boundary Points for Shortest Paths in a Polygonal Domain

Abstract: We consider a variant of two-point Euclidean shortest path query problem: given a polygonal domain, build a data structure for two-point shortest path query, provided that query points always lie on the boundary of the domain. As a main result, we show that a logarithmic-time query for shortest paths between boundary points can be performed using O~ (n^5) preprocessing time and O(n^5) space where n is the number of corners of the polygonal domain and the O~ notation suppresses the polylogarithmic factor. This is realized by observing a connection between Davenport-Schinzel sequences and our problem in the parameterized space. We also provide a tradeoff between space and query time; a sublinear time query is possible using O(n^{3+epsilon}) space. Our approach also extends to the case where query points should lie on a given set of line segments.


Autosolvability of halting problem instances for instruction sequences

Abstract: We position Turing's result regarding the undecidability of the halting problem as a result about programs rather than machines. The mere requirement that a program of a certain kind must solve the halting problem for all programs of that kind leads to a contradiction in the case of a recent unsolvability result regarding the halting problem for programs. In this paper, we investigate this autosolvability requirement in a setting in which programs take the form of instruction sequences.


Time-domain approach to energy efficiency in high-performance network element design

Abstract: Energy efficiency is a corner stone of sustainability in data center and high-performance networking. However, at present there is a notable structural mismatch between network silicon development targets and network equipment utilization patterns in the field. In particular, some aspects of network energy utilization (eg load-proportional energy consumption) routinely stay out of focus during system design and implementation. Drawing from hands-on research and development in high-speed and grid networking, we identify a novel approach to energy efficiency in network engineering. In this paper, we demonstrate how the problem of efficient network system design can be dissected into smaller sections based on timescales of traffic processing. The newly proposed approach allows R&D efforts to be tightly paired to resources and sustainability targets to improve energy efficiency in many classes of network and telecom devices.


An $O(n^2)$ Algorithm for Computing Longest Common Cyclic Subsequence

Abstract: The {\em longest common subsequence (LCS)} problem is a classic and well-studied problem in computer science. LCS is a central problem in stringology and finds broad applications in text compression, error-detecting codes and biological sequence comparison. However, in numerous contexts, words represent cyclic sequences of symbols and LCS must be generalized to consider all circular shifts of the strings. This occurs especially in computational biology when genetic material is sequenced form circular DNA or RNA molecules. This initiates the problem of {\em longest common cyclic subsequence (LCCS)} which finds the longest subsequence between all circular shifts of two strings. In this paper, we give an $O(n^2)$ algorithm for solving LCCS problem where $n$ is the number of symbols in the strings.


A Semantic Similarity Measure for Expressive Description Logics

Abstract: A totally semantic measure is presented which is able to calculate a similarity value between concept descriptions and also between concept description and individual or between individuals expressed in an expressive description logic. It is applicable on symbolic descriptions although it uses a numeric approach for the calculus. Considering that Description Logics stand as the theoretic framework for the ontological knowledge representation and reasoning, the proposed measure can be effectively used for agglomerative and divisional clustering task applied to the semantic web domain.


Integrating the Probabilistic Models BM25/BM25F into Lucene

Abstract: This document describes the BM25 and BM25F implementation using the Lucene Java Framework. Both models have stood out at TREC by their performance and are considered as state-of-the-art in the IR community. BM25 is applied to retrieval on plain text documents, that is for documents that do not contain fields, while BM25F is applied to documents with structure.


Faster FAST(Feedback Arc Set in Tournaments)

Abstract: We present an algorithm that finds a feedback arc set of size $k$ in a tournament in time $n^{O(1)}2^{O(\sqrt{k})}$. This is asymptotically faster than the running time of previously known algorithms for this problem.


