Split decomposition and graph-labelled trees: characterizations and fully-dynamic algorithms for totally decomposable graphs

Abstract: In this paper, we revisit the split decomposition of graphs and give new combinatorial and algorithmic results for the class of totally decomposable graphs, also known as the distance hereditary graphs, and for two non-trivial subclasses, namely the cographs and the 3-leaf power graphs. Precisely, we give strutural and incremental characterizations, leading to optimal fully-dynamic recognition algorithms for vertex and edge modifications, for each of these classes. These results rely on a new framework to represent the split decomposition, namely the graph-labelled trees, which also captures the modular decomposition of graphs and thereby unify these two decompositions techniques. The point of the paper is to use bijections between these graph classes and trees whose nodes are labelled by cliques and stars. Doing so, we are also able to derive an intersection model for distance hereditary graphs, which answers an open problem.


1.25 Approximation Algorithm for the Steiner Tree Problem with Distances One and Two

Abstract: We give a 1.25 approximation algorithm for the Steiner Tree Problem with distances one and two, improving on the best known bound for that problem.


SOSEMANUK: a fast software-oriented stream cipher

Abstract: Sosemanuk is a new synchronous software-oriented stream cipher, corresponding to Profile 1 of the ECRYPT call for stream cipher primitives. Its key length is variable between 128 and 256 bits. It ac- commodates a 128-bit initial value. Any key length is claimed to achieve 128-bit security. The Sosemanuk cipher uses both some basic design principles from the stream cipher SNOW 2.0 and some transformations derived from the block cipher SERPENT. Sosemanuk aims at improv- ing SNOW 2.0 both from the security and from the efficiency points of view. Most notably, it uses a faster IV-setup procedure. It also requires a reduced amount of static data, yielding better performance on several architectures.


Unsatisfiable (k,(4*2^k/k))-CNF formulas

Abstract: A boolean formula in a conjuctive normal form is called a (k,s)-formula if every clause contains exactly k variables and every variable occurs in at most s clauses. We prove the existence of a (k, 4 * (2^k/k))-CNF formula which is unsatisfiable.


Disproving the Neighborhood Conjecture

Abstract: We study the following Maker/Breaker game. Maker and Breaker take turns in choosing vertices from a given n-uniform hypergraph F, with Maker going first. Maker's goal is to completely occupy a hyperedge and Breaker tries to avoid this. Beck conjectures that if the maximum neighborhood size of F is at most 2^(n-1) then Breaker has a winning strategy. We disprove this conjecture by establishing an n-uniform hypergraph with maximum neighborhood size 3*2^(n-3) where Maker has a winning strategy. Moreover, we show how to construct an n-uniform hypergraph with maximum degree 2^(n-1)/n where Maker has a winning strategy. Finally we show that each n-uniform hypergraph with maximum degree at most 2^(n-2)/(en) has a proper halving 2-coloring, which solves another open problem posed by Beck related to the Neighborhood Conjecture.


A global physician-oriented medical information system

Abstract: We propose to improve medical decision making and reduce global health care costs by employing a free Internet-based medical information system with two main target groups: practicing physicians and medical researchers. After acquiring patients' consent, physicians enter medical histories, physiological data and symptoms or disorders into the system; an integrated expert system can then assist in diagnosis and statistical software provides a list of the most promising treatment options and medications, tailored to the patient. Physicians later enter information about the outcomes of the chosen treatments, data the system uses to optimize future treatment recommendations. Medical researchers can analyze the aggregate data to compare various drugs or treatments in defined patient populations on a large scale.


Characterizing 1-Dof Henneberg-I graphs with efficient configuration spaces

Abstract: We define and study exact, efficient representations of realization spaces of a natural class of underconstrained 2D Euclidean Distance Constraint Systems(EDCS) or Frameworks based on 1-dof Henneberg-I graphs. Each representation corresponds to a choice of parameters and yields a different parametrized configuration space. Our notion of efficiency is based on the algebraic complexities of sampling the configuration space and of obtaining a realization from the sample (parametrized) configuration. Significantly, we give purely combinatorial characterizations that capture (i) the class of graphs that have efficient configuration spaces and (ii) the possible choices of representation parameters that yield efficient configuration spaces for a given graph. Our results automatically yield an efficient algorithm for sampling realizations, without missing extreme or boundary realizations. In addition, our results formally show that our definition of efficient configuration space is robust and that our characterizations are tight. We choose the class of 1-dof Henneberg-I graphs in order to take the next step in a systematic and graded program of combinatorial characterizations of efficient configuration spaces. In particular, the results presented here are the first characterizations that go beyond graphs that have connected and convex configuration spaces.


Visualization Optimization : Application to the RoboCup Rescue Domain

Abstract: In this paper we demonstrate the use of intelligent optimization methodologies on the visualization optimization of virtual / simulated environments. The problem of automatic selection of an optimized set of views, which better describes an on-going simulation over a virtual environment is addressed in the context of the RoboCup Rescue Simulation domain. A generic architecture for optimization is proposed and described. We outline the possible extensions of this architecture and argue on how several problems within the fields of Interactive Rendering and Visualization can benefit from it.


Modeling of Social Transitions Using Intelligent Systems

Abstract: In this study, we reproduce two new hybrid intelligent systems, involve three prominent intelligent computing and approximate reasoning methods: Self Organizing feature Map (SOM), Neruo-Fuzzy Inference System and Rough Set Theory (RST),called SONFIS and SORST. We show how our algorithms can be construed as a linkage of government-society interactions, where government catches various states of behaviors: solid (absolute) or flexible. So, transition of society, by changing of connectivity parameters (noise) from order to disorder is inferred.


On characterising strong bisimilarity in a fragment of CCS with replication

Abstract: We provide a characterisation of strong bisimilarity in a fragment of CCS that contains only prefix, parallel composition, synchronisation and a limited form of replication. The characterisation is not an axiomatisation, but is instead presented as a rewriting system. We discuss how our method allows us to derive a new congruence result in the $\pi$-calculus: congruence holds in the sub-calculus that does not include restriction nor sum, and features a limited form of replication. We have not formalised the latter result in all details.


Initial Offset Placement in p2p Live Streaming Systems

Abstract: Initial offset placement in p2p streaming systems is studied in this paper. Proportional placement (PP) scheme is proposed. In this scheme, peer places the initial offset as the offset reported by other reference peer with a shift proportional to the buffer width or offset lag of this reference peer. This will introduce a stable placement that supports larger buffer width for peers and small buffer width for tracker. Real deployed placement method in PPLive is studied through measurement. It shows that, instead of based on offset lag, the placement is based on buffer width of the reference peer to facilitate the initial chunk fetching. We will prove that, such a PP scheme may not be stable under arbitrary buffer occupation in the reference peer. The required average buffer width then is derived. A simple good peer selection mechanism to check the buffer occupation of reference peer is proposed for a stable PP scheme based on buffer width


Fetching Strategy in the Startup Stage of p2p Live Streaming

Abstract: A protocol named Threshold Bipolar (TB) is proposed as a fetching strategy at the startup stage of p2p live streaming systems. In this protocol, chunks are fetched consecutively from buffer head at the beginning. After the buffer is filled into a threshold, chunks at the buffer tail will be fetched first while keeping the contiguously filled part in the buffer above the threshold even when the buffer is drained at a playback rate. High download rate, small startup latency and natural strategy handover can be reached at the same time by this protocol. Important parameters in this protocol are identified. The buffer progress under this protocol is then expressed as piecewise lines specified by those parameters. Startup traces of peers measured from PPLive are studied to show the real performance of TB protocol in a real system. A simple design model of TB protocol is proposed to reveal important considerations in a practical design.


A Model for Communication in Clusters of Multi-core Machines

Abstract: A common paradigm for scientific computing is distributed message-passing systems, and a common approach to these systems is to implement them across clusters of high-performance workstations. As multi-core architectures become increasingly mainstream, these clusters are very likely to include multi-core machines. However, the theoretical models which are currently used to develop communication algorithms across these systems do not take into account the unique properties of processes running on shared-memory architectures, including shared external network connections and communication via shared memory locations. Because of this, existing algorithms are far from optimal for modern clusters. Additionally, recent attempts to adapt these algorithms to multicore systems have proceeded without the introduction of a more accurate formal model and have generally neglected to capitalize on the full power these systems offer. We propose a new model which simply and effectively captures the strengths of multi-core machines in collective communications patterns and suggest how it could be used to properly optimize these patterns.


A simple local 3-approximation algorithm for vertex cover

Abstract: We present a local algorithm (constant-time distributed algorithm) for finding a 3-approximate vertex cover in bounded-degree graphs. The algorithm is deterministic, and no auxiliary information besides port numbering is required.


Structural abstract interpretation, A formal study using Coq

Abstract: interpreters are tools to compute approximations for behaviors of a program. These approximations can then be used for optimisation or for error detection. In this paper, we show how to describe an abstract interpreter using the type-theory based theorem prover Coq, using inductive types for syntax and structural recursive programming for the abstract interpreter's kernel. The abstract interpreter can then be proved correct with respect to a Hoare logic for the programming language.


