A simple algorithm for random colouring G(n, d/n) using (2+\epsilon)d colours

Abstract: Approximate random k-colouring of a graph G=(V,E) is a very well studied problem in computer science and statistical physics. It amounts to constructing a k-colouring of G which is distributed close to Gibbs distribution, i.e. the uniform distribution over all the k-colourings of G. Here, we deal with the problem when the underlying graph is an instance of Erdos-Renyi random graph G(n,p), where p=d/n and d is fixed. We propose a novel efficient algorithm for approximate random k-colouring with the following properties: given an instance of G(n,d/n) and for any k>(2+\epsilon)d, it returns a k-colouring distributed within total variation distance n^{-Omega(1)} from the Gibbs distribution, with probability 1-n^{-Omega(1)}. What we propose is neither a MCMC algorithm nor some algorithm inspired by the message passing heuristics that were introduced by statistical physicist. Our algorithm is of combinatorial nature. It is based on a rather simple recursion which reduces the random k-colouring of G(n,d/n) to random k-colouring simpler subgraphs first. The lower bound on the number of colours for our algorithm to run in polynomial time is dramatically smaller than the corresponding bounds we have for any previous algorithm.


Approximating Minimum Manhattan Networks in Higher Dimensions

Abstract: We study the minimum Manhattan network problem, which is defined as follows. Given a set of points called \emph{terminals} in $\R^d$, find a minimum-length network such that each pair of terminals is connected by a set of axis-parallel line segments whose total length is equal to the pair's Manhattan (that is, $L_1$-) distance. The problem is NP-hard in 2D and there is no PTAS for 3D (unless ${\cal P}={\cal NP}$). Approximation algorithms are known for 2D, but not for 3D. We present, for any fixed dimension $d$ and any $\eps>0$, an $O(n^\eps)$-approximation algorithm. For 3D, we also give a $4(k-1)$-approximation algorithm for the case that the terminals are contained in the union of $k \ge 2$ parallel planes.


The First-Order Theory of Ground Tree Rewrite Graphs

Abstract: We prove that the complexity of the uniform first-order theory of ground tree rewrite graphs is in ATIME(2^{2^{poly(n)}},O(n)). Providing a matching lower bound, we show that there is some fixed ground tree rewrite graph whose first-order theory is hard for ATIME(2^{2^{poly(n)}},poly(n)) with respect to logspace reductions. Finally, we prove that there exists a fixed ground tree rewrite graph together with a single unary predicate in form of a regular tree language such that the resulting structure has a non-elementary first-order theory.


GraphLab: A Distributed Framework for Machine Learning in the Cloud

Abstract: Machine Learning (ML) techniques are indispensable in a wide range of fields. Unfortunately, the exponential increase of dataset sizes are rapidly extending the runtime of sequential algorithms and threatening to slow future progress in ML. With the promise of affordable large-scale parallel computing, Cloud systems offer a viable platform to resolve the computational challenges in ML. However, designing and implementing efficient, provably correct distributed ML algorithms is often prohibitively challenging. To enable ML researchers to easily and efficiently use parallel systems, we introduced the GraphLab abstraction which is designed to represent the computational patterns in ML algorithms while permitting efficient parallel and distributed implementations. In this paper we provide a formal description of the GraphLab parallel abstraction and present an efficient distributed implementation. We conduct a comprehensive evaluation of GraphLab on three state-of-the-art ML algorithms using real large-scale data and a 64 node EC2 cluster of 512 processors. We find that GraphLab achieves orders of magnitude performance gains over Hadoop while performing comparably or superior to hand-tuned MPI implementations.


Furthering Baseline Core Lucid Standard Specification in the Context of the History of Lucid, Intensional Programming, and Context-Aware Computing

Abstract: This work is multifold. We review the historical literature on the Lucid programming language, its dialects, intensional logic, intensional programming, the implementing systems, and context-oriented and context-aware computing and so on that provide a contextual framework for the converging Core Lucid standard programming model. We are designing a standard specification of a baseline Lucid virtual machine for generic execution of Lucid programs. The resulting Core Lucid language would inherit the properties of generalization attempts of GIPL (1999-2013) and TransLucid (2008-2013) for all future and recent Lucid implementing systems to follow. We also maintain this work across local research group in order to foster deeper collaboration, maintain a list of recent and historical bibliography and a reference manual and reading list for students. We form a (for now informal) SIGLUCID group to keep track of this standard and historical records with eventual long-term goal through iterative revisions for this work to become a book or an encyclopedia of the referenced topics, and perhaps, an RFC. We first begin small with this initial set of notes.


Optimal Point Movement for Covering Circular Regions

Abstract: Given $n$ points in a circular region $C$ in the plane, we study the problems of moving the $n$ points to its boundary to form a regular $n$-gon such that the maximum (min-max) or the sum (min-sum) of the Euclidean distances traveled by the points is minimized. The problems have applications, e.g., in mobile sensor barrier coverage of wireless sensor networks. The min-max problem further has two versions: the decision version and optimization version. For the min-max problem, we present an $O(n\log^2 n)$ time algorithm for the decision version and an $O(n\log^3 n)$ time algorithm for the optimization version. The previously best algorithms for the two problem versions take $O(n^{3.5})$ time and $O(n^{3.5}\log n)$ time, respectively. For the min-sum problem, we show that a special case with all points initially lying on the boundary of the circular region can be solved in $O(n^2)$ time, improving a previous $O(n^4)$ time solution. For the general min-sum problem, we present a 3-approximation $O(n^2)$ time algorithm, improving the previous $(1+\pi)$-approximation $O(n^2)$ time algorithm. A by-product of our techniques is an algorithm for dynamically maintaining the maximum matching of a circular convex bipartite graph; our algorithm can handle each vertex insertion or deletion on the graph in $O(\log^2 n)$ time. This result is interesting in its own right.


Extracting and Verifying Cryptographic Models from C Protocol Code by Symbolic Execution

Abstract: Consider the problem of verifying security properties of a cryptographic protocol coded in C. We propose an automatic solution that needs neither a pre-existing protocol description nor manual annotation of source code. First, symbolically execute the C program to obtain symbolic descriptions for the network messages sent by the protocol. Second, apply algebraic rewriting to obtain a process calculus description. Third, run an existing protocol analyser (ProVerif) to prove security properties or find attacks. We formalise our algorithm and appeal to existing results for ProVerif to establish computational soundness under suitable circumstances. We analyse only a single execution path, so our results are limited to protocols with no significant branching. The results in this paper provide the first computationally sound verification of weak secrecy and authentication for (single execution paths of) C code.


A Novel Multicriteria Group Decision Making Approach With Intuitionistic Fuzzy SIR Method

Abstract: The superiority and inferiority ranking (SIR) method is a generation of the well-known PROMETHEE method, which can be more efficient to deal with multi-criterion decision making (MCDM) problem. Intuitionistic fuzzy sets (IFSs), as an important extension of fuzzy sets (IFs), include both membership functions and non-membership functions and can be used to, more precisely describe uncertain information. In real world, decision situations are usually under uncertain environment and involve multiple individuals who have their own points of view on handing of decision problems. In order to solve uncertainty group MCDM problem, we propose a novel intuitionistic fuzzy SIR method in this paper. This approach uses intuitionistic fuzzy aggregation operators and SIR ranking methods to handle uncertain information; integrate individual opinions into group opinions; make decisions on multiple-criterion; and finally structure a specific decision map. The proposed approach is illustrated in a simulation of group decision making problem related to supply chain management.


Dynamic OFDMA Resource Allocation for QoS Guarantee and System Optimization of Best Effort and Non Real-time Traffic

Abstract: To achieve the requirement of high data rate, low latency, user fairness for next generation wireless networks, proper designing of cross-layer optimized dynamic resource allocation algorithm is prerequisite. In this paper, we propose a dynamic resource allocation scheme in Orthogonal Frequency Division Multiple Access (OFDMA) systems to optimize the non real-time (NRT) traffic, which requires allocation of minimum quantum of data within a predefined time that does not incur packet loss. Most existing and proposed works on resource allocation schemes focused on traffic consisting of delay constraint real-time (RT) or delay-tolerant (NRT, Best-Effort (BE)) applications in a single scheme. In this work, we investigate the resource allocation problem in heterogeneous multiuser OFDMA system with the objective of optimizing the aggregate data delivery of NRT and BE traffic to maximize the overall system performance, by exploiting the inherent time-diversity gain in mobile wireless environment for delay-tolerant applications. Simulation results show that the proposed algorithm greatly enhances the system capacity, when compared to traditional proportional fair resource allocation algorithm.


The traveling salesman problem on cubic and subcubic graphs

Abstract: We study the Travelling Salesman Problem (TSP) on the metric completion of cubic and subcubic graphs, which is known to be NP-hard. The problem is of interest because of its relation to the famous 4/3 conjecture for metric TSP, which says that the integrality gap, i.e., the worst case ratio between the optimal values of the TSP and its linear programming relaxation (the subtour elimination relaxation), is 4/3. We present the first algorithm for cubic graphs with approximation ratio 4/3. The proof uses polyhedral techniques in a surprising way, which is of independent interest. In fact we prove constructively that for any cubic graph on $n$ vertices a tour of length 4n/3-2 exists, which also implies the 4/3 conjecture, as an upper bound, for this class of graph-TSP. Recently, M\"omke and Svensson presented a randomized algorithm that gives a 1.461-approximation for graph-TSP on general graphs and as a side result a 4/3-approximation algorithm for this problem on subcubic graphs, also settling the 4/3 conjecture for this class of graph-TSP. We will present a way to derandomize their algorithm which leads to a smaller running time than the obvious derandomization. All of the latter also works for multi-graphs.


