Information Centric Networking based Handover Support for QoS Maintenance in Cooperative Heterogeneous Wireless Networks

Abstract: Network of Information (NetInf) is a term coined for networks which unlike contemporary network are not node centric. As the name indicates, information supersedes nodes in the network. In this report, we propose an architecture of mobile node for NetInf. We call it NetInf Mobile Node. It is an extension of the basic node architecture proposed for NetInf. It is compatible to NetInf and TCP/IP based networks. The Virtual Node Layer modules in the architecture provide support for managing mobility, power consumption of the node as well data relaying/storing services. In- ner/Outer Locator Construction Routers (I/O LCTR) are two functions introduced in NetInf mobile nodes to operate between NetInf and non- NetInf sites. The basic purpose of NetInf mobile node is to maintain the QoS during mobility events. The handoff/handover are critical situations during mobility where chances of QoS degradation of an ongoing session are high. This report presents one such scenario in which QoS of an appli- cation is maintained during a handoff situations in heterogeneous wireless network environment through our proposed algorithm.


The Statistical methods of Pixel-Based Image Fusion Techniques

Abstract: There are many image fusion methods that can be used to produce high-resolution mutlispectral images from a high-resolution panchromatic (PAN) image and low-resolution multispectral (MS) of remote sensed images. This paper attempts to undertake the study of image fusion techniques with different Statistical techniques for image fusion as Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Regression variable substitution (RVS), Local Correlation Modeling (LCM) and they are compared with one another so as to choose the best technique, that can be applied on multi-resolution satellite images. This paper also devotes to concentrate on the analytical techniques for evaluating the quality of image fusion (F) by using various methods including Standard Deviation (SD), Entropy(En), Correlation Coefficient (CC), Signal-to Noise Ratio (SNR), Normalization Root Mean Square Error (NRMSE) and Deviation Index (DI) to estimate the quality and degree of information improvement of a fused image quantitatively.


Advanced phase retrieval: maximum likelihood technique with sparse regularization of phase and amplitude

Abstract: Sparse modeling is one of the efficient techniques for imaging that allows recovering lost information. In this paper, we present a novel iterative phase-retrieval algorithm using a sparse representation of the object amplitude and phase. The algorithm is derived in terms of a constrained maximum likelihood, where the wave field reconstruction is performed using a number of noisy intensity-only observations with a zero-mean additive Gaussian noise. The developed algorithm enables the optimal solution for the object wave field reconstruction. Our goal is an improvement of the reconstruction quality with respect to the conventional algorithms. Sparse regularization results in advanced reconstruction accuracy, and numerical simulations demonstrate significant enhancement of imaging.


Finding Similar/Diverse Solutions in Answer Set Programming

Abstract: For some computational problems (e.g., product configuration, planning, diagnosis, query answering, phylogeny reconstruction) computing a set of similar/diverse solutions may be desirable for better decision-making. With this motivation, we studied several decision/optimization versions of this problem in the context of Answer Set Programming (ASP), analyzed their computational complexity, and introduced offline/online methods to compute similar/diverse solutions of such computational problems with respect to a given distance function. All these methods rely on the idea of computing solutions to a problem by means of finding the answer sets for an ASP program that describes the problem. The offline methods compute all solutions in advance using the ASP formulation of the problem with an ASP solver, like Clasp, and then identify similar/diverse solutions using clustering methods. The online methods compute similar/diverse solutions following one of the three approaches: by reformulating the ASP representation of the problem to compute similar/diverse solutions at once using an ASP solver; by computing similar/diverse solutions iteratively (one after other) using an ASP solver; by modifying the search algorithm of an ASP solver to compute similar/diverse solutions incrementally. We modified Clasp to implement the last online method and called it Clasp-NK. In the first two online methods, the given distance function is represented in ASP; in the last one it is implemented in C++. We showed the applicability and the effectiveness of these methods on reconstruction of similar/diverse phylogenies for Indo-European languages, and on several planning problems in Blocks World. We observed that in terms of computational efficiency the last online method outperforms the others; also it allows us to compute similar/diverse solutions when the distance function cannot be represented in ASP.


Self-Adjusting Stack Machines

Abstract: Self-adjusting computation offers a language-based approach to writing programs that automatically respond to dynamically changing data. Recent work made significant progress in developing sound semantics and associated implementations of self-adjusting computation for high-level, functional languages. These techniques, however, do not address issues that arise for low-level languages, i.e., stack-based imperative languages that lack strong type systems and automatic memory management. In this paper, we describe techniques for self-adjusting computation which are suitable for low-level languages. Necessarily, we take a different approach than previous work: instead of starting with a high-level language with additional primitives to support self-adjusting computation, we start with a low-level intermediate language, whose semantics is given by a stack-based abstract machine. We prove that this semantics is sound: it always updates computations in a way that is consistent with full reevaluation. We give a compiler and runtime system for the intermediate language used by our abstract machine. We present an empirical evaluation that shows that our approach is efficient in practice, and performs favorably compared to prior proposals.


On the Performance of MPI-OpenMP on a 12 nodes Multi-core Cluster

Abstract: With the increasing number of Quad-Core-based clusters and the introduction of compute nodes designed with large memory capacity shared by multiple cores, new problems related to scalability arise. In this paper, we analyze the overall performance of a cluster built with nodes having a dual Quad-Core Processor on each node. Some benchmark results are presented and some observations are mentioned when handling such processors on a benchmark test. A Quad-Core-based cluster's complexity arises from the fact that both local communication and network communications between the running processes need to be addressed. The potentials of an MPI-OpenMP approach are pinpointed because of its reduced communication overhead. At the end, we come to a conclusion that an MPI-OpenMP solution should be considered in such clusters since optimizing network communications between nodes is as important as optimizing local communications between processors in a multi-core cluster.


Reiter's Default Logic Is a Logic of Autoepistemic Reasoning And a Good One, Too

Abstract: A fact apparently not observed earlier in the literature of nonmonotonic reasoning is that Reiter, in his default logic paper, did not directly formalize informal defaults. Instead, he translated a default into a certain natural language proposition and provided a formalization of the latter. A few years later, Moore noted that propositions like the one used by Reiter are fundamentally different than defaults and exhibit a certain autoepistemic nature. Thus, Reiter had developed his default logic as a formalization of autoepistemic propositions rather than of defaults. The first goal of this paper is to show that some problems of Reiter's default logic as a formal way to reason about informal defaults are directly attributable to the autoepistemic nature of default logic and to the mismatch between informal defaults and the Reiter's formal defaults, the latter being a formal expression of the autoepistemic propositions Reiter used as a representation of informal defaults. The second goal of our paper is to compare the work of Reiter and Moore. While each of them attempted to formalize autoepistemic propositions, the modes of reasoning in their respective logics were different. We revisit Moore's and Reiter's intuitions and present them from the perspective of autotheoremhood, where theories can include propositions referring to the theory's own theorems. We then discuss the formalization of this perspective in the logics of Moore and Reiter, respectively, using the unifying semantic framework for default and autoepistemic logics that we developed earlier. We argue that Reiter's default logic is a better formalization of Moore's intuitions about autoepistemic propositions than Moore's own autoepistemic logic.


Revisiting Epistemic Specifications

Abstract: In 1991, Michael Gelfond introduced the language of epistemic specifications. The goal was to develop tools for modeling problems that require some form of meta-reasoning, that is, reasoning over multiple possible worlds. Despite their relevance to knowledge representation, epistemic specifications have received relatively little attention so far. In this paper, we revisit the formalism of epistemic specification. We offer a new definition of the formalism, propose several semantics (one of which, under syntactic restrictions we assume, turns out to be equivalent to the original semantics by Gelfond), derive some complexity results and, finally, show the effectiveness of the formalism for modeling problems requiring meta-reasoning considered recently by Faber and Woltran. All these results show that epistemic specifications deserve much more attention that has been afforded to them so far.


Origins of Answer-Set Programming - Some Background And Two Personal Accounts

Abstract: We discuss the evolution of aspects of nonmonotonic reasoning towards the computational paradigm of answer-set programming (ASP). We give a general overview of the roots of ASP and follow up with the personal perspective on research developments that helped verbalize the main principles of ASP and differentiated it from the classical logic programming.


Patterns for Business-to-consumer E-Commerce Applications

Abstract: E-commerce is one of the most important web applications. We present here a set of patterns that describe shopping carts, products, catalogue, customer accounts, shipping, and invoices. We combine them in the form of composite patterns, which in turn make up a domain model for business-to-consumer e-commerce. We also indicate how to add security constraints to this model. This domain model can be used as a computation-independent model from which specific applications can be produced using a model-driven architecture approach.


Gadgets and Anti-Gadgets Leading to a Complexity Dichotomy

Abstract: We introduce an idea called anti-gadgets in complexity reductions. These combinatorial gadgets have the effect of erasing the presence of some other graph fragment, as if we had managed to include a negative copy of a graph gadget. We use this idea to prove a complexity dichotomy theorem for the partition function $Z(G)$ on 3-regular directed graphs $G$, where each edge is given a complex-valued binary function $f: \{0,1\}^2 \rightarrow \mathbb{C}$. We show that \[Z(G) = \sum_{\sigma: V(G) \to \{0,1\}} \prod_{(u,v) \in E(G)} f(\sigma(u), \sigma(v)),\] is either computable in polynomial time or #P-hard, depending explicitly on $f$.