Enabling Lock-Free Concurrent Fine-Grain Access to Massive Distributed Data: Application to Supernovae Detection

Abstract: We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and accessed by concurrent clients. On each individual access, a segment of a string, of the order of Megabytes, is read or modified. Our goal is to provide the clients with efficient fine-grain access the data string as concurrently as possible, without locking the string itself. This issue is crucial in the context of applications in the field of astronomy, databases, data mining and multimedia. We illustrate these requiremens with the case of an application for searching supernovae. Our solution relies on distributed, RAM-based data storage, while leveraging a DHT-based, parallel metadata management scheme. The proposed architecture and algorithms have been validated through a software prototype and evaluated in a cluster environment.


Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme

Abstract: This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation provides promising results.


On finite functions with non-trivial arity gap

Abstract: Given an $n$-ary $k-$valued function $f$, $gap(f)$ denotes the minimal number of essential variables in $f$ which become fictive when identifying any two distinct essential variables in $f$. We particularly solve a problem concerning the explicit determination of $n$-ary $k-$valued functions $f$ with $2\leq gap(f)\leq n\leq k$. Our methods yield new combinatorial results about the number of such functions.


Non-Negative Matrix Factorization, Convexity and Isometry

Abstract: In this paper we explore avenues for improving the reliability of dimensionality reduction methods such as Non-Negative Matrix Factorization (NMF) as interpretive exploratory data analysis tools. We first explore the difficulties of the optimization problem underlying NMF, showing for the first time that non-trivial NMF solutions always exist and that the optimization problem is actually convex, by using the theory of Completely Positive Factorization. We subsequently explore four novel approaches to finding globally-optimal NMF solutions using various ideas from convex optimization. We then develop a new method, isometric NMF (isoNMF), which preserves non-negativity while also providing an isometric embedding, simultaneously achieving two properties which are helpful for interpretation. Though it results in a more difficult optimization problem, we show experimentally that the resulting method is scalable and even achieves more compact spectra than standard NMF.


Efficient Pattern Matching on Binary Strings

Abstract: The binary string matching problem consists in finding all the occurrences of a pattern in a text where both strings are built on a binary alphabet. This is an interesting problem in computer science, since binary data are omnipresent in telecom and computer network applications. Moreover the problem finds applications also in the field of image processing and in pattern matching on compressed texts. Recently it has been shown that adaptations of classical exact string matching algorithms are not very efficient on binary data. In this paper we present two efficient algorithms for the problem adapted to completely avoid any reference to bits allowing to process pattern and text byte by byte. Experimental results show that the new algorithms outperform existing solutions in most cases.


Faster and better: a machine learning approach to corner detection

Abstract: The repeatability and efficiency of a corner detector determines how likely it is to be useful in a real-world application. The repeatability is importand because the same scene viewed from different positions should yield features which correspond to the same real-world 3D locations [Schmid et al 2000]. The efficiency is important because this determines whether the detector combined with further processing can operate at frame rate. Three advances are described in this paper. First, we present a new heuristic for feature detection, and using machine learning we derive a feature detector from this which can fully process live PAL video using less than 5% of the available processing time. By comparison, most other detectors cannot even operate at frame rate (Harris detector 115%, SIFT 195%). Second, we generalize the detector, allowing it to be optimized for repeatability, with little loss of efficiency. Third, we carry out a rigorous comparison of corner detectors based on the above repeatability criterion applied to 3D scenes. We show that despite being principally constructed for speed, on these stringent tests, our heuristic detector significantly outperforms existing feature detectors. Finally, the comparison demonstrates that using machine learning produces significant improvements in repeatability, yielding a detector that is both very fast and very high quality.


Dynamic assignment: there is an equilibrium !

Abstract: Given a network with a continuum of users at some origins, suppose that the users wish to reach specific destinations, but that they are not indifferent to the time needed to reach their destination. They may have several possibilities (of routes or deparure time), but their choices modify the travel times on the network. Hence, each user faces the following problem: given a pattern of travel times for the different possible routes that reach the destination, find a shortest path. The situation in a context of perfect information is a so-called Nash equilibrium, and the question whether there is such an equilibrium and of finding it if it exists is the so-called equilibrium assignment problem. It arises for various kind of networks, such as computers, communication or transportation network. When each user occupies permanently the whole route from the origin to its destination, we call it the static assignment problem, which has been extensively studied with pioneers works by Wardrop or Beckmann. A less studied, but more realistic, and maybe more difficult, problem is when the time needed to reach an arc is taken into account. We speak then of a dynamic assignment problem. Several models have been proposed. For some of them, the existence of an equilibrium has been proved, but always under some technical assumptions or in a very special case (a network with one arc for the case when the users may chose their departure time). The present paper proposes a compact model, with minimal and natural assumptions. For this model, we prove that there is always an equilibrium. To our knowledge, this imply all previous results about existence of an equilibrium for the dynamic assignment problem.


On combinations of local theory extensions

Abstract: In this paper we study possibilities of efficient reasoning in combinations of theories over possibly non-disjoint signatures. We first present a class of theory extensions (called local extensions) in which hierarchical reasoning is possible, and give several examples from computer science and mathematics in which such extensions occur in a natural way. We then identify situations in which combinations of local extensions of a theory are again local extensions of that theory. We thus obtain criteria both for recognizing wider classes of local theory extensions, and for modular reasoning in combinations of theories over non-disjoint signatures.


DSTC Layering Protocols in Wireless Cooperative Networks

Abstract: In a radio network with single source-destination pair and some relays, a link between any two nodes is considered to have same or zero path loss. However in practice some links may have considerably high path loss than others but still being useful. In this report, we take into account signals received from these links also. \indent Our system model consists of a source-destination pair with two layers of relays in which weaker links between source and second layer and between the first layer and destination are also considered. We propose some protocols in this system model, run simulations under optimum power allocation, and compare these protocols. We show that under reasonable channel strength of these weaker links, the proposed protocols perform ($ \approx 2$ dB) better than the existing basic protocol. As expected, the degree of improvement increases with the strength of the weaker links. We also show that with the receive channel knowledge in relays, the reliability and data rate are improved.


Path Planner for Objects, Robots and Mannequins by Multi-Agents Systems or Motion Captures

Abstract: In order to optimise the costs and time of design of the new products while improving their quality, concurrent engineering is based on the digital model of these products. However, in order to be able to avoid definitively physical model without loss of information, new tools must be available. Especially, a tool making it possible to check simply and quickly the maintainability of complex mechanical sets using the numerical model is necessary. Since one decade, the MCM team of IRCCyN works on the creation of tools for the generation and the analysis of trajectories of virtual mannequins. The simulation of human tasks can be carried out either by robot-like simulation or by simulation by motion capture. This paper presents some results on the both two methods. The first method is based on a multi-agent system and on a digital mock-up technology, to assess an efficient path planner for a manikin or a robot for access and visibility task taking into account ergonomic constraints or joint limits. The human operator is integrated in the process optimisation to contribute to a global perception of the environment. This operator cooperates, in real-time, with several automatic local elementary agents. In the second method, we worked with the CEA and EADS/CCR to solve the constraints related to the evolution of human virtual in its environment on the basis of data resulting from motion capture system. An approach using of the virtual guides was developed to allow to the user the realization of precise trajectory in absence of force feedback.


A Vision-based Computed Torque Control for Parallel Kinematic Machines

Abstract: In this paper, a novel approach for parallel kinematic machine control relying on a fast exteroceptive measure is implemented and validated on the Orthoglide robot. This approach begins with rewriting the robot models as a function of the only end-effector pose. It is shown that such an operation reduces the model complexity. Then, this approach uses a classical Cartesian space computed torque control with a fast exteroceptive measure, reducing the control schemes complexity. Simulation results are given to show the expected performance improvements and experiments prove the practical feasibility of the approach.


On the cubicity of bipartite graphs

Abstract: {\it A unit cube in $k$-dimension (or a $k$-cube) is defined as the cartesian product $R_1 \times R_2 \times ... \times R_k$, where each $R_i$ is a closed interval on the real line of the form $[a_i, a_i+1]$. The {\it cubicity} of $G$, denoted as $cub(G)$, is the minimum $k$ such that $G$ is the intersection graph of a collection of $k$-cubes. Many NP-complete graph problems can be solved efficiently or have good approximation ratios in graphs of low cubicity. In most of these cases the first step is to get a low dimensional cube representation of the given graph. It is known that for a graph $G$, $cub(G) \leq \lfloor\frac{2n}{3}\rfloor$. Recently it has been shown that for a graph $G$, $cub(G) \leq 4(\Delta + 1)\ln n$, where $n$ and $\Delta$ are the number of vertices and maximum degree of $G$, respectively. In this paper, we show that for a bipartite graph $G = (A \cup B, E)$ with $|A| = n_1$, $|B| = n_2$, $n_1 \leq n_2$, and $\Delta' = \min\{\Delta_A, \Delta_B\}$, where $\Delta_A = {max}_{a \in A}d(a)$ and $\Delta_B = {max}_{b \in B}d(b)$, $d(a)$ and $d(b)$ being the degree of $a$ and $b$ in $G$ respectively, $cub(G) \leq 2(\Delta'+2) \lceil \ln n_2 \rceil$. We also give an efficient randomized algorithm to construct the cube representation of $G$ in $3(\Delta'+2)\lceil \ln n_2 \rceil$ dimensions. The reader may note that in general $\Delta'$ can be much smaller than $\Delta$.}


A Simple Linear Ranking Algorithm Using Query Dependent Intercept Variables

Abstract: The LETOR website contains three information retrieval datasets used as a benchmark for testing machine learning ideas for ranking. Algorithms participating in the challenge are required to assign score values to search results for a collection of queries, and are measured using standard IR ranking measures (NDCG, precision, MAP) that depend only the relative score-induced order of the results. Similarly to many of the ideas proposed in the participating algorithms, we train a linear classifier. In contrast with other participating algorithms, we define an additional free variable (intercept, or benchmark) for each query. This allows expressing the fact that results for different queries are incomparable for the purpose of determining relevance. The cost of this idea is the addition of relatively few nuisance parameters. Our approach is simple, and we used a standard logistic regression library to test it. The results beat the reported participating algorithms. Hence, it seems promising to combine our approach with other more complex ideas.


