The use of technological resources in education has lead to positive changes in the elaboration of new methodologies, in this context technologies such as the Digital Interactive Whiteboard (DIW) can act by facilitating Learning. The mere presence of the DIW does not guarantee benefits for the student's learning process, that raises doubts about whether or not the resources available are used in a satisfactory manner. In this research it was possible to verify that there are few tools available for the DIW context, and many of them have problems of usability and content quality. Thus, a form of facilitate the content elaboration for the DIW is the use of Authoring Tools (ATs). In order to verify whether or not the use of ATs promotes better use of the DIW, an AT (entitled AtauDIW) was developed to assist the use of DIWs.
his project is part of the FlowNet initiative.
FlowNet aims at providing Internet freedom and free flow
information through socially informed, censor resistant online
social networks. My contribution for FLowNet is in devel-
oping an Android application, SecurePost. The requirement
for SecurePost is two-fold. First, the system should facilitate
secure, anonymous, group communication within a closed
group of trusted members. Second, the general public on the
Internet viewing this content, should be able to verify that the
content was generated only by the said closed group of trusted
members. The system consists of an Android client application,
a proxy server and a browser-plugin. The OSNs supported by
this system are Twitter and Facebook.
I analyzed the Hextech-Crafting in a Stochastic Simulation with 10 Million Players and found that you're going to make more Riot Points than you spend (in value) and thats without counting Champs. I've made some assumptions, which can be found down in the paper itself for those interested. For everyone else: If you're trying to maximize your RP-Net-Worth stack up on Hextech Chests.
Las observaciones han mostrado que el numero de neutrinos electrónicos νe que llegan a la tierra desde el sol es aproximadamente la mitad del número esperado de nuestro conocimiento de las reacciones nucleares que ocurren al interior del sol. Estas observaciones se explican como el resultado de que algunos neutrinos electrónicos νe se convierten en neutrinos muónicos νμ y neutrinos tauónicos ντ durante su recorrido entre su creación al interior del sol y su observación en la tierra. Este cambio de un sabor a otro se conoce como oscilaciónes del neutrino. Se introduce un término de masa para el neutrino que es invariante de Lorentz en la densidad lagrangiana del modelo estándar (SM), y se describe el estado del neutrino |να⟩(α = e, μ, τ) como una combinación lineal de autoestados de masa |νi⟩ (i=1,2,3), lo cual conduce a las oscilaciones del neutrino.
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In the last few years the resolution of NLP tasks with architectures composed of neural models has taken vogue. There are many advantages to using these approaches especially because there is no need to do features engineering. In this paper, we make a survey of a Deep Learning architecture that propose a resolutive approach to some classical tasks of the NLP. The Deep Learning architecture is based on a cutting-edge model that exploits both word-level and character-level representations through the combination of bidirectional LSTM, CNN and CRF. This architecture has provided cutting-edge performance in several sequential labeling activities for the English language. The architecture that will be treated uses the same approach for the Italian language. The same guideline is extended to perform a multi-task learning involving PoS labeling and sentiment analysis. The results show that the system performs well and achieves good results in all activities. In some cases it exceeds the best systems previously developed for Italian.