Notes – Unit 2
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
500 Natural Sciences and Mathematics
500 500 Natural sciences and mathematics Natural sciences: sciences that deal with matter and energy, or with objects and processes observable in nature Class here interdisciplinary works on natural and applied sciences Class natural history in 508. Class scientific principles of a subject with the subject, plus notation 01 from Table 1, e.g., scientific principles of photography 770.1 For government policy on science, see 338.9; for applied sciences, see 600 See Manual at 231.7 vs. 213, 500, 576.8; also at 338.9 vs. 352.7, 500; also at 500 vs. 001 SUMMARY 500.2–.8 [Physical sciences, space sciences, groups of people] 501–509 Standard subdivisions and natural history 510 Mathematics 520 Astronomy and allied sciences 530 Physics 540 Chemistry and allied sciences 550 Earth sciences 560 Paleontology 570 Biology 580 Plants 590 Animals .2 Physical sciences For astronomy and allied sciences, see 520; for physics, see 530; for chemistry and allied sciences, see 540; for earth sciences, see 550 .5 Space sciences For astronomy, see 520; for earth sciences in other worlds, see 550. For space sciences aspects of a specific subject, see the subject, plus notation 091 from Table 1, e.g., chemical reactions in space 541.390919 See Manual at 520 vs. 500.5, 523.1, 530.1, 919.9 .8 Groups of people Add to base number 500.8 the numbers following —08 in notation 081–089 from Table 1, e.g., women in science 500.82 501 Philosophy and theory Class scientific method as a general research technique in 001.4; class scientific method applied in the natural sciences in 507.2 502 Miscellany 577 502 Dewey Decimal Classification 502 .8 Auxiliary techniques and procedures; apparatus, equipment, materials Including microscopy; microscopes; interdisciplinary works on microscopy Class stereology with compound microscopes, stereology with electron microscopes in 502; class interdisciplinary works on photomicrography in 778.3 For manufacture of microscopes, see 681. -
A New Rule-Based Method of Automatic Phonetic Notation On
A New Rule-based Method of Automatic Phonetic Notation on Polyphones ZHENG Min, CAI Lianhong (Department of Computer Science and Technology of Tsinghua University, Beijing, 100084) Email: [email protected], [email protected] Abstract: In this paper, a new rule-based method of automatic 2. A rule-based method on polyphones phonetic notation on the 220 polyphones whose appearing frequency exceeds 99% is proposed. Firstly, all the polyphones 2.1 Classify the polyphones beforehand in a sentence are classified beforehand. Secondly, rules are Although the number of polyphones is large, the extracted based on eight features. Lastly, automatic phonetic appearing frequency is widely discrepant. The statistic notation is applied according to the rules. The paper puts forward results in our experiment show: the accumulative a new concept of prosodic functional part of speech in order to frequency of the former 100 polyphones exceeds 93%, improve the numerous and complicated grammatical information. and the accumulative frequency of the former 180 The examples and results of this method are shown at the end of polyphones exceeds 97%. The distributing chart of this paper. Compared with other approaches dealt with polyphones’ accumulative frequency is shown in the polyphones, the results show that this new method improves the chart 3.1. In order to improve the accuracy of the accuracy of phonetic notation on polyphones. grapheme-phoneme conversion more, we classify the Keyword: grapheme-phoneme conversion; polyphone; prosodic 700 polyphones in the GB_2312 Chinese-character word; prosodic functional part of speech; feature extracting; system into three kinds in our text-to-speech system 1. -
Management of Data Elements in Information Processing