Online Vehicle Detection For Estimating Traffic Status

Abstract: We propose a traffic congestion estimation system based on unsupervised on-line learning algorithm. The system does not rely on background extraction or motion detection. It extracts local features inside detection regions of variable size which are drawn on lanes in advance. The extracted features are then clustered into two classes using K-means and Gaussian Mixture Models(GMM). A Bayes classifier is used to detect vehicles according to the previous cluster information which keeps updated whenever system is running by on-line EM algorithm. Experimental result shows that our system can be adapted to various traffic scenes for estimating traffic status.


Adding Query Privacy to Robust DHTs

Abstract: Interest in anonymous communication over distributed hash tables (DHTs) has increased in recent years. However, almost all known solutions solely aim at achieving sender or requestor anonymity in DHT queries. In many application scenarios, it is crucial that the queried key remains secret from intermediate peers that (help to) route the queries towards their destinations. In this paper, we satisfy this requirement by presenting an approach for providing privacy for the keys in DHT queries. We use the concept of oblivious transfer (OT) in communication over DHTs to preserve query privacy without compromising spam resistance. Although our OT-based approach can work over any DHT, we concentrate on communication over robust DHTs that can tolerate Byzantine faults and resist spam. We choose the best-known robust DHT construction, and employ an efficient OT protocol well-suited for achieving our goal of obtaining query privacy over robust DHTs. Finally, we compare the performance of our privacy-preserving protocols with their more privacy-invasive counterparts. We observe that there is no increase in the message complexity and only a small overhead in the computational complexity.


Genome Halving by Block Interchange

Abstract: We address the problem of finding the minimal number of block interchanges (exchange of two intervals) required to transform a duplicated linear genome into a tandem duplicated linear genome. We provide a formula for the distance as well as a polynomial time algorithm for the sorting problem.


Spatial Features for Multi-Font/Multi-Size Kannada Numerals and Vowels Recognition

Abstract: This paper presents multi-font/multi-size Kannada numerals and vowels recognition based on spatial features. Directional spatial features viz stroke density, stroke length and the number of stokes in an image are employed as potential features to characterize the printed Kannada numerals and vowels. Based on these features 1100 numerals and 1400 vowels are classified with Multi-class Support Vector Machines (SVM). The proposed system achieves the recognition accuracy as 98.45% and 90.64% for numerals and vowels respectively.


Breaking GSM with rainbow Tables

Abstract: Since 1998 the GSM security has been academically broken but no real attack has ever been done until in 2008 when two engineers of Pico Computing (FPGA manufacture) revealed that they could break the GSM encryption in 30 seconds with 200'000$ hardware and precomputed rainbow tables. Since then the hardware was either available for rich people only or was confiscated by government agencies. So Chris Paget and Karsten Nohl decided to react and do the same thing but in a distributed open source form (on torrent). This way everybody could "enjoy" breaking GSM security and operators will be forced to upgrade the GSM protocol that is being used by more than 4 billion users and that is more than 20 years old.


Node Sampling using Random Centrifugal Walks

Abstract: Sampling a network with a given probability distribution has been identified as a useful operation. In this paper we propose distributed algorithms for sampling networks, so that nodes are selected by a special node, called the \emph{source}, with a given probability distribution. All these algorithms are based on a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW is a random walk that starts at the source and always moves away from it. Firstly, an algorithm to sample any connected network using RCW is proposed. The algorithm assumes that each node has a weight, so that the sampling process must select a node with a probability proportional to its weight. This algorithm requires a preprocessing phase before the sampling of nodes. In particular, a minimum diameter spanning tree (MDST) is created in the network, and then nodes' weights are efficiently aggregated using the tree. The good news are that the preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. After that, every sample is done with a RCW whose length is bounded by the network diameter. Secondly, RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source. The key features of the RCW algorithms (unlike previous Markovian approaches) are that (1) they do not need to warm-up (stabilize), (2) the sampling always finishes in a number of hops bounded by the network diameter, and (3) it selects a node with the exact probability distribution.


Selling train tickets by SMS

Abstract: Selling train tickets has evolved in the last ten years from queuing in the railway station, to buying tickets on the internet and printing them. Both alternatives are still viable options, though they are time consuming or need printing devices. Nowadays it is essential to offer a service that is as fast and efficient as possible: mobile phones provide an accessible, affordable and widely available tool for supplying information and transferring data. The goal of this project is to design a train ticket contained in a SMS message. While there are several challenges related to the project, the main one is the security and how we can digitally sign a train ticket that is contained in 160 characters. The solution offered in this project is the implementation of the MOVA Signature (from the name of the inventors MOnnerat and VAudenay) that uses an interactive verification and therefore allows signature of 20 bits (roughly 4 characters).


Misbehavior in Mobile Application Markets

Abstract: Mobile application markets facilitate the distribution of applications and thus help developers advertise their work and customers find useful applications. In addition, the operators of mobile application markets can control the quality and the content of the applications. These markets are growing rapidly with more than 300'000 application in the App Store of Apple and more than 100'000 in the Android Market of Google. This is not only a great opportunity for phone manufacturers to earn money but also for indie developers (single or small teams of developers with small financial support) who can thus have a great distribution channel. Steve Demeter, the Trim game developer for iPhone, became millionaire with a single puzzle game . Obviously, as new markets generate a lot of money, the temptation of misbehavior to steal part of the benefits is big. The first famous case was the one of Molinker who self-rated his applications with 5 stars to pump up his ranking in order to increase its revenue stream. In this report, we will consider the problem of misbehavior in mobile application markets. We will investigate multiple attacks by misbehaving developers, users or network operators that aim at breaking rules for their own benefit, managing to outwit the operators' control on which applications can be installed. We notably suggest novel attacks that may affect mobile markets in the future: in particular, we show that it is possible to get revenue for applications created by someone else, trick a user to download and buy an application and new ways to pump up an application's ranking. We will also discuss possible solutions against spyware applications and cheating developer


SERIMI - Resource Description Similarity, RDF Instance Matching and Interlinking

Abstract: The interlinking of datasets published in the Linked Data Cloud is a challenging problem and a key factor for the success of the Semantic Web. Manual rule-based methods are the most effective solution for the problem, but they require skilled human data publishers going through a laborious, error prone and time-consuming process for manually describing rules mapping instances between two datasets. Thus, an automatic approach for solving this problem is more than welcome. In this paper, we propose a novel interlinking method, SERIMI, for solving this problem automatically. SERIMI matches instances between a source and a target datasets, without prior knowledge of the data, domain or schema of these datasets. Experiments conducted with benchmark collections demonstrate that our approach considerably outperforms state-of-the-art automatic approaches for solving the interlinking problem on the Linked Data Cloud.


Integrating Generic Sensor Fusion Algorithms with Sound State Representations through Encapsulation of Manifolds

Abstract: Common estimation algorithms, such as least squares estimation or the Kalman filter, operate on a state in a state space S that is represented as a real-valued vector. However, for many quantities, most notably orientations in 3D, S is not a vector space, but a so-called manifold, i.e. it behaves like a vector space locally but has a more complex global topological structure. For integrating these quantities, several ad-hoc approaches have been proposed. Here, we present a principled solution to this problem where the structure of the manifold S is encapsulated by two operators, state displacement [+]:S x R^n --> S and its inverse [-]: S x S --> R^n. These operators provide a local vector-space view \delta; --> x [+] \delta; around a given state x. Generic estimation algorithms can then work on the manifold S mainly by replacing +/- with [+]/[-] where appropriate. We analyze these operators axiomatically, and demonstrate their use in least-squares estimation and the Unscented Kalman Filter. Moreover, we exploit the idea of encapsulation from a software engineering perspective in the Manifold Toolkit, where the [+]/[-] operators mediate between a "flat-vector" view for the generic algorithm and a "named-members" view for the problem specific functions.


AISMOTIF-An Artificial Immune System for DNA Motif Discovery

Abstract: Discovery of transcription factor binding sites is a much explored and still exploring area of research in functional genomics. Many computational tools have been developed for finding motifs and each of them has their own advantages as well as disadvantages. Most of these algorithms need prior knowledge about the data to construct background models. However there is not a single technique that can be considered as best for finding regulatory motifs. This paper proposes an artificial immune system based algorithm for finding the transcription factor binding sites or motifs and two new weighted scores for motif evaluation. The algorithm is enumerative, but sufficient pruning of the pattern search space has been incorporated using immune system concepts. The performance of AISMOTIF has been evaluated by comparing it with eight state of art composite motif discovery algorithms and found that AISMOTIF predicts known motifs as well as new motifs from the benchmark dataset without any prior knowledge about the data.


Celerity: A Low-Delay Multi-Party Conferencing Solution

Abstract: In this paper, we attempt to revisit the problem of multi-party conferencing from a practical perspective, and to rethink the design space involved in this problem. We believe that an emphasis on low end-to-end delays between any two parties in the conference is a must, and the source sending rate in a session should adapt to bandwidth availability and congestion. We present Celerity, a multi-party conferencing solution specifically designed to achieve our objectives. It is entirely Peer-to-Peer (P2P), and as such eliminating the cost of maintaining centrally administered servers. It is designed to deliver video with low end-to-end delays, at quality levels commensurate with available network resources over arbitrary network topologies where bottlenecks can be anywhere in the network. This is in contrast to commonly assumed P2P scenarios where bandwidth bottlenecks reside only at the edge of the network. The highlight in our design is a distributed and adaptive rate control protocol, that can discover and adapt to arbitrary topologies and network conditions quickly, converging to efficient link rate allocations allowed by the underlying network. In accordance with adaptive link rate control, source video encoding rates are also dynamically controlled to optimize video quality in arbitrary and unpredictable network conditions. We have implemented Celerity in a prototype system, and demonstrate its superior performance over existing solutions in a local experimental testbed and over the Internet.


