Tailoring Collation to Users and Languages Markus Scherer (Google)
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Sort Algorithms 15-110 - Friday 2/28 Learning Objectives
Sort Algorithms 15-110 - Friday 2/28 Learning Objectives • Recognize how different sorting algorithms implement the same process with different algorithms • Recognize the general algorithm and trace code for three algorithms: selection sort, insertion sort, and merge sort • Compute the Big-O runtimes of selection sort, insertion sort, and merge sort 2 Search Algorithms Benefit from Sorting We use search algorithms a lot in computer science. Just think of how many times a day you use Google, or search for a file on your computer. We've determined that search algorithms work better when the items they search over are sorted. Can we write an algorithm to sort items efficiently? Note: Python already has built-in sorting functions (sorted(lst) is non-destructive, lst.sort() is destructive). This lecture is about a few different algorithmic approaches for sorting. 3 Many Ways of Sorting There are a ton of algorithms that we can use to sort a list. We'll use https://visualgo.net/bn/sorting to visualize some of these algorithms. Today, we'll specifically discuss three different sorting algorithms: selection sort, insertion sort, and merge sort. All three do the same action (sorting), but use different algorithms to accomplish it. 4 Selection Sort 5 Selection Sort Sorts From Smallest to Largest The core idea of selection sort is that you sort from smallest to largest. 1. Start with none of the list sorted 2. Repeat the following steps until the whole list is sorted: a) Search the unsorted part of the list to find the smallest element b) Swap the found element with the first unsorted element c) Increment the size of the 'sorted' part of the list by one Note: for selection sort, swapping the element currently in the front position with the smallest element is faster than sliding all of the numbers down in the list. -
PROC SORT (Then And) NOW Derek Morgan, PAREXEL International
Paper 143-2019 PROC SORT (then and) NOW Derek Morgan, PAREXEL International ABSTRACT The SORT procedure has been an integral part of SAS® since its creation. The sort-in-place paradigm made the most of the limited resources at the time, and almost every SAS program had at least one PROC SORT in it. The biggest options at the time were to use something other than the IBM procedure SYNCSORT as the sorting algorithm, or whether you were sorting ASCII data versus EBCDIC data. These days, PROC SORT has fallen out of favor; after all, PROC SQL enables merging without using PROC SORT first, while the performance advantages of HASH sorting cannot be overstated. This leads to the question: Is the SORT procedure still relevant to any other than the SAS novice or the terminally stubborn who refuse to HASH? The answer is a surprisingly clear “yes". PROC SORT has been enhanced to accommodate twenty-first century needs, and this paper discusses those enhancements. INTRODUCTION The largest enhancement to the SORT procedure is the addition of collating sequence options. This is first and foremost recognition that SAS is an international software package, and SAS users no longer work exclusively with English-language data. This capability is part of National Language Support (NLS) and doesn’t require any additional modules. You may use standard collations, SAS-provided translation tables, custom translation tables, standard encodings, or rules to produce your sorted dataset. However, you may only use one collation method at a time. USING STANDARD COLLATIONS, TRANSLATION TABLES AND ENCODINGS A long time ago, SAS would allow you to sort data using ASCII rules on an EBCDIC system, and vice versa. -
Overview of Sorting Algorithms
Unit 7 Sorting Algorithms Simple Sorting algorithms Quicksort Improving Quicksort Overview of Sorting Algorithms Given a collection of items we want to arrange them in an increasing or decreasing order. You probably have seen a number of sorting algorithms including ¾ selection sort ¾ insertion sort ¾ bubble sort ¾ quicksort ¾ tree sort using BST's In terms of efficiency: ¾ average complexity of the first three is O(n2) ¾ average complexity of quicksort and tree sort is O(n lg n) ¾ but its worst case is still O(n2) which is not acceptable In this section, we ¾ review insertion, selection and bubble sort ¾ discuss quicksort and its average/worst case analysis ¾ show how to eliminate tail recursion ¾ present another sorting algorithm called heapsort Unit 7- Sorting Algorithms 2 Selection Sort Assume that data ¾ are integers ¾ are stored in an array, from 0 to size-1 ¾ sorting is in ascending order Algorithm for i=0 to size-1 do x = location with smallest value in locations i to size-1 swap data[i] and data[x] end Complexity If array has n items, i-th step will perform n-i operations First step performs n operations second step does n-1 operations ... last step performs 1 operatio. Total cost : n + (n-1) +(n-2) + ... + 2 + 1 = n*(n+1)/2 . Algorithm is O(n2). Unit 7- Sorting Algorithms 3 Insertion Sort Algorithm for i = 0 to size-1 do temp = data[i] x = first location from 0 to i with a value greater or equal to temp shift all values from x to i-1 one location forwards data[x] = temp end Complexity Interesting operations: comparison and shift i-th step performs i comparison and shift operations Total cost : 1 + 2 + .. -
