Amdahl's and Gustafson-Barsis laws revisited

Abstract: The paper presents a simple derivation of the Gustafson-Barsis law from the Amdahl's law. In the computer literature these two laws describing the speedup limits of parallel applications are derived separately. It is shown, that treating the time of the execution of the sequential part of the application as a constant, in few lines the Gustafson-Barsis law can be obtained from the Amdahl's law and that the popular claim, that Gustafson-Barsis law overthrows Amdahl's law is a mistake.


Sector and Sphere: Towards Simplified Storage and Processing of Large Scale Distributed Data

Abstract: Cloud computing has demonstrated that processing very large datasets over commodity clusters can be done simply given the right programming model and infrastructure. In this paper, we describe the design and implementation of the Sector storage cloud and the Sphere compute cloud. In contrast to existing storage and compute clouds, Sector can manage data not only within a data center, but also across geographically distributed data centers. Similarly, the Sphere compute cloud supports User Defined Functions (UDF) over data both within a data center and across data centers. As a special case, MapReduce style programming can be implemented in Sphere by using a Map UDF followed by a Reduce UDF. We describe some experimental studies comparing Sector/Sphere and Hadoop using the Terasort Benchmark. In these studies, Sector is about twice as fast as Hadoop. Sector/Sphere is open source.


Bounded Underapproximations

Abstract: We show a new and constructive proof of the following language-theoretic result: for every context-free language L, there is a bounded context-free language L' included in L which has the same Parikh (commutative) image as L. Bounded languages, introduced by Ginsburg and Spanier, are subsets of regular languages of the form w1*w2*...wk* for some finite words w1,...,wk. In particular bounded subsets of context-free languages have nice structural and decidability properties. Our proof proceeds in two parts. First, using Newton's iterations on the language semiring, we construct a context-free subset Ls of L that can be represented as a sequence of substitutions on a linear language and has the same Parikh image as L. Second, we inductively construct a Parikh-equivalent bounded context-free subset of Ls. We show two applications of this result in model checking: to underapproximate the reachable state space of multithreaded procedural programs and to underapproximate the reachable state space of recursive counter programs. The bounded language constructed above provides a decidable underapproximation for the original problems. By iterating the construction, we get a semi-algorithm for the original problems that constructs a sequence of underapproximations such that no two underapproximations of the sequence can be compared. This provides a progress guarantee: every word w in L is in some underapproximation of the sequence. In addition, we show that our approach subsumes context-bounded reachability for multithreaded programs.


A Fuzzy Commitment Scheme

Abstract: This paper attempt has been made to explain a fuzzy commitment scheme. In the conventional Commitment schemes, both committed string m and valid opening key are required to enable the sender to prove the commitment. However there could be many instances where the transmission involves noise or minor errors arising purely because of the factors over which neither the sender nor the receiver have any control. The fuzzy commitment scheme presented in this paper is to accept the opening key that is close to the original one in suitable distance metric, but not necessarily identical. The concept itself is illustrated with the help of simple situation.


Domain Specific Software Architecture for Design Center Automation

Abstract: Domain specific software architecture aims at software reuse through construction of domain architecture reference model. The constructed reference model presents a set of individual components and their interaction points. When starting on a new large software project, the design engineer starts with pre-constructed model, which can be easily browsed and picks up opportunities of use in the new solution design. This report discusses application of domain reference design methods by deriving domain specific reference architecture for a product ordering system in a design center. The product in this case is instock and special order blinds from different manufacturers in a large supply store. The development of mature domain specific reference software architecture for this domain is not the objective of this report. However, this report would like to capture the method used in one such process and that is the primary concern of this report. This report lists subjective details of such a process applied to the domain of ordering custom and instock blinds from a large home construction and goods supply store. This report also describes the detailed process of derivation of knowledge models, unified knowledge models and the reference architecture for this domain. However, this domain model is only partially complete which may not be used for any real applications. This report is a result of a course project undertaken while studying this methodology.


How applicable is Python as first computer language for teaching programming in a pre-university educational environment, from a teacher's point of view?

Abstract: This project report attempts to evaluate the educational properties of the Python computer language, in practice. This is done by examining computer language evolution history, related scientific background work, the existing educational research on computer languages and Python's experimental application in higher secondary education in Greece, during first half of year 2002. This Thesis Report was delivered in advance of a thesis defense for a Masters/Doctorandus (MSc/Drs) title with the Amstel Institute/Universiteit van Amsterdam, during the same year.


Probabilistic Systems with LimSup and LimInf Objectives

Abstract: We give polynomial-time algorithms for computing the values of Markov decision processes (MDPs) with limsup and liminf objectives. A real-valued reward is assigned to each state, and the value of an infinite path in the MDP is the limsup (resp. liminf) of all rewards along the path. The value of an MDP is the maximal expected value of an infinite path that can be achieved by resolving the decisions of the MDP. Using our result on MDPs, we show that turn-based stochastic games with limsup and liminf objectives can be solved in NP \cap coNP.


Obtaining Exact Interpolation Multivariate Polynomial by Approximation

Abstract: In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In order to improve the situation, exactly interpolating methods are often proposed for the exact results and approximate interpolating methods for the approximate ones. In this paper, we study how to obtain exact interpolation polynomial with rational coefficients by approximate interpolating methods.


An optimal local approximation algorithm for max-min linear programs

Abstract: We present a local algorithm (constant-time distributed algorithm) for approximating max-min LPs. The objective is to maximise $\omega$ subject to $Ax \le 1$, $Cx \ge \omega 1$, and $x \ge 0$ for nonnegative matrices $A$ and $C$. The approximation ratio of our algorithm is the best possible for any local algorithm; there is a matching unconditional lower bound.


Consistent Query Answers in the Presence of Universal Constraints

Abstract: The framework of consistent query answers and repairs has been introduced to alleviate the impact of inconsistent data on the answers to a query. A repair is a minimally different consistent instance and an answer is consistent if it is present in every repair. In this article we study the complexity of consistent query answers and repair checking in the presence of universal constraints. We propose an extended version of the conflict hypergraph which allows to capture all repairs w.r.t. a set of universal constraints. We show that repair checking is in PTIME for the class of full tuple-generating dependencies and denial constraints, and we present a polynomial repair algorithm. This algorithm is sound, i.e. always produces a repair, but also complete, i.e. every repair can be constructed. Next, we present a polynomial-time algorithm computing consistent answers to ground quantifier-free queries in the presence of denial constraints, join dependencies, and acyclic full-tuple generating dependencies. Finally, we show that extending the class of constraints leads to intractability. For arbitrary full tuple-generating dependencies consistent query answering becomes coNP-complete. For arbitrary universal constraints consistent query answering is \Pi_2^p-complete and repair checking coNP-complete.


A computer verified, monadic, functional implementation of the integral

Abstract: We provide a computer verified exact monadic functional implementation of the Riemann integral in type theory. Together with previous work by O'Connor, this may be seen as the beginning of the realization of Bishop's vision to use constructive mathematics as a programming language for exact analysis.


When is there a representer theorem? Vector versus matrix regularizers

Abstract: We consider a general class of regularization methods which learn a vector of parameters on the basis of linear measurements. It is well known that if the regularizer is a nondecreasing function of the inner product then the learned vector is a linear combination of the input data. This result, known as the {\em representer theorem}, is at the basis of kernel-based methods in machine learning. In this paper, we prove the necessity of the above condition, thereby completing the characterization of kernel methods based on regularization. We further extend our analysis to regularization methods which learn a matrix, a problem which is motivated by the application to multi-task learning. In this context, we study a more general representer theorem, which holds for a larger class of regularizers. We provide a necessary and sufficient condition for these class of matrix regularizers and highlight them with some concrete examples of practical importance. Our analysis uses basic principles from matrix theory, especially the useful notion of matrix nondecreasing function.


ECOLANG - Communications Language for Ecological Simulations Network

Abstract: This document describes the communication language used in one multiagent system environment for ecological simulations, based on EcoDynamo simulator application linked with several intelligent agents and visualisation applications, and extends the initial definition of the language. The agents actions and perceptions are translated into messages exchanged with the simulator application and other agents. The concepts and definitions used follow the BNF notation (Backus et al. 1960) and is inspired in the Coach Unilang language (Reis and Lau 2002).


Computing with Classical Real Numbers

Abstract: There are two incompatible Coq libraries that have a theory of the real numbers; the Coq standard library gives an axiomatic treatment of classical real numbers, while the CoRN library from Nijmegen defines constructively valid real numbers. Unfortunately, this means results about one structure cannot easily be used in the other structure. We present a way interfacing these two libraries by showing that their real number structures are isomorphic assuming the classical axioms already present in the standard library reals. This allows us to use O'Connor's decision procedure for solving ground inequalities present in CoRN to solve inequalities about the reals from the Coq standard library, and it allows theorems from the Coq standard library to apply to problem about the CoRN reals.


A Tiered Security System for Mobile Devices

Abstract: We have designed a tiered security system for mobile devices where each security tier holds user-defined security triggers and actions. It has a friendly interface that allows users to easily define and configure the different circumstances and actions they need according to context. The system can be set up and activated from any browser or directly on the mobile device itself. When the security system is operated from a Web site or server, its configuration can be readily shared across multiple devices. When operated directly from the mobile device, no server is needed for activation. Many different types of security circumstances and actions can be set up and employed from its tiers. Security circumstances can range from temporary misplacement of a mobile device at home to malicious theft in a hostile region. Security actions can range from ringing a simple alarm to automatically erasing, overwriting, and re-erasing drives.


