Foundations of SPARQL Query Optimization

Abstract: The SPARQL query language is a recent W3C standard for processing RDF data, a format that has been developed to encode information in a machine-readable way. We investigate the foundations of SPARQL query optimization and (a) provide novel complexity results for the SPARQL evaluation problem, showing that the main source of complexity is operator OPTIONAL alone; (b) propose a comprehensive set of algebraic query rewriting rules; (c) present a framework for constraint-based SPARQL optimization based upon the well-known chase procedure for Conjunctive Query minimization. In this line, we develop two novel termination conditions for the chase. They subsume the strongest conditions known so far and do not increase the complexity of the recognition problem, thus making a larger class of both Conjunctive and SPARQL queries amenable to constraint-based optimization. Our results are of immediate practical interest and might empower any SPARQL query optimizer.


Bootstrapping Inductive and Coinductive Types in HasCASL

Abstract: We discuss the treatment of initial datatypes and final process types in the wide-spectrum language HasCASL. In particular, we present specifications that illustrate how datatypes and process types arise as bootstrapped concepts using HasCASL's type class mechanism, and we describe constructions of types of finite and infinite trees that establish the conservativity of datatype and process type declarations adhering to certain reasonable formats. The latter amounts to modifying known constructions from HOL to avoid unique choice; in categorical terminology, this means that we establish that quasitoposes with an internal natural numbers object support initial algebras and final coalgebras for a range of polynomial functors, thereby partially generalising corresponding results from topos theory. Moreover, we present similar constructions in categories of internal complete partial orders in quasitoposes.


Decting Errors in Reversible Circuits With Invariant Relationships

Abstract: Reversible logic is experience renewed interest as we are approach the limits of CMOS technologies. While physical implementations of reversible gates have yet to materialize, it is safe to assume that they will rely on faulty individual components. In this work we present a present a method to provide fault tolerance to a reversible circuit based on invariant relationships.


Succinct Greedy Geometric Routing in the Euclidean Plane

Abstract: In greedy geometric routing, messages are passed in a network embedded in a metric space according to the greedy strategy of always forwarding messages to nodes that are closer to the destination. We show that greedy geometric routing schemes exist for the Euclidean metric in R^2, for 3-connected planar graphs, with coordinates that can be represented succinctly, that is, with O(log n) bits, where n is the number of vertices in the graph. Moreover, our embedding strategy introduces a coordinate system for R^2 that supports distance comparisons using our succinct coordinates. Thus, our scheme can be used to significantly reduce bandwidth, space, and header size over other recently discovered greedy geometric routing implementations for R^2.


Pancake Flipping with Two Spatulas

Abstract: In this paper we study several variations of the \emph{pancake flipping problem}, which is also well known as the problem of \emph{sorting by prefix reversals}. We consider the variations in the sorting process by adding with prefix reversals other similar operations such as prefix transpositions and prefix transreversals. These type of sorting problems have applications in interconnection networks and computational biology. We first study the problem of sorting unsigned permutations by prefix reversals and prefix transpositions and present a 3-approximation algorithm for this problem. Then we give a 2-approximation algorithm for sorting by prefix reversals and prefix transreversals. We also provide a 3-approximation algorithm for sorting by prefix reversals and prefix transpositions where the operations are always applied at the unsorted suffix of the permutation. We further analyze the problem in more practical way and show quantitatively how approximation ratios of our algorithms improve with the increase of number of prefix reversals applied by optimal algorithms. Finally, we present experimental results to support our analysis.


Graph Field Automata

Abstract: The Graph Automata have been the paradigm in the expression of utilizing Graphs as a language. Matrix Graph grammars \cite{Pedro} are an algebratization of graph rewriting systems. Here we present the dual of this formalizm which some extensions which we term Graph Field Automata The advantage to this approach is a framework for expressing machines that can use Matrix Graph Grammars.


The Offset Tree for Learning with Partial Labels

Abstract: We present an algorithm, called the Offset Tree, for learning to make decisions in situations where the payoff of only one choice is observed, rather than all choices. The algorithm reduces this setting to binary classification, allowing one to reuse of any existing, fully supervised binary classification algorithm in this partial information setting. We show that the Offset Tree is an optimal reduction to binary classification. In particular, it has regret at most $(k-1)$ times the regret of the binary classifier it uses (where $k$ is the number of choices), and no reduction to binary classification can do better. This reduction is also computationally optimal, both at training and test time, requiring just $O(\log_2 k)$ work to train on an example or make a prediction. Experiments with the Offset Tree show that it generally performs better than several alternative approaches.


Finding Still Lifes with Memetic/Exact Hybrid Algorithms

Abstract: The maximum density still life problem (MDSLP) is a hard constraint optimization problem based on Conway's game of life. It is a prime example of weighted constrained optimization problem that has been recently tackled in the constraint-programming community. Bucket elimination (BE) is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply BE is too high, a heuristic method based on it (denominated mini-buckets) can be used to calculate bounds for the optimal solution. Nevertheless, the curse of dimensionality makes these techniques unpractical for large size problems. In response to this situation, we present a memetic algorithm for the MDSLP in which BE is used as a mechanism for recombining solutions, providing the best possible child from the parental set. Subsequently, a multi-level model in which this exact/metaheuristic hybrid is further hybridized with branch-and-bound techniques and mini-buckets is studied. Extensive experimental results analyze the performance of these models and multi-parent recombination. The resulting algorithm consistently finds optimal patterns for up to date solved instances in less time than current approaches. Moreover, it is shown that this proposal provides new best known solutions for very large instances.


The Complexity of Weighted Boolean #CSP with Mixed Signs

Abstract: We give a complexity dichotomy for the problem of computing the partition function of a weighted Boolean constraint satisfaction problem. Such a problem is parameterized by a set of rational-valued functions, which generalize constraints. Each function assigns a weight to every assignment to a set of Boolean variables. Our dichotomy extends previous work in which the weight functions were restricted to being non-negative. We represent a weight function as a product of the form (-1)^s g, where the polynomial s determines the sign of the weight and the non-negative function g determines its magnitude. We show that the problem of computing the partition function (the sum of the weights of all possible variable assignments) is in polynomial time if either every weight function can be defined by a "pure affine" magnitude with a quadratic sign polynomial or every function can be defined by a magnitude of "product type" with a linear sign polynomial. In all other cases, computing the partition function is FP^#P-complete.


XML Rewriting Attacks: Existing Solutions and their Limitations

Abstract: Web Services are web-based applications made available for web users or remote Web-based programs. In order to promote interoperability, they publish their interfaces in the so-called WSDL file and allow remote call over the network. Although Web Services can be used in different ways, the industry standard is the Service Oriented Architecture Web Services that doesn't rely on the implementation details. In this architecture, communication is performed through XML-based messages called SOAP messages. However, those messages are prone to attacks that can lead to code injection, unauthorized accesses, identity theft, etc. This type of attacks, called XML Rewriting Attacks, are all based on unauthorized, yet possible, modifications of SOAP messages. We present in this paper an explanation of this kind of attack, review the existing solutions, and show their limitations. We also propose some ideas to secure SOAP messages, as well as implementation ideas.


How Many Attackers Can Selfish Defenders Catch?

Abstract: In a distributed system with {\it attacks} and {\it defenses,} both {\it attackers} and {\it defenders} are self-interested entities. We assume a {\it reward-sharing} scheme among {\it interdependent} defenders; each defender wishes to (locally) maximize her own total {\it fair share} to the attackers extinguished due to her involvement (and possibly due to those of others). What is the {\em maximum} amount of protection achievable by a number of such defenders against a number of attackers while the system is in a {\it Nash equilibrium}? As a measure of system protection, we adopt the {\it Defense-Ratio} \cite{MPPS05a}, which provides the expected (inverse) proportion of attackers caught by the defenders. In a {\it Defense-Optimal} Nash equilibrium, the Defense-Ratio is optimized. We discover that the possibility of optimizing the Defense-Ratio (in a Nash equilibrium) depends in a subtle way on how the number of defenders compares to two natural graph-theoretic thresholds we identify. In this vein, we obtain, through a combinatorial analysis of Nash equilibria, a collection of trade-off results: - When the number of defenders is either sufficiently small or sufficiently large, there are cases where the Defense-Ratio can be optimized. The optimization problem is computationally tractable for a large number of defenders; the problem becomes ${\cal NP}$-complete for a small number of defenders and the intractability is inherited from a previously unconsidered combinatorial problem in {\em Fractional Graph Theory}. - Perhaps paradoxically, there is a middle range of values for the number of defenders where optimizing the Defense-Ratio is never possible.


Client-server multi-task learning from distributed datasets

Abstract: A client-server architecture to simultaneously solve multiple learning tasks from distributed datasets is described. In such architecture, each client is associated with an individual learning task and the associated dataset of examples. The goal of the architecture is to perform information fusion from multiple datasets while preserving privacy of individual data. The role of the server is to collect data in real-time from the clients and codify the information in a common database. The information coded in this database can be used by all the clients to solve their individual learning task, so that each client can exploit the informative content of all the datasets without actually having access to private data of others. The proposed algorithmic framework, based on regularization theory and kernel methods, uses a suitable class of mixed effect kernels. The new method is illustrated through a simulated music recommendation system.


