The IEEE provides guidelines for the preparation of papers and presentations for their conference proceedings, including a series of LaTeX templates.
A number of templates using the IEEE style are available on Overleaf to help you get started - click above to use this template for Computer Science journals, or use the tags below to find more.
IEEEtran.cls version: 1.8b
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.
Lazaridou., et al 2017 proposed a framework for language learning that relies on multi-agent communication. The agents in the framework were setup in a referential game where they communicated about many images. In this paper, we propose an experiment where agents develop a private language for referring to specified sentences given a set of sentences. The challenge is for the agents to learn a method of distinguishing differences between sentences and to develop a shared language to be able to refer to particular sentences by those distinguishing features. We will evaluate the agents' ability to accurately identify and differentiate the sentences. In addition, we will identify patterns in the methods that the agents develop to refer to the different types of sentences.Keywords: Reinforcement learning, multi-agent coordination
This research paper aims at exploiting efficient ways of implementing the N-Body problem. The N-Body problem, in the field of physics, predicts the movements and planets and their gravitational interactions. In this paper, the efficient execution of heavy computational work through usage of different cores in CPU and GPU is looked into; achieved by integrating the OpenMP parallelization API and the Nvidia CUDA into the code. The paper also aims at performance analysis of various algorithms used to solve the same problem. This research not only aids as an alternative to complex simulations but also for bigger data that requires work distribution and computationally expensive procedures.