Minimum Cycle Basis and All-Pairs Min Cut of a Planar Graph in Subquadratic Time

Abstract: A minimum cycle basis of a weighted undirected graph $G$ is a basis of the cycle space of $G$ such that the total weight of the cycles in this basis is minimized. If $G$ is a planar graph with non-negative edge weights, such a basis can be found in $O(n^2)$ time and space, where $n$ is the size of $G$. We show that this is optimal if an explicit representation of the basis is required. We then present an $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space algorithm that computes a minimum cycle basis \emph{implicitly}. From this result, we obtain an output-sensitive algorithm that explicitly computes a minimum cycle basis in $O(n^{3/2}\log n + C)$ time and $O(n^{3/2} + C)$ space, where $C$ is the total size (number of edges and vertices) of the cycles in the basis. These bounds reduce to $O(n^{3/2}\log n)$ and $O(n^{3/2})$, respectively, when $G$ is unweighted. We get similar results for the all-pairs min cut problem since it is dual equivalent to the minimum cycle basis problem for planar graphs. We also obtain $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space algorithms for finding, respectively, the weight vector and a Gomory-Hu tree of $G$. The previous best time and space bound for these two problems was quadratic. From our Gomory-Hu tree algorithm, we obtain the following result: with $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space for preprocessing, the weight of a min cut between any two given vertices of $G$ can be reported in constant time. Previously, such an oracle required quadratic time and space for preprocessing. The oracle can also be extended to report the actual cut in time proportional to its size.


Open Access, Intellectual Property, and How Biotechnology Becomes a New Software Science

Abstract: Innovation is slowing greatly in the pharmaceutical sector. It is considered here how part of the problem is due to overly limiting intellectual property relations in the sector. On the other hand, computing and software in particular are characterized by great richness of intellectual property frameworks. Could the intellectual property ecosystem of computing come to the aid of the biosciences and life sciences? We look at how the answer might well be yes, by looking at (i) the extent to which a drug mirrors a software program, and (ii) what is to be gleaned from trends in research publishing in the life and biosciences.


Subshifts as Models for MSO Logic

Abstract: We study the Monadic Second Order (MSO) Hierarchy over colourings of the discrete plane, and draw links between classes of formula and classes of subshifts. We give a characterization of existential MSO in terms of projections of tilings, and of universal sentences in terms of combinations of "pattern counting" subshifts. Conversely, we characterise logic fragments corresponding to various classes of subshifts (subshifts of finite type, sofic subshifts, all subshifts). Finally, we show by a separation result how the situation here is different from the case of tiling pictures studied earlier by Giammarresi et al.


Conception d'un outil d'aide \`a l'indexation de ressources p\'edagogiques - Extraction automatique des th\'ematiques et des mots-clefs de documents UNIT

Abstract: Indexing learning documents using the Learning Object Metadata (LOM) is often carried out manually by archivists. Filling out the LOM fields is a long and difficult task, requiring a complete reading and a full knowledge on the topic dealt within the document. In this paper, we present an innovative model and method to assist the archivists in finding the important concepts and keywords of a learning document. The application is performed using wikipedia's category links.


Automatic creation of urban velocity fields from aerial video

Abstract: In this paper, we present a system for modelling vehicle motion in an urban scene from low frame-rate aerial video. In particular, the scene is modelled as a probability distribution over velocities at every pixel in the image. We describe the complete system for acquiring this model. The video is captured from a helicopter and stabilized by warping the images to match an orthorectified image of the area. A pixel classifier is applied to the stabilized images, and the response is segmented to determine car locations and orientations. The results are fed in to a tracking scheme which tracks cars for three frames, creating tracklets. This allows the tracker to use a combination of velocity, direction, appearance, and acceleration cues to keep only tracks likely to be correct. Each tracklet provides a measurement of the car velocity at every point along the tracklet's length, and these are then aggregated to create a histogram of vehicle velocities at every pixel in the image. The results demonstrate that the velocity probability distribution prior can be used to infer a variety of information about road lane directions, speed limits, vehicle speeds and common trajectories, and traffic bottlenecks, as well as providing a means of describing environmental knowledge about traffic rules that can be used in tracking.


Energy Efficient Scheduling via Partial Shutdown

Abstract: Motivated by issues of saving energy in data centers we define a collection of new problems referred to as "machine activation" problems. The central framework we introduce considers a collection of $m$ machines (unrelated or related) with each machine $i$ having an {\em activation cost} of $a_i$. There is also a collection of $n$ jobs that need to be performed, and $p_{i,j}$ is the processing time of job $j$ on machine $i$. We assume that there is an activation cost budget of $A$ -- we would like to {\em select} a subset $S$ of the machines to activate with total cost $a(S) \le A$ and {\em find} a schedule for the $n$ jobs on the machines in $S$ minimizing the makespan (or any other metric). For the general unrelated machine activation problem, our main results are that if there is a schedule with makespan $T$ and activation cost $A$ then we can obtain a schedule with makespan $\makespanconstant T$ and activation cost $\costconstant A$, for any $\epsilon >0$. We also consider assignment costs for jobs as in the generalized assignment problem, and using our framework, provide algorithms that minimize the machine activation and the assignment cost simultaneously. In addition, we present a greedy algorithm which only works for the basic version and yields a makespan of $2T$ and an activation cost $A (1+\ln n)$. For the uniformly related parallel machine scheduling problem, we develop a polynomial time approximation scheme that outputs a schedule with the property that the activation cost of the subset of machines is at most $A$ and the makespan is at most $(1+\epsilon) T$ for any $\epsilon >0$.


Algorithms and Hardness for Subspace Approximation

Abstract: The subspace approximation problem Subspace($k$,$p$) asks for a $k$-dimensional linear subspace that fits a given set of points optimally, where the error for fitting is a generalization of the least squares fit and uses the $\ell_{p}$ norm instead. Most of the previous work on subspace approximation has focused on small or constant $k$ and $p$, using coresets and sampling techniques from computational geometry. In this paper, extending another line of work based on convex relaxation and rounding, we give a polynomial time algorithm, \emph{for any $k$ and any $p \geq 2$}, with the approximation guarantee roughly $\gamma_{p} \sqrt{2 - \frac{1}{n-k}}$, where $\gamma_{p}$ is the $p$-th moment of a standard normal random variable N(0,1). We show that the convex relaxation we use has an integrality gap (or "rank gap") of $\gamma_{p} (1 - \epsilon)$, for any constant $\epsilon > 0$. Finally, we show that assuming the Unique Games Conjecture, the subspace approximation problem is hard to approximate within a factor better than $\gamma_{p} (1 - \epsilon)$, for any constant $\epsilon > 0$.


Nonlinear Effects in Stiffness Modeling of Robotic Manipulators

Abstract: The paper focuses on the enhanced stiffness modeling of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the virtual joint technique that describes the compliance of manipulator elements by a set of localized six-dimensional springs separated by rigid links and perfect joints. In contrast to the conventional formulation, which is valid for the unloaded mode and small displacements, the proposed approach implicitly assumes that the loading leads to the non-negligible changes of the manipulator posture and corresponding amendment of the Jacobian. The developed numerical technique allows computing the static equilibrium and relevant force/torque reaction of the manipulator for any given displacement of the end-effector. This enables designer detecting essentially nonlinear effects in elastic behavior of manipulator, similar to the buckling of beam elements. It is also proposed the linearization procedure that is based on the inversion of the dedicated matrix composed of the stiffness parameters of the virtual springs and the Jacobians/Hessians of the active and passive joints. The developed technique is illustrated by an application example that deals with the stiffness analysis of a parallel manipulator of the Orthoglide family.


Context and Keyword Extraction in Plain Text Using a Graph Representation

Abstract: Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist indexing specialized documents, experience plays an important role. But indexing documents on different topics is much harder. This article proposes an innovative method for an indexing support system. This system takes as input an ontology and a plain text document and provides as output contextualized keywords of the document. The method has been evaluated by exploiting Wikipedia's category links as a termino-ontological resources.


Understanding edge-connectivity in the Internet through core-decomposition

Abstract: Internet is a complex network composed by several networks: the Autonomous Systems, each one designed to transport information efficiently. Routing protocols aim to find paths between nodes whenever it is possible (i.e., the network is not partitioned), or to find paths verifying specific constraints (e.g., a certain QoS is required). As connectivity is a measure related to both of them (partitions and selected paths) this work provides a formal lower bound to it based on core-decomposition, under certain conditions, and low complexity algorithms to find it. We apply them to analyze maps obtained from the prominent Internet mapping projects, using the LaNet-vi open-source software for its visualization.


Good characterization for path packing in a subclass of Karzanov networks

Abstract: The path packing problem is stated finding the maximum number of edge-disjoint paths between predefined pairs of nodes in an undirected multigraph. Such a multigraph together with predefined node pairs is often called a network.


A survey on algorithmic aspects of modular decomposition

Abstract: The modular decomposition is a technique that applies but is not restricted to graphs. The notion of module naturally appears in the proofs of many graph theoretical theorems. Computing the modular decomposition tree is an important preprocessing step to solve a large number of combinatorial optimization problems. Since the first polynomial time algorithm in the early 70's, the algorithmic of the modular decomposition has known an important development. This paper survey the ideas and techniques that arose from this line of research.