Correlated Equilibria in Continuous Games: Characterization and Computation

Abstract: We present several new characterizations of correlated equilibria in games with continuous utility functions. These have the advantage of being more computationally and analytically tractable than the standard definition in terms of departure functions. We use these characterizations to construct effective algorithms for approximating a single correlated equilibrium or the entire set of correlated equilibria of a game with polynomial utility functions.


An Improved Approximation Algorithm for the Column Subset Selection Problem

Abstract: We consider the problem of selecting the best subset of exactly $k$ columns from an $m \times n$ matrix $A$. We present and analyze a novel two-stage algorithm that runs in $O(\min\{mn^2,m^2n\})$ time and returns as output an $m \times k$ matrix $C$ consisting of exactly $k$ columns of $A$. In the first (randomized) stage, the algorithm randomly selects $\Theta(k \log k)$ columns according to a judiciously-chosen probability distribution that depends on information in the top-$k$ right singular subspace of $A$. In the second (deterministic) stage, the algorithm applies a deterministic column-selection procedure to select and return exactly $k$ columns from the set of columns selected in the first stage. Let $C$ be the $m \times k$ matrix containing those $k$ columns, let $P_C$ denote the projection matrix onto the span of those columns, and let $A_k$ denote the best rank-$k$ approximation to the matrix $A$. Then, we prove that, with probability at least 0.8, $$ \FNorm{A - P_CA} \leq \Theta(k \log^{1/2} k) \FNorm{A-A_k}. $$ This Frobenius norm bound is only a factor of $\sqrt{k \log k}$ worse than the best previously existing existential result and is roughly $O(\sqrt{k!})$ better than the best previous algorithmic result for the Frobenius norm version of this Column Subset Selection Problem (CSSP). We also prove that, with probability at least 0.8, $$ \TNorm{A - P_CA} \leq \Theta(k \log^{1/2} k)\TNorm{A-A_k} + \Theta(k^{3/4}\log^{1/4}k)\FNorm{A-A_k}. $$ This spectral norm bound is not directly comparable to the best previously existing bounds for the spectral norm version of this CSSP. Our bound depends on $\FNorm{A-A_k}$, whereas previous results depend on $\sqrt{n-k}\TNorm{A-A_k}$; if these two quantities are comparable, then our bound is asymptotically worse by a $(k \log k)^{1/4}$ factor.


Solution of Peter Winkler's Pizza Problem

Abstract: Bob cuts a pizza into slices of not necessarily equal size and shares it with Alice by alternately taking turns. One slice is taken in each turn. The first turn is Alice's. She may choose any of the slices. In all other turns only those slices can be chosen that have a neighbor slice already eaten. We prove a conjecture of Peter Winkler by showing that Alice has a strategy for obtaining 4/9 of the pizza. This is best possible, that is, there is a cutting and a strategy for Bob to get 5/9 of the pizza. We also give a characterization of Alice's best possible gain depending on the number of slices. For a given cutting of the pizza, we describe a linear time algorithm that computes Alice's strategy gaining at least 4/9 of the pizza and another algorithm that computes the optimal strategy for both players in any possible position of the game in quadratic time. We distinguish two types of turns, shifts and jumps. We prove that Alice can gain 4/9, 7/16 and 1/3 of the pizza if she is allowed to make at most two jumps, at most one jump and no jump, respectively, and the three constants are the best possible.


Some sufficient conditions on Hamiltonian digraph

Abstract: Z-mapping graph is a balanced bipartite graph $G$ of a digraph $D$ by split each vertex of $D$ into a pair of vertices of $G$. Based on the property of the $G$, it is proved that if $D$ is strong connected and $G$ is Hamiltonian, then $D$ is Hamiltonian. It is also proved if $D$ is Hamiltonian, then $G$ contains at least a perfect matching. Thus some existence sufficient conditions for Hamiltonian digraph and Hamiltonian graph are proved to be equivalent, and two sufficient conditions of disjoint Hamiltonian digraph are given in this paper.


The Plane-Width of Graphs

Abstract: Map vertices of a graph to (not necessarily distinct) points of the plane so that two adjacent vertices are mapped at least a unit distance apart. The plane-width of a graph is the minimum diameter of the image of the vertex set over all such mappings. We establish a relation between the plane-width of a graph and its chromatic number, and connect it to other well-known areas, including the circular chromatic number and the problem of packing unit discs in the plane. We also investigate how plane-width behaves under various operations, such as homomorphism, disjoint union, complement, and the Cartesian product.


Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

Abstract: I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more beautiful. Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and (since 1990) artificial systems.


On Some Classes of Functions and Hypercubes

Abstract: In this paper, some classes of discrete functions of $k$-valued logic are considered, that depend on sets of their variables in a particular way. Obtained results allow to "construct" these functions and to present them in their tabular, analytical or matrix form, that is, as hypercubes, and in particular Latin hypercubes. Results connected with identifying of variables of some classes of functions are obtained.


An $O(k^{3} log n)$-Approximation Algorithm for Vertex-Connectivity Survivable Network Design

Abstract: In the Survivable Network Design problem (SNDP), we are given an undirected graph $G(V,E)$ with costs on edges, along with a connectivity requirement $r(u,v)$ for each pair $u,v$ of vertices. The goal is to find a minimum-cost subset $E^*$ of edges, that satisfies the given set of pairwise connectivity requirements. In the edge-connectivity version we need to ensure that there are $r(u,v)$ edge-disjoint paths for every pair $u, v$ of vertices, while in the vertex-connectivity version the paths are required to be vertex-disjoint. The edge-connectivity version of SNDP is known to have a 2-approximation. However, no non-trivial approximation algorithm has been known so far for the vertex version of SNDP, except for special cases of the problem. We present an extremely simple algorithm to achieve an $O(k^3 \log n)$-approximation for this problem, where $k$ denotes the maximum connectivity requirement, and $n$ denotes the number of vertices. We also give a simple proof of the recently discovered $O(k^2 \log n)$-approximation result for the single-source version of vertex-connectivity SNDP. We note that in both cases, our analysis in fact yields slightly better guarantees in that the $\log n$ term in the approximation guarantee can be replaced with a $\log \tau$ term where $\tau$ denotes the number of distinct vertices that participate in one or more pairs with a positive connectivity requirement.


The Latent Relation Mapping Engine: Algorithm and Experiments

Abstract: Many AI researchers and cognitive scientists have argued that analogy is the core of cognition. The most influential work on computational modeling of analogy-making is Structure Mapping Theory (SMT) and its implementation in the Structure Mapping Engine (SME). A limitation of SME is the requirement for complex hand-coded representations. We introduce the Latent Relation Mapping Engine (LRME), which combines ideas from SME and Latent Relational Analysis (LRA) in order to remove the requirement for hand-coded representations. LRME builds analogical mappings between lists of words, using a large corpus of raw text to automatically discover the semantic relations among the words. We evaluate LRME on a set of twenty analogical mapping problems, ten based on scientific analogies and ten based on common metaphors. LRME achieves human-level performance on the twenty problems. We compare LRME with a variety of alternative approaches and find that they are not able to reach the same level of performance.


Emergence of Spontaneous Order Through Neighborhood Formation in Peer-to-Peer Recommender Systems

Abstract: The advent of the Semantic Web necessitates paradigm shifts away from centralized client/server architectures towards decentralization and peer-to-peer computation, making the existence of central authorities superfluous and even impossible. At the same time, recommender systems are gaining considerable impact in e-commerce, providing people with recommendations that are personalized and tailored to their very needs. These recommender systems have traditionally been deployed with stark centralized scenarios in mind, operating in closed communities detached from their host network's outer perimeter. We aim at marrying these two worlds, i.e., decentralized peer-to-peer computing and recommender systems, in one agent-based framework. Our architecture features an epidemic-style protocol maintaining neighborhoods of like-minded peers in a robust, selforganizing fashion. In order to demonstrate our architecture's ability to retain scalability, robustness and to allow for convergence towards high-quality recommendations, we conduct offline experiments on top of the popular MovieLens dataset.


Mining User Profiles to Support Structure and Explanation in Open Social Networking

Abstract: The proliferation of media sharing and social networking websites has brought with it vast collections of site-specific user generated content. The result is a Social Networking Divide in which the concepts and structure common across different sites are hidden. The knowledge and structures from one social site are not adequately exploited to provide new information and resources to the same or different users in comparable social sites. For music bloggers, this latent structure, forces bloggers to select sub-optimal blogrolls. However, by integrating the social activities of music bloggers and listeners, we are able to overcome this limitation: improving the quality of the blogroll neighborhoods, in terms of similarity, by 85 percent when using tracks and by 120 percent when integrating tags from another site.


A computationally-efficient construction for the matrix-based key distribution in sensor network

Abstract: This paper introduces a variant for the symmetric matrix-based key distribution in sensor network introduced by Du et al. Our slight modification shows that the usage of specific structures for the public matrix instead of fully random matrix with elements in $\mathbb{Z}_q$ can reduce the computation overhead for generating the public key information and the key itself. An intensive analysis followed by modified scheme demonstrates the value of our contribution in relation with the current work and show the equivalence of the security


System Theoretic Viewpoint on Modeling of Complex Systems: Design, Synthesis, Simulation, and Control

Abstract: We consider the basic features of complex dynamic and control systems, including systems having hierarchical structure. Special attention is paid to the problems of design and synthesis of complex systems and control models, and to the development of simulation techniques and systems. A model of complex system is proposed and briefly analyzed.


