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Managing funerary systems in the pandemic: lessons learned and an application of a scenario simulation in São Paulo City, Brazil
(2021-01-01)
Purpose: This study, a practice forum article, aims to presents the lessons learned and the development of a discrete event simulation model to support the funerary system management of São Paulo City, Brazil, during the ...
Learning Profile Identification Based on the Analysis of the User Context of Interaction
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2011)
One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content ...
Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention
(2013)
Abstract
Background
Educational computer games are examples of computer-assisted learning objects, representing an educational ...
A Knowledge-Based Recommendation System That Includes Sentiment Analysis and Deep Learning
(Ieee-inst Electrical Electronics Engineers Inc, 2019-04-01)
Online social networks provide relevant information on users' opinion about different themes. Thus, applications, such as monitoring and recommendation systems (RS) can collect and analyze this data. This paper presents a ...
Learning obstacle avoidance with an operant behavioral model
(Massachusetts Institute of Technology, 2004)
Artificial intelligence researchers have been attracted by the idea of having robots learn how to accomplish a task, rather than being told explicitly. Reinforcement learning has been proposed as an appealing framework to ...
How to design tools for supporting self-regulated learning in MOOCs? Lessons learned from a literature review from 2008 to 2016
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2018)
Educational Repositories: Study of the Current Situation and Strategies to Improve Their Effective Use at Ecuadorian Universities
(EDUCATION SOCIETY OF IEEE (SPANISH CHAPTER), 2018)
Network-based stochastic semisupervised learning
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCPISCATAWAY, 2012)
Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a ...
Intrusion Detection System Based on Flows Using Machine Learning Algorithms
(2017-10-01)
The use of technology information and communication by different types of devices generates a large quantity of data packets that contains of confidential and personal information. The traffic of data packet can be summarized ...