LZ77 Encoding Algorithm
|
|
- Sophia Moody
- 7 years ago
- Views:
Transcription
1 Components of LZ77 General Strategy: See if the current character (or sequence of characters) in the input string has already occurred earlier in the input data. If it has, then output a pointer to the earlier occurrence. LZ77 is implemented by using a sliding window that is divided into two parts: - the search buffer which represents the most recently encoded characters. It is an implicit dictionary, so we don't have to roll the dictionary into the compressed data - a lookahead buffer which contains characters yet to be encoded. This lookahead buffer starts where the search buffer ends, and, at times during the algorithm, the search buffer extends into the lookahead buffer. November 16 2
2 LZ77 Encoding Algorithm 1) Start with the first character of the lookahead buffer 2) Find the longest match in the window for the lookahead buffer. That is, find the longest string in the search buffer that matches a recurring pattern at the beginning of the lookahead buffer. (If possible take into account that end of the search buffer in the beginning of the lookahead buffer.) 3) Output the triplet <O, L, C> where: O: is the backward offset from beginning of lookahead buffer L: is the length of the match C: is the code for the first character in the lookahead buffer that didn't match; 4) If not done, move the sliding window L+1 characters forward and return to step 2. November 16 3
3 LZ77: An Example Assume that LZ77 has a sliding window of size 20 with lookahead buffer size of 10, and search buffer size of 10. Use it to encode: she sells sea shells by the seashore $ denotes the end of input and _ denotes the space. Use C(x) to denote the encoding of character x. This encoding might well be done using another compression technique. LZ77: Remarks The search buffer is generally thousands of bytes long, while the lookahead buffer is tens of bytes long. The encoding can be quite time consuming, due to the large number of pattern-matching comparisons performed on the characters in the lookahead and search buffers. LZ77 assumes (hopes, prays) that patterns in the input string occur close together. Decoding? An improvement is achieved by eliminating the need of the third component LZ78 and LZW. November 16 4
4 In the LZ77 data compression algorithm, parameters determining the efficiency of the algorithm are the size of the file being compressed (F), the size of the search buffer (S), the size of the lookahead buffer (L), and the number of characters in the alphabet of the data being compressed (C). Assume F is an order of magnitude bigger than C -- otherwise the worst case part of this question is too easy. Provide an example of the best case execution of the LZ77 algorithm. Here "best case" refers to the best possible compression, not the fastest run time. For this best case express the size of the encoded (compressed) data in big-o terms using the four parameters F, S, L, and C. For this best case express the run time of the algorithm in big-o terms using the four parameters F, S, L, and C. Provide an example of the worst case execution of the LZ77 algorithm. Here "worst case" refers to the worst possible compression, not the slowest run time. For this worst case express the size of the encoded (compressed) data in big-o terms using the four parameters F, S, L, and C. For this worst case express the run time of the algorithm in big-o terms using the four parameters F, S, L, and C. November 16 5
5 Where is the LZ77 dictionary? What are its limitations? LZ78 Algorithms Create a dictionary of the phrases that occur in the input data. When the encoder encounters a phrase already present in the dictionary, the index number of the phrase in the dictionary is used as code. Components of LZ78 LZ78 keeps a dictionary of previously encountered strings. The encoder outputs tokens of the form: <pointer to string P, code of symbol C> where: - P denotes a string from the dictionary. - C denotes the input character currently being processed. November 16 6