Random Projections for the Nonnegative Least-Squares Problem

Abstract: Constrained least-squares regression problems, such as the Nonnegative Least Squares (NNLS) problem, where the variables are restricted to take only nonnegative values, often arise in applications. Motivated by the recent development of the fast Johnson-Lindestrauss transform, we present a fast random projection type approximation algorithm for the NNLS problem. Our algorithm employs a randomized Hadamard transform to construct a much smaller NNLS problem and solves this smaller problem using a standard NNLS solver. We prove that our approach finds a nonnegative solution vector that, with high probability, is close to the optimum nonnegative solution in a relative error approximation sense. We experimentally evaluate our approach on a large collection of term-document data and verify that it does offer considerable speedups without a significant loss in accuracy. Our analysis is based on a novel random projection type result that might be of independent interest. In particular, given a tall and thin matrix $\Phi \in \mathbb{R}^{n \times d}$ ($n \gg d$) and a vector $y \in \mathbb{R}^d$, we prove that the Euclidean length of $\Phi y$ can be estimated very accurately by the Euclidean length of $\tilde{\Phi}y$, where $\tilde{\Phi}$ consists of a small subset of (appropriately rescaled) rows of $\Phi$.


Time series of Internet AS-level topology graphs: four patterns and one model

Abstract: Researchers have proposed a variety of Internet topology models. However almost all of them focus on generating one graph based on one single static source graph. On the other hand, Internet topology is evolving over time continuously with the addition and deletion of nodes and edges. If a model is based on all the topologies in the past, instead of one of them, it will be more accurate and closer to the real world topology. In this paper, we study the Internet As-level topology time-series from two different sources and find that both of them obey four same dynamic graph patterns. Then we propose a mode that can infer the topology in the future based on all the topologies in the past. Through theoretical and experimental analysis, we prove the topology that our model generates can match both the static and dynamic graph patterns. In addition, the parameters in the model are meaningful. Finally, we theoretically and experimentally prove that these parameters are directly related to some important graph characteristics.


Indoor Channel Measurements and Communications System Design at 60 GHz

Abstract: This paper presents a brief overview of several studies concerning the indoor wireless communications at 60 GHz performed by the IETR. The characterization and the modeling of the radio propagation channel are based on several measurement campaigns realized with the channel sounder developed at IETR. Some typical residential environments were also simulated by ray tracing and Gaussian Beam Tracking. The obtained results show a good agreement with the similar experimental results. Currently, the IETR is developing a high data rate wireless communication system operating at 60 GHz. The single-carrier architecture of this system is also presented.


Induction and Co-induction in Sequent Calculus

Abstract: Proof search has been used to specify a wide range of computation systems. In order to build a framework for reasoning about such specifications, we make use of a sequent calculus involving induction and co-induction. These proof principles are based on a proof theoretic (rather than set-theoretic) notion of definition. Definitions are akin to (stratified) logic programs, where the left and right rules for defined atoms allow one to view theories as "closed" or defining fixed points. The use of definitions makes it possible to reason intensionally about syntax, in particular enforcing free equality via unification. We add in a consistent way rules for pre and post fixed points, thus allowing the user to reason inductively and co-inductively about properties of computational system making full use of higher-order abstract syntax. Consistency is guaranteed via cut-elimination, where we give the first, to our knowledge, cut-elimination procedure in the presence of general inductive and co-inductive definitions.


On Wireless Link Scheduling and Flow Control

Abstract: This thesis focuses on link scheduling in wireless mesh networks by taking into account physical layer characteristics. The assumption made throughout is that a packet is received successfully only if the Signal to Interference and Noise Ratio (SINR) at the receiver exceeds the communication threshold. The thesis also discusses the complementary problem of flow control. (1) We consider various problems on centralized link scheduling in Spatial Time Division Multiple Access (STDMA) wireless mesh networks. We motivate the use of spatial reuse as performance metric and provide an explicit characterization of spatial reuse. We propose link scheduling algorithms based on certain graph models (communication graph, SINR graph) of the network. Our algorithms achieve higher spatial reuse than that of existing algorithms, with only a slight increase in computational complexity. (2) We investigate random access algorithms in wireless networks. We assume that the receiver is capable of power-based capture and propose a splitting algorithm that varies transmission powers of users on the basis of quaternary channel feedback. We model the algorithm dynamics by a Discrete Time Markov Chain and consequently show that its maximum stable throughput is 0.5518. Our algorithm achieves higher maximum stable throughput and significantly lower delay than the First Come First Serve (FCFS) splitting algorithm with uniform transmission power. (3) We consider the problem of flow control in packet networks from an information-theoretic perspective. We derive the maximum entropy of a flow which conforms to traffic constraints imposed by a generalized token bucket regulator (GTBR), by taking into account the covert information present in randomness of packet lengths.


On Optimal Linear Redistribution of VCG Payments in Assignment of Heterogeneous Objects

Abstract: There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. Our main result is an impossibility theorem which rules out linear rebate functions with non-zero efficiency in heterogeneous object assignment. Motivated by this theorem, we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero are possible when the valuations for the objects are correlated. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed.


The Road Coloring for Mapping on k States(withdrawn)

Abstract: Let $\Gamma$ be directed strongly connected finite graph of uniform outdegree (constant outdegree of any vertex) and let some coloring of edges of $\Gamma$ turn the graph into deterministic complete automaton. Let the word $s$ be a word in the alphabet of colors (considered also as letters) on the edges of $\Gamma$ and let $\Gamma s$ be a mapping of vertices $\Gamma$.


Nominalistic Logic (Extended Abstract)

Abstract: Nominalistic Logic (NL) is a new presentation of Paul Gilmore's Intensional Type Theory (ITT) as a sequent calculus together with a succinct nominalization axiom (N) that permits names of predicates as individuals in certain cases. The logic has a flexible comprehension axiom, but no extensionality axiom and no infinity axiom, although axiom N is the key to the derivation of Peano's postulates for the natural numbers.


The Complexity of Generalized Satisfiability for Linear Temporal Logic

Abstract: In a seminal paper from 1985, Sistla and Clarke showed that satisfiability for Linear Temporal Logic (LTL) is either NP-complete or PSPACE-complete, depending on the set of temporal operators used. If, in contrast, the set of propositional operators is restricted, the complexity may decrease. This paper undertakes a systematic study of satisfiability for LTL formulae over restricted sets of propositional and temporal operators. Since every propositional operator corresponds to a Boolean function, there exist infinitely many propositional operators. In order to systematically cover all possible sets of them, we use Post's lattice. With its help, we determine the computational complexity of LTL satisfiability for all combinations of temporal operators and all but two classes of propositional functions. Each of these infinitely many problems is shown to be either PSPACE-complete, NP-complete, or in P.


Formalizing common sense for scalable inconsistency-robust information integration using Direct Logic(TM) reasoning and the Actor Model

Abstract: Because contemporary large software systems are pervasively inconsistent, it is not safe to reason about them using classical logic. The goal of Direct Logic is to be a minimal fix to classical mathematical logic that meets the requirements of large-scale Internet applications (including sense making for natural language) by addressing the following issues: inconsistency robustness, contrapositive inference bug, and direct argumentation. Direct Logic makes the following contributions over previous work: * Direct Inference (no contrapositive bug for inference) * Direct Argumentation (inference directly expressed) * Inconsistency-robust deduction without artifices such as indices (labels) on propositions or restrictions on reiteration * Intuitive inferences hold including the following: * Boolean Equivalences * Reasoning by splitting for disjunctive cases * Soundness * Inconsistency-robust Proof by Contradiction Since the global state model of computation (first formalized by Turing) is inadequate to the needs of modern large-scale Internet applications the Actor Model was developed to meet this need. Using, the Actor Model, this paper proves that Logic Programming is not computationally universal in that there are computations that cannot be implemented using logical inference. Consequently the Logic Programming paradigm is strictly less general than the Procedural Embedding of Knowledge paradigm.


Almost stable matchings in constant time

Abstract: We show that the ratio of matched individuals to blocking pairs grows linearly with the number of propose--accept rounds executed by the Gale--Shapley algorithm for the stable marriage problem. Consequently, the participants can arrive at an almost stable matching even without full information about the problem instance; for each participant, knowing only its local neighbourhood is enough. In distributed-systems parlance, this means that if each person has only a constant number of acceptable partners, an almost stable matching emerges after a constant number of synchronous communication rounds. This holds even if ties are present in the preference lists. We apply our results to give a distributed $(2+\epsilon)$-approximation algorithm for maximum-weight matching in bicoloured graphs and a centralised randomised constant-time approximation scheme for estimating the size of a stable matching.


Obtaining a Planar Graph by Vertex Deletion

Abstract: In the k-Apex problem the task is to find at most k vertices whose deletion makes the given graph planar. The graphs for which there exists a solution form a minor closed class of graphs, hence by the deep results of Robertson and Seymour, there is an O(n^3) time algorithm for every fixed value of k. However, the proof is extremely complicated and the constants hidden by the big-O notation are huge. Here we give a much simpler algorithm for this problem with quadratic running time, by iteratively reducing the input graph and then applying techniques for graphs of bounded treewidth.


Importance Weighted Active Learning

Abstract: We present a practical and statistically consistent scheme for actively learning binary classifiers under general loss functions. Our algorithm uses importance weighting to correct sampling bias, and by controlling the variance, we are able to give rigorous label complexity bounds for the learning process. Experiments on passively labeled data show that this approach reduces the label complexity required to achieve good predictive performance on many learning problems.