PB-249-530 MANAGEMENT OF DATA ELEMENTS IN INFORMATION PROCESSING U.S. DEPARTMENT OF COMMERCE / National Bureau of Standards SECOND NATIONAL SYMPOSIUM NATIONAL BUREAU OF STANDARDS GAITHERSBURG, MARYLAND 1975 OCTOBER 23-24 Available by purchase from the National Technical Information Service, 5285 Port Royal Road, Springfield, Va. 221 Price: $9.25 hardcopy; $2.25 microfiche. National Technical Information Service U. S. DEPARTMENT OF COMMERCE PB-249-530 Management of Data Elements in Information Processing Proceedings of a Second Symposium Sponsored by the American National Standards Institute and by The National Bureau of Standards 1975 October 23-24 NBS, Gaithersburg, Maryland Hazel E. McEwen, Editor Institute for Computer Sciences and Technology National Bureau of Standards Washington, D.C. 20234 U.S. DEPARTMENT OF COMMERCE, Elliot L. Richardson, Secrefary NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Acfing Direc/or Table of Contents Page Introduction to the Program of the Second National Symposium on The Management of Data Elements in Information Processing ix David V. Savidge, Program Chairman On-Line Tactical Data Inputting: Research in Operator Training and Performance 1 Irving Alderman, Ph.D. "Turning the Corner" on MIS, A Proposed Program of Data Standards in Post-Secondary Education 9 Donald R. Arnold, Ph.D. ASCII - The Data Alphabet That Will Endure 17 Robert W. Bemer Techniques in Developing Standard Procedures for Data Editing 23 George W. Covill An Adaptive File Management Systems 45 Dennis L. Dance and Udo W. Pooch (Given by Dance) A Focus on the Role of the Data Manager 57 Ruth M, Davis, Ph.D. A Proposed Standard Routine for Generating Proposed Standard Check Characters 61 Paul -Andre Desjardins Methodology for Development of Standard Data Elements within Multiple Public Agencies 69 L. -
The Romantext Format: a Flexible and Standard Method for Representing Roman Numeral Analyses
THE ROMANTEXT FORMAT: A FLEXIBLE AND STANDARD METHOD FOR REPRESENTING ROMAN NUMERAL ANALYSES Dmitri Tymoczko1 Mark Gotham2 Michael Scott Cuthbert3 Christopher Ariza4 1 Princeton University, NJ 2 Cornell University, NY 3 M.I.T., MA 4 Independent [email protected], [email protected], [email protected] ABSTRACT Absolute chord labels are performer-oriented in the sense that they specify which notes should be played, but Roman numeral analysis has been central to the West- do not provide any information about their function or ern musician’s toolkit since its emergence in the early meaning: thus one and the same symbol can represent nineteenth century: it is an extremely popular method for a tonic, dominant, or subdominant chord. Accordingly, recording subjective analytical decisions about the chords these labels obscure a good deal of musical structure: a and keys implied by a passage of music. Disagreements dominant-functioned G major chord (i.e. G major in the about these judgments have led to extensive theoretical de- local key of C) is considerably more likely to descend by bates and ongoing controversies. Such debates are exac- perfect fifth than a subdominant-functioned G major (i.e. G erbated by the absence of a public corpus of expert Ro- major in the key of D major). This sort of contextual in- man numeral analyses, and by the more fundamental lack formation is readily available to both trained and untrained of an agreed-upon, computer-readable syntax in which listeners, who are typically more sensitive to relative scale those analyses might be expressed. This paper specifies degrees than absolute pitches. -
Figured-Bass Notation
MU 182: Theory II R. Vigil FIGURED-BASS NOTATION General In common-practice tonal music, chords are generally understood in two different ways. On the one hand, they can be seen as triadic structures emanating from a generative root . In this system, a root-position triad is understood as the "ideal" or "original" form, and other forms are understood as inversions , where the root has been placed above one of the other chord tones. This approach emphasizes the structural similarity of chords that share a common root (a first- inversion C major triad and a root-position C major triad are both C major triads). This type of thinking is represented analytically in the practice of applying Roman numerals to various chords within a given key - all chords with allegiance to the same Roman numeral are understood to be related, regardless of inversion and voicing, texture, etc. On the other hand, chords can be understood as vertical arrangements of tones above a given bass . This system is not based on a judgment as to the primacy of any particular chordal arrangement over another. Rather, it is simply a descriptive mechanism, for identifying what notes are present in addition to the bass. In this regime, chords are described in terms of the simplest possible arrangement of those notes as intervals above the bass. The intervals are represented as Arabic numerals (figures), and the resulting nomenclatural system is known as figured bass . Terminological Distinctions Between Roman Numeral Versus Figured Bass Approaches When dealing with Roman numerals, everything is understood in relation to the root; therefore, the components of a triad are the root, the third, and the fifth. -