Subgraph Sparsification and Nearly Optimal Ultrasparsifiers

Abstract: We consider a variation of the spectral sparsification problem where we are required to keep a subgraph of the original graph. Formally, given a union of two weighted graphs $G$ and $W$ and an integer $k$, we are asked to find a $k$-edge weighted graph $W_k$ such that $G+W_k$ is a good spectral sparsifer of $G+W$. We will refer to this problem as the subgraph (spectral) sparsification. We present a nontrivial condition on $G$ and $W$ such that a good sparsifier exists and give a polynomial time algorithm to find the sparsifer. %$O(\frac{n}{k})\log n \tilde{O}(\log \log n)$ As a significant application of our technique, we show that for each positive integer $k$, every $n$-vertex weighted graph has an $(n-1+k)$-edge spectral sparsifier with relative condition number at most $\frac{n}{k} \log n \tilde{O}(\log\log n)$ where $\tilde{O}()$ hides lower order terms. Our bound is within a factor of $\tilde{O}(\log \log n)$ from optimal. This nearly settles a question left open by Spielman and Teng about ultrasparsifiers, which is a key component in their nearly linear-time algorithms for solving diagonally dominant symmetric linear systems. We also present another application of our technique to spectral optimization in which the goal is to maximize the algebraic connectivity of a graph (e.g. turn it into an expander) with a limited number of edges.


Completeness of the WDS method in Checking Positivity of Integral Forms

Abstract: Examples show that integral forms can be efficiently proved positive semidefinite by the WDS method, but it was unknown that how many steps of substitutions are needed, or furthermore, which integral forms is this method applicable for. In this paper, we give upper bounds of step numbers of WDS required in proving that an integral form is positive definite, positive semidefinite, or not positive semidefinite, thus deducing that the WDS method is complete.


On the Rationality of Escalation

Abstract: Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its connection with the same concept for finite games) to study carefully and formally the infinite games especially those called dollar auctions, which are considered as the paradigm of escalation. Unlike what is commonly admitted, we show that, provided one assumes that the other agent will always stop, bidding is rational, because it results in a subgame perfect equilibrium. We show that this is not the only rational strategy profile (the only subgame perfect equilibrium). Indeed if an agent stops and will stop at every step, we claim that he is rational as well, if one admits that his opponent will never stop, because this corresponds to a subgame perfect equilibrium. Amazingly, in the infinite dollar auction game, the behavior in which both agents stop at each step is not a Nash equilibrium, hence is not a subgame perfect equilibrium, hence is not rational.


On the Optimality of a Class of LP-based Algorithms

Abstract: In this paper we will be concerned with a class of packing and covering problems which includes Vertex Cover and Independent Set. Typically, one can write an LP relaxation and then round the solution. In this paper, we explain why the simple LP-based rounding algorithm for the \\VC problem is optimal assuming the UGC. Complementing Raghavendra's result, our result generalizes to a class of strict, covering/packing type CSPs.


Communication Complexity and Intrinsic Universality in Cellular Automata

Abstract: The notions of universality and completeness are central in the theories of computation and computational complexity. However, proving lower bounds and necessary conditions remains hard in most of the cases. In this article, we introduce necessary conditions for a cellular automaton to be "universal", according to a precise notion of simulation, related both to the dynamics of cellular automata and to their computational power. This notion of simulation relies on simple operations of space-time rescaling and it is intrinsic to the model of cellular automata. Intrinsinc universality, the derived notion, is stronger than Turing universality, but more uniform, and easier to define and study. Our approach builds upon the notion of communication complexity, which was primarily designed to study parallel programs, and thus is, as we show in this article, particulary well suited to the study of cellular automata: it allowed to show, by studying natural problems on the dynamics of cellular automata, that several classes of cellular automata, as well as many natural (elementary) examples, could not be intrinsically universal.


iSSEE: IMS Sensors Search Engine Enabler for Sensors Mashups Convergent Application

Abstract: Integrating the sensing capabilities in Internet Protocol network will open the opportunities to build a wide range of novel multimedia applications. The problem when using sensors (e.g. temperature sensor, camera, audio, humidity, etc.) connected to the network is to know dynamically at any time if they are always connected or not, what type of data they can transmit and where they are geographically located. This paper describes an application enabler: IMS Sensor Search Engine Enabler (iSSEE), which allows IMS applications using sensors and IMS based devices, to get information about the sensor availability, its location and the type of the sensor. Using data collected by sensors and from the web, mash-ups convergent applications use cases are proposed by combining the contents from heterogeneous data.


Emotions in Pervasive Computing Environments

Abstract: The ability of an intelligent environment to connect and adapt to real internal sates, needs and behaviors' meaning of humans can be made possible by considering users' emotional states as contextual parameters. In this paper, we build on enactive psychology and investigate the incorporation of emotions in pervasive systems. We define emotions, and discuss the coding of emotional human markers by smart environments. In addition, we compare some existing works and identify how emotions can be detected and modeled by a pervasive system in order to enhance its service and response to users. Finally, we analyze closely one XML-based language for representing and annotating emotions known as EARL and raise two important issues which pertain to emotion representation and modeling in XML-based languages.


Detection of Denial of Service Attacks against Domain Name System Using Neural Networks

Abstract: In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against Domain Name System (DNS). Our system architecture consists of two most important parts: a statistical preprocessor and a neural network classifier. The preprocessor extracts required statistical features in a shorttime frame from traffic received by the target name server. We compared three different neural networks for detecting and classifying different types of DoS attacks. The proposed system is evaluated in a simulated network and showed that the best performed neural network is a feed-forward backpropagation with an accuracy of 99%.


Parsing of part-of-speech tagged Assamese Texts

Abstract: A natural language (or ordinary language) is a language that is spoken, written, or signed by humans for general-purpose communication, as distinguished from formal languages (such as computer-programming languages or the "languages" used in the study of formal logic). The computational activities required for enabling a computer to carry out information processing using natural language is called natural language processing. We have taken Assamese language to check the grammars of the input sentence. Our aim is to produce a technique to check the grammatical structures of the sentences in Assamese text. We have made grammar rules by analyzing the structures of Assamese sentences. Our parsing program finds the grammatical errors, if any, in the Assamese sentence. If there is no error, the program will generate the parse tree for the Assamese sentence


Association Rule Pruning based on Interestingness Measures with Clustering

Abstract: Association rule mining plays vital part in knowledge mining. The difficult task is discovering knowledge or useful rules from the large number of rules generated for reduced support. For pruning or grouping rules, several techniques are used such as rule structure cover methods, informative cover methods, rule clustering, etc. Another way of selecting association rules is based on interestingness measures such as support, confidence, correlation, and so on. In this paper, we study how rule clusters of the pattern Xi - Y are distributed over different interestingness measures.


Using social annotation and web log to enhance search engine

Abstract: Search services have been developed rapidly in social Internet. It can help web users easily to find their documents. So that, finding a best method search is always an imagine. This paper would like introduce hybrid method of LPageRank algorithm and Social Sim Rank algorithm. LPageRank is the method using link structure to rank priority of page. It doesn't care content of page and content of query. Therefore, we want to use benefit of social annotations to create the latent semantic association between queries and annotations. This model, we use algorithm SocialPageRank and LPageRank to enhance accuracy of search system. To experiment and evaluate the proposed of the new model, we have used this model for Music Machine Website with their web logs.


Document Searching System based on Natural Language Query Processing for Vietnam Open Courseware Library

Abstract: The necessary of buiding the searching system being able to support users expressing their searching by natural language queries is very important and opens the researching direction with many potential. It combines the traditional methods of information retrieval and the researching of Question Answering (QA). In this paper, we introduce a searching system built by us for searching courses on the Vietnam OpenCourseWare Program (VOCW). It can be considered as the first tool to be able to perform the user's Vietnamese questions. The experiment results are rather good when we evaluate this system on the precision


Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph

Abstract: This paper proposes a method of gesture recognition with a focus on important actions for distinguishing similar gestures. The method generates a partial action sequence by using optical flow images, expresses the sequence in the eigenspace, and checks the feature vector sequence by applying an optimum path-searching method of weighted graph to focus the important actions. Also presented are the results of an experiment on the recognition of similar sign language words.


Lexicographic Multi-objective Geometric Programming Problems

Abstract: A Geometric programming (GP) is a type of mathematical problem characterized by objective and constraint functions that have a special form. Many methods have been developed to solve large scale engineering design GP problems. In this paper GP technique has been used to solve multi-objective GP problem as a vector optimization problem. The duality theory for lexicographic geometric programming has been developed to solve the problems with posynomial in objectives and constraints.