Proceedings 8th International Conference Words 2011

Abstract: WORDS is the main international event in Combinatorics on Words. It is a biannual conference devoted to research of words (i.e., finite or infinite sequences of symbols over a finite alphabet) from combinatorial, algebraic and algorithmic points of view. The emphasis of the conference is on mathematical theory of words but the conference is also open to applications, mainly in computer science, biology, linguistics and physics, gaining from the fact that words arise as a natural object in many areas. The eighth edition of the conference was organized in Prague from 12th to 16th September 2011 as a joint undertaking of the Czech Technical University and the Charles University. This volume consists of contributed papers accepted for presentation at the conference and summaries of invited lectures.


Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks

Abstract: We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the {\em count-tracking} problem, where there are $k$ players, each holding a counter $n_i$ that gets incremented over time, and the goal is to track an $\eps$-approximation of their sum $n=\sum_i n_i$ continuously at all times, using minimum communication. While the deterministic communication complexity of the problem is $\Theta(k/\eps \cdot \log N)$, where $N$ is the final value of $n$ when the tracking finishes, we show that with randomization, the communication cost can be reduced to $\Theta(\sqrt{k}/\eps \cdot \log N)$. Our algorithm is simple and uses only O(1) space at each player, while the lower bound holds even assuming each player has infinite computing power. Then, we extend our techniques to two related distributed tracking problems: {\em frequency-tracking} and {\em rank-tracking}, and obtain similar improvements over previous deterministic algorithms. Both problems are of central importance in large data monitoring and analysis, and have been extensively studied in the literature.


Biologically Inspired Process Calculi, Petri Nets and Membrane Computing

Abstract: This volume represents the proceedings of the 5th Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC 2011), held together with the 12th International Conference on Membrane Computing on 23rd August 2011 in Fontainebleau, France.


Reversibility in Massive Concurrent Systems

Abstract: Reversing a (forward) computation history means undoing the history. In concurrent systems, undoing the history is not performed in a deterministic way but in a causally consistent fashion, where states that are reached during a backward computation are states that could have been reached during the computation history by just performing independent actions in a different order.


Petri Nets and Bio-Modelling - and how to benefit from their synergy

Abstract: In this talk we are concerned with the intrinsic similarities and differences between Petri nets on the one hand, and membrane systems and reaction systems on the other hand.


A Testing Framework for P Systems

Abstract: Testing equivalence was originally defined by De Nicola and Hennessy in a process algebraic setting (CCS) with the aim of defining an equivalence relation between processes being less discriminating than bisimulation and with a natural interpretation in the practice of system development. Finite characterizations of the defined preorders and relations led to the possibility of verification by comparing an implementation with a specification in a setting where systems were seen as black boxes with input and output capabilities, thus neglecting internal undetectable behaviours. In this paper, we start defining a porting of the well-established testing theory into membrane computing, in order to investigate possible benefits in terms of inherited analysis/verification techniques and interesting biological applications. P Algebra, a process algebra for describing P Systems, is used as a natural candidate for the porting since it enjoys the desirable property of being compositional and comes with other observational equivalences already defined and studied.


Brane Calculi Systems: A Static Preview of their Possible Behaviour

Abstract: We improve the precision of a previous Control Flow Analysis for Brane Calculi, by adding information on the context and introducing causality information on the membranes. This allows us to prove some biological properties on the behaviour of systems specified in Brane Calculi.


Synchronization of P Systems with Simplex Channels

Abstract: We solve the Firing Squad Synchronization Problem (FSSP), for P systems based on digraphs with simplex channels, where communication is restricted by the direction of structural arcs. Previous work on FSSP for P systems focused exclusively on P systems with duplex channels, where communication between parents and children is bidirectional. Our P solution, the first for simplex channels, requires cell IDs, strongly connected digraphs and some awareness of the local topology (such as each cell's outdegree)---we argue that these requirements are necessary. Compared to the known solutions for cellular automata, our solution is substantially simpler and faster.


Further Results on Languages of Membrane Structures

Abstract: P systems with active membranes were used to generate languages, in the sense of languages associated with the structure of membrane systems. Here, we analyze the power of P systems with membrane creation and dissolution restricted to elementary membranes, P systems without membrane dissolution operating according to certain output modes. This leads us to characterizations of recursively enumerable languages.


Generalized Communicating P Systems Working in Fair Sequential Model

Abstract: In this article we consider a new derivation mode for generalized communicating P systems (GCPS) corresponding to the functioning of population protocols (PP) and based on the sequential derivation mode and a fairness condition. We show that PP can be seen as a particular variant of GCPS. We also consider a particular stochastic evolution satisfying the fairness condition and obtain that it corresponds to the run of a Gillespie's SSA. This permits to further describe the dynamics of GCPS by a system of ODEs when the population size goes to the infinity.


Abstracting Asynchronous Multi-Valued Networks: An Initial Investigation

Abstract: Multi-valued networks provide a simple yet expressive qualitative state based modelling approach for biological systems. In this paper we develop an abstraction theory for asynchronous multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. The abstraction theory therefore provides a mechanism for coping with the state space explosion problem and supports the analysis and comparison of multi-valued networks. We take as our starting point the abstraction theory for synchronous multi-valued networks which is based on the finite set of traces that represent the behaviour of such a model. The problem with extending this approach to the asynchronous case is that we can now have an infinite set of traces associated with a model making a simple trace inclusion test infeasible. To address this we develop a decision procedure for checking asynchronous abstractions based on using the finite state graph of an asynchronous multi-valued network to reason about its trace semantics. We illustrate the abstraction techniques developed by considering a detailed case study based on a multi-valued network model of the regulation of tryptophan biosynthesis in Escherichia coli.


Modelling of Genetic Regulatory Mechanisms with GReg

Abstract: Most available tools propose simulation frameworks to study models of biological systems, but simulation only explores a few of the most probable behaviours of the system. On the contrary, techniques such as model checking, coming from IT-systems analysis, explore all the possible behaviours of the modelled systems, thus helping to identify emergent properties. A main drawback from most model checking tools in the life sciences domain is that they take as input a language designed for computer scientists, that is not easily understood by non-expert users. We propose in this article an approach based on DSL. It provides a comprehensible language to describe the system while allowing the use of complex and powerful underlying model checking techniques.


Premise Selection for Mathematics by Corpus Analysis and Kernel Methods

Abstract: Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. A good method for premise selection in complex mathematical libraries is the application of machine learning to large corpora of proofs. This work develops learning-based premise selection in two ways. First, a newly available minimal dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a benchmark consisting of 2078 large-theory mathematical problems is constructed,extending the older MPTP Challenge benchmark. The combined effect of the techniques results in a 50% improvement on the benchmark over the Vampire/SInE state-of-the-art system for automated reasoning in large theories.


A Novel and Robust Evolution Algorithm for Optimizing Complicated Functions

Abstract: In this paper, a novel mutation operator of differential evolution algorithm is proposed. A new algorithm called divergence differential evolution algorithm (DDEA) is developed by combining the new mutation operator with divergence operator and assimilation operator (divergence operator divides population, and, assimilation operator combines population), which can detect multiple solutions and robustness in noisy environment. The new algorithm is applied to optimize Michalewicz Function and to track changing of rain-induced-attenuation process. The results based on DDEA are compared with those based on Differential Evolution Algorithm (DEA). It shows that DDEA algorithm gets better results than DEA does in the same premise. The new algorithm is significant for optimizing and tracking the characteristics of MIMO (Multiple Input Multiple Output) channel at millimeter waves.


New separation between $s(f)$ and $bs(f)$

Abstract: In this note we give a new separation between sensitivity and block sensitivity of Boolean functions: $bs(f)=(2/3)s(f)^2-(1/3)s(f)$.


Model for networks of spatial objects and simulation of geographical phenomena propagation

Abstract: The topic of this paper is the presentation of a new network model designed for networks consisting of spatial objects. This model allows the development of more advance representations of systems of networked objects and the study of geographical phenomena propagated through networks. The capabilities of the model in simulation of geographical phenomena propagation are also studied and relevant algorithms are presented. As examples of use, modeling of water supply network and the simulation of traffic flow in road networks are presented.


Applications of Zigzag Persistence to Topological Data Analysis

Abstract: The theory of zigzag persistence is a substantial extension of persistent homology, and its development has enabled the investigation of several unexplored avenues in the area of topological data analysis. In this paper, we discuss three applications of zigzag persistence: topological bootstrapping, parameter thresholding, and the comparison of witness complexes.


Proceedings of the 5th Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC 2011)


Hierarchical Object Parsing from Structured Noisy Point Clouds

Abstract: Object parsing and segmentation from point clouds are challenging tasks because the relevant data is available only as thin structures along object boundaries or other features, and is corrupted by large amounts of noise. To handle this kind of data, flexible shape models are desired that can accurately follow the object boundaries. Popular models such as Active Shape and Active Appearance models lack the necessary flexibility for this task, while recent approaches such as the Recursive Compositional Models make model simplifications in order to obtain computational guarantees. This paper investigates a hierarchical Bayesian model of shape and appearance in a generative setting. The input data is explained by an object parsing layer, which is a deformation of a hidden PCA shape model with Gaussian prior. The paper also introduces a novel efficient inference algorithm that uses informed data-driven proposals to initialize local searches for the hidden variables. Applied to the problem of object parsing from structured point clouds such as edge detection images, the proposed approach obtains state of the art parsing errors on two standard datasets without using any intensity information.