H/W3 Binary to Denary
Name ___________________________________ Form ________ H/W Year 8 Homework Booklet Theme 1 Data Representation Computers themselves, and “ software yet to be developed, will revolutionize “ the way we learn. - Steve Jobs Founder of Apple Introduction What language does a computer understand? How does a computer represent data, information and images? Soon, you will be able to answer the questions above! In this theme we will explore the different ways in which data is represented by the computer, ranging from numbers to images. We will learn and understand the number bases and conversions between denary and binary. We will also be looking at units of information, binary addition and how we can convert binary data into a black and white image! See the key below to find out what the icons below mean: Self Assessment: You will mark your work at the start of next lesson. ENSURE YOU COMPELTE HOMEWORK AS MARKS WILL BE COLLECTED IN! Edmodo Quiz: The will be a quiz the start of next lesson based on your homework. SO MAKE SURE YOU REVISE! Peer Assessment: Homework marked by your class mate at the start of next lesson. MAKE SURE YOU HAVE YOUR HOMEWORK DONE SO YOU CAN SWAP WITH ANOTHER PUPIL! Stuck? Got a question? Email your teacher. Mr Rifai (Head of Computing) [email protected] Miss Davison [email protected] Miss Pascoe [email protected] 2 Due Date: H/W1 Data & Number Bases Read and digest the information below. You will be quizzed next lesson! Any set of characters gathered and translated for What is Data? some purpose. -
Notation Guide for Precalculus and Calculus Students
Notation Guide for Precalculus and Calculus Students Sean Raleigh Last modified: August 27, 2007 Contents 1 Introduction 5 2 Expression versus equation 7 3 Handwritten math versus typed math 9 3.1 Numerals . 9 3.2 Letters . 10 4 Use of calculators 11 5 General organizational principles 15 5.1 Legibility of work . 15 5.2 Flow of work . 16 5.3 Using English . 18 6 Precalculus 21 6.1 Multiplication and division . 21 6.2 Fractions . 23 6.3 Functions and variables . 27 6.4 Roots . 29 6.5 Exponents . 30 6.6 Inequalities . 32 6.7 Trigonometry . 35 6.8 Logarithms . 38 6.9 Inverse functions . 40 6.10 Order of functions . 42 7 Simplification of answers 43 7.1 Redundant notation . 44 7.2 Factoring and expanding . 45 7.3 Basic algebra . 46 7.4 Domain matching . 47 7.5 Using identities . 50 7.6 Log functions and exponential functions . 51 7.7 Trig functions and inverse trig functions . 53 1 8 Limits 55 8.1 Limit notation . 55 8.2 Infinite limits . 57 9 Derivatives 59 9.1 Derivative notation . 59 9.1.1 Lagrange’s notation . 59 9.1.2 Leibniz’s notation . 60 9.1.3 Euler’s notation . 62 9.1.4 Newton’s notation . 63 9.1.5 Other notation issues . 63 9.2 Chain rule . 65 10 Integrals 67 10.1 Integral notation . 67 10.2 Definite integrals . 69 10.3 Indefinite integrals . 71 10.4 Integration by substitution . 72 10.5 Improper integrals . 77 11 Sequences and series 79 11.1 Sequences . -
Grapheme-To-Phoneme Models for (Almost) Any Language
Grapheme-to-Phoneme Models for (Almost) Any Language Aliya Deri and Kevin Knight Information Sciences Institute Department of Computer Science University of Southern California {aderi, knight}@isi.edu Abstract lang word pronunciation eng anybody e̞ n iː b ɒ d iː Grapheme-to-phoneme (g2p) models are pol żołądka z̻owon̪t̪ka rarely available in low-resource languages, ben শ嗍 s̪ ɔ k t̪ ɔ as the creation of training and evaluation ʁ a l o m o t חלומות heb data is expensive and time-consuming. We use Wiktionary to obtain more than 650k Table 1: Examples of English, Polish, Bengali, word-pronunciation pairs in more than 500 and Hebrew pronunciation dictionary