High Availability Cluster System for Local Disaster Recovery with Markov Modeling Approach

Abstract: The need for high availability (HA) and disaster recovery (DR) in IT environment is more stringent than most of the other sectors of enterprises. Many businesses require the availability of business-critical applications 24 hours a day, seven days a week, and can afford no data loss in the event of a disaster. It is vital that the IT infrastructure is resilient with regard to disruption, even site failures, and that business operations can continue without significant impact. As a result, DR has gained great importance in IT. Clustering of multiple industries standard servers together to allow workload sharing and fail-over capabilities is a low cost approach. In this paper, we present the availability model through Semi-Markov Process (SMP) and also analyze the difference in downtime of the SMP model and the approximate Continuous Time Markov Chain (CTMC) model. To acquire system availability, we perform numerical analysis and SHARPE tool evaluation.


A Brief History of Context

Abstract: Context is a rich concept and is an elusive concept to define. The concept of context has been studied by philosophers, linguists, psychologists, and recently by computer scientists. Within each research community the term context was interpreted in a certain way that is well-suited for their goals, however no attempt was made to define context. In many areas of research in computer science, notably on web-based services, human-computer interaction (HCI), ubiquitous computing applications, and context-aware systems there is a need to provide a formal operational definition of context. In this brief survey an account of the early work on context, as well as the recent work on many working definitions of context, context modeling, and a formalization of context are given. An attempt is made to unify the different context models within the formalization. A brief commentary on the usefulness of the formalization in the development of context-aware and dependable systems is included.


ICT in Universities of the Western Himalayan Region in India: Status, Performance- An Assessment

Abstract: The present paper describes a live project study carried out for the universities located in the western Himalayan region of India in the year 2009. The objective of this study is to undertake the task of assessment regarding initiative, utilization of ICT resources, its performance and impact in these higher educational institutions/universities. In order to answer these, initially basic four- tier framework was prepared. Followed by a questionnaire containing different ICT components 18 different groups like vision, planning, implementation, ICT infrastructure and related activities exhibiting performance. Primary data in the form of feedback on the five point scale, of the questionnaire, was gathered from six universities of the region. A simple statistical analysis was undertaken using weighted mean, to assess the ICT initiative, status and performance of various universities. In the process, a question related to Performance Indicator was identified from each group, whose Coefficient of Correlation was calculated. This study suggests that a progressive vision, planning and initiative regarding academic syllabi, ICT infrastructure, used in training the skilled human resource, is going to have a favourable impact through actual placement, research and play a dominant role at the National and International level.


Adaptive Scheduling of Data Paths using Uppaal Tiga

Abstract: We apply Uppaal Tiga to automatically compute adaptive scheduling strategies for an industrial case study dealing with a state-of-the-art image processing pipeline of a printer. As far as we know, this is the first application of timed automata technology to an industrial scheduling problem with uncertainty in job arrivals.


Markovian Testing Equivalence and Exponentially Timed Internal Actions

Abstract: In the theory of testing for Markovian processes developed so far, exponentially timed internal actions are not admitted within processes. When present, these actions cannot be abstracted away, because their execution takes a nonzero amount of time and hence can be observed. On the other hand, they must be carefully taken into account, in order not to equate processes that are distinguishable from a timing viewpoint. In this paper, we recast the definition of Markovian testing equivalence in the framework of a Markovian process calculus including exponentially timed internal actions. Then, we show that the resulting behavioral equivalence is a congruence, has a sound and complete axiomatization, has a modal logic characterization, and can be decided in polynomial time.


Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems

Abstract: This paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually specified as probabilistic system invariants and modeled in proof-based environments are evaluated using bounded model checking techniques. Our specific contributions include the statement of a theorem that is central to model checking safety properties of proof-based systems, the establishment of a procedure; and its full implementation in a prototype system (YAGA) which readily transforms a probabilistic model specified in a proof-based environment to its equivalent verifiable PRISM model equipped with reward structures. The reward structures capture the exact interpretation of the probabilistic invariants and can reveal succinct information about the model during experimental investigations. Finally, we demonstrate the novelty of the technique on a probabilistic library case study.


Modelling Clock Synchronization in the Chess gMAC WSN Protocol

Abstract: We present a detailled timed automata model of the clock synchronization algorithm that is currently being used in a wireless sensor network (WSN) that has been developed by the Dutch company Chess. Using the Uppaal model checker, we establish that in certain cases a static, fully synchronized network may eventually become unsynchronized if the current algorithm is used, even in a setting with infinitesimal clock drifts.


Strong, Weak and Branching Bisimulation for Transition Systems and Markov Reward Chains: A Unifying Matrix Approach

Abstract: We first study labeled transition systems with explicit successful termination. We establish the notions of strong, weak, and branching bisimulation in terms of boolean matrix theory, introducing thus a novel and powerful algebraic apparatus. Next we consider Markov reward chains which are standardly presented in real matrix theory. By interpreting the obtained matrix conditions for bisimulations in this setting, we automatically obtain the definitions of strong, weak, and branching bisimulation for Markov reward chains. The obtained strong and weak bisimulations are shown to coincide with some existing notions, while the obtained branching bisimulation is new, but its usefulness is questionable.


Verifying Real-Time Systems using Explicit-time Description Methods

Abstract: Timed model checking has been extensively researched in recent years. Many new formalisms with time extensions and tools based on them have been presented. On the other hand, Explicit-Time Description Methods aim to verify real-time systems with general untimed model checkers. Lamport presented an explicit-time description method using a clock-ticking process (Tick) to simulate the passage of time together with a group of global variables for time requirements. This paper proposes a new explicit-time description method with no reliance on global variables. Instead, it uses rendezvous synchronization steps between the Tick process and each system process to simulate time. This new method achieves better modularity and facilitates usage of more complex timing constraints. The two explicit-time description methods are implemented in DIVINE, a well-known distributed-memory model checker. Preliminary experiment results show that our new method, with better modularity, is comparable to Lamport's method with respect to time and memory efficiency.


Peer-to-Peer Cloud Provisioning: Service Discovery and Load-Balancing

Abstract: This chapter presents: (i) a layered peer-to-peer Cloud provisioning architecture; (ii) a summary of the current state-of-the-art in Cloud provisioning with particular emphasis on service discovery and load-balancing; (iii) a classification of the existing peer-to-peer network management model with focus on extending the DHTs for indexing and managing complex provisioning information; and (iv) the design and implementation of novel, extensible software fabric (Cloud peer) that combines public/private clouds, overlay networking and structured peer-to-peer indexing techniques for supporting scalable and self-managing service discovery and load-balancing in Cloud computing environments. Finally, an experimental evaluation is presented that demonstrates the feasibility of building next generation Cloud provisioning systems based on peer-to-peer network management and information dissemination models. The experimental test-bed has been deployed on a public cloud computing platform, Amazon EC2, which demonstrates the effectiveness of the proposed peer-to-peer Cloud provisioning software fabric.


Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks

Abstract: Recently, an image scrambling encryption algorithm of pixel bit based on chaos map was proposed. Considering the algorithm as a typical binary image scrambling/permutation algorithm exerting on plaintext of size $M\times (8N)$, this paper proposes a novel optimal method to break it with some known/chosen-plaintexts. The spatial complexity and computational complexity of the attack are only $O(32\cdot MN)$ and $O(16\cdot n_0\cdot MN)$ respectively, where $n_0$ is the number of known/chosen-plaintexts used. The method can be easily extended to break any permutation-only encryption scheme exerting on plaintext of size $M\times N$ and with $L$ different levels of values. The corresponding spatial complexity and computational complexity are only $O(MN)$ and $O(\lceil\log_L(MN)\rceil \cdot MN)$ respectively. In addition, some specific remarks on the performance of the image scrambling encryption algorithm are presented.


An L(1/3) algorithm for ideal class group and regulator computation in certain number fields

Abstract: We analyse the complexity of the computation of the class group structure, regulator, and a system of fundamental units of a certain class of number fields. Our approach differs from Buchmann's, who proved a complexity bound of L(1/2,O(1)) when the discriminant tends to infinity with fixed degree. We achieve a subexponential complexity in O(L(1/3,O(1))) when both the discriminant and the degree of the extension tend to infinity by using techniques due to Enge and Gaudry in the context of algebraic curves over finite fields.


Sponsored Search, Market Equilibria, and the Hungarian Method

Abstract: Matching markets play a prominent role in economic theory. A prime example of such a market is the sponsored search market. Here, as in other markets of that kind, market equilibria correspond to feasible, envy free, and bidder optimal outcomes. For settings without budgets such an outcome always exists and can be computed in polynomial-time by the so-called Hungarian Method. Moreover, every mechanism that computes such an outcome is incentive compatible. We show that the Hungarian Method can be modified so that it finds a feasible, envy free, and bidder optimal outcome for settings with budgets. We also show that in settings with budgets no mechanism that computes such an outcome can be incentive compatible for all inputs. For inputs in general position, however, the presented mechanism---as any other mechanism that computes such an outcome for settings with budgets---is incentive compatible.


