Tight Bounds for Online Stable Sorting

Abstract: Although many authors have considered how many ternary comparisons it takes to sort a multiset $S$ of size $n$, the best known upper and lower bounds still differ by a term linear in $n$. In this paper we restrict our attention to online stable sorting and prove upper and lower bounds that are within (o (n)) not only of each other but also of the best known upper bound for offline sorting. Specifically, we first prove that if the number of distinct elements (\sigma = o (n / \log n)), then ((H + 1) n + o (n)) comparisons are sufficient, where $H$ is the entropy of the distribution of the elements in $S$. We then give a simple proof that ((H + 1) n - o (n)) comparisons are necessary in the worst case.


Function Interface Models for Hardware Compilation: Types, Signatures, Protocols

Abstract: The problem of synthesis of gate-level descriptions of digital circuits from behavioural specifications written in higher-level programming languages (hardware compilation) has been studied for a long time yet a definitive solution has not been forthcoming. The argument of this essay is mainly methodological, bringing a perspective that is informed by recent developments in programming-language theory. We argue that one of the major obstacles in the way of hardware compilation becoming a useful and mature technology is the lack of a well defined function interface model, i.e. a canonical way in which functions communicate with arguments. We discuss the consequences of this problem and propose a solution based on new developments in programming language theory. We conclude by presenting a prototype implementation and some examples illustrating our principles.


Deterministic Polynomial Time Algorithms for Matrix Completion Problems

Abstract: We present new deterministic algorithms for several cases of the maximum rank matrix completion problem (for short matrix completion), i.e. the problem of assigning values to the variables in a given symbolic matrix as to maximize the resulting matrix rank. Matrix completion belongs to the fundamental problems in computational complexity with numerous important algorithmic applications, among others, in computing dynamic transitive closures or multicast network codings (Harvey et al SODA 2005, Harvey et al SODA 2006). We design efficient deterministic algorithms for common generalizations of the results of Lovasz and Geelen on this problem by allowing linear functions in the entries of the input matrix such that the submatrices corresponding to each variable have rank one. We present also a deterministic polynomial time algorithm for finding the minimal number of generators of a given module structure given by matrices. We establish further several hardness results related to matrix algebras and modules. As a result we connect the classical problem of polynomial identity testing with checking surjectivity (or injectivity) between two given modules. One of the elements of our algorithm is a construction of a greedy algorithm for finding a maximum rank element in the more general setting of the problem. The proof methods used in this paper could be also of independent interest.


Bayesian Multitask Learning with Latent Hierarchies

Abstract: We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share covariance structure. Our hierarchical model is seen to subsume several previously proposed multitask learning models and performs well on three distinct real-world data sets.


Cross-Task Knowledge-Constrained Self Training

Abstract: We present an algorithmic framework for learning multiple related tasks. Our framework exploits a form of prior knowledge that relates the output spaces of these tasks. We present PAC learning results that analyze the conditions under which such learning is possible. We present results on learning a shallow parser and named-entity recognition system that exploits our framework, showing consistent improvements over baseline methods.


A Bayesian Model for Discovering Typological Implications

Abstract: A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as ``if objects come after verbs, then adjectives come after nouns.'' Such implications are typically discovered by painstaking hand analysis over a small sample of languages. We propose a computational model for assisting at this process. Our model is able to discover both well-known implications as well as some novel implications that deserve further study. Moreover, through a careful application of hierarchical analysis, we are able to cope with the well-known sampling problem: languages are not independent.


Search-based Structured Prediction

Abstract: We present Searn, an algorithm for integrating search and learning to solve complex structured prediction problems such as those that occur in natural language, speech, computational biology, and vision. Searn is a meta-algorithm that transforms these complex problems into simple classification problems to which any binary classifier may be applied. Unlike current algorithms for structured learning that require decomposition of both the loss function and the feature functions over the predicted structure, Searn is able to learn prediction functions for any loss function and any class of features. Moreover, Searn comes with a strong, natural theoretical guarantee: good performance on the derived classification problems implies good performance on the structured prediction problem.


A generalized inner and outer product of arbitrary multi-dimensional arrays using A Mathematics of Arrays (MoA)

Abstract: An algorithm has been devised to compute the inner and outer product between two arbitrary multi-dimensional arrays A and B in a single piece of code. It was derived using A Mathematics of Arrays (MoA) and the $\psi$-calculus. Extensive tests of the new algorithm are presented for running in sequential as well as OpenMP multiple processor modes.


Tensors and n-d Arrays:A Mathematics of Arrays (MoA), psi-Calculus and the Composition of Tensor and Array Operations

Abstract: The Kronecker product is a key algorithm and is ubiquitous across the physical, biological, and computation social sciences. Thus considerations of optimal implementation are important. The need to have high performance and computational reproducibility is paramount. Moreover, due to the need to compose multiple Kronecker products, issues related to data structures, layout and indexing algebra require a new look at an old problem. This paper discusses the outer product/tensor product and a special case of the tensor product: the Kronecker product, along with optimal implementation when composed, and mapped to complex processor/memory hierarchies. We discuss how the use of ``A Mathematics of Arrays" (MoA), and the psi-Calculus, (a calculus of indexing with shapes), provides optimal, verifiable, reproducible, scalable, and portable implementations of both hardware and software.


Induction of Word and Phrase Alignments for Automatic Document Summarization

Abstract: Current research in automatic single document summarization is dominated by two effective, yet naive approaches: summarization by sentence extraction, and headline generation via bag-of-words models. While successful in some tasks, neither of these models is able to adequately capture the large set of linguistic devices utilized by humans when they produce summaries. One possible explanation for the widespread use of these models is that good techniques have been developed to extract appropriate training data for them from existing document/abstract and document/headline corpora. We believe that future progress in automatic summarization will be driven both by the development of more sophisticated, linguistically informed models, as well as a more effective leveraging of document/abstract corpora. In order to open the doors to simultaneously achieving both of these goals, we have developed techniques for automatically producing word-to-word and phrase-to-phrase alignments between documents and their human-written abstracts. These alignments make explicit the correspondences that exist in such document/abstract pairs, and create a potentially rich data source from which complex summarization algorithms may learn. This paper describes experiments we have carried out to analyze the ability of humans to perform such alignments, and based on these analyses, we describe experiments for creating them automatically. Our model for the alignment task is based on an extension of the standard hidden Markov model, and learns to create alignments in a completely unsupervised fashion. We describe our model in detail and present experimental results that show that our model is able to learn to reliably identify word- and phrase-level alignments in a corpus of <document,abstract> pairs.


A Noisy-Channel Model for Document Compression

Abstract: We present a document compression system that uses a hierarchical noisy-channel model of text production. Our compression system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. The system then uses a statistical hierarchical model of text production in order to drop non-important syntactic and discourse constituents so as to generate coherent, grammatical document compressions of arbitrary length. The system outperforms both a baseline and a sentence-based compression system that operates by simplifying sequentially all sentences in a text. Our results support the claim that discourse knowledge plays an important role in document summarization.


A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model

Abstract: Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, extending the named entity detection and coreference resolution task by considering mentions other than names (pronouns, definite descriptions, etc.). Like NE tagging and coreference resolution, most solutions to the EDT task separate out the mention detection aspect from the coreference aspect. By doing so, these solutions are limited to using only local features for learning. In contrast, by modeling both aspects of the EDT task simultaneously, we are able to learn using highly complex, non-local features. We develop a new joint EDT model and explore the utility of many features, demonstrating their effectiveness on this task.


A Bayesian Model for Supervised Clustering with the Dirichlet Process Prior

Abstract: We develop a Bayesian framework for tackling the supervised clustering problem, the generic problem encountered in tasks such as reference matching, coreference resolution, identity uncertainty and record linkage. Our clustering model is based on the Dirichlet process prior, which enables us to define distributions over the countably infinite sets that naturally arise in this problem. We add supervision to our model by positing the existence of a set of unobserved random variables (we call these "reference types") that are generic across all clusters. Inference in our framework, which requires integrating over infinitely many parameters, is solved using Markov chain Monte Carlo techniques. We present algorithms for both conjugate and non-conjugate priors. We present a simple--but general--parameterization of our model based on a Gaussian assumption. We evaluate this model on one artificial task and three real-world tasks, comparing it against both unsupervised and state-of-the-art supervised algorithms. Our results show that our model is able to outperform other models across a variety of tasks and performance metrics.


Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction

Abstract: Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., linear chains) in which search and parameter estimation can be performed exactly. Unfortunately, in many complex problems, it is rare that exact search or parameter estimation is tractable. Instead of learning exact models and searching via heuristic means, we embrace this difficulty and treat the structured output problem in terms of approximate search. We present a framework for learning as search optimization, and two parameter updates with convergence theorems and bounds. Empirical evidence shows that our integrated approach to learning and decoding can outperform exact models at smaller computational cost.


Breaking a new substitution-diffusion based image cipher using chaotic standard and logistic maps

Abstract: Recently, an image encryption scheme based on chaotic standard and logistic maps was proposed. This paper studies the security of the scheme and shows that it can be broken with only one chosen-plaintext. Some other security defects of the scheme are also reported.