entries, with languages. We then develop phoneme and pronunciations represented with the International language distance metrics based on phono- Phonetic Alphabet (IPA). logical and linguistic knowledge; apply- ing those, we adapt g2p models for high- word eng deu nld resource languages to create models for gift ɡ ɪ f tʰ ɡ ɪ f t ɣ ɪ f t related low-resource languages. We pro- class kʰ l æ s k l aː s k l ɑ s vide results for models for 229 adapted lan- send s e̞ n d z ɛ n t s ɛ n t guages. Table 2: Example pronunciations of English words 1 Introduction using English, German, and Dutch g2p models. Grapheme-to-phoneme (g2p) models convert words into pronunciations, and are ubiquitous in For most of the world’s more than 7,100 lan- speech- and text-processing systems. Due to the guages (Lewis et al., 2009), no data exists and the diversity of scripts, phoneme inventories, phono- many technologies enabled by g2p models are in- tactic constraints, and spelling conventions among accessible. -
Style and Notation Guide
Physical Review Style and Notation Guide Instructions for correct notation and style in preparation of REVTEX compuscripts and conventional manuscripts Published by The American Physical Society First Edition July 1983 Revised February 1993 Compiled and edited by Minor Revision June 2005 Anne Waldron, Peggy Judd, and Valerie Miller Minor Revision June 2011 Copyright 1993, by The American Physical Society Permission is granted to quote from this journal with the customary acknowledgment of the source. To reprint a figure, table or other excerpt requires, in addition, the consent of one of the original authors and notification of APS. No copying fee is required when copies of articles are made for educational or research purposes by individuals or libraries (including those at government and industrial institutions). Republication or reproduction for sale of articles or abstracts in this journal is permitted only under license from APS; in addition, APS may require that permission also be obtained from one of the authors. Address inquiries to the APS Administrative Editor (Editorial Office, 1 Research Rd., Box 1000, Ridge, NY 11961). Physical Review Style and Notation Guide Anne Waldron, Peggy Judd, and Valerie Miller (Received: ) Contents I. INTRODUCTION 2 II. STYLE INSTRUCTIONS FOR PARTS OF A MANUSCRIPT 2 A. Title ..................................................... 2 B. Author(s) name(s) . 2 C. Author(s) affiliation(s) . 2 D. Receipt date . 2 E. Abstract . 2 F. Physics and Astronomy Classification Scheme (PACS) indexing codes . 2 G. Main body of the paper|sequential organization . 2 1. Types of headings and section-head numbers . 3 2. Reference, figure, and table numbering . 3 3. -
Scientific Notations for the Digital
Scientific notations for the digital era Konrad Hinsen Centre de Biophysique Moléculaire (UPR4301 CNRS) Rue Charles Sadron, 45071 Orléans Cédex 2, France [email protected] Synchrotron SOLEIL, Division Expériences B.P. 48, 91192 Gif sur Yvette, France Abstract Computers have profoundly changed the way scientific research is done. Whereas the importance of computers as research tools is evident to every- one, the impact of the digital revolution on the representation of scientific knowledge is not yet widely recognized. An ever increasing part of today’s scientific knowledge is expressed, published, and archived exclusively in the form of software and electronic datasets. In this essay, I compare these digital scientific notations to the the traditional scientific notations that have been used for centuries, showing how the digital notations optimized for computerized processing are often an obstacle to scientific communi- cation and to creative work by human scientists. I analyze the causes and propose guidelines for the design of more human-friendly digital scientific notations. Note: This article is also available in the Self-Journal of Science, where it is open for public discussion and review. 1 Introduction arXiv:1605.02960v1 [physics.soc-ph] 10 May 2016 Today’s computing culture is focused on results. Computers and software are seen primarily as tools that get a job done. They are judged by the utility of the results they produce, by the resources (mainly time and energy) they consume, and by the effort required for their construction and maintenance. In fact, we have the same utilitarian attitude towards computers and software as towards other technical artifacts such as refrigerators or airplanes. -
