2011 06 01 (uned) emadrid aelsaddik uottawa tangible objects for e learning

Tangible Objects for E-Learning Abdulmotaleb El Saddik FIEEE, FCAE, FEIC

At a glance Creation of Advanced Multimedia LO Protection of LO Navigation of LOR by VR metaphors Adaptation of LO according to user context/profile & network QoS LO Delivery to user

Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Multimedia and Authoring ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Multimedia Authoring Tools ,[object Object],[object Object]

HAMLAT ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

A Multimedia Handwriting Learning and Evaluation Tool ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Multimedia Learning Tool ,[object Object],[object Object],[object Object],[object Object],[object Object]

Learning Mode -1- ,[object Object],[object Object]

Learning Mode -2- ,[object Object],[object Object],[object Object],[object Object]

Evaluation Mode -1- ,[object Object]

Evaluation Mode -2- ,[object Object],[object Object],[object Object],[object Object],Given two time series // x i is a point in the test trajectory X = x 0 , x 1 , …, x N-1 // y i is a point in the ref. trajectory Y = y 0 , y 1 , …, y T-1 D(x i ,y i ) = sqrt((abs(x i )-abs(y i ))^2 + (ord(x i )-ord(y i ))^2) DTW[0,0] = D(x 0 ,y 0 ) For i=1 to T-1 DTW[0,i] = D(x 0 ,y i ) + DTW[0,i-1] For i=1 to N-1 DTW[i,0] = D(x i ,y 0 ) + DTW[i-1,0] For i=1 to N-1 For j=1 to T-1 DTW[i,j]=D(x i ,y j )+min{DTW[i,j-1],DTW[i-1,j],DTW[i-1,j-1]} Return (DTW[N-1,T-1])

Performance Evaluation -1- ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Performance Evaluation -2- ,[object Object]

Performance Evaluation -3- ,[object Object]

Performance Evaluation -4- (Demo) The DTW distances for five Japanese characters Character Threshold Distance (x10 3 mm) Easy Medium Difficult Sa 5.5 2.5 1 Shi 4 1 0.5 Chi 5 2.5 1 Tsu 4 1.5 1 Na 10 6 1

Haptic signal prediction, compression, and watermarking Watermark haptic signals to protect copyright and authenticate content.

Case Study: Identifying Human Pattern with Haptics The Experiment Methodology Dynamic Time Warping : + Nelder-Mead non-linear minimization Spectral analysis: Fast Fourier Transform Unsupervised Method: K-Means Graphic Representation Data Trial Timestamp Position X Position Y … Force X ( N) 1 0 0.23344 0.56768 0.00456 1 … .. … … 1 0.0123090 0.37676 0.98976 0,03767

Verifying such feasibility ( demo ) Virtual Check Virtual Mobile Phone Performance Ambient Intelligent Engine

At a glance Creation of Advanced Multimedia LO Protection of LO by Digital Watermarking Navigation of LOR by VR metaphors Adaptation of LO according to user context/profile & network QoS LO Delivery to user

Navigation ,[object Object],[object Object],[object Object]

[object Object],[object Object]

Toddler Interfaces ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Alphabet Learning Evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Demo 1 Demo 2

Clustering and 3D Mapping Semantic keyword metrics MST tree Overall clustering process design

Searching/Sharing Learning Objects

Sample Interface: Dynamic Traffic Layout

Multimodal Interaction ( demo )

October 4, 2005 Dankie WAD MAHAD SAN TAHAY GADDA GUEY Ευχαριστώ Urakoze Asante متشکرم DMnvwd go raibh maith agaibh

2011 06 01 (uned) emadrid aelsaddik uottawa tangible objects for e learning

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