Multirate Anypath Routing in Wireless Mesh Networks

Abstract: In this paper, we present a new routing paradigm that generalizes opportunistic routing in wireless mesh networks. In multirate anypath routing, each node uses both a set of next hops and a selected transmission rate to reach a destination. Using this rate, a packet is broadcast to the nodes in the set and one of them forwards the packet on to the destination. To date, there is no theory capable of jointly optimizing both the set of next hops and the transmission rate used by each node. We bridge this gap by introducing a polynomial-time algorithm to this problem and provide the proof of its optimality. The proposed algorithm runs in the same running time as regular shortest-path algorithms and is therefore suitable for deployment in link-state routing protocols. We conducted experiments in a 802.11b testbed network, and our results show that multirate anypath routing performs on average 80% and up to 6.4 times better than anypath routing with a fixed rate of 11 Mbps. If the rate is fixed at 1 Mbps instead, performance improves by up to one order of magnitude.


Agent-based Ecological Model Calibration - on the Edge of a New Approach

Abstract: The purpose of this paper is to present a new approach to ecological model calibration -- an agent-based software. This agent works on three stages: 1- It builds a matrix that synthesizes the inter-variable relationships; 2- It analyses the steady-state sensitivity of different variables to different parameters; 3- It runs the model iteratively and measures model lack of fit, adequacy and reliability. Stage 3 continues until some convergence criteria are attained. At each iteration, the agent knows from stages 1 and 2, which parameters are most likely to produce the desired shift on predicted results.


Circumference, Chromatic Number and Online Coloring

Abstract: Erd\"os conjectured that if $G$ is a triangle free graph of chromatic number at least $k\geq 3$, then it contains an odd cycle of length at least $k^{2-o(1)}$ \cite{sudakovverstraete, verstraete}. Nothing better than a linear bound (\cite{gyarfas}, Problem 5.1.55 in \cite{West}) was so far known. We make progress on this conjecture by showing that $G$ contains an odd cycle of length at least $O(k\log\log k)$. Erd\"os' conjecture is known to hold for graphs with girth at least 5. We show that if a girth 4 graph is $C_5$ free, then Erd\"os' conjecture holds. When the number of vertices is not too large we can prove better bounds on $\chi$. We also give bounds on the chromatic number of graphs with at most $r$ cycles of length $1\bmod k$, or at most $s$ cycles of length $2\bmod k$, or no cycles of length $3\bmod k$. Our techniques essentially consist of using a depth first search tree to decompose the graph into ordered paths, which are then fed to an online coloring algorithm. Using this technique we give simple proofs of some old results, and also obtain several simpler results. We also obtain a lower bound on the number of colors an online coloring algorithm needs to use on triangle free graphs.


Improved Smoothed Analysis of the k-Means Method

Abstract: The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving a gap between practical and theoretical performance. Arthur and Vassilvitskii (FOCS 2006) aimed at closing this gap, and they proved a bound of $\poly(n^k, \sigma^{-1})$ on the smoothed running-time of the k-means method, where n is the number of data points and $\sigma$ is the standard deviation of the Gaussian perturbation. This bound, though better than the worst-case bound, is still much larger than the running-time observed in practice. We improve the smoothed analysis of the k-means method by showing two upper bounds on the expected running-time of k-means. First, we prove that the expected running-time is bounded by a polynomial in $n^{\sqrt k}$ and $\sigma^{-1}$. Second, we prove an upper bound of $k^{kd} \cdot \poly(n, \sigma^{-1})$, where d is the dimension of the data space. The polynomial is independent of k and d, and we obtain a polynomial bound for the expected running-time for $k, d \in O(\sqrt{\log n/\log \log n})$. Finally, we show that k-means runs in smoothed polynomial time for one-dimensional instances.


Cellular Automata as a Model of Physical Systems

Abstract: Cellular Automata (CA), as they are presented in the literature, are abstract mathematical models of computation. In this pa- per we present an alternate approach: using the CA as a model or theory of physical systems and devices. While this approach abstracts away all details of the underlying physical system, it remains faithful to the fact that there is an underlying physical reality which it describes. This imposes certain restrictions on the types of computations a CA can physically carry out, and the resources it needs to do so. In this paper we explore these and other consequences of our reformalization.


Automatic Identification and Data Extraction from 2-Dimensional Plots in Digital Documents

Abstract: Most search engines index the textual content of documents in digital libraries. However, scholarly articles frequently report important findings in figures for visual impact and the contents of these figures are not indexed. These contents are often invaluable to the researcher in various fields, for the purposes of direct comparison with their own work. Therefore, searching for figures and extracting figure data are important problems. To the best of our knowledge, there exists no tool to automatically extract data from figures in digital documents. If we can extract data from these images automatically and store them in a database, an end-user can query and combine data from multiple digital documents simultaneously and efficiently. We propose a framework based on image analysis and machine learning to extract information from 2-D plot images and store them in a database. The proposed algorithm identifies a 2-D plot and extracts the axis labels, legend and the data points from the 2-D plot. We also segregate overlapping shapes that correspond to different data points. We demonstrate performance of individual algorithms, using a combination of generated and real-life images.


The complexity of counting solutions to Generalised Satisfiability Problems modulo k

Abstract: Generalised Satisfiability Problems (or Boolean Constraint Satisfaction Problems), introduced by Schaefer in 1978, are a general class of problem which allow the systematic study of the complexity of satisfiability problems with different types of constraints. In 1979, Valiant introduced the complexity class parity P, the problem of counting the number of solutions to NP problems modulo two. Others have since considered the question of counting modulo other integers. We give a dichotomy theorem for the complexity of counting the number of solutions to Generalised Satisfiability Problems modulo integers. This follows from an earlier result of Creignou and Hermann which gave a counting dichotomy for these types of problem, and the dichotomy itself is almost identical. Specifically, counting the number of solutions to a Generalised Satisfiability Problem can be done in polynomial time if all the relations are affine. Otherwise, except for one special case with k = 2, it is #_kP-complete.


Thinking Twice about Second-Price Ad Auctions

Abstract: Recent work has addressed the algorithmic problem of allocating advertisement space for keywords in sponsored search auctions so as to maximize revenue, most of which assume that pricing is done via a first-price auction. This does not realistically model the Generalized Second Price (GSP) auction used in practice, in which bidders pay the next-highest bid for keywords that they are allocated. Towards the goal of more realistically modeling these auctions, we introduce the Second-Price Ad Auctions problem, in which bidders' payments are determined by the GSP mechanism. We show that the complexity of the Second-Price Ad Auctions problem is quite different than that of the more studied First-Price Ad Auctions problem. First, unlike the first-price variant, for which small constant-factor approximations are known, it is NP-hard to approximate the Second-Price Ad Auctions problem to any non-trivial factor, even when the bids are small compared to the budgets. Second, this discrepancy extends even to the 0-1 special case that we call the Second-Price Matching problem (2PM). Offline 2PM is APX-hard, and for online 2PM there is no deterministic algorithm achieving a non-trivial competitive ratio and no randomized algorithm achieving a competitive ratio better than 2. This contrasts with the results for the analogous special case in the first-price model, the standard bipartite matching problem, which is solvable in polynomial time and which has deterministic and randomized online algorithms achieving better competitive ratios. On the positive side, we provide a 2-approximation for offline 2PM and a 5.083-competitive randomized algorithm for online 2PM. The latter result makes use of a new generalization of a result on the performance of the "Ranking" algorithm for online bipartite matching.


Fast C-K-R Partitions of Sparse Graphs

Abstract: We present fast algorithms for constructing probabilistic embeddings and approximate distance oracles in sparse graphs. The main ingredient is a fast algorithm for sampling the probabilistic partitions of Calinescu, Karloff, and Rabani in sparse graphs.


Betweenness Centrality : Algorithms and Lower Bounds

Abstract: One of the most fundamental problems in large scale network analysis is to determine the importance of a particular node in a network. Betweenness centrality is the most widely used metric to measure the importance of a node in a network. In this paper, we present a randomized parallel algorithm and an algebraic method for computing betweenness centrality of all nodes in a network. We prove that any path-comparison based algorithm cannot compute betweenness in less than O(nm) time.


Randomized Distributed Configuration Management of Wireless Networks: Multi-layer Markov Random Fields and Near-Optimality

Abstract: Distributed configuration management is imperative for wireless infrastructureless networks where each node adjusts locally its physical and logical configuration through information exchange with neighbors. Two issues remain open. The first is the optimality. The second is the complexity. We study these issues through modeling, analysis, and randomized distributed algorithms. Modeling defines the optimality. We first derive a global probabilistic model for a network configuration which characterizes jointly the statistical spatial dependence of a physical- and a logical-configuration. We then show that a local model which approximates the global model is a two-layer Markov Random Field or a random bond model. The complexity of the local model is the communication range among nodes. The local model is near-optimal when the approximation error to the global model is within a given error bound. We analyze the trade-off between an approximation error and complexity, and derive sufficient conditions on the near-optimality of the local model. We validate the model, the analysis and the randomized distributed algorithms also through simulation.


Protocol Channels

Abstract: Covert channel techniques are used by attackers to transfer data in a way prohibited by the security policy. There are two main categories of covert channels: timing channels and storage channels. This paper introduces a new storage channel technique called a protocol channel. A protocol channel switches one of at least two protocols to send a bit combination to a destination. The main goal of a protocol channel is that packets containing covert information look equal to all other packets within a network, what makes a protocol channel hard to detect.