Feature Reinforcement Learning In Practice

Abstract: Following a recent surge in using history-based methods for resolving perceptual aliasing in reinforcement learning, we introduce an algorithm based on the feature reinforcement learning framework called PhiMDP. To create a practical algorithm we devise a stochastic search procedure for a class of context trees based on parallel tempering and a specialized proposal distribution. We provide the first empirical evaluation for PhiMDP. Our proposed algorithm achieves superior performance to the classical U-tree algorithm and the recent active-LZ algorithm, and is competitive with MC-AIXI-CTW that maintains a bayesian mixture over all context trees up to a chosen depth.We are encouraged by our ability to compete with this sophisticated method using an algorithm that simply picks one single model, and uses Q-learning on the corresponding MDP. Our PhiMDP algorithm is much simpler, yet consumes less time and memory. These results show promise for our future work on attacking more complex and larger problems.


Interactions between Digital Geometry and Combinatorics on Words

Abstract: We review some recent results in digital geometry obtained by using a combinatorics on words approach to discrete geometry. Motivated on the one hand by the well-known theory of Sturmian words which model conveniently discrete lines in the plane, and on the other hand by the development of digital geometry, this study reveals strong links between the two fields. Discrete figures are identified with polyominoes encoded by words. The combinatorial tools lead to elegant descriptions of geometrical features and efficient algorithms. Among these, radix-trees are useful for efficiently detecting path intersection, Lyndon and Christoffel words appear as the main tools for describing digital convexity; equations on words allow to better understand tilings by translations.


Infinite permutations vs. infinite words

Abstract: I am going to compare well-known properties of infinite words with those of infinite permutations, a new object studied since middle 2000s. Basically, it was Sergey Avgustinovich who invented this notion, although in an early study by Davis et al. permutations appear in a very similar framework as early as in 1977. I am going to tell about periodicity of permutations, their complexity according to several definitions and their automatic properties, that is, about usual parameters of words, now extended to permutations and behaving sometimes similarly to those for words, sometimes not. Another series of results concerns permutations generated by infinite words and their properties. Although this direction of research is young, many people, including two other speakers of this meeting, have participated in it, and I believe that several more topics for further study are really promising.


Combinatorics on words in information security: Unavoidable regularities in the construction of multicollision attacks on iterated hash functions

Abstract: Classically in combinatorics on words one studies unavoidable regularities that appear in sufficiently long strings of symbols over a fixed size alphabet. In this paper we take another viewpoint and focus on combinatorial properties of long words in which the number of occurrences of any symbol is restritced by a fixed constant. We then demonstrate the connection of these properties to constructing multicollision attacks on so called generalized iterated hash functions.


Finite-Repetition threshold for infinite ternary words

Abstract: The exponent of a word is the ratio of its length over its smallest period. The repetitive threshold r(a) of an a-letter alphabet is the smallest rational number for which there exists an infinite word whose finite factors have exponent at most r(a). This notion was introduced in 1972 by Dejean who gave the exact values of r(a) for every alphabet size a as it has been eventually proved in 2009. The finite-repetition threshold for an a-letter alphabet refines the above notion. It is the smallest rational number FRt(a) for which there exists an infinite word whose finite factors have exponent at most FRt(a) and that contains a finite number of factors with exponent r(a). It is known from Shallit (2008) that FRt(2)=7/3. With each finite-repetition threshold is associated the smallest number of r(a)-exponent factors that can be found in the corresponding infinite word. It has been proved by Badkobeh and Crochemore (2010) that this number is 12 for infinite binary words whose maximal exponent is 7/3. We show that FRt(3)=r(3)=7/4 and that the bound is achieved with an infinite word containing only two 7/4-exponent words, the smallest number. Based on deep experiments we conjecture that FRt(4)=r(4)=7/5. The question remains open for alphabets with more than four letters. Keywords: combinatorics on words, repetition, repeat, word powers, word exponent, repetition threshold, pattern avoidability, word morphisms.


Uniformly balanced words with linear complexity and prescribed letter frequencies

Abstract: We consider the following problem. Let us fix a finite alphabet A; for any given d-uple of letter frequencies, how to construct an infinite word u over the alphabet A satisfying the following conditions: u has linear complexity function, u is uniformly balanced, the letter frequencies in u are given by the given d-uple. This paper investigates a construction method for such words based on the use of mixed multidimensional continued fraction algorithms.


Recurrent Partial Words

Abstract: Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words). Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.


Bounded Parikh Automata

Abstract: The Parikh finite word automaton model (PA) was introduced and studied by Klaedtke and Ruess in 2003. Here, by means of related models, it is shown that the bounded languages recognized by PA are the same as those recognized by deterministic PA. Moreover, this class of languages is the class of bounded languages whose set of iterations is semilinear.


From Regular to Strictly Locally Testable Languages

Abstract: A classical result (often credited to Y. Medvedev) states that every language recognized by a finite automaton is the homomorphic image of a local language, over a much larger so-called local alphabet, namely the alphabet of the edges of the transition graph. Local languages are characterized by the value k=2 of the sliding window width in the McNaughton and Papert's infinite hierarchy of strictly locally testable languages (k-slt). We generalize Medvedev's result in a new direction, studying the relationship between the width and the alphabetic ratio telling how much larger the local alphabet is. We prove that every regular language is the image of a k-slt language on an alphabet of doubled size, where the width logarithmically depends on the automaton size, and we exhibit regular languages for which any smaller alphabetic ratio is insufficient. More generally, we express the trade-off between alphabetic ratio and width as a mathematical relation derived from a careful encoding of the states. At last we mention some directions for theoretical development and application.


Substitutions over infinite alphabet generating (-\beta)-integers

Abstract: This contribution is devoted to the study of positional numeration systems with negative base introduced by Ito and Sadahiro in 2009, called (-\beta)-expansions. We give an admissibility criterion for more general case of (-\beta)-expansions and discuss the properties of the set of (-\beta)-integers. We give a description of distances within this set and show that this set can be coded by an infinite word over an infinite alphabet, which is a fixed point of a non-erasing non-trivial morphism.


On Pansiot Words Avoiding 3-Repetitions

Abstract: The recently confirmed Dejean's conjecture about the threshold between avoidable and unavoidable powers of words gave rise to interesting and challenging problems on the structure and growth of threshold words. Over any finite alphabet with k >= 5 letters, Pansiot words avoiding 3-repetitions form a regular language, which is a rather small superset of the set of all threshold words. Using cylindric and 2-dimensional words, we prove that, as k approaches infinity, the growth rates of complexity for these regular languages tend to the growth rate of complexity of some ternary 2-dimensional language. The numerical estimate of this growth rate is about 1.2421.


A new proof for the decidability of D0L ultimate periodicity

Abstract: We give a new proof for the decidability of the D0L ultimate periodicity problem based on the decidability of p-periodicity of morphic words adapted to the approach of Harju and Linna.


The complexity of tangent words

Abstract: In a previous paper, we described the set of words that appear in the coding of smooth (resp. analytic) curves at arbitrary small scale. The aim of this paper is to compute the complexity of those languages.


Unambiguous 1-Uniform Morphisms

Abstract: A morphism h is unambiguous with respect to a word w if there is no other morphism g that maps w to the same image as h. In the present paper we study the question of whether, for any given word, there exists an unambiguous 1-uniform morphism, i.e., a morphism that maps every letter in the word to an image of length 1.


Constructing Premaximal Binary Cube-free Words of Any Level

Abstract: We study the structure of the language of binary cube-free words. Namely, we are interested in the cube-free words that cannot be infinitely extended preserving cube-freeness. We show the existence of such words with arbitrarily long finite extensions, both to one side and to both sides.


Systems of Word Equations and Polynomials: a New Approach

Abstract: We develop new polynomial methods for studying systems of word equations. We use them to improve some earlier results and to analyze how sizes of systems of word equations satisfying certain independence properties depend on the lengths of the equations. These methods give the first nontrivial upper bounds for the sizes of the systems.


Word posets, with applications to Coxeter groups

Abstract: We discuss the theory of certain partially ordered sets that capture the structure of commutation classes of words in monoids. As a first application, it follows readily that counting words in commutation classes is #P-complete. We then apply the partially ordered sets to Coxeter groups. Some results are a proof that enumerating the reduced words of elements of Coxeter groups is #P-complete, a recursive formula for computing the number of commutation classes of reduced words, as well as stronger bounds on the maximum number of commutation classes than were previously known. This also allows us to improve the known bounds on the number of primitive sorting networks.


Optimizing Properties of Balanced Words

Abstract: In the past few decades there has been a good deal of papers which are concerned with optimization problems in different areas of mathematics (along 0-1 words, finite or infinite) and which yield - sometimes quite unexpectedly - balanced words as optimal. In this note we list some key results along these lines known to date.


On the Delone property of (-\beta)-integers

Abstract: The (-\beta)-integers are natural generalisations of the \beta-integers, and thus of the integers, for negative real bases. They can be described by infinite words which are fixed points of anti-morphisms. We show that they are not necessarily uniformly discrete and relatively dense in the real numbers.


Permutation complexity of the fixed points of some uniform binary morphisms

Abstract: An infinite permutation is a linear order on the set N. We study the properties of infinite permutations generated by fixed points of some uniform binary morphisms, and find the formula for their complexity.


