Search results for "string"

showing 10 items of 381 documents

Material Flow in FSW of T-joints: Experimental and Numerical Analysis

2008

In the paper the authors present the results of both an experimental and a numerical campaign focused on the analysis of the occurring material flow in the FSW of T joints of aluminum alloys. In particular to investigate the metal flow experimental tests and observations has been developed utilizing a thin foil of copper as marker placed between the skin and the stringer. In this way, the actual metal flow occurring during the FSW of T-joints has been highlighted together with the real bonding surface. The acquired information is definitively useful in order to choose effective set of process parameters, improving the process mechanics and avoiding the insurgence of defects.

FEMMaterials scienceNumerical analysisFSWMetallurgyT-JointProcess (computing)Mechanical engineeringFinite element methodMaterial flowMetal flowStringerGeneral Materials Sciencematerial flowSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneFOIL method
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On the Greedy Algorithm for the Shortest Common Superstring Problem with Reversals

2015

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem Shortest Common Superstring with Reversals (SCS-R). This problem has been introduced by Jiang et al., who designed a greedy-like algorithm with length approximation ratio $4$. In this paper, we show that a natural adaptation of the classical greedy algorithm for SCS has (optimal) compression ratio $\frac12$, i.e., the sum of the overlaps in the output string is at least half the sum of the overlaps in an optimal solution. We also provide a linear-time implement…

FOS: Computer and information sciences0102 computer and information sciences02 engineering and technologyInformation System01 natural sciencesString (physics)Theoretical Computer ScienceCombinatoricsHigh Energy Physics::TheoryAnalysis of algorithmGreedy algorithmComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Greedy algorithmFinite setAnalysis of algorithmsMathematicsSuperstring theoryShortest Common SuperstringComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsReversalShortest Path Faster Algorithm010201 computation theory & mathematicsCompression ratioSignal Processing020201 artificial intelligence & image processingK shortest path routingInformation Systems
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Novel Results on the Number of Runs of the Burrows-Wheeler-Transform

2021

The Burrows-Wheeler-Transform (BWT), a reversible string transformation, is one of the fundamental components of many current data structures in string processing. It is central in data compression, as well as in efficient query algorithms for sequence data, such as webpages, genomic and other biological sequences, or indeed any textual data. The BWT lends itself well to compression because its number of equal-letter-runs (usually referred to as $r$) is often considerably lower than that of the original string; in particular, it is well suited for strings with many repeated factors. In fact, much attention has been paid to the $r$ parameter as measure of repetitiveness, especially to evalua…

FOS: Computer and information sciencesBurrows–Wheeler transformSettore INF/01 - InformaticaCombinatorics on wordsFormal Languages and Automata Theory (cs.FL)Computer scienceString (computer science)Search engine indexingCompressed data structuresComputer Science - Formal Languages and Automata TheoryString indexingData structureMeasure (mathematics)Burrows-Wheeler-TransformRepetitivenessCombinatorics on wordsBurrows-Wheeler-Transform Compressed data structures String indexing Repetitiveness Combinatorics on wordsTransformation (function)Computer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)AlgorithmData compression
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Adaptive learning of compressible strings

2020

Suppose an oracle knows a string $S$ that is unknown to us and that we want to determine. The oracle can answer queries of the form "Is $s$ a substring of $S$?". In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle $\sigma n/4 -O(n)$ queries in order to be able to reconstruct the hidden string, where $\sigma$ is the size of the alphabet of $S$ and $n$ its length, and gave an algorithm that spends $(\sigma-1)n+O(\sigma \sqrt{n})$ queries to reconstruct $S$. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compre…