6 LZ78 Encoding Algorithm 1) At the start, the dictionary and P are empty; 2) C = next input character to be processed; 3) Is the string P+C in the dictionary? (a) if it is, P = P+C (concatenate C with P); (b) if not, i) output the token <pointer to string P, code of C>; ii) add the string P+C to the dictionary; iii) P = empty; (4) Are there more input characters to be processed? (a) if yes, return to step 2; (b) if not: i) if P is not empty, output the token <pointer to P, code of C>; ii) END. LZ78: An Example Use LZ78 to encode: sir sid eastman easily teases sea sick seals The symbol _ denotes the space and $ end of file. "x" will denote the encoding of character x. At the beginning the dictionary is empty. It starts with the null string at position zero. November 16 7
7 After the First 12 Encoding Steps sir sid easeman easily teases sea sick seals$ Dictionary Output Position String Token 0 null 1 s <0, "s"> 2 i <0, "i"> 3 r <0, "r"> 4 - <0, "-"> 5 si <1, "i"> 6 d <0, "d"> 7 -e <4, "e"> 8 a <0, "a"> 9 st <1, "t"> 10 m <0, "m"> 11 an <8, "n"> 12 -ea <7, "a"> November 16 8
8 Final Dictionary and Encoding (Continued) sir sid eastman easily teases sea sick seals$ 13 sil <5,"l"> 14 y <0, "y"> 15 -t <4, "t"> 16 e <0, "e"> 17 as <8, "s"> 18 es <16, "s"> 19 -s <4, "s"> 20 ea <16, "a"> 21 -si <19, "i"> 22 c <0, "c"> 23 k <0, "k"> 24 -se <19, "e"> 25 al <8, "l"> 26 s$ <l, "$"> November 16 9
Multimedia Systems WS 2010/2011
Multimedia Systems WS 2010/2011 31.01.2011 M. Rahamatullah Khondoker (Room # 36/410 ) University of Kaiserslautern Department of Computer Science Integrated Communication Systems ICSY http://www.icsy.de
More informationLempel-Ziv Coding Adaptive Dictionary Compression Algorithm
Lempel-Ziv Coding Adaptive Dictionary Compression Algorithm 1. LZ77:Sliding Window Lempel-Ziv Algorithm [gzip, pkzip] Encode a string by finding the longest match anywhere within a window of past symbols
More informationCompression techniques
Compression techniques David Bařina February 22, 2013 David Bařina Compression techniques February 22, 2013 1 / 37 Contents 1 Terminology 2 Simple techniques 3 Entropy coding 4 Dictionary methods 5 Conclusion
More informationStreaming Lossless Data Compression Algorithm (SLDC)
Standard ECMA-321 June 2001 Standardizing Information and Communication Systems Streaming Lossless Data Compression Algorithm (SLDC) Phone: +41 22 849.60.00 - Fax: +41 22 849.60.01 - URL: http://www.ecma.ch
More informationStorage Optimization in Cloud Environment using Compression Algorithm
Storage Optimization in Cloud Environment using Compression Algorithm K.Govinda 1, Yuvaraj Kumar 2 1 School of Computing Science and Engineering, VIT University, Vellore, India kgovinda@vit.ac.in 2 School
More informationLossless Data Compression Standard Applications and the MapReduce Web Computing Framework
Lossless Data Compression Standard Applications and the MapReduce Web Computing Framework Sergio De Agostino Computer Science Department Sapienza University of Rome Internet as a Distributed System Modern
More informationArithmetic Coding: Introduction
Data Compression Arithmetic coding Arithmetic Coding: Introduction Allows using fractional parts of bits!! Used in PPM, JPEG/MPEG (as option), Bzip More time costly than Huffman, but integer implementation
More informationAnalysis of Compression Algorithms for Program Data
Analysis of Compression Algorithms for Program Data Matthew Simpson, Clemson University with Dr. Rajeev Barua and Surupa Biswas, University of Maryland 12 August 3 Abstract Insufficient available memory
More informationLexical analysis FORMAL LANGUAGES AND COMPILERS. Floriano Scioscia. Formal Languages and Compilers A.Y. 2015/2016
Master s Degree Course in Computer Engineering Formal Languages FORMAL LANGUAGES AND COMPILERS Lexical analysis Floriano Scioscia 1 Introductive terminological distinction Lexical string or lexeme = meaningful
More informationOn the Use of Compression Algorithms for Network Traffic Classification