Permutation Complexity Related to the Letter Doubling Map

Abstract: Given a countable set X (usually taken to be the natural numbers or integers), an infinite permutation, \pi, of X is a linear ordering of X. This paper investigates the combinatorial complexity of infinite permutations on the natural numbers associated with the image of uniformly recurrent aperiodic binary words under the letter doubling map. An upper bound for the complexity is found for general words, and a formula for the complexity is established for the Sturmian words and the Thue-Morse word.


AIG Rewriting Using 5-Input Cuts

Abstract: Rewriting is a common approach to logic optimization based on local transformations. Most commercially available logic synthesis tools include a rewriting engine that may be used multiple times on the same netlist during optimization. This paper presents an And-Inverter graph based rewriting algorithm using 5-input cuts. The best circuits are pre-computed for a subset of NPN classes of 5-variable functions. Cut enumeration and Boolean matching are used to identify replacement candidates. The presented approach is expected to complement existing rewriting approaches which are usually based on 4-input cuts. The experimental results show that, by adding the new rewriting algorithm to ABC synthesis tool, we can further reduce the area of heavily optimized large circuits by 5.57% on average.


Substring Range Reporting

Abstract: We revisit various string indexing problems with range reporting features, namely, position-restricted substring searching, indexing substrings with gaps, and indexing substrings with intervals. We obtain the following main results. {itemize} We give efficient reductions for each of the above problems to a new problem, which we call \emph{substring range reporting}. Hence, we unify the previous work by showing that we may restrict our attention to a single problem rather than studying each of the above problems individually. We show how to solve substring range reporting with optimal query time and little space. Combined with our reductions this leads to significantly improved time-space trade-offs for the above problems. In particular, for each problem we obtain the first solutions with optimal time query and $O(n\log^{O(1)} n)$ space, where $n$ is the length of the indexed string. We show that our techniques for substring range reporting generalize to \emph{substring range counting} and \emph{substring range emptiness} variants. We also obtain non-trivial time-space trade-offs for these problems. {itemize} Our bounds for substring range reporting are based on a novel combination of suffix trees and range reporting data structures. The reductions are simple and general and may apply to other combinations of string indexing with range reporting.


Model of skyscraper evacuation with the use of space symmetry and fluid dynamic approximation

Abstract: The simulation of evacuation of pedestrians from skyscraper is a situation where the symmetry analysis method and equations of fluid dynamics finds to be very useful. When applied, they strongly reduce the number of free parameters used in simulations and in such a way speed up the calculations and make them easier to manage by the programmer and what is even more important, they can give a fresh insight into a problem of evacuation and help with incorporation of "Ambient Intelligent Devices" into future real buildings. We have analyzed various, simplified, cases of evacuation from skyscraper by employing improved "Social Force Model". For each of them we obtained the average force acting on the pedestrian as a function of the evacuation time. The results clearly show that both methods mentioned above, can be successfully implemented in the simulation process and return with satisfactory conclusions.


Modeling Routing Overhead Generated by Wireless Reactive Routing Protocols

Abstract: In this paper, we have modeled the routing over- head generated by three reactive routing protocols; Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and DYnamic MANET On-deman (DYMO). Routing performed by reactive protocols consists of two phases; route discovery and route maintenance. Total cost paid by a protocol for efficient routing is sum of the cost paid in the form of energy consumed and time spent. These protocols majorly focus on the optimization performed by expanding ring search algorithm to control the flooding generated by the mechanism of blind flooding. So, we have modeled the energy consumed and time spent per packet both for route discovery and route maintenance. The proposed framework is evaluated in NS-2 to compare performance of the chosen routing protocols.


Identifying Design Requirements for Wireless Routing Link Metrics

Abstract: In this paper, we identify and analyze the requirements to design a new routing link metric for wireless multihop networks. Considering these requirements, when a link metric is proposed, then both the design and implementation of the link metric with a routing protocol become easy. Secondly, the underlying network issues can easily be tackled. Thirdly, an appreciable performance of the network is guaranteed. Along with the existing implementation of three link metrics Expected Transmission Count (ETX), Minimum Delay (MD), and Minimum Loss (ML), we implement inverse ETX; invETX with Optimized Link State Routing (OLSR) using NS-2.34. The simulation results show that how the computational burden of a metric degrades the performance of the respective protocol and how a metric has to trade-off between different performance parameters.


Evaluating Impact of Mobility on Wireless Routing Protocols

Abstract: In this paper, we evaluate, analyze, and compare the impact of mobility on the behavior of three reactive protocols (AODV, DSR, DYMO) and three proactive protocols (DSDV, FSR, OLSR) in multi-hop wireless networks. We take into account throughput, end-to-end delay, and normalized routing load as performance parameters. Based upon the extensive simulation results in NS-2, we rank all of six protocols according to the performance parameters. Besides providing the interesting facts regarding the response of each protocol on varying mobilities and speeds, we also study the trade-offs, the routing protocols have to make. Such as, to achieve throughput, a protocol has to pay some cost in the form of increased end-to-end delay or routing overhead.


Doing Better Than UCT: Rational Monte Carlo Sampling in Trees

Abstract: UCT, a state-of-the art algorithm for Monte Carlo tree sampling (MCTS), is based on UCB, a sampling policy for the Multi-armed Bandit Problem (MAB) that minimizes the accumulated regret. However, MCTS differs from MAB in that only the final choice, rather than all arm pulls, brings a reward, that is, the simple regret, as opposite to the cumulative regret, must be minimized. This ongoing work aims at applying meta-reasoning techniques to MCTS, which is non-trivial. We begin by introducing policies for multi-armed bandits with lower simple regret than UCB, and an algorithm for MCTS which combines cumulative and simple regret minimization and outperforms UCT. We also develop a sampling scheme loosely based on a myopic version of perfect value of information. Finite-time and asymptotic analysis of the policies is provided, and the algorithms are compared empirically.


The Successive Approximation Approach for NUM Frameworks with Elastic and Inelastic Traffic

Abstract: The concave utility in the Network Utility Maximization (NUM) problem is only suitable for elastic flows. However, the networks with the multiclass traffic, the utility of inelastic traffic is usually represented by the sigmoidal function which is a nonconcave function. Hence, the basic NUM problem becomes a nonconvex optimization problem. Solving the nonconvex NUM distributively is a difficult problem. The current works utilize the standard dual-based algorithm for the convex NUM and find the criteria for the global optimal convergence of the algorithm. It turns out that the link capacity must higher than a certain value to achieve the global optimum. We propose a new distributed algorithm that converges to the suboptimal solution of the nonconvex NUM for all of link capacity. We approximate the logarithm of the original problem to the convex problem which is solved efficiently by the standard dual-base distributed algorithm. After a sequence of approximations, the solutions converge to the KKT solution of the original problem. In many of our experiments, it also converges to the global optimal solution of the NUM. Moreover, we extend our work to solve the joint rate and power NUM problem with elastic and inelastic traffic in a wireless network. Our techniques can be applied to any log-concave utilities.


Computational Models of Certain Hyperspaces of Quasi-metric Spaces

Abstract: In this paper, for a given sequentially Yoneda-complete T_1 quasi-metric space (X,d), the domain theoretic models of the hyperspace K_0(X) of nonempty compact subsets of (X,d) are studied. To this end, the $\omega$-Plotkin domain of the space of formal balls BX, denoted by CBX is considered. This domain is given as the chain completion of the set of all finite subsets of BX with respect to the Egli-Milner relation. Further, a map $\phi:K_0(X)\rightarrow CBX$ is established and proved that it is an embedding whenever K_0(X) is equipped with the Vietoris topology and respectively CBX with the Scott topology. Moreover, if any compact subset of (X,d) is d^{-1}-precompact, \phi is an embedding with respect to the topology of Hausdorff quasi-metric H_d on K_0(X). Therefore, it is concluded that (CBX,\sqsubseteq,\phi) is an $\omega$-computational model for the hyperspace K_0(X) endowed with the Vietoris and respectively the Hausdorff topology. Next, an algebraic sequentially Yoneda-complete quasi-metric D on CBX$ is introduced in such a way that the specialization order $\sqsubseteq_D$ is equivalent to the usual partial order of CBX and, furthermore, $\phi:({\cal K}_0(X),H_d)\rightarrow({\bf C}{\bf B}X,D)$ is an isometry. This shows that (CBX,\sqsubseteq,\phi,D) is a quantitative $\omega$-computational model for (K_(X),H_d).


Self-Organizing Mixture Networks for Representation of Grayscale Digital Images

Abstract: Self-Organizing Maps are commonly used for unsupervised learning purposes. This paper is dedicated to the certain modification of SOM called SOMN (Self-Organizing Mixture Networks) used as a mechanism for representing grayscale digital images. Any grayscale digital image regarded as a distribution function can be approximated by the corresponding Gaussian mixture. In this paper, the use of SOMN is proposed in order to obtain such approximations for input grayscale images in unsupervised manner.


