New technologies for high speed computer networks: a wavelet approach

Abstract: Indoor multpropagation channel is modeled by the Kaiser electromagnetic wavelet. A method for channel characterization is proposed by modeling all the reflections of indoor propagation in a kernel function instead of its impulse response. This lead us to consider a fractal modulation scheme in which Kaiser wavelets substitute the traditional sinusoidal carrier.


A Methodology for Learning Players' Styles from Game Records

Abstract: We describe a preliminary investigation into learning a Chess player's style from game records. The method is based on attempting to learn features of a player's individual evaluation function using the method of temporal differences, with the aid of a conventional Chess engine architecture. Some encouraging results were obtained in learning the styles of two recent Chess world champions, and we report on our attempt to use the learnt styles to discriminate between the players from game records by trying to detect who was playing white and who was playing black. We also discuss some limitations of our approach and propose possible directions for future research. The method we have presented may also be applicable to other strategic games, and may even be generalisable to other domains where sequences of agents' actions are recorded.


Exponential Family Graph Matching and Ranking

Abstract: We present a method for learning max-weight matching predictors in bipartite graphs. The method consists of performing maximum a posteriori estimation in exponential families with sufficient statistics that encode permutations and data features. Although inference is in general hard, we show that for one very relevant application - web page ranking - exact inference is efficient. For general model instances, an appropriate sampler is readily available. Contrary to existing max-margin matching models, our approach is statistically consistent and, in addition, experiments with increasing sample sizes indicate superior improvement over such models. We apply the method to graph matching in computer vision as well as to a standard benchmark dataset for learning web page ranking, in which we obtain state-of-the-art results, in particular improving on max-margin variants. The drawback of this method with respect to max-margin alternatives is its runtime for large graphs, which is comparatively high.


Better Quality in Synthesis through Quantitative Objectives

Abstract: Most specification languages express only qualitative constraints. However, among two implementations that satisfy a given specification, one may be preferred to another. For example, if a specification asks that every request is followed by a response, one may prefer an implementation that generates responses quickly but does not generate unnecessary responses. We use quantitative properties to measure the "goodness" of an implementation. Using games with corresponding quantitative objectives, we can synthesize "optimal" implementations, which are preferred among the set of possible implementations that satisfy a given specification. In particular, we show how automata with lexicographic mean-payoff conditions can be used to express many interesting quantitative properties for reactive systems. In this framework, the synthesis of optimal implementations requires the solution of lexicographic mean-payoff games (for safety requirements), and the solution of games with both lexicographic mean-payoff and parity objectives (for liveness requirements). We present algorithms for solving both kinds of novel graph games.


On Finding Directed Trees with Many Leaves

Abstract: The Rooted Maximum Leaf Outbranching problem consists in finding a spanning directed tree rooted at some prescribed vertex of a digraph with the maximum number of leaves. Its parameterized version asks if there exists such a tree with at least $k$ leaves. We use the notion of $s-t$ numbering to exhibit combinatorial bounds on the existence of spanning directed trees with many leaves. These combinatorial bounds allow us to produce a constant factor approximation algorithm for finding directed trees with many leaves, whereas the best known approximation algorithm has a $\sqrt{OPT}$-factor. We also show that Rooted Maximum Leaf Outbranching admits a quadratic kernel, improving over the cubic kernel given by Fernau et al.


Bounded Linear Logic, Revisited

Abstract: We present QBAL, an extension of Girard, Scedrov and Scott's bounded linear logic. The main novelty of the system is the possibility of quantifying over resource variables. This generalization makes bounded linear logic considerably more flexible, while preserving soundness and completeness for polynomial time. In particular, we provide compositional embeddings of Leivant's RRW and Hofmann's LFPL into QBAL.


New Branching Rules: Improvements on Independent Set and Vertex Cover in Sparse Graphs

Abstract: We present an $O^*(1.0919^n)$-time algorithm for finding a maximum independent set in an $n$-vertex graph with degree bounded by 3, which improves the previously known algorithm of running time $O^*(1.0977^n)$ by Bourgeois, Escoffier and Paschos [IWPEC 2008]. We also present an $O^*(1.1923^k)$-time algorithm to decide if a graph with degree bounded by 3 has a vertex cover of size $k$, which improves the previously known algorithm of running time $O^*(1.1939^k)$ by Chen, Kanj and Xia [ISAAC 2003]. Two new branching techniques, \emph{branching on a bottle} and \emph{branching on a 4-cycle}, are introduced, which help us to design simple and fast algorithms for the maximum independent set and minimum vertex cover problems and avoid tedious branching rules.


Fast dynamics in Internet topology: preliminary observations and explanations

Abstract: By focusing on what can be observed by running traceroute-like measurements at a high frequency from a single monitor to a fixed destination set, we show that the observed view of the topology is constantly evolving at a pace much higher than expected. Repeated measurements discover new IP addresses at a constant rate, for long period of times (up to several months). In order to provide explanations, we study this phenomenon both at the IP, and at the Autonomous System levels. We show that this renewal of IP addresses is partially caused by a BGP routing dynamics, altering paths between existing ASes. Furthermore, we conjecture that an intra AS routing dynamics is another cause of this phenomenon.


On Counteracting Byzantine Attacks in Network Coded Peer-to-Peer Networks

Abstract: Random linear network coding can be used in peer-to-peer networks to increase the efficiency of content distribution and distributed storage. However, these systems are particularly susceptible to Byzantine attacks. We quantify the impact of Byzantine attacks on the coded system by evaluating the probability that a receiver node fails to correctly recover a file. We show that even for a small probability of attack, the system fails with overwhelming probability. We then propose a novel signature scheme that allows packet-level Byzantine detection. This scheme allows one-hop containment of the contamination, and saves bandwidth by allowing nodes to detect and drop the contaminated packets. We compare the net cost of our signature scheme with various other Byzantine schemes, and show that when the probability of Byzantine attacks is high, our scheme is the most bandwidth efficient.


Fast Computation of Empirically Tight Bounds for the Diameter of Massive Graphs

Abstract: The diameter of a graph is among its most basic parameters. Since a few years, it moreover became a key issue to compute it for massive graphs in the context of complex network analysis. However, known algorithms, including the ones producing approximate values, have too high a time and/or space complexity to be used in such cases. We propose here a new approach relying on very simple and fast algorithms that compute (upper and lower) bounds for the diameter. We show empirically that, on various real-world cases representative of complex networks studied in the literature, the obtained bounds are very tight (and even equal in some cases). This leads to rigorous and very accurate estimations of the actual diameter in cases which were previously untractable in practice.


Detection, Understanding, and Prevention of Traceroute Measurement Artifacts

Abstract: Traceroute is widely used: from the diagnosis of network problems to the assemblage of internet maps. Unfortu- nately, there are a number of problems with traceroute methodology, which lead to the inference of erroneous routes. This paper studies particular structures arising in nearly all traceroute measurements. We characterize them as "loops", "cycles", and "diamonds". We iden- tify load balancing as a possible cause for the appear- ance of false loops, cycles and diamonds, i.e., artifacts that do not represent the internet topology. We pro- vide a new publicly-available traceroute, called Paris traceroute, which, by controlling the packet header con- tents, provides a truer picture of the actual routes that packets follow. We performed measurements, from the perspective of a single source tracing towards multiple destinations, and Paris traceroute allowed us to show that many of the particular structures we observe are indeed traceroute measurement artifacts.


Reconstruction and Clustering in Random Constraint Satisfaction Problems

Abstract: Random instances of Constraint Satisfaction Problems (CSP's) appear to be hard for all known algorithms, when the number of constraints per variable lies in a certain interval. Contributing to the general understanding of the structure of the solution space of a CSP in the satisfiable regime, we formulate a set of natural technical conditions on a large family of (random) CSP's, and prove bounds on three most interesting thresholds for the density of such an ensemble: namely, the satisfiability threshold, the threshold for clustering of the solution space, and the threshold for an appropriate reconstruction problem on the CSP's. The bounds become asymptoticlally tight as the number of degrees of freedom in each clause diverges. The families are general enough to include commonly studied problems such as, random instances of Not-All-Equal-SAT, k-XOR formulae, hypergraph 2-coloring, and graph k-coloring. An important new ingredient is a condition involving the Fourier expansion of clauses, which characterizes the class of problems with a similar threshold structure.


A Non-Holonomic Systems Approach to Special Function Identities

Abstract: We extend Zeilberger's approach to special function identities to cases that are not holonomic. The method of creative telescoping is thus applied to definite sums or integrals involving Stirling or Bernoulli numbers, incomplete Gamma function or polylogarithms, which are not covered by the holonomic framework. The basic idea is to take into account the dimension of appropriate ideals in Ore algebras. This unifies several earlier extensions and provides algorithms for summation and integration in classes that had not been accessible to computer algebra before.


Non Homogeneous Poisson Process Model based Optimal Modular Software Testing using Fault Tolerance

Abstract: In software development process we come across various modules. Which raise the idea of priority of the different modules of a software so that important modules are tested on preference. This approach is desirable because it is not possible to test each module regressively due to time and cost constraints. This paper discuss on some parameters, required to prioritize several modules of a software and provides measure of optimal time and cost for testing based on non homogeneous Poisson process.


