Academic literature on the topic 'String algorithm'
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Journal articles on the topic "String algorithm"
Bhagya Sri, Mukku, Rachita Bhavsar, and Preeti Narooka. "String Matching Algorithms." International Journal Of Engineering And Computer Science 7, no. 03 (March 23, 2018): 23769–72. http://dx.doi.org/10.18535/ijecs/v7i3.19.
Full textZhang, Zhaoyang. "Review on String-Matching Algorithm." SHS Web of Conferences 144 (2022): 03018. http://dx.doi.org/10.1051/shsconf/202214403018.
Full textRusso, Luıs, and Alexandre Francisco. "Small Longest Tandem Scattered Subsequences." Scientific Annals of Computer Science 31, no. 1 (August 9, 2021): 79–110. http://dx.doi.org/10.7561/sacs.2021.1.79.
Full textJantan, Hamidah, and Nurul Aisyiah Baharudin. "Mobile-Based Word Matching Detection using Intelligent Predictive Algorithm." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 09 (September 5, 2019): 140. http://dx.doi.org/10.3991/ijim.v13i09.10848.
Full textKhadiev, Kamil, Artem Ilikaev, and Jevgenijs Vihrovs. "Quantum Algorithms for Some Strings Problems Based on Quantum String Comparator." Mathematics 10, no. 3 (January 26, 2022): 377. http://dx.doi.org/10.3390/math10030377.
Full textFranek, Frantisek, and Michael Liut. "Computing Maximal Lyndon Substrings of a String." Algorithms 13, no. 11 (November 12, 2020): 294. http://dx.doi.org/10.3390/a13110294.
Full textTsarev, Roman Yu, Elena A. Tsareva, and Alexey S. Chernigovskiy. "Combined String Searching Algorithm." Journal of Siberian Federal University. Engineering & Technologies 10, no. 1 (February 2017): 126–35. http://dx.doi.org/10.17516/1999-494x-2017-10-1-126-135.
Full textSubada, Mhd Ali. "Comparisonal Analysis Of Even-Rodeh Algorithm Code And Fibonacci Code Algorithm For Text File Compression." Journal Basic Science and Technology 11, no. 1 (February 28, 2022): 1–7. http://dx.doi.org/10.35335/jbst.v11i1.1765.
Full textGhuman, Sukhpal, Emanuele Giaquinta, and Jorma Tarhio. "Lyndon Factorization Algorithms for Small Alphabets and Run-Length Encoded Strings." Algorithms 12, no. 6 (June 21, 2019): 124. http://dx.doi.org/10.3390/a12060124.
Full textMarkić, Ivan, Maja Štula, Marija Zorić, and Darko Stipaničev. "Entropy-Based Approach in Selection Exact String-Matching Algorithms." Entropy 23, no. 1 (December 28, 2020): 31. http://dx.doi.org/10.3390/e23010031.
Full textDissertations / Theses on the topic "String algorithm"
Berry, Thomas. "Algorithm engineering : string processing." Thesis, Liverpool John Moores University, 2002. http://researchonline.ljmu.ac.uk/4973/.
Full textMacLeod, Christopher. "The synthesis of artificial neural networks using single string evolutionary techniques." Thesis, Robert Gordon University, 1999. http://hdl.handle.net/10059/367.
Full textDubois, Simon. "Offline Approximate String Matching forInformation Retrieval : An experiment on technical documentation." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Informationsteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-22566.
Full textFrey, Jeffrey Daniel. "Finding Song Melody Similarities Using a DNA String Matching Algorithm." Kent State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=kent1208961242.
Full textGundu, Pavan Kumar. "Trajectory Tracking Control of Unmanned Ground Vehicles using an Intermittent Learning Algorithm." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/93213.