Institutional Repository saber.ula.ve: A testimonial perspective

Abstract: In this paper, we describe our decade-long experience of building and operating one of the most active Institutional Repository in the world: www.saber.ula.ve <http://www.saber.ula.ve> (University of the Andes, Merida-Venezuela). In order to share our experience with other institutions, we firstly explain the steps we followed to preserve and disseminate the scientific production of the University of Los Andes' researchers. We then present some recent quantitative results about our repository activities and we outline some methodological guidelines that could be applied in order to replicate similar experiences. These guidelines list the ingredients or building blocks as well as the processes followed for developing and maintaining the services of an Institutional Repository. These include technological infrastructure; institutional policies on preservation, publication and dissemination of knowledge; recommendations on incentives for open access publication; the process of selection, testing and adaptation of technological tools; the planning and organization of services, and the dissemination and support within the scientific community that will eventually lead to the adoption of the ideas that lie behind the open access movement. We summarize the results obtained regarding the acceptance, adoption and use of the technological tools used for the publication of our institution's intellectual production, and we present the main obstacles encountered on the way.


Efficient Gaussian Elimination on a 2D SIMD Array of Processors without Column Broadcasts

Abstract: This paper presents an efficient method for implementing the Gaussian elimination technique for an nxm (m>=n) matrix, using a 2D SIMD array of nxm processors. The described algorithm consists of 2xn-1=O(n) iterations, which provides an optimal speed-up over the serial version. A particularity of the algorithm is that it only requires broadcasts on the rows of the processor matrix and not on its columns. The paper also presents several extensions and applications of the Gaussian elimination algorithm.


Computation Tree Logic with Deadlock Detection

Abstract: We study the equivalence relation on states of labelled transition systems of satisfying the same formulas in Computation Tree Logic without the next state modality (CTL-X). This relation is obtained by De Nicola & Vaandrager by translating labelled transition systems to Kripke structures, while lifting the totality restriction on the latter. They characterised it as divergence sensitive branching bisimulation equivalence. We find that this equivalence fails to be a congruence for interleaving parallel composition. The reason is that the proposed application of CTL-X to non-total Kripke structures lacks the expressiveness to cope with deadlock properties that are important in the context of parallel composition. We propose an extension of CTL-X, or an alternative treatment of non-totality, that fills this hiatus. The equivalence induced by our extension is characterised as branching bisimulation equivalence with explicit divergence, which is, moreover, shown to be the coarsest congruence contained in divergence sensitive branching bisimulation equivalence.


Dispersion in disks

Abstract: We present three new approximation algorithms with improved constant ratios for selecting $n$ points in $n$ disks such that the minimum pairwise distance among the points is maximized. (1) A very simple $O(n\log n)$-time algorithm with ratio $0.511$ for disjoint unit disks. (2) An LP-based algorithm with ratio $0.707$ for disjoint disks of arbitrary radii that uses a linear number of variables and constraints, and runs in polynomial time. (3) A hybrid algorithm with ratio either $0.4487$ or $0.4674$ for (not necessarily disjoint) unit disks that uses an algorithm of Cabello in combination with either the simple $O(n\log n)$-time algorithm or the LP-based algorithm. The LP algorithm can be extended for disjoint balls of arbitrary radii in $\RR^d$, for any (fixed) dimension $d$, while preserving the features of the planar algorithm. The algorithm introduces a novel technique which combines linear programming and projections for approximating Euclidean distances. The previous best approximation ratio for dispersion in disjoint disks, even when all disks have the same radius, was $1/2$. Our results give a partial answer to an open question raised by Cabello, who asked whether the ratio $1/2$ could be improved.


Proceedings First Workshop on Quantitative Formal Methods: Theory and Applications

Abstract: This volume contains the papers presented at the 1st workshop on Quantitative Formal Methods: Theory and Applications, which was held in Eindhoven on 3 November 2009 as part of the International Symposium on Formal Methods 2009. This volume contains the final versions of all contributions accepted for presentation at the workshop.


Enterprise Multi-Branch Database Synchronization with MSMQ

Abstract: When we talk about databases there have always been problems concerning data synchronization. The latter is a technique for maintaining consistency among different copies of data (often called replicas). In general, there is no universal solution to this problem and often a particular situation requires a particular approach driven by specific conditions. This paper presents an approach tackling the issue of data synchronization in a distributed multi-branch enterprise database. The proposed solution is based on MSMQ (Microsoft Message Queue), a mechanism for asynchronous messaging.


Effective Carrier Sensing in CSMA Networks under Cumulative Interference

Abstract: This paper proposes and investigates the concept of a safe carrier-sensing range that can guarantee interference safe (also termed hidden-node-free) transmissions in CSMA networks under the cumulative interference model. Compared with the safe carrier-sensing range under the commonly assumed but less realistic pairwise interference model, we show that the safe carrier-sensing range required under the cumulative interference model is larger by a constant multiplicative factor. The concept of a safe carrier-sensing range, although amenable to elegant analytical results, is inherently not compatible with the conventional power threshold carrier-sensing mechanism (e.g., that used in IEEE 802.11). Specifically, the absolute power sensed by a node in the conventional mechanism does not contain enough information for it to derive its distances from other concurrent transmitter nodes. We show that, fortunately, a carrier-sensing mechanism called Incremental-Power Carrier-Sensing (IPCS) can realize the carrier-sensing range concept in a simple way. Instead of monitoring the absolute detected power, the IPCS mechanism monitors every increment in the detected power. This means that IPCS can separate the detected power of every concurrent transmitter, and map the power profile to the required distance information.


Matrix Graph Grammars: Transformation of Restrictions

Abstract: In the Matrix approach to graph transformation we represent simple digraphs and rules with Boolean matrices and vectors, and the rewriting is expressed using Boolean operations only. In previous works, we developed analysis techniques enabling the study of the applicability of rule sequences, their independence, stated reachability and the minimal digraph able to fire a sequence. In [20], graph constraints and application conditions (so-called restrictions) have been studied in detail. In the present contribution we tackle the problem of translating post-conditions into pre-conditions and vice versa. Moreover, we shall see that application conditions can be moved along productions inside a sequence (restriction delocalization). As a practical-theoretical application we show how application conditions allow us to perform multidigraph rewriting (as opposed to simple digraph rewriting) using Matrix Graph Grammars


The Smallville Effect: Social Ties Make Mobile Networks More Secure Against the Node Capture Attack

Abstract: Mobile Ad Hoc networks, due to the unattended nature of the network itself and the dispersed location of nodes, are subject to several unique security issues. One of the most vexed security threat is node capture. A few solutions have already been proposed to address this problem; however, those solutions are either centralized or focused on theoretical mobility models alone. In the former case the solution does not fit well the distributed nature of the network while, in the latter case, the quality of the solutions obtained for realistic mobility models severely differs from the results obtained for theoretical models. The rationale of this paper is inspired by the observation that re-encounters of mobile nodes do elicit a form of social ties. Leveraging these ties, it is possible to design efficient and distributed algorithms that, with a moderated degree of node cooperation, enforce the emergent property of node capture detection. In particular, in this paper we provide a proof of concept proposing a set of algorithms that leverage, to different extent, node mobility and node cooperation--that is, identifying social ties--to thwart node capture attack. In particular, we test these algorithms on a realistic mobility scenario. Extensive simulations show the quality of the proposed solutions and, more important, the viability of the proposed approach.


Computing a Discrete Logarithm in O(n^3)

Abstract: This paper presents a means with time complexity of at worst O(n^3) to compute the discrete logarithm on cyclic finite groups of integers modulo p. The algorithm makes use of reduction of the problem to that of finding the concurrent zeros of two periodic functions in the real numbers. The problem is treated as an analog to a form of analog rotor-code computed cipher.


Design of Intelligent layer for flexible querying in databases

Abstract: Computer-based information technologies have been extensively used to help many organizations, private companies, and academic and education institutions manage their processes and information systems hereby become their nervous centre. The explosion of massive data sets created by businesses, science and governments necessitates intelligent and more powerful computing paradigms so that users can benefit from this data. Therefore most new-generation database applications demand intelligent information management to enhance efficient interactions between database and the users. Database systems support only a Boolean query model. A selection query on SQL database returns all those tuples that satisfy the conditions in the query.


Evaluation of Varrying Mobility Models & Network Loads on DSDV Protocol of MANETs

Abstract: A mobile ad-hoc network (MANET) is collection of intercommunicating mobile hosts forming a spontaneous network without using established network infrastructure. Unlike the cellular or infrastructure networks who have a wired backbone connecting the base-station, the MANETs have neither fixed routers nor fixed locations. Their performance largely depend upon the routing mechanism & nature of mobility. Earlier research hints that the Destination Sequenced Distance Vector (DSDV) routing protocol is one of the most efficient and popular protocols, as far as general parameters have been concerned.[1,6] We have experimentally evaluated, the performance metrics for network load, packet delivery fraction and end-to-end delay with DSDV Protocol using NS2 Simulator.This paper presents, the performance of DSDV protocol for four different mobility models namely: Random Waypoint, Reference Point Group Mobility, Gauss Markov & Manhattan Mobility Model having varying network load & speed. The experimental results suggest that DSDV protocol with RPGM mobility model has optimized results for varying network load and speed.