A Simple, Linear-Time Algorithm for x86 Jump Encoding

Abstract: The problem of space-optimal jump encoding in the x86 instruction set, also known as branch displacement optimization, is described, and a linear-time algorithm is given that uses no complicated data structures, no recursion, and no randomization. The only assumption is that there are no array declarations whose size depends on the negative of the size of a section of code (Hyde 2006), which is reasonable for real code.


Bootstrapping Key Pre-Distribution: Secure, Scalable and User-Friendly Initialization of Sensor Nodes

Abstract: To establish secure (point-to-point and/or broadcast) communication channels among the nodes of a wireless sensor network is a fundamental task. To this end, a plethora of (socalled) key pre-distribution schemes have been proposed in the past. All these schemes, however, rely on shared secret(s), which are assumed to be somehow pre-loaded onto the sensor nodes. In this paper, we propose a novel method for secure initialization of sensor nodes based on a visual out-of-band channel. Using the proposed method, the administrator of a sensor network can distribute keys onto the sensor nodes, necessary to bootstrap key pre-distribution. Our secure initialization method requires only a little extra cost, is efficient and scalable with respect to the number of sensor nodes. Moreover, based on a usability study that we conducted, the method turns out to be quite user-friendly and easy to use by naive human users.


An Array Algebra

Abstract: This is a proposal of an algebra which aims at distributed array processing. The focus lies on re-arranging and distributing array data, which may be multi-dimensional. The context of the work is scientific processing; thus, the core science operations are assumed to be taken care of in external libraries or languages. A main design driver is the desire to carry over some of the strategies of the relational algebra into the array domain.


A Pseudopolynomial Algorithm for Alexandrov's Theorem

Abstract: Alexandrov's Theorem states that every metric with the global topology and local geometry required of a convex polyhedron is in fact the intrinsic metric of a unique convex polyhedron. Recent work by Bobenko and Izmestiev describes a differential equation whose solution leads to the polyhedron corresponding to a given metric. We describe an algorithm based on this differential equation to compute the polyhedron to arbitrary precision given the metric, and prove a pseudopolynomial bound on its running time. Along the way, we develop pseudopolynomial algorithms for computing shortest paths and weighted Delaunay triangulations on a polyhedral surface, even when the surface edges are not shortest paths.


A 7/9 - Approximation Algorithm for the Maximum Traveling Salesman Problem

Abstract: We give a 7/9 - Approximation Algorithm for the Maximum Traveling Salesman Problem.


Symmetric and Asymmetric Asynchronous Interaction

Abstract: We investigate classes of systems based on different interaction patterns with the aim of achieving distributability. As our system model we use Petri nets. In Petri nets, an inherent concept of simultaneity is built in, since when a transition has more than one preplace, it can be crucial that tokens are removed instantaneously. When modelling a system which is intended to be implemented in a distributed way by a Petri net, this built-in concept of synchronous interaction may be problematic. To investigate this we consider asynchronous implementations of nets, in which removing tokens from places can no longer be considered as instantaneous. We model this by inserting silent (unobservable) transitions between transitions and some of their preplaces. We investigate three such implementations, differing in the selection of preplaces of a transition from which the removal of a token is considered time consuming, and the possibility of collecting the tokens in a given order. We investigate the effect of these different transformations of instantaneous interaction into asynchronous interaction patterns by comparing the behaviours of nets before and after insertion of the silent transitions. We exhibit for which classes of Petri nets we obtain equivalent behaviour with respect to failures equivalence. It turns out that the resulting hierarchy of Petri net classes can be described by semi-structural properties. For two of the classes we obtain precise characterisations; for the remaining class we obtain lower and upper bounds. We briefly comment on possible applications of our results to Message Sequence Charts.


On Synchronous and Asynchronous Interaction in Distributed Systems

Abstract: When considering distributed systems, it is a central issue how to deal with interactions between components. In this paper, we investigate the paradigms of synchronous and asynchronous interaction in the context of distributed systems. We investigate to what extent or under which conditions synchronous interaction is a valid concept for specification and implementation of such systems. We choose Petri nets as our system model and consider different notions of distribution by associating locations to elements of nets. First, we investigate the concept of simultaneity which is inherent in the semantics of Petri nets when transitions have multiple input places. We assume that tokens may only be taken instantaneously by transitions on the same location. We exhibit a hierarchy of `asynchronous' Petri net classes by different assumptions on possible distributions. Alternatively, we assume that the synchronisations specified in a Petri net are crucial system properties. Hence transitions and their preplaces may no longer placed on separate locations. We then answer the question which systems may be implemented in a distributed way without restricting concurrency, assuming that locations are inherently sequential. It turns out that in both settings we find semi-structural properties of Petri nets describing exactly the problematic situations for interactions in distributed systems.


Exact Histogram Specification Optimized for Structural Similarity

Abstract: An exact histogram specification (EHS) method modifies its input image to have a specified histogram. Applications of EHS include image (contrast) enhancement (e.g., by histogram equalization) and histogram watermarking. Performing EHS on an image, however, reduces its visual quality. Starting from the output of a generic EHS method, we maximize the structural similarity index (SSIM) between the original image (before EHS) and the result of EHS iteratively. Essential in this process is the computationally simple and accurate formula we derive for SSIM gradient. As it is based on gradient ascent, the proposed EHS always converges. Experimental results confirm that while obtaining the histogram exactly as specified, the proposed method invariably outperforms the existing methods in terms of visual quality of the result. The computational complexity of the proposed method is shown to be of the same order as that of the existing methods. Index terms: histogram modification, histogram equalization, optimization for perceptual visual quality, structural similarity gradient ascent, histogram watermarking, contrast enhancement.


Cloud Computing and Grid Computing 360-Degree Compared

Abstract: Cloud Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Cloud Computing and there seems to be no consensus on what a Cloud is. On the other hand, Cloud Computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established Grid Computing paradigm, and other relevant technologies such as utility computing, cluster computing, and distributed systems in general. This paper strives to compare and contrast Cloud Computing with Grid Computing from various angles and give insights into the essential characteristics of both.


Design and Evaluation of a Collective IO Model for Loosely Coupled Petascale Programming

Abstract: Loosely coupled programming is a powerful paradigm for rapidly creating higher-level applications from scientific programs on petascale systems, typically using scripting languages. This paradigm is a form of many-task computing (MTC) which focuses on the passing of data between programs as ordinary files rather than messages. While it has the significant benefits of decoupling producer and consumer and allowing existing application programs to be executed in parallel with no recoding, its typical implementation using shared file systems places a high performance burden on the overall system and on the user who will analyze and consume the downstream data. Previous efforts have achieved great speedups with loosely coupled programs, but have done so with careful manual tuning of all shared file system access. In this work, we evaluate a prototype collective IO model for file-based MTC. The model enables efficient and easy distribution of input data files to computing nodes and gathering of output results from them. It eliminates the need for such manual tuning and makes the programming of large-scale clusters using a loosely coupled model easier. Our approach, inspired by in-memory approaches to collective operations for parallel programming, builds on fast local file systems to provide high-speed local file caches for parallel scripts, uses a broadcast approach to handle distribution of common input data, and uses efficient scatter/gather and caching techniques for input and output. We describe the design of the prototype model, its implementation on the Blue Gene/P supercomputer, and present preliminary measurements of its performance on synthetic benchmarks and on a large-scale molecular dynamics application.


Using constraint programming to resolve the multi-source/multi-site data movement paradigm on the Grid

Abstract: In order to achieve both fast and coordinated data transfer to collaborative sites as well as to create a distribution of data over multiple sites, efficient data movement is one of the most essential aspects in distributed environment. With such capabilities at hand, truly distributed task scheduling with minimal latencies would be reachable by internationally distributed collaborations (such as ones in HENP) seeking for scavenging or maximizing on geographically spread computational resources. But it is often not all clear (a) how to move data when available from multiple sources or (b) how to move data to multiple compute resources to achieve an optimal usage of available resources. We present a method of creating a Constraint Programming (CP) model consisting of sites, links and their attributes such as bandwidth for grid network data transfer also considering user tasks as part of the objective function for an optimal solution. We will explore and explain trade-off between schedule generation time and divergence from the optimal solution and show how to improve and render viable the solution's finding time by using search tree time limit, approximations, restrictions such as symmetry breaking or grouping similar tasks together, or generating sequence of optimal schedules by splitting the input problem. Results of data transfer simulation for each case will also include a well known Peer-2-Peer model, and time taken to generate a schedule as well as time needed for a schedule execution will be compared to a CP optimal solution. We will additionally present a possible implementation aimed to bring a distributed datasets (multiple sources) to a given site in a minimal time.


Techniques for Distributed Reachability Analysis with Partial Order and Symmetry based Reductions

Abstract: In this work we propose techniques for efficient reachability analysis of the state space (e.g., detection of bad states) using a combination of partial order and symmetry based reductions in a distributed setting. The proposed techniques are focused towards explicit state space enumeration based model-checkers like SPIN. We consider variants for both depth-first as well as breadth-first based generation of the reduced state graphs on-the-fly.