List of Mathematical Symbols by Subject from Wikipedia, the Free Encyclopedia
List of mathematical symbols by subject From Wikipedia, the free encyclopedia This list of mathematical symbols by subject shows a selection of the most common symbols that are used in modern mathematical notation within formulas, grouped by mathematical topic. As it is virtually impossible to list all the symbols ever used in mathematics, only those symbols which occur often in mathematics or mathematics education are included. Many of the characters are standardized, for example in DIN 1302 General mathematical symbols or DIN EN ISO 80000-2 Quantities and units – Part 2: Mathematical signs for science and technology. The following list is largely limited to non-alphanumeric characters. It is divided by areas of mathematics and grouped within sub-regions. Some symbols have a different meaning depending on the context and appear accordingly several times in the list. Further information on the symbols and their meaning can be found in the respective linked articles. Contents 1 Guide 2 Set theory 2.1 Definition symbols 2.2 Set construction 2.3 Set operations 2.4 Set relations 2.5 Number sets 2.6 Cardinality 3 Arithmetic 3.1 Arithmetic operators 3.2 Equality signs 3.3 Comparison 3.4 Divisibility 3.5 Intervals 3.6 Elementary functions 3.7 Complex numbers 3.8 Mathematical constants 4 Calculus 4.1 Sequences and series 4.2 Functions 4.3 Limits 4.4 Asymptotic behaviour 4.5 Differential calculus 4.6 Integral calculus 4.7 Vector calculus 4.8 Topology 4.9 Functional analysis 5 Linear algebra and geometry 5.1 Elementary geometry 5.2 Vectors and matrices 5.3 Vector calculus 5.4 Matrix calculus 5.5 Vector spaces 6 Algebra 6.1 Relations 6.2 Group theory 6.3 Field theory 6.4 Ring theory 7 Combinatorics 8 Stochastics 8.1 Probability theory 8.2 Statistics 9 Logic 9.1 Operators 9.2 Quantifiers 9.3 Deduction symbols 10 See also 11 References 12 External links Guide The following information is provided for each mathematical symbol: Symbol: The symbol as it is represented by LaTeX. -
On Identifying Basic Discourse Units in Speech: Theoretical and Empirical Issues
Discours Revue de linguistique, psycholinguistique et informatique. A journal of linguistics, psycholinguistics and computational linguistics 4 | 2009 Linearization and Segmentation in Discourse On identifying basic discourse units in speech: theoretical and empirical issues Liesbeth Degand and Anne Catherine Simon Electronic version URL: http://journals.openedition.org/discours/5852 DOI: 10.4000/discours.5852 ISSN: 1963-1723 Publisher: Laboratoire LATTICE, Presses universitaires de Caen Electronic reference Liesbeth Degand and Anne Catherine Simon, « On identifying basic discourse units in speech: theoretical and empirical issues », Discours [Online], 4 | 2009, Online since 30 June 2009, connection on 10 December 2020. URL : http://journals.openedition.org/discours/5852 ; DOI : https://doi.org/ 10.4000/discours.5852 Discours est mis à disposition selon les termes de la licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Pas de Modification 4.0 International. Discours 4 | 2009, Linearization and Segmentation in Discourse (Special issue) On identifying basic discourse units in speech: theoretical and empirical issues Liesbeth Degand1,2, Anne Catherine Simon2 1FNRS, 2Université catholique de Louvain Abstract: In spite of its crucial role in discourse segmentation and discourse interpretation, there is no consensus in the literature on what a discourse unit is and how it should be identified. Working with spoken data, we claim that the basic discourse unit (BDU) is a multi-dimensional unit that should be defined in terms of two linguistic criteria: prosody and syntax. In this paper, we explain which criteria are used to perform the prosodic and syntactic segmentation, and how these levels are mapped onto one another. We discuss three types BDUs (one-to-one, syntax-bound, prosody- bound) and open up a number of theoretical issues with respect to their function in discourse interpretation.