Downlink Scheduling over Markovian Fading Channels

Abstract: We consider the scheduling problem in downlink wireless networks with heterogeneous, Markov-modulated, ON/OFF channels. It is well-known that the performance of scheduling over fading channels relies heavily on the accuracy of the available Channel State Information (CSI), which is costly to acquire. Thus, we consider the CSI acquisition via a practical ARQ-based feedback mechanism whereby channel states are revealed at the end of only scheduled users' transmissions. In the assumed presence of temporally-correlated channel evolutions, the desired scheduler must optimally balance the exploitation-exploration trade-off, whereby it schedules transmissions both to exploit those channels with up-to-date CSI and to explore the current state of those with outdated CSI. In earlier works, Whittle's Index Policy had been suggested as a low-complexity and high-performance solution to this problem. However, analyzing its performance in the typical scenario of statistically heterogeneous channel state processes has remained elusive and challenging, mainly because of the highly-coupled and complex dynamics it possesses. In this work, we overcome these difficulties to rigorously establish the asymptotic optimality properties of Whittle's Index Policy in the limiting regime of many users. More specifically: (1) we prove the local optimality of Whittle's Index Policy, provided that the initial state of the system is within a certain neighborhood of a carefully selected state; (2) we then establish the global optimality of Whittle's Index Policy under a recurrence assumption that is verified numerically for our problem. These results establish that Whittle's Index Policy possesses analytically provable optimality characteristics for scheduling over heterogeneous and temporally-correlated channels.


Policy Iteration is well suited to optimize PageRank

Abstract: The question of knowing whether the policy Iteration algorithm (PI) for solving Markov Decision Processes (MDPs) has exponential or (strongly) polynomial complexity has attracted much attention in the last 50 years. Recently, Fearnley proposed an example on which PI needs an exponential number of iterations to converge. Though, it has been observed that Fearnley's example leaves open the possibility that PI behaves well in many particular cases, such as in problems that involve a fixed discount factor, or that are restricted to deterministic actions. In this paper, we analyze a large class of MDPs and we argue that PI is efficient in that case. The problems in this class are obtained when optimizing the PageRank of a particular node in the Markov chain. They are motivated by several practical applications. We show that adding natural constraints to this PageRank Optimization problem (PRO) makes it equivalent to the problem of optimizing the length of a stochastic path, which is a widely studied family of MDPs. Finally, we conjecture that PI runs in a polynomial number of iterations when applied to PRO. We give numerical arguments as well as the proof of our conjecture in a number of particular cases of practical importance.


Using Inverse lambda and Generalization to Translate English to Formal Languages

Abstract: We present a system to translate natural language sentences to formulas in a formal or a knowledge representation language. Our system uses two inverse lambda-calculus operators and using them can take as input the semantic representation of some words, phrases and sentences and from that derive the semantic representation of other words and phrases. Our inverse lambda operator works on many formal languages including first order logic, database query languages and answer set programming. Our system uses a syntactic combinatorial categorial parser to parse natural language sentences and also to construct the semantic meaning of the sentences as directed by their parsing. The same parser is used for both. In addition to the inverse lambda-calculus operators, our system uses a notion of generalization to learn semantic representation of words from the semantic representation of other words that are of the same category. Together with this, we use an existing statistical learning approach to assign weights to deal with multiple meanings of words. Our system produces improved results on standard corpora on natural language interfaces for robot command and control and database queries.


Language understanding as a step towards human level intelligence - automatizing the construction of the initial dictionary from example sentences

Abstract: For a system to understand natural language, it needs to be able to take natural language text and answer questions given in natural language with respect to that text; it also needs to be able to follow instructions given in natural language. To achieve this, a system must be able to process natural language and be able to capture the knowledge within that text. Thus it needs to be able to translate natural language text into a formal language. We discuss our approach to do this, where the translation is achieved by composing the meaning of words in a sentence. Our initial approach uses an inverse lambda method that we developed (and other methods) to learn meaning of words from meaning of sentences and an initial lexicon. We then present an improved method where the initial lexicon is also learned by analyzing the training sentence and meaning pairs. We evaluate our methods and compare them with other existing methods on a corpora of database querying and robot command and control.


Solving puzzles described in English by automated translation to answer set programming and learning how to do that translation

Abstract: We present a system capable of automatically solving combinatorial logic puzzles given in (simplified) English. It involves translating the English descriptions of the puzzles into answer set programming(ASP) and using ASP solvers to provide solutions of the puzzles. To translate the descriptions, we use a lambda-calculus based approach using Probabilistic Combinatorial Categorial Grammars (PCCG) where the meanings of words are associated with parameters to be able to distinguish between multiple meanings of the same word. Meaning of many words and the parameters are learned. The puzzles are represented in ASP using an ontology which is applicable to a large set of logic puzzles.


A SWAR Approach to Counting Ones

Abstract: We investigate the complexity of algorithms counting ones in different sets of operations. With addition and logical operations (but no shift) $O(\log^2(n))$ steps suffice to count ones. Parity can be computed with complexity $O(\log(n))$, which is the same bound as for methods using shift-operations. If multiplication is available, a solution of time complexity $O(\log^*(n))$ is possible improving the known bound $O(\log\log(n))$.


City on the Sky: Flexible, Secure Data Sharing on the Cloud

Abstract: Sharing data from various sources and of diverse kinds, and fusing them together for sophisticated analytics and mash-up applications are emerging trends, and are prerequisites for grand visions such as that of cyber-physical systems enabled smart cities. Cloud infrastructure can enable such data sharing both because it can scale easily to an arbitrary volume of data and computation needs on demand, as well as because of natural collocation of diverse such data sets within the infrastructure. However, in order to convince data owners that their data are well protected while being shared among cloud users, the cloud platform needs to provide flexible mechanisms for the users to express the constraints (access rules) subject to which the data should be shared, and likewise, enforce them effectively. We study a comprehensive set of practical scenarios where data sharing needs to be enforced by methods such as aggregation, windowed frame, value constrains, etc., and observe that existing basic access control mechanisms do not provide adequate flexibility to enable effective data sharing in a secure and controlled manner. In this paper, we thus propose a framework for cloud that extends popular XACML model significantly by integrating flexible access control decisions and data access in a seamless fashion. We have prototyped the framework and deployed it on commercial cloud environment for experimental runs to test the efficacy of our approach and evaluate the performance of the implemented prototype.


A Design Methodology for Folded, Pipelined Architectures in VLSI Applications using Projective Space Lattices

Abstract: Semi-parallel, or folded, VLSI architectures are used whenever hardware resources need to be saved at design time. Most recent applications that are based on Projective Geometry (PG) based balanced bipartite graph also fall in this category. In this paper, we provide a high-level, top-down design methodology to design optimal semi-parallel architectures for applications, whose Data Flow Graph (DFG) is based on PG bipartite graph. Such applications have been found e.g. in error-control coding and matrix computations. Unlike many other folding schemes, the topology of connections between physical elements does not change in this methodology. Another advantage is the ease of implementation. To lessen the throughput loss due to folding, we also incorporate a multi-tier pipelining strategy in the design methodology. The design methodology has been verified by implementing a synthesis tool in C++, which has been verified as well. The tool is publicly available. Further, a complete decoder was manually protototyped before the synthesis tool design, to verify all the algorithms evolved in this paper, towards various steps of refinement. Another specific high-performance design of an LDPC decoder based on this methodology was worked out in past, and has been patented as well.


Three-dimensional Torques and Power of Horse Forelimb Joints at Trot

Abstract: Reasons for Performing Study: Equine gait analysis has focused on 2D analysis in the sagittal plane, while descriptions of 3D kinetics and ground reaction force could provide more information on the Equine gait analysis. Hypothesis or Objectives: The aim of this study was to characterize the 3D torques and powers of the forelimb joints at trotting. Methods: Eight sound horses were used in the study. A full 3D torque and power for elbow, carpus, fetlock, pastern and coffin joints of right forelimb in horses at trot were obtained by calculating the inverse kinetics of simplified link segmental model. Results: Over two third of energy (70%) generated by all joints come from stance phase, and most of energy generated was by elbow joint both in stance (77%) and sway (88%) phases. Energy absorbed by all joints during stance (40%) and sway (60%) phases respectively is not a big difference. During stance phase, all most two third of energy (65%) absorbed was by fetlock joint, while over two third of energy (74%) absorbed was by carpus joint during sway phase. Conclusions & Clinical Relevance: This study presents a full 3D kinetic analysis of the relative motion of the humerus, radius, cannon, pastern and coffin segments of the forelimb at the trot. The results could provide for a more sensitive measure for kinetic analysis.


Multihop Adjustment for the Number of Nodes in Contention-Based MAC Protocols for Wireless Ad hoc Networks

Abstract: The number of contending neighbors of a node in a multihop ad hoc network has to be adjusted while analyzing the performance of the network such as computing the end-to-end delays along a path from a given source to a destination. In this paper, we describe a method to adjust the number of contending neighbors of a node in a multihop wireless ad hoc network. Our method is based on the minimum number of neighbors that has to be common between two consecutive nodes along a path. We derive an analytical expression for the adjustment factor.


Extracting, Transforming and Archiving Scientific Data

Abstract: It is becoming common to archive research datasets that are not only large but also numerous. In addition, their corresponding metadata and the software required to analyse or display them need to be archived. Yet the manual curation of research data can be difficult and expensive, particularly in very large digital repositories, hence the importance of models and tools for automating digital curation tasks. The automation of these tasks faces three major challenges: (1) research data and data sources are highly heterogeneous, (2) future research needs are difficult to anticipate, (3) data is hard to index. To address these problems, we propose the Extract, Transform and Archive (ETA) model for managing and mechanizing the curation of research data. Specifically, we propose a scalable strategy for addressing the research-data problem, ranging from the extraction of legacy data to its long-term storage. We review some existing solutions and propose novel avenues of research.


Query Expansion: Term Selection using the EWC Semantic Relatedness Measure

Abstract: This paper investigates the efficiency of the EWC semantic relatedness measure in an ad-hoc retrieval task. This measure combines the Wikipedia-based Explicit Semantic Analysis measure, the WordNet path measure and the mixed collocation index. In the experiments, the open source search engine Terrier was utilised as a tool to index and retrieve data. The proposed technique was tested on the NTCIR data collection. The experiments demonstrated promising results.