On Allocating Goods to Maximize Fairness

Abstract: Given a set of $m$ agents and a set of $n$ items, where agent $A$ has utility $u_{A,i}$ for item $i$, our goal is to allocate items to agents to maximize fairness. Specifically, the utility of an agent is the sum of its utilities for items it receives, and we seek to maximize the minimum utility of any agent. While this problem has received much attention recently, its approximability has not been well-understood thus far: the best known approximation algorithm achieves an $\tilde{O}(\sqrt{m})$-approximation, and in contrast, the best known hardness of approximation stands at 2. Our main result is an approximation algorithm that achieves an $\tilde{O}(n^{\eps})$ approximation for any $\eps=\Omega(\log\log n/\log n)$ in time $n^{O(1/\eps)}$. In particular, we obtain poly-logarithmic approximation in quasi-polynomial time, and for any constant $\eps > 0$, we obtain $O(n^{\eps})$ approximation in polynomial time. An interesting aspect of our algorithm is that we use as a building block a linear program whose integrality gap is $\Omega(\sqrt m)$. We bypass this obstacle by iteratively using the solutions produced by the LP to construct new instances with significantly smaller integrality gaps, eventually obtaining the desired approximation. We also investigate the special case of the problem, where every item has a non-zero utility for at most two agents. We show that even in this restricted setting the problem is hard to approximate upto any factor better tha 2, and show a factor $(2+\eps)$-approximation algorithm running in time $poly(n,1/\eps)$ for any $\eps>0$. This special case can be cast as a graph edge orientation problem, and our algorithm can be viewed as a generalization of Eulerian orientations to weighted graphs.


Filtering Microarray Correlations by Statistical Literature Analysis Yields Potential Hypotheses for Lactation Research

Abstract: Our results demonstrated that a previously reported protein name co-occurrence method (5-mention PubGene) which was not based on a hypothesis testing framework, it is generally statistically more significant than the 99th percentile of Poisson distribution-based method of calculating co-occurrence. It agrees with previous methods using natural language processing to extract protein-protein interaction from text as more than 96% of the interactions found by natural language processing methods to overlap with the results from 5-mention PubGene method. However, less than 2% of the gene co-expressions analyzed by microarray were found from direct co-occurrence or interaction information extraction from the literature. At the same time, combining microarray and literature analyses, we derive a novel set of 7 potential functional protein-protein interactions that had not been previously described in the literature.


Dynamic Muscle Fatigue Evaluation in Virtual Working Environment

Abstract: Musculoskeletal disorder (MSD) is one of the major health problems in mechanical work especially in manual handling jobs. Muscle fatigue is believed to be the main reason for MSD. Posture analysis techniques have been used to expose MSD risks of the work, but most of the conventional methods are only suitable for static posture analysis. Meanwhile the subjective influences from the inspectors can result differences in the risk assessment. Another disadvantage is that the evaluation has to be taken place in the workshop, so it is impossible to avoid some design defects before data collection in the field environment and it is time consuming. In order to enhance the efficiency of ergonomic MSD risk evaluation and avoid subjective influences, we develop a new muscle fatigue model and a new fatigue index to evaluate the human muscle fatigue during manual handling jobs in this paper. Our new fatigue model is closely related to the muscle load during working procedure so that it can be used to evaluate the dynamic working process. This muscle fatigue model is mathematically validated and it is to be further experimental validated and integrated into a virtual working environment to evaluate the muscle fatigue and predict the MSD risks quickly and objectively.


Offline Algorithmic Techniques for Several Content Delivery Problems in Some Restricted Types of Distributed Systems

Abstract: In this paper we consider several content delivery problems (broadcast and multicast, in particular) in some restricted types of distributed systems (e.g. optical Grids and wireless sensor networks with tree-like topologies). For each problem we provide efficient algorithmic techniques for computing optimal content delivery strategies. The techniques we present are offline, which means that they can be used only when full information is available and the problem parameters do not fluctuate too much.


An Algorithm for File Transfer Scheduling in Grid Environments

Abstract: This paper addresses the data transfer scheduling problem for Grid environments, presenting a centralized scheduler developed with dynamic and adaptive features. The algorithm offers a reservation system for user transfer requests that allocates them transfer times and bandwidth, according to the network topology and the constraints the user specified for the requests. This paper presents the projects related to the data transfer field, the design of the framework for which the scheduler was built, the main features of the scheduler, the steps for transfer requests rescheduling and two tests that illustrate the system's behavior for different types of transfer requests.


Design of a P System based Artificial Graph Chemistry

Abstract: Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and to develop a unified framework to characterize and classify symbolic artificial chemistries by devising appropriate formalism to capture semantic and organizational information. An extension of P system is considered by associating probabilities with the rules providing the topological framework for the evolution of a labeled undirected graph based molecular reaction semantics.


Resolution-based Query Answering for Semantic Access to Relational Databases: A Research Note

Abstract: We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent instantiation of these schematic answers using a conventional relational DBMS. In this research note, we outline the main idea of this technique -- using abstractions of databases and constrained clauses for deriving schematic answers. The proposed method can be directly used with regular RDB, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.


Protecting infrastructure networks from cost-based attacks

Abstract: It has been known that heterogeneous networks are vulnerable to the intentional removal of a small fraction of highly connected or loaded nodes, which implies that, to protect a network effectively, a few important nodes should be allocated with more defense resources than the others. However, if too many resources are allocated to the few important nodes, the numerous less-important nodes will be less protected, which, when attacked all together, still capable of causing a devastating damage. A natural question therefore is how to efficiently distribute the limited defense resources among the network nodes such that the network damage is minimized whatever attack strategy the attacker may take. In this paper, taking into account the factor of attack cost, we will revisit the problem of network security and search for efficient network defense against the cost-based attacks. The study shows that, for a general complex network, there will exist an optimal distribution of the defense resources, with which the network is well protected from cost-based attacks. Furthermore, it is found that the configuration of the optimal defense is dependent on the network parameters. Specifically, network that has a larger size, sparser connection and more heterogeneous structure will be more benefited from the defense optimization.


Weighted Naive Bayes Model for Semi-Structured Document Categorization

Abstract: The aim of this paper is the supervised classification of semi-structured data. A formal model based on bayesian classification is developed while addressing the integration of the document structure into classification tasks. We define what we call the structural context of occurrence for unstructured data, and we derive a recursive formulation in which parameters are used to weight the contribution of structural element relatively to the others. A simplified version of this formal model is implemented to carry out textual documents classification experiments. First results show, for a adhoc weighting strategy, that the structural context of word occurrences has a significant impact on classification results comparing to the performance of a simple multinomial naive Bayes classifier. The proposed implementation competes on the Reuters-21578 data with the SVM classifier associated or not with the splitting of structural components. These results encourage exploring the learning of acceptable weighting strategies for this model, in particular boosting strategies.


Interprocedural Dataflow Analysis over Weight Domains with Infinite Descending Chains

Abstract: We study generalized fixed-point equations over idempotent semirings and provide an efficient algorithm for the detection whether a sequence of Kleene's iterations stabilizes after a finite number of steps. Previously known approaches considered only bounded semirings where there are no infinite descending chains. The main novelty of our work is that we deal with semirings without the boundedness restriction. Our study is motivated by several applications from interprocedural dataflow analysis. We demonstrate how the reachability problem for weighted pushdown automata can be reduced to solving equations in the framework mentioned above and we describe a few applications to demonstrate its usability.


Measures for classification and detection in steganalysis

Abstract: Still and multi-media images are subject to transformations for compression, steganographic embedding and digital watermarking. In a major program of activities we are engaged in the modeling, design and analysis of digital content. Statistical and pattern classification techniques should be combined with understanding of run length, transform coding techniques, and also encryption techniques.


On the Optimal Convergence Probability of Univariate Estimation of Distribution Algorithms

Abstract: In this paper, we obtain bounds on the probability of convergence to the optimal solution for the compact Genetic Algorithm (cGA) and the Population Based Incremental Learning (PBIL). We also give a sufficient condition for convergence of these algorithms to the optimal solution and compute a range of possible values of the parameters of these algorithms for which they converge to the optimal solution with a confidence level.


A Step Forward in Studying the Compact Genetic Algorithm

Abstract: The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent population instead of using traditional recombination and mutation operators. The cGA only needs a small amount of memory; therefore, it may be quite useful in memory-constrained applications. This paper introduces a theoretical framework for studying the cGA from the convergence point of view in which, we model the cGA by a Markov process and approximate its behavior using an Ordinary Differential Equation (ODE). Then, we prove that the corresponding ODE converges to local optima and stays there. Consequently, we conclude that the cGA will converge to the local optima of the function to be optimized.


Contextual hypotheses and semantics of logic programs

Abstract: Logic programming has developed as a rich field, built over a logical substratum whose main constituent is a nonclassical form of negation, sometimes coexisting with classical negation. The field has seen the advent of a number of alternative semantics, with Kripke-Kleene semantics, the well-founded semantics, the stable model semantics, and the answer-set semantics standing out as the most successful. We show that all aforementioned semantics are particular cases of a generic semantics, in a framework where classical negation is the unique form of negation and where the literals in the bodies of the rules can be `marked' to indicate that they can be the targets of hypotheses. A particular semantics then amounts to choosing a particular marking scheme and choosing a particular set of hypotheses. When a literal belongs to the chosen set of hypotheses, all marked occurrences of that literal in the body of a rule are assumed to be true, whereas the occurrences of that literal that have not been marked in the body of the rule are to be derived in order to contribute to the firing of the rule. Hence the notion of hypothetical reasoning that is presented in this framework is not based on making global assumptions, but more subtly on making local, contextual assumptions, taking effect as indicated by the chosen marking scheme on the basis of the chosen set of hypotheses. Our approach offers a unified view on the various semantics proposed in logic programming, classical in that only classical negation is used, and links the semantics of logic programs to mechanisms that endow rule-based systems with the power to harness hypothetical reasoning.