Adaptive Hybrid Deflection and Retransmission Routing for Optical Burst-Switched Networks

Abstract: Burst contention is a well known challenging problem in Optical Burst Switching (OBS) networks. Deflection routing is used to resolve contention. Burst retransmission is used to reduce the Burst Loss Ratio (BLR) by retransmitting dropped bursts. Previous works show that combining deflection and retransmission outperforms both pure deflection and pure retransmission approaches. This paper proposes a new Adaptive Hybrid Deflection and Retransmission (AHDR) approach that dynamically combines deflection and retransmission approaches based on network conditions such as BLR and link utilization. Network Simulator 2 (ns-2) is used to simulate the proposed approach on different network topologies. Simulation results show that the proposed approach outperforms static approaches in terms of BLR and goodput.


A comparison of the notions of optimality in soft constraints and graphical games

Abstract: The notion of optimality naturally arises in many areas of applied mathematics and computer science concerned with decision making. Here we consider this notion in the context of two formalisms used for different purposes and in different research areas: graphical games and soft constraints. We relate the notion of optimality used in the area of soft constraint satisfaction problems (SCSPs) to that used in graphical games, showing that for a large class of SCSPs that includes weighted constraints every optimal solution corresponds to a Nash equilibrium that is also a Pareto efficient joint strategy.


Welfare Undominated Groves Mechanisms

Abstract: A common objective in mechanism design is to choose the outcome (for example, allocation of resources) that maximizes the sum of the agents' valuations, without introducing incentives for agents to misreport their preferences. The class of Groves mechanisms achieves this; however, these mechanisms require the agents to make payments, thereby reducing the agents' total welfare. In this paper we introduce a measure for comparing two mechanisms with respect to the final welfare they generate. This measure induces a partial order on mechanisms and we study the question of finding minimal elements with respect to this partial order. In particular, we say a non-deficit Groves mechanism is welfare undominated if there exists no other non-deficit Groves mechanism that always has a smaller or equal sum of payments. We focus on two domains: (i) auctions with multiple identical units and unit-demand bidders, and (ii) mechanisms for public project problems. In the first domain we analytically characterize all welfare undominated Groves mechanisms that are anonymous and have linear payment functions, by showing that the family of optimal-in-expectation linear redistribution mechanisms, which were introduced in [6] and include the Bailey-Cavallo mechanism [1,2], coincides with the family of welfare undominated Groves mechanisms that are anonymous and linear in the setting we study. In the second domain we show that the classic VCG (Clarke) mechanism is welfare undominated for the class of public project problems with equal participation costs, but is not undominated for a more general class.


Sheaves and geometric logic and applications to the modular verification of complex systems

Abstract: In this paper we show that states, transitions and behavior of concurrent systems can often be modeled as sheaves over a suitable topological space. In this context, geometric logic can be used to describe which local properties (i.e. properties of individual systems) are preserved, at a global level, when interconnecting the systems. The main area of application is to modular verification of complex systems. We illustrate the ideas by means of an example involving a family of interacting controllers for trains on a rail track.


Taming Modal Impredicativity: Superlazy Reduction

Abstract: Pure, or type-free, Linear Logic proof nets are Turing complete once cut-elimination is considered as computation. We introduce modal impredicativity as a new form of impredicativity causing the complexity of cut-elimination to be problematic from a complexity point of view. Modal impredicativity occurs when, during reduction, the conclusion of a residual of a box b interacts with a node that belongs to the proof net inside another residual of b. Technically speaking, superlazy reduction is a new notion of reduction that allows to control modal impredicativity. More specifically, superlazy reduction replicates a box only when all its copies are opened. This makes the overall cost of reducing a proof net finite and predictable. Specifically, superlazy reduction applied to any pure proof nets takes primitive recursive time. Moreover, any primitive recursive function can be computed by a pure proof net via superlazy reduction.


Iterated Regret Minimization: A More Realistic Solution Concept

Abstract: For some well-known games, such as the Traveler's Dilemma or the Centipede Game, traditional game-theoretic solution concepts--and most notably Nash equilibrium--predict outcomes that are not consistent with empirical observations. In this paper, we introduce a new solution concept, iterated regret minimization, which exhibits the same qualitative behavior as that observed in experiments in many games of interest, including Traveler's Dilemma, the Centipede Game, Nash bargaining, and Bertrand competition. As the name suggests, iterated regret minimization involves the iterated deletion of strategies that do not minimize regret.


Watermarking Digital Images Based on a Content Based Image Retrieval Technique

Abstract: The current work is focusing on the implementation of a robust watermarking algorithm for digital images, which is based on an innovative spread spectrum analysis algorithm for watermark embedding and on a content-based image retrieval technique for watermark detection. The highly robust watermark algorithms are applying "detectable watermarks" for which a detection mechanism checks if the watermark exists or no (a Boolean decision) based on a watermarking key. The problem is that the detection of a watermark in a digital image library containing thousands of images means that the watermark detection algorithm is necessary to apply all the keys to the digital images. This application is non-efficient for very large image databases. On the other hand "readable" watermarks may prove weaker but easier to detect as only the detection mechanism is required. The proposed watermarking algorithm combine's the advantages of both "detectable" and "readable" watermarks. The result is a fast and robust watermarking algorithm.


Combining Semantic Wikis and Controlled Natural Language

Abstract: We demonstrate AceWiki that is a semantic wiki using the controlled natural language Attempto Controlled English (ACE). The goal is to enable easy creation and modification of ontologies through the web. Texts in ACE can automatically be translated into first-order logic and other languages, for example OWL. Previous evaluation showed that ordinary people are able to use AceWiki without being instructed.


On the Complexity of Core, Kernel, and Bargaining Set

Abstract: Coalitional games are mathematical models suited to analyze scenarios where players can collaborate by forming coalitions in order to obtain higher worths than by acting in isolation. A fundamental problem for coalitional games is to single out the most desirable outcomes in terms of appropriate notions of worth distributions, which are usually called solution concepts. Motivated by the fact that decisions taken by realistic players cannot involve unbounded resources, recent computer science literature reconsidered the definition of such concepts by advocating the relevance of assessing the amount of resources needed for their computation in terms of their computational complexity. By following this avenue of research, the paper provides a complete picture of the complexity issues arising with three prominent solution concepts for coalitional games with transferable utility, namely, the core, the kernel, and the bargaining set, whenever the game worth-function is represented in some reasonable compact form (otherwise, if the worths of all coalitions are explicitly listed, the input sizes are so large that complexity problems are---artificially---trivial). The starting investigation point is the setting of graph games, about which various open questions were stated in the literature. The paper gives an answer to these questions, and in addition provides new insights on the setting, by characterizing the computational complexity of the three concepts in some relevant generalizations and specializations.


Clone Theory: Its Syntax and Semantics, Applications to Universal Algebra, Lambda Calculus and Algebraic Logic

Abstract: The primary goal of this paper is to present a unified way to transform the syntax of a logic system into certain initial algebraic structure so that it can be studied algebraically. The algebraic structures which one may choose for this purpose are various clones over a full subcategory of a category. We show that the syntax of equational logic, lambda calculus and first order logic can be represented as clones or right algebras of clones over the set of positive integers. The semantics is then represented by structures derived from left algebras of these clones.


Optimal Strategies in Sequential Bidding

Abstract: We are interested in mechanisms that maximize social welfare. In [1] this problem was studied for multi-unit auctions with unit demand bidders and for the public project problem, and in each case social welfare undominated mechanisms in the class of feasible and incentive compatible mechanisms were identified. One way to improve upon these optimality results is by allowing the players to move sequentially. With this in mind, we study here sequential versions of two feasible Groves mechanisms used for single item auctions: the Vickrey auction and the Bailey-Cavallo mechanism. Because of the absence of dominant strategies in this sequential setting, we focus on a weaker concept of an optimal strategy. For each mechanism we introduce natural optimal strategies and observe that in each mechanism these strategies exhibit different behaviour. However, we then show that among all optimal strategies, the one we introduce for each mechanism maximizes the social welfare when each player follows it. The resulting social welfare can be larger than the one obtained in the simultaneous setting. Finally, we show that, when interpreting both mechanisms as simultaneous ones, the vectors of the proposed strategies form a Pareto optimal Nash equilibrium in the class of optimal strategies.


A Distributed Platform for Mechanism Design

Abstract: We describe a structured system for distributed mechanism design. It consists of a sequence of layers. The lower layers deal with the operations relevant for distributed computing only, while the upper layers are concerned only with communication among players, including broadcasting and multicasting, and distributed decision making. This yields a highly flexible distributed system whose specific applications are realized as instances of its top layer. This design supports fault-tolerance, prevents manipulations and makes it possible to implement distributed policing. The system is implemented in Java. We illustrate it by discussing a number of implemented examples.