Full textMaster of Science
A risen research effort in the area of autonomous vehicles has been witnessed in the past few decades because these systems improve safety, comfort, transport time and energy consumption which are some of the main issues humans are facing in the modern world’s highway systems. Systems like emergency braking, automatic parking, blind angle vehicle detection are creating a safer driving environment in populated areas. Advanced driver assistance systems (ADAS) are what such kind of systems are known as. An extension of these partially automated ADAS are vehicles with fully automated driving abilities, which are able to drive by themselves without any human involvement. An extensively proposed approach for making traffic throughput more efficient on existing highways is to assemble autonomous vehicles into platoons. Small intervehicle spacing and many vehicles constituting each platoon formation improve the traffic throughput significantly. Lately, the advancements in computational capabilities, in terms of both algorithms and hardware, communications, and navigation and sensing devices contributed a lot to the development of autonomous systems (both single and multiagent) that operate with high reliability in uncertain/dynamic operating conditions and environments. Motion control is an important area in the autonomous vehicles research. Trajectory-tracking is a widely studied motion control scenario which is about designing control laws that force a system to follow some time-dependent reference path and it is important to have an effective and efficient trajectory-tracking control law in an autonomous vehicle to reduce the resources consumed and tracking error. The goal of this work is to design an intermittent model-free trajectory tracking control algorithm where there is no need of any mathematical model of the vehicle system being controlled and which can reduce the controller updates by allowing the system to evolve in an open loop fashion and close the loop only when an user defined triggering condition is satisfied. The approach is energy efficient in that the control updates are limited to instances when they are needed rather than unnecessary periodic updates. Q-learning which is a model-free reinforcement learning technique is used in the trajectory tracking motion control algorithm to make the vehicles track their respective reference trajectories without any requirement of their motion model, the knowledge of which is generally needed when dealing with a motion control problem. The testing of the designed algorithm in simulations and experiments is presented in this work. The study and development of a vehicle platform in order to perform the experiments is also discussed. Different motion control and sensing techniques are presented and used. The vehicle platform is shown to track a reference trajectory autonomously without any human intervention, both in simulations and experiments, proving the effectiveness of the proposed algorithm.
Momeninasab, Leila. "Design and Implementation of a Name Matching Algorithm for Persian Language." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-102210.
Full textBERNARDINI, GIULIA. "COMBINATORIAL METHODS FOR BIOLOGICAL DATA." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/305220.
Full textThe main goal of this thesis is to develop new algorithmic frameworks to deal with (i) a convenient representation of a set of similar genomes and (ii) phylogenetic data, with particular attention to the increasingly accurate tumor phylogenies. A “pan-genome” is, in general, any collection of genomic sequences to be analyzed jointly or to be used as a reference for a population. A phylogeny, in turn, is meant to describe the evolutionary relationships among a group of items, be they species of living beings, genes, natural languages, ancient manuscripts or cancer cells. With the exception of one of the results included in this thesis, related to the analysis of tumor phylogenies, the focus of the whole work is mainly theoretical, the intent being to lay firm algorithmic foundations for the problems by investigating their combinatorial aspects, rather than to provide practical tools for attacking them. Deep theoretical insights on the problems allow a rigorous analysis of existing methods, identifying their strong and weak points, providing details on how they perform and helping to decide which problems need to be further addressed. In addition, it is often the case where new theoretical results (algorithms, data structures and reductions to other well-studied problems) can either be directly applied or adapted to fit the model of a practical problem, or at least they serve as inspiration for developing new practical tools. The first part of this thesis is devoted to methods for handling an elastic-degenerate text, a computational object that compactly encodes a collection of similar texts, like a pan-genome. Specifically, we attack the problem of matching a sequence in an elastic-degenerate text, both exactly and allowing a certain amount of errors, and the problem of comparing two degenerate texts. In the second part we consider both tumor phylogenies, describing the evolution of a tumor, and “classical” phylogenies, representing, for instance, the evolutionary history of the living beings. In particular, we present new techniques to compare two or more tumor phylogenies, needed to evaluate the results of different inference methods, and we give a new, efficient solution to a longstanding problem on “classical” phylogenies: to decide whether, in the presence of missing data, it is possible to arrange a set of species in a phylogenetic tree that enjoys specific properties.
Moradi, Arvin. "Smart Clustering System for Filtering and Cleaning User Generated Content : Creating a profanity filter for Truecaller." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-124408.
Full textDenna avhandling fokuserar på att utreda och skapa en applikation för filtrering av användargenererat innehåll. Metoden gick ut på att undersöka hur svordomar samt rasistiska uttryck används och manipuleras för att undgå filtrerings processer i liknande system. Fokus gick även ut på att studera olika algoritmer för att få denna process att vara snabb och effektiv, dvs kunna bearbeta så många namn på kortast möjliga tid. Detta beror på att kunden i detta sammanhang får in miljontals nya uppladdningar varje dag, som måste filtreras innan använding. Resultatet visar att applikationen upptäcker svordomar i olika former. Data från kundens databas användes också för test syfte, och resultatet visade att applikationen även fungerar i praktiken. Prestanda testet visar att applikationen har en snabb exekveringstid. Detta kunde vi se genom att estimera den till en linjär funktion med hänsyn till tid och antal namn som matats in. Slutsatsen blev att filtret fungerar och upptäcker svordomar som inte upptäckts tidigare i kundens databas. För att stärka besluten i processen kan man i framtida uppdateringar införa tredje parts tjänster, eller ett web interface där man manuelt kan styra beslut. Exekverings tiden är bra och visar att 10 miljoner namn kan bearbetas på cirka 6 timmar. I framtiden kan man parallellisera förfrågningarna till databasen så att flera namn kan bearbetas samtidigt.