Distributed Preemption Decisions: Probabilistic Graphical Model, Algorithm and Near-Optimality

Abstract: Cooperative decision making is a vision of future network management and control. Distributed connection preemption is an important example where nodes can make intelligent decisions on allocating resources and controlling traffic flows for multi-class service networks. A challenge is that nodal decisions are spatially dependent as traffic flows trespass multiple nodes in a network. Hence the performance-complexity trade-off becomes important, i.e., how accurate decisions are versus how much information is exchanged among nodes. Connection preemption is known to be NP-complete. Centralized preemption is optimal but computationally intractable. Decentralized preemption is computationally efficient but may result in a poor performance. This work investigates distributed preemption where nodes decide whether and which flows to preempt using only local information exchange with neighbors. We develop, based on the probabilistic graphical models, a near-optimal distributed algorithm. The algorithm is used by each node to make collectively near-optimal preemption decisions. We study trade-offs between near-optimal performance and complexity that corresponds to the amount of information-exchange of the distributed algorithm. The algorithm is validated by both analysis and simulation.


A Theoretical Analysis of Joint Manifolds

Abstract: The emergence of low-cost sensor architectures for diverse modalities has made it possible to deploy sensor arrays that capture a single event from a large number of vantage points and using multiple modalities. In many scenarios, these sensors acquire very high-dimensional data such as audio signals, images, and video. To cope with such high-dimensional data, we typically rely on low-dimensional models. Manifold models provide a particularly powerful model that captures the structure of high-dimensional data when it is governed by a low-dimensional set of parameters. However, these models do not typically take into account dependencies among multiple sensors. We thus propose a new joint manifold framework for data ensembles that exploits such dependencies. We show that simple algorithms can exploit the joint manifold structure to improve their performance on standard signal processing applications. Additionally, recent results concerning dimensionality reduction for manifolds enable us to formulate a network-scalable data compression scheme that uses random projections of the sensed data. This scheme efficiently fuses the data from all sensors through the addition of such projections, regardless of the data modalities and dimensions.


Approximate inference on planar graphs using Loop Calculus and Belief Propagation

Abstract: We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006) allows to express the exact partition function of a graphical model as a finite sum of terms that can be evaluated once the belief propagation (BP) solution is known. In general, full summation over all correction terms is intractable. We develop an algorithm for the approach presented in (Certkov et al., 2008) which represents an efficient truncation scheme on planar graphs and a new representation of the series in terms of Pfaffians of matrices. We analyze the performance of the algorithm for the partition function approximation for models with binary variables and pairwise interactions on grids and other planar graphs. We study in detail both the loop series and the equivalent Pfaffian series and show that the first term of the Pfaffian series for the general, intractable planar model, can provide very accurate approximations. The algorithm outperforms previous truncation schemes of the loop series and is competitive with other state-of-the-art methods for approximate inference.


A new muscle fatigue and recovery model and its ergonomics application in human simulation

Abstract: Although automatic techniques have been employed in manufacturing industries to increase productivity and efficiency, there are still lots of manual handling jobs, especially for assembly and maintenance jobs. In these jobs, musculoskeletal disorders (MSDs) are one of the major health problems due to overload and cumulative physical fatigue. With combination of conventional posture analysis techniques, digital human modelling and simulation (DHM) techniques have been developed and commercialized to evaluate the potential physical exposures. However, those ergonomics analysis tools are mainly based on posture analysis techniques, and until now there is still no fatigue index available in the commercial software to evaluate the physical fatigue easily and quickly. In this paper, a new muscle fatigue and recovery model is proposed and extended to evaluate joint fatigue level in manual handling jobs. A special application case is described and analyzed by digital human simulation technique.


Weighted Well-Covered Graphs without Cycles of Length 4, 5, 6 and 7

Abstract: A graph is well-covered if every maximal independent set has the same cardinality. The recognition problem of well-covered graphs is known to be co-NP-complete. Let w be a weight function defined on the vertices of G. Then G is w-well-covered if all maximal independent sets of G are of the same weight. The set of weight functions w for which a graph is w-well-covered is a vector space. We prove that finding the vector space of weight functions under which an input graph is w-well-covered can be done in polynomial time, if the input graph does not contain cycles of length 4, 5, 6 and 7.


On the Complexity of Deciding Call-by-Need

Abstract: In a recent paper we introduced a new framework for the study of call by need computations to normal form and root-stable form in term rewriting. Using elementary tree automata techniques and ground tree transducers we obtained simple decidability proofs for classes of rewrite systems that are much larger than earlier classes defined using the complicated sequentiality concept. In this paper we show that we can do without ground tree transducers in order to arrive at decidability proofs that are phrased in direct tree automata constructions. This allows us to derive better complexity bounds.


Developments in ROOT I/O and trees

Abstract: For the last several months the main focus of development in the ROOT I/O package has been code consolidation and performance improvements. Access to remote files is affected both by bandwidth and latency. We introduced a pre-fetch mechanism to minimize the number of transactions between client and server and hence reducing the effect of latency. We will review the implementation and how well it works in different conditions (gain of an order of magnitude for remote file access). We will also review new utilities, including a faster implementation of TTree cloning (gain of an order of magnitude), a generic mechanism for object references, and a new entry list mechanism tuned both for small and large number of selections. In addition to reducing the coupling with the core module and becoming its owns library (libRIO) (as part of the general restructuration of the ROOT libraries), the I/O package has been enhanced in the area of XML and SQL support, thread safety, schema evolution, TTreeFormula, and many other areas. We will also discuss various ways, ROOT will be able to benefit from multi-core architecture to improve I/O performances.


Fault Attacks on RSA Public Keys: Left-To-Right Implementations are also Vulnerable

Abstract: After attacking the RSA by injecting fault and corresponding countermeasures, works appear now about the need for protecting RSA public elements against fault attacks. We provide here an extension of a recent attack based on the public modulus corruption. The difficulty to decompose the "Left-To-Right" exponentiation into partial multiplications is overcome by modifying the public modulus to a number with known factorization. This fault model is justified here by a complete study of faulty prime numbers with a fixed size. The good success rate of this attack combined with its practicability raises the question of using faults for changing algebraic properties of finite field based cryptosystems.


An \Omega(n log n) lower bound for computing the sum of even-ranked elements

Abstract: Given a sequence A of 2n real numbers, the Even-Rank-Sum problem asks for the sum of the n values that are at the even positions in the sorted order of the elements in A. We prove that, in the algebraic computation-tree model, this problem has time complexity \Theta(n log n). This solves an open problem posed by Michael Shamos at the Canadian Conference on Computational Geometry in 2008.


Identification with Encrypted Biometric Data

Abstract: Biometrics make human identification possible with a sample of a biometric trait and an associated database. Classical identification techniques lead to privacy concerns. This paper introduces a new method to identify someone using his biometrics in an encrypted way. Our construction combines Bloom Filters with Storage and Locality-Sensitive Hashing. We apply this error-tolerant scheme, in a Hamming space, to achieve biometric identification in an efficient way. This is the first non-trivial identification scheme dealing with fuzziness and encrypted data.


FAIR: Fuzzy-based Aggregation providing In-network Resilience for real-time Wireless Sensor Networks

Abstract: This work introduces FAIR, a novel framework for Fuzzy-based Aggregation providing In-network Resilience for Wireless Sensor Networks. FAIR addresses the possibility of malicious aggregator nodes manipulating data. It provides data-integrity based on a trust level of the WSN response and it tolerates link or node failures. Compared to available solutions, it offers a general aggregation model and makes the trust level visible to the querier. We classify the proposed approach as complementary to protocols ensuring resilience against sensor leaf nodes providing faulty data. Thanks to our flexible resilient framework and due to the use of Fuzzy Inference Schemes, we achieve promising results within a short design cycle.


A High Dynamic Range 3-Moduli-Set with Efficient Reverse Converter

Abstract: -Residue Number System (RNS) is a valuable tool for fast and parallel arithmetic. It has a wide application in digital signal processing, fault tolerant systems, etc. In this work, we introduce the 3-moduli set {2^n, 2^{2n}-1, 2^{2n}+1} and propose its residue to binary converter using the Chinese Remainder Theorem. We present its simple hardware implementation that mainly includes one Carry Save Adder (CSA) and a Modular Adder (MA). We compare the performance and area utilization of our reverse converter to the reverse converters of the moduli sets {2^n-1, 2^n, 2^n+1, 2^{2n}+1} and {2^n-1, 2^n, 2^n+1, 2^n-2^{(n+1)/2}+1, 2^n+2^{(n+1)/2}+1} that have the same dynamic range and we demonstrate that our architecture is better in terms of performance and area utilization. Also, we show that our reverse converter is faster than the reverse converter of {2^n-1, 2^n, 2^n+1} for dynamic ranges like 8-bit, 16-bit, 32-bit and 64-bit however it requires more area.