A cache-friendly truncated FFT

Abstract: We describe a cache-friendly version of van der Hoeven's truncated FFT and inverse truncated FFT, focusing on the case of `large' coefficients, such as those arising in the Schonhage--Strassen algorithm for multiplication in Z[x]. We describe two implementations and examine their performance.


Dynamic Approaches to In-Network Aggregation

Abstract: Collaboration between small-scale wireless devices hinges on their ability to infer properties shared across multiple nearby nodes. Wireless-enabled mobile devices in particular create a highly dynamic environment not conducive to distributed reasoning about such global properties. This paper addresses a specific instance of this problem: distributed aggregation. We present extensions to existing unstructured aggregation protocols that enable estimation of count, sum, and average aggregates in highly dynamic environments. With the modified protocols, devices with only limited connectivity can maintain estimates of the aggregate, despite \textit{unexpected} peer departures and arrivals. Our analysis of these aggregate maintenance extensions demonstrates their effectiveness in unstructured environments despite high levels of node mobility.


A static theory of promises

Abstract: We discuss for the concept of promises within a framework that can be applied to either humans or technology. We compare promises to the more established notion of obligations and find promises to be both simpler and more effective at reducing uncertainty in behavioural outcomes.


A sound spatio-temporal Hoare logic for the verification of structured interactive programs with registers and voices

Abstract: Interactive systems with registers and voices (shortly, "rv-systems") are a model for interactive computing obtained closing register machines with respect to a space-time duality transformation ("voices" are the time-dual counterparts of "registers"). In the same vain, AGAPIA v0.1, a structured programming language for rv-systems, is the space-time dual closure of classical while programs (over a specific type of data). Typical AGAPIA programs describe open processes located at various sites and having their temporal windows of adequate reaction to the environment. The language naturally supports process migration, structured interaction, and deployment of components on heterogeneous machines. In this paper a sound Hoare-like spatio-temporal logic for the verification of AGAPIA v0.1 programs is introduced. As a case study, a formal verification proof of a popular distributed termination detection protocol is presented.


Enhancements to A Lightweight RFID Authentication Protocol

Abstract: Vajda and Buttyan (VB) proposed a set of five lightweight RFID authentication protocols. Defend, Fu, and Juels (DFJ) did cryptanalysis on two of them - XOR and SUBSET. To the XOR protocol, DFJ proposed repeated keys attack and nibble attack. In this paper, we identify the vulnerability existed in the original VB's successive session key permutation algorithm. We propose three enhancements to prevent DFJ's attacks and make XOR protocol stronger without introducing extra resource cost.


The Fundamental Problem with the Building Block Hypothesis

Abstract: Skepticism of the building block hypothesis (BBH) has previously been expressed on account of the weak theoretical foundations of this hypothesis and the anomalies in the empirical record of the simple genetic algorithm. In this paper we hone in on a more fundamental cause for skepticism--the extraordinary strength of some of the assumptions that undergird the BBH. Specifically, we focus on assumptions made about the distribution of fitness over the genome set, and argue that these assumptions are unacceptably strong. As most of these assumptions have been embraced by the designers of so-called "competent" genetic algorithms, our critique is relevant to an appraisal of such algorithms as well.


Two Remarkable Computational Competencies of the Simple Genetic Algorithm

Abstract: Since the inception of genetic algorithmics the identification of computational efficiencies of the simple genetic algorithm (SGA) has been an important goal. In this paper we distinguish between a computational competency of the SGA--an efficient, but narrow computational ability--and a computational proficiency of the SGA--a computational ability that is both efficient and broad. Till date, attempts to deduce a computational proficiency of the SGA have been unsuccessful. It may, however, be possible to inductively infer a computational proficiency of the SGA from a set of related computational competencies that have been deduced. With this in mind we deduce two computational competencies of the SGA. These competencies, when considered together, point toward a remarkable computational proficiency of the SGA. This proficiency is pertinent to a general problem that is closely related to a well-known statistical problem at the cutting edge of computational genetics.


Detecting the Most Unusual Part of a Digital Image

Abstract: The purpose of this paper is to introduce an algorithm that can detect the most unusual part of a digital image. The most unusual part of a given shape is defined as a part of the image that has the maximal distance to all non intersecting shapes with the same form. The method can be used to scan image databases with no clear model of the interesting part or large image databases, as for example medical databases.


Efficient Algorithms and Routing Protocols for Handling Transient Single Node Failures

Abstract: Single node failures represent more than 85% of all node failures in the today's large communication networks such as the Internet. Also, these node failures are usually transient. Consequently, having the routing paths globally recomputed does not pay off since the failed nodes recover fairly quickly, and the recomputed routing paths need to be discarded. Instead, we develop algorithms and protocols for dealing with such transient single node failures by suppressing the failure (instead of advertising it across the network), and routing messages to the destination via alternate paths that do not use the failed node. We compare our solution to that of Ref. [11] wherein the authors have presented a "Failure Insensitive Routing" protocol as a proactive recovery scheme for handling transient node failures. We show that our algorithms are faster by an order of magnitude while our paths are equally good. We show via simulation results that our paths are usually within 15% of the optimal for randomly generated graph with 100-1000 nodes.


The many faces of optimism - Extended version

Abstract: The exploration-exploitation dilemma has been an intriguing and unsolved problem within the framework of reinforcement learning. "Optimism in the face of uncertainty" and model building play central roles in advanced exploration methods. Here, we integrate several concepts and obtain a fast and simple algorithm. We show that the proposed algorithm finds a near-optimal policy in polynomial time, and give experimental evidence that it is robust and efficient compared to its ascendants.


A Call-Graph Profiler for GNU Octave

Abstract: We report the design and implementation of a call-graph profiler for GNU Octave, a numerical computing platform. GNU Octave simplifies matrix computation for use in modeling or simulation. Our work provides a call-graph profiler, which is an improvement on the flat profiler. We elaborate design constraints of building a profiler for numerical computation, and benchmark the profiler by comparing it to the rudimentary timer start-stop (tic-toc) measurements, for a similar set of programs. The profiler code provides clean interfaces to internals of GNU Octave, for other (newer) profiling tools on GNU Octave.


Social Learning Methods in Board Games

Abstract: This paper discusses the effects of social learning in training of game playing agents. The training of agents in a social context instead of a self-play environment is investigated. Agents that use the reinforcement learning algorithms are trained in social settings. This mimics the way in which players of board games such as scrabble and chess mentor each other in their clubs. A Round Robin tournament and a modified Swiss tournament setting are used for the training. The agents trained using social settings are compared to self play agents and results indicate that more robust agents emerge from the social training setting. Higher state space games can benefit from such settings as diverse set of agents will have multiple strategies that increase the chances of obtaining more experienced players at the end of training. The Social Learning trained agents exhibit better playing experience than self play agents. The modified Swiss playing style spawns a larger number of better playing agents as the population size increases.


A Study of NK Landscapes' Basins and Local Optima Networks

Abstract: We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces (Doye, 2002). We use the well-known family of $NK$ landscapes as an example. In our case the inherent network is the graph where the vertices are all the local maxima and edges mean basin adjacency between two maxima. We exhaustively extract such networks on representative small NK landscape instances, and show that they are 'small-worlds'. However, the maxima graphs are not random, since their clustering coefficients are much larger than those of corresponding random graphs. Furthermore, the degree distributions are close to exponential instead of Poissonian. We also describe the nature of the basins of attraction and their relationship with the local maxima network.


The Connectivity of NK Landscapes' Basins: A Network Analysis

Abstract: We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces. We use the well-known family of NK landscapes as an example. In our case the inherent network is the graph where the vertices represent the local maxima in the landscape, and the edges account for the transition probabilities between their corresponding basins of attraction. We exhaustively extracted such networks on representative small NK landscape instances, and performed a statistical characterization of their properties. We found that most of these network properties can be related to the search difficulty on the underlying NK landscapes with varying values of K.


Hierarchical Bag of Paths for Kernel Based Shape Classification

Abstract: Graph kernels methods are based on an implicit embedding of graphs within a vector space of large dimension. This implicit embedding allows to apply to graphs methods which where until recently solely reserved to numerical data. Within the shape classification framework, graphs are often produced by a skeletonization step which is sensitive to noise. We propose in this paper to integrate the robustness to structural noise by using a kernel based on a bag of path where each path is associated to a hierarchy encoding successive simplifications of the path. Several experiments prove the robustness and the flexibility of our approach compared to alternative shape classification methods.


