The SNS-Based E-Learning Model to Provide Smart Solution for E-Learning

We are in the era of social networking sites that gives platform to billions of individuals for offering and conveying to each other's. These social sites additionally give a worldwide platform to students and educators to satisfy their learning or instructing necessities. The incorporation of social networking sites (SNS) and online tools with e-learning, getting high fame, extraordinarily in instructive space. Learners are more comfortable with these SNS, they feel pleasure to join, participate and collaborate with peers or teachers in these sites. The smart integration of social sites and online tools with conventional e-learning platform could revolutionize the current e-learning model. Various e-learning issues including learner’s participation, association, motivation and engagement can be mitigated by this integration. Number of SNS and online tools have great components for learning, teaching or training however their balanced use and incorporation with e-learning model is as yet an exploration challenge. In this paper, we present a model that utilizes social networking sites and tools effectively with e-learning platform.  The basic idea of this model is to make e-learning simple and more compelling by using normal, easy to understand and generally free social sites and online tools. This paper also highlights some open research issues and challenges that might be faced SNS-based e-learning model. The idea, knowledge and open research issues that talk about in this paper may create another heading of research in the space of innovation bolstered learning

El modelo de e-learning basado en SNS para proporcionar una solución inteligente para el aprendizaje electrónico

URL del artículo en la web de la Revista: https://www.upo.es/revistas/index.php/IJERI/article/view/2764We are in the era of social networking sites that gives platform to billions of individuals for offering and conveying to each other's. These social sites additionally give a worldwide platform to students and educators to satisfy their learning or instructing necessities. The incorporation of social networking sites (SNS) and online tools with e-learning, getting high fame, extraordinarily in instructive space. Learners are more comfortable with these SNS, they feel pleasure to join, participate and collaborate with peers or teachers in these sites. The smart integration of social sites and online tools with conventional e-learning platform could revolutionize the current e-learning model. Various e-learning issues including learner's participation, association, motivation and engagement can be mitigated by this integration. Number of SNS and online tools have great components for learning, teaching or training however their balanced use and incorporation with e-learning model is as yet an exploration challenge. In this paper, we present a model that utilizes social networking sites and tools effectively with e-learning platform. The basic idea of this model is to make e-learning simple and more compelling by using normal, easy to understand and generally free social sites and online tools. This paper also highlights some open research issues and challenges that might be faced SNS-based e-learning model. The idea, knowledge and open research issues that talk about in this paper may create another heading of research in the space of innovation bolstered learning.Estamos en la era de los sitios de redes sociales que ofrece una plataforma a miles de millones de individuos para ofrecer y transmitir los unos a los otros. Estos sitios sociales, además, brindan una plataforma mundial a estudiantes y educadores para satisfacer sus necesidades de aprendizaje o instrucción. La incorporación de sitios de redes sociales (SNS) y herramientas en línea con e-learning, obteniendo una gran fama, extraordinariamente instructivo en el espacio. Los alumnos se sienten más cómodos con estos SNS, se sienten complacidos de unirse, participar y colaborar con compañeros o profesores en estos sitios. La integración inteligente de los sitios sociales y las herramientas en línea con la plataforma de e-learning convencional podría revolucionar el modelo actual de e-learning. Varias cuestiones de aprendizaje electrónico, incluida la participación, la asociación, la motivación y el compromiso de los alumnos pueden mitigarse con esta integración. El número de SNS y las herramientas en línea tienen grandes componentes para el aprendizaje, la enseñanza o la capacitación, sin embargo, su uso equilibrado e incorporación con el modelo de aprendizaje electrónico es aún un desafío de exploración. En este artículo, presentamos un modelo que utiliza sitios y herramientas de redes sociales de manera efectiva con la plataforma de aprendizaje electrónico. La idea básica de este modelo es hacer que el e-learning sea simple y más atractivo al usar sitios sociales y herramientas en línea, fáciles de comprender y, en general, gratuitos. Este documento también resalta algunos problemas y desafíos de investigación abiertos que podrían enfrentar el modelo de e-learning basado en SNS. La idea, el conocimiento y los temas de investigación abierta de los que se explicita en este artículo pueden crear otro rumbo de investigación en el espacio de aprendizaje orientado por la innovación.Universidad Pablo de Olavid

Towards the Deployment of Machine Learning Solutions in Network Traffic Classification: A Systematic Survey

International audienceTraffic analysis is a compound of strategies intended to find relationships, patterns, anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic classification is a subgroup of strategies in this field that aims at identifying the application's name or type of Internet traffic. Nowadays, traffic classification has become a challenging task due to the rise of new technologies, such as traffic encryption and encapsulation, which decrease the performance of classical traffic classification strategies. Machine Learning gains interest as a new direction in this field, showing signs of future success, such as knowledge extraction from encrypted traffic, and more accurate Quality of Service management. Machine Learning is fast becoming a key tool to build traffic classification solutions in real network traffic scenarios; in this sense, the purpose of this investigation is to explore the elements that allow this technique to work in the traffic classification field. Therefore, a systematic review is introduced based on the steps to achieve traffic classification by using Machine Learning techniques. The main aim is to understand and to identify the procedures followed by the existing works to achieve their goals. As a result, this survey paper finds a set of trends derived from the analysis performed on this domain; in this manner, the authors expect to outline future directions for Machine Learning based traffic classification