Materialized View Selection by Query Clustering in XML Data Warehouses

Abstract: XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native XML database management systems currently bear limited performances and it is necessary to design strategies to optimize them. In this paper, we propose an automatic strategy for the selection of XML materialized views that exploits a data mining technique, more precisely the clustering of the query workload. To validate our strategy, we implemented an XML warehouse modeled along the XCube specifications. We executed a workload of XQuery decision-support queries on this warehouse, with and without using our strategy. Our experimental results demonstrate its efficiency, even when queries are complex.


Dynamic index selection in data warehouses

Abstract: Analytical queries defined on data warehouses are complex and use several join operations that are very costly, especially when run on very large data volumes. To improve response times, data warehouse administrators casually use indexing techniques. This task is nevertheless complex and fastidious. In this paper, we present an automatic, dynamic index selection method for data warehouses that is based on incremental frequent itemset mining from a given query workload. The main advantage of this approach is that it helps update the set of selected indexes when workload evolves instead of recreating it from scratch. Preliminary experimental results illustrate the efficiency of this approach, both in terms of performance enhancement and overhead.


Knowledge and Metadata Integration for Warehousing Complex Data

Abstract: With the ever-growing availability of so-called complex data, especially on the Web, decision-support systems such as data warehouses must store and process data that are not only numerical or symbolic. Warehousing and analyzing such data requires the joint exploitation of metadata and domain-related knowledge, which must thereby be integrated. In this paper, we survey the types of knowledge and metadata that are needed for managing complex data, discuss the issue of knowledge and metadata integration, and propose a CWM-compliant integration solution that we incorporate into an XML complex data warehousing framework we previously designed.


A Join Index for XML Data Warehouses

Abstract: XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native-XML database management systems (DBMSs) currently bear limited performances and it is necessary to research for ways to optimize them. In this paper, we propose a new join index that is specifically adapted to the multidimensional architecture of XML warehouses. It eliminates join operations while preserving the information contained in the original warehouse. A theoretical study and experimental results demonstrate the efficiency of our join index. They also show that native XML DBMSs can compete with XML-compatible, relational DBMSs when warehousing and analyzing XML data.


Distributing Labels on Infinite Trees

Abstract: Sturmian words are infinite binary words with many equivalent definitions: They have a minimal factor complexity among all aperiodic sequences; they are balanced sequences (the labels 0 and 1 are as evenly distributed as possible) and they can be constructed using a mechanical definition. All this properties make them good candidates for being extremal points in scheduling problems over two processors. In this paper, we consider the problem of generalizing Sturmian words to trees. The problem is to evenly distribute labels 0 and 1 over infinite trees. We show that (strongly) balanced trees exist and can also be constructed using a mechanical process as long as the tree is irrational. Such trees also have a minimal factor complexity. Therefore they bring the hope that extremal scheduling properties of Sturmian words can be extended to such trees, as least partially. Such possible extensions are illustrated by one such example.


Weyl's Predicative Classical Mathematics as a Logic-Enriched Type Theory

Abstract: We construct a logic-enriched type theory LTTW that corresponds closely to the predicative system of foundations presented by Hermann Weyl in Das Kontinuum. We formalise many results from that book in LTTW, including Weyl's definition of the cardinality of a set and several results from real analysis, using the proof assistant Plastic that implements the logical framework LF. This case study shows how type theory can be used to represent a non-constructive foundation for mathematics.


Low congestion online routing and an improved mistake bound for online prediction of graph labeling

Abstract: In this paper, we show a connection between a certain online low-congestion routing problem and an online prediction of graph labeling. More specifically, we prove that if there exists a routing scheme that guarantees a congestion of $\alpha$ on any edge, there exists an online prediction algorithm with mistake bound $\alpha$ times the cut size, which is the size of the cut induced by the label partitioning of graph vertices. With previous known bound of $O(\log n)$ for $\alpha$ for the routing problem on trees with $n$ vertices, we obtain an improved prediction algorithm for graphs with high effective resistance. In contrast to previous approaches that move the graph problem into problems in vector space using graph Laplacian and rely on the analysis of the perceptron algorithm, our proof are purely combinatorial. Further more, our approach directly generalizes to the case where labels are not binary.


Clustered Multi-Task Learning: A Convex Formulation

Abstract: In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from the others. In the context of learning linear functions for supervised classification or regression, this can be achieved by including a priori information about the weight vectors associated with the tasks, and how they are expected to be related to each other. In this paper, we assume that tasks are clustered into groups, which are unknown beforehand, and that tasks within a group have similar weight vectors. We design a new spectral norm that encodes this a priori assumption, without the prior knowledge of the partition of tasks into groups, resulting in a new convex optimization formulation for multi-task learning. We show in simulations on synthetic examples and on the IEDB MHC-I binding dataset, that our approach outperforms well-known convex methods for multi-task learning, as well as related non convex methods dedicated to the same problem.


An approximation algorithm for approximation rank

Abstract: One of the strongest techniques available for showing lower bounds on quantum communication complexity is the logarithm of the approximation rank of the communication matrix--the minimum rank of a matrix which is entrywise close to the communication matrix. This technique has two main drawbacks: it is difficult to compute, and it is not known to lower bound quantum communication complexity with entanglement. Linial and Shraibman recently introduced a norm, called gamma_2^{alpha}, to quantum communication complexity, showing that it can be used to lower bound communication with entanglement. Here the parameter alpha is a measure of approximation which is related to the allowable error probability of the protocol. This bound can be written as a semidefinite program and gives bounds at least as large as many techniques in the literature, although it is smaller than the corresponding alpha-approximation rank, rk_alpha. We show that in fact log gamma_2^{alpha}(A)$ and log rk_{alpha}(A)$ agree up to small factors. As corollaries we obtain a constant factor polynomial time approximation algorithm to the logarithm of approximate rank, and that the logarithm of approximation rank is a lower bound for quantum communication complexity with entanglement.


Algorithms for Locating Constrained Optimal Intervals

Abstract: In this work, we obtain the following new results. 1. Given a sequence $D=((h_1,s_1), (h_2,s_2) ..., (h_n,s_n))$ of number pairs, where $s_i>0$ for all $i$, and a number $L_h$, we propose an O(n)-time algorithm for finding an index interval $[i,j]$ that maximizes $\frac{\sum_{k=i}^{j} h_k}{\sum_{k=i}^{j} s_k}$ subject to $\sum_{k=i}^{j} h_k \geq L_h$. 2. Given a sequence $D=((h_1,s_1), (h_2,s_2) ..., (h_n,s_n))$ of number pairs, where $s_i=1$ for all $i$, and an integer $L_s$ with $1\leq L_s\leq n$, we propose an $O(n\frac{T(L_s^{1/2})}{L_s^{1/2}})$-time algorithm for finding an index interval $[i,j]$ that maximizes $\frac{\sum_{k=i}^{j} h_k}{\sqrt{\sum_{k=i}^{j} s_k}}$ subject to $\sum_{k=i}^{j} s_k \geq L_s$, where $T(n')$ is the time required to solve the all-pairs shortest paths problem on a graph of $n'$ nodes. By the latest result of Chan \cite{Chan}, $T(n')=O(n'^3 \frac{(\log\log n')^3}{(\log n')^2})$, so our algorithm runs in subquadratic time $O(nL_s\frac{(\log\log L_s)^3}{(\log L_s)^2})$.


The Potluck Problem

Abstract: This paper proposes the Potluck Problem as a model for the behavior of independent producers and consumers under standard economic assumptions, as a problem of resource allocation in a multi-agent system in which there is no explicit communication among the agents.


Fairness in Combinatorial Auctioning Systems

Abstract: One of the Multi-Agent Systems that is widely used by various government agencies, buyers and sellers in a market economy, in such a manner so as to attain optimized resource allocation, is the Combinatorial Auctioning System (CAS). We study another important aspect of resource allocations in CAS, namely fairness. We present two important notions of fairness in CAS, extended fairness and basic fairness. We give an algorithm that works by incorporating a metric to ensure fairness in a CAS that uses the Vickrey-Clark-Groves (VCG) mechanism, and uses an algorithm of Sandholm to achieve optimality. Mathematical formulations are given to represent measures of extended fairness and basic fairness.


On (Omega-)Regular Model Checking

Abstract: Checking infinite-state systems is frequently done by encoding infinite sets of states as regular languages. Computing such a regular representation of, say, the set of reachable states of a system requires acceleration techniques that can finitely compute the effect of an unbounded number of transitions. Among the acceleration techniques that have been proposed, one finds both specific and generic techniques. Specific techniques exploit the particular type of system being analyzed, e.g. a system manipulating queues or integers, whereas generic techniques only assume that the transition relation is represented by a finite-state transducer, which has to be iterated. In this paper, we investigate the possibility of using generic techniques in cases where only specific techniques have been exploited so far. Finding that existing generic techniques are often not applicable in cases easily handled by specific techniques, we have developed a new approach to iterating transducers. This new approach builds on earlier work, but exploits a number of new conceptual and algorithmic ideas, often induced with the help of experiments, that give it a broad scope, as well as good performances.