Recursive Concurrent Stochastic Games

Abstract: We study Recursive Concurrent Stochastic Games (RCSGs), extending our recent analysis of recursive simple stochastic games to a concurrent setting where the two players choose moves simultaneously and independently at each state. For multi-exit games, our earlier work already showed undecidability for basic questions like termination, thus we focus on the important case of single-exit RCSGs (1-RCSGs). We first characterize the value of a 1-RCSG termination game as the least fixed point solution of a system of nonlinear minimax functional equations, and use it to show PSPACE decidability for the quantitative termination problem. We then give a strategy improvement technique, which we use to show that player 1 (maximizer) has \epsilon-optimal randomized Stackless & Memoryless (r-SM) strategies for all \epsilon > 0, while player 2 (minimizer) has optimal r-SM strategies. Thus, such games are r-SM-determined. These results mirror and generalize in a strong sense the randomized memoryless determinacy results for finite stochastic games, and extend the classic Hoffman-Karp strategy improvement approach from the finite to an infinite state setting. The proofs in our infinite-state setting are very different however, relying on subtle analytic properties of certain power series that arise from studying 1-RCSGs. We show that our upper bounds, even for qualitative (probability 1) termination, can not be improved, even to NP, without a major breakthrough, by giving two reductions: first a P-time reduction from the long-standing square-root sum problem to the quantitative termination decision problem for finite concurrent stochastic games, and then a P-time reduction from the latter problem to the qualitative termination problem for 1-RCSGs.


A Minimum Relative Entropy Principle for Learning and Acting

Abstract: This paper proposes a method to construct an adaptive agent that is universal with respect to a given class of experts, where each expert is an agent that has been designed specifically for a particular environment. This adaptive control problem is formalized as the problem of minimizing the relative entropy of the adaptive agent from the expert that is most suitable for the unknown environment. If the agent is a passive observer, then the optimal solution is the well-known Bayesian predictor. However, if the agent is active, then its past actions need to be treated as causal interventions on the I/O stream rather than normal probability conditions. Here it is shown that the solution to this new variational problem is given by a stochastic controller called the Bayesian control rule, which implements adaptive behavior as a mixture of experts. Furthermore, it is shown that under mild assumptions, the Bayesian control rule converges to the control law of the most suitable expert.


Experimental Study of Application Specific Source Coding for Wireless Sensor Networks

Abstract: The energy bottleneck in Wireless Sensor Network(WSN) can be reduced by limiting communication overhead. Application specific source coding schemes for the sensor networks provide fewer bits to represent the same amount of information exploiting the redundancy present in the source model, network architecture and the physical process. This paper reports the performance of representative codes from various families of source coding schemes (lossless, lossy, constant bit-rate, variable bit-rate, distributed and joint encoding/decoding) in terms of energy consumed, bit-rate achieved, quantization-error/reconstruction-error, latency and complexity of encoder-decoder(codec). A reusable frame work for testing source codes is provided. Finally we propose a set of possible applications and suitable source codes in terms of these parameters.


Emergency Centre Organization and Automated Triage System

Abstract: The excessive rate of patients arriving at accident and emergency centres is a major problem facing South African hospitals. Patients are prioritized for medical care through a triage process. Manual systems allow for inconsistency and error. This paper proposes a novel system to automate accident and emergency centre triage and uses this triage score along with an artificial intelligence estimate of patient-doctor time to optimize the queue order. A fuzzy inference system is employed to triage patients and a similar system estimates the time but adapts continuously through fuzzy Q-learning. The optimal queue order is found using a novel procedure based on genetic algorithms. These components are integrated in a simple graphical user interface. Live tests could not be performed but simulations reveal that the average waiting time can be reduced by 48 minutes and priority is given to urgent patients


Characterising Testing Preorders for Finite Probabilistic Processes

Abstract: In 1992 Wang & Larsen extended the may- and must preorders of De Nicola and Hennessy to processes featuring probabilistic as well as nondeterministic choice. They concluded with two problems that have remained open throughout the years, namely to find complete axiomatisations and alternative characterisations for these preorders. This paper solves both problems for finite processes with silent moves. It characterises the may preorder in terms of simulation, and the must preorder in terms of failure simulation. It also gives a characterisation of both preorders using a modal logic. Finally it axiomatises both preorders over a probabilistic version of CSP.


Distributed Estimation over Wireless Sensor Networks with Packet Losses

Abstract: A distributed adaptive algorithm to estimate a time-varying signal, measured by a wireless sensor network, is designed and analyzed. One of the major features of the algorithm is that no central coordination among the nodes needs to be assumed. The measurements taken by the nodes of the network are affected by noise, and the communication among the nodes is subject to packet losses. Nodes exchange local estimates and measurements with neighboring nodes. Each node of the network locally computes adaptive weights that minimize the estimation error variance. Decentralized conditions on the weights, needed for the convergence of the estimation error throughout the overall network, are presented. A Lipschitz optimization problem is posed to guarantee stability and the minimization of the variance. An efficient strategy to distribute the computation of the optimal solution is investigated. A theoretical performance analysis of the distributed algorithm is carried out both in the presence of perfect and lossy links. Numerical simulations illustrate performance for various network topologies and packet loss probabilities.


Design of a Fractional Order PID Controller Using Particle Swarm Optimization Technique

Abstract: Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better performance than their integer order counterparts. Controller synthesis is based on required peak overshoot and rise time specifications. The characteristic equation is minimized to obtain an optimum set of controller parameters. Results show that this design method can effectively tune the parameters of the fractional order controller.


Best-effort Group Service in Dynamic Networks

Abstract: We propose a group membership service for dynamic ad hoc networks. It maintains as long as possible the existing groups and ensures that each group diameter is always smaller than a constant, fixed according to the application using the groups. The proposed protocol is self-stabilizing and works in dynamic distributed systems. Moreover, it ensures a kind of continuity in the service offer to the application while the system is converging, except if too strong topology changes happen. Such a best effort behavior allows applications to rely on the groups while the stabilization has not been reached, which is very useful in dynamic ad hoc networks.


Relationship between Diversity and Perfomance of Multiple Classifiers for Decision Support

Abstract: The paper presents the investigation and implementation of the relationship between diversity and the performance of multiple classifiers on classification accuracy. The study is critical as to build classifiers that are strong and can generalize better. The parameters of the neural network within the committee were varied to induce diversity; hence structural diversity is the focus for this study. The hidden nodes and the activation function are the parameters that were varied. The diversity measures that were adopted from ecology such as Shannon and Simpson were used to quantify diversity. Genetic algorithm is used to find the optimal ensemble by using the accuracy as the cost function. The results observed shows that there is a relationship between structural diversity and accuracy. It is observed that the classification accuracy of an ensemble increases as the diversity increases. There was an increase of 3%-6% in the classification accuracy.


Power Control in Two-Tier Femtocell Networks

Abstract: In a two tier cellular network -- comprised of a central macrocell underlaid with shorter range femtocell hotspots -- cross-tier interference limits overall capacity with universal frequency reuse. To quantify near-far effects with universal frequency reuse, this paper derives a fundamental relation providing the largest feasible cellular Signal-to-Interference-Plus-Noise Ratio (SINR), given any set of feasible femtocell SINRs. We provide a link budget analysis which enables simple and accurate performance insights in a two-tier network. A distributed utility-based SINR adaptation at femtocells is proposed in order to alleviate cross-tier interference at the macrocell from cochannel femtocells. The Foschini-Miljanic (FM) algorithm is a special case of the adaptation. Each femtocell maximizes their individual utility consisting of a SINR based reward less an incurred cost (interference to the macrocell). Numerical results show greater than 30% improvement in mean femtocell SINRs relative to FM. In the event that cross-tier interference prevents a cellular user from obtaining its SINR target, an algorithm is proposed that reduces transmission powers of the strongest femtocell interferers. The algorithm ensures that a cellular user achieves its SINR target even with 100 femtocells/cell-site, and requires a worst case SINR reduction of only 16% at femtocells. These results motivate design of power control schemes requiring minimal network overhead in two-tier networks with shared spectrum.


Modeling Spatial and Temporal Dependencies of User Mobility in Wireless Mobile Networks

Abstract: Realistic mobility models are fundamental to evaluate the performance of protocols in mobile ad hoc networks. Unfortunately, there are no mobility models that capture the non-homogeneous behaviors in both space and time commonly found in reality, while at the same time being easy to use and analyze. Motivated by this, we propose a time-variant community mobility model, referred to as the TVC model, which realistically captures spatial and temporal correlations. We devise the communities that lead to skewed location visiting preferences, and time periods that allow us to model time dependent behaviors and periodic re-appearances of nodes at specific locations. To demonstrate the power and flexibility of the TVC model, we use it to generate synthetic traces that match the characteristics of a number of qualitatively different mobility traces, including wireless LAN traces, vehicular mobility traces, and human encounter traces. More importantly, we show that, despite the high level of realism achieved, our TVC model is still theoretically tractable. To establish this, we derive a number of important quantities related to protocol performance, such as the average node degree, the hitting time, and the meeting time, and provide examples of how to utilize this theory to guide design decisions in routing protocols.


On the Equation $x^{2^l+1}+x+a=0$ over $\mathrm{GF}(2^k)$ (Extended Version)

Abstract: In this paper, the polynomials $P_a(x)=x^{2^l+1}+x+a$ with $a\in\mathrm{GF}(2^k)$ are studied. New criteria for the number of zeros of $P_a(x)$ in $\mathrm{GF}(2^k)$ are proved. In particular, a criterion for $P_a(x)$ to have exactly one zero in $\mathrm{GF}(2^k)$ when $\gcd(l,k)=1$ is formulated in terms of the values of permutation polynomials introduced by Dobbertin. We also study the affine polynomial $a^{2^l}x^{2^{2l}}+x^{2^l}+ax+1$ which is closely related to $P_a(x)$. In many cases, explicit expressions for calculating zeros of these polynomials are provided.


