The Dot Product
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Research Brief March 2017 Publication #2017-16
Research Brief March 2017 Publication #2017-16 Flourishing From the Start: What Is It and How Can It Be Measured? Kristin Anderson Moore, PhD, Child Trends Christina D. Bethell, PhD, The Child and Adolescent Health Measurement Introduction Initiative, Johns Hopkins Bloomberg School of Every parent wants their child to flourish, and every community wants its Public Health children to thrive. It is not sufficient for children to avoid negative outcomes. Rather, from their earliest years, we should foster positive outcomes for David Murphey, PhD, children. Substantial evidence indicates that early investments to foster positive child development can reap large and lasting gains.1 But in order to Child Trends implement and sustain policies and programs that help children flourish, we need to accurately define, measure, and then monitor, “flourishing.”a Miranda Carver Martin, BA, Child Trends By comparing the available child development research literature with the data currently being collected by health researchers and other practitioners, Martha Beltz, BA, we have identified important gaps in our definition of flourishing.2 In formerly of Child Trends particular, the field lacks a set of brief, robust, and culturally sensitive measures of “thriving” constructs critical for young children.3 This is also true for measures of the promotive and protective factors that contribute to thriving. Even when measures do exist, there are serious concerns regarding their validity and utility. We instead recommend these high-priority measures of flourishing -
21. Orthonormal Bases
21. Orthonormal Bases The canonical/standard basis 011 001 001 B C B C B C B0C B1C B0C e1 = B.C ; e2 = B.C ; : : : ; en = B.C B.C B.C B.C @.A @.A @.A 0 0 1 has many useful properties. • Each of the standard basis vectors has unit length: q p T jjeijj = ei ei = ei ei = 1: • The standard basis vectors are orthogonal (in other words, at right angles or perpendicular). T ei ej = ei ej = 0 when i 6= j This is summarized by ( 1 i = j eT e = δ = ; i j ij 0 i 6= j where δij is the Kronecker delta. Notice that the Kronecker delta gives the entries of the identity matrix. Given column vectors v and w, we have seen that the dot product v w is the same as the matrix multiplication vT w. This is the inner product on n T R . We can also form the outer product vw , which gives a square matrix. 1 The outer product on the standard basis vectors is interesting. Set T Π1 = e1e1 011 B C B0C = B.C 1 0 ::: 0 B.C @.A 0 01 0 ::: 01 B C B0 0 ::: 0C = B. .C B. .C @. .A 0 0 ::: 0 . T Πn = enen 001 B C B0C = B.C 0 0 ::: 1 B.C @.A 1 00 0 ::: 01 B C B0 0 ::: 0C = B. .C B. .C @. .A 0 0 ::: 1 In short, Πi is the diagonal square matrix with a 1 in the ith diagonal position and zeros everywhere else. -
Vectors, Matrices and Coordinate Transformations
S. Widnall 16.07 Dynamics Fall 2009 Lecture notes based on J. Peraire Version 2.0 Lecture L3 - Vectors, Matrices and Coordinate Transformations By using vectors and defining appropriate operations between them, physical laws can often be written in a simple form. Since we will making extensive use of vectors in Dynamics, we will summarize some of their important properties. Vectors For our purposes we will think of a vector as a mathematical representation of a physical entity which has both magnitude and direction in a 3D space. Examples of physical vectors are forces, moments, and velocities. Geometrically, a vector can be represented as arrows. The length of the arrow represents its magnitude. Unless indicated otherwise, we shall assume that parallel translation does not change a vector, and we shall call the vectors satisfying this property, free vectors. Thus, two vectors are equal if and only if they are parallel, point in the same direction, and have equal length. Vectors are usually typed in boldface and scalar quantities appear in lightface italic type, e.g. the vector quantity A has magnitude, or modulus, A = |A|. In handwritten text, vectors are often expressed using the −→ arrow, or underbar notation, e.g. A , A. Vector Algebra Here, we introduce a few useful operations which are defined for free vectors. Multiplication by a scalar If we multiply a vector A by a scalar α, the result is a vector B = αA, which has magnitude B = |α|A. The vector B, is parallel to A and points in the same direction if α > 0. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
ISO Basic Latin Alphabet