Computer Science II
Computer Science II Dr. Chris Bourke Department of Computer Science & Engineering University of Nebraska|Lincoln Lincoln, NE 68588, USA http://chrisbourke.unl.edu [email protected] 2019/08/15 13:02:17 Version 0.2.0 This book is a draft covering Computer Science II topics as presented in CSCE 156 (Computer Science II) at the University of Nebraska|Lincoln. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License i Contents 1 Introduction1 2 Object Oriented Programming3 2.1 Introduction.................................... 3 2.2 Objects....................................... 4 2.3 The Four Pillars.................................. 4 2.3.1 Abstraction................................. 4 2.3.2 Encapsulation................................ 4 2.3.3 Inheritance ................................. 4 2.3.4 Polymorphism................................ 4 2.4 SOLID Principles................................. 4 2.4.1 Inversion of Control............................. 4 3 Relational Databases5 3.1 Introduction.................................... 5 3.2 Tables ....................................... 9 3.2.1 Creating Tables...............................10 3.2.2 Primary Keys................................16 3.2.3 Foreign Keys & Relating Tables......................18 3.2.4 Many-To-Many Relations .........................22 3.2.5 Other Keys .................................24 3.3 Structured Query Language ...........................26 3.3.1 Creating Data................................28 3.3.2 Retrieving Data...............................30 -
Automatic Labeling of Voiced Consonants for Morphological Analysis of Modern Japanese Literature
Automatic Labeling of Voiced Consonants for Morphological Analysis of Modern Japanese Literature Teruaki Oka† Mamoru Komachi† [email protected] [email protected] Toshinobu Ogiso‡ Yuji Matsumoto† [email protected] [email protected] Nara Institute of Science and Technology National† Institute for Japanese Language and Linguistics ‡ Abstract literary text,2 which achieves high performance on analysis for existing electronic text (e.g. Aozora- Since the present-day Japanese use of bunko, an online digital library of freely available voiced consonant mark had established books and work mainly from out-of-copyright ma- in the Meiji Era, modern Japanese lit- terials). erary text written in the Meiji Era of- However, the performance of morphological an- ten lacks compulsory voiced consonant alyzers using the dictionary deteriorates if the text marks. This deteriorates the performance is not normalized, because these dictionaries often of morphological analyzers using ordi- lack orthographic variations such as Okuri-gana,3 nary dictionary. In this paper, we pro- accompanying characters following Kanji stems pose an approach for automatic labeling of in Japanese written words. This is problematic voiced consonant marks for modern liter- because not all historical texts are manually cor- ary Japanese. We formulate the task into a rected with orthography, and it is time-consuming binary classification problem. Our point- to annotate by hand. It is one of the major issues wise prediction method uses as its feature in applying NLP tools to Japanese Linguistics be- set only surface information about the sur- cause ancient materials often contain a wide vari- rounding character strings. -
Unicode Collators
Title stata.com unicode collator — Language-specific Unicode collators Description Syntax Remarks and examples Also see Description unicode collator list lists the subset of locales that have language-specific collators for the Unicode string comparison functions: ustrcompare(), ustrcompareex(), ustrsortkey(), and ustrsortkeyex(). Syntax unicode collator list pattern pattern is one of all, *, *name*, *name, or name*. If you specify nothing, all, or *, then all results will be listed. *name* lists all results containing name; *name lists all results ending with name; and name* lists all results starting with name. Remarks and examples stata.com Remarks are presented under the following headings: Overview of collation The role of locales in collation Further controlling collation Overview of collation Collation is the process of comparing and sorting Unicode character strings as a human might logically order them. We call this ordering strings in a language-sensitive manner. To do this, Stata uses a Unicode tool known as the Unicode collation algorithm, or UCA. To perform language-sensitive string sorts, you must combine ustrsortkey() or ustr- sortkeyex() with sort. It is a complicated process and there are several issues about which you need to be aware. For details, see [U] 12.4.2.5 Sorting strings containing Unicode characters. To perform language-sensitive string comparisons, you can use ustrcompare() or ustrcompareex(). For details about the UCA, see http://www.unicode.org/reports/tr10/. The role of locales in collation During collation, Stata can use the default collator or it can perform language-sensitive string comparisons or sorts that require knowledge of a locale. A locale identifies a community with a certain set of preferences for how their language should be written; see [U] 12.4.2.4 Locales in Unicode. -