A Bayesian Rule for Adaptive Control based on Causal Interventions

Abstract: Explaining adaptive behavior is a central problem in artificial intelligence research. Here we formalize adaptive agents as mixture distributions over sequences of inputs and outputs (I/O). Each distribution of the mixture constitutes a `possible world', but the agent does not know which of the possible worlds it is actually facing. The problem is to adapt the I/O stream in a way that is compatible with the true world. A natural measure of adaptation can be obtained by the Kullback-Leibler (KL) divergence between the I/O distribution of the true world and the I/O distribution expected by the agent that is uncertain about possible worlds. In the case of pure input streams, the Bayesian mixture provides a well-known solution for this problem. We show, however, that in the case of I/O streams this solution breaks down, because outputs are issued by the agent itself and require a different probabilistic syntax as provided by intervention calculus. Based on this calculus, we obtain a Bayesian control rule that allows modeling adaptive behavior with mixture distributions over I/O streams. This rule might allow for a novel approach to adaptive control based on a minimum KL-principle.


Standardization of the formal representation of lexical information for NLP

Abstract: A survey of dictionary models and formats is presented as well as a presentation of corresponding recent standardisation activities.


Approximation Schemes for Steiner Forest on Planar Graphs and Graphs of Bounded Treewidth

Abstract: We give the first polynomial-time approximation scheme (PTAS) for the Steiner forest problem on planar graphs and, more generally, on graphs of bounded genus. As a first step, we show how to build a Steiner forest spanner for such graphs. The crux of the process is a clustering procedure called prize-collecting clustering that breaks down the input instance into separate subinstances which are easier to handle; moreover, the terminals in different subinstances are far from each other. Each subinstance has a relatively inexpensive Steiner tree connecting all its terminals, and the subinstances can be solved (almost) separately. Another building block is a PTAS for Steiner forest on graphs of bounded treewidth. Surprisingly, Steiner forest is NP-hard even on graphs of treewidth 3. Therefore, our PTAS for bounded treewidth graph needs a nontrivial combination of approximation arguments and dynamic programming on the tree decomposition. We further show that Steiner forest can be solved in polynomial time for series-parallel graphs (graphs of treewidth at most two) by a novel combination of dynamic programming and minimum cut computations, completing our thorough complexity study of Steiner forest in the range of bounded treewidth graphs, planar graphs, and bounded genus graphs.


Self-Reference Ultra-Wideband Systems

Abstract: Towards employing low complexity transceivers for signal reception in Ultra-Wideband (UWB) systems, Transmitted Reference (TR) and Differential TR (DTR) schemes have attracted researchers attention. In this letter, we introduce an alternative, less complex scheme, called Self Reference (SR) UWB transceiver, which uses a modified replica of the received signal itself as reference pulse, resulting in double data rates compared to TR schemes. Moreover, SR eliminates the need for delay lines at the receiver side, which constitute a major drawback of the conventional TR and DTR schemes, while it also requires no channel estimations, resulting in lower complexity implementations and power savings. The performance of the SR scheme is investigated in high-frequency (HF) channels, showing that it offers a better or comparable performance to that of DTR, depending on the channel conditions.


Analyzing Midpoint Subdivision

Abstract: Midpoint subdivision generalizes the Lane-Riesenfeld algorithm for uniform tensor product splines and can also be applied to non regular meshes. For example, midpoint subdivision of degree 2 is a specific Doo-Sabin algorithm and midpoint subdivision of degree 3 is a specific Catmull-Clark algorithm. In 2001, Zorin and Schroeder were able to prove C1-continuity for midpoint subdivision surfaces analytically up to degree 9. Here, we develop general analysis tools to show that the limiting surfaces under midpoint subdivision of any degree >= 2 are C1-continuous at their extraordinary points.