Measurement-Adaptive Cellular Random Access Protocols

Abstract: This work considers a single-cell random access channel (RACH) in cellular wireless networks. Communications over RACH take place when users try to connect to a base station during a handover or when establishing a new connection. Within the framework of Self-Organizing Networks (SONs), the system should self- adapt to dynamically changing environments (channel fading, mobility, etc.) without human intervention. For the performance improvement of the RACH procedure, we aim here at maximizing throughput or alternatively minimizing the user dropping rate. In the context of SON, we propose protocols which exploit information from measurements and user reports in order to estimate current values of the system unknowns and broadcast global action-related values to all users. The protocols suggest an optimal pair of user actions (transmission power and back-off probability) found by minimizing the drift of a certain function. Numerical results illustrate considerable benefits of the dropping rate, at a very low or even zero cost in power expenditure and delay, as well as the fast adaptability of the protocols to environment changes. Although the proposed protocol is designed to minimize primarily the amount of discarded users per cell, our framework allows for other variations (power or delay minimization) as well.


Reachability Analysis of Time Basic Petri Nets: a Time Coverage Approach

Abstract: We introduce a technique for reachability analysis of Time-Basic (TB) Petri nets, a powerful formalism for real- time systems where time constraints are expressed as intervals, representing possible transition firing times, whose bounds are functions of marking's time description. The technique consists of building a symbolic reachability graph relying on a sort of time coverage, and overcomes the limitations of the only available analyzer for TB nets, based in turn on a time-bounded inspection of a (possibly infinite) reachability-tree. The graph construction algorithm has been automated by a tool-set, briefly described in the paper together with its main functionality and analysis capability. A running example is used throughout the paper to sketch the symbolic graph construction. A use case describing a small real system - that the running example is an excerpt from - has been employed to benchmark the technique and the tool-set. The main outcome of this test are also presented in the paper. Ongoing work, in the perspective of integrating with a model-checking engine, is shortly discussed.


Not So Easy Problems for Tree Decomposable Graphs

Abstract: We consider combinatorial problems that can be solved in polynomial time for graphs of bounded treewidth but where the order of the polynomial that bounds the running time is expected to depend on the treewidth bound. First we review some recent results for problems regarding list and equitable colorings, general factors, and generalized satisfiability. Second we establish a new hardness result for the problem of minimizing the maximum weighted outdegree for orientations of edge-weighted graphs of bounded treewidth.


QuantUM: Quantitative Safety Analysis of UML Models

Abstract: When developing a safety-critical system it is essential to obtain an assessment of different design alternatives. In particular, an early safety assessment of the architectural design of a system is desirable. In spite of the plethora of available formal quantitative analysis methods it is still difficult for software and system architects to integrate these techniques into their every day work. This is mainly due to the lack of methods that can be directly applied to architecture level models, for instance given as UML diagrams. Also, it is necessary that the description methods used do not require a profound knowledge of formal methods. Our approach bridges this gap and improves the integration of quantitative safety analysis methods into the development process. All inputs of the analysis are specified at the level of a UML model. This model is then automatically translated into the analysis model, and the results of the analysis are consequently represented on the level of the UML model. Thus the analysis model and the formal methods used during the analysis are hidden from the user. We illustrate the usefulness of our approach using an industrial strength case study.


Two-Player Reachability-Price Games on Single-Clock Timed Automata

Abstract: We study two player reachability-price games on single-clock timed automata. The problem is as follows: given a state of the automaton, determine whether the first player can guarantee reaching one of the designated goal locations. If a goal location can be reached then we also want to compute the optimum price of doing so. Our contribution is twofold. First, we develop a theory of cost functions, which provide a comprehensive methodology for the analysis of this problem. This theory allows us to establish our second contribution, an EXPTIME algorithm for computing the optimum reachability price, which improves the existing 3EXPTIME upper bound.


Time Delays in Membrane Systems and Petri Nets

Abstract: Timing aspects in formalisms with explicit resources and parallelism are investigated, and it is presented a formal link between timed membrane systems and timed Petri nets with localities. For both formalisms, timing does not increase the expressive power; however both timed membrane systems and timed Petri nets are more flexible in describing molecular phenomena where time is a critical resource. We establish a link between timed membrane systems and timed Petri nets with localities, and prove an operational correspondence between them.


Real-Reward Testing for Probabilistic Processes (Extended Abstract)

Abstract: We introduce a notion of real-valued reward testing for probabilistic processes by extending the traditional nonnegative-reward testing with negative rewards. In this richer testing framework, the may and must preorders turn out to be inverses. We show that for convergent processes with finitely many states and transitions, but not in the presence of divergence, the real-reward must-testing preorder coincides with the nonnegative-reward must-testing preorder. To prove this coincidence we characterise the usual resolution-based testing in terms of the weak transitions of processes, without having to involve policies, adversaries, schedulers, resolutions, or similar structures that are external to the process under investigation. This requires establishing the continuity of our function for calculating testing outcomes.


A Stochastic Broadcast Pi-Calculus

Abstract: In this paper we propose a stochastic broadcast PI-calculus which can be used to model server-client based systems where synchronization is always governed by only one participant. Therefore, there is no need to determine the joint synchronization rates. We also take immediate transitions into account which is useful to model behaviors with no impact on the temporal properties of a system. Since immediate transitions may introduce non-determinism, we will show how these non-determinism can be resolved, and as result a valid CTMC will be obtained finally. Also some practical examples are given to show the application of this calculus.


Improvements for Free

Abstract: "Theorems for Free!" (Wadler, FPCA 1989) is a slogan for a technique that allows to derive statements about functions just from their types. So far, the statements considered have always had a purely extensional flavor: statements relating the value semantics of program expressions, but not statements relating their runtime (or other) cost. Here we study an extension of the technique that allows precisely statements of the latter flavor, by deriving quantitative theorems for free. After developing the theory, we walk through a number of example derivations. Probably none of the statements derived in those simple examples will be particularly surprising to most readers, but what is maybe surprising, and at the very least novel, is that there is a general technique for obtaining such results on a quantitative level in a principled way. Moreover, there is good potential to bring that technique to bear on more complex examples as well. We turn our attention to short-cut fusion (Gill et al., FPCA 1993) in particular.


Analysis of Non-Linear Probabilistic Hybrid Systems

Abstract: This paper shows how to compute, for probabilistic hybrid systems, the clock approximation and linear phase-portrait approximation that have been proposed for non probabilistic processes by Henzinger et al. The techniques permit to define a rectangular probabilistic process from a non rectangular one, hence allowing the model-checking of any class of systems. Clock approximation, which applies under some restrictions, aims at replacing a non rectangular variable by a clock variable. Linear phase-approximation applies without restriction and yields an approximation that simulates the original process. The conditions that we need for probabilistic processes are the same as those for the classic case.


Distances for Weighted Transition Systems: Games and Properties

Abstract: We develop a general framework for reasoning about distances between transition systems with quantitative information. Taking as starting point an arbitrary distance on system traces, we show how this leads to natural definitions of a linear and a branching distance on states of such a transition system. We show that our framework generalizes and unifies a large variety of previously considered system distances, and we develop some general properties of our distances. We also show that if the trace distance admits a recursive characterization, then the corresponding branching distance can be obtained as a least fixed point to a similar recursive characterization. The central tool in our work is a theory of infinite path-building games with quantitative objectives.


Computing Distances between Probabilistic Automata

Abstract: We present relaxed notions of simulation and bisimulation on Probabilistic Automata (PA), that allow some error epsilon. When epsilon is zero we retrieve the usual notions of bisimulation and simulation on PAs. We give logical characterisations of these notions by choosing suitable logics which differ from the elementary ones, L with negation and L without negation, by the modal operator. Using flow networks, we show how to compute the relations in PTIME. This allows the definition of an efficiently computable non-discounted distance between the states of a PA. A natural modification of this distance is introduced, to obtain a discounted distance, which weakens the influence of long term transitions. We compare our notions of distance to others previously defined and illustrate our approach on various examples. We also show that our distance is not expansive with respect to process algebra operators. Although L without negation is a suitable logic to characterise epsilon-(bi)simulation on deterministic PAs, it is not for general PAs; interestingly, we prove that it does characterise weaker notions, called a priori epsilon-(bi)simulation, which we prove to be NP-difficult to decide.


HYPE with stochastic events

Abstract: The process algebra HYPE was recently proposed as a fine-grained modelling approach for capturing the behaviour of hybrid systems. In the original proposal, each flow or influence affecting a variable is modelled separately and the overall behaviour of the system then emerges as the composition of these flows. The discrete behaviour of the system is captured by instantaneous actions which might be urgent, taking effect as soon as some activation condition is satisfied, or non-urgent meaning that they can tolerate some (unknown) delay before happening. In this paper we refine the notion of non-urgent actions, to make such actions governed by a probability distribution. As a consequence of this we now give HYPE a semantics in terms of Transition-Driven Stochastic Hybrid Automata, which are a subset of a general class of stochastic processes termed Piecewise Deterministic Markov Processes.