Locally computable approximations for spectral clustering and absorption times of random walks

Abstract: We address the problem of determining a natural local neighbourhood or "cluster" associated to a given seed vertex in an undirected graph. We formulate the task in terms of absorption times of random walks from other vertices to the vertex of interest, and observe that these times are well approximated by the components of the principal eigenvector of the corresponding fundamental matrix of the graph's adjacency matrix. We further present a locally computable gradient-descent method to estimate this Dirichlet-Fiedler vector, based on minimising the respective Rayleigh quotient. Experimental evaluation shows that the approximations behave well and yield well-defined local clusters.


Bicycle cycles and mobility patterns - Exploring and characterizing data from a community bicycle program

Abstract: This paper provides an analysis of human mobility data in an urban area using the amount of available bikes in the stations of the community bicycle program Bicing in Barcelona. The data was obtained by periodic mining of a KML-file accessible through the Bicing website. Although in principle very noisy, after some preprocessing and filtering steps the data allows to detect temporal patterns in mobility as well as identify residential, university, business and leisure areas of the city. The results lead to a proposal for an improvement of the bicing website, including a prediction of the number of available bikes in a certain station within the next minutes/hours. Furthermore a model for identifying the most probable routes between stations is briefly sketched.


Interval Semantics for Standard Floating-Point Arithmetic

Abstract: If the non-zero finite floating-point numbers are interpreted as point intervals, then the effect of rounding can be interpreted as computing one of the bounds of the result according to interval arithmetic. We give an interval interpretation for the signed zeros and infinities, so that the undefined operations 0*inf, inf - inf, inf/inf, and 0/0 become defined. In this way no operation remains that gives rise to an error condition. Mathematically questionable features of the floating-point standard become well-defined sets of reals. Interval semantics provides a basis for the verification of numerical algorithms. We derive the results of the newly defined operations and consider the implications for hardware implementation.


Ogden's Lemma for Regular Tree Languages

Abstract: We motivate and prove a strong pumping lemma for regular tree languages. The new lemma can be seen as the natural correspondent of Ogden's lemma for context-free string languages.


Binding bigraphs as symmetric monoidal closed theories

Abstract: Milner's bigraphs are a general framework for reasoning about distributed and concurrent programming languages. Notably, it has been designed to encompass both the pi-calculus and the Ambient calculus. This paper is only concerned with bigraphical syntax: given what we here call a bigraphical signature K, Milner constructs a (pre-) category of bigraphs BBig(K), whose main features are (1) the presence of relative pushouts (RPOs), which makes them well-behaved w.r.t. bisimulations, and that (2) the so-called structural equations become equalities. Examples of the latter include, e.g., in pi and Ambient, renaming of bound variables, associativity and commutativity of parallel composition, or scope extrusion for restricted names. Also, bigraphs follow a scoping discipline ensuring that, roughly, bound variables never escape their scope. Here, we reconstruct bigraphs using a standard categorical tool: symmetric monoidal closed (SMC) theories. Our theory enforces the same scoping discipline as bigraphs, as a direct property of SMC structure. Furthermore, it elucidates the slightly mysterious status of so-called links in bigraphs. Finally, our category is also considerably larger than the category of bigraphs, notably encompassing in the same framework terms and a flexible form of higher-order contexts.


Efficient Algorithmic Techniques for Several Multidimensional Geometric Data Management and Analysis Problems

Abstract: In this paper I present several novel, efficient, algorithmic techniques for solving some multidimensional geometric data management and analysis problems. The techniques are based on several data structures from computational geometry (e.g. segment tree and range tree) and on the well-known sweep-line method.


Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

Abstract: In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.


An Eye Tracking Study into the Effects of Graph Layout

Abstract: Graphs are typically visualized as node-link diagrams. Although there is a fair amount of research focusing on crossing minimization to improve readability, little attention has been paid on how to handle crossings when they are an essential part of the final visualizations. This requires us to understand how people read graphs and how crossings affect reading performance. As an initial step to this end, a preliminary eye tracking experiment was conducted. The specific purpose of this experiment was to test the effects of crossing angles and geometric-path tendency on eye movements and performance. Sixteen subjects performed both path search and node locating tasks with six drawings. The results showed that small angles can slow down and trigger extra eye movements, causing delays for path search tasks, whereas crossings have little impact on node locating tasks. Geometric-path tendency indicates that a path between two nodes can become harder to follow when many branches of the path go toward the target node. The insights obtained are discussed with a view to further confirmation in future work.


Randomization Adaptive Self-Stabilization

Abstract: We present a scheme to convert self-stabilizing algorithms that use randomization during and following convergence to self-stabilizing algorithms that use randomization only during convergence. We thus reduce the number of random bits from an infinite number to a bounded number. The scheme is applicable to the cases in which there exits a local predicate for each node, such that global consistency is implied by the union of the local predicates. We demonstrate our scheme over the token circulation algorithm of Herman and the recent constant time Byzantine self-stabilizing clock synchronization algorithm by Ben-Or, Dolev and Hoch. The application of our scheme results in the first constant time Byzantine self-stabilizing clock synchronization algorithm that uses a bounded number of random bits.


The Mob core language and abstract machine (rev 0.2)

Abstract: Most current mobile agent systems are based on programming languages whose semantics are difficult to prove correct as they lack an adequate underlying formal theory. In recent years, the development of the theory of concurrent systems, namely of process calculi, has allowed for the first time the modeling of mobile agent systems.Languages directly based on process calculi are, however, very low-level and it is desirable to provide the programmer with higher level abstractions, while keeping the semantics of the base calculus. In this technical report we present the syntax and the semantics of a scripting language for programming mobile agents called Mob. We describe the language's syntax and semantics. Mob is service-oriented, meaning that agents act both as servers and as clients of services and that this coupling is done dynamically at run-time. The language is implemented on top of a process calculus which allows us to prove that the framework is sound by encoding its semantics into the underlying calculus. This provides a form of language security not available to other mobile agent languages developed using a more ah-doc approach.


Logics for XML

Abstract: This thesis describes the theoretical and practical foundations of a system for the static analysis of XML processing languages. The system relies on a fixpoint temporal logic with converse, derived from the mu-calculus, where models are finite trees. This calculus is expressive enough to capture regular tree types along with multi-directional navigation in trees, while having a single exponential time complexity. Specifically the decidability of the logic is proved in time 2^O(n) where n is the size of the input formula. Major XML concepts are linearly translated into the logic: XPath navigation and node selection semantics, and regular tree languages (which include DTDs and XML Schemas). Based on these embeddings, several problems of major importance in XML applications are reduced to satisfiability of the logic. These problems include XPath containment, emptiness, equivalence, overlap, coverage, in the presence or absence of regular tree type constraints, and the static type-checking of an annotated query. The focus is then given to a sound and complete algorithm for deciding the logic, along with a detailed complexity analysis, and crucial implementation techniques for building an effective solver. Practical experiments using a full implementation of the system are presented. The system appears to be efficient in practice for several realistic scenarios. The main application of this work is a new class of static analyzers for programming languages using both XPath expressions and XML type annotations (input and output). Such analyzers allow to ensure at compile-time valuable properties such as type-safety and optimizations, for safer and more efficient XML processing.


New Constructions for Query-Efficient Locally Decodable Codes of Subexponential Length

Abstract: A $(k,\delta,\epsilon)$-locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$ is an error-correcting code that encodes each message $\vec{x}=(x_{1},x_{2},...,x_{n}) \in F_{q}^{n}$ to $C(\vec{x}) \in F_{q}^{N}$ and has the following property: For any $\vec{y} \in {\bf F}_{q}^{N}$ such that $d(\vec{y},C(\vec{x})) \leq \delta N$ and each $1 \leq i \leq n$, the symbol $x_{i}$ of $\vec{x}$ can be recovered with probability at least $1-\epsilon$ by a randomized decoding algorithm looking only at $k$ coordinates of $\vec{y}$. The efficiency of a $(k,\delta,\epsilon)$-locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$ is measured by the code length $N$ and the number $k$ of queries. For any $k$-query locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$, the code length $N$ is conjectured to be exponential of $n$, however, this was disproved. Yekhanin [In Proc. of STOC, 2007] showed that there exists a 3-query locally decodable code $C: F_{2}^{n} \to F_{2}^{N}$ such that $N=\exp(n^{(1/\log \log n)})$ assuming that the number of Mersenne primes is infinite. For a 3-query locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$, Efremenko [ECCC Report No.69, 2008] reduced the code length further to $N=\exp(n^{O((\log \log n/ \log n)^{1/2})})$, and also showed that for any integer $r>1$, there exists a $k$-query locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$ such that $k \leq 2^{r}$ and $N=\exp(n^{O((\log \log n/ \log n)^{1-1/r})})$. In this paper, we present a query-efficient locally decodable code and show that for any integer $r>1$, there exists a $k$-query locally decodable code $C: F_{q}^{n} \to F_{q}^{N}$ such that $k \leq 3 \cdot 2^{r-2}$ and $N=\exp(n^{O((\log \log n/ \log n)^{1-1/r})})$.