Untangling Phase and Time in Monophonic Sounds

Abstract: We are looking for a mathematical model of monophonic sounds with independent time and phase dimensions. With such a model we can resynthesise a sound with arbitrarily modulated frequency and progress of the timbre. We propose such a model and show that it exactly fulfils some natural properties, like a kind of time-invariance, robustness against non-harmonic frequencies, envelope preservation, and inclusion of plain resampling as a special case. The resulting algorithm is efficient and allows to process data in a streaming manner with phase and shape modulation at sample rate, what we demonstrate with an implementation in the functional language Haskell. It allows a wide range of applications, namely pitch shifting and time scaling, creative FM synthesis effects, compression of monophonic sounds, generating loops for sampled sounds, synthesise sounds similar to wavetable synthesis, or making ultrasound audible.


An Implementation of the Language Lambda Prolog Organized around Higher-Order Pattern Unification

Abstract: This thesis concerns the implementation of Lambda Prolog, a higher-order logic programming language that supports the lambda-tree syntax approach to representing and manipulating formal syntactic objects. Lambda Prolog achieves its functionality by extending a Prolog-like language by using typed lambda terms as data structures that it then manipulates via higher-order unification and some new program-level abstraction mechanisms. These additional features raise new implementation questions that must be adequately addressed for Lambda Prolog to be an effective programming tool. We consider these questions here, providing eventually a virtual machine and compilation based realization. A key idea is the orientation of the computation model of Lambda Prolog around a restricted version of higher-order unification with nice algorithmic properties and appearing to encompass most interesting applications. Our virtual machine embeds a treatment of this form of unification within the structure of the Warren Abstract Machine that is used in traditional Prolog implementations. Along the way, we treat various auxiliary issues such as the low-level representation of lambda terms, the implementation of reduction on such terms and the optimized processing of types in computation. We also develop an actual implementation of Lambda Prolog called Teyjus Version 2. A characteristic of this system is that it realizes an emulator for the virtual machine in the C language a compiler in the OCaml language. We present a treatment of the software issues that arise from this kind of mixing of languages within one system and we discuss issues relevant to the portability of our virtual machine emulator across arbitrary architectures. Finally, we assess the the efficacy of our various design ideas through experiments carried out using the system.


PAKE-based mutual HTTP authentication for preventing phishing attacks

Abstract: This paper describes a new password-based mutual authentication protocol for Web systems which prevents various kinds of phishing attacks. This protocol provides a protection of user's passwords against any phishers even if dictionary attack is employed, and prevents phishers from imitating a false sense of successful authentication to users. The protocol is designed considering interoperability with many recent Web applications which requires many features which current HTTP authentication does not provide. The protocol is proposed as an Internet Draft submitted to IETF, and implemented in both server side (as an Apache extension) and client side (as a Mozilla-based browser and an IE-based one). The paper also proposes a new user-interface for this protocol which is always distinguishable from fake dialogs provided by phishers.


Complex Algebras of Arithmetic

Abstract: An 'arithmetic circuit' is a labeled, acyclic directed graph specifying a sequence of arithmetic and logical operations to be performed on sets of natural numbers. Arithmetic circuits can also be viewed as the elements of the smallest subalgebra of the complex algebra of the semiring of natural numbers. In the present paper, we investigate the algebraic structure of complex algebras of natural numbers, and make some observations regarding the complexity of various theories of such algebras.


A note on upper bounds for the maximum span in interval edge colorings of graphs

Abstract: An edge coloring of a graph $G$ with colors $1,2,..., t$ is called an interval $t$-coloring if for each $i\in \{1,2,...,t\}$ there is at least one edge of $G$ colored by $i$, the colors of edges incident to any vertex of $G$ are distinct and form an interval of integers. In 1994 Asratian and Kamalian proved that if a connected graph $G$ admits an interval $t$-coloring, then $t\leq (d+1) (\Delta -1) +1$, and if $G$ is also bipartite, then this upper bound can be improved to $t\leq d(\Delta -1) +1$, where $\Delta$ is the maximum degree in $G$ and $d$ is the diameter of $G$. In this paper we show that these upper bounds can not be significantly improved.