Lift-and-Project Integrality Gaps for the Traveling Salesperson Problem

Abstract: We study the lift-and-project procedures of Lov{\'a}sz-Schrijver and Sherali-Adams applied to the standard linear programming relaxation of the traveling salesperson problem with triangle inequality. For the asymmetric TSP tour problem, Charikar, Goemans, and Karloff (FOCS 2004) proved that the integrality gap of the standard relaxation is at least 2. We prove that after one round of the Lov{\'a}sz-Schrijver or Sherali-Adams procedures, the integrality gap of the asymmetric TSP tour problem is at least 3/2, with a small caveat on which version of the standard relaxation is used. For the symmetric TSP tour problem, the integrality gap of the standard relaxation is known to be at least 4/3, and Cheung (SIOPT 2005) proved that it remains at least 4/3 after $o(n)$ rounds of the Lov{\'a}sz-Schrijver procedure, where $n$ is the number of nodes. For the symmetric TSP path problem, the integrality gap of the standard relaxation is known to be at least 3/2, and we prove that it remains at least 3/2 after $o(n)$ rounds of the Lov{\'a}sz-Schrijver procedure, by a simple reduction to Cheung's result.


Separator Theorems for Minor-Free and Shallow Minor-Free Graphs with Applications

Abstract: Alon, Seymour, and Thomas generalized Lipton and Tarjan's planar separator theorem and showed that a $K_h$-minor free graph with $n$ vertices has a separator of size at most $h^{3/2}\sqrt n$. They gave an algorithm that, given a graph $G$ with $m$ edges and $n$ vertices and given an integer $h\geq 1$, outputs in $O(\sqrt{hn}m)$ time such a separator or a $K_h$-minor of $G$. Plotkin, Rao, and Smith gave an $O(hm\sqrt{n\log n})$ time algorithm to find a separator of size $O(h\sqrt{n\log n})$. Kawarabayashi and Reed improved the bound on the size of the separator to $h\sqrt n$ and gave an algorithm that finds such a separator in $O(n^{1 + \epsilon})$ time for any constant $\epsilon > 0$, assuming $h$ is constant. This algorithm has an extremely large dependency on $h$ in the running time (some power tower of $h$ whose height is itself a function of $h$), making it impractical even for small $h$. We are interested in a small polynomial time dependency on $h$ and we show how to find an $O(h\sqrt{n\log n})$-size separator or report that $G$ has a $K_h$-minor in $O(\poly(h)n^{5/4 + \epsilon})$ time for any constant $\epsilon > 0$. We also present the first $O(\poly(h)n)$ time algorithm to find a separator of size $O(n^c)$ for a constant $c < 1$. As corollaries of our results, we get improved algorithms for shortest paths and maximum matching. Furthermore, for integers $\ell$ and $h$, we give an $O(m + n^{2 + \epsilon}/\ell)$ time algorithm that either produces a $K_h$-minor of depth $O(\ell\log n)$ or a separator of size at most $O(n/\ell + \ell h^2\log n)$. This improves the shallow minor algorithm of Plotkin, Rao, and Smith when $m = \Omega(n^{1 + \epsilon})$. We get a similar running time improvement for an approximation algorithm for the problem of finding a largest $K_h$-minor in a given graph.


Text Classification: A Sequential Reading Approach

Abstract: We propose to model the text classification process as a sequential decision process. In this process, an agent learns to classify documents into topics while reading the document sentences sequentially and learns to stop as soon as enough information was read for deciding. The proposed algorithm is based on a modelisation of Text Classification as a Markov Decision Process and learns by using Reinforcement Learning. Experiments on four different classical mono-label corpora show that the proposed approach performs comparably to classical SVM approaches for large training sets, and better for small training sets. In addition, the model automatically adapts its reading process to the quantity of training information provided.


On counting untyped lambda terms

Abstract: We present several results on counting untyped lambda terms, i.e., on telling how many terms belong to such or such class, according to the size of the terms and/or to the number of free variables.


Estimation of Sparse MIMO Channels with Common Support

Abstract: We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimation of SCS channel parameters in Rayleigh fading conditions are derived. Finally, an analytical spatial channel model is derived, and simulations on this model in the OFDM setting show the symbol error rate (SER) is reduced by a factor 2 (0 dB of SNR) to 5 (high SNR) compared to standard non-parametric methods - e.g. lowpass interpolation.


Conway games, algebraically and coalgebraically

Abstract: Using coalgebraic methods, we extend Conway's theory of games to possibly non-terminating, i.e. non-wellfounded games (hypergames). We take the view that a play which goes on forever is a draw, and hence rather than focussing on winning strategies, we focus on non-losing strategies. Hypergames are a fruitful metaphor for non-terminating processes, Conway's sum being similar to shuffling. We develop a theory of hypergames, which extends in a non-trivial way Conway's theory; in particular, we generalize Conway's results on game determinacy and characterization of strategies. Hypergames have a rather interesting theory, already in the case of impartial hypergames, for which we give a compositional semantics, in terms of a generalized Grundy-Sprague function and a system of generalized Nim games. Equivalences and congruences on games and hypergames are discussed. We indicate a number of intriguing directions for future work. We briefly compare hypergames with other notions of games used in computer science.


On the Furthest Hyperplane Problem and Maximal Margin Clustering

Abstract: This paper introduces the Furthest Hyperplane Problem (FHP), which is an unsupervised counterpart of Support Vector Machines. Given a set of n points in Rd, the objective is to produce the hyperplane (passing through the origin) which maximizes the separation margin, that is, the minimal distance between the hyperplane and any input point. To the best of our knowledge, this is the first paper achieving provable results regarding FHP. We provide both lower and upper bounds to this NP-hard problem. First, we give a simple randomized algorithm whose running time is n^O(1/{\theta}^2) where {\theta} is the optimal separation margin. We show that its exponential dependency on 1/{\theta}^2 is tight, up to sub-polynomial factors, assuming SAT cannot be solved in sub-exponential time. Next, we give an efficient approxima- tion algorithm. For any {\alpha} \in [0, 1], the algorithm produces a hyperplane whose distance from at least 1 - 5{\alpha} fraction of the points is at least {\alpha} times the optimal separation margin. Finally, we show that FHP does not admit a PTAS by presenting a gap preserving reduction from a particular version of the PCP theorem.


Bidirected minimum Manhattan network problem

Abstract: In the bidirected minimum Manhattan network problem, given a set T of n terminals in the plane, we need to construct a network N(T) of minimum total length with the property that the edges of N(T) are axis-parallel and oriented in a such a way that every ordered pair of terminals is connected in N(T) by a directed Manhattan path. In this paper, we present a polynomial factor 2 approximation algorithm for the bidirected minimum Manhattan network problem.


Algorithms for Synthesizing Priorities in Component-based Systems

Abstract: We present algorithms to synthesize component-based systems that are safe and deadlock-free using priorities, which define stateless-precedence between enabled actions. Our core method combines the concept of fault-localization (using safety-game) and fault-repair (using SAT for conflict resolution). For complex systems, we propose three complementary methods as preprocessing steps for priority synthesis, namely (a) data abstraction to reduce component complexities, (b) alphabet abstraction and #-deadlock to ignore components, and (c) automated assumption learning for compositional priority synthesis.


Efficient Loop Navigation for Symbolic Execution

Abstract: Symbolic execution is a successful and very popular technique used in software verification and testing. A key limitation of symbolic execution is in dealing with code containing loops. The problem is that even a single loop can generate a huge number of different symbolic execution paths, corresponding to different number of loop iterations and taking various paths through the loop. We introduce a technique which, given a start location above some loops and a target location anywhere below these loops, returns a feasible path between these two locations, if such a path exists. The technique infers a collection of constraint systems from the program and uses them to steer the symbolic execution towards the target. On reaching a loop it iteratively solves the appropriate constraint system to find out which path through this loop to take, or, alternatively, whether to continue below the loop. To construct the constraint systems we express the values of variables modified in a loop as functions of the number of times a given path through the loop was executed. We have built a prototype implementation of our technique and compared it to state-of-the-art symbolic execution tools on simple programs with loops. The results show significant improvements in the running time. We found instances where our algorithm finished in seconds, whereas the other tools did not finish within an hour. Our approach also shows very good results in the case when the target location is not reachable by any feasible path.


The Limited Power of Powering: Polynomial Identity Testing and a Depth-four Lower Bound for the Permanent

Abstract: Polynomial identity testing and arithmetic circuit lower bounds are two central questions in algebraic complexity theory. It is an intriguing fact that these questions are actually related. One of the authors of the present paper has recently proposed a "real {\tau}-conjecture" which is inspired by this connection. The real {\tau}-conjecture states that the number of real roots of a sum of products of sparse univariate polynomials should be polynomially bounded. It implies a superpolynomial lower bound on the size of arithmetic circuits computing the permanent polynomial. In this paper we show that the real {\tau}-conjecture holds true for a restricted class of sums of products of sparse polynomials. This result yields lower bounds for a restricted class of depth-4 circuits: we show that polynomial size circuits from this class cannot compute the permanent, and we also give a deterministic polynomial identity testing algorithm for the same class of circuits.


A novel methodology for antenna design and optimization: Variable Zo

Abstract: This paper describes "Variable Zo," a novel and proprietary approach to antenna design and optimization. The new methodology is illustrated by applying it to the design of a resistively-loaded bowtie antenna and to two broadband Yagi-Uda arrays. Variable Zo is applicable to any antenna design or optimization methodology. Using it will result in generally better antenna designs across any user-specified set of performance objectives.