Algebraic Ordinals

Abstract: An algebraic tree T is one determined by a finite system of fixed point equations. The frontier \Fr(T) of an algebraic tree t is linearly ordered by the lexicographic order \lex. When (\Fr(T),\lex) is well-ordered, its order type is an \textbf{algebraic ordinal}. We prove that the algebraic ordinals are exactly the ordinals less than $\omega^{\omega^\omega}$.


Self-Improving Algorithms

Abstract: We investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an unknown input distribution D. We assume here that D is of product type. More precisely, suppose that we need to process a sequence I_1, I_2, ... of inputs I = (x_1, x_2, ..., x_n) of some fixed length n, where each x_i is drawn independently from some arbitrary, unknown distribution D_i. The goal is to design an algorithm for these inputs so that eventually the expected running time will be optimal for the input distribution D = D_1 * D_2 * ... * D_n. We give such self-improving algorithms for two problems: (i) sorting a sequence of numbers and (ii) computing the Delaunay triangulation of a planar point set. Both algorithms achieve optimal expected limiting complexity. The algorithms begin with a training phase during which they collect information about the input distribution, followed by a stationary regime in which the algorithms settle to their optimized incarnations.


Randomized Incremental Construction of Compressed Quadtrees

Abstract: We present a simple randomized incremental algorithm for building compressed quadtrees. The resulting algorithm seems to be simpler than previously known algorithms for this task.


CRDTs: Consistency without concurrency control

Abstract: A CRDT is a data type whose operations commute when they are concurrent. Replicas of a CRDT eventually converge without any complex concurrency control. As an existence proof, we exhibit a non-trivial CRDT: a shared edit buffer called Treedoc. We outline the design, implementation and performance of Treedoc. We discuss how the CRDT concept can be generalised, and its limitations.


The threshold for random (1,2)-QSAT

Abstract: The QSAT problem is the quantified version of the SAT problem. We show the existence of a threshold effect for the phase transition associated with the satisfiability of random quantified extended 2-CNF formulas. We consider boolean CNF formulas of the form $\forall X \exists Y \varphi(X,Y)$, where $X$ has $m$ variables, $Y$ has $n$ variables and each clause in $\varphi$ has one literal from $X$ and two from $Y$. For such formulas, we show that the threshold phenomenon is controlled by the ratio between the number of clauses and the number $n$ of existential variables. Then we give the exact location of the associated critical ratio $c^{*}$. Indeed, we prove that $c^{*}$ is a decreasing function of $ \alpha$, where $\alpha$ is the limiting value of $m / \log (n)$ when $n$ tends to infinity.


The Soft Cumulative Constraint

Abstract: This research report presents an extension of Cumulative of Choco constraint solver, which is useful to encode over-constrained cumulative problems. This new global constraint uses sweep and task interval violation-based algorithms.


Representing Real Numbers in a Generalized Numeration Systems

Abstract: We show how to represent an interval of real numbers in an abstract numeration system built on a language that is not necessarily regular. As an application, we consider representations of real numbers using the Dyck language. We also show that our framework can be applied to the rational base numeration systems.


Attacking the combination generator

Abstract: We present one of the most efficient attacks against the combination generator. This attack is inherent to this system as its only assumption is that the filtering function has a good autocorrelation. This is usually the case if the system is designed to be resistant to other kinds of attacks. We use only classical tools, namely vectorial correlation, weight 4 multiples and Walsh transform.


A class of structured P2P systems supporting browsing

Abstract: Browsing is a way of finding documents in a large amount of data which is complementary to querying and which is particularly suitable for multimedia documents. Locating particular documents in a very large collection of multimedia documents such as the ones available in peer to peer networks is a difficult task. However, current peer to peer systems do not allow to do this by browsing. In this report, we show how one can build a peer to peer system supporting a kind of browsing. In our proposal, one must extend an existing distributed hash table system with a few features : handling partial hash-keys and providing appropriate routing mechanisms for these hash-keys. We give such an algorithm for the particular case of the Tapestry distributed hash table. This is a work in progress as no proper validation has been done yet.


Apply Local Clustering Method to Improve the Running Speed of Ant Colony Optimization

Abstract: Ant Colony Optimization (ACO) has time complexity O(t*m*N*N), and its typical application is to solve Traveling Salesman Problem (TSP), where t, m, and N denotes the iteration number, number of ants, number of cities respectively. Cutting down running time is one of study focuses, and one way is to decrease parameter t and N, especially N. For this focus, the following method is presented in this paper. Firstly, design a novel clustering algorithm named Special Local Clustering algorithm (SLC), then apply it to classify all cities into compact classes, where compact class is the class that all cities in this class cluster tightly in a small region. Secondly, let ACO act on every class to get a local TSP route. Thirdly, all local TSP routes are jointed to form solution. Fourthly, the inaccuracy of solution caused by clustering is eliminated. Simulation shows that the presented method improves the running speed of ACO by 200 factors at least. And this high speed is benefit from two factors. One is that class has small size and parameter N is cut down. The route length at every iteration step is convergent when ACO acts on compact class. The other factor is that, using the convergence of route length as termination criterion of ACO and parameter t is cut down.


Learning Gaussian Mixtures with Arbitrary Separation

Abstract: In this paper we present a method for learning the parameters of a mixture of $k$ identical spherical Gaussians in $n$-dimensional space with an arbitrarily small separation between the components. Our algorithm is polynomial in all parameters other than $k$. The algorithm is based on an appropriate grid search over the space of parameters. The theoretical analysis of the algorithm hinges on a reduction of the problem to 1 dimension and showing that two 1-dimensional mixtures whose densities are close in the $L^2$ norm must have similar means and mixing coefficients. To produce such a lower bound for the $L^2$ norm in terms of the distances between the corresponding means, we analyze the behavior of the Fourier transform of a mixture of Gaussians in 1 dimension around the origin, which turns out to be closely related to the properties of the Vandermonde matrix obtained from the component means. Analysis of this matrix together with basic function approximation results allows us to provide a lower bound for the norm of the mixture in the Fourier domain. In recent years much research has been aimed at understanding the computational aspects of learning parameters of Gaussians mixture distributions in high dimension. To the best of our knowledge all existing work on learning parameters of Gaussian mixtures assumes minimum separation between components of the mixture which is an increasing function of either the dimension of the space $n$ or the number of components $k$. In our paper we prove the first result showing that parameters of a $n$-dimensional Gaussian mixture model with arbitrarily small component separation can be learned in time polynomial in $n$.


Design of an Optimal Bayesian Incentive Compatible Broadcast Protocol for Ad hoc Networks with Rational Nodes

Abstract: Nodes in an ad hoc wireless network incur certain costs for forwarding packets since packet forwarding consumes the resources of the nodes. If the nodes are rational, free packet forwarding by the nodes cannot be taken for granted and incentive based protocols are required to stimulate cooperation among the nodes. Existing incentive based approaches are based on the VCG (Vickrey-Clarke-Groves) mechanism which leads to high levels of incentive budgets and restricted applicability to only certain topologies of networks. Moreover, the existing approaches have only focused on unicast and multicast. Motivated by this, we propose an incentive based broadcast protocol that satisfies Bayesian incentive compatibility and minimizes the incentive budgets required by the individual nodes. The proposed protocol, which we call {\em BIC-B} (Bayesian incentive compatible broadcast) protocol, also satisfies budget balance. We also derive a necessary and sufficient condition for the ex-post individual rationality of the BIC-B protocol. The {\em BIC-B} protocol exhibits superior performance in comparison to a dominant strategy incentive compatible broadcast protocol.


Self-Assembling Systems are Distributed Systems

Abstract: In 2004, Klavins et al. introduced the use of graph grammars to describe -- and to program -- systems of self-assembly. We show that these graph grammars can be embedded in a graph rewriting characterization of distributed systems that was proposed by Degano and Montanari over twenty years ago. We apply this embedding to generalize Soloveichik and Winfree's local determinism criterion (for achieving a unique terminal assembly), from assembly systems of 4-sided tiles that embed in the plane, to arbitrary graph assembly systems. We present a partial converse of the embedding result, by providing sufficient conditions under which systems of distributed processors can be simulated by graph assembly systems topologically, in the plane, and in 3-space. We conclude by defining a new complexity measure: "surface cost" (essentially the convex hull of the space inhabited by agents at the conclusion of a self-assembled computation). We show that, for growth-bounded graphs, executing a subroutine to find a Maximum Independent Set only increases the surface cost of a self-assembling computation by a constant factor. We obtain this complexity bound by using the simulation results to import the distributed computing notions of "local synchronizer" and "deterministic coin flipping" into self-assembly.


Quasi-Polynomial Time Approximation Schemes for Target Tracking

Abstract: We consider the problem of tracking $n$ targets in the plane using $2n$ cameras. We can use two cameras to estimate the location of a target. We are then interested in forming $n$ camera pairs where each camera belongs to exactly one pair, followed by forming a matching between the targets and camera pairs so as to best estimate the locations of each of the targets. We consider a special case of this problem where each of the cameras are placed along a horizontal line $l$, and we consider two objective functions which have been shown to give good estimates of the locations of the targets when the distances between the targets and the cameras are sufficiently large. In the first objective, the value of an assignment of a camera pair to a target is the tracking angle formed by the assignment. Here, we are interested in maximizing the sum of these tracking angles. A polynomial time 2-approximation is known for this problem. We give a quasi-polynomial time algorithm that returns a solution whose value is at least a $(1-\epsilon)$ factor of the value of an optimal solution for any $\epsilon > 0$. In the second objective, the cost of an assignment of a camera pair to a target is the ratio of the vertical distance between the target and $l$ to the horizontal distance between the cameras in the camera pair. In this setting, we are interested in minimizing the sum of these ratios. A polynomial time 2-approximation is known for this problem. We give a quasi-polynomial time algorithm that returns a solution whose value is at most a $(1+\epsilon)$ factor of the value of an optimal solution for any $\epsilon > 0$.