More Jabber about the Collatz Conjecture and a Closed Form for Detecting Cycles on Special Subsequences [Assertion: Collatz cycles]

Abstract: Professor Cadogan at the University of the West Indies identified special starting points that yield long subsequences where the normalization constant, k, is always one. I studied these special sequences and found an implicit mixed integer equation in closed form which if solved would produce seed values in cycling subsequences. Such cycles only occur among extremely large numbers, causing the equation to be difficult to solve numerically.


Weakness in a Mutual Authentication Scheme for Session Initiation Protocol using Elliptic Curve Cryptography

Abstract: The session initiation protocol (SIP) is a powerful signaling protocol that controls communication on the Internet, establishing, maintaining, and terminating the sessions. The services that are enabled by SIP are equally applicable in the world of mobile and ubiquitous computing. In 2009, Tsai proposed an authenticated key agreement scheme as an enhancement to SIP. Very recently, Arshad et al. demonstrated that Tsai's scheme was vulnerable to offline password guessing attack and stolen-verifier attack. They also pointed that Tsai's scheme did not provide known-key secrecy and perfect forward secrecy. In order to overcome the weaknesses, Arshad et al. also proposed an improved mutual authentication scheme based on elliptic curve discrete logarithm problem for SIP and claimed that their scheme can withstand various attacks. In this paper, we do a cryptanalysis of Arshad et al.'s scheme and show that Arshad et al.'s scheme is vulnerable to the password guessing attack.


Proceedings 18th International Workshop on Expressiveness in Concurrency

Abstract: This volume contains the proceedings of the 18th International Workshop on Expressiveness in Concurrency (EXPRESS 2011), which took place on 5th September 2011 in Aachen, as a satellite workshop of CONCUR 2011. The EXPRESS workshop series aim at bringing together researchers who are interested in the expressiveness and comparison of formal models that broadly relate to concurrency. In particular, this also includes emergent fields such as logic and interaction, game-theoretic models, and service-oriented computing.


Convergence Properties of Two ({\mu} + {\lambda}) Evolutionary Algorithms On OneMax and Royal Roads Test Functions

Abstract: We present a number of bounds on convergence time for two elitist population-based Evolutionary Algorithms using a recombination operator k-Bit-Swap and a mainstream Randomized Local Search algorithm. We study the effect of distribution of elite species and population size.


Convergence of a Recombination-Based Elitist Evolutionary Algorithm on the Royal Roads Test Function

Abstract: We present an analysis of the performance of an elitist Evolutionary algorithm using a recombination operator known as 1-Bit-Swap on the Royal Roads test function based on a population. We derive complete, approximate and asymptotic convergence rates for the algorithm. The complete model shows the benefit of the size of the population and re- combination pool.


OSD: A Source Level Bug Localization Technique Incorporating Control Flow and State Information in Object Oriented Program

Abstract: Bug localization in object oriented program ha s always been an important issue in softeware engineering. In this paper, I propose a source level bug localization technique for object oriented embedded programs. My proposed technique, presents the idea of debugging an object oriented program in class level, incorporating the object state information into the Class Dependence Graph (ClDG). Given a program (having buggy statement) and an input that fails and others pass, my approach uses concrete as well as symbolic execution to synthesize the passing inputs that marginally from the failing input in their control flow behavior. A comparison of the execution traces of the failing input and the passing input provides necessary clues to the root-cause of the failure. A state trace difference, regarding the respective nodes of the ClDG is obtained, which leads to detect the bug in the program.


Multisensor Images Fusion Based on Feature-Level

Abstract: Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for fusion. It aims at finding a transformation of the original space that would produce such new features, which preserve or improve as much as possible. This study introduces three different types of Image fusion techniques including Principal Component Analysis based Feature Fusion (PCA), Segment Fusion (SF) and Edge fusion (EF). This paper also devotes to concentrate on the analytical techniques for evaluating the quality of image fusion (F) by using various methods including (SD), (En), (CC), (SNR), (NRMSE) and (DI) to estimate the quality and degree of information improvement of a fused image quantitatively.


A New Trusted and Collaborative Agent Based Approach for Ensuring Cloud Security

Abstract: In order to determine the user's trust is a growing concern for ensuring privacy and security in a cloud computing environment. In cloud, user's data is stored in one or more remote server(s) which poses more security challenges for the system. One of the most important concerns is to protect user's sensitive information from other users and hackers that may cause data leakage in cloud storage. Having this security challenge in mind, this paper focuses on the development of a more secure cloud environment, to determine the trust of the service requesting authorities by using a novel VM (Virtual Machine) monitoring system. Moreover, this research aims towards proposing a new trusted and collaborative agent-based two-tier framework, titled WAY (Who Are You?), to protect cloud resources. The framework can be used to provide security in network, infrastructure, as well as data storage in a heterogeneous cloud platform. If the trust updating policy is based on network activities, then the framework can provide network security. Similarly, it provides storage security by monitoring unauthorized access activities by the Cloud Service Users (CSU). Infrastructure security can be provided by monitoring the use of privileged instructions within the isolated VMs. The uniqueness of the proposed security solution lies in the fact that it ensures security and privacy both at the service provider level as well as at the user level in a cloud environment.


Spatial Interactions of Peers and Performance of File Sharing Systems

Abstract: We propose a new model for peer-to-peer networking which takes the network bottlenecks into account beyond the access. This model allows one to cope with key features of P2P networking like degree or locality constraints or the fact that distant peers often have a smaller rate than nearby peers. We show that the spatial point process describing peers in their steady state then exhibits an interesting repulsion phenomenon. We analyze two asymptotic regimes of the peer-to-peer network: the fluid regime and the hard--core regime. We get closed form expressions for the mean (and in some cases the law) of the peer latency and the download rate obtained by a peer as well as for the spatial density of peers in the steady state of each regime, as well as an accurate approximation that holds for all regimes. The analytical results are based on a mix of mathematical analysis and dimensional analysis and have important design implications. The first of them is the existence of a setting where the equilibrium mean latency is a decreasing function of the load, a phenomenon that we call super-scalability.


QoS Routing using OLSR with Optimization for Flooding

Abstract: Mobile Ad-hoc Network (MANET) is the self organizing collection of mobile nodes. The communication in MANET is done via a wireless media. Ad hoc wireless networks have massive commercial and military potential because of their mobility support. Due to demanding real time multimedia applications, Quality of Services (QoS) support in such infrastructure less networks have become essential. QoS routing in mobile Ad-Hoc networks is challenging due to rapid change in network topology. Consequently, the available state information for routing is inherently imprecise. QoS routing may suffer badly due to several factors including radio interference on available bandwidth, and inefficient flooding of information to the adjacent nodes. As a result the performance of the network degrades substantially. This paper aims at the solution for energy efficient QoS routing by best utilization of network resources such as energy and bandwidth. A comparative study shows that despite the overhead due to QoS management, this solution performs better than classical OLSR protocol in terms of QoS and efficient utilization of energy.


Modeling Smart Grid using Generalized Stochastic Petri Net

Abstract: Building smart grid for power system is a major challenge for safe, automated and energy efficient usage of electricity. The full implementation of the smart grid will evolve over time. However, before a new set of infrastructures are invested to build the smart grid, proper modeling and analysis is needed to avoid wastage of resources. Modeling also helps to identify and prioritize appropriate systems parameters. In this paper, an all comprehensive model of smart grid have been proposed using Generalized Stochastic Petri Nets (GSPN). The model is used to analyze the constraints and deliverables of the smart power grid of future.


Dynamic Pricing with Limited Supply

Abstract: We consider the problem of dynamic pricing with limited supply. A seller has $k$ identical items for sale and is facing $n$ potential buyers ("agents") that are arriving sequentially. Each agent is interested in buying one item. Each agent's value for an item is an IID sample from some fixed distribution with support $[0,1]$. The seller offers a take-it-or-leave-it price to each arriving agent (possibly different for different agents), and aims to maximize his expected revenue. We focus on "prior-independent" mechanisms -- ones that do not use any information about the distribution. They are desirable because knowing the distribution is unrealistic in many practical scenarios. We study how the revenue of such mechanisms compares to the revenue of the optimal offline mechanism that knows the distribution ("offline benchmark"). We present a prior-independent dynamic pricing mechanism whose revenue is at most $O((k \log n)^{2/3})$ less than the offline benchmark, for every distribution that is regular. In fact, this guarantee holds without *any* assumptions if the benchmark is relaxed to fixed-price mechanisms. Further, we prove a matching lower bound. The performance guarantee for the same mechanism can be improved to $O(\sqrt{k} \log n)$, with a distribution-dependent constant, if $k/n$ is sufficiently small. We show that, in the worst case over all demand distributions, this is essentially the best rate that can be obtained with a distribution-specific constant. On a technical level, we exploit the connection to multi-armed bandits (MAB). While dynamic pricing with unlimited supply can easily be seen as an MAB problem, the intuition behind MAB approaches breaks when applied to the setting with limited supply. Our high-level conceptual contribution is that even the limited supply setting can be fruitfully treated as a bandit problem.