Quantifying Resource Use in Computations

Abstract: It is currently not possible to quantify the resources needed to perform a computation. As a consequence, it is not possible to reliably evaluate the hardware resources needed for the application of algorithms or the running of programs. This is apparent in both computer science, for instance, in cryptanalysis, and in neuroscience, for instance, comparative neuro-anatomy. A System versus Environment game formalism is proposed based on Computability Logic that allows to define a computational work function that describes the theoretical and physical resources needed to perform any purely algorithmic computation. Within this formalism, the cost of a computation is defined as the sum of information storage over the steps of the computation. The size of the computational device, eg, the action table of a Universal Turing Machine, the number of transistors in silicon, or the number and complexity of synapses in a neural net, is explicitly included in the computational cost. The proposed cost function leads in a natural way to known computational trade-offs and can be used to estimate the computational capacity of real silicon hardware and neural nets. The theory is applied to a historical case of 56 bit DES key recovery, as an example of application to cryptanalysis. Furthermore, the relative computational capacities of human brain neurons and the C. elegans nervous system are estimated as an example of application to neural nets.


Maximin affinity learning of image segmentation

Abstract: Images can be segmented by first using a classifier to predict an affinity graph that reflects the degree to which image pixels must be grouped together and then partitioning the graph to yield a segmentation. Machine learning has been applied to the affinity classifier to produce affinity graphs that are good in the sense of minimizing edge misclassification rates. However, this error measure is only indirectly related to the quality of segmentations produced by ultimately partitioning the affinity graph. We present the first machine learning algorithm for training a classifier to produce affinity graphs that are good in the sense of producing segmentations that directly minimize the Rand index, a well known segmentation performance measure. The Rand index measures segmentation performance by quantifying the classification of the connectivity of image pixel pairs after segmentation. By using the simple graph partitioning algorithm of finding the connected components of the thresholded affinity graph, we are able to train an affinity classifier to directly minimize the Rand index of segmentations resulting from the graph partitioning. Our learning algorithm corresponds to the learning of maximin affinities between image pixel pairs, which are predictive of the pixel-pair connectivity.


De la recherche sociale d'information \`a la recherche collaborative d'information

Abstract: In this paper, we explain social information retrieval (SIR) and collaborative information retrieval (CIR). We see SIR as a way of knowing who to collaborate with in resolving an information problem while CIR entails the process of mutual understanding and solving of an information problem among collaborators. We are interested in the transition from SIR to CIR hence we developed a communication model to facilitate knowledge sharing during CIR.


Note on Max Lin-2 above Average

Abstract: In the Max Lin-2 problem we are given a system $S$ of $m$ linear equations in $n$ variables over $\mathbb{F}_2$ in which Equation $j$ is assigned a positive integral weight $w_j$ for each $j$. We wish to find an assignment of values to the variables which maximizes the total weight of satisfied equations. This problem generalizes Max Cut. The expected weight of satisfied equations is $W/2$, where $W=w_1+... +w_m$; $W/2$ is a tight lower bound on the optimal solution of Max Lin-2. Mahajan et al. (J. Comput. Syst. Sci. 75, 2009) stated the following parameterized version of Max Lin-2: decide whether there is an assignment of values to the variables that satisfies equations of total weight at least $W/2+k$, where $k$ is the parameter. They asked whether this parameterized problem is fixed-parameter tractable, i.e., can be solved in time $f(k)(nm)^{O(1)}$, where $f(k)$ is an arbitrary computable function in $k$ only. Their question remains open, but using some probabilistic inequalities and, in one case, a Fourier analysis inequality, Gutin et al. (IWPEC 2009) proved that the problem is fixed-parameter tractable in three special cases. In this paper we significantly extend two of the three special cases using only tools from combinatorics. We show that one of our results can be used to obtain a combinatorial proof that another problem from Mahajan et al. (J. Comput. Syst. Sci. 75, 2009), Max $r$-SAT above the Average, is fixed-parameter tractable for each $r\ge 2.$ Note that Max $r$-SAT above the Average has been already shown to be fixed-parameter tractable by Alon et al. (SODA 2010), but the paper used the approach of Gutin et al. (IWPEC 2009).