Learning Isometric Separation Maps

Abstract: Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensional spaces, often revealing the true intrinsic dimension. In this paper we show how to also incorporate supervised class information into an MVU-like method without breaking its convexity. We call this method the Isometric Separation Map and we show that the resulting kernel matrix can be used as a binary/multiclass Support Vector Machine-like method in a semi-supervised (transductive) framework. We also show that the method always finds a kernel matrix that linearly separates the training data exactly without projecting them in infinite dimensional spaces. In traditional SVMs we choose a kernel and hope that the data become linearly separable in the kernel space. In this paper we show how the hyperplane can be chosen ad-hoc and the kernel is trained so that data are always linearly separable. Comparisons with Large Margin SVMs show comparable performance.


Assembling Actor-based Mind-Maps from Text Stream

Abstract: For human beings, the processing of text streams of unknown size leads generally to problems because e.g. noise must be selected out, information be tested for its relevance or redundancy, and linguistic phenomenon like ambiguity or the resolution of pronouns be advanced. Putting this into simulation by using an artificial mind-map is a challenge, which offers the gate for a wide field of applications like automatic text summarization or punctual retrieval. In this work we present a framework that is a first step towards an automatic intellect. It aims at assembling a mind-map based on incoming text streams and on a subject-verb-object strategy, having the verb as an interconnection between the adjacent nouns. The mind-map's performance is enriched by a pronoun resolution engine that bases on the work of D. Klein, and C. D. Manning.


Graph-based classification of multiple observation sets

Abstract: We consider the problem of classification of an object given multiple observations that possibly include different transformations. The possible transformations of the object generally span a low-dimensional manifold in the original signal space. We propose to take advantage of this manifold structure for the effective classification of the object represented by the observation set. In particular, we design a low complexity solution that is able to exploit the properties of the data manifolds with a graph-based algorithm. Hence, we formulate the computation of the unknown label matrix as a smoothing process on the manifold under the constraint that all observations represent an object of one single class. It results into a discrete optimization problem, which can be solved by an efficient and low complexity algorithm. We demonstrate the performance of the proposed graph-based algorithm in the classification of sets of multiple images. Moreover, we show its high potential in video-based face recognition, where it outperforms state-of-the-art solutions that fall short of exploiting the manifold structure of the face image data sets.


On Granular Knowledge Structures

Abstract: Knowledge plays a central role in human and artificial intelligence. One of the key characteristics of knowledge is its structured organization. Knowledge can be and should be presented in multiple levels and multiple views to meet people's needs in different levels of granularities and from different perspectives. In this paper, we stand on the view point of granular computing and provide our understanding on multi-level and multi-view of knowledge through granular knowledge structures (GKS). Representation of granular knowledge structures, operations for building granular knowledge structures and how to use them are investigated. As an illustration, we provide some examples through results from an analysis of proceeding papers. Results show that granular knowledge structures could help users get better understanding of the knowledge source from set theoretical, logical and visual point of views. One may consider using them to meet specific needs or solve certain kinds of problems.


A topological chaos framework for hash functions

Abstract: This paper presents a new procedure of generating hash functions which can be evaluated using some mathematical tools. This procedure is based on discrete chaotic iterations. First, it is mathematically proven, that these discrete chaotic iterations can be considered as a \linebreak particular case of topological chaos. Then, the process of generating hash function based on the \linebreak topological chaos is detailed. Finally it is shown how some tools coming from the domain of \linebreak topological chaos can be used to measure quantitatively and qualitatively some desirable properties for hash functions. An illustration example is detailed in order to show how one can create hash functions using our theoretical study. Key-words : Discrete chaotic iterations. Topological chaos. Hash function


A watermarking algorithm satisfying topological chaos properties

Abstract: A new watermarking algorithm is given, it is based on the so-called chaotic iterations and on the choice of some coefficients which are deduced from the description of the carrier medium. After defining these coefficients, chaotic discrete iterations are used to encrypt the watermark and to embed it in the carrier medium. This procedure generates a topological chaos and ensures that the required properties of a watermarking algorithm are satisfied. Key-words: Watermarking, Encryption, Chaotic iterations, Topological chaos, Information hiding


Kernel(s) for Problems With no Kernel: On Out-Trees With Many Leaves

Abstract: The {\sc $k$-Leaf Out-Branching} problem is to find an out-branching (i.e. a rooted oriented spanning tree) with at least $k$ leaves in a given digraph. The problem has recently received much attention from the viewpoint of parameterized algorithms {alonLNCS4596,AlonFGKS07fsttcs,BoDo2,KnLaRo}. In this paper we step aside and take a kernelization based approach to the {\sc $k$-Leaf-Out-Branching} problem. We give the first polynomial kernel for {\sc Rooted $k$-Leaf-Out-Branching}, a variant of {\sc $k$-Leaf-Out-Branching} where the root of the tree searched for is also a part of the input. Our kernel has cubic size and is obtained using extremal combinatorics. For the {\sc $k$-Leaf-Out-Branching} problem we show that no polynomial kernel is possible unless polynomial hierarchy collapses to third level %$PH=\Sigma_p^3$ by applying a recent breakthrough result by Bodlaender et al. {BDFH08} in a non-trivial fashion. However our positive results for {\sc Rooted $k$-Leaf-Out-Branching} immediately imply that the seemingly intractable the {\sc $k$-Leaf-Out-Branching} problem admits a data reduction to $n$ independent $O(k^3)$ kernels. These two results, tractability and intractability side by side, are the first separating {\it many-to-one kernelization} from {\it Turing kernelization}. This answers affirmatively an open problem regarding "cheat kernelization" raised in {IWPECOPEN08}.


XQuery Join Graph Isolation

Abstract: A purely relational account of the true XQuery semantics can turn any relational database system into an XQuery processor. Compiling nested expressions of the fully compositional XQuery language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers--the B-tree indexing subsystem and join tree planner, in particular--to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the XQuery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient XQuery processors readily available today.


A constructive proof of the Lovasz Local Lemma

Abstract: The Lovasz Local Lemma [EL75] is a powerful tool to prove the existence of combinatorial objects meeting a prescribed collection of criteria. The technique can directly be applied to the satisfiability problem, yielding that a k-CNF formula in which each clause has common variables with at most 2^(k-2) other clauses is always satisfiable. All hitherto known proofs of the Local Lemma are non-constructive and do thus not provide a recipe as to how a satisfying assignment to such a formula can be efficiently found. In his breakthrough paper [Bec91], Beck demonstrated that if the neighbourhood of each clause be restricted to O(2^(k/48)), a polynomial time algorithm for the search problem exists. Alon simplified and randomized his procedure and improved the bound to O(2^(k/8)) [Alo91]. Srinivasan presented in [Sri08] a variant that achieves a bound of essentially O(2^(k/4)). In [Mos08], we improved this to O(2^(k/2)). In the present paper, we give a randomized algorithm that finds a satisfying assignment to every k-CNF formula in which each clause has a neighbourhood of at most the asymptotic optimum of 2^(k-5)-1 other clauses and that runs in expected time polynomial in the size of the formula, irrespective of k. If k is considered a constant, we can also give a deterministic variant. In contrast to all previous approaches, our analysis does not anymore invoke the standard non-constructive versions of the Local Lemma and can therefore be considered an alternative, constructive proof of it.


The adaptability of physiological systems optimizes performance: new directions in augmentation

Abstract: This paper contributes to the human-machine interface community in two ways: as a critique of the closed-loop AC (augmented cognition) approach, and as a way to introduce concepts from complex systems and systems physiology into the field. Of particular relevance is a comparison of the inverted-U (or Gaussian) model of optimal performance and multidimensional fitness landscape model. Hypothetical examples will be given from human physiology and learning and memory. In particular, a four-step model will be introduced that is proposed as a better means to characterize multivariate systems during behavioral processes with complex dynamics such as learning. Finally, the alternate approach presented herein is considered as a preferable design alternate in human-machine systems. It is within this context that future directions are discussed.


On Finite Bases for Weak Semantics: Failures versus Impossible Futures

Abstract: We provide a finite basis for the (in)equational theory of the process algebra BCCS modulo the weak failures preorder and equivalence. We also give positive and negative results regarding the axiomatizability of BCCS modulo weak impossible futures semantics.


Exponential-Time Approximation of Hard Problems

Abstract: We study optimization problems that are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. Specifically, we focus on Maximum Independent Set, Vertex Coloring, Set Cover, and Bandwidth. In recent years, many researchers design exact exponential-time algorithms for these and other hard problems. The goal is getting the time complexity still of order $O(c^n)$, but with the constant $c$ as small as possible. In this work we extend this line of research and we investigate whether the constant $c$ can be made even smaller when one allows constant factor approximation. In fact, we describe a kind of approximation schemes -- trade-offs between approximation factor and the time complexity. We study two natural approaches. The first approach consists of designing a backtracking algorithm with a small search tree. We present one result of that kind: a $(4r-1)$-approximation of Bandwidth in time $O^*(2^{n/r})$, for any positive integer $r$. The second approach uses general transformations from exponential-time exact algorithms to approximations that are faster but still exponential-time. For example, we show that for any reduction rate $r$, one can transform any $O^*(c^n)$-time algorithm for Set Cover into a $(1+\ln r)$-approximation algorithm running in time $O^*(c^{n/r})$. We believe that results of that kind extend the applicability of exact algorithms for NP-hard problems.