A Lower Bound for Succinct Rank Queries

Abstract: The rank problem in succinct data structures asks to preprocess an array A[1..n] of bits into a data structure using as close to n bits as possible, and answer queries of the form rank(k) = Sum_{i=1}^k A[i]. The problem has been intensely studied, and features as a subroutine in a majority of succinct data structures. We show that in the cell probe model with w-bit cells, if rank takes t time, the space of the data structure must be at least n + n/w^{O(t)} bits. This redundancy/query trade-off is essentially optimal, matching our upper bound from [FOCS'08].


Approximating Spanning Trees with Low Crossing Number

Abstract: We present a linear programming based algorithm for computing a spanning tree $T$ of a set $P$ of $n$ points in $\Re^d$, such that its crossing number is $O(\min(t \log n, n^{1-1/d}))$, where $t$ the minimum crossing number of any spanning tree of $P$. This is the first guaranteed approximation algorithm for this problem. We provide a similar approximation algorithm for the more general settings of building a spanning tree for a set system with bounded \VC dimension. Our approach is an alternative to the reweighting technique previously used in computing such spanning trees. Our approach is an alternative to the reweighting technique previously used in computing such spanning trees.


Using HB Family of Protocols for Privacy-Preserving Authentication of RFID Tags in a Population

Abstract: In this paper, we propose an HB-like protocol for privacy-preserving authentication of RFID tags, whereby a tag can remain anonymous and untraceable to an adversary during the authentication process. Previous proposals of such protocols were based on PRF computations. Our protocol can instead be used on low-cost tags that may be incapable of computing standard PRFs. Moreover, since the underlying computations in HB protocols are very efficient, our protocol also reduces reader load compared to PRF-based protocols. We suggest a tree-based approach that replaces the PRF-based authentication from prior work with a procedure such as HB+ or HB#. We optimize the tree- traversal stage through usage of a "light version" of the underlying protocol and shared random challenges across all levels of the tree. This provides significant reduction of the communication resources, resulting in a privacy-preserving protocol almost as efficient as the underlying HB+ or HB#


ChOrDa: a methodology for the modeling of business processes with BPMN

Abstract: In this paper we present a modeling methodology for BPMN, the standard notation for the representation of business processes. Our methodology simplifies the development of collaborative BPMN diagrams, enabling the automated creation of skeleton process diagrams representing complex choreographies. To evaluate and tune the methodology, we have developed a tool supporting it, that we apply to the modeling of an international patenting process as a working example.


How Controlled English can Improve Semantic Wikis

Abstract: The motivation of semantic wikis is to make acquisition, maintenance, and mining of formal knowledge simpler, faster, and more flexible. However, most existing semantic wikis have a very technical interface and are restricted to a relatively low level of expressivity. In this paper, we explain how AceWiki uses controlled English - concretely Attempto Controlled English (ACE) - to provide a natural and intuitive interface while supporting a high degree of expressivity. We introduce recent improvements of the AceWiki system and user studies that indicate that AceWiki is usable and useful.


How to Evaluate Controlled Natural Languages

Abstract: This paper presents a general framework how controlled natural languages can be evaluated and compared on the basis of user experiments. The subjects are asked to classify given statements (in the language to be tested) as either true or false with respect to a certain situation that is shown in a graphical notation called "ontographs". A first experiment has been conducted that applies this framework to the language Attempto Controlled English (ACE).


We Can Remember It for You Wholesale: Implications of Data Remanence on the Use of RAM for True Random Number Generation on RFID Tags (RFIDSec 2009)

Abstract: Random number generation is a fundamental security primitive for RFID devices. However, even this relatively simple requirement is beyond the capacity of today's average RFID tag. A recently proposed solution, Fingerprint Extraction and Random Number Generation in SRAM (FERNS) [14, 15], involves the use of onboard RAM as the source of "true" randomness. Unfortunately, practical considerations prevent this approach from reaching its full potential. First, this method must compete with other system functionalities for use of memory. Thus, the amount of uninitialized RAM available for utilization as a randomness generator may be severely restricted. Second, RAM is subject to data remanence; there is a time period after losing power during which stored data remains intact in memory. This means that after a portion of memory has been used for entropy collection once it will require a relatively extended period of time without power before it can be reused. In a usable RFID based security application, which requires multiple or long random numbers, this may lead to unacceptably high delays. In this paper, we show that data remanence negatively affects RAM based random number generation. We demonstrate the practical considerations that must be taken into account when using RAM as an entropy source. We also discuss the implementation of a true random number generator on Intel's WISP RFID tag, which is the first such implementation to the authors' best knowledge. By relating this to the requirements of some popular RFID authentication protocols, we assess the (im)practicality of utilizing memory based randomness techniques on resource constrained devices.


The Complexity of Guarding Terrains

Abstract: A set $G$ of points on a 1.5-dimensional terrain, also known as an $x$-monotone polygonal chain, is said to guard the terrain if any point on the terrain is 'seen' by a point in $G$. Two points on the terrain see each other if and only if the line segment between them is never strictly below the terrain. The minimum terrain guarding problem asks for a minimum guarding set for the given input terrain. We prove that the decision version of this problem is NP-hard. This solves a significant open problem and complements recent positive approximability results for the optimization problem. Our proof uses a reduction from PLANAR 3-SAT. We build gadgets capable of 'mirroring' a consistent variable assignment back and forth across a main valley. The structural simplicity of 1.5-dimensional terrains makes it difficult to build general clause gadgets that do not destroy this assignment when they are evaluated. However, we exploit the structure in instances of PLANAR 3-SAT to find very specific operations involving only 'adjacent' variables. For these restricted operations we can construct gadgets that allow a full reduction to work.


Online Sorting via Searching and Selection

Abstract: In this paper, we present a framework based on a simple data structure and parameterized algorithms for the problems of finding items in an unsorted list of linearly ordered items based on their rank (selection) or value (search). As a side-effect of answering these online selection and search queries, we progressively sort the list. Our algorithms are based on Hoare's Quickselect, and are parameterized based on the pivot selection method. For example, if we choose the pivot as the last item in a subinterval, our framework yields algorithms that will answer q<=n unique selection and/or search queries in a total of O(n log q) average time. After q=\Omega(n) queries the list is sorted. Each repeated selection query takes constant time, and each repeated search query takes O(log n) time. The two query types can be interleaved freely. By plugging different pivot selection methods into our framework, these results can, for example, become randomized expected time or deterministic worst-case time. Our methods are easy to implement, and we show they perform well in practice.


Reducing Tile Complexity for the Self-Assembly of Scaled Shapes Through Temperature Programming

Abstract: This paper concerns the self-assembly of scaled-up versions of arbitrary finite shapes. We work in the multiple temperature model that was introduced by Aggarwal, Cheng, Goldwasser, Kao, and Schweller (Complexities for Generalized Models of Self-Assembly, SODA 2004). The multiple temperature model is a natural generalization of Winfree's abstract tile assembly model, where the temperature of a tile system is allowed to be shifted up and down as self-assembly proceeds. We first exhibit two constant-size tile sets in which scaled-up versions of arbitrary shapes self-assemble. Our first tile set has the property that each scaled shape self-assembles via an asymptotically "Kolmogorov-optimum" temperature sequence but the scaling factor grows with the size of the shape being assembled. In contrast, our second tile set assembles each scaled shape via a temperature sequence whose length is proportional to the number of points in the shape but the scaling factor is a constant independent of the shape being assembled. We then show that there is no constant-size tile set that can uniquely assemble an arbitrary (non-scaled, connected) shape in the multiple temperature model, i.e., the scaling is necessary for self-assembly. This answers an open question of Kao and Schweller (Reducing Tile Complexity for Self-Assembly Through Temperature Programming, SODA 2006), who asked whether such a tile set existed.


On the Complexity of Envy-Free Cake Cutting

Abstract: We study the envy-free cake-cutting problem for $d+1$ players with $d$ cuts, for both the oracle function model and the polynomial time function model. For the former, we derive a $\theta(({1\over\epsilon})^{d-1})$ time matching bound for the query complexity of $d+1$ player cake cutting with Lipschitz utilities for any $d> 1$. When the utility functions are given by a polynomial time algorithm, we prove the problem to be PPAD-complete. For measurable utility functions, we find a fully polynomial-time algorithm for finding an approximate envy-free allocation of a cake among three people using two cuts.


Graph Based Reduction of Program Verification Conditions

Abstract: Increasing the automaticity of proofs in deductive verification of C programs is a challenging task. When applied to industrial C programs known heuristics to generate simpler verification conditions are not efficient enough. This is mainly due to their size and a high number of irrelevant hypotheses. This work presents a strategy to reduce program verification conditions by selecting their relevant hypotheses. The relevance of a hypothesis is determined by the combination of a syntactic analysis and two graph traversals. The first graph is labeled by constants and the second one by the predicates in the axioms. The approach is applied on a benchmark arising in industrial program verification.