Decomposition width - a new width parameter for matroids

Abstract: We introduce a new width parameter for matroids called decomposition width and prove that every matroid property expressible in the monadic second order logic can be computed in linear time for matroids with bounded decomposition width if their decomposition is given. Since decompositions of small width for our new notion can be computed in polynomial time for matroids of bounded branch-width represented over finite fields, our results include recent algorithmic results of Hlineny [J. Combin. Theory Ser. B 96 (2006), 325-351] in this area and extend his results to matroids not necessarily representable over finite fields.


Principle of development

Abstract: Today, science have a powerful tool for the description of reality - the numbers. However, the concept of number was not immediately, lets try to trace the evolution of the concept. The numbers emerged as the need for accurate estimates of the amount in order to permit a comparison of some objects. So if you see to it how many times a day a person uses the numbers and compare, it becomes evident that the comparison is used much more frequently. However, the comparison is not possible without two opposite basic standards. Thus, to introduce the concept of comparison, must have two opposing standards, in turn, the operation of comparison is necessary to introduce the concept of number. Arguably, the scientific description of reality is impossible without the concept of opposites. In this paper analyzes the concept of opposites, as the basis for the introduction of the principle of development.


On FO2 quantifier alternation over words

Abstract: We show that each level of the quantifier alternation hierarchy within FO^2[<] -- the 2-variable fragment of the first order logic of order on words -- is a variety of languages. We then use the notion of condensed rankers, a refinement of the rankers defined by Weis and Immerman, to produce a decidable hierarchy of varieties which is interwoven with the quantifier alternation hierarchy -- and conjecturally equal to it. It follows that the latter hierarchy is decidable within one unit: given a formula alpha in FO^2[<], one can effectively compute an integer m such that alpha is equivalent to a formula with at most m+1 alternating blocks of quantifiers, but not to a formula with only m-1 blocks. This is a much more precise result than what is known about the quantifier alternation hierarchy within FO[<], where no decidability result is known beyond the very first levels.


Towards an Intelligent System for Risk Prevention and Management

Abstract: Making a decision in a changeable and dynamic environment is an arduous task owing to the lack of information, their uncertainties and the unawareness of planners about the future evolution of incidents. The use of a decision support system is an efficient solution of this issue. Such a system can help emergency planners and responders to detect possible emergencies, as well as to suggest and evaluate possible courses of action to deal with the emergency. We are interested in our work to the modeling of a monitoring preventive and emergency management system, wherein we stress the generic aspect. In this paper we propose an agent-based architecture of this system and we describe a first step of our approach which is the modeling of information and their representation using a multiagent system.


Agent-Based Decision Support System to Prevent and Manage Risk Situations

Abstract: The topic of risk prevention and emergency response has become a key social and political concern. One approach to address this challenge is to develop Decision Support Systems (DSS) that can help emergency planners and responders to detect emergencies, as well as to suggest possible course of actions to deal with the emergency. Our research work comes in this framework and aims to develop a DSS that must be generic as much as possible and independent from the case study.


Inconsistency Robustness in Logic Programs

Abstract: Inconsistency robustness is "information system performance in the face of continually pervasive inconsistencies." A fundamental principle of Inconsistency Robustness is to make contradictions explicit so that arguments for and against propositions can be formalized. This paper explores the role of Inconsistency Robustness in the history and theory of Logic Programs. Robert Kowalski put forward a bold thesis: "Looking back on our early discoveries, I value most the discovery that computation could be subsumed by deduction." However, mathematical logic cannot always infer computational steps because computational systems make use of arbitration for determining which message is processed next by a recipient that is sent multiple messages concurrently. Since reception orders are in general indeterminate, they cannot be inferred from prior information by mathematical logic alone. Therefore mathematical logic cannot in general implement computation. Over the course of history, the term "Functional Program" has grown more precise and technical as the field has matured. "Logic Program" should be on a similar trajectory. Accordingly, "Logic Program" should have a general precise characterization. In the fall of 1972, different characterizations of Logic Programs that have continued to this day: * A Logic Program uses Horn-Clause syntax for forward and backward chaining * Each computational step (according to Actor Model) of a Logic Program is deductively inferred (e.g. in Direct Logic). The above examples are illustrative of how issues of inconsistency robustness have repeatedly arisen in Logic Programs.


An efficient quantum search engine on unsorted database

Abstract: We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using $O(log_{4}N)$ queries to factorized oracles. But the algorithm requires that all the property values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the property values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is $O(P*Q*M*log_{4}N)$, where P is the number of the potential simple query requests in the complex query request, Q is the maximum number of calls to the factorized quantum search algorithm of the simple queries, M is the number of the auxiliary files for the property on which our algorithm are searching for desired items. This implies that to manage an unsorted database on an actual quantum computer is possible and efficient.


Approximate counting with a floating-point counter

Abstract: Memory becomes a limiting factor in contemporary applications, such as analyses of the Webgraph and molecular sequences, when many objects need to be counted simultaneously. Robert Morris [Communications of the ACM, 21:840--842, 1978] proposed a probabilistic technique for approximate counting that is extremely space-efficient. The basic idea is to increment a counter containing the value $X$ with probability $2^{-X}$. As a result, the counter contains an approximation of $\lg n$ after $n$ probabilistic updates stored in $\lg\lg n$ bits. Here we revisit the original idea of Morris, and introduce a binary floating-point counter that uses a $d$-bit significand in conjunction with a binary exponent. The counter yields a simple formula for an unbiased estimation of $n$ with a standard deviation of about $0.6\cdot n2^{-d/2}$, and uses $d+\lg\lg n$ bits. We analyze the floating-point counter's performance in a general framework that applies to any probabilistic counter, and derive practical formulas to assess its accuracy.


Using Dissortative Mating Genetic Algorithms to Track the Extrema of Dynamic Deceptive Functions

Abstract: Traditional Genetic Algorithms (GAs) mating schemes select individuals for crossover independently of their genotypic or phenotypic similarities. In Nature, this behaviour is known as random mating. However, non-random schemes - in which individuals mate according to their kinship or likeness - are more common in natural systems. Previous studies indicate that, when applied to GAs, negative assortative mating (a specific type of non-random mating, also known as dissortative mating) may improve their performance (on both speed and reliability) in a wide range of problems. Dissortative mating maintains the genetic diversity at a higher level during the run, and that fact is frequently observed as an explanation for dissortative GAs ability to escape local optima traps. Dynamic problems, due to their specificities, demand special care when tuning a GA, because diversity plays an even more crucial role than it does when tackling static ones. This paper investigates the behaviour of dissortative mating GAs, namely the recently proposed Adaptive Dissortative Mating GA (ADMGA), on dynamic trap functions. ADMGA selects parents according to their Hamming distance, via a self-adjustable threshold value. The method, by keeping population diversity during the run, provides an effective means to deal with dynamic problems. Tests conducted with deceptive and nearly deceptive trap functions indicate that ADMGA is able to outperform other GAs, some specifically designed for tracking moving extrema, on a wide range of tests, being particularly effective when speed of change is not very fast. When comparing the algorithm to a previously proposed dissortative GA, results show that performance is equivalent on the majority of the experiments, but ADMGA performs better when solving the hardest instances of the test set.


P vs NP Problem in the field anthropology

Abstract: An attempt of a new kind of complexity anthropology is considered.


Distributed Maintenance of Anytime Available Spanning Trees in Dynamic Networks

Abstract: We address the problem of building and maintaining distributed spanning trees in highly dynamic networks, in which topological events can occur at any time and any rate, and no stable periods can be assumed. In these harsh environments, we strive to preserve some properties such as cycle-freeness or the existence of a root in each tree, in order to make it possible to keep using the trees uninterruptedly (to a possible extent). Our algorithm operates at a coarse-grain level, using atomic pairwise interactions in a way akin to recent population protocol models. The algorithm relies on a perpetual alternation of \emph{topology-induced splittings} and \emph{computation-induced mergings} of a forest of spanning trees. Each tree in the forest hosts exactly one token (also called root) that performs a random walk {\em inside} the tree, switching parent-child relationships as it crosses edges. When two tokens are located on both sides of a same edge, their trees are merged upon this edge and one token disappears. Whenever an edge that belongs to a tree disappears, its child endpoint regenerates a new token instantly. The main features of this approach is that both \emph{merging} and \emph{splitting} are purely localized phenomenons. In this paper, we present and motivate the algorithm, and we prove its correctness in arbitrary dynamic networks. Then we discuss several implementation choices around this general principle. Preliminary results regarding its analysis are also discussed, in particular an analytical expression of the expected merging time for two given trees in a static context.


Counting Paths and Packings in Halves

Abstract: It is shown that one can count $k$-edge paths in an $n$-vertex graph and $m$-set $k$-packings on an $n$-element universe, respectively, in time ${n \choose k/2}$ and ${n \choose mk/2}$, up to a factor polynomial in $n$, $k$, and $m$; in polynomial space, the bounds hold if multiplied by $3^{k/2}$ or $5^{mk/2}$, respectively. These are implications of a more general result: given two set families on an $n$-element universe, one can count the disjoint pairs of sets in the Cartesian product of the two families with $\nO(n \ell)$ basic operations, where $\ell$ is the number of members in the two families and their subsets.


Variations on Muchnik's Conditional Complexity Theorem

Abstract: Muchnik's theorem about simple conditional descriptions states that for all strings $a$ and $b$ there exists a short program $p$ transforming $a$ to $b$ that has the least possible length and is simple conditional on $b$. In this paper we present two new proofs of this theorem. The first one is based on the on-line matching algorithm for bipartite graphs. The second one, based on extractors, can be generalized to prove a version of Muchnik's theorem for space-bounded Kolmogorov complexity.


Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method

Abstract: Neighborhood graphs are gaining popularity as a concise data representation in machine learning. However, naive graph construction by pairwise distance calculation takes $O(n^2)$ runtime for $n$ data points and this is prohibitively slow for millions of data points. For strings of equal length, the multiple sorting method (Uno, 2008) can construct an $\epsilon$-neighbor graph in $O(n+m)$ time, where $m$ is the number of $\epsilon$-neighbor pairs in the data. To introduce this remarkably efficient algorithm to continuous domains such as images, signals and texts, we employ a random projection method to convert vectors to strings. Theoretical results are presented to elucidate the trade-off between approximation quality and computation time. Empirical results show the efficiency of our method in comparison to fast nearest neighbor alternatives.


On the distributed evaluation of recursive queries over graphs

Abstract: Logical formalisms such as first-order logic (FO) and fixpoint logic (FP) are well suited to express in a declarative manner fundamental graph functionalities required in distributed systems. We show that these logics constitute good abstractions for programming distributed systems as a whole, since they can be evaluated in a fully distributed manner with reasonable complexity upper-bounds. We first prove that FO and FP can be evaluated with a polynomial number of messages of logarithmic size. We then show that the (global) logical formulas can be translated into rule programs describing the local behavior of the nodes of the distributed system, which compute equivalent results. Finally, we introduce local fragments of these logics, which preserve as much as possible the locality of their distributed computation, while offering a rich expressive power for networking functionalities. We prove that they admit tighter upper-bounds with bounded number of messages of bounded size. Finally, we show that the semantics and the complexity of the local fragments are preserved over locally consistent networks as well as anonymous networks, thus showing the robustness of the proposed local logical formalisms.


Reconstructing 3-colored grids from horizontal and vertical projections is NP-hard

Abstract: We consider the problem of coloring a grid using k colors with the restriction that in each row and each column has an specific number of cells of each color. In an already classical result, Ryser obtained a necessary and sufficient condition for the existence of such a coloring when two colors are considered. This characterization yields a linear time algorithm for constructing such a coloring when it exists. Gardner et al. showed that for k>=7 the problem is NP-hard. Afterward Chrobak and Durr improved this result, by proving that it remains NP-hard for k>=4. We solve the gap by showing that for 3 colors the problem is already NP-hard. Besides we also give some results on tiling tomography problems.


On the Complexity of Submodular Function Minimisation on Diamonds

Abstract: Let $(L; \sqcap, \sqcup)$ be a finite lattice and let $n$ be a positive integer. A function $f : L^n \to \mathbb{R}$ is said to be submodular if $f(\tup{a} \sqcap \tup{b}) + f(\tup{a} \sqcup \tup{b}) \leq f(\tup{a}) + f(\tup{b})$ for all $\tup{a}, \tup{b} \in L^n$. In this paper we study submodular functions when $L$ is a diamond. Given oracle access to $f$ we are interested in finding $\tup{x} \in L^n$ such that $f(\tup{x}) = \min_{\tup{y} \in L^n} f(\tup{y})$ as efficiently as possible. We establish a min--max theorem, which states that the minimum of the submodular function is equal to the maximum of a certain function defined over a certain polyhedron; and a good characterisation of the minimisation problem, i.e., we show that given an oracle for computing a submodular $f : L^n \to \mathbb{Z}$ and an integer $m$ such that $\min_{\tup{x} \in L^n} f(\tup{x}) = m$, there is a proof of this fact which can be verified in time polynomial in $n$ and $\max_{\tup{t} \in L^n} \log |f(\tup{t})|$; and a pseudo-polynomial time algorithm for the minimisation problem, i.e., given an oracle for computing a submodular $f : L^n \to \mathbb{Z}$ one can find $\min_{\tup{t} \in L^n} f(\tup{t})$ in time bounded by a polynomial in $n$ and $\max_{\tup{t} \in L^n} |f(\tup{t})|$.


Measurement of eDonkey Activity with Distributed Honeypots

Abstract: Collecting information about user activity in peer-to-peer systems is a key but challenging task. We describe here a distributed platform for doing so on the eDonkey network, relying on a group of honeypot peers which claim to have certain files and log queries they receive for these files. We then conduct some measurements with typical scenarios and use the obtained data to analyze the impact of key parameters like measurement duration, number of honeypots involved, and number of advertised files. This illustrates both the possible uses of our measurement system, and the kind of data one may collect using it.


Efficient Measurement of Complex Networks Using Link Queries

Abstract: Complex networks are at the core of an intense research activity. However, in most cases, intricate and costly measurement procedures are needed to explore their structure. In some cases, these measurements rely on link queries: given two nodes, it is possible to test the existence of a link between them. These tests may be costly, and thus minimizing their number while maximizing the number of discovered links is a key issue. This paper studies this problem: we observe that properties classically observed on real-world complex networks give hints for their efficient measurement; we derive simple principles and several measurement strategies based on this, and experimentally evaluate their efficiency on real-world cases. In order to do so, we introduce methods to evaluate the efficiency of strategies. We also explore the bias that different measurement strategies may induce.


The Business of Selling Electronic Documents

Abstract: The music industry has huge troubles adapting to the new technologies. As many pointed out, when copying music is essentially free and socially accepted it becomes increasingly tempting for users to infringe copyrights and copy music from one person to another. The answer of the music industry is to outlaw a majority of citizens. This article describes how the music industry should reinvent itself and adapt to a world where the network is ubiquitous and exchanging information is essentially free. It relies on adapting prices to the demand and lower costs of electronic documents in a dramatic way.


On evaluation of permanents

Abstract: We study the time and space complexity of matrix permanents over rings and semirings.


FastLMFI: An Efficient Approach for Local Maximal Patterns Propagation and Maximal Patterns Superset Checking

Abstract: Maximal frequent patterns superset checking plays an important role in the efficient mining of complete Maximal Frequent Itemsets (MFI) and maximal search space pruning. In this paper we present a new indexing approach, FastLMFI for local maximal frequent patterns (itemset) propagation and maximal patterns superset checking. Experimental results on different sparse and dense datasets show that our work is better than the previous well known progressive focusing technique. We have also integrated our superset checking approach with an existing state of the art maximal itemsets algorithm Mafia, and compare our results with current best maximal itemsets algorithms afopt-max and FP (zhu)-max. Our results outperform afopt-max and FP (zhu)-max on dense (chess and mushroom) datasets on almost all support thresholds, which shows the effectiveness of our approach.


HybridMiner: Mining Maximal Frequent Itemsets Using Hybrid Database Representation Approach

Abstract: In this paper we present a novel hybrid (arraybased layout and vertical bitmap layout) database representation approach for mining complete Maximal Frequent Itemset (MFI) on sparse and large datasets. Our work is novel in terms of scalability, item search order and two horizontal and vertical projection techniques. We also present a maximal algorithm using this hybrid database representation approach. Different experimental results on real and sparse benchmark datasets show that our approach is better than previous state of art maximal algorithms.


Ramp: Fast Frequent Itemset Mining with Efficient Bit-Vector Projection Technique

Abstract: Mining frequent itemset using bit-vector representation approach is very efficient for dense type datasets, but highly inefficient for sparse datasets due to lack of any efficient bit-vector projection technique. In this paper we present a novel efficient bit-vector projection technique, for sparse and dense datasets. To check the efficiency of our bit-vector projection technique, we present a new frequent itemset mining algorithm Ramp (Real Algorithm for Mining Patterns) build upon our bit-vector projection technique. The performance of the Ramp is compared with the current best (all, maximal and closed) frequent itemset mining algorithms on benchmark datasets. Different experimental results on sparse and dense datasets show that mining frequent itemset using Ramp is faster than the current best algorithms, which show the effectiveness of our bit-vector projection idea. We also present a new local maximal frequent itemsets propagation and maximal itemset superset checking approach FastLMFI, build upon our PBR bit-vector projection technique. Our different computational experiments suggest that itemset maximality checking using FastLMFI is fast and efficient than a previous will known progressive focusing approach.


Fast Algorithms for Mining Interesting Frequent Itemsets without Minimum Support

Abstract: Real world datasets are sparse, dirty and contain hundreds of items. In such situations, discovering interesting rules (results) using traditional frequent itemset mining approach by specifying a user defined input support threshold is not appropriate. Since without any domain knowledge, setting support threshold small or large can output nothing or a large number of redundant uninteresting results. Recently a novel approach of mining only N-most/Top-K interesting frequent itemsets has been proposed, which discovers the top N interesting results without specifying any user defined support threshold. However, mining interesting frequent itemsets without minimum support threshold are more costly in terms of itemset search space exploration and processing cost. Thereby, the efficiency of their mining highly depends upon three main factors (1) Database representation approach used for itemset frequency counting, (2) Projection of relevant transactions to lower level nodes of search space and (3) Algorithm implementation technique. Therefore, to improve the efficiency of mining process, in this paper we present two novel algorithms called (N-MostMiner and Top-K-Miner) using the bit-vector representation approach which is very efficient in terms of itemset frequency counting and transactions projection. In addition to this, several efficient implementation techniques of N-MostMiner and Top-K-Miner are also present which we experienced in our implementation. Our experimental results on benchmark datasets suggest that the NMostMiner and Top-K-Miner are very efficient in terms of processing time as compared to current best algorithms BOMO and TFP.