A Log-space Algorithm for Canonization of Planar Graphs

Abstract: Graph Isomorphism is the prime example of a computational problem with a wide difference between the best known lower and upper bounds on its complexity. We bridge this gap for a natural and important special case, planar graph isomorphism, by presenting an upper bound that matches the known logspace hardness [Lindell'92]. In fact, we show the formally stronger result that planar graph canonization is in logspace. This improves the previously known upper bound of AC1 [MillerReif'91]. Our algorithm first constructs the biconnected component tree of a connected planar graph and then refines each biconnected component into a triconnected component tree. The next step is to logspace reduce the biconnected planar graph isomorphism and canonization problems to those for 3-connected planar graphs, which are known to be in logspace by [DattaLimayeNimbhorkar'08]. This is achieved by using the above decomposition, and by making significant modifications to Lindell's algorithm for tree canonization, along with changes in the space complexity analysis. The reduction from the connected case to the biconnected case requires further new ideas, including a non-trivial case analysis and a group theoretic lemma to bound the number of automorphisms of a colored 3-connected planar graph. This lemma is crucial for the reduction to work in logspace.


An Energy-Aware On-Demand Routing Protocol for Ad-Hoc Wireless Networks

Abstract: An ad-hoc wireless network is a collection of nodes that come together to dynamically create a network, with no fixed infrastructure or centralized administration. An ad-hoc network is characterized by energy constrained nodes, bandwidth constrained links and dynamic topology. With the growing use of wireless networks (including ad-hoc networks) for real-time applications, such as voice, video, and real-time data, the need for Quality of Service (QoS) guarantees in terms of delay, bandwidth, and packet loss is becoming increasingly important. Providing QoS in ad-hoc networks is a challenging task because of dynamic nature of network topology and imprecise state information. Hence, it is important to have a dynamic routing protocol with fast re-routing capability, which also provides stable route during the life-time of the flows. In this thesis, we have proposed a novel, energy aware, stable routing protocol named, Stability-based QoS-capable Ad-hoc On-demand Distance Vector (SQ-AODV), which is an enhancement of the well-known Ad-hoc On-demand Distance Vector (AODV) routing protocol for ad-hoc wireless networks. SQ-AODV utilizes a cross-layer design approach in which information about the residual energy of a node is used for route selection and maintenance. An important feature of SQ-AODV protocol is that it uses only local information and requires no additional communication or co-operation between the network nodes. SQ-AODV possesses a make-before-break re-routing capability that enables near-zero packet drops and is compatible with the basic AODV data formats and operation, making it easy to adopt in ad-hoc networks.


Datalog and Constraint Satisfaction with Infinite Templates

Abstract: On finite structures, there is a well-known connection between the expressive power of Datalog, finite variable logics, the existential pebble game, and bounded hypertree duality. We study this connection for infinite structures. This has applications for constraint satisfaction with infinite templates. If the template Gamma is omega-categorical, we present various equivalent characterizations of those Gamma such that the constraint satisfaction problem (CSP) for Gamma can be solved by a Datalog program. We also show that CSP(Gamma) can be solved in polynomial time for arbitrary omega-categorical structures Gamma if the input is restricted to instances of bounded treewidth. Finally, we characterize those omega-categorical templates whose CSP has Datalog width 1, and those whose CSP has strict Datalog width k.


Structures de r\'ealisabilit\'e, RAM et ultrafiltre sur N

Abstract: We show how to transform into programs the proofs in classical Analysis which use the existence of an ultrafilter on the integers. The method mixes the classical realizability introduced by the author, with the "forcing" of P. Cohen. The programs we obtain, use read and write instructions in random access memory.


Electricity Demand and Energy Consumption Management System

Abstract: This project describes the electricity demand and energy consumption management system and its application to Southern Peru smelter. It is composed of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows efficient management of energy peak demands before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules facilitate electricity demand and consumption proper planning, because they allow knowing the behavior of the hourly demand and the consumption patterns of the plant, including the bill components, but also energy deficiencies and opportunities for improvement, based on analysis of information about equipments, processes and production plans, as well as maintenance programs. Finally the results of its application in Southern Peru smelter are presented.


NP-Completeness of Hamiltonian Cycle Problem on Rooted Directed Path Graphs

Abstract: The Hamiltonian cycle problem is to decide whether a given graph has a Hamiltonian cycle. Bertossi and Bonuccelli (1986, Information Processing Letters, 23, 195-200) proved that the Hamiltonian Cycle Problem is NP-Complete even for undirected path graphs and left the Hamiltonian cycle problem open for directed path graphs. Narasimhan (1989, Information Processing Letters, 32, 167-170) proved that the Hamiltonian Cycle Problem is NP-Complete even for directed path graphs and left the Hamiltonian cycle problem open for rooted directed path graphs. In this paper we resolve this open problem by proving that the Hamiltonian Cycle Problem is also NP-Complete for rooted directed path graphs.


The fast intersection transform with applications to counting paths

Abstract: We present an algorithm for evaluating a linear ``intersection transform'' of a function defined on the lattice of subsets of an $n$-element set. In particular, the algorithm constructs an arithmetic circuit for evaluating the transform in ``down-closure time'' relative to the support of the function and the evaluation domain. As an application, we develop an algorithm that, given as input a digraph with $n$ vertices and bounded integer weights at the edges, counts paths by weight and given length $0\leq\ell\leq n-1$ in time $O^*(\exp(n\cdot H(\ell/(2n))))$, where $H(p)=-p\log p-(1-p)\log(1-p)$, and the notation $O^*(\cdot)$ suppresses a factor polynomial in $n$.


On the vertices of the k-addiive core

Abstract: The core of a game $v$ on $N$, which is the set of additive games $\phi$ dominating $v$ such that $\phi(N)=v(N)$, is a central notion in cooperative game theory, decision making and in combinatorics, where it is related to submodular functions, matroids and the greedy algorithm. In many cases however, the core is empty, and alternative solutions have to be found. We define the $k$-additive core by replacing additive games by $k$-additive games in the definition of the core, where $k$-additive games are those games whose M\"obius transform vanishes for subsets of more than $k$ elements. For a sufficiently high value of $k$, the $k$-additive core is nonempty, and is a convex closed polyhedron. Our aim is to establish results similar to the classical results of Shapley and Ichiishi on the core of convex games (corresponds to Edmonds' theorem for the greedy algorithm), which characterize the vertices of the core.


Multidimensional Visualization of Oracle Performance Using Barry007

Abstract: Most generic performance tools display only system-level performance data using 2-dimensional plots or diagrams and this limits the informational detail that can be displayed. Moreover, a modern relational database system, like Oracle, can concurrently serve thousands of client processes with different workload characteristics, so that generic performance-data displays inevitably hide important information. Drawing on our previous work, this paper demonstrates the application of Barry007 multidimensional visualization to the analysis of Oracle end-user, session-level, performance data, showing both collective trends and individual performance anomalies.


Getting in the Zone for Successful Scalability

Abstract: The universal scalability law (USL) is an analytic model used to quantify application scaling. It is universal because it subsumes Amdahl's law and Gustafson linearized scaling as special cases. Using simulation, we show: (i) that the USL is equivalent to synchronous queueing in a load-dependent machine repairman model and (ii) how USL, Amdahl's law, and Gustafson scaling can be regarded as boundaries defining three scalability zones. Typical throughput measurements lie across all three zones. Simulation scenarios provide deeper insight into queueing effects and thus provide a clearer indication of which application features should be tuned to get into the optimal performance zone.


Normalized Information Distance

Abstract: The normalized information distance is a universal distance measure for objects of all kinds. It is based on Kolmogorov complexity and thus uncomputable, but there are ways to utilize it. First, compression algorithms can be used to approximate the Kolmogorov complexity if the objects have a string representation. Second, for names and abstract concepts, page count statistics from the World Wide Web can be used. These practical realizations of the normalized information distance can then be applied to machine learning tasks, expecially clustering, to perform feature-free and parameter-free data mining. This chapter discusses the theoretical foundations of the normalized information distance and both practical realizations. It presents numerous examples of successful real-world applications based on these distance measures, ranging from bioinformatics to music clustering to machine translation.


Simpler Analyses of Local Search Algorithms for Facility Location

Abstract: We study local search algorithms for metric instances of facility location problems: the uncapacitated facility location problem (UFL), as well as uncapacitated versions of the $k$-median, $k$-center and $k$-means problems. All these problems admit natural local search heuristics: for example, in the UFL problem the natural moves are to open a new facility, close an existing facility, and to swap a closed facility for an open one; in $k$-medians, we are allowed only swap moves. The local-search algorithm for $k$-median was analyzed by Arya et al. (SIAM J. Comput. 33(3):544-562, 2004), who used a clever ``coupling'' argument to show that local optima had cost at most constant times the global optimum. They also used this argument to show that the local search algorithm for UFL was 3-approximation; their techniques have since been applied to other facility location problems. In this paper, we give a proof of the $k$-median result which avoids this coupling argument. These arguments can be used in other settings where the Arya et al. arguments have been used. We also show that for the problem of opening $k$ facilities $F$ to minimize the objective function $\Phi_p(F) = \big(\sum_{j \in V} d(j, F)^p\big)^{1/p}$, the natural swap-based local-search algorithm is a $\Theta(p)$-approximation. This implies constant-factor approximations for $k$-medians (when $p=1$), and $k$-means (when $p = 2$), and an $O(\log n)$-approximation algorithm for the $k$-center problem (which is essentially $p = \log n$).


Largest Empty Circle Centered on a Query Line

Abstract: The Largest Empty Circle problem seeks the largest circle centered within the convex hull of a set $P$ of $n$ points in $\mathbb{R}^2$ and devoid of points from $P$. In this paper, we introduce a query version of this well-studied problem. In our query version, we are required to preprocess $P$ so that when given a query line $Q$, we can quickly compute the largest empty circle centered at some point on $Q$ and within the convex hull of $P$. We present solutions for two special cases and the general case; all our queries run in $O(\log n)$ time. We restrict the query line to be horizontal in the first special case, which we preprocess in $O(n \alpha(n) \log n)$ time and space, where $\alpha(n)$ is the slow growing inverse of the Ackermann's function. When the query line is restricted to pass through a fixed point, the second special case, our preprocessing takes $O(n \alpha(n)^{O(\alpha(n))} \log n)$ time and space. We use insights from the two special cases to solve the general version of the problem with preprocessing time and space in $O(n^3 \log n)$ and $O(n^3)$ respectively.