Towards an $O(\sqrt[3]{\log n})$-Approximation Algorithm for {\sc Balanced Separator}

Abstract: The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new directions of progress in the {\sc $c$-Balanced Separator} problem. More specifically, we propose a new family of mathematical programs, which depends upon a parameter $\epsilon > 0$, and extend the seminal work of Arora-Rao-Vazirani ({\sf ARV}) \cite{ARV} to show that the polynomial time solvability of the proposed family of programs implies an improvement in the approximation factor to $O(\log^{{1/3} + \epsilon} n)$ from the best-known factor of $O(\sqrt{\log n})$ due to {\sf ARV}. In fact, for $\epsilon = 1/3$, the program we get is the SDP proposed by {\sf ARV}. For $\epsilon < 1/3$, this family of programs is not convex but one can transform them into so called \emph{\textbf{concave programs}} in which one optimizes a concave function over a convex feasible set. The properties of concave programs allows one to apply techniques due to Hoffman \cite{H81} or Tuy \emph{et al} \cite{TTT85} to solve such problems with arbitrary accuracy. But the problem of finding of a method to solve these programs that converges in polynomial time still remains open. Our result, although conditional, introduces a new family of programs which is more powerful than semi-definite programming in the context of approximation algorithms and hence it will of interest to investigate this family both in the direction of designing efficient algorithms and proving hardness results.


PT-Scotch: A tool for efficient parallel graph ordering

Abstract: The parallel ordering of large graphs is a difficult problem, because on the one hand minimum degree algorithms do not parallelize well, and on the other hand the obtainment of high quality orderings with the nested dissection algorithm requires efficient graph bipartitioning heuristics, the best sequential implementations of which are also hard to parallelize. This paper presents a set of algorithms, implemented in the PT-Scotch software package, which allows one to order large graphs in parallel, yielding orderings the quality of which is only slightly worse than the one of state-of-the-art sequential algorithms. Our implementation uses the classical nested dissection approach but relies on several novel features to solve the parallel graph bipartitioning problem. Thanks to these improvements, PT-Scotch produces consistently better orderings than ParMeTiS on large numbers of processors.


Privacy constraints in regularized convex optimization

Abstract: This paper is withdrawn due to some errors, which are corrected in arXiv:0912.0071v4 [cs.LG].


How discontinuous is Computing Nash Equilibria?

Abstract: We investigate the degree of discontinuity of several solution concepts from non-cooperative game theory. While the consideration of Nash equilibria forms the core of our work, also pure and correlated equilibria are dealt with. Formally, we restrict the treatment to two player games, but results and proofs extend to the n-player case. As a side result, the degree of discontinuity of solving systems of linear inequalities is settled.


Testing Probabilistic Processes: Can Random Choices Be Unobservable?

Abstract: A central paradigm behind process semantics based on observability and testing is that the exact moment of occurring of an internal nondeterministic choice is unobservable. It is natural, therefore, for this property to hold when the internal choice is quantified with probabilities. However, ever since probabilities have been introduced in process semantics, it has been a challenge to preserve the unobservability of the random choice, while not violating the other laws of process theory and probability theory. This paper addresses this problem. It proposes two semantics for processes where the internal nondeterminism has been quantified with probabilities. The first one is based on the notion of testing, i.e. interaction between the process and its environment. The second one, the probabilistic ready trace semantics, is based on the notion of observability. Both are shown to coincide. They are also preserved under the standard operators.


Augmenting Light Field to model Wave Optics effects

Abstract: The ray-based 4D light field representation cannot be directly used to analyze diffractive or phase--sensitive optical elements. In this paper, we exploit tools from wave optics and extend the light field representation via a novel "light field transform". We introduce a key modification to the ray--based model to support the transform. We insert a "virtual light source", with potentially negative valued radiance for certain emitted rays. We create a look-up table of light field transformers of canonical optical elements. The two key conclusions are that (i) in free space, the 4D light field completely represents wavefront propagation via rays with real (positive as well as negative) valued radiance and (ii) at occluders, a light field composed of light field transformers plus insertion of (ray--based) virtual light sources represents resultant phase and amplitude of wavefronts. For free--space propagation, we analyze different wavefronts and coherence possibilities. For occluders, we show that the light field transform is simply based on a convolution followed by a multiplication operation. This formulation brings powerful concepts from wave optics to computer vision and graphics. We show applications in cubic-phase plate imaging and holographic displays.


Incorporating Integrity Constraints in Uncertain Databases

Abstract: We develop an approach to incorporate additional knowledge, in the form of general purpose integrity constraints (ICs), to reduce uncertainty in probabilistic databases. While incorporating ICs improves data quality (and hence quality of answers to a query), it significantly complicates query processing. To overcome the additional complexity, we develop an approach to map an uncertain relation U with ICs to another uncertain relation U', that approximates the set of consistent worlds represented by U. Queries over U can instead be evaluated over U' achieving higher quality (due to reduced uncertainty in U') without additional complexity in query processing due to ICs. We demonstrate the effectiveness and scalability of our approach to large data-sets with complex constraints. We also present experimental results demonstrating the utility of incorporating integrity constraints in uncertain relations, in the context of an information extraction application.


Simple Random Walks on Radio Networks (Simple Random Walks on Hyper-Graphs)

Abstract: In recent years, protocols that are based on the properties of random walks on graphs have found many applications in communication and information networks, such as wireless networks, peer-to-peer networks and the Web. For wireless networks (and other networks), graphs are actually not the correct model of the communication; instead hyper-graphs better capture the communication over a wireless shared channel. Motivated by this example, we study in this paper random walks on hyper-graphs. First, we formalize the random walk process on hyper-graphs and generalize key notions from random walks on graphs. We then give the novel definition of radio cover time, namely, the expected time of a random walk to be heard (as opposed to visit) by all nodes. We then provide some basic bounds on the radio cover, in particular, we show that while on graphs the radio cover time is O(mn), in hyper-graphs it is O(mnr) where n, m and r are the number of nodes, the number of edges and the rank of the hyper-graph, respectively. In addition, we define radio hitting times and give a polynomial algorithm to compute them. We conclude the paper with results on specific hyper-graphs that model wireless networks in one and two dimensions.


Modelling Concurrency with Comtraces and Generalized Comtraces

Abstract: Comtraces (combined traces) are extensions of Mazurkiewicz traces that can model the "not later than" relationship. In this paper, we first introduce the novel notion of generalized comtraces, extensions of comtraces that can additionally model the "non-simultaneously" relationship. Then we study some basic algebraic properties and canonical reprentations of comtraces and generalized comtraces. Finally we analyze the relationship between generalized comtraces and generalized stratified order structures. The major technical contribution of this paper is a proof showing that generalized comtraces can be represented by generalized stratified order structures.


Role of Weak Ties in Link Prediction of Complex Networks

Abstract: Plenty of algorithms for link prediction have been proposed and were applied to various real networks. Among these works, the weights of links are rarely taken into account. In this paper, we use local similarity indices to estimate the likelihood of the existence of links in weighted networks, including Common Neighbor, Adamic-Adar Index, Resource Allocation Index, and their weighted versions. In both the unweighted and weighted cases, the resource allocation index performs the best. To our surprise, the weighted indices perform worse, which reminds us of the well-known Weak Tie Theory. Further extensive experimental study shows that the weak ties play a significant role in the link prediction problem, and to emphasize the contribution of weak ties can remarkably enhance the predicting accuracy.


The SAT solving method as applied to cryptographic analysis of asymmetric ciphers

Abstract: The one of the most interesting problem of discrete mathematics is the SAT (satisfiability) problem. Good way in SAT solver developing is to transform the SAT problem to the problem of continuous search of global minimums of the functional associated with the CNF. This article proves the special construction of the functional and offers to solve the system of non-linear algebraic equation that determines functional stationary points via modified method of consecutive approximation. The article describes parallel versions of the method. Also gives the schema of using the method to important problems of cryptographic analysis of asymmetric ciphers, including determining concrete bits of multipliers (in binary form) in large factorization problems and concrete bits of exponent of discrete logarithm problem.


Classified Stable Matching

Abstract: We introduce the {\sc classified stable matching} problem, a problem motivated by academic hiring. Suppose that a number of institutes are hiring faculty members from a pool of applicants. Both institutes and applicants have preferences over the other side. An institute classifies the applicants based on their research areas (or any other criterion), and, for each class, it sets a lower bound and an upper bound on the number of applicants it would hire in that class. The objective is to find a stable matching from which no group of participants has reason to deviate. Moreover, the matching should respect the upper/lower bounds of the classes. In the first part of the paper, we study classified stable matching problems whose classifications belong to a fixed set of ``order types.'' We show that if the set consists entirely of downward forests, there is a polynomial-time algorithm; otherwise, it is NP-complete to decide the existence of a stable matching. In the second part, we investigate the problem using a polyhedral approach. Suppose that all classifications are laminar families and there is no lower bound. We propose a set of linear inequalities to describe stable matching polytope and prove that it is integral. This integrality allows us to find various optimal stable matchings using Ellipsoid algorithm. A further ramification of our result is the description of the stable matching polytope for the many-to-many (unclassified) stable matching problem. This answers an open question posed by Sethuraman, Teo and Qian.


