DOCSLIB.ORG

Yelieseva S. V. Information Technologies in Translation.Pdf

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

The Ministry of Education and Science of Ukraine Petro Mohyla Black Sea National University S. V. Yelisieieva INFORMATION TECHNOLOGIES IN TRANSLATION A STUDY GUIDE PMBSNU Publishing House Mykolaiv – 2018 S. V. Yelisieieva UDC 81' 322.2 Y 40 Рекомендовано до друку вченою радою Чорноморського національного університету імені Петра Могили (протокол № 12 від 03.07.2018). Рецензенти: Демецька В. В., д-р філол. наук, професор, декан факультету перекладознавства Херсонського державного університету; Філіпова Н. М., д-р філол. наук, професор кафедри прикладної лінгвістики Національного морського університету ім. адмірала Макарова; Кондратенко Ю. П., д-р техн. наук, професор, професор кафедри інтелектуальних інформаційних систем факультету коп’ютерних наук Чорноморського національного університету ім. Петра Могили; Бабій Ю. Б., канд. філол. наук, доцент кафедри прикла- дної лінгвістики Миколаївського національного університету ім. В. О. Сухомлинського. Y 40 Yelisieieva S. V. Information Technologies in Translation : A Study Guide / S. V. Yelisieieva. – Мykolaiv : PMBSNU Publishing House, 2018. – 176 р. ISBN 978-966-336-399-8 The basis of the training course Information Technologies in Translation lies the model of work cycle on translation, which describes the sequence of necessary actions for qualified performance and further maintenance of written translation order. At each stage, translators use the appropriate software (S/W), which simplifies the work and allows to improve the quality of the finished documentation. The course familiarizes students with all stages of the translation work cycle and with those components of the software used at each stage. Besides, this training course includes information on working with the latest multimedia technologies that are widely used nowadays for presentations of various information materials. This training course is designed primarily for those students who acquire the qualification of translator, but it can be useful for those willing to improve their knowledge in working with translation programs. UDC 81' 322.2 BBC 73 © Yelisieieva S. V., 2018 ISBN 978-966-336-399-8 © Petro Mohyla Black Sea National University, 2018 2 Information Technologies in Translation CONTENT INTRODUCTION ................................................................................... 6 I. GENERAL INFORMATION ABOUT INFORMATIONAL TECHNOLOGIES ........................................... 8 1.1. The definition of information technology ........................................... 8 1.2. Comprehension Questions .................................................................. 9 1.3. Translation, Information Technologies in translation ......................... 9 1.4. Comprehension Questions ................................................................ 10 1.5. Text translation in application programs .......................................... 11 1.6. Translation work cycle...................................................................... 11 1.7. Comprehension Questions ................................................................ 12 II. ELECTRONIC MAIL PROGRAMS ............................................. 13 2.1. Receiving translation orders by e-mail ............................................. 13 2.2. Microsoft Outlook mail program ...................................................... 14 2.3. Mail program The Bat! .................................................................... 20 2.4. Comprehension Questions ................................................................ 24 III. OPTICAL RECOGNITION .......................................................... 25 3.1. Optical Character Recognition .......................................................... 25 3.2. History of Optical Character Recognition system development ....... 25 3.3. OCR technology ............................................................................... 27 3.4. Recognition programs ....................................................................... 28 3.5. Comprehension Questions ................................................................ 31 IV. ELECTRONIC DICTIONARIES ................................................. 32 4.1. The definition of Electronic Dictionary ............................................ 32 4.2. Classification of Electronic Dictionaries by their basic technical and operational characteristics ........................................... 37 4.3. Popular Electronic Dictionaries and programs ................................. 39 4.4. Online Electronic Dictionaries .......................................................... 40 4.5. Comprehension Questions ................................................................ 40 V. MACHINE TRANSLATION .......................................................... 41 5.1. Machine Translation, history of Machine Translation ...................... 41 5.2. Forms of interaction organization between ECM and human in the process of machine translation .............................. 43 3 S. V. Yelisieieva 5.3. Machine Translation system ............................................................. 43 5.4. Algorithm of Machine Translation process ...................................... 44 5.5. Machine Translation quality ............................................................. 45 5.5.1. Improving machine translation quality ................................... .45 5.6. Comprehension Questions ................................................................ 47 5.7. General approaches to the Machine Translation ............................... 48 5.8. Parameters of Machine Translation system ...................................... 48 5.9. Advantages of Machine Translation programs ................................. 49 5.10. Statistical machine translation ........................................................ 50 5.11. Comprehension Questions .............................................................. 50 VI. COMPUTER-AIDED TRANSLATION ....................................... 51 6.1. Definition of Computer-Aided Translation....................................... 51 6.2. CAT Tools ........................................................................................ 52 6.3. Comprehension Questions ................................................................ 53 VII. TRANSLATION MEMORY ........................................................ 54 7.1. Definition of the Translation Memory .............................................. 54 7.2. Standards and formats of TM ........................................................... 54 7.3. TM popular program systems ........................................................... 56 7.3.1. Wordfast .................................................................................. 56 7.3.2. Déjà Vu ................................................................................... 59 7.4. Comprehension Questions ................................................................ 59 VIII. TRANSLATION MEMORY DATABASES .............................. 60 8.1. General information, Unicode coding standard ................................ 60 8.2. The main function of Integrated Translation Systems ...................... 60 8.3. Basic components of Integrated Translation Systems ...................... 61 8.4. TM component.................................................................................. 61 8.5. Contents of Integrated Translation Systems database ....................... 62 8.6. Modules of the main component of Commercial Integrated Systems ..... 63 8.7. Comprehension Questions ................................................................ 64 IX. LINGUISTIC SOFTWARE ........................................................... 65 9.1. Types of linguistic software .............................................................. 65 9.2. The main linguistic software ............................................................. 65 9.3. Comprehension Questions ................................................................ 80 X. LAYOUT ........................................................................................... 82 10.1. Layout, history of Layout ............................................................... 82 10.2. Layout programs ............................................................................. 82 10.3. Computer publishing system QuarkXPress .................................... 85 4 Information Technologies in Translation 10.3.1. History of QuarkXPress…………………………………..86 10.3.2. QuarkXPress program description………………………..86 10.4. Comprehension Questions .............................................................. 90 XI. MULTIMEDIA TECHNOLOGIES .............................................. 91 11.1. General information about Multimedia Technology ....................... 91 11.2. Multimedia computers, Multimedia computer equipment .............. 91 11.3. Multimedia projectors ..................................................................... 92 11.3.1. LCD-technologies of multimedia projectors Manufacturing ................................................................... 93 11.3.2. DMD/DLP-technology ....................................................... 94 11.3.3. D-ILA-technology .............................................................. 95 11.4. The classification of authorial multimedia means .......................... 96 11.5. Comprehension Questions .............................................................. 97 11.6. Presentations ..................................................................................
Recommended publications
  • Translators' Tool