On the Use of for Network Traffic Classification Christian CALLEGARI Department of Information Ingeneering University of Pisa 23 September 2008 COST-TMA Meeting Samos, Greece Outline Outline 1 Introduction
More informationA Multiple Sliding Windows Approach to Speed Up String Matching Algorithms
A Multiple Sliding Windows Approach to Speed Up String Matching Algorithms Simone Faro and Thierry Lecroq Università di Catania, Viale A.Doria n.6, 95125 Catania, Italy Université de Rouen, LITIS EA 4108,
More informationLZ77. Example 2.10: Let T = badadadabaab and assume d max and l max are large. phrase b a d adadab aa b
LZ77 The original LZ77 algorithm works as follows: A phrase T j starting at a position i is encoded as a triple of the form distance, length, symbol. A triple d, l, s means that: T j = T [i...i + l] =
More informationSymbol Tables. Introduction
Symbol Tables Introduction A compiler needs to collect and use information about the names appearing in the source program. This information is entered into a data structure called a symbol table. The
More informationThis is a preview - click here to buy the full publication INTERNATIONAL STANDARD
INTERNATIONAL STANDARD lso/iec 500 First edition 996-l -0 Information technology - Adaptive Lossless Data Compression algorithm (ALDC) Technologies de I informa tjon - Algorithme de compression de don&es
More informationImage Compression through DCT and Huffman Coding Technique
International Journal of Current Engineering and Technology E-ISSN 2277 4106, P-ISSN 2347 5161 2015 INPRESSCO, All Rights Reserved Available at http://inpressco.com/category/ijcet Research Article Rahul
More informationA Catalogue of the Steiner Triple Systems of Order 19
A Catalogue of the Steiner Triple Systems of Order 19 Petteri Kaski 1, Patric R. J. Östergård 2, Olli Pottonen 2, and Lasse Kiviluoto 3 1 Helsinki Institute for Information Technology HIIT University of
More informationChapter 2: Elements of Java
Chapter 2: Elements of Java Basic components of a Java program Primitive data types Arithmetic expressions Type casting. The String type (introduction) Basic I/O statements Importing packages. 1 Introduction
More informationData Reduction: Deduplication and Compression. Danny Harnik IBM Haifa Research Labs
Data Reduction: Deduplication and Compression Danny Harnik IBM Haifa Research Labs Motivation Reducing the amount of data is a desirable goal Data reduction: an attempt to compress the huge amounts of
More informationInformation Theory and Coding Prof. S. N. Merchant Department of Electrical Engineering Indian Institute of Technology, Bombay
Information Theory and Coding Prof. S. N. Merchant Department of Electrical Engineering Indian Institute of Technology, Bombay Lecture - 17 Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding
More informationInformation, Entropy, and Coding
Chapter 8 Information, Entropy, and Coding 8. The Need for Data Compression To motivate the material in this chapter, we first consider various data sources and some estimates for the amount of data associated
More informationKhalid Sayood and Martin C. Rost Department of Electrical Engineering University of Nebraska
PROBLEM STATEMENT A ROBUST COMPRESSION SYSTEM FOR LOW BIT RATE TELEMETRY - TEST RESULTS WITH LUNAR DATA Khalid Sayood and Martin C. Rost Department of Electrical Engineering University of Nebraska The
More informationCompressing Medical Records for Storage on a Low-End Mobile Phone
Honours Project Report Compressing Medical Records for Storage on a Low-End Mobile Phone Paul Brittan pbrittan@cs.uct.ac.za Supervised By: Sonia Berman, Gary Marsden & Anne Kayem Category Min Max Chosen
More informationBase Table. (a) Conventional Relational Representation Basic DataIndex Representation. Basic DataIndex on RetFlag
Indexing and Compression in Data Warehouses Kiran B. Goyal Computer Science Dept. Indian Institute of Technology, Bombay kiran@cse.iitb.ernet.in Anindya Datta College of Computing. Georgia Institute of
More informationCHAPTER 2 LITERATURE REVIEW