Fast search for Dirichlet process mixture models

Abstract: Dirichlet process (DP) mixture models provide a flexible Bayesian framework for density estimation. Unfortunately, their flexibility comes at a cost: inference in DP mixture models is computationally expensive, even when conjugate distributions are used. In the common case when one seeks only a maximum a posteriori assignment of data points to clusters, we show that search algorithms provide a practical alternative to expensive MCMC and variational techniques. When a true posterior sample is desired, the solution found by search can serve as a good initializer for MCMC. Experimental results show that using these techniques is it possible to apply DP mixture models to very large data sets.


Bayesian Query-Focused Summarization

Abstract: We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.


Frustratingly Easy Domain Adaptation

Abstract: We describe an approach to domain adaptation that is appropriate exactly in the case when one has enough ``target'' data to do slightly better than just using only ``source'' data. Our approach is incredibly simple, easy to implement as a preprocessing step (10 lines of Perl!) and outperforms state-of-the-art approaches on a range of datasets. Moreover, it is trivially extended to a multi-domain adaptation problem, where one has data from a variety of different domains.


A new intrinsic numerical method for PDE on surfaces

Abstract: In this note we shall introduce a simple, effective numerical method for solving partial differential equations for scalar and vector-valued data defined on surfaces. Even though we shall follow the traditional way to approximate the regular surfaces under consideration by triangular meshes, the key idea of our algorithm is to develop an intrinsic and unified way to compute directly the partial derivatives of functions defined on triangular meshes. We shall present examples in computer graphics and image processing applications.


An Evolved Neural Controller for Bipdedal Walking with Dynamic Balance

Abstract: We successfully evolved a neural network controller that produces dynamic walking in a simulated bipedal robot with compliant actuators, a difficult control problem. The evolutionary evaluation uses a detailed software simulation of a physical robot. We describe: 1) a novel theoretical method to encourage populations to evolve "around" local optima, which employs multiple demes and fitness functions of progressively increasing difficulty, and 2) the novel genetic representation of the neural controller.


A PTAS for the Minimum Consensus Clustering Problem with a Fixed Number of Clusters

Abstract: The Consensus Clustering problem has been introduced as an effective way to analyze the results of different microarray experiments. The problem consists of looking for a partition that best summarizes a set of input partitions (each corresponding to a different microarray experiment) under a simple and intuitive cost function. The problem admits polynomial time algorithms on two input partitions, but is APX-hard on three input partitions. We investigate the restriction of Consensus Clustering when the output partition is required to contain at most k sets, giving a polynomial time approximation scheme (PTAS) while proving the NP-hardness of this restriction.


Learning Equilibria in Games by Stochastic Distributed Algorithms

Abstract: We consider a class of fully stochastic and fully distributed algorithms, that we prove to learn equilibria in games. Indeed, we consider a family of stochastic distributed dynamics that we prove to converge weakly (in the sense of weak convergence for probabilistic processes) towards their mean-field limit, i.e an ordinary differential equation (ODE) in the general case. We focus then on a class of stochastic dynamics where this ODE turns out to be related to multipopulation replicator dynamics. Using facts known about convergence of this ODE, we discuss the convergence of the initial stochastic dynamics: For general games, there might be non-convergence, but when convergence of the ODE holds, considered stochastic algorithms converge towards Nash equilibria. For games admitting Lyapunov functions, that we call Lyapunov games, the stochastic dynamics converge. We prove that any ordinal potential game, and hence any potential game is a Lyapunov game, with a multiaffine Lyapunov function. For Lyapunov games with a multiaffine Lyapunov function, we prove that this Lyapunov function is a super-martingale over the stochastic dynamics. This leads a way to provide bounds on their time of convergence by martingale arguments. This applies in particular for many classes of games that have been considered in literature, including several load balancing game scenarios and congestion games.


Amplified Hardness of Approximation for VCG-Based Mechanisms

Abstract: If a two-player social welfare maximization problem does not admit a PTAS, we prove that any maximal-in-range truthful mechanism that runs in polynomial time cannot achieve an approximation factor better than 1/2. Moreover, for the k-player version of the same problem, the hardness of approximation improves to 1/k under the same two-player hardness assumption. (We note that 1/k is achievable by a trivial deterministic maximal-in-range mechanism.) This hardness result encompasses not only deterministic maximal-in-range mechanisms, but also all universally-truthful randomized maximal in range algorithms, as well as a class of strictly more powerful truthful-in-expectation randomized mechanisms recently introduced by Dobzinski and Dughmi. Our result applies to any class of valuation functions that satisfies some minimal closure properties. These properties are satisfied by the valuation functions in all well-studied APX-hard social welfare maximization problems, such as coverage, submodular, and subadditive valuations. We also prove a stronger result for universally-truthful maximal-in-range mechanisms. Namely, even for the class of budgeted additive valuations, which admits an FPTAS, no such mechanism can achieve an approximation factor better than 1/k in polynomial time.


On the Chances of Completing the Game of "Perpetual Motion"

Abstract: This brief paper describes the single-player card game called "Perpetual Motion" and reports on a computational analysis of the game's outcome. The analysis follows a Monte Carlo methodology based on a sample of 10,000 randomly generated games. The key result is that 54.55% +/- 0.89% of games can be completed (by a patient player!) but that the remaining 45.45% result in non-terminating cycles. The lengths of these non-terminating cycles leave some outstanding questions.


BPDMN: A Conservative Extension of BPMN with Enhanced Data Representation Capabilities

Abstract: The design of business processes involves the usage of modeling languages, tools and methodologies. In this paper we highlight and address a relevant limitation of the Business Process Modeling Notation (BPMN): its weak data representation capabilities. In particular, we extend it with data-specific constructs derived from existing data modeling notations and adapted to blend gracefully into BPMN diagrams. The extension has been developed taking existing modeling languages and requirement analyses into account: we characterize our notation using the Workfl ow Data Patterns and provide mappings to the main XML-based business process languages.


Foundations for a Developmental State: A case for technical education

Abstract: This paper studies the viability of making a country a developmental state. In particular it studies the characteristics of a developmental state and how they are linked to technology. It then identifies technical education, as a vital force for the creation of a developmental state. In particular it identifies analytical, numeracy, computational and communication skills as vital forces for a society to create a developmental society.


Refining interfaces: the case of the B method

Abstract: Model-driven design of software for safety-critical applications often relies on mathematically grounded techniques such as the B method. Such techniques consist in the successive applications of refinements to derive a concrete implementation from an abstract specification. Refinement theory defines verification conditions to guarantee that such operations preserve the intended behaviour of the abstract specifications. One of these conditions requires however that concrete operations have exactly the same signatures as their abstract counterpart, which is not always a practical requirement. This paper shows how changes of signatures can be achieved while still staying within the bounds of refinement theory. This makes it possible to take advantage of the mathematical guarantees and tool support provided for the current refinement-based techniques, such as the B method.


Strategyproof Approximation Mechanisms for Location on Networks

Abstract: We consider the problem of locating a facility on a network, represented by a graph. A set of strategic agents have different ideal locations for the facility; the cost of an agent is the distance between its ideal location and the facility. A mechanism maps the locations reported by the agents to the location of the facility. Specifically, we are interested in social choice mechanisms that do not utilize payments. We wish to design mechanisms that are strategyproof, in the sense that agents can never benefit by lying, or, even better, group strategyproof, in the sense that a coalition of agents cannot all benefit by lying. At the same time, our mechanisms must provide a small approximation ratio with respect to one of two optimization targets: the social cost or the maximum cost. We give an almost complete characterization of the feasible truthful approximation ratio under both target functions, deterministic and randomized mechanisms, and with respect to different network topologies. Our main results are: We show that a simple randomized mechanism is group strategyproof and gives a (2-2/n)-approximation for the social cost, where n is the number of agents, when the network is a circle (known as a ring in the case of computer networks); we design a novel "hybrid" strategyproof randomized mechanism that provides a tight approximation ratio of 3/2 for the maximum cost when the network is a circle; and we show that no randomized SP mechanism can provide an approximation ratio better than 2-o(1) to the maximum cost even when the network is a tree, thereby matching a trivial upper bound of two.


Randomised Buffer Management with Bounded Delay against Adaptive Adversary

Abstract: We give a new analysis of the RMix algorithm by Chin et al. for the Buffer Management with Bounded Delay problem (or online scheduling of unit jobs to maximise weighted throughput). Unlike the original proof of e/(e-1)-competitiveness, the new one holds even in adaptive-online adversary model. In fact, the proof works also for a slightly more general problem studied by Bie{\'n}kowski et al.


A Type System For Call-By-Name Exceptions

Abstract: We present an extension of System F with call-by-name exceptions. The type system is enriched with two syntactic constructs: a union type for programs whose execution may raise an exception at top level, and a corruption type for programs that may raise an exception in any evaluation context (not necessarily at top level). We present the syntax and reduction rules of the system, as well as its typing and subtyping rules. We then study its properties, such as confluence. Finally, we construct a realizability model using orthogonality techniques, from which we deduce that well-typed programs are weakly normalizing and that the ones who have the type of natural numbers really compute a natural number, without raising exceptions.