Security Visualization for peer-to-peer resource sharing applications

Abstract: Security of an information system is only as strong as its weakest element. Popular elements of such system include hardware, software, network and people. Current approaches to computer security problems usually exclude people in their studies even though it is an integral part of these systems. To fill that gap, this paper discusses crucial people-related problems in computer security and proposes a method of improving security in such systems by integrating people tightly into the whole system. The integration is implemented via visualization to provide visual feedbacks and capture people's awareness of their actions and consequent results. By doing it, we can improve system usability, shorten user's learning curve, and hence enable user uses computer systems more securely.


Detection and Prevention of New and Unknown Malware using Honeypots

Abstract: Security has become ubiquitous in every domain today as newly emerging malware pose an ever-increasing perilous threat to systems. Consequently, honeypots are fast emerging as an indispensible forensic tool for the analysis of malicious network traffic. Honeypots can be considered to be traps for hackers and intruders and are generally deployed complimentary to Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) in a network. They help system administrators perform a rigorous analysis of external and internal attacks on their networks. They are also used by security firms and research labs to capture the latest variants of malware. However, honeypots would serve a slightly different purpose in our proposed system. We intend to use honeypots for generating and broadcasting instant cures for new and unknown malware in a network. The cures which will be in the form of on-the-fly anti-malware signatures would spread in a fashion that is similar to the way malware spreads across networks. The most striking advantage of implementing this technology is that an effective initial control can be exercised on malware. Proposed system would be capable of providing cures for new fatal viruses which have not yet been discovered by prime security firms of the world.


A QoS-Aware Intelligent Replica Management Architecture for Content Distribution in Peer-to-Peer Overlay Networks

Abstract: The large scale content distribution systems were improved broadly using the replication techniques. The demanded contents can be brought closer to the clients by multiplying the source of information geographically, which in turn reduce both the access latency and the network traffic. The system scalability can be improved by distributing the load across multiple servers which is proposed by replication. If a copy of the requested object (e.g., a web page or an image) is located in its closer proximity then the clients would feel low access latency. Depending on the position of the replicas, the effectiveness of replication tends to a large extent. A QoS based overlay network architecture involving an intelligent replica placement algorithm is proposed in this paper. Its main goal is to improve the network utilization and fault tolerance of the P2P system. In addition to the replica placement, it also has a caching technique, to reduce the search latency. We are able to show that our proposed architecture attains less latency and better throughput with reduced bandwidth usage, through the simulation results.


Performance Metrics Analysis of Torus Embedded Hypercube Interconnection Network

Abstract: Advantages of hypercube network and torus topology are used to derive an embedded architecture for product network known as torus embedded hypercube scalable interconnection network. This paper analyzes torus embedded hypercube network pertinent to parallel architecture. The network metrics are used to show how good embedded network can be designed for parallel computation. Network parameter analysis and comparison of embedded network with basic networks is presented.


Fault Predictions in Object Oriented Software

Abstract: The dynamic software development organizations optimize the usage of resources to deliver the products in the specified time with the fulfilled requirements. This requires prevention or repairing of the faults as quick as possible. In this paper an approach for predicting the run-time errors in java is introduced. The paper is concerned with faults due to inheritance and violation of java constraints. The proposed fault prediction model is designed to separate the faulty classes in the field of software testing. Separated faulty classes are classified according to the fault occurring in the specific class. The results are papered by clustering the faults in the class. This model can be used for predicting software reliability.


Synthesis of supervised classification algorithm using intelligent and statistical tools

Abstract: A fundamental task in detecting foreground objects in both static and dynamic scenes is to take the best choice of color system representation and the efficient technique for background modeling. We propose in this paper a non-parametric algorithm dedicated to segment and to detect objects in color images issued from a football sports meeting. Indeed segmentation by pixel concern many applications and revealed how the method is robust to detect objects, even in presence of strong shadows and highlights. In the other hand to refine their playing strategy such as in football, handball, volley ball, Rugby..., the coach need to have a maximum of technical-tactics information about the on-going of the game and the players. We propose in this paper a range of algorithms allowing the resolution of many problems appearing in the automated process of team identification, where each player is affected to his corresponding team relying on visual data. The developed system was tested on a match of the Tunisian national competition. This work is prominent for many next computer vision studies as it's detailed in this study.


Survey of clustering algorithms for MANET

Abstract: Many clustering schemes have been proposed for ad hoc networks. A systematic classification of these clustering schemes enables one to better understand and make improvements. In mobile ad hoc networks, the movement of the network nodes may quickly change the topology resulting in the increase of the overhead message in topology maintenance. Protocols try to keep the number of nodes in a cluster around a pre-defined threshold to facilitate the optimal operation of the medium access control protocol. The clusterhead election is invoked on-demand, and is aimed to reduce the computation and communication costs. A large variety of approaches for ad hoc clustering have been developed by researchers which focus on different performance metrics. This paper presents a survey of different clustering schemes.


PKI Implementation Issues: A Comparative Study of Pakistan with some Asian Countries

Abstract: The paper includes Public Key Infrastructure (PKI), its need and requirements and introduction of some renowned PKI products. However, the major thrust of this work is that how PKI can enhance security of various systems. The paper is intended to serve as a guide on how to adequately prepare for some of the challenges that may be encountered especially in developing countries like Pakistan. The detail of PKI implementation issues is also included in the paper along with future challenges regarding implementation of PKI. Furthermore, paper includes technical issues hindering the implementation of PKI through comparison of PKI issues in Pakistan and some of Asian countries mainly Taiwan, Japan and Singapore. The paper also highlights the PKI issues and learnt lessons regarding PKI implementation and can act as a comprehensive guide for successful future PKI deployments.


Rank Based Clustering For Document Retrieval From Biomedical Databases

Abstract: Now a day's, search engines are been most widely used for extracting information's from various resources throughout the world. Where, majority of searches lies in the field of biomedical for retrieving related documents from various biomedical databases. Currently search engines lacks in document clustering and representing relativeness level of documents extracted from the databases. In order to overcome these pitfalls a text based search engine have been developed for retrieving documents from Medline and PubMed biomedical databases. The search engine has incorporated page ranking bases clustering concept which automatically represents relativeness on clustering bases. Apart from this graph tree construction is made for representing the level of relatedness of the documents that are networked together. This advance functionality incorporation for biomedical document based search engine found to provide better results in reviewing related documents based on relativeness.


NeuralNetwork Based 3D Surface Reconstruction

Abstract: This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach


Early Detection of Breast Cancer using SVM Classifier Technique

Abstract: This paper presents a tumor detection algorithm from mammogram. The proposed system focuses on the solution of two problems. One is how to detect tumors as suspicious regions with a very weak contrast to their background and another is how to extract features which categorize tumors. The tumor detection method follows the scheme of (a) mammogram enhancement. (b) The segmentation of the tumor area. (c) The extraction of features from the segmented tumor area. (d) The use of SVM classifier. The enhancement can be defined as conversion of the image quality to a better and more understandable level. The mammogram enhancement procedure includes filtering, top hat operation, DWT. Then the contrast stretching is used to increase the contrast of the image. The segmentation of mammogram images has been playing an important role to improve the detection and diagnosis of breast cancer. The most common segmentation method used is thresholding. The features are extracted from the segmented breast area. Next stage include, which classifies the regions using the SVM classifier. The method was tested on 75 mammographic images, from the mini-MIAS database. The methodology achieved a sensitivity of 88.75%.


Steganography An Art of Hiding Data

Abstract: In today's world the art of sending & displaying the hidden information especially in public places, has received more attention and faced many challenges. Therefore, different methods have been proposed so far for hiding information in different cover media. In this paper a method for hiding of information on the billboard display is presented. It is well known that encryption provides secure channels for communicating entities. However, due to lack of covertness on these channels, an eavesdropper can identify encrypted streams through statistical tests and capture them for further cryptanalysis. In this paper we propose a new form of steganography, on-line hiding of information on the output screens of the instrument. This method can be used for announcing a secret message in public place. It can be extended to other means such as electronic advertising board around sports stadium, railway station or airport. This method of steganography is very similar to image steganography and video steganography. Private marking system using symmetric key steganography technique and LSB technique is used here for hiding the secret information.


Identifying the Importance of Software Reuse in COCOMO81, COCOMOII

Abstract: Software project management is an interpolation of project planning, project monitoring and project termination. The substratal goals of planning are to scout for the future, to diagnose the attributes that are essentially done for the consummation of the project successfully, animate the scheduling and allocate resources for the attributes. Software cost estimation is a vital role in preeminent software project decisions such as resource allocation and bidding. This paper articulates the conventional overview of software cost estimation modus operandi available. The cost, effort estimates of software projects done by the various companies are congregated, the results are segregated with the present cost models and the MRE (Mean Relative Error) is enumerated. We have administered the historical data to COCOMO 81, COCOMOII model and identified that the stellar predicament is that no cost model gives the exact estimate of a software project.