    Translators' Tool

    The Translator’s Tool Box A Computer Primer for Translators by Jost Zetzsche Version 9, December 2010 Copyright © 2010 International Writers’ Group, LLC. All rights reserved. This document, or any part thereof, may not be reproduced or transmitted electronically or by any other means without the prior written permission of International Writers’ Group, LLC. ABBYY FineReader and PDF Transformer are copyrighted by ABBYY Software House. Acrobat, Acrobat Reader, Dreamweaver, FrameMaker, HomeSite, InDesign, Illustrator, PageMaker, Photoshop, and RoboHelp are registered trademarks of Adobe Systems Inc. Acrocheck is copyrighted by acrolinx GmbH. Acronis True Image is a trademark of Acronis, Inc. Across is a trademark of Nero AG. AllChars is copyrighted by Jeroen Laarhoven. ApSIC Xbench and Comparator are copyrighted by ApSIC S.L. Araxis Merge is copyrighted by Araxis Ltd. ASAP Utilities is copyrighted by eGate Internet Solutions. Authoring Memory Tool is copyrighted by Sajan. Belarc Advisor is a trademark of Belarc, Inc. Catalyst and Publisher are trademarks of Alchemy Software Development Ltd. ClipMate is a trademark of Thornsoft Development. ColourProof, ColourTagger, and QA Solution are copyrighted by Yamagata Europe. Complete Word Count is copyrighted by Shauna Kelly. CopyFlow is a trademark of North Atlantic Publishing Systems, Inc. CrossCheck is copyrighted by Global Databases, Ltd. Déjà Vu is a trademark of ATRIL Language Engineering, S.L. Docucom PDF Driver is copyrighted by Zeon Corporation. dtSearch is a trademark of dtSearch Corp. EasyCleaner is a trademark of ToniArts. ExamDiff Pro is a trademark of Prestosoft. EmEditor is copyrighted by Emura Software inc. Error Spy is copyrighted by D.O.G. GmbH. FileHippo is copyrighted by FileHippo.com.
  • OCR Pwds and Assistive Qatari Using OCR Issue No