Mathematical Tool of Discrete Dynamic Modeling of Complex Systems in Control Loop

Abstract: In this paper we present a method of discrete modeling and analysis of multi-level dynamics of complex large-scale hierarchical dynamic systems subject to external dynamic control mechanism. In a model each state describes parallel dynamics and simultaneous trends of changes in system parameters. The essence of the approach is in analysis of system state dynamics while it is in the control loop.


An MAS-Based ETL Approach for Complex Data

Abstract: In a data warehousing process, the phase of data integration is crucial. Many methods for data integration have been published in the literature. However, with the development of the Internet, the availability of various types of data (images, texts, sounds, videos, databases...) has increased, and structuring such data is a difficult task. We name these data, which may be structured or unstructured, "complex data". In this paper, we propose a new approach for complex data integration, based on a Multi-Agent System (MAS), in association to a data warehousing approach. Our objective is to take advantage of the MAS to perform the integration phase for complex data. We indeed consider the different tasks of the data integration process as services offered by agents. To validate this approach, we have actually developed an MAS for complex data integration.


Frequent itemsets mining for database auto-administration

Abstract: With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The aim of auto-administrative systems is to administrate and adapt themselves automatically without loss (or even with a gain) in performance. The idea of using data mining techniques to extract useful knowledge for administration from the data themselves has existed for some years. However, little research has been achieved. This idea nevertheless remains a very promising approach, notably in the field of data warehousing, where queries are very heterogeneous and cannot be interpreted easily. The aim of this study is to search for a way of extracting useful knowledge from stored data themselves to automatically apply performance optimization techniques, and more particularly indexing techniques. We have designed a tool that extracts frequent itemsets from a given workload to compute an index configuration that helps optimizing data access time. The experiments we performed showed that the index configurations generated by our tool allowed performance gains of 15% to 25% on a test database and a test data warehouse.


A Complex Data Warehouse for Personalized, Anticipative Medicine

Abstract: With the growing use of new technologies, healthcare is nowadays undergoing significant changes. Information-based medicine has to exploit medical decision-support systems and requires the analysis of various, heterogeneous data, such as patient records, medical images, biological analysis results, etc. In this paper, we present the design of the complex data warehouse relating to high-level athletes. It is original in two ways. First, it is aimed at storing complex medical data. Second, it is designed to allow innovative and quite different kinds of analyses to support: (1) personalized and anticipative medicine (in opposition to curative medicine) for well-identified patients; (2) broad-band statistical studies over a given population of patients. Furthermore, the system includes data relating to several medical fields. It is also designed to be evolutionary to take into account future advances in medical research.


Expressing OLAP operators with the TAX XML algebra

Abstract: With the rise of XML as a standard for representing business data, XML data warehouses appear as suitable solutions for Web-based decision-support applications. In this context, it is necessary to allow OLAP analyses over XML data cubes (XOLAP). Thus, XQuery extensions are needed. To help define a formal framework and allow much-needed performance optimizations on analytical queries expressed in XQuery, having an algebra at one's disposal is desirable. However, XOLAP approaches and algebras from the literature still largely rely on the relational model and/or only feature a small number of OLAP operators. In opposition, we propose in this paper to express a broad set of OLAP operators with the TAX XML algebra.


An Unified Definition of Data Mining

Abstract: Since many years, theoretical concepts of Data Mining have been developed and improved. Data Mining has become applied to many academic and industrial situations, and recently, soundings of public opinion about privacy have been carried out. However, a consistent and standardized definition is still missing, and the initial explanation given by Frawley et al. has pragmatically often changed over the years. Furthermore, alternative terms like Knowledge Discovery have been conjured and forged, and a necessity of a Data Warehouse has been endeavoured to persuade the users. In this work, we pick up current definitions and introduce an unified definition that covers existing attempted explanations. For this, we appeal to the natural original of chemical states of aggregation.


SWIM: A Simple Model to Generate Small Mobile Worlds

Abstract: This paper presents small world in motion (SWIM), a new mobility model for ad-hoc networking. SWIM is relatively simple, is easily tuned by setting just a few parameters, and generates traces that look real--synthetic traces have the same statistical properties of real traces. SWIM shows experimentally and theoretically the presence of the power law and exponential decay dichotomy of inter-contact time, and, most importantly, our experiments show that it can predict very accurately the performance of forwarding protocols.


Predicting Abnormal Returns From News Using Text Classification

Abstract: We show how text from news articles can be used to predict intraday price movements of financial assets using support vector machines. Multiple kernel learning is used to combine equity returns with text as predictive features to increase classification performance and we develop an analytic center cutting plane method to solve the kernel learning problem efficiently. We observe that while the direction of returns is not predictable using either text or returns, their size is, with text features producing significantly better performance than historical returns alone.


A Simple Framework to Typify Social Bibliographic Communities

Abstract: Social Communities in bibliographic databases exist since many years, researchers share common research interests, and work and publish together. A social community may vary in type and size, being fully connected between participating members or even more expressed by a consortium of small and individual members who play individual roles in it. In this work, we focus on social communities inside the bibliographic database DBLP and characterize communities through a simple typifying description model. Generally, we understand a publication as a transaction between the associated authors. The idea therefore is to concern with directed associative relationships among them, to decompose each pattern to its fundamental structure, and to describe the communities by expressive attributes. Finally, we argue that the decomposition supports the management of discovered structures towards the use of adaptive-incremental mind-maps.


Correlation of Expert and Search Engine Rankings

Abstract: In previous research it has been shown that link-based web page metrics can be used to predict experts' assessment of quality. We are interested in a related question: do expert rankings of real-world entities correlate with search engine rankings of corresponding web resources? For example, each year US News & World Report publishes a list of (among others) top 50 graduate business schools. Does their expert ranking correlate with the search engine ranking of the URLs of those business schools? To answer this question we conducted 9 experiments using 8 expert rankings on a range of academic, athletic, financial and popular culture topics. We compared the expert rankings with the rankings in Google, Live Search (formerly MSN) and Yahoo (with list lengths of 10, 25, and 50). In 57 search engine vs. expert comparisons, only 1 strong and 4 moderate correlations were statistically significant. In 42 inter-search engine comparisons, only 2 strong and 4 moderate correlations were statistically significant. The correlations appeared to decrease with the size of the lists: the 3 strong correlations were for lists of 10, the 8 moderate correlations were for lists of 25, and no correlations were found for lists of 50.


Polynomial kernels for 3-leaf power graph modification problems

Abstract: A graph G=(V,E) is a 3-leaf power iff there exists a tree T whose leaves are V and such that (u,v) is an edge iff u and v are at distance at most 3 in T. The 3-leaf power graph edge modification problems, i.e. edition (also known as the closest 3-leaf power), completion and edge-deletion, are FTP when parameterized by the size of the edge set modification. However polynomial kernel was known for none of these three problems. For each of them, we provide cubic kernels that can be computed in linear time for each of these problems. We thereby answer an open problem first mentioned by Dom, Guo, Huffner and Niedermeier (2005).


On an algorithm that generates an interesting maximal set P(n) of the naturals for any n greater than or equal to 2

Abstract: The paper considers the problem of finding the largest possible set P(n), a subset of the set N of the natural numbers, with the property that a number is in P(n) if and only if it is a sum of n distinct naturals all in P(n) or none in P(n). Here largest is in the set theoretic sense and n is greater than or equal to 2. We call P(n) a maximal set obeying this property. For small n say 2 or 3, it is possible to develop P(n) intuitively but we strongly felt the necessity of an algorithm for any n greater than or equal to 2. Now P(n) shall invariably be a infinite set so we define another set Q(n) such that Q(n)=N-P(n), prove that Q(n) is finite and, since P(n) is automatically known if Q(n) is known, design an algorithm of worst case O(1) complexity which generates Q(n).


Communication-Efficient Construction of the Plane Localized Delaunay Graph

Abstract: Let $V$ be a finite set of points in the plane. We present a 2-local algorithm that constructs a plane $\frac{4 \pi \sqrt{3}}{9}$-spanner of the unit-disk graph $\UDG(V)$. This algorithm makes only one round of communication and each point of $V$ broadcasts at most 5 messages. This improves the previously best message-bound of 11 by Ara\'{u}jo and Rodrigues (Fast localized Delaunay triangulation, Lecture Notes in Computer Science, volume 3544, 2004).


Single source shortest paths in $H$-minor free graphs

Abstract: We present an algorithm for the Single Source Shortest Paths (SSSP) problem in \emph{$H$-minor free} graphs. For every fixed $H$, if $G$ is a graph with $n$ vertices having integer edge lengths and $s$ is a designated source vertex of $G$, the algorithm runs in $\tilde{O}(n^{\sqrt{11.5}-2} \log L) \le O(n^{1.392} \log L)$ time, where $L$ is the absolute value of the smallest edge length. The algorithm computes shortest paths and the distances from $s$ to all vertices of the graph, or else provides a certificate that $G$ is not $H$-minor free. Our result improves an earlier $O(n^{1.5} \log L)$ time algorithm for this problem, which follows from a general SSSP algorithm of Goldberg.


