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Smart Learning Objects for Smart Education in Computer Science: Theory, Methodology and Robot-Based Implementation

This monograph provides the demanding situations, imaginative and prescient and context to layout clever studying items (SLOs) via desktop technological know-how (CS) schooling modelling and have version changes. It provides the newest study at the meta-programming-based generative studying items (the latter with complicated good points are taken care of as SLOs) and using academic robots in instructing CS subject matters.

Activités sensorielles et motrices : éducation, rééducation

Cet ouvrage présente une multitude d'activités psychomotrices pouvant être utilisées en éducation, en rééducation ou en thérapie auprès d'enfants et d'adolescents. Les diverses activités ludiques, sportives et expressives peuvent favoriser le développement body, intellectuel et social de l'enfant.

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1/2 For a test function v T ∈ HT (Γ ), we then obtain the variational problem S Lame uT , v T Γ = − S Lame gn, v T Γ , which is uniquely solvable due to the mapping properties of the Steklov– Poincar´e operator. Note that one may also consider mixed boundary value problems with sliding boundary conditions only on a part ΓS , but standard Dirichlet or Neumann boundary conditions elsewhere. However, to ensure uniqueness, one needs to assume Dirichlet boundary conditions somewhere for each component.

57), u ¯ = γ0ext ue (x) = γ0int ui (x) , αi γ1int ui (x) = αe γ1ext ue (x) for x ∈ Γ, we obtain a coupled Steklov–Poincar´e operator equation to ﬁnd u ¯ ∈ H 1/2 (Γ ) such that ¯)(x) + αe (S ext u ¯)(x) = αi (S int u (S int γ0int up )(x) − γ1int up (x) + αe 1 I − K (V −1 u0 )(x) 2 is satisﬁed for x ∈ Γ . 59) Γ S int γ0int up − γ1int up + αe 1 I − K V −1 u0 , v 2 Γ is satisﬁed for all v ∈ H 1/2 (Γ ). 59) ﬁnally follows from the ellipticity estimates for the interior and exterior Steklov–Poincar´e operators S int and S ext .

48) describes the correct solution for any scaling parameter. 1), we now consider an inhomogeneous Poisson equation with some given right hand side. The Dirichlet boundary value problem for the Poisson equation reads −Δu(x) = f (x) for x ∈ Ω, γ0int u(x) = g(x) for x ∈ Γ. 3), we then obtain the representation formula u∗ (x, y)t(y)dsy − u(x) = Γ int u∗ (x, y)g(y)ds + γ1,y y Γ u∗ (x, y)f (y)dy Ω for x ∈ Ω, where t = γ1int u is the yet unknown Neumann datum. 55) where u∗ (x, y)f (y)dy (N0 f )(x) = for x ∈ Γ Ω is the Newton potential entering the right hand side.