Using Association Rules for Better Treatment of Missing Values

Abstract: The quality of training data for knowledge discovery in databases (KDD) and data mining depends upon many factors, but handling missing values is considered to be a crucial factor in overall data quality. Today real world datasets contains missing values due to human, operational error, hardware malfunctioning and many other factors. The quality of knowledge extracted, learning and decision problems depend directly upon the quality of training data. By considering the importance of handling missing values in KDD and data mining tasks, in this paper we propose a novel Hybrid Missing values Imputation Technique (HMiT) using association rules mining and hybrid combination of k-nearest neighbor approach. To check the effectiveness of our HMiT missing values imputation technique, we also perform detail experimental results on real world datasets. Our results suggest that the HMiT technique is not only better in term of accuracy but it also take less processing time as compared to current best missing values imputation technique based on k-nearest neighbor approach, which shows the effectiveness of our missing values imputation technique.


Introducing Partial Matching Approach in Association Rules for Better Treatment of Missing Values

Abstract: Handling missing values in training datasets for constructing learning models or extracting useful information is considered to be an important research task in data mining and knowledge discovery in databases. In recent years, lot of techniques are proposed for imputing missing values by considering attribute relationships with missing value observation and other observations of training dataset. The main deficiency of such techniques is that, they depend upon single approach and do not combine multiple approaches, that why they are less accurate. To improve the accuracy of missing values imputation, in this paper we introduce a novel partial matching concept in association rules mining, which shows better results as compared to full matching concept that we described in our previous work. Our imputation technique combines the partial matching concept in association rules with k-nearest neighbor approach. Since this is a hybrid technique, therefore its accuracy is much better than as compared to those techniques which depend upon single approach. To check the efficiency of our technique, we also provide detail experimental results on number of benchmark datasets which show better results as compared to previous approaches.


Decision Problems for Nash Equilibria in Stochastic Games

Abstract: We analyse the computational complexity of finding Nash equilibria in stochastic multiplayer games with $\omega$-regular objectives. While the existence of an equilibrium whose payoff falls into a certain interval may be undecidable, we single out several decidable restrictions of the problem. First, restricting the search space to stationary, or pure stationary, equilibria results in problems that are typically contained in PSPACE and NP, respectively. Second, we show that the existence of an equilibrium with a binary payoff (i.e. an equilibrium where each player either wins or loses with probability 1) is decidable. We also establish that the existence of a Nash equilibrium with a certain binary payoff entails the existence of an equilibrium with the same payoff in pure, finite-state strategies.


Optimistic Initialization and Greediness Lead to Polynomial Time Learning in Factored MDPs - Extended Version

Abstract: In this paper we propose an algorithm for polynomial-time reinforcement learning in factored Markov decision processes (FMDPs). The factored optimistic initial model (FOIM) algorithm, maintains an empirical model of the FMDP in a conventional way, and always follows a greedy policy with respect to its model. The only trick of the algorithm is that the model is initialized optimistically. We prove that with suitable initialization (i) FOIM converges to the fixed point of approximate value iteration (AVI); (ii) the number of steps when the agent makes non-near-optimal decisions (with respect to the solution of AVI) is polynomial in all relevant quantities; (iii) the per-step costs of the algorithm are also polynomial. To our best knowledge, FOIM is the first algorithm with these properties. This extended version contains the rigorous proofs of the main theorem. A version of this paper appeared in ICML'09.


State complexity of orthogonal catenation

Abstract: A language $L$ is the orthogonal catenation of languages $L_1$ and $L_2$ if every word of $L$ can be written in a unique way as a catenation of a word in $L_1$ and a word in $L_2$. We establish a tight bound for the state complexity of orthogonal catenation of regular languages. The bound is smaller than the bound for arbitrary catenation.


Identity Based Strong Designated Verifier Parallel Multi-Proxy Signature Scheme

Abstract: This paper presents a new identity based strong designated verifier parallel multi-proxy signature scheme. Multi-Proxy signatures allow the original signer to delegate his signing power to a group of proxy signers. In our scheme, the designated verifier can only validate proxy signatures created by a group of proxy signer.


Some Proxy Signature and Designated verifier Signature Schemes over Braid Groups

Abstract: Braids groups provide an alternative to number theoretic public cryptography and can be implemented quite efficiently. The paper proposes five signature schemes: Proxy Signature, Designated Verifier, Bi-Designated Verifier, Designated Verifier Proxy Signature And Bi-Designated Verifier Proxy Signature scheme based on braid groups. We also discuss the security aspects of each of the proposed schemes.


JConstHide: A Framework for Java Source Code Constant Hiding

Abstract: Software obfuscation or obscuring a software is an approach to defeat the practice of reverse engineering a software for using its functionality illegally in the development of another software. Java applications are more amenable to reverse engineering and re-engineering attacks through methods such as decompilation because Java class files store the program in a semi complied form called byte codes. The existing obfuscation systems obfuscate the Java class files. Obfuscated source code produce obfuscated byte codes and hence two level obfuscation (source code and byte code level) of the program makes it more resilient to reverse engineering attacks . But source code obfuscation is much more difficult due to richer set of programming constructs and the scope of the different variables used in the program and only very little progress has been made on this front. We in this paper are proposing a framework named JConstHide for hiding constants, especially integers in the java source codes, to defeat reverse engineering through decompilation. To the best of our knowledge, no data hiding software are available for java source code constant hiding.


Incentive Compatible Budget Elicitation in Multi-unit Auctions

Abstract: In this paper, we consider the problem of designing incentive compatible auctions for multiple (homogeneous) units of a good, when bidders have private valuations and private budget constraints. When only the valuations are private and the budgets are public, Dobzinski {\em et al} show that the {\em adaptive clinching} auction is the unique incentive-compatible auction achieving Pareto-optimality. They further show thatthere is no deterministic Pareto-optimal auction with private budgets. Our main contribution is to show the following Budget Monotonicity property of this auction: When there is only one infinitely divisible good, a bidder cannot improve her utility by reporting a budget smaller than the truth. This implies that a randomized modification to the adaptive clinching auction is incentive compatible and Pareto-optimal with private budgets. The Budget Monotonicity property also implies other improved results in this context. For revenue maximization, the same auction improves the best-known competitive ratio due to Abrams by a factor of 4, and asymptotically approaches the performance of the optimal single-price auction. Finally, we consider the problem of revenue maximization (or social welfare) in a Bayesian setting. We allow the bidders have public size constraints (on the amount of good they are willing to buy) in addition to private budget constraints. We show a simple poly-time computable 5.83-approximation to the optimal Bayesian incentive compatible mechanism, that is implementable in dominant strategies. Our technique again crucially needs the ability to prevent bidders from over-reporting budgets via randomization.


On the Complexity of Searching in Trees: Average-case Minimization

Abstract: We focus on the average-case analysis: A function w : V -> Z+ is given which defines the likelihood for a node to be the one marked, and we want the strategy that minimizes the expected number of queries. Prior to this paper, very little was known about this natural question and the complexity of the problem had remained so far an open question. We close this question and prove that the above tree search problem is NP-complete even for the class of trees with diameter at most 4. This results in a complete characterization of the complexity of the problem with respect to the diameter size. In fact, for diameter not larger than 3 the problem can be shown to be polynomially solvable using a dynamic programming approach. In addition we prove that the problem is NP-complete even for the class of trees of maximum degree at most 16. To the best of our knowledge, the only known result in this direction is that the tree search problem is solvable in O(|V| log|V|) time for trees with degree at most 2 (paths). We match the above complexity results with a tight algorithmic analysis. We first show that a natural greedy algorithm attains a 2-approximation. Furthermore, for the bounded degree instances, we show that any optimal strategy (i.e., one that minimizes the expected number of queries) performs at most O(\Delta(T) (log |V| + log w(T))) queries in the worst case, where w(T) is the sum of the likelihoods of the nodes of T and \Delta(T) is the maximum degree of T. We combine this result with a non-trivial exponential time algorithm to provide an FPTAS for trees with bounded degree.


On using floating-point computations to help an exact linear arithmetic decision procedure

Abstract: We consider the decision problem for quantifier-free formulas whose atoms are linear inequalities interpreted over the reals or rationals. This problem may be decided using satisfiability modulo theory (SMT), using a mixture of a SAT solver and a simplex-based decision procedure for conjunctions. State-of-the-art SMT solvers use simplex implementations over rational numbers, which perform well for typical problems arising from model-checking and program analysis (sparse inequalities, small coefficients) but are slow for other applications (denser problems, larger coefficients). We propose a simple preprocessing phase that can be adapted on existing SMT solvers and that may be optionally triggered. Despite using floating-point computations, our method is sound and complete - it merely affects efficiency. We implemented the method and provide benchmarks showing that this change brings a naive and slow decision procedure ("textbook simplex" with rational numbers) up to the efficiency of recent SMT solvers, over test cases arising from model-checking, and makes it definitely faster than state-of-the-art SMT solvers on dense examples.


Deconstruction of Infinite Extensive Games using coinduction

Abstract: Finite objects and more specifically finite games are formalized using induction, whereas infinite objects are formalized using coinduction. In this article, after an introduction to the concept of coinduction, we revisit on infinite (discrete) extensive games the basic notions of game theory. Among others, we introduce a definition of Nash equilibrium and a notion of subgame perfect equilibrium for infinite games. We use those concepts to analyze well known infinite games, like the dollar auction game and the centipede game and we show that human behaviors that are often considered as illogic are perfectly rational, if one admits that human agents reason coinductively.