Layered Working-Set Trees

Abstract: The working-set bound [Sleator and Tarjan, J. ACM, 1985] roughly states that searching for an element is fast if the element was accessed recently. Binary search trees, such as splay trees, can achieve this property in the amortized sense, while data structures that are not binary search trees are known to have this property in the worst case. We close this gap and present a binary search tree called a layered working-set tree that guarantees the working-set property in the worst case. The unified bound [Badoiu et al., TCS, 2007] roughly states that searching for an element is fast if it is near (in terms of rank distance) to a recently accessed element. We show how layered working-set trees can be used to achieve the unified bound to within a small additive term in the amortized sense while maintaining in the worst case an access time that is both logarithmic and within a small multiplicative factor of the working-set bound.


SMT-Based Bounded Model Checking for Embedded ANSI-C Software

Abstract: Propositional bounded model checking has been applied successfully to verify embedded software but is limited by the increasing propositional formula size and the loss of structure during the translation. These limitations can be reduced by encoding word-level information in theories richer than propositional logic and using SMT solvers for the generated verification conditions. Here, we investigate the application of different SMT solvers to the verification of embedded software written in ANSI-C. We have extended the encodings from previous SMT-based bounded model checkers to provide more accurate support for finite variables, bit-vector operations, arrays, structures, unions and pointers. We have integrated the CVC3, Boolector, and Z3 solvers with the CBMC front-end and evaluated them using both standard software model checking benchmarks and typical embedded applications from telecommunications, control systems and medical devices. The experiments show that our approach can analyze larger problems and substantially reduce the verification time.


Multiresolution Elastic Medical Image Registration in Standard Intensity Scale

Abstract: Medical image registration is a difficult problem. Not only a registration algorithm needs to capture both large and small scale image deformations, it also has to deal with global and local image intensity variations. In this paper we describe a new multiresolution elastic image registration method that challenges these difficulties in image registration. To capture large and small scale image deformations, we use both global and local affine transformation algorithms. To address global and local image intensity variations, we apply an image intensity standardization algorithm to correct image intensity variations. This transforms image intensities into a standard intensity scale, which allows highly accurate registration of medical images.


The Piranha algebraic manipulator

Abstract: In this paper we present a specialised algebraic manipulation package devoted to Celestial Mechanics. The system, called Piranha, is built on top of a generic and extensible framework, which allows to treat efficiently and in a unified way the algebraic structures most commonly encountered in Celestial Mechanics (such as multivariate polynomials and Poisson series). In this contribution we explain the architecture of the software, with special focus on the implementation of series arithmetics, show its current capabilities, and present benchmarks indicating that Piranha is competitive, performance-wise, with other specialised manipulators.


Simultaneously Sparse Solutions to Linear Inverse Problems with Multiple System Matrices and a Single Observation Vector

Abstract: A linear inverse problem is proposed that requires the determination of multiple unknown signal vectors. Each unknown vector passes through a different system matrix and the results are added to yield a single observation vector. Given the matrices and lone observation, the objective is to find a simultaneously sparse set of unknown vectors that solves the system. We will refer to this as the multiple-system single-output (MSSO) simultaneous sparsity problem. This manuscript contrasts the MSSO problem with other simultaneous sparsity problems and conducts a thorough initial exploration of algorithms with which to solve it. Seven algorithms are formulated that approximately solve this NP-Hard problem. Three greedy techniques are developed (matching pursuit, orthogonal matching pursuit, and least squares matching pursuit) along with four methods based on a convex relaxation (iteratively reweighted least squares, two forms of iterative shrinkage, and formulation as a second-order cone program). The algorithms are evaluated across three experiments: the first and second involve sparsity profile recovery in noiseless and noisy scenarios, respectively, while the third deals with magnetic resonance imaging radio-frequency excitation pulse design.


Fast In-Memory XPath Search over Compressed Text and Tree Indexes

Abstract: A large fraction of an XML document typically consists of text data. The XPath query language allows text search via the equal, contains, and starts-with predicates. Such predicates can efficiently be implemented using a compressed self-index of the document's text nodes. Most queries, however, contain some parts of querying the text of the document, plus some parts of querying the tree structure. It is therefore a challenge to choose an appropriate evaluation order for a given query, which optimally leverages the execution speeds of the text and tree indexes. Here the SXSI system is introduced; it stores the tree structure of an XML document using a bit array of opening and closing brackets, and stores the text nodes of the document using a global compressed self-index. On top of these indexes sits an XPath query engine that is based on tree automata. The engine uses fast counting queries of the text index in order to dynamically determine whether to evaluate top-down or bottom-up with respect to the tree structure. The resulting system has several advantages over existing systems: (1) on pure tree queries (without text search) such as the XPathMark queries, the SXSI system performs on par or better than the fastest known systems MonetDB and Qizx, (2) on queries that use text search, SXSI outperforms the existing systems by 1--3 orders of magnitude (depending on the size of the result set), and (3) with respect to memory consumption, SXSI outperforms all other systems for counting-only queries.


Topology Discovery Using Cisco Discovery Protocol

Abstract: In this paper we address the problem of discovering network topology in proprietary networks. Namely, we investigate topology discovery in Cisco-based networks. Cisco devices run Cisco Discovery Protocol (CDP) which holds information about these devices. We first compare properties of topologies that can be obtained from networks deploying CDP versus Spanning Tree Protocol (STP) and Management Information Base (MIB) Forwarding Database (FDB). Then we describe a method of discovering topology of CDP-based networks. Our experiments show that the physical topology of the network including links that are in Forwarding Block state can be discovered.


Algebraic properties of structured context-free languages: old approaches and novel developments

Abstract: The historical research line on the algebraic properties of structured CF languages initiated by McNaughton's Parenthesis Languages has recently attracted much renewed interest with the Balanced Languages, the Visibly Pushdown Automata languages (VPDA), the Synchronized Languages, and the Height-deterministic ones. Such families preserve to a varying degree the basic algebraic properties of Regular languages: boolean closure, closure under reversal, under concatenation, and Kleene star. We prove that the VPDA family is strictly contained within the Floyd Grammars (FG) family historically known as operator precedence. Languages over the same precedence matrix are known to be closed under boolean operations, and are recognized by a machine whose pop or push operations on the stack are purely determined by terminal letters. We characterize VPDA's as the subclass of FG having a peculiarly structured set of precedence relations, and balanced grammars as a further restricted case. The non-counting invariance property of FG has a direct implication for VPDA too.


Adaptive Point-to-Multipoint Transmission for Multimedia Broadcast Multicast Services in LTE

Abstract: This paper investigates point-to-multipoint (PTM) transmission supporting adaptive modulation and coding (AMC) as well as retransmissions based on incremental redundancy. In contrast to the classical PTM transmission which was introduced by the Multimedia Broadcast Multicast Service (MBMS), the adaptiveness requires user individual feedback channels that allow the receivers to report their radio conditions and send positive or negative acknowledgments (ACK/NACK) for a Layer 1 transport block to the eNodeB. In this work, an adaptive PTM scheme based on feedback from multiple users is presented and evaluated. Furthermore, a simple NACK-oriented feedback mechanism is introduced to relieve the feedback channel that is used in the uplink. Finally, the performance of different single-cell MBMS transmission modes is evaluated by dynamic radio network simulations. It is shown that adaptive PTM transmission outperforms the conventional MBMS configurations in terms of radio resource consumption and user satisfaction rate.


On the maximal number of highly periodic runs in a string

Abstract: A run is a maximal occurrence of a repetition $v$ with a period $p$ such that $2p \le |v|$. The maximal number of runs in a string of length $n$ was studied by several authors and it is known to be between $0.944 n$ and $1.029 n$. We investigate highly periodic runs, in which the shortest period $p$ satisfies $3p \le |v|$. We show the upper bound $0.5n$ on the maximal number of such runs in a string of length $n$ and construct a sequence of words for which we obtain the lower bound $0.406 n$.


Kernels for Feedback Arc Set In Tournaments

Abstract: A tournament T=(V,A) is a directed graph in which there is exactly one arc between every pair of distinct vertices. Given a digraph on n vertices and an integer parameter k, the Feedback Arc Set problem asks whether the given digraph has a set of k arcs whose removal results in an acyclic digraph. The Feedback Arc Set problem restricted to tournaments is known as the k-Feedback Arc Set in Tournaments (k-FAST) problem. In this paper we obtain a linear vertex kernel for k-FAST. That is, we give a polynomial time algorithm which given an input instance T to k-FAST obtains an equivalent instance T' on O(k) vertices. In fact, given any fixed e>0, the kernelized instance has at most (2+e)k vertices. Our result improves the previous known bound of O(k^2) on the kernel size for k-FAST. Our kernelization algorithm solves the problem on a subclass of tournaments in polynomial time and uses a known polynomial time approximation scheme for k-FAST.


Bit Copying - The Ultimate Computational Simplicity

Abstract: A computational abstract machine based on two operations: referencing and bit copying is presented. These operations are sufficient for carrying out any computation. They can be used as the primitives for a Turing-complete programming language. The interesting point is that the computation can be done without logic operations such as AND or OR. The compiler and emulator of this language with sample programs are available on the Internet.