Alex, Ann Theja. "Local Alignment of Gradient Features for Face Photo and Face Sketch Recognition." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1353372694.
Full textPinzon, Yoan Jose. "String algorithms on sequence comparison." Thesis, King's College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395648.
Full textBooks on the topic "String algorithm"
Castillo, Oscar, and Luis Rodriguez. A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-82288-0.
Full textLandau, Gad M. An efficient string matching algorithm with k differences for nucleotide and amino acid sequences. New York: Courant Institute of Mathematical Sciences, New York University, 1985.
Find full textLandau, Gad M. An efficient string matching algorithm with k differences for nucleotide and amino acid sequences. New York: Courant Institute of Mathematical Sciences, New York University, 1985.
Find full textString searching algorithms. Singapore: World Scientific, 1994.
Find full textMailund, Thomas. String Algorithms in C. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5920-7.
Full text1951-, Aoe Jun-ichi, ed. Computer algorithms: String pattern matching strategies. Los Alamitos, Calif: IEEE Computer Society Press, 1994.
Find full textSmyth, Bill. Computing patterns in strings. Harlow, England: Pearson Addison-Wesley, 2003.
Find full textUnited States. National Aeronautics and Space Administration., ed. An algorithm for unsteady flows with strong convection. [Washington, DC]: National Aeronautics and Space Administration, 1988.
Find full text1948-, Apostolico Alberto, and Research Institute for Advanced Computer Science (U.S.), eds. Efficient parallel algorithms for string editing and related problems. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.
Find full textEfficient recovery algorithms with restricted access to strings. [New York, N.Y.?]: [publisher not identified], 2022.
Find full textBook chapters on the topic "String algorithm"
Martin, Eric, Samuel Kaski, Fei Zheng, Geoffrey I. Webb, Xiaojin Zhu, Ion Muslea, Kai Ming Ting, et al. "String Matching Algorithm." In Encyclopedia of Machine Learning, 929. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_791.
Full textCastillo, Oscar, and Luis Rodriguez. "String Theory Algorithm." In A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics, 11–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82288-0_3.
Full textSkiena, Steven S. "Set and String Problems." In The Algorithm Design Manual, 620–56. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-84800-070-4_18.
Full textIliopoulos, Costas S., Laurent Mouchard, and Yoan J. Pinzon. "The Max-Shift Algorithm for Approximate String Matching." In Algorithm Engineering, 13–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44688-5_2.
Full textAllauzen, Cyril, and Mathieu Raffinot. "Simple Optimal String Matching Algorithm." In Combinatorial Pattern Matching, 364–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45123-4_30.
Full textBille, Philip, Inge Li Gørtz, Hjalte Wedel Vildhøj, and Søren Vind. "String Indexing for Patterns with Wildcards." In Algorithm Theory – SWAT 2012, 283–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31155-0_25.
Full textHe, Longtao, and Binxing Fang. "Linear Nondeterministic Dawg String Matching Algorithm (Abstract)." In String Processing and Information Retrieval, 70–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30213-1_8.
Full textBruno, Andrea, Franco Maria Nardini, Giulio Ermanno Pibiri, Roberto Trani, and Rossano Venturini. "TSXor: A Simple Time Series Compression Algorithm." In String Processing and Information Retrieval, 217–23. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86692-1_18.
Full textZaslavski, Alexander J. "Dynamic String-Averaging Subgradient Projection Algorithm." In Springer Optimization and Its Applications, 243–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78849-0_6.
Full textZaslavski, Alexander J. "Dynamic String-Averaging Proximal Point Algorithm." In Springer Optimization and Its Applications, 255–79. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77437-4_7.
Full textConference papers on the topic "String algorithm"
Gupta, Aditi, Divyansh Jaiswal, Kartikeya Sinha, and Aman Duggal. "A2KD string pattern Matching Algorithm." In 2015 1st International Conference on Next Generation Computing Technologies (NGCT). IEEE, 2015. http://dx.doi.org/10.1109/ngct.2015.7375141.