A New Enforcement on Declassification with Reachability Analysis

Abstract: Language-based information flow security aims to decide whether an action-observable program can unintentionally leak confidential information if it has the authority to access confidential data. Recent concerns about declassification polices have provided many choices for practical intended information release, but more precise enforcement mechanism for these policies is insufficiently studied. In this paper, we propose a security property on the where-dimension of declassification and present an enforcement based on automated verification. The approach automatically transforms the abstract model with a variant of self-composition, and checks the reachability of illegal-flow state of the model after transformation. The self-composition is equipped with a store-match pattern to reduce the state space and to model the equivalence of declassified expressions in the premise of property. The evaluation shows that our approach is more precise than type-based enforcement.


Prismatic Algorithm for Discrete D.C. Programming Problems

Abstract: In this paper, we propose the first exact algorithm for minimizing the difference of two submodular functions (D.S.), i.e., the discrete version of the D.C. programming problem. The developed algorithm is a branch-and-bound-based algorithm which responds to the structure of this problem through the relationship between submodularity and convexity. The D.S. programming problem covers a broad range of applications in machine learning because this generalizes the optimization of a wide class of set functions. We empirically investigate the performance of our algorithm, and illustrate the difference between exact and approximate solutions respectively obtained by the proposed and existing algorithms in feature selection and discriminative structure learning.


Comparison Of The Consumption Of Resources Between HTTP And SIP

Abstract: Currently, the development of research around VoIP experience a tremendous growth. In the community of open source Asterisk represents a reliable alternative for a lower cost solution. In this same community as the SIP protocol is a supplement to the more asterisk PBX. to share the benefits claimed by proponents of free software co-existence with other Asterisk server is not yet proven. In this context this paper we show a comparison of the use of simplified resource material for the apache server using the HTTP protocol and server that uses the asterisk SIP.


Coquet: a Coq library for verifying hardware

Abstract: We propose a new library to model and verify hardware circuits in the Coq proof assistant. This library allows one to easily build circuits by following the usual pen-and-paper diagrams. We define a deep-embedding: we use a (dependently typed) data-type that models the architecture of circuits, and a meaning function. We propose tactics that ease the reasoning about the behavior of the circuits, and we demonstrate that our approach is practicable by proving the correctness of various circuits: a text-book divide and conquer adder of parametric size, some higher-order combinators of circuits, and some sequential circuits: a buffer, and a register.


Detection and emergence

Abstract: Two different conceptions of emergence are reconciled as two instances of the phenomenon of detection. In the process of comparing these two conceptions, we find that the notions of complexity and detection allow us to form a unified definition of emergence that clearly delineates the role of the observer.


Edge detection based on morphological amoebas

Abstract: Detecting the edges of objects within images is critical for quality image processing. We present an edge-detecting technique that uses morphological amoebas that adjust their shape based on variation in image contours. We evaluate the method both quantitatively and qualitatively for edge detection of images, and compare it to classic morphological methods. Our amoeba-based edge-detection system performed better than the classic edge detectors.


Formalization of Abstract State Transition Systems for SAT

Abstract: We present a formalization of modern SAT solvers and their properties in a form of abstract state transition systems. SAT solving procedures are described as transition relations over states that represent the values of the solver's global variables. Several different SAT solvers are formalized, including both the classical DPLL procedure and its state-of-the-art successors. The formalization is made within the Isabelle/HOL system and the total correctness (soundness, termination, completeness) is shown for each presented system (with respect to a simple notion of satisfiability that can be manually checked). The systems are defined in a general way and cover procedures used in a wide range of modern SAT solvers. Our formalization builds up on the previous work on state transition systems for SAT, but it gives machine-verifiable proofs, somewhat more general specifications, and weaker assumptions that ensure the key correctness properties. The presented proofs of formal correctness of the transition systems can be used as a key building block in proving correctness of SAT solvers by using other verification approaches.


Tight Bounds on the Optimization Time of the (1+1) EA on Linear Functions

Abstract: The analysis of randomized search heuristics on classes of functions is fundamental for the understanding of the underlying stochastic process and the development of suitable proof techniques. Recently, remarkable progress has been made in bounding the expected optimization time of the simple (1+1) EA on the class of linear functions. We improve the best known bound in this setting from $(1.39+o(1))en\ln n$ to $en\ln n+O(n)$ in expectation and with high probability, which is tight up to lower-order terms. Moreover, upper and lower bounds for arbitrary mutations probabilities $p$ are derived, which imply expected polynomial optimization time as long as $p=O((\ln n)/n)$ and which are tight if $p=c/n$ for a constant $c$. As a consequence, the standard mutation probability $p=1/n$ is optimal for all linear functions, and the (1+1) EA is found to be an optimal mutation-based algorithm. The proofs are based on adaptive drift functions and the recent multiplicative drift theorem.


On Compressing Permutations and Adaptive Sorting

Abstract: Previous compact representations of permutations have focused on adding a small index on top of the plain data $<\pi(1), \pi(2),...\pi(n)>$, in order to efficiently support the application of the inverse or the iterated permutation. In this paper we initiate the study of techniques that exploit the compressibility of the data itself, while retaining efficient computation of $\pi(i)$ and its inverse. In particular, we focus on exploiting {\em runs}, which are subsets (contiguous or not) of the domain where the permutation is monotonic. Several variants of those types of runs arise in real applications such as inverted indexes and suffix arrays. Furthermore, our improved results on compressed data structures for permutations also yield better adaptive sorting algorithms.


Taking the Final Step to a Full Dichotomy of the Possible Winner Problem in Pure Scoring Rules

Abstract: The Possible Winner problem asks, given an election where the voters' preferences over the candidates are specified only partially, whether a designated candidate can become a winner by suitably extending all the votes. Betzler and Dorn [1] proved a result that is only one step away from a full dichotomy of this problem for the important class of pure scoring rules in the case of unweighted voters and an unbounded number of candidates: Possible Winner is NP-complete for all pure scoring rules except plurality, veto, and the scoring rule with vector (2,1,...,1,0), but is solvable in polynomial time for plurality and veto. We take the final step to a full dichotomy by showing that Possible Winner is NP-complete also for the scoring rule with vector (2,1,...,1,0).


Manipulation Can Be Hard in Tractable Voting Systems Even for Constant-Sized Coalitions

Abstract: Voting theory has become increasingly integrated with computational social choice and multiagent systems. Computational complexity has been extensively used as a shield against manipulation of voting systems, however for several voting schemes this complexity may cause calculating the winner to be computationally difficult. Of the many voting systems that have been studied with regard to election manipulation, a few have been found to have an unweighted coalitional manipulation problem that is NP-hard for a constant number of manipulators despite having a winner problem that is in P. We survey this interesting class of voting systems and the work that has analyzed their complexity.


SNF Project Locomotion: Final report 2009-2010

Abstract: Summary of results in last project period (1. 10. 2009 - 30. 9. 2010) of SNFS Project "From locomotion to cognition" The research that we have been involved in, and will continue to do, starts from the insight that in order to understand and design intelligent behavior, we must adopt an embodied perspective, i.e. we must take the entire agent, including its shape or morphology, the materials out of which it is built, and its interaction with the environment into account, in addition to the neural control. A lot of our research in the past has been on relatively low-level sensory-motor tasks such as locomotion (e.g. walking, running, jumping), navigation, and grasping. While this research is of interest in itself, in the context of artificial intelligence and cognitive science, this leads to the question of what these kinds of tasks have to do with higher levels of cognition, or to put it more provocatively, "What does walking have to do with thinking?" This question is of course reminiscent of the notorious "symbol grounding problem". In contrast to most of the research on symbol grounding, we propose to exploit the dynamic interaction between the embodied agent and the environment as the basis for grounding. We use the term "morphological computation" to designate the fact that some of the control or computation can be taken over by the dynamic interaction derived from morphological properties (e.g. the passive forward swing of the leg in walking, the spring-like properties of the muscles, and the weight distribution). By taking morphological computation into account, an agent will be able to achieve not only faster, more robust, and more energy-efficient behavior, but also more situated exploration by the agent for the comprehensive understanding of the environment.


SNF Project Locomotion: Progress report 2008-2009

Abstract: Summary of results (project period 1. 10. 2008 - 30. 9. 2009) of SNFS Project "From locomotion to cognition" The research that we have been involved in, and will continue to do, starts from the insight that in order to understand and design intelligent behavior, we must adopt an embodied perspective, i.e. we must take the entire agent, including its shape or morphology, the materials out of which it is built, and its interaction with the environment into account, in addition to the neural control. A lot of our research in the past has been on relatively low-level sensory-motor tasks such as locomotion (e.g. walking, running, jumping), navigation, and grasping. While this research is of interest in itself, in the context of artificial intelligence and cognitive science, this leads to the question of what these kinds of tasks have to do with higher levels of cognition, or to put it more provocatively, "What does walking have to do with thinking?" This question is of course reminiscent of the notorious "symbol grounding problem". In contrast to most of the research on symbol grounding, we propose to exploit the dynamic interaction between the embodied agent and the environment as the basis for grounding. We use the term "morphological computation" to designate the fact that some of the control or computation can be taken over by the dynamic interaction derived from morphological properties (e.g. the passive forward swing of the leg in walking, the spring-like properties of the muscles, and the weight distribution). By taking morphological computation into account, an agent will be able to achieve not only faster, more robust, and more energy-efficient behavior, but also more situated exploration by the agent for the comprehensive understanding of the environment.