A local construction of the Smith normal form of a matrix polynomial

Abstract: We present an algorithm for computing a Smith form with multipliers of a regular matrix polynomial over a field. This algorithm differs from previous ones in that it computes a local Smith form for each irreducible factor in the determinant separately and then combines them into a global Smith form, whereas other algorithms apply a sequence of unimodular row and column operations to the original matrix. The performance of the algorithm in exact arithmetic is reported for several test cases.


Metrics-Based Spreadsheet Visualization: Support for Focused Maintenance

Abstract: Legacy spreadsheets are both, an asset, and an enduring problem concerning spreadsheets in business. To make spreadsheets stay alive and remain correct, comprehension of a given spreadsheet is highly important. Visualization techniques should ease the complex and mindblowing challenges of finding structures in a huge set of spreadsheet cells for building an adequate mental model of spreadsheet programs. Since spreadsheet programs are as diverse as the purpose they are serving and as inhomogeneous as their programmers, to find an appropriate representation or visualization technique for every spreadsheet program seems futile. We thus propose different visualization and representation methods that may ease spreadsheet comprehension but should not be applied with all kind of spreadsheet programs. Therefore, this paper proposes to use (complexity) measures as indicators for proper visualization.


Automating Spreadsheet Discovery & Risk Assessment

Abstract: There have been many articles and mishaps published about the risks of uncontrolled spreadsheets in today's business environment, including non-compliance, operational risk, errors, and fraud all leading to significant loss events. Spreadsheets fall into the realm of end user developed applications and are often absent the proper safeguards and controls an IT organization would enforce for enterprise applications. There is also an overall lack of software programming discipline enforced in how spreadsheets are developed. However, before an organization can apply proper controls and discipline to critical spreadsheets, an accurate and living inventory of spreadsheets across the enterprise must be created, and all critical spreadsheets must be identified. As such, this paper proposes an automated approach to the initial stages of the spreadsheet management lifecycle - discovery, inventory and risk assessment. Without the use of technology, these phases are often treated as a one-off project. By leveraging technology, they become a sustainable business process.


Kinetostatic Performance of a Planar Parallel Mechanism with Variable Actuation

Abstract: This paper deals with a new planar parallel mechanism with variable actuation and its kinetostatic performance. A drawback of parallel mechanisms is the non homogeneity of kinetostatic performance within their workspace. The common approach to solve this problem is the introduction of actuation redundancy, that involves force control algorithms. Another approach, highlighted in this paper, is to select the actuated joint in each limb with regard to the pose of the end-effector. First, the architecture of the mechanism and two kinetostatic performance indices are described. Then, the actuating modes of the mechanism are compared.


Supervised Dictionary Learning

Abstract: It is now well established that sparse signal models are well suited to restoration tasks and can effectively be learned from audio, image, and video data. Recent research has been aimed at learning discriminative sparse models instead of purely reconstructive ones. This paper proposes a new step in that direction, with a novel sparse representation for signals belonging to different classes in terms of a shared dictionary and multiple class-decision functions. The linear variant of the proposed model admits a simple probabilistic interpretation, while its most general variant admits an interpretation in terms of kernels. An optimization framework for learning all the components of the proposed model is presented, along with experimental results on standard handwritten digit and texture classification tasks.


A Distributed Algorithm for Fair and Efficient User-Network Association in Multi-Technology Wireless Networks

Abstract: Recent mobile equipment (as well as the norm IEEE 802.21) now offers the possibility for users to switch from one technology to another (vertical handover). This allows flexibility in resource assignments and, consequently, increases the potential throughput allocated to each user. In this paper, we design a fully distributed algorithm based on trial and error mechanisms that exploits the benefits of vertical handover by finding fair and efficient assignment schemes. On the one hand, mobiles gradually update the fraction of data packets they send to each network based on the rewards they receive from the stations. On the other hand, network stations send rewards to each mobile that represent the impact each mobile has on the cell throughput. This reward function is closely related to the concept of marginal cost in the pricing literature. Both the station and the mobile algorithms are simple enough to be implemented in current standard equipment. Based on tools from evolutionary games, potential games and replicator dynamics, we analytically show the convergence of the algorithm to solutions that are efficient and fair in terms of throughput. Moreover, we show that after convergence, each user is connected to a single network cell which avoids costly repeated vertical handovers. Several simple heuristics based on this algorithm are proposed to achieve fast convergence. Indeed, for implementation purposes, the number of iterations should remain in the order of a few tens. We also compare, for different loads, the quality of their solutions.


Monadic Datalog over Finite Structures with Bounded Treewidth

Abstract: Bounded treewidth and Monadic Second Order (MSO) logic have proved to be key concepts in establishing fixed-parameter tractability results. Indeed, by Courcelle's Theorem we know: Any property of finite structures, which is expressible by an MSO sentence, can be decided in linear time (data complexity) if the structures have bounded treewidth. In principle, Courcelle's Theorem can be applied directly to construct concrete algorithms by transforming the MSO evaluation problem into a tree language recognition problem. The latter can then be solved via a finite tree automaton (FTA). However, this approach has turned out to be problematical, since even relatively simple MSO formulae may lead to a ``state explosion'' of the FTA. In this work we propose monadic datalog (i.e., datalog where all intentional predicate symbols are unary) as an alternative method to tackle this class of fixed-parameter tractable problems. We show that if some property of finite structures is expressible in MSO then this property can also be expressed by means of a monadic datalog program over the structure plus the tree decomposition. Moreover, we show that the resulting fragment of datalog can be evaluated in linear time (both w.r.t. the program size and w.r.t. the data size). This new approach is put to work by devising new algorithms for the 3-Colorability problem of graphs and for the PRIMALITY problem of relational schemas (i.e., testing if some attribute in a relational schema is part of a key). We also report on experimental results with a prototype implementation.


Kinematic and Dynamic Analyses of the Orthoglide 5-axis

Abstract: This paper deals with the kinematic and dynamic analyses of the Orthoglide 5-axis, a five-degree-of-freedom manipulator. It is derived from two manipulators: i) the Orthoglide 3-axis; a three dof translational manipulator and ii) the Agile eye; a parallel spherical wrist. First, the kinematic and dynamic models of the Orthoglide 5-axis are developed. The geometric and inertial parameters of the manipulator are determined by means of a CAD software. Then, the required motors performances are evaluated for some test trajectories. Finally, the motors are selected in the catalogue from the previous results.


Singularity Analysis of Limited-dof Parallel Manipulators using Grassmann-Cayley Algebra

Abstract: This paper characterizes geometrically the singularities of limited DOF parallel manipulators. The geometric conditions associated with the dependency of six Pl\"ucker vector of lines (finite and infinite) constituting the rows of the inverse Jacobian matrix are formulated using Grassmann-Cayley algebra. Manipulators under consideration do not need to have a passive spherical joint somewhere in each leg. This study is illustrated with three example robots


Framework for Dynamic Evaluation of Muscle Fatigue in Manual Handling Work

Abstract: Muscle fatigue is defined as the point at which the muscle is no longer able to sustain the required force or work output level. The overexertion of muscle force and muscle fatigue can induce acute pain and chronic pain in human body. When muscle fatigue is accumulated, the functional disability can be resulted as musculoskeletal disorders (MSD). There are several posture exposure analysis methods useful for rating the MSD risks, but they are mainly based on static postures. Even in some fatigue evaluation methods, muscle fatigue evaluation is only available for static postures, but not suitable for dynamic working process. Meanwhile, some existing muscle fatigue models based on physiological models cannot be easily used in industrial ergonomic evaluations. The external dynamic load is definitely the most important factor resulting muscle fatigue, thus we propose a new fatigue model under a framework for evaluating fatigue in dynamic working processes. Under this framework, virtual reality system is taken to generate virtual working environment, which can be interacted with the work with haptic interfaces and optical motion capture system. The motion information and load information are collected and further processed to evaluate the overall work load of the worker based on dynamic muscle fatigue models and other work evaluation criterions and to give new information to characterize the penibility of the task in design process.


SINGULAB - A Graphical user Interface for the Singularity Analysis of Parallel Robots based on Grassmann-Cayley Algebra

Abstract: This paper presents SinguLab, a graphical user interface for the singularity analysis of parallel robots. The algorithm is based on Grassmann-Cayley algebra. The proposed tool is interactive and introduces the designer to the singularity analysis performed by this method, showing all the stages along the procedure and eventually showing the solution algebraically and graphically, allowing as well the singularity verification of different robot poses.


Extended ASP tableaux and rule redundancy in normal logic programs

Abstract: We introduce an extended tableau calculus for answer set programming (ASP). The proof system is based on the ASP tableaux defined in [Gebser&Schaub, ICLP 2006], with an added extension rule. We investigate the power of Extended ASP Tableaux both theoretically and empirically. We study the relationship of Extended ASP Tableaux with the Extended Resolution proof system defined by Tseitin for sets of clauses, and separate Extended ASP Tableaux from ASP Tableaux by giving a polynomial-length proof for a family of normal logic programs P_n for which ASP Tableaux has exponential-length minimal proofs with respect to n. Additionally, Extended ASP Tableaux imply interesting insight into the effect of program simplification on the lengths of proofs in ASP. Closely related to Extended ASP Tableaux, we empirically investigate the effect of redundant rules on the efficiency of ASP solving. To appear in Theory and Practice of Logic Programming (TPLP).