FOS: Computer and information sciencesCentroid decompositionGeneral Computer ScienceString compressionAdaptive learningKolmogorov complexityContext (language use)Data_CODINGANDINFORMATIONTHEORYString reconstructionTheoretical Computer ScienceCombinatoricsString reconstruction; String learning; Adaptive learning; Kolmogorov complexity; String compression; Lempel-Ziv; Centroid decomposition; Suffix treeSuffix treeIntegerComputer Science - Data Structures and AlgorithmsOrder (group theory)Data Structures and Algorithms (cs.DS)Adaptive learning; Centroid decomposition; Kolmogorov complexity; Lempel-Ziv; String compression; String learning; String reconstruction; Suffix treeTime complexityComputer Science::DatabasesMathematicsLempel-ZivSettore INF/01 - InformaticaLinear spaceString (computer science)SubstringBounded functionString learningTheoretical Computer Science
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Lightweight LCP construction for very large collections of strings

2016

The longest common prefix array is a very advantageous data structure that, combined with the suffix array and the Burrows-Wheeler transform, allows to efficiently compute some combinatorial properties of a string useful in several applications, especially in biological contexts. Nowadays, the input data for many problems are big collections of strings, for instance the data coming from "next-generation" DNA sequencing (NGS) technologies. In this paper we present the first lightweight algorithm (called extLCP) for the simultaneous computation of the longest common prefix array and the Burrows-Wheeler transform of a very large collection of strings having any length. The computation is reali…

FOS: Computer and information sciencesComputer scienceComputation0102 computer and information sciences02 engineering and technologyParallel computing01 natural sciencesGeneralized Suffix ArrayTheoretical Computer Sciencelaw.inventionlawComputational Theory and MathematicComputer Science - Data Structures and AlgorithmsExtended Burrows-Wheeler TransformData_FILES0202 electrical engineering electronic engineering information engineeringDiscrete Mathematics and CombinatoricsData Structures and Algorithms (cs.DS)Discrete Mathematics and CombinatoricAuxiliary memoryLongest Common Prefix Array; Extended Burrows-Wheeler Transform; Generalized Suffix Array;String (computer science)LCP arraySuffix arrayData structureComputational Theory and Mathematics010201 computation theory & mathematicsLongest Common Prefix Array020201 artificial intelligence & image processingJournal of Discrete Algorithms
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Algorithms for Anti-Powers in Strings

2018

Abstract A string S [ 1 , n ] is a power (or tandem repeat) of order k and period n / k if it can be decomposed into k consecutive equal-length blocks of letters. Powers and periods are fundamental to string processing, and algorithms for their efficient computation have wide application and are heavily studied. Recently, Fici et al. (Proc. ICALP 2016) defined an anti-power of order k to be a string composed of k pairwise-distinct blocks of the same length ( n / k , called anti-period). Anti-powers are a natural converse to powers, and are objects of combinatorial interest in their own right. In this paper we initiate the algorithmic study of anti-powers. Given a string S, we describe an op…

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)Formal Languages and Automata Theory (cs.FL)ComputationComputer Science - Formal Languages and Automata Theory0102 computer and information sciencesString processingInformation System01 natural sciencesUpper and lower boundsAnti-powersTheoretical Computer ScienceLemma (logic)ConverseComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)0101 mathematicsMathematicsCombinatorics on wordSignal processingCombinatorics on wordsComputer Science Applications1707 Computer Vision and Pattern RecognitionAnti-power16. Peace & justice113 Computer and information sciencesSubstringComputer Science Applications010101 applied mathematicsAlgorithmCombinatorics on words010201 computation theory & mathematicsSignal ProcessingAlgorithmAlgorithmsInformation SystemsComputer Science - Discrete Mathematics
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A subquadratic algorithm for minimum palindromic factorization

2014

We give an $\mathcal{O}(n \log n)$-time, $\mathcal{O}(n)$-space algorithm for factoring a string into the minimum number of palindromic substrings. That is, given a string $S [1..n]$, in $\mathcal{O}(n \log n)$ time our algorithm returns the minimum number of palindromes $S_1,\ldots, S_\ell$ such that $S = S_1 \cdots S_\ell$. We also show that the time complexity is $\mathcal{O}(n)$ on average and $\Omega(n\log n)$ in the worst case. The last result is based on a characterization of the palindromic structure of Zimin words.