Internet: Romania vs. Europe

Abstract: This paper presents various access ways to Internet for home users, both for those who are low consumers (consumed time online or traffic monthly value), or large consumers (unlimited connection). The main purpose of the work consists in making a comparison between the situation of the Internet in Romania and other countries in Europe such as Hungary (more western than Romania, so a little more developed, still an Eastern country comparing to the more developed countries in Western Europe and others well developed such as England, Italy, France, and to those in development such as Poland, and at the periphery of Europe such as Ukraine.


Termination of Linear Programs with Nonlinear Constraints

Abstract: Tiwari proved that termination of linear programs (loops with linear loop conditions and updates) over the reals is decidable through Jordan forms and eigenvectors computation. Braverman proved that it is also decidable over the integers. In this paper, we consider the termination of loops with polynomial loop conditions and linear updates over the reals and integers. First, we prove that the termination of such loops over the integers is undecidable. Second, with an assumption, we provide an complete algorithm to decide the termination of a class of such programs over the reals. Our method is similar to that of Tiwari in spirit but uses different techniques. Finally, we conjecture that the termination of linear programs with polynomial loop conditions over the reals is undecidable in general by %constructing a loop and reducing the problem to another decision problem related to number theory and ergodic theory, which we guess undecidable.


VRAC: Virtual Raw Anchor Coordinates Routing in Sensor Networks -- Concepts and Experimental Protocol

Abstract: In order to make full use of geographic routing techniques developed for large scale networks, nodes must be localized. However, localization and virtual localization techniques in sensor networks are dependent either on expensive and sometimes unavailable hardware (e.g. GPS) or on sophisticated localization calculus (e.g. triangulation) which are both error-prone and with a costly overhead. Instead of localizing nodes in a traditional 2-dimensional space, we intend to use directly the raw distance to a set of anchors to route messages in the multi-dimensional space. This should enable us to use any geographic routing protocol in a robust and efficient manner in a very large range of scenarios.


Variations of the Turing Test in the Age of Internet and Virtual Reality

Abstract: Inspired by Hofstadter's Coffee-House Conversation (1982) and by the science fiction short story SAM by Schattschneider (1988), we propose and discuss criteria for non-mechanical intelligence. Firstly, we emphasize the practical need for such tests in view of massively multiuser online role-playing games (MMORPGs) and virtual reality systems like Second Life. Secondly, we demonstrate Second Life as a useful framework for implementing (some iterations of) that test.


Les technologies de l'information et de la communication au niveau mondial et en Roumanie dans les dernieres annees

Abstract: The level of development of the electronic communication market and of the information technology, the indicators regarding the penetration of Internet and the level of penetration of the connections in wide band, the integration degree of the Tic application in the business area are crucial for the development of an informational society and for the creation of a society based on knowledge. Though the levels are still reduced their positive evolution reflects the attenuation of the gaps by Romania, comparatively to other countries.


On the Ambiguity of Commercial Open Source

Abstract: Open source and commercial applications used to be two separate worlds. The former was the work of amateurs who had little interest in making a profit, while the latter was only profit oriented and was produced by big companies. Nowadays open source is a threat and an opportunity to serious businesses of all kinds, generating good profits while delivering low costs products to customers. The competition between commercial and open source software has impacted the industry and the society as a whole. But in the last years, the markets for commercial and open source software are converging rapidly and it is interesting to resume and discuss the implications of this new paradigm, taking into account arguments pro and against it.


Business Process Modeling Notation - An Overview

Abstract: BPMN represents an industrial standard created to offer a common and user friendly notation to all the participants to a business process. The present paper aims to briefly present the main features of this notation as well as an interpretation of some of the main patterns characterizing a business process modeled by the working fluxes.


Tailored business solutions by workflow technologies

Abstract: VISP (Virtual Internet Service Provider) is an IST-STREP project, which is conducting research in the field of these new technologies, targeted to telecom/ISP companies. One of the first tasks of the VISP project is to identify the most appropriate technologies in order to construct the VISP platform. This paper presents the most significant results in the field of choreography and orchestration, two key domains that must accompany process modeling in the construction of a workflow environment.


On one method of boundary value problem regularization by passage to the limit

Abstract: For one class of boundary value problem depending on small parameter for which numerical methods for their solution are actually inapplicable, procedure of limiting problem acquisition which is much easier and which solution as much as close to the initial solution is described.


Computer Aided Optimization of the Unconventional Processing

Abstract: The unconventional technologies, currently applied at a certain category of materials, difficult to be processed through usual techniques, have undergone during the last 60 years all the stages, since their discovery to their use on a large scale. They are based on elementary mechanisms which run the processing through classic methods, yet, they use in addition the interconnections of these methods. This leads to a plus in performance by increasing the outcomes precision, reducing the processing time, increasing the quality of the finite product, etc. This performance can be much increased by using the computer and a software product in assisting the human operator in the processing by an unconventional method such as; the electric or electro-chemical erosion, the complex electric-electro-chemical erosion, the processing by a laser fascicle and so on. The present work presents such an application based on a data base combining the previous experimental results, which proposes a method of optimization of the outcomes.


The use of invariant moments in hand-written character recognition

Abstract: The goal of this paper is to present the implementation of a Radial Basis Function neural network with built-in knowledge to recognize hand-written characters. The neural network includes in its architecture gates controlled by an attraction/repulsion system of coefficients. These coefficients are derived from a preprocessing stage which groups the characters according to their ascendant, central, or descendent components. The neural network is trained using data from invariant moment functions. Results are compared with those obtained using a K nearest neighbor method on the same moment data.


Introduction to Machine Learning: Class Notes 67577

Abstract: Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).


Considerations upon the Machine Learning Technologies

Abstract: Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to "learn". Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.


Collaborative systems and multiagent systems

Abstract: This paper presents some basic elements regarding the domain of the collaborative systems, a domain of maximum actuality and also the multiagent systems, developed as a result of a sound study on the one-agent systems.


Quantum theory can be collectively verified

Abstract: No theory of physics has been collectively scientifically verified in an experiment so far. It is pointed out that probabilistic structure of quantum theory can be collectively scientifically verified in an experiment. It is also argued that experimentalist point of view quantum theory is a complete theory.


The Multimedia Product - between Design and Information, Design and Utility and Design and Entertainment

Abstract: The paper investigates the possible coherent and effective alternatives to solve the problems related to the communication needs of any multimedia product. In essence, the presentation will focus on identifying the issues and principles governing three types of the design - in fact, the multimedia design in a broader sense - namely the information design - precisely aiming at ways of organization and presentation of information in a useful and significant form, the graphical user interface design, whose sub-domain consists of the information displayed on the monitor screen and of interactivity between user, computer and electronic devices, meaning, in fact, everything the user sees, touches, hears and all the elements with which he interacts, the graphic design, whose main concern is to create an aesthetic layout arrangement (from the visual and perceptive) information.


The new multimedia educational technologies, used in open and distance learning

Abstract: This paper reviews and refers to the latest telematics technology that has turned the open system learning and helped it to become an institutional alternative to the face-to-face traditional one. Most technologies, briefly presented here, will be implemented in the "ARTeFACt" project - telematic system for vocational education system of open system learning, system which will be officially launched at the end of 2006, in the institutional offer of the Faculty of Arts of the University West of Timisoara. The scientific coordination of the doctoral project "ARTeFACt" is done by Mr. Prof. Dr. Eng. Savi G. George, representing the Department of Mechatronics Faculty of Mechanical Engineering from the University "Politehnica" of Timisoara, Romania


Semantic Linkage of Control Systems

Abstract: Control systems are sets of interconnected hardware and software components which regulate the behaviour of processes. The software of modern control systems rises for some years by requirements regarding the flexibility and functionality. Thus the force of innovation grows on enterprises, since ever newer products in ever shorter time intervals must be made available. Associated hereby is the crucial shortening of the product life cycle, whose effects show up in reduced care of the software and the spares inventory. The aim, the concept presented here and developed in a modeling environment, is proved and ensures a minimum functionality of software components. Replacing software components of a control system verified for functionality by a framework at run-time and if necessary the software conditions will become adapted. Quintessential point of this implementation is the usage of an abstract syntax tree. Within its hierarchical structure meta information is attached to nodes and processed by the framework. With the development of the concept for semantic proving of software components the lifetime of software-based products is increased.


Semantic Social Network Analysis

Abstract: Social Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merge and exploit the best features of each domain. We present how to facilitate and enhance the analysis of online social networks, exploiting the power of semantic social network analysis.


Output Width Signal Control In Asynchronous Digital Systems Using External Clock Signal

Abstract: In present paper, I propose a method for resolving the timing delays for output signals from an asynchronous sequential system. It will be used an example of an asynchronous sequential system that will set up an output signal when an input signal will be set up. The width of the output signal depends on the input signal width, and in this case it is very short. There are many synthesis methods, like using a RC group system, a monostable system in design of the asynchronous digital system or using an external clock signal, CK. In this paper will be used an external clock signal, CK.