    OCR Pwds and Assistive Qatari Using OCR Issue No

    Arabic Optical State of the Smart Character Art in Arabic Apps for Recognition OCR PWDs and Assistive Qatari using OCR Issue no. 15 Technology Research Nafath Efforts Page 04 Page 07 Page 27 Machine Learning, Deep Learning and OCR Revitalizing Technology Arabic Optical Character Recognition (OCR) Technology at Qatar National Library Overview of Arabic OCR and Related Applications www.mada.org.qa Nafath About AboutIssue 15 Content Mada Nafath3 Page Nafath aims to be a key information 04 Arabic Optical Character resource for disseminating the facts about Recognition and Assistive Mada Center is a private institution for public benefit, which latest trends and innovation in the field of Technology was founded in 2010 as an initiative that aims at promoting ICT Accessibility. It is published in English digital inclusion and building a technology-based community and Arabic languages on a quarterly basis 07 State of the Art in Arabic OCR that meets the needs of persons with functional limitations and intends to be a window of information Qatari Research Efforts (PFLs) – persons with disabilities (PWDs) and the elderly in to the world, highlighting the pioneering Qatar. Mada today is the world’s Center of Excellence in digital work done in our field to meet the growing access in Arabic. Overview of Arabic demands of ICT Accessibility and Assistive 11 OCR and Related Through strategic partnerships, the center works to Technology products and services in Qatar Applications enable the education, culture and community sectors and the Arab region. through ICT to achieve an inclusive community and educational system. The Center achieves its goals 14 Examples of Optical by building partners’ capabilities and supporting the Character Recognition Tools development and accreditation of digital platforms in accordance with international standards of digital access.
  • Certain Mobile Devices, Associated Software, and Components Thereof

    Certain Mobile Devices, Associated Software, and Components Thereof

    In the Matter of Certain Mobile Devices, Associated Software, and Components Thereof Investigation No. 337-TA-744 Publication 4384 March 2013 U.S. International Trade Commission Washington, DC 20436 U.S. International Trade Commission COMMISSIONERS Deanna Tanner Okun, Chairman Irving A. Williamson, Vice Chairman Daniel R. Pearson, Commissioner Shara L. Aranoff, Commissioner Dean A. Pinkert, Commissioner David S. Johanson, Commissioner Address all communications to Secretary to the Commission United States International Trade Commission Washington, DC 20436 U.S. International Trade Commission Washington, DC 20436 www.usitc.gov In the Matter of Certain Mobile Devices, Associated Software, and Components Thereof Investigation No. 337-TA-744 Publication 4384 March 2013 i UNITED STATES INTERNATIONAL TRADE COMMISSION Washington, D.C. In the Matter of CERTAIN MOBILE DEVICES, Investigation No. 337-TA-744 ASSOCIATED SOFTWARE, AND COMPONENTS THEREOF NOTICE OF A COMMISSION FINAL DETERMINATION OF VIOLATION OF SECTION 337; ISSUANCE OF A LIMITED EXCLUSION ORDER; TERMINATION OF INVESTIGATION AGENCY: U.S. International Trade Commission. ACTION: Notice. SUMMARY: Notice is hereby given that the U.S. International Trade Commission has determined that there is a violation of section 337 of the Tariff Act of 1930, as amended (19 U.S.C. § 1337) by respondent Motorola Mobility, Inc. of Libertyville, Illinois ("Motorola") in the above-captioned investigation. The Commission has issued a limited exclusion order directed to the infringing products of Motorola and has terminated the investigation. FOR FURTHER INFORMATION CONTACT: Michael Liberman, Esq., Office ofthe General Counsel, U.S. International Trade Commission, 500 E Street, S.W., Washington, D.C. 20436, telephone (202) 205-3115.
  • Glosar De Termeni