Covering rough sets based on neighborhoods: An approach without using neighborhoods

Abstract: Rough set theory, a mathematical tool to deal with inexact or uncertain knowledge in information systems, has originally described the indiscernibility of elements by equivalence relations. Covering rough sets are a natural extension of classical rough sets by relaxing the partitions arising from equivalence relations to coverings. Recently, some topological concepts such as neighborhood have been applied to covering rough sets. In this paper, we further investigate the covering rough sets based on neighborhoods by approximation operations. We show that the upper approximation based on neighborhoods can be defined equivalently without using neighborhoods. To analyze the coverings themselves, we introduce unary and composition operations on coverings. A notion of homomorphismis provided to relate two covering approximation spaces. We also examine the properties of approximations preserved by the operations and homomorphisms, respectively.


An axiomatic approach to the roughness measure of rough sets

Abstract: In Pawlak's rough set theory, a set is approximated by a pair of lower and upper approximations. To measure numerically the roughness of an approximation, Pawlak introduced a quantitative measure of roughness by using the ratio of the cardinalities of the lower and upper approximations. Although the roughness measure is effective, it has the drawback of not being strictly monotonic with respect to the standard ordering on partitions. Recently, some improvements have been made by taking into account the granularity of partitions. In this paper, we approach the roughness measure in an axiomatic way. After axiomatically defining roughness measure and partition measure, we provide a unified construction of roughness measure, called strong Pawlak roughness measure, and then explore the properties of this measure. We show that the improved roughness measures in the literature are special instances of our strong Pawlak roughness measure and introduce three more strong Pawlak roughness measures as well. The advantage of our axiomatic approach is that some properties of a roughness measure follow immediately as soon as the measure satisfies the relevant axiomatic definition.


Laser Actuated Presentation System

Abstract: We present here a pattern sensitive PowerPoint presentation scheme. The presentation is actuated by simple patterns drawn on the presentation screen by a laser pointer. A specific pattern corresponds to a particular command required to operate the presentation. Laser spot on the screen is captured by a RGB webcam with a red filter mounted, and its location is identified at the blue layer of each captured frame by estimating the mean position of the pixels whose intensity is above a given threshold value. Measured Reliability, Accuracy and Latency of our system are 90%, 10 pixels (in the worst case) and 38 ms respectively.


Building and Installing a Hadoop/MapReduce Cluster from Commodity Components

Abstract: This tutorial presents a recipe for the construction of a compute cluster for processing large volumes of data, using cheap, easily available personal computer hardware (Intel/AMD based PCs) and freely available open source software (Ubuntu Linux, Apache Hadoop).


Choreographies with Secure Boxes and Compromised Principals

Abstract: We equip choreography-level session descriptions with a simple abstraction of a security infrastructure. Message components may be enclosed within (possibly nested) "boxes" annotated with the intended source and destination of those components. The boxes are to be implemented with cryptography. Strand spaces provide a semantics for these choreographies, in which some roles may be played by compromised principals. A skeleton is a partially ordered structure containing local behaviors (strands) executed by regular (non-compromised) principals. A skeleton is realized if it contains enough regular strands so that it could actually occur, in combination with any possible activity of compromised principals. It is delivery guaranteed (DG) realized if, in addition, every message transmitted to a regular participant is also delivered. We define a novel transition system on skeletons, in which the steps add regular strands. These steps solve tests, i.e. parts of the skeleton that could not occur without additional regular behavior. We prove three main results about the transition system. First, each minimal DG realized skeleton is reachable, using the transition system, from any skeleton it embeds. Second, if no step is possible from a skeleton A, then A is DG realized. Finally, if a DG realized B is accessible from A, then B is minimal. Thus, the transition system provides a systematic way to construct the possible behaviors of the choreography, in the presence of compromised principals.