ISO basic Latin alphabet The ISO basic Latin alphabet is a Latin-script alphabet and consists of two sets of 26 letters, codified in[1] various national and international standards and used widely in international communication. The two sets contain the following 26 letters each:[1][2] ISO basic Latin alphabet Uppercase Latin A B C D E F G H I J K L M N O P Q R S T U V W X Y Z alphabet Lowercase Latin a b c d e f g h i j k l m n o p q r s t u v w x y z alphabet Contents History Terminology Name for Unicode block that contains all letters Names for the two subsets Names for the letters Timeline for encoding standards Timeline for widely used computer codes supporting the alphabet Representation Usage Alphabets containing the same set of letters Column numbering See also References History By the 1960s it became apparent to thecomputer and telecommunications industries in the First World that a non-proprietary method of encoding characters was needed. The International Organization for Standardization (ISO) encapsulated the Latin script in their (ISO/IEC 646) 7-bit character-encoding standard. To achieve widespread acceptance, this encapsulation was based on popular usage. The standard was based on the already published American Standard Code for Information Interchange, better known as ASCII, which included in the character set the 26 × 2 letters of the English alphabet. Later standards issued by the ISO, for example ISO/IEC 8859 (8-bit character encoding) and ISO/IEC 10646 (Unicode Latin), have continued to define the 26 × 2 letters of the English alphabet as the basic Latin script with extensions to handle other letters in other languages.[1] Terminology Name for Unicode block that contains all letters The Unicode block that contains the alphabet is called "C0 Controls and Basic Latin". -
CM4L9 Assessment 1) the Specific Heat of Aluminum Is 0.900 J/G Oc
CM4L9 Assessment 1) The specific heat of aluminum is 0.900 J/g oC. How much heat is required to raise the temperature of a 30.0g block of aluminum from 25.0oC to 75.0oC? a. 0.540 J (Incorrect) b. 1.50 J (Incorrect) Show work regardless if student got answer c. 1350 J (Correct) correct or incorrect d. 1670 J (Incorrect) q = mC∆T q = (30.0g)(0.900J/goC)(50oC) q = 1350 J 2) Given the balanced equation representing a reaction at 101.3 kPa and 298K: N2(g) + 3H2(g) 2NH3(g) + 91.8kJ a. It is exothermic and ∆H equals -91.8 kJ (Correct; exothermic reactions have energy as a product and a negative ∆H) b. It is exothermic and ∆H equals +91.8 kJ (Incorrect; exothermic reactions have a negative ∆H) c. It is endothermic and ∆H equals -91.8 kJ (Incorrect; endothermic reactions have a positive ∆H and have energy as a reactant) d. It is endothermic and ∆H equals +91.8 kJ (Incorrect; endothermic reactions have energy as a reactant) 3) The table below shows the specific heat capacity of four substances. Substance Specific Heat J / g oC Water 4.18 Copper 0.39 Gold 0.13 Silver 0.24 For an equal mass of each substance, which one will require the least amount of heat to raise its temperature from 40oC to 50oC? a. water (Incorrect; water would require the most amount of heat (energy) to raise it’s temperature) b. copper (Incorrect; it would take 0.39 J for each degree change in copper. -
Glossary of Linear Algebra Terms
INNER PRODUCT SPACES AND THE GRAM-SCHMIDT PROCESS A. HAVENS 1. The Dot Product and Orthogonality 1.1. Review of the Dot Product. We first recall the notion of the dot product, which gives us a familiar example of an inner product structure on the real vector spaces Rn. This product is connected to the Euclidean geometry of Rn, via lengths and angles measured in Rn. Later, we will introduce inner product spaces in general, and use their structure to define general notions of length and angle on other vector spaces. Definition 1.1. The dot product of real n-vectors in the Euclidean vector space Rn is the scalar product · : Rn × Rn ! R given by the rule n n ! n X X X (u; v) = uiei; viei 7! uivi : i=1 i=1 i n Here BS := (e1;:::; en) is the standard basis of R . With respect to our conventions on basis and matrix multiplication, we may also express the dot product as the matrix-vector product 2 3 v1 6 7 t î ó 6 . 7 u v = u1 : : : un 6 . 7 : 4 5 vn It is a good exercise to verify the following proposition. Proposition 1.1. Let u; v; w 2 Rn be any real n-vectors, and s; t 2 R be any scalars. The Euclidean dot product (u; v) 7! u · v satisfies the following properties. (i:) The dot product is symmetric: u · v = v · u. (ii:) The dot product is bilinear: • (su) · v = s(u · v) = u · (sv), • (u + v) · w = u · w + v · w. -
Threshold Digraphs
Volume 119 (2014) http://dx.doi.org/10.6028/jres.119.007 Journal of Research of the National Institute of Standards and Technology Threshold Digraphs Brian Cloteaux1, M. Drew LaMar2, Elizabeth Moseman1, and James Shook1 1National Institute of Standards and Technology, Gaithersburg, MD 20899 2The College of William and Mary, Williamsburg, VA 23185 [email protected] [email protected] [email protected] [email protected] A digraph whose degree sequence has a unique vertex labeled realization is called threshold. In this paper we present several characterizations of threshold digraphs and their degree sequences, and show these characterizations to be equivalent. Using this result, we obtain a new, short proof of the Fulkerson-Chen theorem on degree sequences of general digraphs. Key words: digraph realizations; Fulkerson-Chen theorem; threshold digraphs. Accepted: May 6, 2014 Published: May 20, 2014 http://dx.doi.org/10.6028/jres.119.007 1. Introduction Creating models of real-world networks, such as social and biological interactions, is a central task for understanding and measuring the behavior of these networks. A usual first step in this type of model creation is to construct a digraph with a given degree sequence. We examine the extreme case of digraph construction where for a given degree sequence there is exactly one digraph that can be created. What follows is a brief introduction to the notation used in the paper. For notation not otherwise defined, see Diestel [1]. We let G=( VE , ) be a digraph where E is a set of ordered pairs called arcs. If (,vw )∈ E, then we say w is an out-neighbor of v and v is an in-neighbor of w. -