11 CHAPTER 2 LITERATURE REVIEW 2.1 INTRODUCTION Image compression is mainly used to reduce storage space, transmission time and bandwidth requirements. In the subsequent sections of this chapter, general
More informationChapter 4: Computer Codes
Slide 1/30 Learning Objectives In this chapter you will learn about: Computer data Computer codes: representation of data in binary Most commonly used computer codes Collating sequence 36 Slide 2/30 Data
More informationToday s topics. Digital Computers. More on binary. Binary Digits (Bits)
Today s topics! Binary Numbers! Brookshear.-.! Slides from Prof. Marti Hearst of UC Berkeley SIMS! Upcoming! Networks Interactive Introduction to Graph Theory http://www.utm.edu/cgi-bin/caldwell/tutor/departments/math/graph/intro
More informationBig Data Technology Map-Reduce Motivation: Indexing in Search Engines
Big Data Technology Map-Reduce Motivation: Indexing in Search Engines Edward Bortnikov & Ronny Lempel Yahoo Labs, Haifa Indexing in Search Engines Information Retrieval s two main stages: Indexing process
More informationDatabase 2 Lecture I. Alessandro Artale
Free University of Bolzano Database 2. Lecture I, 2003/2004 A.Artale (1) Database 2 Lecture I Alessandro Artale Faculty of Computer Science Free University of Bolzano Room: 221 artale@inf.unibz.it http://www.inf.unibz.it/
More informationSection 1.4 Place Value Systems of Numeration in Other Bases
Section.4 Place Value Systems of Numeration in Other Bases Other Bases The Hindu-Arabic system that is used in most of the world today is a positional value system with a base of ten. The simplest reason
More informationParallel Compression and Decompression of DNA Sequence Reads in FASTQ Format
, pp.91-100 http://dx.doi.org/10.14257/ijhit.2014.7.4.09 Parallel Compression and Decompression of DNA Sequence Reads in FASTQ Format Jingjing Zheng 1,* and Ting Wang 1, 2 1,* Parallel Software and Computational
More informationReading 13 : Finite State Automata and Regular Expressions
CS/Math 24: Introduction to Discrete Mathematics Fall 25 Reading 3 : Finite State Automata and Regular Expressions Instructors: Beck Hasti, Gautam Prakriya In this reading we study a mathematical model
More informationCS 464/564 Introduction to Database Management System Instructor: Abdullah Mueen
CS 464/564 Introduction to Database Management System Instructor: Abdullah Mueen LECTURE 14: DATA STORAGE AND REPRESENTATION Data Storage Memory Hierarchy Disks Fields, Records, Blocks Variable-length
More informationTransformation of LOG file using LIPT technique
Research Article International Journal of Advanced Computer Research, Vol 6(23) ISSN (Print): 2249-7277 ISSN (Online): 2277-7970 http://dx.doi.org/ 10.19101/IJACR.2016.623015 Transformation of LOG file
More informationFast Arithmetic Coding (FastAC) Implementations
Fast Arithmetic Coding (FastAC) Implementations Amir Said 1 Introduction This document describes our fast implementations of arithmetic coding, which achieve optimal compression and higher throughput by
More informationSearching BWT compressed text with the Boyer-Moore algorithm and binary search
Searching BWT compressed text with the Boyer-Moore algorithm and binary search Tim Bell 1 Matt Powell 1 Amar Mukherjee 2 Don Adjeroh 3 November 2001 Abstract: This paper explores two techniques for on-line
More informationWan Accelerators: Optimizing Network Traffic with Compression. Bartosz Agas, Marvin Germar & Christopher Tran
Wan Accelerators: Optimizing Network Traffic with Compression Bartosz Agas, Marvin Germar & Christopher Tran Introduction A WAN accelerator is an appliance that can maximize the services of a point-to-point(ptp)
More informationAn efficient matching algorithm for encoded DNA sequences and binary strings
An efficient matching algorithm for encoded DNA sequences and binary strings Simone Faro and Thierry Lecroq faro@dmi.unict.it, thierry.lecroq@univ-rouen.fr Dipartimento di Matematica e Informatica, Università
More informationInternational Journal of Advanced Research in Computer Science and Software Engineering
Volume 3, Issue 7, July 23 ISSN: 2277 28X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Greedy Algorithm:
