'Contextual' diaporamas de présentation

GLOBAL INTERPRETATIONS OF CHRISTIAN SCRIPTURES

1.02k views • 89 slides

27 September 2007

606 views • 60 slides

Making Successful Mistakes

582 views • 47 slides

541 views • 44 slides

Pauline Interpretation of Christianity: ROMANS

495 views • 42 slides

Aegis: A Semantic Implementation of Privacy as Contextual Integrity in Social Ecosystems

Aegis: A Semantic Implementation of Privacy as Contextual Integrity in Social Ecosystems. Imrul Kayes, Adriana Iamnitchi. Social Privacy Risks. Why Does This Happen?. Inappropriate sharing and transferring of information (Permissive) Default privacy settings by OSN provider

499 views • 32 slides

Teaching and Learning Objectives

646 views • 30 slides

Importance of Standardized Terminology in Healthcare Information Systems

Importance of Standardized Terminology in Healthcare Information Systems. Judith J. Warren, PhD, RN, BC, FAAN, FACMI Christine A. Hartley Centennial Professor University of Kansas School of Nursing. Learning Objectives. Importance of Standardized Terminology in Healthcare Information Systems

2.08k views • 26 slides

Contextual Campaigns: Content, Context & Consumer Connections in a Post-Screen World

Digital marketing has moved beyond the screen. Beacons, sensors, IoT, every Thing can be connected and surrounded with content. This research looks at contextual campaigns: what they are, how and why to get started, case examples from companies like Disney and Marantz; and the benefits and risks of diving in.

313 views • 25 slides

Bayesian inference accounts for the filling-in and suppression

Bayesian inference accounts for the filling-in and suppression of visual perception of bars by context. Li Zhaoping 1 & Li Jingling 2 1 University College London, 2 China Medical School. Based on a publication Zhaoping & Jingling (2008) PLoS Comput. Biol.

377 views • 23 slides

Bayesian inference accounts for the filling-in and suppression

Bayesian inference accounts for the filling-in and suppression of visual perception of bars by context. Li Zhaoping 1 & Li Jingling 2 1 University College London, 2 China Medical School. Based on a publication Zhaoping & Jingling (2008) PLoS Comput. Biol.

230 views • 23 slides

224 views • 22 slides

Transforming Heritage An International Workshop for Enhancing UK-South Asia Networks

207 views • 20 slides

Word 2007 Understanding Word Environment

Word 2007 Understanding Word Environment. CSCI150 Introduction to High Technology. Understanding Word Environment. User Interface Ribbon Contextual Tabs Word Galleries Customize the Word Interface. Microsoft Office Button. Ribbon. Tabs organized in the order of use. Ribbon.

242 views • 19 slides

ABX Pentra 400 Specifications Reagents Main features analysis Strengths

471 views • 18 slides

Symbolism in Literature

Symbolism in Literature . Symbols. What is a symbol? A particular person, object, place, event, word or phrase that represents something beyond itself. Example: What does it represent? 13 original colonies, freedom, United States, patriotism, 50 states (stars). Symbols. Example:

1.2k views • 17 slides

The Noncognitive Variable System

The Noncognitive Variable System. William E. Sedlacek University of Maryland wsed@umd.edu http://williamsedlacek.info/. Current Issues . Restriction of Range Tests Grade Inflation Diversity Three Musketeers Problem Range of Abilities. Sternberg. Componential

390 views • 13 slides

KNR 273 : Supportive Environments

KNR 273 : Supportive Environments. Shank & Coyle, 2002. Overview. How does an environment effect behavior? People are part & product of their environment QofL cannot be understood, improved or maintained without consideration of the physical & social elements of an environment

193 views • 7 slides

Beyond Wannabe Contextual Matching

Beyond Wannabe Contextual Matching. Thomas Hargis VP Sales and Marketing. 15 year veteran of the information industry 4 years with YellowBrix P&L responsibility for sales, marketing, customer service and business development. True Contextual Analysis.

152 views • 6 slides

Learn appearance based models for concepts Compute posterior probabilities or Semantic Multinomial (SMN) under app

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83 views • 1 slides