A Some Basic Rules of Tensor Calculus
A Some Basic Rules of Tensor Calculus The tensor calculus is a powerful tool for the description of the fundamentals in con- tinuum mechanics and the derivation of the governing equations for applied prob- lems. In general, there are two possibilities for the representation of the tensors and the tensorial equations: – the direct (symbolic) notation and – the index (component) notation The direct notation operates with scalars, vectors and tensors as physical objects defined in the three dimensional space. A vector (first rank tensor) a is considered as a directed line segment rather than a triple of numbers (coordinates). A second rank tensor A is any finite sum of ordered vector pairs A = a b + ... +c d. The scalars, vectors and tensors are handled as invariant (independent⊗ from the choice⊗ of the coordinate system) objects. This is the reason for the use of the direct notation in the modern literature of mechanics and rheology, e.g. [29, 32, 49, 123, 131, 199, 246, 313, 334] among others. The index notation deals with components or coordinates of vectors and tensors. For a selected basis, e.g. gi, i = 1, 2, 3 one can write a = aig , A = aibj + ... + cidj g g i i ⊗ j Here the Einstein’s summation convention is used: in one expression the twice re- peated indices are summed up from 1 to 3, e.g. 3 3 k k ik ik a gk ∑ a gk, A bk ∑ A bk ≡ k=1 ≡ k=1 In the above examples k is a so-called dummy index. Within the index notation the basic operations with tensors are defined with respect to their coordinates, e. -
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Whenever There Is a Line Or Tilde Over a Vowel, It Is an Abbreviation for the Letters M Or N. in This Case, the Full Word Is Quadam
Whenever there is a line or tilde over a vowel, it is an abbreviation for the letters m or n. In this case, the full word is quadam. In this instance, the line over the e represents an omission of the letter n, giving the word debent when written in full. Whenever a word in Latin had an instance of the letter i in succession, the second i was always written as a j. This applies to all words wherein ii is present and also to the Roman numeral ii, which was written as ij. Therefore, cambij = cambii, negotijs = negotiis. The e with a cedilla was an abbreviation for the letters ae. This word spelled out is quae. Following the letter q, a period or semicolon was used as an abbreviation for the letters ue. The first example reads denique, the second one is quacunque. In the seventeenth century, the letter u and v were interchangeable and not yet viewed as two distinct letters. While not universal, a general rule is that if u or v began a word, it was written as a v; if a u or v occurred in the middle or end of a word, it was written as a u. In the 17th century, a lowercase s had two forms- one long and one short. As a general rule, when a lowercase s occurred as the first letter of the word or in any other place in the word except as the final letter, it was written with a long s, which resembles the letter f. -
Patterns Identification for Hitting Adjacent Key Errors Correction Using Neural Network Models
PATTERNS IDENTIFICATION FOR HITTING ADJACENT KEY ERRORS CORRECTION USING NEURAL NETWORK MODELS Jun Li Department of Land Economy, University of Cambridge, 19 Silver Street, Cambridge, U.K. Karim Ouazzane, Sajid Afzal, Hassan Kazemian Faculty of Computing, London Metropolitan University, London, U.K. Keywords: QWERTY Keyboard, Probabilistic Neural Network, Backpropagation, Key Distance, Time Gap, Error Margin Distance. Abstract: People with Parkinson diseases or motor disability miss-stroke keys. It appears that keyboard layout, key distance, time gap are affecting this group of people’s typing performance. This paper studies these features based on neural network learning algorithms to identify the typing patterns, further to correct the typing mistakes. A specific user typing performance, i.e. Hitting Adjacent Key Errors, is simulated to pilot this research. In this paper, a Time Gap and a Prediction using Time Gap model based on BackPropagation Neural Network, and a Distance, Angle and Time Gap model based on the use of Probabilistic Neural Network are developed respectively for this particular behaviour. Results demonstrate a high performance of the designed model, about 70% of all tests score above Basic Correction Rate, and simulation also shows a very unstable trend of user’s ‘Hitting Adjacent Key Errors’ behaviour with this specific datasets. 1 INTRODUCTION technologies to tackle the typing errors as a whole, while there is no specific solution and convincing Computer users with disabilities or some elderly results for solving the ‘Miss-stroke’ error. people may have difficulties in accurately In the field of computer science, a neural manipulating the QWERTY keyboard. For example, network is a mathematical model or computational motor disability can cause significant typing model that is inspired by the structure and/or mistakes.