Faster Algorithms for Finding and Counting Subgraphs

Abstract: In this paper we study a natural generalization of both {\sc $k$-Path} and {\sc $k$-Tree} problems, namely, the {\sc Subgraph Isomorphism} problem. In the {\sc Subgraph Isomorphism} problem we are given two graphs $F$ and $G$ on $k$ and $n$ vertices respectively as an input, and the question is whether there exists a subgraph of $G$ isomorphic to $F$. We show that if the treewidth of $F$ is at most $t$, then there is a randomized algorithm for the {\sc Subgraph Isomorphism} problem running in time $\cO^*(2^k n^{2t})$. To do so, we associate a new multivariate {Homomorphism polynomial} of degree at most $k$ with the {\sc Subgraph Isomorphism} problem and construct an arithmetic circuit of size at most $n^{\cO(t)}$ for this polynomial. Using this polynomial, we also give a deterministic algorithm to count the number of homomorphisms from $F$ to $G$ that takes $n^{\cO(t)}$ time and uses polynomial space. For the counting version of the {\sc Subgraph Isomorphism} problem, where the objective is to count the number of distinct subgraphs of $G$ that are isomorphic to $F$, we give a deterministic algorithm running in time and space $\cO^*({n \choose k/2}n^{2p})$ or ${n\choose k/2}n^{\cO(t \log k)}$. We also give an algorithm running in time $\cO^{*}(2^{k}{n \choose k/2}n^{5p})$ and taking space polynomial in $n$. Here $p$ and $t$ denote the pathwidth and the treewidth of $F$, respectively. Thus our work not only improves on known results on {\sc Subgraph Isomorphism} but it also extends and generalize most of the known results on {\sc $k$-Path} and {\sc $k$-Tree}.


Closing the Learning-Planning Loop with Predictive State Representations

Abstract: A central problem in artificial intelligence is that of planning to maximize future reward under uncertainty in a partially observable environment. In this paper we propose and demonstrate a novel algorithm which accurately learns a model of such an environment directly from sequences of action-observation pairs. We then close the loop from observations to actions by planning in the learned model and recovering a policy which is near-optimal in the original environment. Specifically, we present an efficient and statistically consistent spectral algorithm for learning the parameters of a Predictive State Representation (PSR). We demonstrate the algorithm by learning a model of a simulated high-dimensional, vision-based mobile robot planning task, and then perform approximate point-based planning in the learned PSR. Analysis of our results shows that the algorithm learns a state space which efficiently captures the essential features of the environment. This representation allows accurate prediction with a small number of parameters, and enables successful and efficient planning.


Succinct Coverage Oracles

Abstract: In this paper, we identify a fundamental algorithmic problem that we term succinct dynamic covering (SDC), arising in many modern-day web applications, including ad-serving and online recommendation systems in eBay and Netflix. Roughly speaking, SDC applies two restrictions to the well-studied Max-Coverage problem: Given an integer k, X={1,2,...,n} and I={S_1, ..., S_m}, S_i a subset of X, find a subset J of I, such that |J| <= k and the union of S in J is as large as possible. The two restrictions applied by SDC are: (1) Dynamic: At query-time, we are given a query Q, a subset of X, and our goal is to find J such that the intersection of Q with the union of S in J is as large as possible; (2) Space-constrained: We don't have enough space to store (and process) the entire input; specifically, we have o(mn), and maybe as little as O((m+n)polylog(mn)) space. The goal of SDC is to maintain a small data structure so as to answer most dynamic queries with high accuracy. We call such a scheme a Coverage Oracle. We present algorithms and complexity results for coverage oracles. We present deterministic and probabilistic near-tight upper and lower bounds on the approximation ratio of SDC as a function of the amount of space available to the oracle. Our lower bound results show that to obtain constant-factor approximations we need Omega(mn) space. Fortunately, our upper bounds present an explicit tradeoff between space and approximation ratio, allowing us to determine the amount of space needed to guarantee certain accuracy.


Adapting Heuristic Mastermind Strategies to Evolutionary Algorithms

Abstract: The art of solving the Mastermind puzzle was initiated by Donald Knuth and is already more than 30 years old; despite that, it still receives much attention in operational research and computer games journals, not to mention the nature-inspired stochastic algorithm literature. In this paper we try to suggest a strategy that will allow nature-inspired algorithms to obtain results as good as those based on exhaustive search strategies; in order to do that, we first review, compare and improve current approaches to solving the puzzle; then we test one of these strategies with an estimation of distribution algorithm. Finally, we try to find a strategy that falls short of being exhaustive, and is then amenable for inclusion in nature inspired algorithms (such as evolutionary or particle swarm algorithms). This paper proves that by the incorporation of local entropy into the fitness function of the evolutionary algorithm it becomes a better player than a random one, and gives a rule of thumb on how to incorporate the best heuristic strategies to evolutionary algorithms without incurring in an excessive computational cost.


Prediction-Based Data Transmission for Energy Conservation in Wireless Body Sensors

Abstract: Wireless body sensors are becoming popular in healthcare applications. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. The energy consequently becomes an extremely scarce resource, and energy conservation turns into a first class design issue for body sensor networks (BSNs). This paper deals with this issue by taking into account the unique characteristics of BSNs in contrast to conventional wireless sensor networks (WSNs) for e.g. environment monitoring. A prediction-based data transmission approach suitable for BSNs is presented, which combines a dual prediction framework and a low-complexity prediction algorithm that takes advantage of PID (proportional-integral-derivative) control. Both the framework and the algorithm are generic, making the proposed approach widely applicable. The effectiveness of the approach is verified through simulations using real-world health monitoring datasets.


Pervasive Emotions in Pervasive Computing Environments

Abstract: This submission has been withdrawn by arXiv admin. It is a verbatim copy of arXiv:0912.1810 with only the author name and title changed.


Markov Modeling of Cooperative Multiplayer Coupon Collectors' Problems

Abstract: The paper introduces a modified version of the classical Coupon Collector's Problem entailing exchanges and cooperation between multiple players. Results of the development show that, within a proper Markov framework, the complexity of the Cooperative Multiplayer Coupon Collectors' Problem can be attacked with an eye to the modeling of resource harvesting and sharing within the context of Next Generation Network. The cost of cooperation is computed in terms of exchange protocol burden and found to be dependent on only ensemble parameters such as the number of players and the number of coupons but not on the detailed collection statistics. The benefits of cooperation are quantified in terms of reduction of the average number of actions before collection completion.


Towards Utility-driven Anonymization of Transactions

Abstract: Publishing person-specific transactions in an anonymous form is increasingly required by organizations. Recent approaches ensure that potentially identifying information (e.g., a set of diagnosis codes) cannot be used to link published transactions to persons' identities, but all are limited in application because they incorporate coarse privacy requirements (e.g., protecting a certain set of m diagnosis codes requires protecting all m-sized sets), do not integrate utility requirements, and tend to explore a small portion of the solution space. In this paper, we propose a more general framework for anonymizing transactional data under specific privacy and utility requirements. We model such requirements as constraints, investigate how these constraints can be specified, and propose COAT (COnstraint-based Anonymization of Transactions), an algorithm that anonymizes transactions using a flexible hierarchy-free generalization scheme to meet the specified constraints. Experiments with benchmark datasets verify that COAT significantly outperforms the current state-of-the-art algorithm in terms of data utility, while being comparable in terms of efficiency. The effectiveness of our approach is also demonstrated in a real-world scenario, which requires disseminating a private, patient-specific transactional dataset in a way that preserves both privacy and utility in intended studies.


Formal Aspects of Grid Brokering

Abstract: Coordination in distributed environments, like Grids, involves selecting the most appropriate services, resources or compositions to carry out the planned activities. Such functionalities appear at various levels of the infrastructure and in various means forming a blurry domain, where it is hard to see how the participating components are related and what their relevant properties are. In this paper we focus on a subset of these problems: resource brokering in Grid middleware. This paper aims at establishing a semantical model for brokering and related activities by defining brokering agents at three levels of the Grid middleware for resource, host and broker selection. The main contribution of this paper is the definition and decomposition of different brokering components in Grids by providing a formal model using Abstract State Machines.


Distributed Branching Bisimulation Minimization by Inductive Signatures

Abstract: We present a new distributed algorithm for state space minimization modulo branching bisimulation. Like its predecessor it uses signatures for refinement, but the refinement process and the signatures have been optimized to exploit the fact that the input graph contains no tau-loops. The optimization in the refinement process is meant to reduce both the number of iterations needed and the memory requirements. In the former case we cannot prove that there is an improvement, but our experiments show that in many cases the number of iterations is smaller. In the latter case, we can prove that the worst case memory use of the new algorithm is linear in the size of the state space, whereas the old algorithm has a quadratic upper bound. The paper includes a proof of correctness of the new algorithm and the results of a number of experiments that compare the performance of the old and the new algorithms.