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)PalindromeCharacterization (mathematics)Binary logarithmOmegaSubstringTheoretical Computer ScienceString algorithmComputational Theory and MathematicsFactorizationComputer Science - Data Structures and AlgorithmsC++ string handlingPalindromeDiscrete Mathematics and CombinatoricsData Structures and Algorithms (cs.DS)FactorizationTime complexityAlgorithmMathematicsComputer Science - Discrete Mathematics
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On the Power of Non-adaptive Learning Graphs

2012

We introduce a notion of the quantum query complexity of a certificate structure. This is a formalisation of a well-known observation that many quantum query algorithms only require the knowledge of the disposition of possible certificates in the input string, not the precise values therein. Next, we derive a dual formulation of the complexity of a non-adaptive learning graph, and use it to show that non-adaptive learning graphs are tight for all certificate structures. By this, we mean that there exists a function possessing the certificate structure and such that a learning graph gives an optimal quantum query algorithm for it. For a special case of certificate structures generated by cer…

FOS: Computer and information sciencesDiscrete mathematicsQuantum PhysicsTheoretical computer scienceComputational complexity theoryComputer scienceGeneral MathematicsExistential quantificationFOS: Physical sciencesGraph theoryString searching algorithmComputational Complexity (cs.CC)Query optimizationCertificateUpper and lower boundsTheoretical Computer ScienceComputational MathematicsComputer Science - Computational ComplexityComputational Theory and MathematicsBounded functionAdaptive learningSpecial caseQuantum Physics (quant-ph)Quantum computerMathematics2013 IEEE Conference on Computational Complexity
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Online Computation of Abelian Runs

2015

Given a word $w$ and a Parikh vector $\mathcal{P}$, an abelian run of period $\mathcal{P}$ in $w$ is a maximal occurrence of a substring of $w$ having abelian period $\mathcal{P}$. We give an algorithm that finds all the abelian runs of period $\mathcal{P}$ in a word of length $n$ in time $O(n\times |\mathcal{P}|)$ and space $O(\sigma+|\mathcal{P}|)$.

FOS: Computer and information sciencesFormal Languages and Automata Theory (cs.FL)Abelian run[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]Computer Science - Formal Languages and Automata Theory0102 computer and information sciences02 engineering and technology[INFO] Computer Science [cs]01 natural sciencesOnline computationTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)[INFO]Computer Science [cs]Abelian groupComputingMilieux_MISCELLANEOUSMathematicsCombinatorics on wordDiscrete mathematicsComputer Science (all)020206 networking & telecommunicationsAbelian periodText algorithm16. Peace & justiceSubstringCombinatorics on words010201 computation theory & mathematicsWord (group theory)Computer Science::Formal Languages and Automata Theory
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Fast computation of abelian runs

2016

Given a word $w$ and a Parikh vector $\mathcal{P}$, an abelian run of period $\mathcal{P}$ in $w$ is a maximal occurrence of a substring of $w$ having abelian period $\mathcal{P}$. Our main result is an online algorithm that, given a word $w$ of length $n$ over an alphabet of cardinality $\sigma$ and a Parikh vector $\mathcal{P}$, returns all the abelian runs of period $\mathcal{P}$ in $w$ in time $O(n)$ and space $O(\sigma+p)$, where $p$ is the norm of $\mathcal{P}$, i.e., the sum of its components. We also present an online algorithm that computes all the abelian runs with periods of norm $p$ in $w$ in time $O(np)$, for any given norm $p$. Finally, we give an $O(n^2)$-time offline randomi…

FOS: Computer and information sciencesGeneral Computer ScienceComputationAbelian run[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Elementary abelian group0102 computer and information sciences02 engineering and technology01 natural sciencesRank of an abelian groupTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)[INFO]Computer Science [cs]Online algorithmAbelian groupComputingMilieux_MISCELLANEOUSMathematicsCombinatorics on wordDiscrete mathematicsComputer Science (all)Abelian periodText algorithm16. Peace & justiceSubstringRandomized algorithmCombinatorics on words010201 computation theory & mathematics020201 artificial intelligence & image processingComputer Science::Formal Languages and Automata Theory
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