A Local Clustering Algorithm for Massive Graphs and its Application to Nearly-Linear Time Graph Partitioning

Abstract: We study the design of local algorithms for massive graphs. A local algorithm is one that finds a solution containing or near a given vertex without looking at the whole graph. We present a local clustering algorithm. Our algorithm finds a good cluster--a subset of vertices whose internal connections are significantly richer than its external connections--near a given vertex. The running time of our algorithm, when it finds a non-empty local cluster, is nearly linear in the size of the cluster it outputs. Our clustering algorithm could be a useful primitive for handling massive graphs, such as social networks and web-graphs. As an application of this clustering algorithm, we present a partitioning algorithm that finds an approximate sparsest cut with nearly optimal balance. Our algorithm takes time nearly linear in the number edges of the graph. Using the partitioning algorithm of this paper, we have designed a nearly-linear time algorithm for constructing spectral sparsifiers of graphs, which we in turn use in a nearly-linear time algorithm for solving linear systems in symmetric, diagonally-dominant matrices. The linear system solver also leads to a nearly linear-time algorithm for approximating the second-smallest eigenvalue and corresponding eigenvector of the Laplacian matrix of a graph. These other results are presented in two companion papers.


Using descriptive mark-up to formalize translation quality assessment

Abstract: The paper deals with using descriptive mark-up to emphasize translation mistakes. The author postulates the necessity to develop a standard and formal XML-based way of describing translation mistakes. It is considered to be important for achieving impersonal translation quality assessment. Marked-up translations can be used in corpus translation studies; moreover, automatic translation assessment based on marked-up mistakes is possible. The paper concludes with setting up guidelines for further activity within the described field.


Criteria on Utility Designing of Convex Optimization in FDMA Networks

Abstract: In this paper, we investigate the network utility maximization problem in FDMA systems. We summarize with a suite of criteria on designing utility functions so as to achieve the global optimization convex. After proposing the general form of the utility functions, we present examples of commonly used utility function forms that are consistent with the criteria proposed in this paper, which include the well-known proportional fairness function and the sigmoidal-like functions. In the second part of this paper, we use numerical results to demonstrate a case study based on the criteria mentioned above, which deals with the subcarrier scheduling problem with dynamic rate allocation in FDMA system.


Distributed Spiral Optimization in Wireless Sensor Networks without Fusion Centers

Abstract: A distributed spiral algorithm for distributed optimization in WSN is proposed. By forming a spiral-shape message passing scheme among clusters, without loss of estimation accuracy and convergence speed, the algorithm is proved to converge with a lower total transport cost than the distributed in-cluster algorithm.


A Heuristic Scheduling Scheme in Multiuser OFDMA Networks

Abstract: Conventional heterogeneous-traffic scheduling schemes utilize zero-delay constraint for real-time services, which aims to minimize the average packet delay among real-time users. However, in light or moderate load networks this strategy is unnecessary and leads to low data throughput for non-real-time users. In this paper, we propose a heuristic scheduling scheme to solve this problem. The scheme measures and assigns scheduling priorities to both real-time and non-real-time users, and schedules the radio resources for the two user classes simultaneously. Simulation results show that the proposed scheme efficiently handles the heterogeneous-traffic scheduling with diverse QoS requirements and alleviates the unfairness between real-time and non-real-time services under various traffic loads.


Performance Comparison of Cooperative and Distributed Spectrum Sensing in Cognitive Radio

Abstract: In this paper, we compare the performances of cooperative and distributed spectrum sensing in wireless sensor networks. After introducing the basic problem, we describe two strategies: 1) a cooperative sensing strategy, which takes advantage of cooperation diversity gain to increase probability of detection and 2) a distributed sensing strategy, which by passing the results in an inter-node manner increases energy efficiency and fairness among nodes. Then, we compare the performances of the strategies in terms of three criteria: agility, energy efficiency, and robustness against SNR changes, and summarize the comparison. It shows that: 1) the non-cooperative strategy has the best fairness of energy consumption, 2) the cooperative strategy leads to the best agility, and 3) the distributed strategy leads to the lowest energy consumption and the best robustness against SNR changes.


Load Balancing Strategies to Solve Flowshop Scheduling on Parallel Computing

Abstract: This paper first presents a parallel solution for the Flowshop Scheduling Problem in parallel environment, and then proposes a novel load balancing strategy. The proposed Proportional Fairness Strategy (PFS) takes computational performance of computing process sets into account, and assigns additional load to computing nodes proportionally to their evaluated performance. In order to efficiently utilize the power of parallel resource, we also discuss the data structure used in communications among computational nodes and design an optimized data transfer strategy. This data transfer strategy combined with the proposed load balancing strategy have been implemented and tested on a super computer consisted of 86 CPUs using MPI as the middleware. The results show that the proposed PFS achieves better performance in terms of computing time than the existing Adaptive Contracting Within Neighborhood Strategy. We also show that the combination of both the Proportional Fairness Strategy and the proposed data transferring strategy achieves additional 13~15% improvement in efficiency of parallelism.


Generalized Prediction Intervals for Arbitrary Distributed High-Dimensional Data

Abstract: This paper generalizes the traditional statistical concept of prediction intervals for arbitrary probability density functions in high-dimensional feature spaces by introducing significance level distributions, which provides interval-independent probabilities for continuous random variables. The advantage of the transformation of a probability density function into a significance level distribution is that it enables one-class classification or outlier detection in a direct manner.


More on Combinatorial Batch Codes

Abstract: Paterson, Stinson and Wei \cite{PSW} introduced Combinatorial batch codes, which are combinatorial description of Batch code. Batch codes were first presented by Ishai, Kushilevita, Ostrovsky and Sahai \cite{IKOS} in STOC'04. In this paper we answer some of the questions put forward by Paterson, Stinson and Wei and give some results for the general case $t>1$ which were not studied by the authors.


Changing Assembly Modes without Passing Parallel Singularities in Non-Cuspidal 3-R\underline{P}R Planar Parallel Robots

Abstract: This paper demonstrates that any general 3-DOF three-legged planar parallel robot with extensible legs can change assembly modes without passing through parallel singularities (configurations where the mobile platform loses its stiffness). While the results are purely theoretical, this paper questions the very definition of parallel singularities.


Ten weeks in the life of an eDonkey server

Abstract: This paper presents a capture of the queries managed by an eDonkey server during almost 10 weeks, leading to the observation of almost 9 billion messages involving almost 90 million users and more than 275 million distinct files. Acquisition and management of such data raises several challenges, which we discuss as well as the solutions we developed. We obtain a very rich dataset, orders of magnitude larger than previously avalaible ones, which we provide for public use. We finally present basic analysis of the obtained data, which already gives evidence of non-trivial features.


An Exploratory Study of Calendar Use

Abstract: In this paper, we report on findings from an ethnographic study of how people use their calendars for personal information management (PIM). Our participants were faculty, staff and students who were not required to use or contribute to any specific calendaring solution, but chose to do so anyway. The study was conducted in three parts: first, an initial survey provided broad insights into how calendars were used; second, this was followed up with personal interviews of a few participants which were transcribed and content-analyzed; and third, examples of calendar artifacts were collected to inform our analysis. Findings from our study include the use of multiple reminder alarms, the reliance on paper calendars even among regular users of electronic calendars, and wide use of calendars for reporting and life-archival purposes. We conclude the paper with a discussion of what these imply for designers of interactive calendar systems and future work in PIM research.


A First Step to Convolutive Sparse Representation

Abstract: In this paper an extension of the sparse decomposition problem is considered and an algorithm for solving it is presented. In this extension, it is known that one of the shifted versions of a signal s (not necessarily the original signal itself) has a sparse representation on an overcomplete dictionary, and we are looking for the sparsest representation among the representations of all the shifted versions of s. Then, the proposed algorithm finds simultaneously the amount of the required shift, and the sparse representation. Experimental results emphasize on the performance of our algorithm.


JDATATRANS for Array Obfuscation in Java Source Code to Defeat Reverse Engineering from Decompiled Codes

Abstract: Software obfuscation or obscuring a software is an approach to defeat the practice of reverse engineering a software for using its functionality illegally in the development of another software. Java applications are more amenable to reverse engineering and re-engineering attacks through methods such as decompilation because Java class files store the program in a semi complied form called 'byte' codes. The existing obfuscation systems obfuscate the Java class files. Obfuscated source code produce obfuscated byte codes and hence two level obfuscation (source code and byte code level) of the program makes it more resilient to reverse engineering attacks. But source code obfuscation is much more difficult due to richer set of programming constructs and the scope of the different variables used in the program and only very little progress has been made on this front. Hence programmers resort to adhoc manual ways of obscuring their program which makes it difficult for its maintenance and usability. To address this issue partially, we developed a user friendly tool JDATATRANS to obfuscate Java source code by obscuring the array usages. Using various array restructuring techniques such as 'array splitting', 'array folding' and 'array flattening', in addition to constant hiding, our system obfuscate the input Java source code and produce an obfuscated Java source code that is functionally equivalent to the input program. We also perform a number of experiments to measure the potency, resilience and cost incurred by our tool.


Inferring Company Structure from Limited Available Information

Abstract: In this paper we present several algorithmic techniques for inferring the structure of a company when only a limited amount of information is available. We consider problems with two types of inputs: the number of pairs of employees with a given property and restricted information about the hierarchical structure of the company. We provide dynamic programming and greedy algorithms for these problems.


Locating Restricted Facilities on Binary Maps

Abstract: In this paper we consider several facility location problems with applications to cost and social welfare optimization, when the area map is encoded as a binary (0,1) mxn matrix. We present algorithmic solutions for all the problems. Some cases are too particular to be used in practical situations, but they are at least a starting point for more generic solutions.