FPT Algorithms and Kernels for the Directed $k$-Leaf Problem

Abstract: A subgraph $T$ of a digraph $D$ is an {\em out-branching} if $T$ is an oriented spanning tree with only one vertex of in-degree zero (called the {\em root}). The vertices of $T$ of out-degree zero are {\em leaves}. In the {\sc Directed $k$-Leaf} Problem, we are given a digraph $D$ and an integral parameter $k$, and we are to decide whether $D$ has an out-branching with at least $k$ leaves. Recently, Kneis et al. (2008) obtained an algorithm for the problem of running time $4^{k}\cdot n^{O(1)}$. We describe a new algorithm for the problem of running time $3.72^{k}\cdot n^{O(1)}$. In {\sc Rooted Directed $k$-Leaf} Problem, apart from $D$ and $k$, we are given a vertex $r$ of $D$ and we are to decide whether $D$ has an out-branching rooted at $r$ with at least $k$ leaves. Very recently, Fernau et al. (2008) found an $O(k^3)$-size kernel for {\sc Rooted Directed $k$-Leaf}. In this paper, we obtain an $O(k)$ kernel for {\sc Rooted Directed $k$-Leaf} restricted to acyclic digraphs.


Automatic structures of bounded degree revisited

Abstract: The first-order theory of a string automatic structure is known to be decidable, but there are examples of string automatic structures with nonelementary first-order theories. We prove that the first-order theory of a string automatic structure of bounded degree is decidable in doubly exponential space (for injective automatic presentations, this holds even uniformly). This result is shown to be optimal since we also present a string automatic structure of bounded degree whose first-order theory is hard for 2EXPSPACE. We prove similar results also for tree automatic structures. These findings close the gaps left open in a previous paper of the second author by improving both, the lower and the upper bounds.


P is not equal to NP

Abstract: SAT is not in P, is true and provable in a simply consistent extension B' of a first order theory B of computing, with a single finite axiom characterizing a universal Turing machine. Therefore, P is not equal to NP, is true and provable in a simply consistent extension B" of B.


Combining Advanced Visualization and Automatized Reasoning for Webometrics: A Test Study

Abstract: This paper presents a first attempt at performing a precise and automatic identification of the linking behaviour in a scientific domain through the analysis of the communication of the related academic institutions on the web. The proposed approach is based on the paradigm of multiple viewpoint data analysis (MVDA) than can be fruitfully exploited to highlight relationships between data, like websites, carrying several kinds of description. It uses the MultiSOM clustering and mapping method. The domain that has been chosen for this study is the domain of Computer Science in Germany. The analysis is conduced on a set of 438 websites of this domain using all together, thematic, geographic and linking information. It highlights interesting results concerning both global and local linking behaviour.


Lower bounds for distributed markov chain problems

Abstract: We study the worst-case communication complexity of distributed algorithms computing a path problem based on stationary distributions of random walks in a network $G$ with the caveat that $G$ is also the communication network. The problem is a natural generalization of shortest path lengths to expected path lengths, and represents a model used in many practical applications such as pagerank and eigentrust as well as other problems involving Markov chains defined by networks. For the problem of computing a single stationary probability, we prove an $\Omega(n^2 \log n)$ bits lower bound; the trivial centralized algorithm costs $O(n^3)$ bits and no known algorithm beats this. We also prove lower bounds for the related problems of approximately computing the stationary probabilities, computing only the ranking of the nodes, and computing the node with maximal rank. As a corollary, we obtain lower bounds for labelling schemes for the hitting time between two nodes.


3D Face Recognition with Sparse Spherical Representations

Abstract: This paper addresses the problem of 3D face recognition using simultaneous sparse approximations on the sphere. The 3D face point clouds are first aligned with a novel and fully automated registration process. They are then represented as signals on the 2D sphere in order to preserve depth and geometry information. Next, we implement a dimensionality reduction process with simultaneous sparse approximations and subspace projection. It permits to represent each 3D face by only a few spherical functions that are able to capture the salient facial characteristics, and hence to preserve the discriminant facial information. We eventually perform recognition by effective matching in the reduced space, where Linear Discriminant Analysis can be further activated for improved recognition performance. The 3D face recognition algorithm is evaluated on the FRGC v.1.0 data set, where it is shown to outperform classical state-of-the-art solutions that work with depth images.


An Activity-Based Model for Separation of Duty

Abstract: This paper offers several contributions for separation of duty (SoD) administration in role-based access control (RBAC) systems. We first introduce a new formal framework, based on business perspective, where SoD constraints are analyzed introducing the activity concept. This notion helps organizations define SoD constraints in terms of business requirements and reduces management complexity in large-scale RBAC systems. The model enables the definition of a wide taxonomy of conflict types. In particular, object-based SoD is introduced using the SoD domain concept, namely the set of data in which transaction conflicts may occur. Together with the formalization of the above properties, in this paper we also show the effectiveness of our proposal: we have applied the model to a large, existing organization; results highlight the benefits of adopting the proposed model in terms of reduced administration cost.


Relating Web pages to enable information-gathering tasks

Abstract: We argue that relationships between Web pages are functions of the user's intent. We identify a class of Web tasks - information-gathering - that can be facilitated by a search engine that provides links to pages which are related to the page the user is currently viewing. We define three kinds of intentional relationships that correspond to whether the user is a) seeking sources of information, b) reading pages which provide information, or c) surfing through pages as part of an extended information-gathering process. We show that these three relationships can be productively mined using a combination of textual and link information and provide three scoring mechanisms that correspond to them: {\em SeekRel}, {\em FactRel} and {\em SurfRel}. These scoring mechanisms incorporate both textual and link information. We build a set of capacitated subnetworks - each corresponding to a particular keyword - that mirror the interconnection structure of the World Wide Web. The scores are computed by computing flows on these subnetworks. The capacities of the links are derived from the {\em hub} and {\em authority} values of the nodes they connect, following the work of Kleinberg (1998) on assigning authority to pages in hyperlinked environments. We evaluated our scoring mechanism by running experiments on four data sets taken from the Web. We present user evaluations of the relevance of the top results returned by our scoring mechanisms and compare those to the top results returned by Google's Similar Pages feature, and the {\em Companion} algorithm proposed by Dean and Henzinger (1999).


The Multi-Core Era - Trends and Challenges

Abstract: Since the very beginning of hardware development, computer processors were invented with ever-increasing clock frequencies and sophisticated in-build optimization strategies. Due to physical limitations, this 'free lunch' of speedup has come to an end. The following article gives a summary and bibliography for recent trends and challenges in CMP architectures. It discusses how 40 years of parallel computing research need to be considered in the upcoming multi-core era. We argue that future research must be driven from two sides - a better expression of hardware structures, and a domain-specific understanding of software parallelism.


Worst-case time decremental connectivity and k-edge witness

Abstract: We give a simple algorithm for decremental graph connectivity that handles edge deletions in worst-case time $O(k \log n)$ and connectivity queries in $O(\log k)$, where $k$ is the number of edges deleted so far, and uses worst-case space $O(m^2)$. We use this to give an algorithm for $k$-edge witness (``does the removal of a given set of $k$ edges disconnect two vertices $u,v$?'') with worst-case time $O(k^2 \log n)$ and space $O(k^2 n^2)$. For $k = o(\sqrt{n})$ these improve the worst-case $O(\sqrt{n})$ bound for deletion due to Eppstein et al. We also give a decremental connectivity algorithm using $O(n^2 \log n / \log \log n)$ space, whose time complexity depends on the toughness and independence number of the input graph. Finally, we show how to construct a distributed data structure for \kvw by giving a labeling scheme. This is the first data structure for \kvw that can efficiently distributed without just giving each vertex a copy of the whole structure. Its complexity depends on being able to construct a linear layout with good properties.


On the length of attractors in boolean networks with an interaction graph by layers

Abstract: We consider a boolean network whose interaction graph has no circuit of length >1. Under this hypothesis, we establish an upper bound on the length of the attractors of the network which only depends on its interaction graph.


A Novel Clustering Algorithm Based on a Modified Model of Random Walk

Abstract: We introduce a modified model of random walk, and then develop two novel clustering algorithms based on it. In the algorithms, each data point in a dataset is considered as a particle which can move at random in space according to the preset rules in the modified model. Further, this data point may be also viewed as a local control subsystem, in which the controller adjusts its transition probability vector in terms of the feedbacks of all data points, and then its transition direction is identified by an event-generating function. Finally, the positions of all data points are updated. As they move in space, data points collect gradually and some separating parts emerge among them automatically. As a consequence, data points that belong to the same class are located at a same position, whereas those that belong to different classes are away from one another. Moreover, the experimental results have demonstrated that data points in the test datasets are clustered reasonably and efficiently, and the comparison with other algorithms also provides an indication of the effectiveness of the proposed algorithms.


Symbolic model checking of tense logics on rational Kripke models

Abstract: We introduce the class of rational Kripke models and study symbolic model checking of the basic tense logic Kt and some extensions of it in models from that class. Rational Kripke models are based on (generally infinite) rational graphs, with vertices labeled by the words in some regular language and transitions recognized by asynchronous two-head finite automata, also known as rational transducers. Every atomic proposition in a rational Kripke model is evaluated in a regular set of states. We show that every formula of Kt has an effectively computable regular extension in every rational Kripke model, and therefore local model checking and global model checking of Kt in rational Kripke models are decidable. These results are lifted to a number of extensions of Kt. We study and partly determine the complexity of the model checking procedures.