On Profit-Maximizing Pricing for the Highway and Tollbooth Problems

Abstract: In the \emph{tollbooth problem}, we are given a tree $\bT=(V,E)$ with $n$ edges, and a set of $m$ customers, each of whom is interested in purchasing a path on the tree. Each customer has a fixed budget, and the objective is to price the edges of $\bT$ such that the total revenue made by selling the paths to the customers that can afford them is maximized. An important special case of this problem, known as the \emph{highway problem}, is when $\bT$ is restricted to be a line. For the tollbooth problem, we present a randomized $O(\log n)$-approximation, improving on the current best $O(\log m)$-approximation. We also study a special case of the tollbooth problem, when all the paths that customers are interested in purchasing go towards a fixed root of $\bT$. In this case, we present an algorithm that returns a $(1-\epsilon)$-approximation, for any $\epsilon > 0$, and runs in quasi-polynomial time. On the other hand, we rule out the existence of an FPTAS by showing that even for the line case, the problem is strongly NP-hard. Finally, we show that in the \emph{coupon model}, when we allow some items to be priced below zero to improve the overall profit, the problem becomes even APX-hard.


A nonclassical symbolic theory of working memory, mental computations, and mental set

Abstract: The paper tackles four basic questions associated with human brain as a learning system. How can the brain learn to (1) mentally simulate different external memory aids, (2) perform, in principle, any mental computations using imaginary memory aids, (3) recall the real sensory and motor events and synthesize a combinatorial number of imaginary events, (4) dynamically change its mental set to match a combinatorial number of contexts? We propose a uniform answer to (1)-(4) based on the general postulate that the human neocortex processes symbolic information in a "nonclassical" way. Instead of manipulating symbols in a read/write memory, as the classical symbolic systems do, it manipulates the states of dynamical memory representing different temporary attributes of immovable symbolic structures stored in a long-term memory. The approach is formalized as the concept of E-machine. Intuitively, an E-machine is a system that deals mainly with characteristic functions representing subsets of memory pointers rather than the pointers themselves. This nonclassical symbolic paradigm is Turing universal, and, unlike the classical one, is efficiently implementable in homogeneous neural networks with temporal modulation topologically resembling that of the neocortex.


Fault Masking By Probabilistic Voting

Abstract: In this study, we introduced a probabilistic voter, regarding symbol probabilities in decision process besides majority consensus. Conventional majority voter is independent of functionality of redundant modules. In our study, proposed probabilistic voter is designed corresponding to functionality of the redundant module. We tested probabilistic voter for 3 and 5 redundant modules with random transient errors inserted the wires and it was seen from simulation results that Multi-Modular Redundancy (M-MR) with Probabilistic Voting (PV) had been shown better availability performance than conventional majority voter.


Logical Algorithms meets CHR: A meta-complexity result for Constraint Handling Rules with rule priorities

Abstract: This paper investigates the relationship between the Logical Algorithms language (LA) of Ganzinger and McAllester and Constraint Handling Rules (CHR). We present a translation schema from LA to CHR-rp: CHR with rule priorities, and show that the meta-complexity theorem for LA can be applied to a subset of CHR-rp via inverse translation. Inspired by the high-level implementation proposal for Logical Algorithm by Ganzinger and McAllester and based on a new scheduling algorithm, we propose an alternative implementation for CHR-rp that gives strong complexity guarantees and results in a new and accurate meta-complexity theorem for CHR-rp. It is furthermore shown that the translation from Logical Algorithms to CHR-rp combined with the new CHR-rp implementation, satisfies the required complexity for the Logical Algorithms meta-complexity result to hold.


An Internet-based Audience Response System for the Improvement of Teaching

Abstract: We have developed an Internet-based audience response system (called ARSBO). In this way we combine the advantages of common audience response systems using handheld devices and the easy and cheap access to the Internet. Evaluations of audience response systems in the literature have shown their success: encouraging participation of the students as well as immediate feedback to answers to the whole group for evaluational purposes of the teacher. However, commercial systems are relatively expensive and the number of students in such a teaching-learning scenario is limited. ARSBO solves these problems. Using the Internet (e.g. in computer rooms or by wireless Internet access) there are no special costs and the number of participating students is not limited. ARSBO is very easy to use for students as well as for the construction of new questions with possible answers and for the visualization of statistical results to questions.


N-norm and N-conorm in Neutrosophic Logic and Set, and the Neutrosophic Topologies

Abstract: In this paper we present the N-norms/N-conorms in neutrosophic logic and set as extensions of T-norms/T-conorms in fuzzy logic and set. Also, as an extension of the Intuitionistic Fuzzy Topology we present the Neutrosophic Topologies.


Using Graphics Processors for Parallelizing Hash-based Data Carving

Abstract: The ability to detect fragments of deleted image files and to reconstruct these image files from all available fragments on disk is a key activity in the field of digital forensics. Although reconstruction of image files from the file fragments on disk can be accomplished by simply comparing the content of sectors on disk with the content of known files, this brute-force approach can be time consuming. This paper presents results from research into the use of Graphics Processing Units (GPUs) in detecting specific image file byte patterns in disk clusters. Unique identifying pattern for each disk sector is compared against patterns in known images. A pattern match indicates the potential presence of an image and flags the disk sector for further in-depth examination to confirm the match. The GPU-based implementation outperforms the software implementation by a significant margin.


Novel Architectures and Algorithms for Delay Reduction in Back-pressure Scheduling and Routing

Abstract: The back-pressure algorithm is a well-known throughput-optimal algorithm. However, its delay performance may be quite poor even when the traffic load is not close to network capacity due to the following two reasons. First, each node has to maintain a separate queue for each commodity in the network, and only one queue is served at a time. Second, the back-pressure routing algorithm may route some packets along very long routes. In this paper, we present solutions to address both of the above issues, and hence, improve the delay performance of the back-pressure algorithm. One of the suggested solutions also decreases the complexity of the queueing data structures to be maintained at each node.


A Generalized Carpenter's Rule Theorem for Self-Touching Linkages

Abstract: The Carpenter's Rule Theorem states that any chain linkage in the plane can be folded continuously between any two configurations while preserving the bar lengths and without the bars crossing. However, this theorem applies only to strictly simple configurations, where bars intersect only at their common endpoints. We generalize the theorem to self-touching configurations, where bars can touch but not properly cross. At the heart of our proof is a new definition of self-touching configurations of planar linkages, based on an annotated configuration space and limits of nontouching configurations. We show that this definition is equivalent to the previously proposed definition of self-touching configurations, which is based on a combinatorial description of overlapping features. Using our new definition, we prove the generalized Carpenter's Rule Theorem using a topological argument. We believe that our topological methodology provides a powerful tool for manipulating many kinds of self-touching objects, such as 3D hinged assemblies of polygons and rigid origami. In particular, we show how to apply our methodology to extend to self-touching configurations universal reconfigurability results for open chains with slender polygonal adornments, and single-vertex rigid origami with convex cones.


Condition for Energy Efficient Watermarking with Random Vector Model without WSS Assumption

Abstract: Energy efficient watermarking preserves the watermark energy after linear attack as much as possible. We consider in this letter non-stationary signal models and derive conditions for energy efficient watermarking under random vector model without WSS assumption. We find that the covariance matrix of the energy efficient watermark should be proportional to host covariance matrix to best resist the optimal linear removal attacks. In WSS process our result reduces to the well known power spectrum condition. Intuitive geometric interpretation of the results are also discussed which in turn also provide more simpler proof of the main results.


Bitslicing and the Method of Four Russians Over Larger Finite Fields

Abstract: We present a method of computing with matrices over very small finite fields of size larger than 2. Specifically, we show how the Method of Four Russians can be efficiently adapted to these larger fields, and introduce a row-wise matrix compression scheme that both reduces memory requirements and allows one to vectorize element operations. We also present timings which confirm the efficiency of these methods and exceed the speed of the fastest implementations the authors are aware of.


An Online Multi-unit Auction with Improved Competitive Ratio

Abstract: We improve the best known competitive ratio (from 1/4 to 1/2), for the online multi-unit allocation problem, where the objective is to maximize the single-price revenue. Moreover, the competitive ratio of our algorithm tends to 1, as the bid-profile tends to ``smoothen''. This algorithm is used as a subroutine in designing truthful auctions for the same setting: the allocation has to be done online, while the payments can be decided at the end of the day. Earlier, a reduction from the auction design problem to the allocation problem was known only for the unit-demand case. We give a reduction for the general case when the bidders have decreasing marginal utilities. The problem is inspired by sponsored search auctions.


Exploiting the Path Propagation Time Differences in Multipath Transmission with FEC

Abstract: We consider a transmission of a delay-sensitive data stream from a single source to a single destination. The reliability of this transmission may suffer from bursty packet losses - the predominant type of failures in today's Internet. An effective and well studied solution to this problem is to protect the data by a Forward Error Correction (FEC) code and send the FEC packets over multiple paths. In this paper we show that the performance of such a multipath FEC scheme can often be further improved. Our key observation is that the propagation times on the available paths often significantly differ, typically by 10-100ms. We propose to exploit these differences by appropriate packet scheduling that we call `Spread'. We evaluate our solution with a precise, analytical formulation and trace-driven simulations. Our studies show that Spread substantially outperforms the state-of-the-art solutions. It typically achieves two- to five-fold improvement (reduction) in the effective loss rate. Or conversely, keeping the same level of effective loss rate, Spread significantly decreases the observed delays and helps fighting the delay jitter.


