Machine learning based augmented reality for improved learning application through object detection algorithms

Detection of objects and their location in an image are important elements of current research in computer vision. In May 2020, Meta released its state-of-the-art object-detection model based on a transformer architecture called detection transformer (DETR). There are several object-detection models such as region-based convolutional neural network (R-CNN), you only look once (YOLO) and single shot detectors (SSD), but none have used a transformer to accomplish this task. These models mentioned earlier, use all sorts of hyperparameters and layers. However, the advantages of using a transformer pattern make the architecture simple and easy to implement. In this paper, we determine the name of a chemical experiment through two steps: firstly, by building a DETR model, trained on a customized dataset, and then integrate it into an augmented reality mobile application. By detecting the objects used during the realization of an experiment, we can predict the name of the experiment using a multi-class classification approach. The combination of various computer vision techniques with augmented reality is indeed promising and offers a better user experience

Towards a System of Guidance, Assistance and Learning Analytics Based on Multi Agent System Applied on Serious Games

With the revolution that the education field has known concerning the methods of learning and especially the integration of new technology, several new tools have appeared to replace the tools already existing, and among them there are serious games, serious games as new tool dedicated to education have occupied an important place, and replaced other tools often used in the learning process. But in the order that serious games reach the intended objectives and help instructors to achieve their perspectives considered, they must be equipped with a guidance and assistance system that will assist the learners during the progression in the sequence of the video game, and in addition, they must be equipped with a system of learning analytics that will help instructors to improve the learning process and teaching methods according to the learning outcomes and feedbacks of their learners. In this perspective of research and development we will establish in this paper a new system of assistance, guidance and learning analytics based on a multi agent system that will work in tandem with a web-based serious game

Deep learning based Arabic short answer grading in serious games

Automatic short answer grading (ASAG) has become part of natural language processing problems. Modern ASAG systems start with natural language preprocessing and end with grading. Researchers started experimenting with machine learning in the preprocessing stage and deep learning techniques in automatic grading for English. However, little research is available on automatic grading for Arabic. Datasets are important to ASAG, and limited datasets are available in Arabic. In this research, we have collected a set of questions, answers, and associated grades in Arabic. We have made this dataset publicly available. We have extended to Arabic the solutions used for English ASAG. We have tested how automatic grading works on answers in Arabic provided by schoolchildren in 6th grade in the context of serious games. We found out those schoolchildren providing answers that are 5.6 words long on average. On such answers, deep learning-based grading has achieved high accuracy even with limited training data. We have tested three different recurrent neural networks for grading. With a transformer, we have achieved an accuracy of 95.67%. ASAG for school children will help detect children with learning problems early. When detected early, teachers can solve learning problems easily. This is the main purpose of this research

Novel Antennas for UHF RFID Tags: Design and Miniaturization

This article focuses of study the nature and characteristics of the antenna, The collective electrical signals acquired from RFID antennas require advanced techniques for feeding, gains and radiation patterns. After an introduction to RFID technology itself (principle and characteristics of different RFID tags), the article offers some examples of applications of this technology in everyday life or in the industry. In order to use radio frequency identification (RFID) antenna for wireless communication and real world applications military and personal communication systems, mobile phones, personal digital assistant (PDA), blue-tooth systems, wireless local area networks (WLAN), road tolling systems, animal traceability etc, studying the nature and characteristics of the antenna is an important use. A novel printed antenna is proposed for Radio Frequency Identification. The antenna has a much wider bandwidth than known printed antenna, mostly planar antennas. The antenna geometry is much smaller than a printed dipole antenna at the same frequency band.DOI:http://dx.doi.org/10.11591/ijece.v4i1.475

Denial-of-Service attacks on 6LoWPAN-RPL networks: Issues and practical solutions

Dados do Censo Escolar de 2011 informam que cerca de um milhão de alunos brasileiros estudavam em classes multisseriadas de escolas do campo. Entretanto, conforme levantamento do INEP (2007), a qualidade da educação dessas escolas não é a esperada pelos órgãos públicos de gestão. Para compreender como é organizada, do ponto de vista pedagógico, uma classe multisseriada inserida no Programa Escola Ativa do MEC, foram observadas aulas e realizadas entrevistas com uma professora de escola do campo do município de Novo Hamburgo/RS. As ferramentas teóricas do estudo estão vinculadas com as teorizações sobre poder de Michel Foucault. Quando da análise do material empírico a respeito da distribuição do tempo, do espaço e dos conteúdos estudados na classe multisseriada, foi possível perceber a existência de movimentos de contraconduta por parte da professora, que não se submeteu ao que era indicado pelo programa oficial do governo

Intrusion detection architecture based on neighbor behavior surveillance

Even when 6LoWPAN has an ideal cryptographyline defense, it is still necessary to implement an intrusiondetection system (IDS) to deal with threats targeting networkperformance such as Denial of Service attacks. IDS discover andstop most attacks that make changes on the operation of thenetwork. However, few IDS solution has been proposed for6LoWPAN networks. IDS missions are to monitor and raise analarm about any possible threats and pass it to the system torestart the keying process for eliminating the attackers. Newtechnique has been proposed recently based on the principle thatneighbor nodes have a trend to have the same behavior, so thedetection of the malicious node is based on the detection of theabnormal node that has a bad behavior different than itneighbors. The security goal is to provide a monitoring systemthat will attempt to detect anomalous malicious behavior and toprevent it from harming the network performance basing on theneighbors nodes behavior monitoring

Platform-Driven Design for serious games, Collaboration and Multilayer methodology

Abstract. The multilayer methodology involves several concepts for serious game design; it can increase the collaboration between several actors of design, obtaining a more efficient serious game. Although it requires a specific environment to provide an effective assistance and visibility during the development of serious games, it improves on the combination of learning and entertainment fields. In this paper, we present the multilayer methodology and how can actors collaborate to provide an effective design, then, we study the implementation of the methodology on an online platform. This methodology can make the design process more structured and improve the collaboration purpose. Finally, we propose a new environment of serious game design