    Glosar De Termeni

    CUPRINS 1. Reprezentarea digitală a informaţiei……………………………………………………….8 1.1. Reducerea datelor………………………………………………………………..10 1.2. Entropia şi câştigul informaţional………………………………………………. 10 2. Identificarea şi analiza tipurilor formatelor de documente pe suport electronic……... 12 2.1. Tipuri de formate pentru documentele pe suport electronic……………………..…13 2.1.1 Formate text……………………………………………………………… 13 2.1.2 Formate imagine……………………...........……………………………....26 2.1.3 Formate audio……………………………………………………………...43 2.1.4 Formate video……………………………………………………………. 48 2.1.5. Formate multimedia.....................................................................................55 2.2. Comparaţie între formate………………………….………………………………72 3. Conţinutul web………………………………………………………………………………74 3.1. Identificarea formatelor de documente pentru conţinutul web……………………. 74 4. Conversia documentelor din format tradiţional în format electronic…………………101 4.1. Metode de digitizare……………………………………………………………..104 4.1.1 Cerinţe în procesul de digitizare……………………………………………104 4.1.2. Scanarea……………………………………………………………………104 4.1.3. Fotografiere digitală………………………………………………………105 4.1.4. Scanarea fotografiilor analogice………………………………………106 4.2. Arhitectura unui sistem de digitizare………………………………………………106 4.3. Moduri de livrare a conţinutului digital………………………………………….108 4.3.1. Text sub imagine………….……………………………………………..108 4.3.2. Text peste imagine…………………………………………….…………108 4.4. Alegerea unui format………………………………………………………………108 4.5. Tehnici de conversie prin Recunoaşterea Optică a Caracterelor (Optical Charater Recognition-OCR)……………………………………………109 4.5.1. Scurt istoric al conversiei documentelor din format tradiţional prin scanare şi OCR-izare…………………... …..109 4.5.2. Starea actuală a tehnologiei OCR……………………………………….110 4.5.3. Tehnologii curente, produse software pentru OCR-izare………………112 4.5.4. Suportul lingvistic al produselor pentru OCR-izare………………….…114 1 4.5.5. Particularităţi ale sistemelor OCR actuale………………………..……..118 5. Elaborarea unui model conceptual pentru un sistem de informare şi documentare………………………………………………………126 5.1.
  • Reconocimiento De Escritura Lecture 4/5 --- Layout Analysis

    Reconocimiento De Escritura Lecture 4/5 --- Layout Analysis

    Reconocimiento de Escritura Lecture 4/5 | Layout Analysis Daniel Keysers Jan/Feb-2008 Keysers: RES-08 1 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 2 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 3 Jan/Feb-2008 Detection of Geometric Primitives some geometric entities important for DIA: I text lines I whitespace rectangles (background in documents) Keysers: RES-08 4 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 5 Jan/Feb-2008 Hough-Transform for Line Detection Assume we are given a set of points (xn; yn) in the image plane. For all points on a line we must have yn = a0 + a1xn If we want to determine the line, each point implies a constraint yn 1 a1 = − a0 xn xn Keysers: RES-08 6 Jan/Feb-2008 Hough-Transform for Line Detection The space spanned by the model parameters a0 and a1 is called model space, parameter space, or Hough space.
  • Penpoint Operating System Overview and Application Development