A High Performance Memory Database for Web Application Caches

Abstract: This paper presents the architecture and characteristics of a memory database intended to be used as a cache engine for web applications. Primary goals of this database are speed and efficiency while running on SMP systems with several CPU cores (four and more). A secondary goal is the support for simple metadata structures associated with cached data that can aid in efficient use of the cache. Due to these goals, some data structures and algorithms normally associated with this field of computing needed to be adapted to the new environment.


On fractionality of the path packing problem

Abstract: In this paper, we study fractional multiflows in undirected graphs. A fractional multiflow in a graph G with a node subset T, called terminals, is a collection of weighted paths with ends in T such that the total weights of paths traversing each edge does not exceed 1. Well-known fractional path packing problem consists of maximizing the total weight of paths with ends in a subset S of TxT over all fractional multiflows. Together, G,T and S form a network. A network is an Eulerian network if all nodes in N\T have even degrees. A term "fractionality" was defined for the fractional path packing problem by A. Karzanov as the smallest natural number D so that there exists a solution to the problem that becomes integer-valued when multiplied by D. A. Karzanov has defined the class of Eulerian networks in terms of T and S, outside which D is infinite and proved that whithin this class D can be 1,2 or 4. He conjectured that D should be 1 or 2 for this class of networks. In this paper we prove this conjecture.


Evaluation of an Intelligent Assistive Technology for Voice Navigation of Spreadsheets

Abstract: An integral part of spreadsheet auditing is navigation. For sufferers of Repetitive Strain Injury who need to use voice recognition technology this navigation can be highly problematic. To counter this the authors have developed an intelligent voice navigation system, iVoice, which replicates common spreadsheet auditing behaviours through simple voice commands. This paper outlines the iVoice system and summarizes the results of a study to evaluate iVoice when compared to a leading voice recognition technology.


Spreadsheet modelling for solving combinatorial problems: The vendor selection problem

Abstract: Spreadsheets have grown up and became very powerful and easy to use tools in applying analytical techniques for solving business problems. Operations managers, production managers, planners and schedulers can work with them in developing solid and practical Do-It-Yourself Decision Support Systems. Small and Medium size organizations, can apply OR methodologies without the presence of specialized software and trained personnel, which in many cases cannot afford anyway. This paper examines an efficient approach in solving combinatorial programming problems with the use of spreadsheets. A practical application, which demonstrates the approach, concerns the development of a spreadsheet-based DSS for the Multi Item Procurement Problem with Fixed Vendor Cost. The DSS has been build using exclusively standard spreadsheet feature and can solve real problems of substantial size. The benefits and limitations of the approach are also discussed.


Spreadsheet Components For All

Abstract: We have prototyped a "spreadsheet component repository" Web site, from which users can copy "components" into their own Excel or Google spreadsheets. Components are collections of cells containing formulae: in real life, they would do useful calculations that many practitioners find hard to program, and would be rigorously tested and documented. Crucially, the user can tell the repository which cells in their spreadsheet to use for a componen's inputs and outputs. The repository will then reshape the component to fit. A single component can therefore be used in many different sizes and shapes of spreadsheet. We hope to set up a spreadsheet equivalent of the high-quality numerical subroutine libraries that revolutionised scientific computing, but where instead of subroutines, the library contains such components.


A Primer on Spreadsheet Analytics

Abstract: This paper provides guidance to an analyst who wants to extract insight from a spreadsheet model. It discusses the terminology of spreadsheet analytics, how to prepare a spreadsheet model for analysis, and a hierarchy of analytical techniques. These techniques include sensitivity analysis, tornado charts,and backsolving (or goal-seeking). This paper presents native-Excel approaches for automating these techniques, and discusses add-ins that are even more efficient. Spreadsheet optimization and spreadsheet Monte Carlo simulation are briefly discussed. The paper concludes by calling for empirical research, and describing desired features spreadsheet sensitivity analysis and spreadsheet optimization add-ins.


Spreadsheet End-User Behaviour Analysis

Abstract: To aid the development of spreadsheet debugging tools, a knowledge of end-users natural behaviour within the Excel environment would be advantageous. This paper details the design and application of a novel data acquisition tool, which can be used for the unobtrusive recording of end-users mouse, keyboard and Excel specific actions during the debugging of Excel spreadsheets. A debugging experiment was conducted using this data acquisition tool, and based on analysis of end-users performance and behaviour data, the authors developed a "spreadsheet cell coverage feedback" debugging tool. Results from the debugging experiment are presented in terms of enduser debugging performance and behaviour, and the outcomes of an evaluation experiment with the debugging tool are detailed.


Controlling End User Computing Applications - a case study

Abstract: We report the results of a project to control the use of end user computing tools for business critical applications in a banking environment. Several workstreams were employed in order to bring about a cultural change within the bank towards the use of spreadsheets and other end-user tools, covering policy development, awareness and skills training, inventory monitoring, user licensing, key risk metrics and mitigation approaches. The outcomes of these activities are discussed, and conclusions are drawn as to the need for appropriate organisational models to guide the use of these tools.


Spreadsheets: Aiming the Accountant's Hammer to Hit the Nail on the Head

Abstract: Accounting and Finance (A&F) Professionals are arguably the most loyal and concentrated population of spreadsheet users. The work that they perform in spreadsheets has the most significant impact on financial data and business processes within global organizations today. Spreadsheets offer the flexibility and ease of use of a desktop application, combined with the power to perform complex data analysis. They are also the lowest cost business IT tool when stacked up against other functional tools. As a result, spreadsheets are used to support critical business processes in most organizations. In fact, research indicates that over half of financial management reporting is performed with spreadsheets by an accounting and finance professional. A disparity exists in the business world between the importance of spreadsheets on financial data (created by A&F Professionals) and the resources devoted to: The development and oversight of global spreadsheet standards; A recognized and accredited certification in spreadsheet proficiency; Corporate sponsored and required training; Awareness of emerging technologies as it relates to spreadsheet use. This management paper focuses on the current topics relevant to the largest user group (A&F Professionals) of the most widely used financial software application, spreadsheets, also known as the accountant's hammer.


Information and Data Quality in Spreadsheets

Abstract: The quality of the data in spreadsheets is less discussed than the structural integrity of the formulas. Yet it is an area of great interest to the owners and users of the spreadsheet. This paper provides an overview of Information Quality (IQ) and Data Quality (DQ) with specific reference to how data is sourced, structured, and presented in spreadsheets.


Overview and main results of the DidaTab project

Abstract: The DidaTab project (Didactics of Spreadsheet, teaching and learning spreadsheets) is a three year project (2005-2007) funded by the French Ministry of Research and dedicated to the study of personal and classroom uses of spreadsheets in the French context, focussing on the processes of appropriation and uses by secondary school students. In this paper, we present an overview of the project, briefly report the studies performed in the framework of the DidaTab project, and give the main results we obtained. We then explore the new research tracks we intend to develop, more in connection with EuSpRIG. Our main result is that the use of spreadsheet during secondary education (grade 6 to 12) is rather sparse for school work (and even more seldom at home) and that student competencies are weak. Curricula have to be reviewed to include more training of dynamics tabular tools (including databases queries) in order to ensure sufficient mastery of computer tools that have became necessary in many educational activities.


Revisiting the Panko-Halverson Taxonomy of Spreadsheet Errors

Abstract: The purpose of this paper is to revisit the Panko-Halverson taxonomy of spreadsheet errors and suggest revisions. There are several reasons for doing so: First, the taxonomy has been widely used. Therefore, it should have scrutiny; Second, the taxonomy has not been widely available in its original form and most users refer to secondary sources. Consequently, they often equate the taxonomy with the simplified extracts used in particular experiments or field studies; Third, perhaps as a consequence, most users use only a fraction of the taxonomy. In particular, they tend not to use the taxonomy's life-cycle dimension; Fourth, the taxonomy has been tested against spreadsheets in experiments and spreadsheets in operational use. It is time to review how it has fared in these tests; Fifth, the taxonomy was based on the types of spreadsheet errors that were known to the authors in the mid-1990s. Subsequent experience has shown that the taxonomy needs to be extended for situations beyond those original experiences; Sixth, the omission category in the taxonomy has proven to be too narrow. Although this paper will focus on the Panko-Halverson taxonomy, this does not mean that that it is the only possible error taxonomy or even the best error taxonomy.


Improved Monotone Circuit Depth Upper Bound for Directed Graph Reachability

Abstract: We prove that the directed graph reachability problem (transitive closure) can be solved by monotone fan-in 2 boolean circuits of depth (1/2+o(1))(log n)^2, where n is the number of nodes. This improves the previous known upper bound (1+o(1))(log n)^2. The proof is non-constructive, but we give a constructive proof of the upper bound (7/8+o(1))(log n)^2.


Robust Near-Isometric Matching via Structured Learning of Graphical Models

Abstract: Models for near-rigid shape matching are typically based on distance-related features, in order to infer matches that are consistent with the isometric assumption. However, real shapes from image datasets, even when expected to be related by "almost isometric" transformations, are actually subject not only to noise but also, to some limited degree, to variations in appearance and scale. In this paper, we introduce a graphical model that parameterises appearance, distance, and angle features and we learn all of the involved parameters via structured prediction. The outcome is a model for near-rigid shape matching which is robust in the sense that it is able to capture the possibly limited but still important scale and appearance variations. Our experimental results reveal substantial improvements upon recent successful models, while maintaining similar running times.