Answering Non-Monotonic Queries in Relational Data Exchange

Abstract: Relational data exchange is the problem of translating relational data from a source schema into a target schema, according to a specification of the relationship between the source data and the target data. One of the basic issues is how to answer queries that are posed against target data. While consensus has been reached on the definitive semantics for monotonic queries, this issue turned out to be considerably more difficult for non-monotonic queries. Several semantics for non-monotonic queries have been proposed in the past few years. This article proposes a new semantics for non-monotonic queries, called the GCWA*-semantics. It is inspired by semantics from the area of deductive databases. We show that the GCWA*-semantics coincides with the standard open world semantics on monotonic queries, and we further explore the (data) complexity of evaluating non-monotonic queries under the GCWA*-semantics. In particular, we introduce a class of schema mappings for which universal queries can be evaluated under the GCWA*-semantics in polynomial time (data complexity) on the core of the universal solutions.


Sets Have Simple Members

Abstract: The combined Universal Probability M(D) of strings x in sets D is close to max M({x}) over x in D: their ~logs differ by at most D's information j=I(D:H) about the halting sequence H. Thus if all x have complexity K(x) >k, D carries >i bits of information on each its x where i+j ~ k. Note that there are no ways to generate D with significant I(D:H).


Vision-Based Navigation II: Error Analysis for a Navigation Algorithm based on Optical-Flow and a Digital Terrain Map

Abstract: The paper deals with the error analysis of a navigation algorithm that uses as input a sequence of images acquired by a moving camera and a Digital Terrain Map (DTM) of the region been imaged by the camera during the motion. The main sources of error are more or less straightforward to identify: camera resolution, structure of the observed terrain and DTM accuracy, field of view and camera trajectory. After characterizing and modeling these error sources in the framework of the CDTM algorithm, a closed form expression for their effect on the pose and motion errors of the camera can be found. The analytic expression provides a priori measurements for the accuracy in terms of the parameters mentioned above.


Analysis and Improvement of Low Rank Representation for Subspace segmentation

Abstract: We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization model of LRR has a unique solution, which is the shape interaction matrix (SIM) of the data matrix. So in essence LRR is equivalent to factorization methods. We also prove that the minimum value of the optimization model of LRR is equal to the rank of the data matrix. For the noisy case, we show that LRR can be approximated as a factorization method that combines noise removal by column sparse robust PCA. We further propose an improved version of LRR, called Robust Shape Interaction (RSI), which uses the corrected data as the dictionary instead of the noisy data. RSI is more robust than LRR when the corruption in data is heavy. Experiments on both synthetic and real data testify to the improved robustness of RSI.


Polyceptron: A Polyhedral Learning Algorithm

Abstract: In this paper we propose a new algorithm for learning polyhedral classifiers which we call as Polyceptron. It is a Perception like algorithm which updates the parameters only when the current classifier misclassifies any training data. We give both batch and online version of Polyceptron algorithm. Finally we give experimental results to show the effectiveness of our approach.


On Multiway Cut parameterized above lower bounds

Abstract: In this paper we consider two above lower bound parameterizations of the Node Multiway Cut problem - above the maximum separating cut and above a natural LP-relaxation - and prove them to be fixed-parameter tractable. Our results imply O*(4^k) algorithms for Vertex Cover above Maximum Matching and Almost 2-SAT as well as an O*(2^k) algorithm for Node Multiway Cut with a standard parameterization by the solution size, improving previous bounds for these problems.


Formation of Common Investment Networks by Project Establishment between Agents

Abstract: We present an investment model integrated with trust-reputation mechanisms where agents interact with each other to establish investment projects. We investigate the establishment of investment projects, the influence of the interaction between agents in the evolution of the distribution of wealth, as well as the formation of common investment networks and some of their properties. Simulation results show that the wealth distribution presents a power law in its tail. Also, it is shown that the trust and reputation mechanism presented leads to the establishment of networks among agents, which present some of the typical characteristics of real-life networks like a high clustering coefficient and short average path length.


Elliptic Curve Based Zero Knowledge Proofs and Their Applicability on Resource Constrained Devices

Abstract: Elliptic Curve Cryptography (ECC) is an attractive alternative to conventional public key cryptography, such as RSA. ECC is an ideal candidate for implementation on constrained devices where the major computational resources i.e. speed, memory are limited and low-power wireless communication protocols are employed. That is because it attains the same security levels with traditional cryptosystems using smaller parameter sizes. Moreover, in several application areas such as person identification and eVoting, it is frequently required of entities to prove knowledge of some fact without revealing this knowledge. Such proofs of knowledge are called Zero Knowledge Interactive Proofs (ZKIP) and involve interactions between two communicating parties, the Prover and the Verifier. In a ZKIP, the Prover demonstrates the possesion of some information (e.g. authentication information) to the Verifier without disclosing it. In this paper, we focus on the application of ZKIP protocols on resource constrained devices. We study well-established ZKIP protocols based on the discrete logarithm problem and we transform them under the ECC setting. Then, we implement the proposed protocols on Wiselib, a generic and open source algorithmic library. Finally, we present a thorough evaluation of the protocols on two popular hardware platforms equipped with low end microcontrollers (Jennic JN5139, TI MSP430) and 802.15.4 RF transceivers, in terms of code size, execution time, message size and energy requirements. To the best of our knowledge, this is the first attempt of implementing and evaluating ZKIP protocols with emphasis on low-end devices. This work's results can be used from developers who wish to achieve certain levels of security and privacy in their applications.


A Proof of the Boyd-Carr Conjecture

Abstract: Determining the precise integrality gap for the subtour LP relaxation of the traveling salesman problem is a significant open question, with little progress made in thirty years in the general case of symmetric costs that obey triangle inequality. Boyd and Carr [3] observe that we do not even know the worst-case upper bound on the ratio of the optimal 2-matching to the subtour LP; they conjecture the ratio is at most 10/9. In this paper, we prove the Boyd-Carr conjecture. In the case that a fractional 2-matching has no cut edge, we can further prove that an optimal 2-matching is at most 10/9 times the cost of the fractional 2-matching.


On the Integrality Gap of the Subtour LP for the 1,2-TSP

Abstract: In this paper, we study the integrality gap of the subtour LP relaxation for the traveling salesman problem in the special case when all edge costs are either 1 or 2. For the general case of symmetric costs that obey triangle inequality, a famous conjecture is that the integrality gap is 4/3. Little progress towards resolving this conjecture has been made in thirty years. We conjecture that when all edge costs $c_{ij}\in \{1,2\}$, the integrality gap is $10/9$. We show that this conjecture is true when the optimal subtour LP solution has a certain structure. Under a weaker assumption, which is an analog of a recent conjecture by Schalekamp, Williamson and van Zuylen, we show that the integrality gap is at most $7/6$. When we do not make any assumptions on the structure of the optimal subtour LP solution, we can show that integrality gap is at most $5/4$; this is the first bound on the integrality gap of the subtour LP strictly less than $4/3$ known for an interesting special case of the TSP. We show computationally that the integrality gap is at most $10/9$ for all instances with at most 12 cities.


Throughput Computation in CSMA Wireless Networks with Collision Effects

Abstract: It is known that link throughputs of CSMA wireless networks can be computed from a time-reversible Markov chain arising from an ideal CSMA network model (ICN). In particular, this model yields general closed-form equations of link throughputs. However, an idealized and important assumption made in ICN is that the backoff countdown process is in "contiuous-time" and carrier sensing is instantaneous. As a result, there is no collision in ICN. In practical CSMA protocols such as IEEE 802.11, the stations count down in "mini-timeslot" and the process is therefore a "discrete-time" process. In particular, two stations may end their backoff process in the same mini-timeslot and then transmit simultaneously, resulting in a packet collision. This paper is an attempt to study how to compute link throughputs after taking such backoff collision effects into account. We propose a generalized ideal CSMA network model (GICN) to characterize the collision states as well as the interactions and dependency among links in the network. We show that link throughputs and collision probability can be computed from GICN. Simulation results validate GICN's accuracy. Interestingly, we also find that the original ICN model yields fairly accurate results despite the fact that collisions are not modeled.


Click Efficiency: A Unified Optimal Ranking for Online Ads and Documents

Abstract: Traditionally the probabilistic ranking principle is used to rank the search results while the ranking based on expected profits is used for paid placement of ads. These rankings try to maximize the expected utilities based on the user click models. Recent empirical analysis on search engine logs suggests a unified click models for both ranked ads and search results. The segregated view of document and ad rankings does not consider this commonality. Further, the used models consider parameters of (i) probability of the user abandoning browsing results (ii) perceived relevance of result snippets. But how to consider them for improved ranking is unknown currently. In this paper, we propose a generalized ranking function---namely "Click Efficiency (CE)"---for documents and ads based on empirically proven user click models. The ranking considers parameters (i) and (ii) above, optimal and has the same time complexity as sorting. To exploit its generality, we examine the reduced forms of CE ranking under different assumptions enumerating a hierarchy of ranking functions. Some of the rankings in the hierarchy are currently used ad and document ranking functions; while others suggest new rankings. While optimality of ranking is sufficient for document ranking, applying CE ranking to ad auctions requires an appropriate pricing mechanism. We incorporate a second price based pricing mechanism with the proposed ranking. Our analysis proves several desirable properties including revenue dominance over VCG for the same bid vector and existence of a Nash Equilibrium in pure strategies. The equilibrium is socially optimal, and revenue equivalent to the truthful VCG equilibrium. Further, we relax the independence assumption in CE ranking and analyze the diversity ranking problem. We show that optimal diversity ranking is NP-Hard in general, and that a constant time approximation is unlikely.