Coordination via Interaction Constraints I: Local Logic

Abstract: Wegner describes coordination as constrained interaction. We take this approach literally and define a coordination model based on interaction constraints and partial, iterative and interactive constraint satisfaction. Our model captures behaviour described in terms of synchronisation and data flow constraints, plus various modes of interaction with the outside world provided by external constraint symbols, on-the-fly constraint generation, and coordination variables. Underlying our approach is an engine performing (partial) constraint satisfaction of the sets of constraints. Our model extends previous work on three counts: firstly, a more advanced notion of external interaction is offered; secondly, our approach enables local satisfaction of constraints with appropriate partial solutions, avoiding global synchronisation over the entire constraints set; and, as a consequence, constraint satisfaction can finally occur concurrently, and multiple parts of a set of constraints can be solved and interact with the outside world in an asynchronous manner, unless synchronisation is required by the constraints. This paper describes the underlying logic, which enables a notion of local solution, and relates this logic to the more global approach of our previous work based on classical logic.


Symbolic Implementation of Connectors in BIP

Abstract: BIP is a component framework for constructing systems by superposing three layers of modeling: Behavior, Interaction, and Priority. Behavior is represented by labeled transition systems communicating through ports. Interactions are sets of ports. A synchronization between components is possible through the interactions specified by a set of connectors. When several interactions are possible, priorities allow to restrict the non-determinism by choosing an interaction, which is maximal according to some given strict partial order. The BIP component framework has been implemented in a language and a tool-set. The execution of a BIP program is driven by a dedicated engine, which has access to the set of connectors and priority model of the program. A key performance issue is the computation of the set of possible interactions of the BIP program from a given state. Currently, the choice of the interaction to be executed involves a costly exploration of enumerative representations for connectors. This leads to a considerable overhead in execution times. In this paper, we propose a symbolic implementation of the execution model of BIP, which drastically reduces this overhead. The symbolic implementation is based on computing boolean representation for components, connectors, and priorities with an existing BDD package.


Integrated Structure and Semantics for Reo Connectors and Petri Nets

Abstract: In this paper, we present an integrated structural and behavioral model of Reo connectors and Petri nets, allowing a direct comparison of the two concurrency models. For this purpose, we introduce a notion of connectors which consist of a number of interconnected, user-defined primitives with fixed behavior. While the structure of connectors resembles hypergraphs, their semantics is given in terms of so-called port automata. We define both models in a categorical setting where composition operations can be elegantly defined and integrated. Specifically, we formalize structural gluings of connectors as pushouts, and joins of port automata as pullbacks. We then define a semantical functor from the connector to the port automata category which preserves this composition. We further show how to encode Reo connectors and Petri nets into this model and indicate applications to dynamic reconfigurations modeled using double pushout graph transformation.


Session Types at the Mirror

Abstract: We (re)define session types as projections of process behaviors with respect to the communication channels they use. In this setting, we give session types a semantics based on fair testing. The outcome is a unified theory of behavioral types that shares common aspects with conversation types and that encompass features of both dyadic and multi-party session types. The point of view we provide sheds light on the nature of session types and gives us a chance to reason about them in a framework where every notion, from well-typedness to the subtyping relation between session types, is semantically -rather than syntactically- grounded.


Pigment Melanin: Pattern for Iris Recognition

Abstract: Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, unavailable in Near-Infrared (NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible solution to observe such patterns may be provided by an adaptive procedure using a variational technique on the image histogram. To describe the patterns, a shape analysis method is used to derive feature-code for each subject. An important question is how much the melanin patterns, extracted from VL, are independent of iris texture in NIR. With this question in mind, the present investigation proposes fusion of features extracted from NIR and VL to boost the recognition performance. We have collected our own database (UTIRIS) consisting of both NIR and VL images of 158 eyes of 79 individuals. This investigation demonstrates that the proposed algorithm is highly sensitive to the patterns of cromophores and improves the iris recognition rate.