Output Width Signal Control In Asynchronous Digital Systems Using Monostable Circuits

Abstract: In present paper, I propose a method for resolving the timing delays for output signals from an asynchronous sequential system. It will be used an example of an asynchronous sequential system that will set up an output signal when an input signal will be set up. The width of the output signal depends on the input signal width, and in this case it is very short. There are many synthesis methods, like using a RC group system, a monostable system in design of the asynchronous digital system or using an external clock signal, CK. In this paper will be used a monostable circuit.


Mesh

Abstract: Whether you just want to take a peek of a remote computer status, or you want to install the latest version of a software on several workstations, you can do all of this from your computer. The networks are growing, the time spent administering the workstations increases and the number of repetitive tasks is going sky high. But here comes MESH to take that load off your shoulders. And because of SMS commands you can take this "command center" wherever you will go. Just connect a GSM phone to the computer (using a cable, IrDA or Bluetooth) and lock/restart/shutdown computers from your LAN with the push of a cell phone button. You can even create your own SMS commands. This is MESH - the network administrator's Swiss knife


Failover of Software Services with State Replication

Abstract: Computing systems are becoming more and more complex and assuming more and more responsibilities in all sectors of human activity. Applications do not run locally on a single computer any more. A lot of today's applications are built as distributed system; with services on different computers communicating with each other. Distributed systems arise everywhere. The Internet is one of the best-known distributed systems and used by nearly everyone today. It is obvious that we are more and more dependent on computer services. Many people expect to be able to buy things like clothing or electronic equipment even at night on the Internet. Computers are expected to be operational and available 7 days a week, 24 hours a day. Downtime, even for maintenance, is no longer acceptable.


Architecture of the Neurath Basic Model View Controller

Abstract: The idea of the Neurath Basic Model View Controller (NBMVC) appeared during the discussion of the design of domain-specific modeling tools based on the Neurath Modeling Language [Yer06]. The NBMVC is the core of the modeling process within the modeling environment. It reduces complexity out of the design process by providing domain-specific interfaces between the developer and the model. These interfaces help to organize and manipulate the model. The organization includes, for example, a layer with visual components to drop them in and filter them out. The control routines includes, for example, model transformations.


The h-Index of a Graph and its Application to Dynamic Subgraph Statistics

Abstract: We describe a data structure that maintains the number of triangles in a dynamic undirected graph, subject to insertions and deletions of edges and of degree-zero vertices. More generally it can be used to maintain the number of copies of each possible three-vertex subgraph in time O(h) per update, where h is the h-index of the graph, the maximum number such that the graph contains $h$ vertices of degree at least h. We also show how to maintain the h-index itself, and a collection of h high-degree vertices in the graph, in constant time per update. Our data structure has applications in social network analysis using the exponential random graph model (ERGM); its bound of O(h) time per edge is never worse than the Theta(sqrt m) time per edge necessary to list all triangles in a static graph, and is strictly better for graphs obeying a power law degree distribution. In order to better understand the behavior of the h-index statistic and its implications for the performance of our algorithms, we also study the behavior of the h-index on a set of 136 real-world networks.


On the Approximability of Geometric and Geographic Generalization and the Min-Max Bin Covering Problem

Abstract: We study the problem of abstracting a table of data about individuals so that no selection query can identify fewer than k individuals. We show that it is impossible to achieve arbitrarily good polynomial-time approximations for a number of natural variations of the generalization technique, unless P = NP, even when the table has only a single quasi-identifying attribute that represents a geographic or unordered attribute: Zip-codes: nodes of a planar graph generalized into connected subgraphs GPS coordinates: points in R2 generalized into non-overlapping rectangles Unordered data: text labels that can be grouped arbitrarily. In addition to impossibility results, we provide approximation algorithms for these difficult single-attribute generalization problems, which, of course, apply to multiple-attribute instances with one that is quasi-identifying. We show theoretically and experimentally that our approximation algorithms can come reasonably close to optimal solutions. Incidentally, the generalization problem for unordered data can be viewed as a novel type of bin packing problem--min-max bin covering--which may be of independent interest.


Approximate Triangle Counting

Abstract: Triangle counting is an important problem in graph mining. Clustering coefficients of vertices and the transitivity ratio of the graph are two metrics often used in complex network analysis. Furthermore, triangles have been used successfully in several real-world applications. However, exact triangle counting is an expensive computation. In this paper we present the analysis of a practical sampling algorithm for counting triangles in graphs. Our analysis yields optimal values for the sampling rate, thus resulting in tremendous speedups ranging from \emph{2800}x to \emph{70000}x when applied to real-world networks. At the same time the accuracy of the estimation is excellent. Our contributions include experimentation on graphs with several millions of nodes and edges, where we show how practical our proposed method is. Finally, our algorithm's implementation is a part of the \pegasus library (Code and datasets are available at (http://www.cs.cmu.edu/~ctsourak/).) a Peta-Graph Mining library implemented in Hadoop, the open source version of Mapreduce.


Formally Specifying and Proving Operational Aspects of Forensic Lucid in Isabelle

Abstract: A Forensic Lucid intensional programming language has been proposed for intensional cyberforensic analysis. In large part, the language is based on various predecessor and codecessor Lucid dialects bound by the higher-order intensional logic (HOIL) that is behind them. This work formally specifies the operational aspects of the Forensic Lucid language and compiles a theory of its constructs using Isabelle, a proof assistant system.


Internet Traffic Periodicities and Oscillations: A Brief Review

Abstract: Internet traffic displays many persistent periodicities (oscillations) on a large range of time scales. This paper describes the measurement methodology to detect Internet traffic periodicities and also describes the main periodicities in Internet traffic.


Automated Epilepsy Diagnosis Using Interictal Scalp EEG

Abstract: Approximately over 50 million people worldwide suffer from epilepsy. Traditional diagnosis of epilepsy relies on tedious visual screening by highly trained clinicians from lengthy EEG recording that contains the presence of seizure (ictal) activities. Nowadays, there are many automatic systems that can recognize seizure-related EEG signals to help the diagnosis. However, it is very costly and inconvenient to obtain long-term EEG data with seizure activities, especially in areas short of medical resources. We demonstrate in this paper that we can use the interictal scalp EEG data, which is much easier to collect than the ictal data, to automatically diagnose whether a person is epileptic. In our automated EEG recognition system, we extract three classes of features from the EEG data and build Probabilistic Neural Networks (PNNs) fed with these features. We optimize the feature extraction parameters and combine these PNNs through a voting mechanism. As a result, our system achieves an impressive 94.07% accuracy, which is very close to reported human recognition accuracy by experienced medical professionals.


La R\'esolvante de Lagrange et ses Applications

Abstract: In this paper, the changes of representations of a group are used in order to describe its action as algebraic Galois group of an univariate polynomial on the roots of factors of any Lagrange resolvent. By this way, the Galois group of resolvent factors are pre-determinated. In follows, different applications are exposed; in particular, some classical results of algebraic Galois theory.


On Smoothed Analysis of Quicksort and Hoare's Find

Abstract: We provide a smoothed analysis of Hoare's find algorithm and we revisit the smoothed analysis of quicksort. Hoare's find algorithm - often called quickselect - is an easy-to-implement algorithm for finding the k-th smallest element of a sequence. While the worst-case number of comparisons that Hoare's find needs is quadratic, the average-case number is linear. We analyze what happens between these two extremes by providing a smoothed analysis of the algorithm in terms of two different perturbation models: additive noise and partial permutations. Moreover, we provide lower bounds for the smoothed number of comparisons of quicksort and Hoare's find for the median-of-three pivot rule, which usually yields faster algorithms than always selecting the first element: The pivot is the median of the first, middle, and last element of the sequence. We show that median-of-three does not yield a significant improvement over the classic rule: the lower bounds for the classic rule carry over to median-of-three.


Refutation of Aslam's Proof that NP = P

Abstract: Aslam presents an algorithm he claims will count the number of perfect matchings in any incomplete bipartite graph with an algorithm in the function-computing version of NC, which is itself a subset of FP. Counting perfect matchings is known to be #P-complete; therefore if Aslam's algorithm is correct, then NP=P. However, we show that Aslam's algorithm does not correctly count the number of perfect matchings and offer an incomplete bipartite graph as a concrete counter-example.


A Critique of "Solving the P/NP Problem Under Intrinsic Uncertainty", arXiv:0811.0463

Abstract: Although whether P equals NP is an important, open problem in computer science, and although Jaeger's 2008 paper, "Solving the P/NP Problem Under Intrinsic Uncertainty" (arXiv:0811.0463) presents an attempt at tackling the problem by discussing the possibility that all computation is uncertain to some degree, there are a number of logical oversights present in that paper which preclude it from serious consideration toward having resolved P-versus-NP. There are several differences between the model of computation presented in Jaeger's paper and the standard model, as well as several bold assumptions that are not well supported in Jaeger's paper or in the literature. In addition, we find several omissions of rigorous proof that ultimately weaken this paper to a point where it cannot be considered a candidate solution to the P-versus-NP problem.


Representating groups on graphs

Abstract: In this paper we formulate and study the problem of representing groups on graphs. We show that with respect to polynomial time turing reducibility, both abelian and solvable group representability are all equivalent to graph isomorphism, even when the group is presented as a permutation group via generators. On the other hand, the representability problem for general groups on trees is equivalent to checking, given a group $G$ and $n$, whether a nontrivial homomorphism from $G$ to $S_n$ exists. There does not seem to be a polynomial time algorithm for this problem, in spite of the fact that tree isomorphism has polynomial time algorithm.