A Step towards an Easy Interconversion of Various Number Systems

Abstract: Any system that is used for naming or representing numbers is a number system, also known as numeral system. The modern civilization is familiar with decimal number system using ten digits. However digital devices and computers use binary number system instead of decimal number system, using only two digits namely, 0 and 1 based on the fundamental concept of the decimal number system. Various other number systems also used this fundamental concept of decimal number system, for example octal system and hexadecimal number systems using eight and sixteen digits respectively. The knowledge of number systems and their inter conversion is essential for understanding of computers. More over, successful programming for digital devices requires a precise understanding of data formats, number systems and their inter conversion. The inter conversion (a process in which things are each converted into the other) of number system requires allot of time and techniques to expertise. In this paper the interconversion of four most common number systems is taken under the consideration in tabulated form. It is a step towards the easy interconversion of theses number systems to understand as well as memorise it. The four number systems are binary, octal, decimal and hexadecimal.


A multilingual/multicultural semantic-based approach to improve Data Sharing in an SDI for Nature Conservation

Abstract: The paper proposes an approach to transcend multicultural and multilingual barriers in the use and reuse of geographical data at the European level. The approach aims at sharing scientific terms in the field of nature conservation with the goal of assisting different user communities with metadata compilation and information discovery. A multi-thesauri solution is proposed, based on a Common Thesaurus Framework for Nature Conservation, where different well-known Knowledge Organization Systems are assembled and shared. It has been designed according to semantic web and W3C recommendations employing SKOS standard models and Linked Data to publish the thesauri as a whole in machine-understandable format. The outcome is a powerful framework satisfying the requirements of modularity and openness for further thesaurus extension and updating, interlinking among thesauri, and exploitability from other systems. The paper supports the employment of Linked Data to deal with terminologies in complex domains such as nature conservation and it proposes a hands-on recipe to publish thesauri in the framework.


Proceedings of the Doctoral Consortium and Poster Session of the 5th International Symposium on Rules (RuleML 2011@IJCAI)

Abstract: This volume contains the papers presented at the first edition of the Doctoral Consortium of the 5th International Symposium on Rules (RuleML 2011@IJCAI) held on July 19th, 2011 in Barcelona, as well as the poster session papers of the RuleML 2011@IJCAI main conference.


Jaywalking your Dog - Computing the Fr\'echet Distance with Shortcuts

Abstract: The similarity of two polygonal curves can be measured using the Fr\'echet distance. We introduce the notion of a more robust Fr\'echet distance, where one is allowed to shortcut between vertices of one of the curves. This is a natural approach for handling noise, in particular batched outliers. We compute a (3+\eps)-approximation to the minimum Fr\'echet distance over all possible such shortcuts, in near linear time, if the curve is c-packed and the number of shortcuts is either small or unbounded. To facilitate the new algorithm we develop several new tools: (A) A data structure for preprocessing a curve (not necessarily c-packed) that supports (1+\eps)-approximate Fr\'echet distance queries between a subcurve (of the original curve) and a line segment. (B) A near linear time algorithm that computes a permutation of the vertices of a curve, such that any prefix of 2k-1 vertices of this permutation, form an optimal approximation (up to a constant factor) to the original curve compared to any polygonal curve with k vertices, for any k > 0. (C) A data structure for preprocessing a curve that supports approximate Fr\'echet distance queries between a subcurve and query polygonal curve. The query time depends quadratically on the complexity of the query curve, and only (roughly) logarithmically on the complexity of the original curve. To our knowledge, these are the first data structures to support these kind of queries efficiently.


Notes on Electronic Lexicography

Abstract: These notes are a continuation of topics covered by V. Selegej in his article "Electronic Dictionaries and Computational lexicography". How can an electronic dictionary have as its object the description of closely related languages? Obviously, such a question allows multiple answers.


A Survey of User-Centric Data Warehouses: From Personalization to Recommendation

Abstract: Providing a customized support for the OLAP brings tremendous challenges to the OLAP technology. Standing at the crossroads of the preferences and the data warehouse, two emerging trends are pointed out; namely: (i) the personalization and (ii) the recommendation. Although the panoply of the proposed approaches, the user-centric data warehouse community issues have not been addressed yet. In this paper we draw an overview of several user centric data warehouse proposals. We also discuss the two promising concepts in this issue, namely, the personalization and the recommendation of the data warehouses. We compare the current approaches among each others with respect to some criteria.


Hamiltonian Paths in Two Classes of Grid Graphs

Abstract: In this paper, we give the necessary and sufficient conditions for the existence of Hamiltonian paths in $L-$alphabet and $C-$alphabet grid graphs. We also present a linear-time algorithm for finding Hamiltonian paths in these graphs.


Efficient coordination mechanisms for unrelated machine scheduling

Abstract: We present new coordination mechanisms for scheduling selfish jobs on $m$ unrelated machines. A coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. The scheduling policies induce a game among the jobs and each job prefers to be scheduled on a machine so that its completion time is minimum given the assignments of the other jobs. We consider the maximum completion time among all jobs as the measure of the efficiency of schedules. The approximation ratio of a coordination mechanism quantifies the efficiency of pure Nash equilibria (price of anarchy) of the induced game. Our mechanisms are deterministic, local, and preemptive. Our first coordination mechanism has approximation ratio $\Theta(\log m)$ and guarantees that the induced game has pure Nash equilibria. This result improves a bound of $O(\log^2 m)$ due to Azar, Jain, and Mirrokni and uses a global ordering of the jobs according to their distinct IDs. Our second mechanism handles anonymous jobs and has approximation ratio $O(\frac{\log m}{\log \log m})$ although the game induced is not a potential game and, hence, the existence of pure Nash equilibria is not guaranteed by potential function arguments. However, it provides evidence that the known lower bounds for non-preemptive coordination mechanisms could be beaten using preemptive scheduling policies. Our third coordination mechanism also handles anonymous jobs and has a nice cost-revealing potential function. We use this potential function in order to prove the existence of equilibria and to upper-bound the price of anarchy of the induced game by $O(\log^2m)$. Our third coordination mechanism is the first that handles anonymous jobs and simultaneously guarantees that the induced game is a potential game and has bounded price of anarchy.


Where Have You Been? Secure Location Provenance for Mobile Devices

Abstract: With the advent of mobile computing, location-based services have recently gained popularity. Many applications use the location provenance of users, i.e., the chronological history of the users' location for purposes ranging from access control, authentication, information sharing, and evaluation of policies. However, location provenance is subject to tampering and collusion attacks by malicious users. In this paper, we examine the secure location provenance problem. We introduce a witness-endorsed scheme for generating collusion-resistant location proofs. We also describe two efficient and privacy-preserving schemes for protecting the integrity of the chronological order of location proofs. These schemes, based on hash chains and Bloom filters respectively, allow users to prove the order of any arbitrary subsequence of their location history to auditors. Finally, we present experimental results from our proof-of-concept implementation on the Android platform and show that our schemes are practical in today's mobile devices.


Efficient Identity Based Public Verifiable Signcryption Scheme

Abstract: Signcryption is a cryptographic primitive which performs encryption and signature in a single logical step. In conventional signcryption only receiver of the signcrypted text can verify the authenticity of the origin i.e. signature of the sender on the message after decrypting the cipher text. In public verifiable signcryption scheme anyone can verify the authenticity of the origin who can access the signcrypted text i.e. signature of the sender on the cipher text. Public verifiable signcryption scheme in which the receiver can convince a third party, by providing additional information other than his private key along with the signcryption is called third party verifiable signcryption schemes. In this paper we proposed an efficient identity based public verifiable signcryption scheme with third party verification and proved its security in the random oracle model.


Task swapping networks in distributed systems

Abstract: In this paper we propose task swapping networks for task reassignments by using task swappings in distributed systems. Some classes of task reassignments are achieved by using iterative local task swappings between software agents in distributed systems. We use group-theoretic methods to find a minimum-length sequence of adjacent task swappings needed from a source task assignment to a target task assignment in a task swapping network of several well-known topologies.


Priority-based task reassignments in hierarchical 2D mesh-connected systems using tableaux

Abstract: Task reassignments in 2D mesh-connected systems (2D-MSs) have been researched for several decades. We propose a hierarchical 2D mesh-connected system (2D-HMS) in order to exploit the regular nature of a 2D-MS. In our approach priority-based task assignments and reassignments in a 2D-HMS are represented by tableaux and their algorithms. We show how task relocations for a priority-based task reassignment in a 2D-HMS are reduced to a jeu de taquin slide.


Matrix powers algorithms for trust evaluation in PKI architectures

Abstract: This paper deals with the evaluation of trust in public-key infrastructures. Different trust models have been proposed to interconnect the various PKI components in order to propagate the trust between them. In this paper we provide a new polynomial algorithm using linear algebra to assess trust relationships in a network using different trust evaluation schemes. The advantages are twofold: first the use of matrix computations instead of graph algorithms provides an optimized computational solution; second, our algorithm can be used for generic graphs, even in the presence of cycles. Our algorithm is designed to evaluate the trust using all existing (finite) trust paths between entities as a preliminary to any exchanges between PKIs. This can give a precise evaluation of trust, and accelerate for instance cross-certificate validation.


