Espace adhérent

Engine for Virtual Learning including tools, standards and new learning approach according to Predictable and Unpredictable Events PDF Print E-mail
User Rating: / 6
PoorBest 
Written by Amin Elsaleh   
Friday, 06 July 2012 14:40

 

Description & Goals:

This presentation describes prerequisites to produce an Engine for virtual learning which main objectives is create new learning approach according to Predictable and Unpredictable Events. What tools will learners use? What standards will apply? What new learning approaches may result as a function of the proposed engine?

These are the scope of our proposal.

To understand the wide scope where the proposed engine applies we describe three scenarios:

 1.    Virtual Tutor where Simulation is used to trigger iterative interactions and create required environment for virtual learning.

2.    Scenario for Robot handling where number and types of semantic rules are defined according to cumulated knowledge acquired by performing more serious games.

3.    Scenario to predict how the particle is produced and how it decays within the Standard Model[1]. The proposed scenario is composed of a set of predefined messages exchanged between LHC and control stations which pilot its mission in measurement of Proton-proton collisions according to predictable events like how the particle is made in the LHC and how it disintegrates into other, more familiar particles as soon as it is created. We propose a new standard to produce a universal engine: SPDF (Standard Process Description Format) which consists of two parts:

a. message structured-data part (including semantics) and,

b. process description part (with higher level of semantics).

Two key outputs of the SPDF research will be a process description specification and framework for the extraction of semantics from legacy systems.

Note that:

a)    Automated process runs on a server and doesn’t require human intervention.

b)    Number and types of semantic rules are defined according to cumulated knowledge acquired through real experiments and simulations.

c)    The more we may have semantic rules the more predictable and unpredictable events are controlled.

d)   The most difficult event is the human factor in the target definition. This kind of unpredictable event may be overcome by adding dedicated semantic rules.

e)    Performing dynamically a given scenario is the goal of the proposed messaging system. 

 

Keywords: virtual learning; virtual tutor; Simulation; universal engine; SPDF (Standard Process Description Format); semantics; BPEL; WSDL; predictable and unpredictable events; Standard Model; Higgs particles; world business collaboration. 



[1]  The tough job ahead is working out whether the Higgs particle is the simple, singular particle that underpins what physicists call the Standard Model – a set of equations that describe how all the known particles behave – or something more complex.One possibility is that the particle they have found is one of a larger family of Higgs particles. To find out, they must study in exquisite detail how the particle is made in the LHC and how it disintegrates into other, more familiar particles as soon as it is created."It will take a lot of time. I don't mean decades, but perhaps years, to verify all the predictions of the Standard Model about how the particle is produced and how it decays," says Weinberg.“To produce a Higgs particle, the LHC smashes protons together about a billion times every second, producing something like one Higgs particle every 10bn collisions. Almost as soon as it is created the Higgs undergoes a radioactive decay into other particles and these are what the giant detectors see. Sometimes a dying Higgs converts into a pair of photons (particles of light), other times it converts into a pair of quarks and so on. We want to know not only how often Higgs particles are created but also how often they convert into the different types of particle” says Jeff Forshaw professor of particle physics.  
Last Updated on Thursday, 12 July 2012 10:06
 

Promotion 1963

MLFcham Promotion 1963

Giverny - Mai 2004

MLFcham Giverny - Mai 2004

Athènes - Oct 08

MLFcham - Athènes - Octobre 2008

Promotion 1962

MLFcham Promotion 1962