    Penpoint Operating System Overview and Application Development

    PenPoint Operating System Overview and Application Development GG24-3978-00 PenPoint Operating System Overview and Application Development Document Number GG24-3978-00 February 1993 International Technical Support Center Boca Raton Take Note! --------------------------------------------------------------------------~ Before using this information and the product it supports, be sure to read the general information under "Special Notices" on page xiii. First Edition (February 1993) This edition applies to PenPoint IBM version, Release Number 1.0 of for use with the IBM 2521 ThinkPad. Order publications through your IBM representative or the IBM branch office serving your locality. Publications are not stocked at the address given below. An ITSC Technical Bulletin Evaluation Form for readers' feedback appears facing Chapter 1. If the form has been removed, comments may be addressed to: IBM Corporation, International Technical Support Center Dept. 91J, Building 235-2 Internal Zip 4423 901 NW 51 st Street Boca Raton, Florida 33431-1328 When you send information to IBM, you grant IBM a non-exclusive right to use or distribute the information in any way it believes appropriate without incurring any obligation to you. © Copyright International Business Machines Corporation 1993. All rights reserved. Note to U.S. Government Users - Documentation related to restricted rights - Use, duplication or disclosure is subject to restrictions set forth in GSA ADP Schedule Contract with IBM Corp. Abstract This document describes the architecture of the Pen Point IBM version, operating system providing sample code for application developers. The Pen Point IBM version executes on IBM ThinkPad 700T and special bid machine IBM ThinkPad 2521. This document provides an overview of the functional capabilities of the operating system and the process of application development.
  • An Accuracy Examination of OCR Tools

    An Accuracy Examination of OCR Tools

    International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-9S4, July 2019 An Accuracy Examination of OCR Tools Jayesh Majumdar, Richa Gupta texts, pen computing, developing technologies for assisting Abstract—In this research paper, the authors have aimed to do a the visually impaired, making electronic images searchable comparative study of optical character recognition using of hard copies, defeating or evaluating the robustness of different open source OCR tools. Optical character recognition CAPTCHA. (OCR) method has been used in extracting the text from images. OCR has various applications which include extracting text from any document or image or involves just for reading and processing the text available in digital form. The accuracy of OCR can be dependent on text segmentation and pre-processing algorithms. Sometimes it is difficult to retrieve text from the image because of different size, style, orientation, a complex background of image etc. From vehicle number plate the authors tried to extract vehicle number by using various OCR tools like Tesseract, GOCR, Ocrad and Tensor flow. The authors in this research paper have tried to diagnose the best possible method for optical character recognition and have provided with a comparative analysis of their accuracy. Keywords— OCR tools; Orcad; GOCR; Tensorflow; Tesseract; I. INTRODUCTION Optical character recognition is a method with which text in images of handwritten documents, scripts, passport documents, invoices, vehicle number plate, bank statements, Fig.1: Functioning of OCR [2] computerized receipts, business cards, mail, printouts of static-data, any appropriate documentation or any II. OCR PROCDURE AND PROCESSING computerized receipts, business cards, mail, printouts of To improve the probability of successful processing of an static-data, any appropriate documentation or any picture image, the input image is often ‘pre-processed’; it may be with text in it gets processed and the text in the picture is de-skewed or despeckled.
  • Introducing a Cat Tool to Translate: Wordfast

    Introducing a Cat Tool to Translate: Wordfast

    Indonesian Journal of English Language Studies Vol. 2, Number 1, February 2016 Introducing a Cat Tool to Translate: Wordfast Fika Apriliana, Ardiyarso Kurniawan, Sandy Ferianda, and Fidelis Chosa Kastuhandani ABSTRACT This article aims at introducing CAT tools to those prospective translators who are familiar with with the tools for the first time. Some of the CAT tools must be paid for while some others are free. This article is to inform the readers about the list of free and paid CAT tools, advantages and disadvantages of those tools. One does not need special training for using a free CAT tool while using the paid CAT tools, one needs some special preparation. This article is going to focus more on Wordfast Pro as the second most widely used CAT tools after SDLTrados. Wordfast Pro is a paid software the functioning of which is based on the creation of a Translation Memory which facilitates and speeds up the translator's work. This article is going to briefly explain the advantages of Wordfast Pro and the steps of using it. The translation example is presented to reveal the different translation results of Wordfast Pro as a paid CAT tool and OmegaT as a free CAT tool. Therefore, the article will facilitate those who intend to know more about Wordfast Pro and start using it. Keywords: CAT tools, Wordfast Pro, OmegaT INTRODUCTION When using CAT tools, it is Computerized translation has attracted immediately clear which parts of the text the attention of a large number of people must be translated; the unchanging who work directly or indirectly on portions are transferred accurately and translational issues such as professional directly; the time savings due to repeating translators, teachers, linguists, researchers expressions is huge; and expressions are and future translators.
  • Should I Market My Translation Or Interpreting Services on Social Media?