More informationGambling and Data Compression
Gambling and Data Compression Gambling. Horse Race Definition The wealth relative S(X) = b(x)o(x) is the factor by which the gambler s wealth grows if horse X wins the race, where b(x) is the fraction
More informationThird Southern African Regional ACM Collegiate Programming Competition. Sponsored by IBM. Problem Set
Problem Set Problem 1 Red Balloon Stockbroker Grapevine Stockbrokers are known to overreact to rumours. You have been contracted to develop a method of spreading disinformation amongst the stockbrokers
More informationFormal Languages and Automata Theory - Regular Expressions and Finite Automata -
Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Samarjit Chakraborty Computer Engineering and Networks Laboratory Swiss Federal Institute of Technology (ETH) Zürich March
More informationData storage Tree indexes
Data storage Tree indexes Rasmus Pagh February 7 lecture 1 Access paths For many database queries and updates, only a small fraction of the data needs to be accessed. Extreme examples are looking or updating
More informationCSC4510 AUTOMATA 2.1 Finite Automata: Examples and D efinitions Definitions
CSC45 AUTOMATA 2. Finite Automata: Examples and Definitions Finite Automata: Examples and Definitions A finite automaton is a simple type of computer. Itsoutputislimitedto yes to or no. It has very primitive
More informationK80TTQ1EP-??,VO.L,XU0H5BY,_71ZVPKOE678_X,N2Y-8HI4VS,,6Z28DDW5N7ADY013
Hill Cipher Project K80TTQ1EP-??,VO.L,XU0H5BY,_71ZVPKOE678_X,N2Y-8HI4VS,,6Z28DDW5N7ADY013 Directions: Answer all numbered questions completely. Show non-trivial work in the space provided. Non-computational
More informationCHAPTER 5. Obfuscation is a process of converting original data into unintelligible data. It
CHAPTER 5 5.1. Introduction Obfuscation is a process of converting original data into unintelligible data. It is similar to encryption but it uses mathematical calculations or programming logics. Encryption
More informationTable of Contents DNS. How to package DNS messages. Wire? DNS on the wire. Some advanced topics. Encoding of domain names.
Table of Contents DNS Some advanced topics Karst Koymans Informatics Institute University of Amsterdam (version 154, 2015/09/14 10:44:10) Friday, September 11, 2015 DNS on the wire Encoding of domain names
More information2110711 THEORY of COMPUTATION
2110711 THEORY of COMPUTATION ATHASIT SURARERKS ELITE Athasit Surarerks ELITE Engineering Laboratory in Theoretical Enumerable System Computer Engineering, Faculty of Engineering Chulalongkorn University
More informationChapter 2: Basics on computers and digital information coding. A.A. 2012-2013 Information Technology and Arts Organizations
Chapter 2: Basics on computers and digital information coding Information Technology and Arts Organizations 1 Syllabus (1/3) 1. Introduction on Information Technologies (IT) and Cultural Heritage (CH)
More informationChapter 2: Algorithm Discovery and Design. Invitation to Computer Science, C++ Version, Third Edition
Chapter 2: Algorithm Discovery and Design Invitation to Computer Science, C++ Version, Third Edition Objectives In this chapter, you will learn about: Representing algorithms Examples of algorithmic problem
More informationNumber Representation
Number Representation CS10001: Programming & Data Structures Pallab Dasgupta Professor, Dept. of Computer Sc. & Engg., Indian Institute of Technology Kharagpur Topics to be Discussed How are numeric data
More informationLempel-Ziv Factorization: LZ77 without Window
Lempel-Ziv Factorization: LZ77 without Window Enno Ohlebusch May 13, 2016 1 Sux arrays To construct the sux array of a string S boils down to sorting all suxes of S in lexicographic order (also known as
More informationCyber Security Workshop Encryption Reference Manual
Cyber Security Workshop Encryption Reference Manual May 2015 Basic Concepts in Encoding and Encryption Binary Encoding Examples Encryption Cipher Examples 1 P a g e Encoding Concepts Binary Encoding Basics