Tarmo: A Framework for Parallelized Bounded Model Checking

Abstract: This paper investigates approaches to parallelizing Bounded Model Checking (BMC) for shared memory environments as well as for clusters of workstations. We present a generic framework for parallelized BMC named Tarmo. Our framework can be used with any incremental SAT encoding for BMC but for the results in this paper we use only the current state-of-the-art encoding for full PLTL. Using this encoding allows us to check both safety and liveness properties, contrary to an earlier work on distributing BMC that is limited to safety properties only. Despite our focus on BMC after it has been translated to SAT, existing distributed SAT solvers are not well suited for our application. This is because solving a BMC problem is not solving a set of independent SAT instances but rather involves solving multiple related SAT instances, encoded incrementally, where the satisfiability of each instance corresponds to the existence of a counterexample of a specific length. Our framework includes a generic architecture for a shared clause database that allows easy clause sharing between SAT solver threads solving various such instances. We present extensive experimental results obtained with multiple variants of our Tarmo implementation. Our shared memory variants have a significantly better performance than conventional single threaded approaches, which is a result that many users can benefit from as multi-core and multi-processor technology is widely available. Furthermore we demonstrate that our framework can be deployed in a typical cluster of workstations, where several multi-core machines are connected by a network.


An Efficient Explicit-time Description Method for Timed Model Checking

Abstract: Timed model checking, the method to formally verify real-time systems, is attracting increasing attention from both the model checking community and the real-time community. Explicit-time description methods verify real-time systems using general model constructs found in standard un-timed model checkers. Lamport proposed an explicit-time description method using a clock-ticking process (Tick) to simulate the passage of time together with a group of global variables to model time requirements. Two methods, the Sync-based Explicit-time Description Method using rendezvous synchronization steps and the Semaphore-based Explicit-time Description Method using only one global variable were proposed; they both achieve better modularity than Lamport's method in modeling the real-time systems. In contrast to timed automata based model checkers like UPPAAL, explicit-time description methods can access and store the current time instant for future calculations necessary for many real-time systems, especially those with pre-emptive scheduling. However, the Tick process in the above three methods increments the time by one unit in each tick; the state spaces therefore grow relatively fast as the time parameters increase, a problem when the system's time period is relatively long. In this paper, we propose a more efficient method which enables the Tick process to leap multiple time units in one tick. Preliminary experimental results in a high performance computing environment show that this new method significantly reduces the state space and improves both the time and memory efficiency.


Parallelizing Deadlock Resolution in Symbolic Synthesis of Distributed Programs

Abstract: Previous work has shown that there are two major complexity barriers in the synthesis of fault-tolerant distributed programs: (1) generation of fault-span, the set of states reachable in the presence of faults, and (2) resolving deadlock states, from where the program has no outgoing transitions. Of these, the former closely resembles with model checking and, hence, techniques for efficient verification are directly applicable to it. Hence, we focus on expediting the latter with the use of multi-core technology. We present two approaches for parallelization by considering different design choices. The first approach is based on the computation of equivalence classes of program transitions (called group computation) that are needed due to the issue of distribution (i.e., inability of processes to atomically read and write all program variables). We show that in most cases the speedup of this approach is close to the ideal speedup and in some cases it is superlinear. The second approach uses traditional technique of partitioning deadlock states among multiple threads. However, our experiments show that the speedup for this approach is small. Consequently, our analysis demonstrates that a simple approach of parallelizing the group computation is likely to be the effective method for using multi-core computing in the context of deadlock resolution.


DiVinE-CUDA - A Tool for GPU Accelerated LTL Model Checking

Abstract: In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate that the tool outperforms non-accelerated version of the algorithm and we discuss where the limits of the tool are and what we intend to do in the future to avoid them.


Construction Sequences and Certifying 3-Connectedness

Abstract: Tutte proved that every 3-connected graph on more than 4 nodes has a contractible edge. Barnette and Gruenbaum proved the existence of a removable edge in the same setting. We show that the sequence of contractions and the sequence of removals from G to the K_4 can be computed in O(|V|^2) time by extending Barnette and Gruenbaum's theorem. As an application, we derive a certificate for the 3-connectedness of graphs that can be easily computed and verified.


Deterministic Identity Testing of Read-Once Algebraic Branching Programs

Abstract: In this paper we study polynomial identity testing of sums of $k$ read-once algebraic branching programs ($\Sigma_k$-RO-ABPs), generalizing the work in (Shpilka and Volkovich 2008,2009), who considered sums of $k$ read-once formulas ($\Sigma_k$-RO-formulas). We show that $\Sigma_k$-RO-ABPs are strictly more powerful than $\Sigma_k$-RO-formulas, for any $k \leq \lfloor n/2\rfloor$, where $n$ is the number of variables. We obtain the following results: 1) Given free access to the RO-ABPs in the sum, we get a deterministic algorithm that runs in time $O(k^2n^7s) + n^{O(k)}$, where $s$ bounds the size of any largest RO-ABP given on the input. This implies we have a deterministic polynomial time algorithm for testing whether the sum of a constant number of RO-ABPs computes the zero polynomial. 2) Given black-box access to the RO-ABPs computing the individual polynomials in the sum, we get a deterministic algorithm that runs in time $k^2n^{O(\log n)} + n^{O(k)}$. 3) Finally, given only black-box access to the polynomial computed by the sum of the $k$ RO-ABPs, we obtain an $n^{O(k + \log n)}$ time deterministic algorithm.


QR Factorization of Tall and Skinny Matrices in a Grid Computing Environment

Abstract: Previous studies have reported that common dense linear algebra operations do not achieve speed up by using multiple geographical sites of a computational grid. Because such operations are the building blocks of most scientific applications, conventional supercomputers are still strongly predominant in high-performance computing and the use of grids for speeding up large-scale scientific problems is limited to applications exhibiting parallelism at a higher level. We have identified two performance bottlenecks in the distributed memory algorithms implemented in ScaLAPACK, a state-of-the-art dense linear algebra library. First, because ScaLAPACK assumes a homogeneous communication network, the implementations of ScaLAPACK algorithms lack locality in their communication pattern. Second, the number of messages sent in the ScaLAPACK algorithms is significantly greater than other algorithms that trade flops for communication. In this paper, we present a new approach for computing a QR factorization -- one of the main dense linear algebra kernels -- of tall and skinny matrices in a grid computing environment that overcomes these two bottlenecks. Our contribution is to articulate a recently proposed algorithm (Communication Avoiding QR) with a topology-aware middleware (QCG-OMPI) in order to confine intensive communications (ScaLAPACK calls) within the different geographical sites. An experimental study conducted on the Grid'5000 platform shows that the resulting performance increases linearly with the number of geographical sites on large-scale problems (and is in particular consistently higher than ScaLAPACK's).


The first Italian research assessment exercise: a bibliometric perspective

Abstract: In December 2003, seventeen years after the first UK research assessment exercise, Italy started up its first-ever national research evaluation, with the aim to evaluate, using the peer review method, the excellence of the national research production. The evaluation involved 20 disciplinary areas, 102 research structures, 18,500 research products and 6,661 peer reviewers (1,465 from abroad); it had a direct cost of 3.55 millions Euros and a time length spanning over 18 months. The introduction of ratings based on ex post quality of output and not on ex ante respect for parameters and compliance is an important leap forward of the national research evaluation system toward meritocracy. From the bibliometric perspective, the national assessment offered the unprecedented opportunity to perform a large-scale comparison of peer review and bibliometric indicators for an important share of the Italian research production. The present investigation takes full advantage of this opportunity to test whether peer review judgements and (article and journal) bibliometric indicators are independent variables and, in the negative case, to measure the sign and strength of the association. Outcomes allow us to advocate the use of bibliometric evaluation, suitably integrated with expert review, for the forthcoming national assessment exercises, with the goal of shifting from the assessment of research excellence to the evaluation of average research performance without significant increase of expenses.


The Multivariate Resultant is NP-hard in any Characteristic

Abstract: The multivariate resultant is a fundamental tool of computational algebraic geometry. It can in particular be used to decide whether a system of n homogeneous equations in n variables is satisfiable (the resultant is a polynomial in the system's coefficients which vanishes if and only if the system is satisfiable). In this paper we present several NP-hardness results for testing whether a multivariate resultant vanishes, or equivalently for deciding whether a square system of homogeneous equations is satisfiable. Our main result is that testing the resultant for zero is NP-hard under deterministic reductions in any characteristic, for systems of low-degree polynomials with coefficients in the ground field (rather than in an extension). We also observe that in characteristic zero, this problem is in the Arthur-Merlin class AM if the generalized Riemann hypothesis holds true. In positive characteristic, the best upper bound remains PSPACE.


Is Ramsey's theorem omega-automatic?

Abstract: We study the existence of infinite cliques in omega-automatic (hyper-)graphs. It turns out that the situation is much nicer than in general uncountable graphs, but not as nice as for automatic graphs. More specifically, we show that every uncountable omega-automatic graph contains an uncountable co-context-free clique or anticlique, but not necessarily a context-free (let alone regular) clique or anticlique. We also show that uncountable omega-automatic ternary hypergraphs need not have uncountable cliques or anticliques at all.


On the theory of moveable objects

Abstract: User-driven applications belong to the new type of programs, in which users get the full control of WHAT, WHEN, and HOW must appear on the screen. Such programs can exist only if the screen view is organized not according with the predetermined scenario, written by the developers, but if any screen object can be moved, resized, and reconfigured by any user at any moment. This article describes the algorithm, by which an object of an arbitrary shape can be turned into moveable and resizable. It also explains some rules of such design and the technique, which can be useful in many cases. Both the individual movements of objects and their synchronous movements are analysed. After discussing the individually moveable controls, different types of groups are analysed and the arbitrary grouping of controls is considered.