Approximating Partition Functions of Two-State Spin Systems

Abstract: Two-state spin systems is a classical topic in statistical physics. We consider the problem of computing the partition function of the systems on a bounded degree graph. Based on the self-avoiding tree, we prove the systems exhibits strong correlation decay under the condition that the absolute value of "inverse temperature" is small. Due to strong correlation decay property, an FPTAS for the partition function is presented under the same condition. This condition is sharp for Ising model.


Towards an embedding of Graph Transformation in Intuitionistic Linear Logic

Abstract: Linear logics have been shown to be able to embed both rewriting-based approaches and process calculi in a single, declarative framework. In this paper we are exploring the embedding of double-pushout graph transformations into quantified linear logic, leading to a Curry-Howard style isomorphism between graphs and transformations on one hand, formulas and proof terms on the other. With linear implication representing rules and reachability of graphs, and the tensor modelling parallel composition of graphs and transformations, we obtain a language able to encode graph transformation systems and their computations as well as reason about their properties.


Subsampling Mathematical Relaxations and Average-case Complexity

Abstract: We initiate a study of when the value of mathematical relaxations such as linear and semidefinite programs for constraint satisfaction problems (CSPs) is approximately preserved when restricting the instance to a sub-instance induced by a small random subsample of the variables. Let $C$ be a family of CSPs such as 3SAT, Max-Cut, etc., and let $\Pi$ be a relaxation for $C$, in the sense that for every instance $P\in C$, $\Pi(P)$ is an upper bound the maximum fraction of satisfiable constraints of $P$. Loosely speaking, we say that subsampling holds for $C$ and $\Pi$ if for every sufficiently dense instance $P \in C$ and every $\epsilon>0$, if we let $P'$ be the instance obtained by restricting $P$ to a sufficiently large constant number of variables, then $\Pi(P') \in (1\pm \epsilon)\Pi(P)$. We say that weak subsampling holds if the above guarantee is replaced with $\Pi(P')=1-\Theta(\gamma)$ whenever $\Pi(P)=1-\gamma$. We show: 1. Subsampling holds for the BasicLP and BasicSDP programs. BasicSDP is a variant of the relaxation considered by Raghavendra (2008), who showed it gives an optimal approximation factor for every CSP under the unique games conjecture. BasicLP is the linear programming analog of BasicSDP. 2. For tighter versions of BasicSDP obtained by adding additional constraints from the Lasserre hierarchy, weak subsampling holds for CSPs of unique games type. 3. There are non-unique CSPs for which even weak subsampling fails for the above tighter semidefinite programs. Also there are unique CSPs for which subsampling fails for the Sherali-Adams linear programming hierarchy. As a corollary of our weak subsampling for strong semidefinite programs, we obtain a polynomial-time algorithm to certify that random geometric graphs (of the type considered by Feige and Schechtman, 2002) of max-cut value $1-\gamma$ have a cut value at most $1-\gamma/10$.


A Decision-Optimization Approach to Quantum Mechanics and Game Theory

Abstract: The fundamental laws of quantum world upsets the logical foundation of classic physics. They are completely counter-intuitive with many bizarre behaviors. However, this paper shows that they may make sense from the perspective of a general decision-optimization principle for cooperation. This principle also offers a generalization of Nash equilibrium, a key concept in game theory, for better payoffs and stability of game playing.


Acquisition d'informations lexicales \`a partir de corpus C\'edric Messiant et Thierry Poibeau

Abstract: This paper is about automatic acquisition of lexical information from corpora, especially subcategorization acquisition.


Checkpointing vs. Migration for Post-Petascale Machines

Abstract: We craft a few scenarios for the execution of sequential and parallel jobs on future generation machines. Checkpointing or migration, which technique to choose?