Benchmarking ordering techniques for nonserial dynamic programming

Abstract: Five ordering algorithms for the nonserial dynamic programming algorithm for solving sparse discrete optimization problems are compared in this paper. The benchmarking reveals that the ordering of the variables has a significant impact on the run-time of these algorithms. In addition, it is shown that different orderings are most effective for different classes of problems. Finally, it is shown that, amongst the algorithms considered here, heuristics based on maximum cardinality search and minimum fill-in perform best for solving the discrete optimization problems considered in this paper.


Propositional equality, identity types, and direct computational paths

Abstract: In proof theory the notion of canonical proof is rather basic, and it is usually taken for granted that a canonical proof of a sentence must be unique up to certain minor syntactical details (such as, e.g., change of bound variables). When setting up a proof theory for equality one is faced with a rather unexpected situation where there may not be a unique canonical proof of an equality statement. Indeed, in a (1994--5) proposal for the formalisation of proofs of propositional equality in the Curry--Howard style, we have already uncovered such a peculiarity. Totally independently, and in a different setting, Hofmann & Streicher (1994) have shown how to build a model of Martin-L\"of's Type Theory in which uniqueness of canonical proofs of identity types does not hold. The intention here is to show that, by considering as sequences of rewrites and substitution, it comes a rather natural fact that two (or more) distinct proofs may be yet canonical and are none to be preferred over one another. By looking at proofs of equality as rewriting (or computational) paths this approach will be in line with the recently proposed connections between type theory and homotopy theory via identity types, since elements of identity types will be, concretely, paths (or homotopies).


Current State and Challenges of Automatic Planning in Web Service Composition

Abstract: This paper gives a survey on the current state of Web Service Compositions and the difficulties and solutions to automated Web Service Compositions. This first gives a definition of Web Service Composition and the motivation and goal of it. It then explores into why we need automated Web Service Compositions and formally defines the domains. Techniques and solutions are proposed by the papers we surveyed to solve the current difficulty of automated Web Service Composition. Verification and future work is discussed at the end to further extend the topic.


Scale-Free Opportunistic Networks: is it Possible?

Abstract: The coupling of scale-free networks with mobile unstructured networks is certainly unusual. In mobile networks, connections active at a given instant are constrained by the geographical distribution of mobile nodes, and by the limited signal strength of the wireless technology employed to build the ad-hoc overlay. This is in contrast with the presence of hubs, typical of scale-free nets. However, opportunistic (mobile) networks possess the distinctive feature to be delay tolerant; mobile nodes implement a store, carry and forward strategy that permits to disseminate data based on a multi-hop route, which is built in time, when nodes encounter other ones while moving. In this paper, we consider opportunistic networks as evolving graphs where links represent contacts among nodes arising during a (non-instantaneous) time interval. We discuss a strategy to control the way nodes manage contacts and build "opportunistic overlays". Based on such an approach, interesting overlays can be obtained, shaped following given desired topologies, such as scale-free ones.


Link Scheduling in Multi-Transmit-Receive Wireless Networks

Abstract: This paper investigates the problem of link scheduling to meet traffic demands with minimum airtime in a multi-transmit-receive (MTR) wireless network. MTR networks are a new class of networks, in which each node can simultaneously transmit to a number of other nodes, or simultaneously receive from a number of other nodes. The MTR capability can be enabled by the use of multiple directional antennas or multiple channels. Potentially, MTR can boost the network capacity significantly. However, link scheduling that makes full use of the MTR capability must be in place before this can happen. We show that optimal link scheduling can be formulated as a linear program (LP). However, the problem is NP-hard because we need to find all the maximal independent sets in a graph first. We propose two computationally efficient algorithms, called Heavy-Weight-First (HWF) and Max-Degree-First (MDF) to solve this problem. Simulation results show that both HWF and MDF can achieve superior performance in terms of runtime and optimality.


Enhanced Genetic Algorithm approach for Solving Dynamic Shortest Path Routing Problems using Immigrants and Memory Schemes

Abstract: In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the memory. Results shows GA with new immigrants shows better convergence result than GA with memory scheme.


Region-based Approach for Determining the Optimal Path Using PSO

Abstract: Many research works have been carried out recently to find the optimal path in network routing. Among them the evolutionary algorithms is an area where work is carried out extensively. We in this paper, have used PSO for finding the optimal path and the concept of region based network is introduced along with the use of indirect encoding. A comparative study of genetic algorithm (GA) and particle swarm optimization (PSO) is carried out, and it was found that PSO performed better than GA.


Knowledge Embedding and Retrieval Strategies in an Informledge System

Abstract: Informledge System (ILS) is a knowledge network with autonomous nodes and intelligent links that integrate and structure the pieces of knowledge. In this paper, we put forward the strategies for knowledge embedding and retrieval in an ILS. ILS is a powerful knowledge network system dealing with logical storage and connectivity of information units to form knowledge using autonomous nodes and multi-lateral links. In ILS, the autonomous nodes known as Knowledge Network Nodes (KNN)s play vital roles which are not only used in storage, parsing and in forming the multi-lateral linkages between knowledge points but also in helping the realization of intelligent retrieval of linked information units in the form of knowledge. Knowledge built in to the ILS forms the shape of sphere. The intelligence incorporated into the links of a KNN helps in retrieving various knowledge threads from a specific set of KNNs. A developed entity of information realized through KNN forms in to the shape of a knowledge cone


Particle Swarm Optimization for Realizing Intelligent Routing in Networks with Quality Grading

Abstract: Significant research has been carried out in the recent years for generating systems exhibiting intelligence for realizing optimized routing in networks. In this paper, a grade based twolevel based node selection method along with Particle Swarm Optimization (PSO) technique is proposed. It assumes that the nodes are intelligent and there exist a knowledge base about the environment in their local memory. There are two levels for approaching the effective route selection process through grading. At the first level, grade based selection is applied and at the second level, the optimum path is explored using PSO. The simulation has been carried out on different topological structures and it is observed that a graded network produces a significant reduction in number of iteration to arrive at the optimal path selection.


A Novel Agent Based Approach for Controlling Network Storms

Abstract: One of the fundamental data transmission mechanisms in Ethernet LAN is broadcasting. Flooding is a direct broadcasting technique used in these networks. A significant drawback of this method is that it can lead to broadcast storms. This phenomenon is more common in multivendor switch environment. Broadcast storms usually results in dissension, collision and redundancy leading to degradation of the network performance. Most of the storms appear without much warning and it affects the efficiency of network even in situations when the network is expected to work most efficiently. There are several characteristic patterns by which storm can appear in a LAN, like rate monotonic repetition, transient appearances with different types of growth properties and decay profiles. In this paper we discuss the storm build up pattern in an industry and present various reasons for storm in LAN. We have identified a strategy for controlling network storms, using multiple static agents. These agents inhibit storm packet regeneration in the network using the knowledge of storm growth pattern. A model developed out of empirical studies is used to differentiate normal packet growth from storm packet growth and used in control mechanism of storms.


Informledge System: A Modified Knowledge Network with Autonomous Nodes using Multi-lateral Links

Abstract: Research in the field of Artificial Intelligence is continually progressing to simulate the human knowledge into automated intelligent knowledge base, which can encode and retrieve knowledge efficiently along with the capability of being is consistent and scalable at all times. However, there is no system at hand that can match the diversified abilities of human knowledge base. In this position paper, we put forward a theoretical model of a different system that intends to integrate pieces of knowledge, Informledge System (ILS). ILS would encode the knowledge, by virtue of knowledge units linked across diversified domains. The proposed ILS comprises of autonomous knowledge units termed as Knowledge Network Node (KNN), which would help in efficient cross-linking of knowledge units to encode fresh knowledge. These links are reasoned and inferred by the Parser and Link Manager, which are part of KNN.


Intuitionistic implication makes model checking hard

Abstract: We investigate the complexity of the model checking problem for intuitionistic and modal propositional logics over transitive Kripke models. More specific, we consider intuitionistic logic IPC, basic propositional logic BPL, formal propositional logic FPL, and Jankov's logic KC. We show that the model checking problem is P-complete for the implicational fragments of all these intuitionistic logics. For BPL and FPL we reach P-hardness even on the implicational fragment with only one variable. The same hardness results are obtained for the strictly implicational fragments of their modal companions. Moreover, we investigate whether formulas with less variables and additional connectives make model checking easier. Whereas for variable free formulas outside of the implicational fragment, FPL model checking is shown to be in LOGCFL, the problem remains P-complete for BPL.


A Novel Adaptive Routing through Fitness Function Estimation Technique with Multiple QoS Parameters Compliance

Abstract: The paper presents a method which shows a significant improvement in discovering the path over the distance vector protocol. The proposed method is a multi-parameter QoS along with the fitness function which shows that it overcomes the limitation of DV like routing loops by spanning tree approach, count-to-infinity problem by decision attribute. The input considered is a topology satisfying the QoS parameters of size 1 to 64 nodes and it was shown that an optimal path selection was obtained efficiently over the classical distance vector algorithm


A Packet Scheduling Strategy in Sensor Networks with SGMH Protocol

Abstract: Data communication in sensor networks can have timing constraints like end to end deadlines. If the deadlines are not met either a catastrophe can happen in hard real time systems or performance deterioration can occur in soft real time systems. In real time sensor networks, the recovery of data through retransmission should be minimized due to the stringent requirements on the worst case time delays. This paper presents the application of Stop and Go Multihop protocol (SGMH) at node level in wireless sensor networks for scheduling and hence to meet the hard real time routing requirements. SGMH is a distributed multihop packet delivery algorithm. The fractions of the total available bandwidth on each channel is assigned to several traffic classes by which the time it takes to traverse each of the hops from the source to the destination is bounded. It is based on the notion of time frames (Tfr). In sensor networks packets can have different delay guarantees. Multiple frame sizes can be assigned for different traffic classes.