Full textArshad, Kamran. "Intelligent Analytical String Search Algorithm." In 2021 International Conference on Innovative Computing (ICIC). IEEE, 2021. http://dx.doi.org/10.1109/icic53490.2021.9692974.
Full textVilca, Omar, and Rosiane De Freitas. "An efficient algorithm for the Closest String Problem." In I Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/etc.2016.9850.
Full textBabaie, Maryam, and Seyed Rasoul Mousavi. "A Memetic Algorithm for closest string problem and farthest string problem." In 2010 18th Iranian Conference on Electrical Engineering (ICEE). IEEE, 2010. http://dx.doi.org/10.1109/iraniancee.2010.5507004.
Full textDai, Liuling, and Yuning Xia. "A Lightweight Multiple String Matching Algorithm." In 2008 International Conference on Computer Science and Information Technology (ICCSIT). IEEE, 2008. http://dx.doi.org/10.1109/iccsit.2008.171.
Full textCui, Yanhong, and Renkuan Guo. "A Naïve String Algorithm." In 2008 International Workshop on Geoscience and Remote Sensing (ETT and GRS). IEEE, 2008. http://dx.doi.org/10.1109/ettandgrs.2008.231.
Full textAlzoabi, Ubaid S., Naser M. Alosaimi, Abdullah S. Bedaiwi, and Abdullatif M. Alabdullatif. "Parallelization of KMP string matching algorithm." In 2013 World Congress on Computer and Information Technology (WCCIT). IEEE, 2013. http://dx.doi.org/10.1109/wccit.2013.6618720.
Full textWang Wen-jian and Wu Shun-xiang. "A jumping string mode matching algorithm." In Education (ICCSE). IEEE, 2009. http://dx.doi.org/10.1109/iccse.2009.5228461.
Full textMeng, Qingduan, Xiaoling Zhang, and Dongwei Lv. "Improved AC_BMH Algorithm for String Matching." In 2010 International Conference on Internet Technology and Applications (iTAP). IEEE, 2010. http://dx.doi.org/10.1109/itapp.2010.5566604.
Full textAbraham, Dona, and Nisha S. Raj. "Approximate string matching algorithm for phishing detection." In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2014. http://dx.doi.org/10.1109/icacci.2014.6968578.
Full textReports on the topic "String algorithm"
Lorenz, Markus. Auswirkungen des Decoy-Effekts auf die Algorithm Aversion. Sonderforschungsgruppe Institutionenanalyse, 2022. http://dx.doi.org/10.46850/sofia.9783947850013.
Full textLaub, Alan J., and Charles Kenney. Numerically Stable Algorithms in String Dynamics. Fort Belvoir, VA: Defense Technical Information Center, September 1993. http://dx.doi.org/10.21236/ada275898.
Full textHelgason, R. V., J. L. Kennington, and K. H. Lewis. Grid Free Algorithms for Strike Planning for Cruise Missiles. Fort Belvoir, VA: Defense Technical Information Center, February 1998. http://dx.doi.org/10.21236/ada338548.
Full textBelkin, Shimshon, Sylvia Daunert, and Mona Wells. Whole-Cell Biosensor Panel for Agricultural Endocrine Disruptors. United States Department of Agriculture, December 2010. http://dx.doi.org/10.32747/2010.7696542.bard.
Full textHu, Zhengzheng, Ralph C. Smith, and Jon Ernstberger. The Homogenized Energy Model (HEM) for Characterizing Polarization and Strains in Hysteretic Ferroelectric Materials: Implementation Algorithms and Data-Driven Parameter Estimation Techniques. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada556961.
Full textIrudayaraj, Joseph, Ze'ev Schmilovitch, Amos Mizrach, Giora Kritzman, and Chitrita DebRoy. Rapid detection of food borne pathogens and non-pathogens in fresh produce using FT-IRS and raman spectroscopy. United States Department of Agriculture, October 2004. http://dx.doi.org/10.32747/2004.7587221.bard.
Full textAlchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.
Full textPERFORMANCE OPTIMIZATION OF A STEEL-UHPC COMPOSITE ORTHOTROPIC BRIDGE WITH INTELLIGENT ALGORITHM. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.160.
Full textPayment Systems Report - June of 2021. Banco de la República, February 2022. http://dx.doi.org/10.32468/rept-sist-pag.eng.2021.
Full text