Related terms search based on WordNet / Wiktionary and its application in Ontology Matching

Abstract: A set of ontology matching algorithms (for finding correspondences between concepts) is based on a thesaurus that provides the source data for the semantic distance calculations. In this wiki era, new resources may spring up and improve this kind of semantic search. In the paper a solution of this task based on Russian Wiktionary is compared to WordNet based algorithms. Metrics are estimated using the test collection, containing 353 English word pairs with a relatedness score assigned by human evaluators. The experiment shows that the proposed method is capable in principle of calculating a semantic distance between pair of words in any language presented in Russian Wiktionary. The calculation of Wiktionary based metric had required the development of the open-source Wiktionary parser software.


Network-aware Adaptation with Real-Time Channel Statistics for Wireless LAN Multimedia Transmissions in the Digital Home

Abstract: This paper suggests the use of intelligent network-aware processing agents in wireless local area network drivers to generate metrics for bandwidth estimation based on real-time channel statistics to enable wireless multimedia application adaptation. Various configurations in the wireless digital home are studied and the experimental results with performance variations are presented.


AWiMA: An architecture for Adhoc Wireless Mobile internet Access

Abstract: This paper suggests a system architecture for wireless widearea- networking access using adhoc networking between a mobile Client node without direct connectivity to a wirelesswide- area-network and a mobile Service Provider node with connectivity to a wireless-wide-area-network. It provides a means for securely providing such adhoc wireless networking services using a Server for tunneling and routing, registration and authentication. The architecture also provides support for handoff of a Client node from one Service Provider to another with persistence of a tunnel between the Client and the Server enabling a soft-handoff. Different wireless protocols may be used for adhoc networking, with filtered interconnection of authenticated Clients implemented at a Service Provider node. The architecture is applicable across different wide-areanetwork protocols, and provides simultaneous support for multiple wide-area-network protocols.


Evaluating Methods to Rediscover Missing Web Pages from the Web Infrastructure

Abstract: Missing web pages (pages that return the 404 "Page Not Found" error) are part of the browsing experience. The manual use of search engines to rediscover missing pages can be frustrating and unsuccessful. We compare four automated methods for rediscovering web pages. We extract the page's title, generate the page's lexical signature (LS), obtain the page's tags from the bookmarking website delicious.com and generate a LS from the page's link neighborhood. We use the output of all methods to query Internet search engines and analyze their retrieval performance. Our results show that both LSs and titles perform fairly well with over 60% URIs returned top ranked from Yahoo!. However, the combination of methods improves the retrieval performance. Considering the complexity of the LS generation, querying the title first and in case of insufficient results querying the LSs second is the preferable setup. This combination accounts for more than 75% top ranked URIs.


An Efficient Algorithm for Factoring Polynomials over Algebraic Extension Field

Abstract: A new efficient algorithm is proposed for factoring polynomials over an algebraic extension field. The extension field is defined by a polynomial ring modulo a maximal ideal. If the maximal ideal is given by its Groebner basis, no extra Groebner basis computation is needed for factoring a polynomial over this extension field. Nothing more than linear algebraic technique is used to get a polynomial over the ground field by a generic linear map. Then this polynomial is factorized over the ground field. From these factors, the factorization of the polynomial over the extension field is obtained. The new algorithm has been implemented and computer experiments indicate that the new algorithm is very efficient, particularly in complicated examples.


Separations of non-monotonic randomness notions

Abstract: In the theory of algorithmic randomness, several notions of random sequence are defined via a game-theoretic approach, and the notions that received most attention are perhaps Martin-Loef randomness and computable randomness. The latter notion was introduced by Schnorr and is rather natural: an infinite binary sequence is computably random if no total computable strategy succeeds on it by betting on bits in order. However, computably random sequences can have properties that one may consider to be incompatible with being random, in particular, there are computably random sequences that are highly compressible. The concept of Martin-Loef randomness is much better behaved in this and other respects, on the other hand its definition in terms of martingales is considerably less natural. Muchnik, elaborating on ideas of Kolmogorov and Loveland, refined Schnorr's model by also allowing non-monotonic strategies, i.e. strategies that do not bet on bits in order. The subsequent ``non-monotonic'' notion of randomness, now called Kolmogorov-Loveland randomness, has been shown to be quite close to Martin-Loef randomness, but whether these two classes coincide remains a fundamental open question. As suggested by Miller and Nies, we study in this paper weak versions of Kolmogorov-Loveland randomness, where the betting strategies are non-adaptive (i.e., the positions of the bits to bet on should be decided before the game). We obtain a full classification of the different notions we consider.


Cooperation in Subset Team Games: Altruism and Selfishness

Abstract: This paper extends the theory of subset team games, a generalization of cooperative game theory requiring a payoff function that is defined for all subsets of players. This subset utility is used to define both altruistic and selfish contributions of a player to the team. We investigate properties of these games, and analyze the implications of altruism and selfishness for general situations, for prisoner's dilemma, and for a specific game with a Cobb-Douglas utility.


Computing Multidimensional Persistence

Abstract: The theory of multidimensional persistence captures the topology of a multifiltration -- a multiparameter family of increasing spaces. Multifiltrations arise naturally in the topological analysis of scientific data. In this paper, we give a polynomial time algorithm for computing multidimensional persistence. We recast this computation as a problem within computational algebraic geometry and utilize algorithms from this area to solve it. While the resulting problem is Expspace-complete and the standard algorithms take doubly-exponential time, we exploit the structure inherent withing multifiltrations to yield practical algorithms. We implement all algorithms in the paper and provide statistical experiments to demonstrate their feasibility.


Sequential Posted Pricing and Multi-parameter Mechanism Design

Abstract: We consider the classical mathematical economics problem of {\em Bayesian optimal mechanism design} where a principal aims to optimize expected revenue when allocating resources to self-interested agents with preferences drawn from a known distribution. In single-parameter settings (i.e., where each agent's preference is given by a single private value for being served and zero for not being served) this problem is solved [Myerson '81]. Unfortunately, these single parameter optimal mechanisms are impractical and rarely employed [Ausubel and Milgrom '06], and furthermore the underlying economic theory fails to generalize to the important, relevant, and unsolved multi-dimensional setting (i.e., where each agent's preference is given by multiple values for each of the multiple services available) [Manelli and Vincent '07]. In contrast to the theory of optimal mechanisms we develop a theory of sequential posted price mechanisms, where agents in sequence are offered take-it-or-leave-it prices. These mechanisms are approximately optimal in single-dimensional settings, and avoid many of the properties that make optimal mechanisms impractical. Furthermore, these mechanisms generalize naturally to give the first known approximations to the elusive optimal multi-dimensional mechanism design problem. In particular, we solve multi-dimensional multi-unit auction problems and generalizations to matroid feasibility constraints. The constant approximations we obtain range from 1.5 to 8. For all but one case, our posted price sequences can be computed in polynomial time.


Pattern Based Term Extraction Using ACABIT System

Abstract: In this paper, we propose a pattern-based term extraction approach for Japanese, applying ACABIT system originally developed for French. The proposed approach evaluates termhood using morphological patterns of basic terms and term variants. After extracting term candidates, ACABIT system filters out non-terms from the candidates based on log-likelihood. This approach is suitable for Japanese term extraction because most of Japanese terms are compound nouns or simple phrasal patterns.


Benchmarking Declarative Approximate Selection Predicates

Abstract: Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize data quality primitives on top of any relational data source. A primary advantage of such an approach is the ease of use and integration with existing applications. Several similarity predicates have been proposed in the past for common quality primitives (approximate selections, joins, etc.) and have been fully expressed using declarative SQL statements. In this thesis, new similarity predicates are proposed along with their declarative realization, based on notions of probabilistic information retrieval. Then, full declarative specifications of previously proposed similarity predicates in the literature are presented, grouped into classes according to their primary characteristics. Finally, a thorough performance and accuracy study comparing a large number of similarity predicates for data cleaning operations is performed.


Extremal problems in ordered graphs

Abstract: In this thesis we consider ordered graphs (that is, graphs with a fixed linear ordering on their vertices). We summarize and further investigations on the number of edges an ordered graph may have while avoiding a fixed forbidden ordered graph as a subgraph. In particular, we take a step toward confirming a conjecture of Pach and Tardos regarding the number of edges allowed when the forbidden pattern is a tree by establishing an upper bound for a particular ordered graph for which existing techniques have failed. We also generalize a theorem of Geneson by establishing an upper bound on the number of edges allowed if the forbidden graphs fit a generalized notion of a matching.


Community Cloud Computing

Abstract: Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.


Gossip-based Search in Multipeer Communication Networks

Abstract: We study a gossip-based algorithm for searching data objects in a multipeer communication network. All of the nodes in the network are able to communicate with each other. There exists an initiator node that starts a round of searches by randomly querying one or more of its neighbors for a desired object. The queried nodes can also be activated and look for the object. We examine several behavioural patterns of nodes with respect to their willingness to cooperate in the search. We derive mathematical models for the search process based on the balls and bins model, as well as known approximations for the rumour-spreading problem. All models are validated with simulations. We also evaluate the performance of the algorithm and examine the impact of search parameters.