Better Global Polynomial Approximation for Image Rectification

Abstract: When using images to locate objects, there is the problem of correcting for distortion and misalignment in the images. An elegant way of solving this problem is to generate an error correcting function that maps points in an image to their corrected locations. We generate such a function by fitting a polynomial to a set of sample points. The objective is to identify a polynomial that passes "sufficiently close" to these points with "good" approximation of intermediate points. In the past, it has been difficult to achieve good global polynomial approximation using only sample points. We report on the development of a global polynomial approximation algorithm for solving this problem. Key Words: Polynomial approximation, interpolation, image rectification.


Guarded resolution for answer set programming

Abstract: We describe a variant of resolution rule of proof and show that it is complete for stable semantics of logic programs. We show applications of this result.


Successive Difference Substitution Based on Column Stochastic Matrix and Mechanical Decision for Positive Semi-definite Forms

Abstract: The theory part of this paper is sketched as follows. Based on column stochastic average matrix $T_n$ selected as a basic substitution matrix, the method of advanced successive difference substitution is established. Then, a set of necessary and sufficient conditions for deciding positive semi-definite form on $\R^n_+$ is derived from this method. And furthermore, it is proved that the sequence of SDS sets of a positive definite form is positively terminating. Worked out according to these results, the Maple program TSDS3 not only automatically proves the polynomial inequalities, but also outputs counter examples for the false. Sometimes TSDS3 does not halt, but it is very useful by experimenting on so many examples.


Content-Based Sub-Image Retrieval with Relevance Feedback

Abstract: The typical content-based image retrieval problem is to find images within a database that are similar to a given query image. This paper presents a solution to a different problem, namely that of content based sub-image retrieval, i.e., finding images from a database that contains another image. Note that this is different from finding a region in a (segmented) image that is similar to another image region given as a query. We present a technique for CBsIR that explores relevance feedback, i.e., the user's input on intermediary results, in order to improve retrieval efficiency. Upon modeling images as a set of overlapping and recursive tiles, we use a tile re-weighting scheme that assigns penalties to each tile of the database images and updates the tile penalties for all relevant images retrieved at each iteration using both the relevant and irrelevant images identified by the user. Each tile is modeled by means of its color content using a compact but very efficient method which can, indirectly, capture some notion of texture as well, despite the fact that only color information is maintained. Performance evaluation on a largely heterogeneous dataset of over 10,000 images shows that the system can achieve a stable average recall value of 70% within the top 20 retrieved (and presented) images after only 5 iterations, with each such iteration taking about 2 seconds on an off-the-shelf desktop computer.


Un protocole de routage \`a basse consommation d'\'energie pour les MANETs

Abstract: Maximizing network lifetime is a very challenging issue in routing protocol design for Mobile Ad-hoc NETworks (MANETs), since mobile nodes are powered by limited-capacity batteries. Furthermore, replacing or recharging batteries is often impossible in critical environments (e.g. battlefields, disaster areas, etc.). Energy consumption was considered for a long time equivalent to bandwidth consumption. However, recent works have shown that "energy" and "bandwidth" are substantially different metrics. Moreover, it was found that traditional routing policies such as "the shortest path" one can have a negative impact on energy consumption balance. Therefore, several new approaches have been proposed addressing energy efficiency explicitly. Our work is related to energy efficient routing for MANETs' problem. The proposed MEA-DSR (Multipath Energy-Aware on Demand Source Routing) protocol is based on a load sharing strategy between mobile nodes in order to maximize network lifetime. To achieve this goal, we used multipath routing; nodes' residual energies and paths length were also considered when making routing decisions. Simulation results have shown the efficiency of the proposed protocol under difficult scenarios characterised by high mobility, high density and important traffic load.


Security impact ratings considered harmful

Abstract: In this paper, we question the common practice of assigning security impact ratings to OS updates. Specifically, we present evidence that ranking updates by their perceived security importance, in order to defer applying some updates, exposes systems to significant risk. We argue that OS vendors and security groups should not focus on security updates to the detriment of other updates, but should instead seek update technologies that make it feasible to distribute updates for all disclosed OS bugs in a timely manner.


Approximation Algorithms for Key Management in Secure Multicast

Abstract: Many data dissemination and publish-subscribe systems that guarantee the privacy and authenticity of the participants rely on symmetric key cryptography. An important problem in such a system is to maintain the shared group key as the group membership changes. We consider the problem of determining a key hierarchy that minimizes the average communication cost of an update, given update frequencies of the group members and an edge-weighted undirected graph that captures routing costs. We first present a polynomial-time approximation scheme for minimizing the average number of multicast messages needed for an update. We next show that when routing costs are considered, the problem is NP-hard even when the underlying routing network is a tree network or even when every group member has the same update frequency. Our main result is a polynomial time constant-factor approximation algorithm for the general case where the routing network is an arbitrary weighted graph and group members have nonuniform update frequencies.


Two-Way Unary Temporal Logic over Trees

Abstract: We consider a temporal logic EF+F^-1 for unranked, unordered finite trees. The logic has two operators: EF\phi, which says "in some proper descendant \phi holds", and F^-1\phi, which says "in some proper ancestor \phi holds". We present an algorithm for deciding if a regular language of unranked finite trees can be expressed in EF+F^-1. The algorithm uses a characterization expressed in terms of forest algebras.


On Constructor Rewrite Systems and the Lambda-Calculus (Long Version)

Abstract: We prove that orthogonal constructor term rewrite systems and lambda-calculus with weak (i.e., no reduction is allowed under the scope of a lambda-abstraction) call-by-value reduction can simulate each other with a linear overhead. In particular, weak call-by-value beta-reduction can be simulated by an orthogonal constructor term rewrite system in the same number of reduction steps. Conversely, each reduction in a term rewrite system can be simulated by a constant number of beta-reduction steps. This is relevant to implicit computational complexity, because the number of beta steps to normal form is polynomially related to the actual cost (that is, as performed on a Turing machine) of normalization, under weak call-by-value reduction. Orthogonal constructor term rewrite systems and lambda-calculus are thus both polynomially related to Turing machines, taking as notion of cost their natural parameters.


HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

Abstract: We present HONEI, an open-source collection of libraries offering a hardware oriented approach to numerical calculations. HONEI abstracts the hardware, and applications written on top of HONEI can be executed on a wide range of computer architectures such as CPUs, GPUs and the Cell processor. We demonstrate the flexibility and performance of our approach with two test applications, a Finite Element multigrid solver for the Poisson problem and a robust and fast simulation of shallow water waves. By linking against HONEI's libraries, we achieve a twofold speedup over straight forward C++ code using HONEI's SSE backend, and additional 3-4 and 4-16 times faster execution on the Cell and a GPU. A second important aspect of our approach is that the full performance capabilities of the hardware under consideration can be exploited by adding optimised application-specific operations to the HONEI libraries. HONEI provides all necessary infrastructure for development and evaluation of such kernels, significantly simplifying their development.


Fundamentals of the Backoff Process in 802.11: Dichotomy of the Aggregation

Abstract: This paper discovers fundamental principles of the backoff process that governs the performance of IEEE 802.11. A simplistic principle founded upon regular variation theory is that the backoff time has a truncated Pareto-type tail distribution with an exponent of $(\log \gamma)/\log m$ ($m$ is the multiplicative factor and $\gamma$ is the collision probability). This reveals that the per-node backoff process is heavy-tailed in the strict sense for $\gamma>1/m^2$, and paves the way for the following unifying result. The state-of-the-art theory on the superposition of the heavy-tailed processes is applied to establish a dichotomy exhibited by the aggregate backoff process, putting emphasis on the importance of time-scale on which we view the backoff processes. While the aggregation on normal time-scales leads to a Poisson process, it is approximated by a new limiting process possessing long-range dependence (LRD) on coarse time-scales. This dichotomy turns out to be instrumental in formulating short-term fairness, extending existing formulas to arbitrary population, and to elucidate the absence of LRD in practical situations. A refined wavelet analysis is conducted to strengthen this argument.


Denial of service attack in the Internet: agent-based intrusion detection and reaction

Abstract: This paper deals with denial of service attack. Overview of the existing attacks and methods is proposed. Classification scheme is presented for a different denial of service attacks. There is considered agent-based intrusion detection systems architecture. Considered main components and working principles for a systems of such kind.


Parallel Random Apollonian Networks

Abstract: We present and study in this paper a simple algorithm that produces so called growing Parallel Random Apollonian Networks (P-RAN) in any dimension d. Analytical derivations show that these networks still exhibit small-word and scale-free characteristics. To characterize further the structure of P-RAN, we introduce new parameters that we refer to as the parallel degree and the parallel coefficient, that determine locally and in average the number of vertices inside the (d+1)-cliques composing the network. We provide analytical derivations for the computation of the degree and parallel degree distributions, parallel and clustering coefficients. We give an upper bound for the average path lengths for P-RAN and finally show that our derivations are in very good agreement with our simulations.


Java Technology : a Strategic Solution for Interactive Distributed Applications

Abstract: In a world demanding the best performance from financial investments, distributed applications occupy the first place among the proposed solutions. This particularity is due to their distributed architecture which is able to acheives high performance. Currently, many research works aim to develop tools that facilitate the implementation of such applications. The urgent need for such applications in all areas pushes researchers to accelerate this process. However, the lack of standardization results in the absence of strategic decisions taken by computer science community. In this article, we argue that Java technology represents an elegant compromise ahead of the list of the currently available solutions. In fact, by promoting the independence of hardware and software, Java technology makes it possible to overcome pitfalls that are inherent to the creation of distributed applications.