Fast Algorithms for Max Independent Set in Graphs of Small Average Degree

Abstract: Max Independent Set (MIS) is a paradigmatic problem in theoretical computer science and numerous studies tackle its resolution by exact algorithms with non-trivial worst-case complexity. The best such complexity is, to our knowledge, the $O^*(1.1889^n)$ algorithm claimed by J.M. Robson (T.R. 1251-01, LaBRI, Univ. Bordeaux I, 2001) in his unpublished technical report. We also quote the $O^*(1.2210^n)$ algorithm by Fomin and al. (in Proc. SODA'06, pages 18-25, 2006), that is the best published result about MIS. In this paper we settle MIS in (connected) graphs with "small" average degree, more precisely with average degree at most 3, 4, 5 and 6. Dealing with graphs of average degree at most 3, the best bound known is the recent $O^*(1.0977^n)$ bound by N. Bourgeois and al. in Proc. IWPEC'08, pages 55-65, 2008). Here we improve this result down to $O^*(1.0854^n)$ by proposing finer and more powerful reduction rules. We then propose a generic method showing how improvement of the worst-case complexity for MIS in graphs of average degree $d$ entails improvement of it in any graph of average degree greater than $d$ and, based upon it, we tackle MIS in graphs of average degree 4, 5 and 6. For MIS in graphs with average degree 4, we provide an upper complexity bound of $O^*(1.1571^n)$ that outperforms the best known bound of $O^*(1.1713^n)$ by R. Beigel (Proc. SODA'99, pages 856-857, 1999). For MIS in graphs of average degree at most 5 and 6, we provide bounds of $O^*(1.1969^n)$ and $O^*(1.2149^n)$, respectively, that improve upon the corresponding bounds of $O^*(1.2023^n)$ and $O^*(1.2172^n)$ in graphs of maximum degree 5 and 6 by (Fomin et al., 2006).


Towards a Framework for Observing Artificial Evolutionary Systems

Abstract: Establishing the emergence of evolutionary behavior as a defining characteristic of 'life' is a major step in the Artificial life (ALife) studies. We present here an abstract formal framework for this aim based upon the notion of high-level observations made on the ALife model at hand during its simulations. An observation process is defined as a computable transformation from the underlying dynamic structure of the model universe to a tuple consisting of abstract components needed to establish the evolutionary processes in the model. Starting with defining entities and their evolutionary relationships observed during the simulations of the model, the framework prescribes a series of definitions, followed by the axioms (conditions) that must be met in order to establish the level of evolutionary behavior in the model. The examples of Cellular Automata based Langton Loops and Lambda calculus based Algorithmic Chemistry are used to illustrate the framework. Generic design suggestions for the ALife research are also drawn based upon the framework design and case study analysis.


Adaptive threshold-based decision for efficient hybrid deflection and retransmission scheme in OBS networks

Abstract: Burst contention is a well-known challenging problem in Optical Burst Switching (OBS) networks. Deflection routing is used to resolve contention. Burst retransmission is used to reduce the Burst Loss Ratio (BLR) by retransmitting dropped bursts. Previous works show that combining deflection and retransmission outperforms both pure deflection and pure retransmission approaches. This paper proposes a new Adaptive Hybrid Deflection and Retransmission (AHDR) approach that dynamically combines deflection and retransmission approaches based on network conditions such as BLR and link utilization. Network Simulator 2 (ns-2) is used to simulate the proposed approach on different network topologies. Simulation results show that the proposed approach outperforms static approaches in terms of BLR by using an adaptive decision threshold.


Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion

Abstract: We describe a new data format for storing triangular, symmetric, and Hermitian matrices called RFPF (Rectangular Full Packed Format). The standard two dimensional arrays of Fortran and C (also known as full format) that are used to represent triangular and symmetric matrices waste nearly half of the storage space but provide high performance via the use of Level 3 BLAS. Standard packed format arrays fully utilize storage (array space) but provide low performance as there is no Level 3 packed BLAS. We combine the good features of packed and full storage using RFPF to obtain high performance via using Level 3 BLAS as RFPF is a standard full format representation. Also, RFPF requires exactly the same minimal storage as packed format. Each LAPACK full and/or packed triangular, symmetric, and Hermitian routine becomes a single new RFPF routine based on eight possible data layouts of RFPF. This new RFPF routine usually consists of two calls to the corresponding LAPACK full format routine and two calls to Level 3 BLAS routines. This means {\it no} new software is required. As examples, we present LAPACK routines for Cholesky factorization, Cholesky solution and Cholesky inverse computation in RFPF to illustrate this new work and to describe its performance on several commonly used computer platforms. Performance of LAPACK full routines using RFPF versus LAPACK full routines using standard format for both serial and SMP parallel processing is about the same while using half the storage. Performance gains are roughly one to a factor of 43 for serial and one to a factor of 97 for SMP parallel times faster using vendor LAPACK full routines with RFPF than with using vendor and/or reference packed routines.


Towards Optimal Range Medians

Abstract: We consider the following problem: given an unsorted array of $n$ elements, and a sequence of intervals in the array, compute the median in each of the subarrays defined by the intervals. We describe a simple algorithm which uses O(n) space and needs $O(n\log k + k\log n)$ time to answer the first $k$ queries. This improves previous algorithms by a logarithmic factor and matches a lower bound for $k=O(n)$. Since the algorithm decomposes the range of element values rather than the array, it has natural generalizations to higher dimensional problems -- it reduces a range median query to a logarithmic number of range counting queries.


A Holistic Approach to Information Distribution in Ad Hoc Networks

Abstract: We investigate the problem of spreading information contents in a wireless ad hoc network with mechanisms embracing the peer-to-peer paradigm. In our vision, information dissemination should satisfy the following requirements: (i) it conforms to a predefined distribution and (ii) it is evenly and fairly carried by all nodes in their turn. In this paper, we observe the dissemination effects when the information moves across nodes according to two well-known mobility models, namely random walk and random direction. Our approach is fully distributed and comes at a very low cost in terms of protocol overhead; in addition, simulation results show that the proposed solution can achieve the aforementioned goals under different network scenarios, provided that a sufficient number of information replicas are injected into the network. This observation calls for a further step: in the realistic case where the user content demand varies over time, we need a content replication/drop strategy to adapt the number of information replicas to the changes in the information query rate. We therefore devise a distributed, lightweight scheme that performs efficiently in a variety of scenarios.


Detecting lacunary perfect powers and computing their roots

Abstract: We consider solutions to the equation f = h^r for polynomials f and h and integer r > 1. Given a polynomial f in the lacunary (also called sparse or super-sparse) representation, we first show how to determine if f can be written as h^r and, if so, to find such an r. This is a Monte Carlo randomized algorithm whose cost is polynomial in the number of non-zero terms of f and in log(deg f), i.e., polynomial in the size of the lacunary representation, and it works over GF(q)[x] (for large characteristic) as well as Q[x]. We also give two deterministic algorithms to compute the perfect root h given f and r. The first is output-sensitive (based on the sparsity of h) and works only over Q[x]. A sparsity-sensitive Newton iteration forms the basis for the second approach to computing h, which is extremely efficient and works over both GF(q)[x] (for large characteristic) and Q[x], but depends on a number-theoretic conjecture. Work of Erdos, Schinzel, Zannier, and others suggests that both of these algorithms are unconditionally polynomial-time in the lacunary size of the input polynomial f. Finally, we demonstrate the efficiency of the randomized detection algorithm and the latter perfect root computation algorithm with an implementation in the C++ library NTL.


Randomized Self-Assembly for Exact Shapes

Abstract: Working in Winfree's abstract tile assembly model, we show that a constant-size tile assembly system can be programmed through relative tile concentrations to build an n x n square with high probability, for any sufficiently large n. This answers an open question of Kao and Schweller (Randomized Self-Assembly for Approximate Shapes, ICALP 2008), who showed how to build an approximately n x n square using tile concentration programming, and asked whether the approximation could be made exact with high probability. We show how this technique can be modified to answer another question of Kao and Schweller, by showing that a constant-size tile assembly system can be programmed through tile concentrations to assemble arbitrary finite *scaled shapes*, which are shapes modified by replacing each point with a c x c block of points, for some integer c. Furthermore, we exhibit a smooth tradeoff between specifying bits of n via tile concentrations versus specifying them via hard-coded tile types, which allows tile concentration programming to be employed for specifying a fraction of the bits of "input" to a tile assembly system, under the constraint that concentrations can only be specified to a limited precision. Finally, to account for some unrealistic aspects of the tile concentration programming model, we show how to modify the construction to use only concentrations that are arbitrarily close to uniform.


How to improve the accuracy of the discrete gradient method in the one-dimensional case

Abstract: We present a new numerical scheme for one dimensional dynamical systems. This is a modification of the discrete gradient method and keeps its advantages, including the stability and the conservation of the energy integral. However, its accuracy is higher by several orders of magnitude.


Entropy, Triangulation, and Point Location in Planar Subdivisions

Abstract: A data structure is presented for point location in connected planar subdivisions when the distribution of queries is known in advance. The data structure has an expected query time that is within a constant factor of optimal. More specifically, an algorithm is presented that preprocesses a connected planar subdivision G of size n and a query distribution D to produce a point location data structure for G. The expected number of point-line comparisons performed by this data structure, when the queries are distributed according to D, is H + O(H^{2/3}+1) where H=H(G,D) is a lower bound on the expected number of point-line comparisons performed by any linear decision tree for point location in G under the query distribution D. The preprocessing algorithm runs in O(n log n) time and produces a data structure of size O(n). These results are obtained by creating a Steiner triangulation of G that has near-minimum entropy.