More informationUnit 6. Loop statements
Unit 6 Loop statements Summary Repetition of statements The while statement Input loop Loop schemes The for statement The do statement Nested loops Flow control statements 6.1 Statements in Java Till now
More informationSheet 7 (Chapter 10)
King Saud University College of Computer and Information Sciences Department of Information Technology CAP240 First semester 1430/1431 Multiple-choice Questions Sheet 7 (Chapter 10) 1. Which error detection
More informationRegular Languages and Finite State Machines
Regular Languages and Finite State Machines Plan for the Day: Mathematical preliminaries - some review One application formal definition of finite automata Examples 1 Sets A set is an unordered collection
More informationIllustration 1: Diagram of program function and data flow
The contract called for creation of a random access database of plumbing shops within the near perimeter of FIU Engineering school. The database features a rating number from 1-10 to offer a guideline
More informationAutomata Theory. Şubat 2006 Tuğrul Yılmaz Ankara Üniversitesi
Automata Theory Automata theory is the study of abstract computing devices. A. M. Turing studied an abstract machine that had all the capabilities of today s computers. Turing s goal was to describe the
More informationChapter 3: Sample Questions, Problems and Solutions Bölüm 3: Örnek Sorular, Problemler ve Çözümleri
Chapter 3: Sample Questions, Problems and Solutions Bölüm 3: Örnek Sorular, Problemler ve Çözümleri Örnek Sorular (Sample Questions): What is an unacknowledged connectionless service? What is an acknowledged
More informationUnordered Linked Lists
Unordered Linked Lists Derive class unorderedlinkedlist from the abstract class linkedlisttype Implement the operations search, insertfirst, insertlast, deletenode See code on page 292 Defines an unordered
More informationCardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set.
Section 2.5 Cardinality (another) Definition: The cardinality of a set A is equal to the cardinality of a set B, denoted A = B, if and only if there is a bijection from A to B. If there is an injection
More informationFast string matching
Fast string matching This exposition is based on earlier versions of this lecture and the following sources, which are all recommended reading: Shift-And/Shift-Or 1. Flexible Pattern Matching in Strings,
More informationTCP/IP Networking, Part 2: Web-Based Control
TCP/IP Networking, Part 2: Web-Based Control Microchip TCP/IP Stack HTTP2 Module 2007 Microchip Technology Incorporated. All Rights Reserved. Building Embedded Web Applications Slide 1 Welcome to the next
More informationChapter 13: Query Processing. Basic Steps in Query Processing
Chapter 13: Query Processing! Overview! Measures of Query Cost! Selection Operation! Sorting! Join Operation! Other Operations! Evaluation of Expressions 13.1 Basic Steps in Query Processing 1. Parsing
More informationPackage RCassandra. R topics documented: February 19, 2015. Version 0.1-3 Title R/Cassandra interface
Version 0.1-3 Title R/Cassandra interface Package RCassandra February 19, 2015 Author Simon Urbanek Maintainer Simon Urbanek This packages provides
More informationOutput: 12 18 30 72 90 87. struct treenode{ int data; struct treenode *left, *right; } struct treenode *tree_ptr;
50 20 70 10 30 69 90 14 35 68 85 98 16 22 60 34 (c) Execute the algorithm shown below using the tree shown above. Show the exact output produced by the algorithm. Assume that the initial call is: prob3(root)
More information1 DNS Packet Structure
Fundamentals of Computer Networking Project 1 Primer: DNS Overview CS4700/CS5700 Fall 2009 17 September 2009 The DNS protocol is well-documented online, however, we describe the salient pieces here for
More informationPython Programming: An Introduction to Computer Science
Python Programming: An Introduction to Computer Science Sequences: Strings and Lists Python Programming, 2/e 1 Objectives To understand the string data type and how strings are represented in the computer.