Towards a Calculus of Object Programs

Abstract: Verifying properties of object-oriented software requires a method for handling references in a simple and intuitive way, closely related to how O-O programmers reason about their programs. The method presented here, a Calculus of Object Programs, combines four components: compositional logic, a framework for describing program semantics and proving program properties; negative variables to address the specifics of O-O programming, in particular qualified calls; the alias calculus, which determines whether reference expressions can ever have the same value; and the calculus of object structures, a specification technique for the structures that arise during the execution of an object-oriented program. The article illustrates the Calculus by proving the standard algorithm for reversing a linked list.


Tight Approximation Bounds for Vertex Cover on Dense k-Partite Hypergraphs

Abstract: We establish almost tight upper and lower approximation bounds for the Vertex Cover problem on dense k-partite hypergraphs.


An Approximation Algorithm for #k-SAT

Abstract: We present a simple randomized algorithm that approximates the number of satisfying assignments of Boolean formulas in conjunctive normal form. To the best of our knowledge this is the first algorithm which approximates #k-SAT for any k >= 3 within a running time that is not only non-trivial, but also significantly better than that of the currently fastest exact algorithms for the problem. More precisely, our algorithm is a randomized approximation scheme whose running time depends polynomially on the error tolerance and is mildly exponential in the number n of variables of the input formula. For example, even stipulating sub-exponentially small error tolerance, the number of solutions to 3-CNF input formulas can be approximated in time O(1.5366^n). For 4-CNF input the bound increases to O(1.6155^n). We further show how to obtain upper and lower bounds on the number of solutions to a CNF formula in a controllable way. Relaxing the requirements on the quality of the approximation, on k-CNF input we obtain significantly reduced running times in comparison to the above bounds.


Efficient Deterministic Replay Using Complete Race Detection

Abstract: Data races can significantly affect the executions of multi-threaded programs. Hence, one has to recur the results of data races to deterministically replay a multi-threaded program. However, data races are concealed in enormous number of memory operations in a program. Due to the difficulty of accurately identifying data races, previous multi-threaded deterministic record/replay schemes for commodity multi-processor system give up to record data races directly. Consequently, they either record all shared memory operations, which brings remarkable slowdown to the production run, or record the synchronization only, which introduces significant efforts to replay. Inspired by the advances in data race detection, we propose an efficient software-only deterministic replay scheme for commodity multi-processor systems, which is named RacX. The key insight of RacX is as follows: although it is NP-hard to accurately identify the existence of data races between a pair of memory operations, we can find out all potential data races in a multi-threaded program, in which the false positives can be reduced to a small amount with our automatic false positive reduction techniques. As a result, RacX can efficiently monitor all potential data races to deterministically replay a multi-threaded program. To evaluate RacX, we have carried out experiments over a number of well-known multi-threaded programs from SPLASH-2 benchmark suite and large-scale commercial programs. RacX can precisely recur production runs of these programs with value determinism. Averagely, RacX causes only about 1.21%, 1.89%, 2.20%, and 8.41% slowdown to the original run during recording (for 2-, 4-, 8- and 16-thread programs, respectively). The soundness, efficiency, scalability, and portability of RacX well demonstrate its superiority.


Robustness of Structurally Equivalent Concurrent Parity Games

Abstract: We consider two-player stochastic games played on a finite state space for an infinite number of rounds. The games are concurrent: in each round, the two players (player 1 and player 2) choose their moves independently and simultaneously; the current state and the two moves determine a probability distribution over the successor states. We also consider the important special case of turn-based stochastic games where players make moves in turns, rather than concurrently. We study concurrent games with \omega-regular winning conditions specified as parity objectives. The value for player 1 for a parity objective is the maximal probability with which the player can guarantee the satisfaction of the objective against all strategies of the opponent. We study the problem of continuity and robustness of the value function in concurrent and turn-based stochastic parity gameswith respect to imprecision in the transition probabilities. We present quantitative bounds on the difference of the value function (in terms of the imprecision of the transition probabilities) and show the value continuity for structurally equivalent concurrent games (two games are structurally equivalent if the support of the transition function is same and the probabilities differ). We also show robustness of optimal strategies for structurally equivalent turn-based stochastic parity games. Finally we show that the value continuity property breaks without the structurally equivalent assumption (even for Markov chains) and show that our quantitative bound is asymptotically optimal. Hence our results are tight (the assumption is both necessary and sufficient) and optimal (our quantitative bound is asymptotically optimal).


A note on the generalized min-sum set cover problem

Abstract: In this paper, we consider the generalized min-sum set cover problem, introduced by Azar, Gamzu, and Yin. Bansal, Gupta, and Krishnaswamy give a 485-approximation algorithm for the problem. We are able to alter their algorithm and analysis to obtain a 28-approximation algorithm, improving the performance guarantee by an order of magnitude. We use concepts from $\alpha$-point scheduling to obtain our improvements.


Kunchenko's Polynomials for Template Matching

Abstract: This paper reviews Kunchenko's polynomials using as template matching method to recognize template in one-dimensional input signal. Kunchenko's polynomials method is compared with classical methods - cross-correlation and sum of squared differences according to numerical statistical example.


Extend Commitment Protocols with Temporal Regulations: Why and How

Abstract: The proposal of Elisa Marengo's thesis is to extend commitment protocols to explicitly account for temporal regulations. This extension will satisfy two needs: (1) it will allow representing, in a flexible and modular way, temporal regulations with a normative force, posed on the interaction, so as to represent conventions, laws and suchlike; (2) it will allow committing to complex conditions, which describe not only what will be achieved but to some extent also how. These two aspects will be deeply investigated in the proposal of a unified framework, which is part of the ongoing work and will be included in the thesis.


Rule-Based Semantic Sensing

Abstract: Rule-Based Systems have been in use for decades to solve a variety of problems but not in the sensor informatics domain. Rules aid the aggregation of low-level sensor readings to form a more complete picture of the real world and help to address 10 identified challenges for sensor network middleware. This paper presents the reader with an overview of a system architecture and a pilot application to demonstrate the usefulness of a system integrating rules with sensor middleware.


Advancing Multi-Context Systems by Inconsistency Management

Abstract: Multi-Context Systems are an expressive formalism to model (possibly) non-monotonic information exchange between heterogeneous knowledge bases. Such information exchange, however, often comes with unforseen side-effects leading to violation of constraints, making the system inconsistent, and thus unusable. Although there are many approaches to assess and repair a single inconsistent knowledge base, the heterogeneous nature of Multi-Context Systems poses problems which have not yet been addressed in a satisfying way: How to identify and explain a inconsistency that spreads over multiple knowledge bases with different logical formalisms (e.g., logic programs and ontologies)? What are the causes of inconsistency if inference/information exchange is non-monotonic (e.g., absent information as cause)? How to deal with inconsistency if access to knowledge bases is restricted (e.g., companies exchange information, but do not allow arbitrary modifications to their knowledge bases)? Many traditional approaches solely aim for a consistent system, but automatic removal of inconsistency is not always desireable. Therefore a human operator has to be supported in finding the erroneous parts contributing to the inconsistency. In my thesis those issues will be adressed mainly from a foundational perspective, while our research project also provides algorithms and prototype implementations.


Rule-based query answering method for a knowledge base of economic crimes

Abstract: We present a description of the PhD thesis which aims to propose a rule-based query answering method for relational data. In this approach we use an additional knowledge which is represented as a set of rules and describes the source data at concept (ontological) level. Queries are posed in the terms of abstract level. We present two methods. The first one uses hybrid reasoning and the second one exploits only forward chaining. These two methods are demonstrated by the prototypical implementation of the system coupled with the Jess engine. Tests are performed on the knowledge base of the selected economic crimes: fraudulent disbursement and money laundering.


Semantic-ontological combination of Business Rules and Business Processes in IT Service Management

Abstract: IT Service Management deals with managing a broad range of items related to complex system environments. As there is both, a close connection to business interests and IT infrastructure, the application of semantic expressions which are seamlessly integrated within applications for managing ITSM environments, can help to improve transparency and profitability. This paper focuses on the challenges regarding the integration of semantics and ontologies within ITSM environments. It will describe the paradigm of relationships and inheritance within complex service trees and will present an approach of ontologically expressing them. Furthermore, the application of SBVR-based rules as executable SQL triggers will be discussed. Finally, the broad range of topics for further research, derived from the findings, will be presented.


Decidable Problems for Probabilistic Automata on Infinite Words

Abstract: We consider probabilistic automata on infinite words with acceptance defined by parity conditions. We consider three qualitative decision problems: (i) the positive decision problem asks whether there is a word that is accepted with positive probability; (ii) the almost decision problem asks whether there is a word that is accepted with probability 1; and (iii) the limit decision problem asks whether for every epsilon > 0 there is a word that is accepted with probability at least 1 - epsilon. We unify and generalize several decidability results for probabilistic automata over infinite words, and identify a robust (closed under union and intersection) subclass of probabilistic automata for which all the qualitative decision problems are decidable for parity conditions. We also show that if the input words are restricted to lasso shape (regular) words, then the positive and almost problems are decidable for all probabilistic automata with parity conditions. For most decidable problems we show an optimal PSPACE-complete complexity bound.