\chapter{The Leggett-Garg Inequalities} Consider a system characterized by a dichotomous observable, which assumes values $\pm1$. Leggett-Garg inequalities (from now on LGI) set constrains on the value accessible to the two-times correlations functions $C_{ij}= \langle Q_{i}Q_{j} \rangle$, obtain measuring it at $t_{i}$ and $t_{j}$. The simplest of them is: \begin{equation}\label{LGI} -3 \leq K \leq 1 \end{equation} \begin{equation}\label{K} K=C_{12}+C_{23}-C_{31} \end{equation} This inequality
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Cs2093 Child psychology case one report tile: Piaget' s theory is it fit in with the Hong Kong society ? Student Name :Wong Nga Wai ,Emma(11675470) Section :54 Lecturer: Danny sir Introduction Cognition is ability of thinking、reasoning and recollecting . In 1921, Jean Piaget published the result of his groundbreaking research on child development .He set out four powerful stages of child which will shape our thinking for years to come . The first
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| |K1 |Knowledge of the development trends and standards in the Web and e commerce |( | |K2 |Critical awareness of strategies for e-commerce (including B2B and B2C scenarios for e-commerce solutions) |( | | |and the ability to
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The Kalman Filter Max Welling California Institute of Technology 136-93 Pasadena, CA 91125 welling@vision.caltech.edu Until now we have only looked at systems without any dynamics or structure over time. The models had spatial structure but were de ned at one moment in time, i.e. they were \static". In this lecture we will analyse a powerfull dynamic model, which could be characterized as factor analysis over time, although the number of observed features is not necessarily larger than the number
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ELAN ˝GO TO MARKET STRATEGY˝ Group members: Laura Sešek 19553905, Mateja Pirnat 19554965, Vito Petan 19553657, Tilen Lenarčič 19537762, Dejan Lukić 19538765 Ljubljana, 28/05/2015 TABLE OF CONTENT 1. Five-steps analysis of Elan 4 Step 1: TARGET MARKETS 4 Step 2: TARGET CUSTOMER 6 Step 2.1: ONLINE SURVEY 7 Step 2.2: CUSTOMER PROFILE EXAMPLE based on online survey and analysis of the Elan skis: 13 Step 3: BRAND POSITIONING 14 Step 4: OFFERING 14 Step 5: CHANNELS
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Econ 9720: Econometrics II GSU Department of Economics, Spring 2016 Practice Midterm Questions (No Solution will be Provided) 1. Suppose the data generating process (the true relationship) is y = Xβ + ε, where E[ε|X] = 0, E[εε |X] = σ 2 I n ; and X includes an intercept term. You do not observe the data set Z = [y X]. Instead you observe 150 15 50 Z Z = 15 25 0 50 0 100 2 Compute the least squares estimators β, s2 , R2 and RAdj (the adjusted R2 ). Is there anything to be gained
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ELAN ˝GO TO MARKET STRATEGY˝ TABLE OF CONTENT 1. Five-steps analysis of Elan 4 Step 1: TARGET MARKETS 4 Step 2: TARGET CUSTOMER 6 Step 2.1: ONLINE SURVEY 7 Step 2.2: CUSTOMER PROFILE EXAMPLE based on online survey and analysis of the Elan skis: 13 Step 3: BRAND POSITIONING 14 Step 4: OFFERING 14 Step 5: CHANNELS 15 2. BUSINESS IDEAS: 18 2.1 SHORT TERM 18 2.1.1 ˝OLD FOR NEW˝ 18 2.1.2 PROMOTION VIDEOS 18 2.1.3 OUTDOOR EVENTS WITH SPORT CELEBRITIES 19 2.1.4 ELAN
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Computational Condensed Matter 4 (2015) 32e39 Contents lists available at ScienceDirect Computational Condensed Matter journal homepage: http://ees.elsevier.com/cocom/default.asp Regular article Putting DFT to the trial: First principles pressure dependent analysis on optical properties of cubic perovskite SrZrO3 Ghazanfar Nazir a, b, *, Afaq Ahmad b, Muhammad Farooq Khan a, Saad Tariq b a b Department of Physics and Graphene Research Institute, Sejong University, Seoul 143-747
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for creating or pulling the dependencies is excluded from the object. However identifying the objects in which the DI is to be implemented is a difficult task and further implementing those objects is complex. IOC describes a solution for this problem. As per this solution we want to create a special entity only for this responsibility, such entity is generally considered/referred as IOC container. The spring framework implements this pattern for managing java objects; this implementation of
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root tests to have good size, but that information criteria such as the AIC and BIC tend to select a truncation lag that is very small. Furthermore, size distortions increase with the number of deterministic terms in the regression. We trace these problems to the fact that information criteria omit important biases induced by a low order augmented autoregression. We consider a class of Modi ed Information Criteria MIC , de ned as mink ln^ 2 + CT T k + k =T, where T k accounts for the fact that
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