More informationRegular Expressions. General Concepts About Regular Expressions
Regular Expressions This appendix explains regular expressions and how to use them in Cisco IOS software commands. It also provides details for composing regular expressions. This appendix has the following
More informationLecture 2: Regular Languages [Fa 14]
Caveat lector: This is the first edition of this lecture note. Please send bug reports and suggestions to jeffe@illinois.edu. But the Lord came down to see the city and the tower the people were building.
More informationML-Flex Implementation Notes
ML-Flex Implementation Notes Aaron Turon adrassi@uchicago.edu February 17, 2006 Contents 1 Organization 2 2 Theory 3 2.1 Regular expressions................................ 3 2.2 Derivatives.....................................
More informationCompiler Construction
Compiler Construction Regular expressions Scanning Görel Hedin Reviderad 2013 01 23.a 2013 Compiler Construction 2013 F02-1 Compiler overview source code lexical analysis tokens intermediate code generation
More informationSecurity Analysis of DRBG Using HMAC in NIST SP 800-90
Security Analysis of DRBG Using MAC in NIST SP 800-90 Shoichi irose Graduate School of Engineering, University of Fukui hrs shch@u-fukui.ac.jp Abstract. MAC DRBG is a deterministic random bit generator
More information7.1 Our Current Model
Chapter 7 The Stack In this chapter we examine what is arguably the most important abstract data type in computer science, the stack. We will see that the stack ADT and its implementation are very simple.
More informationHow to Send Video Images Through Internet
Transmitting Video Images in XML Web Service Francisco Prieto, Antonio J. Sierra, María Carrión García Departamento de Ingeniería de Sistemas y Automática Área de Ingeniería Telemática Escuela Superior
More informationSecure File Transmission using Split & Merge Technique
Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 4, Issue. 4, April 2015,
More informationData Mining Un-Compressed Images from cloud with Clustering Compression technique using Lempel-Ziv-Welch
Data Mining Un-Compressed Images from cloud with Clustering Compression technique using Lempel-Ziv-Welch 1 C. Parthasarathy 2 K.Srinivasan and 3 R.Saravanan Assistant Professor, 1,2,3 Dept. of I.T, SCSVMV
More informationBinary Trees and Huffman Encoding Binary Search Trees
Binary Trees and Huffman Encoding Binary Search Trees Computer Science E119 Harvard Extension School Fall 2012 David G. Sullivan, Ph.D. Motivation: Maintaining a Sorted Collection of Data A data dictionary
More informationWeb Services Credit Card Errors A Troubleshooter
Web Services Credit Card Errors A Troubleshooter March 2011 This manual and accompanying electronic media are proprietary products of Optimal Payments plc. They are to be used only by licensed users of
More informationCharacter Translation Methods
Supplement to: Irvine, Kip R. Assembly Language for Intel-Based Computers, 4th Edition. This file may be duplicated or printed for classroom use, as long as the author name, book title, and copyright notice
More informationITU-T V.42bis Data Dictionary Search on the StarCore SC140/SC1400 Cores
Freescale Semiconductor Application Note AN2270 Rev. 1, 11/2004 ITU-T V.42bis Data Dictionary Search on the StarCore SC140/SC1400 Cores By Emilian Medve 1 This application note presents a StarCore SC140/SC1400
More informationLecture 9. Semantic Analysis Scoping and Symbol Table
Lecture 9. Semantic Analysis Scoping and Symbol Table Wei Le 2015.10 Outline Semantic analysis Scoping The Role of Symbol Table Implementing a Symbol Table Semantic Analysis Parser builds abstract syntax
More informationDetailed Specifications
1 of 6 Appendix Detailed Specifications 1. Standards The following standards are used in the document under the following abbreviations: - BASE32, BASE64, BASE64-URL: Network Working Group: Request for
More informationData Compression Using Long Common Strings
Data Compression Using Long Common Strings Jon Bentley Bell Labs, Room 2C-514 600 Mountain Avenue Murray Hill, NJ 07974 jlb@research.bell-labs.com Douglas McIlroy Department of Computer Science Dartmouth
More informationThis section describes how LabVIEW stores data in memory for controls, indicators, wires, and other objects.