    Should I Market My Translation Or Interpreting Services on Social Media?

    The Voice of Interpreters and Translators THE ATA Nov/Dec 2020 Volume XLIX Number 6 SHOULD I MARKET MY TRANSLATION OR INTERPRETING SERVICES ON SOCIAL MEDIA? A Publication of the American Translators Association American Translators Association 225 Reinekers Lane, Suite 590 Alexandria, VA 22314 USA Tel: +1-703-683-6100 Fax: +1-703-683-6122 Email: [email protected] Website: www.atanet.org Editorial Board Jost Zetzsche (chair) FROM THE PRESIDENT Paula Arturo TED R. WOZNIAK Lois Feuerle [email protected] Ben Karl Barbara Inge Karsch Ted Wozniak State of the Association Publisher/Executive Director Walter Bacak, CAE 020 has certainly been a unique and spurred on and supported by ATA [email protected] challenging year for ATA, as it has members working on advocacy. 2 been for all of us. The Association, But all is not peaches and cream. ATA Editor or should I say the hundreds of volunteer continues to face financial challenges, Jeff Sanfacon members and ATA Headquarters staff, have primarily due to a very slow but steady [email protected] demonstrated a degree of resilience and decline in individual membership. We have fortitude in the face of an unprecedented seen about a 15% decline in individual Advertising global health and economic crisis of which membership since its peak in 2010. [email protected] we can all be proud. Tel: +1-703-683-6100, ext. 3007 ATA remains strong, vibrant, and ATA must continue to work Fax: +1-703-683-6122 flexible. We have adjusted to the Design & Production temporary reality and restrictions imposed on improving and expanding Blue House DC on us by the pandemic.
  • Gradu04243.Pdf

    Gradu04243.Pdf

    Paperilomakkeesta tietomalliin Kalle Malin Tampereen yliopisto Tietojenkäsittelytieteiden laitos Tietojenkäsittelyoppi Pro gradu -tutkielma Ohjaaja: Erkki Mäkinen Toukokuu 2010 i Tampereen yliopisto Tietojenkäsittelytieteiden laitos Tietojenkäsittelyoppi Kalle Malin: Paperilomakkeesta tietomalliin Pro gradu -tutkielma, 61 sivua, 3 liitesivua Toukokuu 2010 Tässä tutkimuksessa käsitellään paperilomakkeiden digitalisointiin liittyvää kokonaisprosessia yleisellä tasolla. Prosessiin tutustutaan tarkastelemalla eri osa-alueiden toimintoja ja laitteita kokonaisjärjestelmän vaatimusten näkökul- masta. Tarkastelu aloitetaan paperilomakkeiden skannaamisesta ja lopetetaan kerättyjen tietojen tallentamiseen tietomalliin. Lisäksi luodaan silmäys markki- noilla oleviin valmisratkaisuihin, jotka sisältävät prosessin kannalta oleelliset toiminnot. Avainsanat ja -sanonnat: lomake, skannaus, lomakerakenne, lomakemalli, OCR, OFR, tietomalli. ii Lyhenteet ADRT = Adaptive Document Recoginition Technology API = Application Programming Interface BAG = Block Adjacency Graph DIR = Document Image Recognition dpi= Dots Per Inch ICR = Intelligent Character Recognition IFPS = Intelligent Forms Processing System IR = Information Retrieval IRM = Image and Records Management IWR = Intelligent Word Recognition NAS = Network Attached Storage OCR = Optical Character Recognition OFR = Optical Form Recognition OHR = Optical Handwriting Recognition OMR = Optical Mark Recognition PDF = Portable Document Format SAN = Storage Area Networks SDK = Software Development Kit SLM
  • Xxxx General Blogs

