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Vehicle-to-grid (V2G) technology is used in the modern eco-friendly environment for demand response management. It helps in reducing the carbon footprints in the environment. However, security and privacy of the information exchange between different entities are significant concerns keeping in view of the information exchange via an open channel, i.e., Internet among different entities such as plug-in hybrid electric vehicles (PHEVs), charging stations (CSs), and controllers in V2G environment. With an exponential rise in Electric vehicles (EVs) usage across the globe, there is a requirement of developing a seamless charging infrastructure for charging and billing. Moreover, secure information flow needs to be maintained at different levels in such an environment. Hence, this paper proposes a blockchain-based demand response management for efficient energy trading between EVs and CSs. In this proposal, miner nodes and block verifiers are selected using their power consumption and processing power. These nodes are responsible for the authentication of various transactions in the proposal. We also proposed a game theory-based solution to support energy management and peak load control off-peak and peak conditions. The proposed scheme has been evaluated using various performance evaluation metrics where its performance is found superior in comparison to the existing solutions in the literature.

Phishing phenomena are increasing day after day due to its simplicity to use; it is enough for hackers to clone legitimate website and send it by e-mail to victims to access it within the use of social engineering techniques to lure them and gain their confidence. Hackers use the lack of knowledge of regular users when surfing on the internet and understanding the role of uniform resource locator (URL) of a web page. This fact let hackers create malicious forms of URLs, like very long ones or containing some suspicious characters. Despite cloning web pages, hackers can inject malicious codes into this web page for nefarious uses, so detecting or preventing this kind of web pages is the objective of this paper. We present a new hybrid framework to identify phishing web pages based on different ways and methodologies for features extraction techniques using only the URL as the main entry and without having any visual experience before, also we use hybrid analysis to be complete and accurate.

In this paper, the authors present a cloud system that incorporate tools developed in HTML5 and JQuery technologies, which are offered to professors and students in the development of a teaching methodology called flipped classroom, where the theoretical content is usually delivered by video files and self-assessment tools that students can display from home. This system aims to eliminate the technical limitations to facilitate communication and a real learning process by monitoring and evaluating the students and teachers. Highlighting main functions, the authors do find: the wizard of quality content, visual interactive wizard, the audio note as tool for audio records, and finally the graphical evaluator that provides a graphical and intuitive result, providing a clear image of the theoretical and practical difficulties that students experience.

The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give the system dynamic self-learning capabilities from the behaviors exhibited by the teachers and students to create the appropriate pedagogy and automatically adjust the e-learning environments to suit the pedagogies. In this respect, artificial intelligence techniques may be useful for several reasons, including their ability to develop and imitate human reasoning and decision-making processes (learning-teaching model) and minimize the sources of uncertainty to achieve an effective learning-teaching context. These learning capabilities ensure both learner and system improvement over the lifelong learning mechanism. In this paper, we present a survey of raised and related topics to the field of artificial intelligence techniques employed for adaptive educational systems within e-learning, their advantages and disadvantages, and a discussion of the importance of using those techniques to achieve more intelligent and adaptive e-learning environments.

Technological advancements within the educational sector and online learning promoted portable data-based adaptive techniques to influence the developments within transformative learning and enhancing the learning experience. However, many common adaptive educational systems tend to focus on adopting learning content that revolves around pre-black box learner modelling and teaching models that depend on the ideas of a few experts. Such views might be characterized by various sources of uncertainty about the learner response evaluation with adaptive educational system, linked to learner reception of instruction. High linguistic uncertainty levels in e-learning settings result in different user interpretations and responses to the same techniques, words, or terms according to their plans, cognition, pre-knowledge, and motivation levels. Hence, adaptive teaching models must be targeted to individual learners’ needs. Thus, developing a teaching model based on the knowledge of how learners interact with the learning environment in readable and interpretable white box models is critical in the guidance of the adaptation approach for learners’ needs as well as understanding the way learning is achieved.

During the last two decades, the Internet has changed people’s habits and improved their daily life activities and services. In particular, the emergence of e-commerce provided manufactures and vendors with more business opportunities. This allowed customers to benefit from a global, quicker and cheaper shopping environment. However, e-commerce is evolving from a centralised approach, where consumers directly purchase products and services from businesses, to a Peer-to-Peer (P2P) perspective, in which customers buy and sell goods amongst themselves. In P2P scenarios, it is crucial to protect both buyers and sellers (the peers) from being victimised by possible fraud arising from the uncertainties, vagueness and ambiguities that characterise the interactions amongst unknown business entities. For this reason, the so-called reputation models are becoming a key architectural component of any e-commerce portal. These systems are intended to evaluate the basic features of each entity (buyer, seller, goods, etc.) involved in a given trading transaction in order to assess the trust level of the given transaction and minimise fraud. However, in spite of their wide deployment, the reputation models need to be enhanced to handle the various sources of uncertainties in order to produce more accurate outputs which will allow to increase the trust and decrease the fraud levels within e-commerce systems. In this paper, we present an interval type-2 fuzzy logic based framework for reputation management in (P2P) e-commerce which is capable of better handling the faced uncertainties. We have carried out various experiments based on eBay ® -like transaction datasets which have shown that the proposed type-2 fuzzy logic based system can provide better performance (in terms of malicious peer detection and exchanged message overhead) when compared to the other well-known and heavily used approaches like the eBay ® approach, EigenTrust, PeerTrust as well as the type-1 fuzzy based counterpart approach. [ABSTRACT FROM AUTHOR]

The students of obligatory learning, once finished their studies don’t get any help, at the improvement of their curriculum. For it these students could chose a work formation different to the needed professional formation. This variant would consist in entering to the work environment through learning contracts. These contracts would be associated with not regulated formation hours, not official, through given courses through the collaborated entities. To maintain an actualized curriculum, it would be necessary to establish a system that guarantees the acquisition of these competences, in function of the professional labor chose by the student. To do this you need to establish a track training cycle than previously known, as is the case of the training cycles professional family computer, through an analysis of the curricula of these training cycles and verification state thereof. This procedure can be carried out through a temporary employment agency or placement agency, which keeps track of the different needs of students.

The education system is always being challenged by their limited capacity to adapt according to today's realities. In this paper we present a new methodology where teachers take into consideration the students’ perspective to find weaknesses in the educational system. By using this method, the system is capable to have a broad view and can adapt the school to meet the incredible pace of technology change. Our proposal here is to create a platform that is able to collect information from students’ moods, using RFID tags to represent three different moods. Students can click on them to express how they feel.

In this paper we introduce online social networks as part of secondary schools system, to allow the development of values, attitudes, socio-emotional skills and ethical standards among students. Students will learn to be citizens, how to vote, and be responsible for the improvements and changes of their own educative system under the supervision of the management team of the center and the school board. This methodology is intended for all students to have responsibilities through their participation in their own school system.

This paper presents the evolution of the eLearniXML platform by carrying it into the cloud with “C-LearniXML++”. At the same time, we make use of the extensive communication between students in social networks, and capture their attention to insert this communication processes into an educational scope. In this situation, students of all high schools, of an autonomous region, once registered in the system can communicate and perform the learning process in a collaborative way. Students can access and display the common educational content of the various high schools. This relationship gives rise to the students of various high schools to work in a collaborative way and support their peers.