Application Note 154 LabVIEW Data Storage Introduction This Application Note describes the formats in which you can save data. This information is most useful to advanced users, such as those using shared
More informationPaynow 3rd Party Shopping Cart or Link Integration Guide
Paynow 3rd Party Shopping Cart or Link Integration Guide Version 1.0.5 15 August 2014 A guide outlining merchant integration into Paynow for externally hosted shopping carts or applications. For details
More informationPhysical Data Organization
Physical Data Organization Database design using logical model of the database - appropriate level for users to focus on - user independence from implementation details Performance - other major factor
More informationChapter 11: Input/Output Organisation. Lesson 06: Programmed IO
Chapter 11: Input/Output Organisation Lesson 06: Programmed IO Objective Understand the programmed IO mode of data transfer Learn that the program waits for the ready status by repeatedly testing the status
More informationUnified Language for Network Security Policy Implementation
Unified Language for Network Security Policy Implementation Dmitry Chernyavskiy Information Security Faculty National Research Nuclear University MEPhI Moscow, Russia milnat2004@yahoo.co.uk Natalia Miloslavskaya
More information6 3 4 9 = 6 10 + 3 10 + 4 10 + 9 10
Lesson The Binary Number System. Why Binary? The number system that you are familiar with, that you use every day, is the decimal number system, also commonly referred to as the base- system. When you
More information================================================================
==== ==== ================================================================ DR 6502 AER 201S Engineering Design 6502 Execution Simulator ================================================================
More informationInformation and Computer Science Department ICS 324 Database Systems Lab#11 SQL-Basic Query
Information and Computer Science Department ICS 324 Database Systems Lab#11 SQL-Basic Query Objectives The objective of this lab is to learn the query language of SQL. Outcomes After completing this Lab,
More informationAlgorithms for Delta Compression and Remote File Synchronization
Algorithms for Delta Compression and Remote File Synchronization Torsten Suel Nasir Memon CIS Department Polytechnic University Brooklyn, NY 11201 suel,memon @poly.edu Abstract Delta compression and remote
More informationTHE TURING DEGREES AND THEIR LACK OF LINEAR ORDER
THE TURING DEGREES AND THEIR LACK OF LINEAR ORDER JASPER DEANTONIO Abstract. This paper is a study of the Turing Degrees, which are levels of incomputability naturally arising from sets of natural numbers.
More informationzdelta: An Efficient Delta Compression Tool
zdelta: An Efficient Delta Compression Tool Dimitre Trendafilov Nasir Memon Torsten Suel Department of Computer and Information Science Technical Report TR-CIS-2002-02 6/26/2002 zdelta: An Efficient Delta
More information15.0. Percent Exceptions 10.0 5.0 0.0
WhyCOTSSoftwareIncreasesSecurityRisks GaryMcGraw ReliableSoftwareTechnologies 21515RidgetopCircle,Suite250,Sterling,VA20166 phone:(703)404-9293,fax:(703)404-9295 email:gem@rstcorp.com http://www.rstcorp.com
More informationarxiv:0810.2390v2 [cs.ds] 15 Oct 2008
Efficient Pattern Matching on Binary Strings Simone Faro 1 and Thierry Lecroq 2 arxiv:0810.2390v2 [cs.ds] 15 Oct 2008 1 Dipartimento di Matematica e Informatica, Università di Catania, Italy 2 University
More informationKey Components of WAN Optimization Controller Functionality
Key Components of WAN Optimization Controller Functionality Introduction and Goals One of the key challenges facing IT organizations relative to application and service delivery is ensuring that the applications
More informationUnderstanding 7z Compression File Format written by gordon@romvault.com
Understanding 7z Compression File Format written by gordon@romvault.com To understand the data structures used in the 7z file format you must first understand how 7z internally works. 7z has 2 concepts
More information