    Xxxx General Blogs

    Category Technology Description Website (URL) General Blogs (e.g., Wordpress, Kirby, Tumblr) Online platforms for creating user-made content in the form of online diaries, journals, audiovisual albums, commentaries, fan sites, etc. Most can be x x x x setup to be designed collaboratively or allow comments/feedback and other forms of asynchronous interactions between users. General Course Management Software (e.g., Canvas, Course management systems are used by Blackboard, Laulima) universities for a variety of classroom purposes. They typically offer teachers the ability to post x online activities, assessments, and discussions, manage grades, and coordinate online interactions x between other students and teachers. General e-Portfolios Online or digitally created portfolios designed to display learning achievement and development. Depending on the focus, this could include x x homework assignments, draft writing, feedback (instructor, peer, or self), a vocabulary journal, or any other digital record of development over time. General Learning Management System (e.g., Course management systems (or learning Blackboard, Canvas, Laulima) management systems) are used by universities for a variety of classroom purposes. They typically offer x teachers the ability to post online activities, assessments, and discussions, manage grades, and coordinate online interactions between other x x students and teachers. General Messaging apps (E.g., Line, iMessage, Google Online messaging applications through desktop, Hangouts) web-based, and mobile platforms used to x communicate via text, audio files, images, or videos between two or more individuals asynchronously. x General Mobile dictionaries (e.g., e.g., Imiwa Mobile-based dictionary applications, many of Japanese-English Dictionary, Larousse which provide several features useful for second x French-English Dictionary) language speakers such as pronunciation cues, stroke orders, example sentences, multi-language translations, radical searches, etc.
  • Webserver WEBSER  Shell-Zugriff Via Webbrowser Debian 6.0 S

    Webserver WEBSER  Shell-Zugriff Via Webbrowser Debian 6.0 S

    COMMUNITY-EDITION Frei kopieren und beliebig weiter verteilen ! 04.2011 04.2011 APACHE-ALTERNATIVEN: WEBSITES AUFSETZEN UND PFLEGEN VER WEBSERVER WEBSER Shell-Zugriff via Webbrowser Debian 6.0 S. 6 Live- und Install-DVDs So verwalten Sie mit PHP Shell und Shell in a Box für 32- und 64-Bit-PCs den Webserver über die Kommandozeile S. 33, DVD Analyse-Tools für die Website Server-Logs grafisch aufbereiten und Benutzerzugriffe detailliert auswerten mit Webalizer und Piwik S. 38, 42, DVD Fünf Apache-Alternativen für alle Fälle S. 20, 28, DVD Profi-Server Nginx, hochsicherer Hiawatha, Allrounder Lighttpd, Minimalist Thttpd, schneller Einstieg mit Monkey HTTP Daemon MoonOS 4 S. 12 Schicke Mac-Optik für Ubuntu „Maverick“ Laptop-Schnäppchen Aspire 5253 Acers neuer 15,6-Zöller auf AMD-Fusion-Basis mit satter Grafik-Leistung und langer Laufzeit S. 80 Texterkennung in Platzfresser von Profi-Qualität S. 48, DVD der Platte putzen S. 70 Unity 2010.2 S. 8 Cuneiform: multilinguale OCR Dateileichen und Altlasten Maßgeschneiderte mit intuitiver Oberfläche aufspüren mit JDiskReport Distro auf Knopfdruck MythTV-Export Geballtes Wissen auf Knopfdruck S. 66 stets zur Hand S. 82, DVD Aufnahmen unkompliziert Goldendict vereint On- und wandeln, streamen, brennen Offline-Lexika in einer GUI ATI FIREPRO 3D • GOLDENDICT LOUT LUCIDOR MYTHTV OCR ATI 4 196067 008502 04 www.linux-user.de EDITORIAL Klare Ansage Sehr geehrte Leserinnen und Leser, im Vorfeld von Ubuntu 11.04 Wohlgemerkt: Die MIT-Lizenz des statt Lizenzgebühren zu verlan- sorgte Canonical immer wieder für Banshee-Projekts hätte jegliche gen. Diesem Geschäftsmodell fol- Schlagzeilen – zuletzt im Zusam- Änderungen auch ganz ohne Nach- gend, werde man grundsätzlich wo menhang mit der Ablösung des frage erlaubt, formaljuristisch war immer möglich aus der Software bisherigen Mediaplayers Rhythm- Canonicals Ansinnen völlig in der freien Upstream-Projekte Ge- box durch Banshee: Der nämlich Ordnung.