GMap: Drawing Graphs as Maps

Abstract: Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through dimensionality reduction techniques. However, these traditional methods often do not capture well the underlying structural information, clustering, and neighborhoods. In this paper, we describe GMap: a practical tool for visualizing relational data with geographic-like maps. We illustrate the effectiveness of this approach with examples from several domains All the maps referenced in this paper can be found in http://www.research.att.com/~yifanhu/GMap


Homogeneous formulas and symmetric polynomials

Abstract: We investigate the arithmetic formula complexity of the elementary symmetric polynomials S(k,n). We show that every multilinear homogeneous formula computing S(k,n) has size at least k^(Omega(log k))n, and that product-depth d multilinear homogeneous formulas for S(k,n) have size at least 2^(Omega(k^{1/d}))n. Since S(n,2n) has a multilinear formula of size O(n^2), we obtain a superpolynomial separation between multilinear and multilinear homogeneous formulas. We also show that S(k,n) can be computed by homogeneous formulas of size k^(O(log k))n, answering a question of Nisan and Wigderson. Finally, we present a superpolynomial separation between monotone and non-monotone formulas in the noncommutative setting, answering a question of Nisan.


Finding Fullerene Patches in Polynomial Time

Abstract: We consider the following question, motivated by the enumeration of fullerenes. A fullerene patch is a 2-connected plane graph G in which inner faces have length 5 or 6, non-boundary vertices have degree 3, and boundary vertices have degree 2 or 3. The degree sequence along the boundary is called the boundary code of G. We show that the question whether a given sequence S is a boundary code of some fullerene patch can be answered in polynomial time when such patches have at most five 5-faces. We conjecture that our algorithm gives the correct answer for any number of 5-faces, and sketch how to extend the algorithm to the problem of counting the number of different patches with a given boundary code.


Towards Hybrid Intensional Programming with JLucid, Objective Lucid, and General Imperative Compiler Framework in the GIPSY

Abstract: Pure Lucid programs are concurrent with very fine granularity. Sequential Threads (STs) are functions introduced to enlarge the grain size; they are passed from server to workers by Communication Procedures (CPs) in the General Intensional Programming System (GIPSY). A JLucid program combines Java code for the STs with Lucid code for parallel control. Thus first, in this thesis, we describe the way in which the new JLucid compiler generates STs and CPs. JLucid also introduces array support. Further exploration goes through the additional transformations that the Lucid family of languages has undergone to enable the use of Java objects and their members, in the Generic Intensional Programming Language (GIPL), and Indexical Lucid: first, in the form of JLucid allowing the use of pseudo-objects, and then through the specifically-designed the Objective Lucid language. The syntax and semantic definitions of Objective Lucid and the meaning of Java objects within an intensional program are provided with discussions and examples. Finally, there are many useful scientific and utility routines written in many imperative programming languages other than Java, for example in C, C++, Fortran, Perl, etc. Therefore, it is wise to provide a framework to facilitate inclusion of these languages into the GIPSY and their use by Lucid programs. A General Imperative Compiler Framework and its concrete implementation is proposed to address this issue.


The Complexity of Approximating Bounded-Degree Boolean \sharp CSP

Abstract: The degree of a CSP instance is the maximum number of times that any variable appears in the scopes of constraints. We consider the approximate counting problem for Boolean CSP with bounded-degree instances, for constraint languages containing the two unary constant relations {0} and {1}. When the maximum allowed degree is large enough (at least 6) we obtain a complete classification of the complexity of this problem. It is exactly solvable in polynomial-time if every relation in the constraint language is affine. It is equivalent to the problem of approximately counting independent sets in bipartite graphs if every relation can be expressed as conjunctions of {0}, {1} and binary implication. Otherwise, there is no FPRAS unless NP=RP. For lower degree bounds, additional cases arise, where the complexity is related to the complexity of approximately counting independent sets in hypergraphs.


Bounded Delay Packet Scheduling in a Bounded Buffer

Abstract: We study the problem of buffer management in QoS-enabled network switches in the bounded delay model where each packet is associated with a weight and a deadline. We consider the more realistic situation where the network switch has a finite buffer size. A 9.82-competitive algorithm is known for the case of multiple buffers (Azar and Levy, SWAT'06). Recently, for the case of a single buffer, a 3-competitive deterministic algorithm and a 2.618-competitive randomized algorithm was known (Li, INFOCOM'09). In this paper we give a simple deterministic 2-competitive algorithm for the case of a single buffer.


The Visualization of the Road Coloring Algorithm in the package TESTAS

Abstract: A synchronizing word of a deterministic automaton is a word in the alphabet of colors of its edges that maps the automaton to a single state. A coloring of edges of a directed graph is synchronizing if the coloring turns the graph into a deterministic finite automaton possessing a synchronizing word. The road coloring problem is the problem of synchronizing coloring of a directed finite strongly connected graph with constant outdegree of all its vertices if the greatest common divisor of the lengths of all its cycles is one. A polynomial time algorithm of the road coloring has been based on recent positive solution of this old famous problem. One can use our new visualization program for demonstration of the algorithm as well as for visualization of the transition graph of any finite automaton. The visual image presents some structure properties of the transition graph. This help tool is linear in the size of the automaton.


On Cyclic and Nearly Cyclic Multiagent Interactions in the Plane

Abstract: We discuss certain types of cyclic and nearly cyclic interactions among N "point"-agents in the plane, leading to formations of interesting limiting geometric configurations. Cyclic pursuit and local averaging interactions have been analyzed in the context of multi-agent gathering. In this paper, we consider some nearly cyclic interactions that break symmetry leading to factor circulants rather than circulant interaction matrices.


Modelling Concurrent Behaviors in the Process Specification Language

Abstract: In this paper, we propose a first-order ontology for generalized stratified order structure. We then classify the models of the theory using model-theoretic techniques. An ontology mapping from this ontology to the core theory of Process Specification Language is also discussed.


Scalable Probabilistic Similarity Ranking in Uncertain Databases (Technical Report)

Abstract: This paper introduces a scalable approach for probabilistic top-k similarity ranking on uncertain vector data. Each uncertain object is represented by a set of vector instances that are assumed to be mutually-exclusive. The objective is to rank the uncertain data according to their distance to a reference object. We propose a framework that incrementally computes for each object instance and ranking position, the probability of the object falling at that ranking position. The resulting rank probability distribution can serve as input for several state-of-the-art probabilistic ranking models. Existing approaches compute this probability distribution by applying a dynamic programming approach of quadratic complexity. In this paper we theoretically as well as experimentally show that our framework reduces this to a linear-time complexity while having the same memory requirements, facilitated by incremental accessing of the uncertain vector instances in increasing order of their distance to the reference object. Furthermore, we show how the output of our method can be used to apply probabilistic top-k ranking for the objects, according to different state-of-the-art definitions. We conduct an experimental evaluation on synthetic and real data, which demonstrates the efficiency of our approach.


4G Wireless Networks: Opportunities and Challenges

Abstract: With the major wireless service providers planning to start deployment of 4G wireless networks by mid 2010, research and industry communities are racing against time to find solutions for some of the prominent still open issues in 4G networks. The growing interest in 4G networks is driven by the set of new services will be made available for the first time such as accessing the Internet anytime from anywhere, global roaming, and wider support for multimedia applications. In this paper describe some of the key opportunities will be made available by 4G networks, present key challenges and point to some proposed solutions.


Distributed anonymous function computation in information fusion and multiagent systems

Abstract: We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes, with bounded computation and storage capabilities that do not scale with the network size. Our goal is to characterize the class of functions that can be computed within this model. In our main result, we exhibit a class of non-computable functions, and prove that every function outside this class can at least be approximated. The problem of computing averages in a distributed manner plays a central role in our development.


Untangling the Braid: Finding Outliers in a Set of Streams

Abstract: Monitoring the performance of large shared computing systems such as the cloud computing infrastructure raises many challenging algorithmic problems. One common problem is to track users with the largest deviation from the norm (outliers), for some measure of performance. Taking a stream-computing perspective, we can think of each user's performance profile as a stream of numbers (such as response times), and the aggregate performance profile of the shared infrastructure as a "braid" of these intermixed streams. The monitoring system's goal then is to untangle this braid sufficiently to track the top k outliers. This paper investigates the space complexity of one-pass algorithms for approximating outliers of this kind, proves lower bounds using multi-party communication complexity, and proposes small-memory heuristic algorithms. On one hand, stream outliers are easily tracked for simple measures, such as max or min, but our theoretical results rule out even good approximations for most of the natural measures such as average, median, or the quantiles. On the other hand, we show through simulation that our proposed heuristics perform quite well for a variety of synthetic data.


Service-Oriented Architectures and Web Services: Course Tutorial and Lab Notes

Abstract: This document presents a number of quick-step instructions to get started on writing mini-service-oriented web services-based applications using OpenESB 2.31, Tomcat 6, GlassFish 2.x/3.0.1 with BPEL support, and Java 1.6+ primarily in Scientific Linux 6.6 with user quota restrictions. While the tutorial notes are oriented towards the students taking the SOEN487 on service-oriented architectures (SOA) at Computer Science and Software Engineering (CSE) Department, Faculty of Engineering and Computer Science (ENCS), other may find some of it useful as well outside of CSE or Concordia. The notes are compiled mostly based on the students' needs and feedback.