On the Power of Randomization in Algorithmic Mechanism Design

Abstract: In many settings the power of truthful mechanisms is severely bounded. In this paper we use randomization to overcome this problem. In particular, we construct an FPTAS for multi-unit auctions that is truthful in expectation, whereas there is evidence that no polynomial-time truthful deterministic mechanism provides an approximation ratio better than 2. We also show for the first time that truthful in expectation polynomial-time mechanisms are \emph{provably} stronger than polynomial-time universally truthful mechanisms. Specifically, we show that there is a setting in which: (1) there is a non-polynomial time truthful mechanism that always outputs the optimal solution, and that (2) no universally truthful randomized mechanism can provide an approximation ratio better than 2 in polynomial time, but (3) an FPTAS that is truthful in expectation exists.


On-the-fly erasure coding for real-time video applications

Abstract: This paper introduces a robust point-to-point transmission scheme: Tetrys, that relies on a novel on-the-fly erasure coding concept which reduces the delay for recovering lost data at the receiver side. In current erasure coding schemes, the packets that are not rebuilt at the receiver side are either lost or delayed by at least one RTT before transmission to the application. The present contribution aims at demonstrating that Tetrys coding scheme can fill the gap between real-time applications requirements and full reliability. Indeed, we show that in several cases, Tetrys can recover lost packets below one RTT over lossy and best-effort networks. We also show that Tetrys allows to enable full reliability without delay compromise and as a result: significantly improves the performance of time constrained applications. For instance, our evaluations present that video-conferencing applications obtain a PSNR gain up to 7dB compared to classic block-based erasure codes.


Orientation-Constrained Rectangular Layouts

Abstract: We construct partitions of rectangles into smaller rectangles from an input consisting of a planar dual graph of the layout together with restrictions on the orientations of edges and junctions of the layout. Such an orientation-constrained layout, if it exists, may be constructed in polynomial time, and all orientation-constrained layouts may be listed in polynomial time per layout.


Lower Bounds on Syntactic Logic Expressions for Optimization Problems and Duality using Lagrangian Dual to characterize optimality conditions

Abstract: We show that simple syntactic expressions such as existential second order (ESO) universal Horn formulae can express NP-hard optimisation problems. There is a significant difference between the expressibilities of decision problems and optimisation problems. This is similar to the difference in computation times for the two classes of problems; for example, a 2SAT Horn formula can be satisfied in polynomial time, whereas the optimisation version in NP-hard. It is known that all polynomially solvable decision problems can be expressed as ESO universal ($\Pi_1$) Horn sentences in the presence of a successor relation. We show here that, on the other hand, if $P \neq NP$, optimisation problems defy such a characterisation, by demonstrating that even a $\Pi_0$ (quantifier free) Horn formula is unable to guarantee polynomial time solvability. Finally, by connecting concepts in optimisation duality with those in descriptive complexity, we will show a method by which optimisation problems can be solved by a single call to a "decision" Turing machine, as opposed to multiple calls using a classical binary search setting.


Ing\'enierie syst\`eme d'un syst\`eme d'information d'entreprise centr\'e sur le produit bas\'ee sur un cadre de mod\'elisation multi-\'echelles : application \`a un cas d'\'etude de l'AIP lorrain

Abstract: Through its projects, the ?Atelier Inter-\'etablissements de Productique Lorrain? (AIPL), as the owner and contractor of rank 1, is committed to provide his customers (teachers, training courses, students etc...) credible teaching materials at the scale of a real industrial flexible production of goods and services. In this changing context, its managerial team has chosen to suppress the CIM concept, which proposes an integrated enterprise, to steering distributed system information (SI), heterogeneous, autonomous and scalable depending on the ephemeral cooperation between industrial partners who now exchanges information and material flows. These aspects are studied in research on CRAN (Centre de Recherche en Automatique de Nancy ? Research Centre for Automatic Control) as part of a thesis based on the recursive aspect of systems and their models and their multi-scale aspects and multi-views, in a Model-Based-System-Engineering (MBSE) methodology proposal of an System-Engineering (SE) focused on the product. To validate this research, a MBSE has been implemented on a case study to AIPL: the "eLearning in eProduction? project.


Computing the biases of parity-check relations

Abstract: A divide-and-conquer cryptanalysis can often be mounted against some keystream generators composed of several (nonlinear) independent devices combined by a Boolean function. In particular, any parity-check relation derived from the periods of some constituent sequences usually leads to a distinguishing attack whose complexity is determined by the bias of the relation. However, estimating this bias is a difficult problem since the piling-up lemma cannot be used. Here, we give two exact expressions for this bias. Most notably, these expressions lead to a new algorithm for computing the bias of a parity-check relation, and they also provide some simple formulae for this bias in some particular cases which are commonly used in cryptography.


Bounds on series-parallel slowdown

Abstract: We use activity networks (task graphs) to model parallel programs and consider series-parallel extensions of these networks. Our motivation is two-fold: the benefits of series-parallel activity networks and the modelling of programming constructs, such as those imposed by current parallel computing environments. Series-parallelisation adds precedence constraints to an activity network, usually increasing its makespan (execution time). The slowdown ratio describes how additional constraints affect the makespan. We disprove an existing conjecture positing a bound of two on the slowdown when workload is not considered. Where workload is known, we conjecture that 4/3 slowdown is always achievable, and prove our conjecture for small networks using max-plus algebra. We analyse a polynomial-time algorithm showing that achieving 4/3 slowdown is in exp-APX. Finally, we discuss the implications of our results.


Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance

Abstract: In this paper, we consider the coherent theory of (epistemic) uncertainty of Walley, in which beliefs are represented through sets of probability distributions, and we focus on the problem of modeling prior ignorance about a categorical random variable. In this setting, it is a known result that a state of prior ignorance is not compatible with learning. To overcome this problem, another state of beliefs, called \emph{near-ignorance}, has been proposed. Near-ignorance resembles ignorance very closely, by satisfying some principles that can arguably be regarded as necessary in a state of ignorance, and allows learning to take place. What this paper does, is to provide new and substantial evidence that also near-ignorance cannot be really regarded as a way out of the problem of starting statistical inference in conditions of very weak beliefs. The key to this result is focusing on a setting characterized by a variable of interest that is \emph{latent}. We argue that such a setting is by far the most common case in practice, and we provide, for the case of categorical latent variables (and general \emph{manifest} variables) a condition that, if satisfied, prevents learning to take place under prior near-ignorance. This condition is shown to be easily satisfied even in the most common statistical problems. We regard these results as a strong form of evidence against the possibility to adopt a condition of prior near-ignorance in real statistical problems.


Adaptive Learning with Binary Neurons

Abstract: A efficient incremental learning algorithm for classification tasks, called NetLines, well adapted for both binary and real-valued input patterns is presented. It generates small compact feedforward neural networks with one hidden layer of binary units and binary output units. A convergence theorem ensures that solutions with a finite number of hidden units exist for both binary and real-valued input patterns. An implementation for problems with more than two classes, valid for any binary classifier, is proposed. The generalization error and the size of the resulting networks are compared to the best published results on well-known classification benchmarks. Early stopping is shown to decrease overfitting, without improving the generalization performance.


Graph Homomorphisms, Circular Colouring, and Fractional Covering by H-cuts

Abstract: A graph homomorphism is a vertex map which carries edges from a source graph to edges in a target graph. The instances of the Weighted Maximum H-Colourable Subgraph problem (MAX H-COL) are edge-weighted graphs G and the objective is to find a subgraph of G that has maximal total edge weight, under the condition that the subgraph has a homomorphism to H; note that for H=K_k this problem is equivalent to MAX k-CUT. Farnqvist et al. have introduced a parameter on the space of graphs that allows close study of the approximability properties of MAX H-COL. Specifically, it can be used to extend previously known (in)approximability results to larger classes of graphs. Here, we investigate the properties of this parameter on circular complete graphs K_{p/q}, where 2 <= p/q <= 3. The results are extended to K_4-minor-free graphs and graphs with bounded maximum average degree. We also consider connections with Samal's work on fractional covering by cuts: we address, and decide, two conjectures concerning cubical chromatic numbers.


Temporal data mining for root-cause analysis of machine faults in automotive assembly lines

Abstract: Engine assembly is a complex and heavily automated distributed-control process, with large amounts of faults data logged everyday. We describe an application of temporal data mining for analyzing fault logs in an engine assembly plant. Frequent episode discovery framework is a model-free method that can be used to deduce (temporal) correlations among events from the logs in an efficient manner. In addition to being theoretically elegant and computationally efficient, frequent episodes are also easy to interpret in the form actionable recommendations. Incorporation of domain-specific information is critical to successful application of the method for analyzing fault logs in the manufacturing domain. We show how domain-specific knowledge can be incorporated using heuristic rules that act as pre-filters and post-filters to frequent episode discovery. The system described here is currently being used in one of the engine assembly plants of General Motors and is planned for adaptation in other plants. To the best of our knowledge, this paper presents the first real, large-scale application of temporal data mining in the manufacturing domain. We believe that the ideas presented in this paper can help practitioners engineer tools for analysis in other similar or related application domains as well.