The Gaussian Surface Area and Noise Sensitivity of Degree-$d$ Polynomials

Abstract: We provide asymptotically sharp bounds for the Gaussian surface area and the Gaussian noise sensitivity of polynomial threshold functions. In particular we show that if $f$ is a degree-$d$ polynomial threshold function, then its Gaussian sensitivity at noise rate $\epsilon$ is less than some quantity asymptotic to $\frac{d\sqrt{2\epsilon}}{\pi}$ and the Gaussian surface area is at most $\frac{d}{\sqrt{2\pi}}$. Furthermore these bounds are asymptotically tight as $\epsilon\to 0$ and $f$ the threshold function of a product of $d$ distinct homogeneous linear functions.


Parallel symbolic state-space exploration is difficult, but what is the alternative?

Abstract: State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal.


Combining Partial Order Alignment and Progressive Near-Optimal Alignment

Abstract: In this paper, I proposed to utilize partial-order alignment technique as a heuristic method to cope with the state-space explosion problem in progressive near-optimal alignment. The key idea of my approach is a formal treatment of progressive partial order alignment based on the graph product construction.


Relaxed spanners for directed disk graphs

Abstract: Let $(V,\delta)$ be a finite metric space, where $V$ is a set of $n$ points and $\delta$ is a distance function defined for these points. Assume that $(V,\delta)$ has a constant doubling dimension $d$ and assume that each point $p\in V$ has a disk of radius $r(p)$ around it. The disk graph that corresponds to $V$ and $r(\cdot)$ is a \emph{directed} graph $I(V,E,r)$, whose vertices are the points of $V$ and whose edge set includes a directed edge from $p$ to $q$ if $\delta(p,q)\leq r(p)$. In \cite{PeRo08} we presented an algorithm for constructing a $(1+\eps)$-spanner of size $O(n/\eps^d \log M)$, where $M$ is the maximal radius $r(p)$. The current paper presents two results. The first shows that the spanner of \cite{PeRo08} is essentially optimal, i.e., for metrics of constant doubling dimension it is not possible to guarantee a spanner whose size is independent of $M$. The second result shows that by slightly relaxing the requirements and allowing a small perturbation of the radius assignment, considerably better spanners can be constructed. In particular, we show that if it is allowed to use edges of the disk graph $I(V,E,r_{1+\eps})$, where $r_{1+\eps}(p) = (1+\eps)\cdot r(p)$ for every $p\in V$, then it is possible to get a $(1+\eps)$-spanner of size $O(n/\eps^d)$ for $I(V,E,r)$. Our algorithm is simple and can be implemented efficiently.


An iterative approach for generating statistically realistic populations of households

Abstract: Background: Many different simulation frameworks, in different topics, need to treat realistic datasets to initialize and calibrate the system. A precise reproduction of initial states is extremely important to obtain reliable forecast from the model. Methodology/Principal Findings: This paper proposes an algorithm to create an artificial population where individuals are described by their age, and are gathered in households respecting a variety of statistical constraints (distribution of household types, sizes, age of household head, difference of age between partners and among parents and children). Such a population is often the initial state of microsimulation or (agent) individual-based models. To get a realistic distribution of households is often very important, because this distribution has an impact on the demographic evolution. Usual techniques from microsimulation approach cross different sources of aggregated data for generating individuals. In our case the number of combinations of different households (types, sizes, age of participants) makes it computationally difficult to use directly such methods. Hence we developed a specific algorithm to make the problem more easily tractable. Conclusions/Significance: We generate the populations of two pilot municipalities in Auvergne region (France), to illustrate the approach. The generated populations show a good agreement with the available statistical datasets (not used for the generation) and are obtained in a reasonable computational time.


Intrusion Detection In Mobile Ad Hoc Networks Using GA Based Feature Selection

Abstract: Mobile ad hoc networking (MANET) has become an exciting and important technology in recent years because of the rapid proliferation of wireless devices. MANETs are highly vulnerable to attacks due to the open medium, dynamically changing network topology and lack of centralized monitoring point. It is important to search new architecture and mechanisms to protect the wireless networks and mobile computing application. IDS analyze the network activities by means of audit data and use patterns of well-known attacks or normal profile to detect potential attacks. There are two methods to analyze: misuse detection and anomaly detection. Misuse detection is not effective against unknown attacks and therefore, anomaly detection method is used. In this approach, the audit data is collected from each mobile node after simulating the attack and compared with the normal behavior of the system. If there is any deviation from normal behavior then the event is considered as an attack. Some of the features of collected audit data may be redundant or contribute little to the detection process. So it is essential to select the important features to increase the detection rate. This paper focuses on implementing two feature selection methods namely, markov blanket discovery and genetic algorithm. In genetic algorithm, bayesian network is constructed over the collected features and fitness function is calculated. Based on the fitness value the features are selected. Markov blanket discovery also uses bayesian network and the features are selected depending on the minimum description length. During the evaluation phase, the performances of both approaches are compared based on detection rate and false alarm rate.


Multi-valued Action Languages in CLP(FD)

Abstract: Action description languages, such as A and B, are expressive instruments introduced for formalizing planning domains and planning problem instances. The paper starts by proposing a methodology to encode an action language (with conditional effects and static causal laws), a slight variation of B, using Constraint Logic Programming over Finite Domains. The approach is then generalized to raise the use of constraints to the level of the action language itself. A prototype implementation has been developed, and the preliminary results are presented and discussed. To appear in Theory and Practice of Logic Programming (TPLP)


JSC : A JavaScript Object System

Abstract: The JSC language is a superset of JavaScript designed to ease the development of large web applications. This language extends JavaScripts own object system by isolating code in a class declaration, simplifying multiple inheritance and using method implementation agreements.


Representing human and machine dictionaries in Markup languages

Abstract: In this chapter we present the main issues in representing machine readable dictionaries in XML, and in particular according to the Text Encoding Dictionary (TEI) guidelines.


Specification and Verification of Side Channel Declassification

Abstract: Side channel attacks have emerged as a serious threat to the security of both networked and embedded systems -- in particular through the implementations of cryptographic operations. Side channels can be difficult to model formally, but with careful coding and program transformation techniques it may be possible to verify security in the presence of specific side-channel attacks. But what if a program intentionally makes a tradeoff between security and efficiency and leaks some information through a side channel? In this paper we study such tradeoffs using ideas from recent research on declassification. We present a semantic model of security for programs which allow for declassification through side channels, and show how side-channel declassification can be verified using off-the-shelf software model checking tools. Finally, to make it simpler for verifiers to check that a program conforms to a particular side-channel declassification policy we introduce a further tradeoff between efficiency and verifiability: by writing programs in a particular "manifest form" security becomes considerably easier to verify.


Set Systems and Families of Permutations with Small Traces

Abstract: We study the maximum size of a set system on $n$ elements whose trace on any $b$ elements has size at most $k$. We show that if for some $b \ge i \ge 0$ the shatter function $f_R$ of a set system $([n],R)$ satisfies $f_R(b) < 2^i(b-i+1)$ then $|R| = O(n^i)$; this generalizes Sauer's Lemma on the size of set systems with bounded VC-dimension. We use this bound to delineate the main growth rates for the same problem on families of permutations, where the trace corresponds to the inclusion for permutations. This is related to a question of Raz on families of permutations with bounded VC-dimension that generalizes the Stanley-Wilf conjecture on permutations with excluded patterns.


Graph unique-maximum and conflict-free colorings

Abstract: We investigate the relationship between two kinds of vertex colorings of graphs: unique-maximum colorings and conflict-free colorings. In a unique-maximum coloring, the colors are ordered, and in every path of the graph the maximum color appears only once. In a conflict-free coloring, in every path of the graph there is a color that appears only once. We also study computational complexity aspects of conflict-free colorings and prove a completeness result. Finally, we improve lower bounds for those chromatic numbers of the grid graph.


Proceedings 8th International Workshop on Parallel and Distributed Methods in verifiCation

Abstract: The 8th International Workshop on Parallel and Distributed Methods in verifiCation (PDMC 2009) took place on November 4, 2009 at the Eindhoven University of Technology, in conjunction with Formal Methods 2009 and other related events for the first time under the heading of Formal Methods Week. This volume contains the final workshop proceedings.


Breaking a modified substitution-diffusion image cipher based on chaotic standard and logistic maps

Abstract: Recently, an image encryption scheme based on chaotic standard and logistic maps was proposed by Patidar et al. It was later reported by Rhouma et al. that an equivalent secret key can be reconstructed with only one known/chosen-plaintext and the corresponding ciphertext. Patidar et al. soon modified the original scheme and claimed that the modified scheme is secure against Rhouma et al.'s attack. In this paper, we point out that the modified scheme is still insecure against the same known/chosen-plaintext attack. In addition, some other security defects existing in both the original and the modified schemes are also reported.