Braille Decoding Device Employing Microcontroller
International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8, Issue-2S11, September 2019 Braille Decoding Device Employing Microcontroller Kanika Jindal, Adittee Mattoo, Bhupendra Kumar Abstract—The Braille decoding method has been The proposed circuit has primary objective to recognize conventionally used by the visually challenged persons to read Braille character inputs from a visually challenged user and books etc. The designed system in the current paper has transmit them to another similar Braille device. This system implemented a method to interface the Braille characters and has been embedded onto a glove that can be worn by the blind English text characters. The system will help to communicate the Braille message from one visually challenged person to another as person. The first four fingers of the glove, starting from the well as help us to transform the Braille language to English text thumb will fitted with tactile micro switches and a vibration through a microcontroller and a PC in order to communicate with motor. This circuit is then connected with a microcontroller the visually challenged persons and PC via RS232C cable to interface the Braille words with the PC based text language. The switch pressed by any person Keyword: Universal synchronous/Asynchronous will create a Braille code that should be converted to ASCII receiver/transmitter, braille, PWM, Vibration Motor, Transistor, form by ASCII conversion program for microcontroller and Diode. these letters will be seen on computer screen. This is used in I. INTRODUCTION order to make the characters USART compatible. Similarly, the computer text word will be reverse programmed into Braille mechanism was founded by Louis Braille in 1821. -
Program Details
Home Program Hotel Be an Exhibitor Be a Sponsor Review Committee Press Room Past Events Contact Us Program Details Monday, November 3, 2014 08:30-10:00 MORNING TUTORIALS Track 1: An Introduction to Writing Systems & Unicode Presenter: This tutorial will provide you with a good understanding of the many unique characteristics of non-Latin Richard Ishida writing systems, and illustrate the problems involved in implementing such scripts in products. It does not Internationalization provide detailed coding advice, but does provide the essential background information you need to Activity Lead, W3C understand the fundamental issues related to Unicode deployment, across a wide range of scripts. It has proved to be an excellent orientation for newcomers to the conference, providing the background needed to assist understanding of the other talks! The tutorial goes beyond encoding issues to discuss characteristics related to input of ideographs, combining characters, context-dependent shape variation, text direction, vowel signs, ligatures, punctuation, wrapping and editing, font issues, sorting and indexing, keyboards, and more. The concepts are introduced through the use of examples from Chinese, Japanese, Korean, Arabic, Hebrew, Thai, Hindi/Tamil, Russian and Greek. While the tutorial is perfectly accessible to beginners, it has also attracted very good reviews from people at an intermediate and advanced level, due to the breadth of scripts discussed. No prior knowledge is needed. Presenters: Track 2: Localization Workshop Daniel Goldschmidt Two highly experienced industry experts will illuminate the basics of localization for session participants Sr. International over the course of three one-hour blocks. This instruction is particularly oriented to participants who are Program Manager, new to localization. -
MSDB Foundation Provides Digital Braille Access Family Learning Weekends Have Become a Successful Tradition
MONTANA SCHOOL for the DEAF & BLIND ExpressVolume XIII, Issue 3, Summer 2015 giving kids the building blocks to independence MSDB Foundation Provides Digital Braille Access PAGES 8-9 Family Learning Weekends Have Become a Successful Tradition PAGE 16 Russian Peer to Peer Exchange By Pam Boespflug, Outreach Consultant n late April the MSDB family had an opportunity to host a group of staff and students from the Lipetsk school for the Blind in Russia. Four adults and five students arrived in Great Falls, where they observed MSDB classes and toured local sites for a week. I In exchange, an MSDB contingent traveled to Russia the following month. Superintendent Donna Sorensen, Outreach Supervisor and instigator of this awesome project Carol Clayton-Bye, teacher Diane Blake, student Seri Brammer, and I left for Russia on May 11. We flew into Moscow and were met by the Lipetsk School van and staff. We had