Magneto-mechanical actuation model for fin-based locomotion

Abstract: In this paper, we report the results from the analysis of a numerical model used for the design of a magnetic linear actuator with applications to fin-based locomotion. Most of the current robotic fish generate bending motion using rotary motors which implies at least one mechanical conversion of the motion. We seek a solution that directly bends the fin and, at the same time, is able to exploit the magneto-mechanical properties of the fin material. This strong fin-actuator coupling blends the actuator and the body of the robot, allowing cross optimization of the system's elements. We study a simplified model of an elastic element, a spring-mass system representing a flexible fin, subjected to nonlinear forcing, emulating magnetic interaction. The dynamics of the system is studied under unforced and periodic forcing conditions. The analysis is focused on the limit cycles present in the system, which allows the periodic bending of the fin and the generation of thrust. The frequency, maximum amplitude and center of the periodic orbits (offset of the bending) depend directly on the stiffness of the fin and the intensity of the forcing; we use this dependency to sketch a simple parameter controller. Although the model is strongly simplified, it provides means to estimate first values of the parameters for this kind of actuator and it is useful to evaluate the feasibility of minimal actuation control of such systems.


Graphical representation of covariant-contravariant modal formulae

Abstract: Covariant-contravariant simulation is a combination of standard (covariant) simulation, its contravariant counterpart and bisimulation. We have previously studied its logical characterization by means of the covariant-contravariant modal logic. Moreover, we have investigated the relationships between this model and that of modal transition systems, where two kinds of transitions (the so-called may and must transitions) were combined in order to obtain a simple framework to express a notion of refinement over state-transition models. In a classic paper, Boudol and Larsen established a precise connection between the graphical approach, by means of modal transition systems, and the logical approach, based on Hennessy-Milner logic without negation, to system specification. They obtained a (graphical) representation theorem proving that a formula can be represented by a term if, and only if, it is consistent and prime. We show in this paper that the formulae from the covariant-contravariant modal logic that admit a "graphical" representation by means of processes, modulo the covariant-contravariant simulation preorder, are also the consistent and prime ones. In order to obtain the desired graphical representation result, we first restrict ourselves to the case of covariant-contravariant systems without bivariant actions. Bivariant actions can be incorporated later by means of an encoding that splits each bivariant action into its covariant and its contravariant parts.


Information Flow Safety in Multiparty Sessions

Abstract: We consider a calculus for multiparty sessions enriched with security levels for messages. We propose a monitored semantics for this calculus, which blocks the execution of processes as soon as they attempt to leak information. We illustrate the use of our monitored semantics with various examples, and show that the induced safety property implies a noninterference property studied previously.


Read Operators and their Expressiveness in Process Algebras

Abstract: We study two different ways to enhance PAFAS, a process algebra for modelling asynchronous timed concurrent systems, with non-blocking reading actions. We first add reading in the form of a read-action prefix operator. This operator is very flexible, but its somewhat complex semantics requires two types of transition relations. We also present a read-set prefix operator with a simpler semantics, but with syntactic restrictions. We discuss the expressiveness of read prefixes; in particular, we compare them to read-arcs in Petri nets and justify the simple semantics of the second variant by showing that its processes can be translated into processes of the first with timed-bisimilar behaviour. It is still an open problem whether the first algebra is more expressive than the second; we give a number of laws that are interesting in their own right, and can help to find a backward translation.


Soft Session Types

Abstract: We show how systems of session types can enforce interactions to be bounded for all typable processes. The type system we propose is based on Lafont's soft linear logic and is strongly inspired by recent works about session types as intuitionistic linear logic formulas. Our main result is the existence, for every typable process, of a polynomial bound on the length of any reduction sequence starting from it and on the size of any of its reducts.


Linearization of CIF Through SOS

Abstract: Linearization is the procedure of rewriting a process term into a linear form, which consist only of basic operators of the process language. This procedure is interesting both from a theoretical and a practical point of view. In particular, a linearization algorithm is needed for the Compositional Interchange Format (CIF), an automaton based modeling language. The problem of devising efficient linearization algorithms is not trivial, and has been already addressed in literature. However, the linearization algorithms obtained are the result of an inventive process, and the proof of correctness comes as an afterthought. Furthermore, the semantic specification of the language does not play an important role on the design of the algorithm. In this work we present a method for obtaining an efficient linearization algorithm, through a step-wise refinement of the SOS rules of CIF. As a result, we show how the semantic specification of the language can guide the implementation of such a procedure, yielding a simple proof of correctness.


Synchrony vs Causality in the Asynchronous Pi-Calculus

Abstract: We study the relation between process calculi that differ in their either synchronous or asynchronous interaction mechanism. Concretely, we are interested in the conditions under which synchronous interaction can be implemented using just asynchronous interactions in the pi-calculus. We assume a number of minimal conditions referring to the work of Gorla: a "good" encoding must be compositional and preserve and reflect computations, deadlocks, divergence, and success. Under these conditions, we show that it is not possible to encode synchronous interactions without introducing additional causal dependencies in the translation.


A Logic with Reverse Modalities for History-preserving Bisimulations

Abstract: We introduce event identifier logic (EIL) which extends Hennessy-Milner logic by the addition of (1) reverse as well as forward modalities, and (2) identifiers to keep track of events. We show that this logic corresponds to hereditary history-preserving (HH) bisimulation equivalence within a particular true-concurrency model, namely stable configuration structures. We furthermore show how natural sublogics of EIL correspond to coarser equivalences. In particular we provide logical characterisations of weak history-preserving (WH) and history-preserving (H) bisimulation. Logics corresponding to HH and H bisimulation have been given previously, but not to WH bisimulation (when autoconcurrency is allowed), as far as we are aware. We also present characteristic formulas which characterise individual structures with respect to history-preserving equivalences.


Synchrony vs. Causality in Asynchronous Petri Nets

Abstract: Given a synchronous system, we study the question whether the behaviour of that system can be exhibited by a (non-trivially) distributed and hence asynchronous implementation. In this paper we show, by counterexample, that synchronous systems cannot in general be implemented in an asynchronous fashion without either introducing an infinite implementation or changing the causal structure of the system behaviour.


Parameterized Complexity of MaxSat Above Average

Abstract: In MaxSat, we are given a CNF formula $F$ with $n$ variables and $m$ clauses and asked to find a truth assignment satisfying the maximum number of clauses. Let $r_1,..., r_m$ be the number of literals in the clauses of $F$. Then $asat(F)=\sum_{i=1}^m (1-2^{-r_i})$ is the expected number of clauses satisfied by a random truth assignment (the truth values to the variables are distributed uniformly and independently). It is well-known that, in polynomial time, one can find a truth assignment satisfying at least $asat(F)$ clauses. In the parameterized problem MaxSat-AA, we are to decide whether there is a truth assignment satisfying at least $asat(F)+k$ clauses, where $k$ is the parameter. We prove that MaxSat-AA is para-NP-complete and, thus, MaxSat-AA is not fixed-parameter tractable unless P$=$NP. This is in sharp contrast to MaxLin2-AA which was recently proved to be fixed-parameter tractable by Crowston et al. (arXiv:1104.1135v3). In fact, we consider a more refined version of {\sc MaxSat-AA}, {\sc Max-$r(n)$-Sat-AA}, where $r_j\le r(n)$ for each $j$. Alon {\em et al.} (SODA 2010) proved that if $r=r(n)$ is a constant, then {\sc Max-$r$-Sat-AA} is fixed-parameter tractable. We prove that {\sc Max-$r(n)$-Sat-AA} is para-NP-complete for $r(n)=\lceil \log n\rceil.$ We also prove that assuming the exponential time hypothesis, {\sc Max-$r(n)$-Sat-AA} is not in XP already for any $r(n)\ge \log \log n +\phi(n)$, where $\phi(n)$ is any unbounded strictly increasing function. This lower bound on $r(n)$ cannot be decreased much further as we prove that {\sc Max-$r(n)$-Sat-AA} is (i) in XP for any $r(n)\le \log \log n - \log \log \log n$ and (ii) fixed-parameter tractable for any $r(n)\le \log \log n - \log \log \log n - \phi(n)$, where $\phi(n)$ is any unbounded strictly increasing function. The proof uses some results on {\sc MaxLin2-AA}.


Trading Order for Degree in Creative Telescoping

Abstract: We analyze the differential equations produced by the method of creative telescoping applied to a hyperexponential term in two variables. We show that equations of low order have high degree, and that higher order equations have lower degree. More precisely, we derive degree bounding formulas which allow to estimate the degree of the output equations from creative telescoping as a function of the order. As an application, we show how the knowledge of these formulas can be used to improve, at least in principle, the performance of creative telescoping implementations, and we deduce bounds on the asymptotic complexity of creative telescoping for hyperexponential terms.


Scalable Continual Top-k Keyword Search in Relational Databases

Abstract: Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. Most of existing methods focus on answering snapshot keyword queries in static databases. In practice, however, databases are updated frequently, and users may have long-term interests on specific topics. To deal with such a situation, it is necessary to build effective and efficient facility in a database system to support continual keyword queries. In this paper, we propose an efficient method for answering continual top-$k$ keyword queries over relational databases. The proposed method is built on an existing scheme of keyword search on relational data streams, but incorporates the ranking mechanisms into the query processing methods and makes two improvements to support efficient top-$k$ keyword search in relational databases. Compared to the existing methods, our method is more efficient both in computing the top-$k$ results in a static database and in maintaining the top-$k$ results when the database continually being updated. Experimental results validate the effectiveness and efficiency of the proposed method.