plenty of time to visit on our 6 hour drive with our English teacher/ Interpreter Oksana and our host Svetlana, whom Carol had worked with for three years. We were introduced to our host families that evening and arrived the next morning at school to a jazz band serenade and the traditional bread and salt ceremony. The week in Lipetsk went fast as we visited many classes at the school of over Left to right: Donna Sorensen, Igor Batishcheva, Carol 500 students including those in distance education. Clayton-Bye, Pam Boespflug, Seri Brammer, Diana Blake, We also toured the local city, statues and cathedrals, and Svetlana Veretennikova. We are standing in front of a museums, a zoo, summer camps, and got to know our fountain for preserving eyesight just outside of Lipetsk. -
5892 Cisco Category: Standards Track August 2010 ISSN: 2070-1721
Internet Engineering Task Force (IETF) P. Faltstrom, Ed. Request for Comments: 5892 Cisco Category: Standards Track August 2010 ISSN: 2070-1721 The Unicode Code Points and Internationalized Domain Names for Applications (IDNA) Abstract This document specifies rules for deciding whether a code point, considered in isolation or in context, is a candidate for inclusion in an Internationalized Domain Name (IDN). It is part of the specification of Internationalizing Domain Names in Applications 2008 (IDNA2008). Status of This Memo This is an Internet Standards Track document. This document is a product of the Internet Engineering Task Force (IETF). It represents the consensus of the IETF community. It has received public review and has been approved for publication by the Internet Engineering Steering Group (IESG). Further information on Internet Standards is available in Section 2 of RFC 5741. Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at http://www.rfc-editor.org/info/rfc5892. Copyright Notice Copyright (c) 2010 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License. -
Mysql Globalization Abstract
MySQL Globalization Abstract This is the MySQL Globalization extract from the MySQL 5.6 Reference Manual. For legal information, see the Legal Notices. For help with using MySQL, please visit the MySQL Forums, where you can discuss your issues with other MySQL users. Document generated on: 2021-09-23 (revision: 70881) Table of Contents Preface and Legal Notices .................................................................................................................. v 1 Character Sets, Collations, Unicode ................................................................................................. 1 1.1 Character Sets and Collations in General .............................................................................. 2 1.2 Character Sets and Collations in MySQL ............................................................................... 3 1.2.1 Character Set Repertoire ........................................................................................... 5 1.2.2 UTF-8 for Metadata ................................................................................................... 6 1.3 Specifying Character Sets and Collations .............................................................................. 8 1.3.1 Collation Naming Conventions .................................................................................... 8 1.3.2 Server Character Set and Collation ............................................................................ 9 1.3.3 Database Character Set and Collation ..................................................................... -
Quick Sort Algorithm Song Qin Dept
Quick Sort Algorithm Song Qin Dept. of Computer Sciences Florida Institute of Technology Melbourne, FL 32901 ABSTRACT each iteration. Repeat this on the rest of the unsorted region Given an array with n elements, we want to rearrange them in without the first element. ascending order. In this paper, we introduce Quick Sort, a Bubble sort works as follows: keep passing through the list, divide-and-conquer algorithm to sort an N element array. We exchanging adjacent element, if the list is out of order; when no evaluate the O(NlogN) time complexity in best case and O(N2) exchanges are required on some pass, the list is sorted. in worst case theoretically. We also introduce a way to approach the best case. Merge sort [4] has a O(NlogN) time complexity. It divides the 1. INTRODUCTION array into two subarrays each with N/2 items. Conquer each Search engine relies on sorting algorithm very much. When you subarray by sorting it. Unless the array is sufficiently small(one search some key word online, the feedback information is element left), use recursion to do this. Combine the solutions to brought to you sorted by the importance of the web page. the subarrays by merging them into single sorted array. 2 Bubble, Selection and Insertion Sort, they all have an O(N2) time In Bubble sort, Selection sort and Insertion sort, the O(N ) time complexity that limits its usefulness to small number of element complexity limits the performance when N gets very big. no more than a few thousand data points.