This work describes a bibliometric analysis of the literature on the use of computer vision algorithms in Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Extended Reality (XR) environments. The analysis aims to highlight the evolution, trends, and effects of research in this field. This review provides an overview of immersive technologies and their applications, as well as the role of computer vision algorithms in enabling these technologies and the potential benefits of using such algorithms. This study identifies important authors, institutions, and research themes by using bibliometric indicators such as citation counts, co-citation analysis, and network analysis. The analysis also identifies gaps and opportunities for additional research in this area, as well as a critical assessment of the quality and relevance of the publications.

BACKGROUND: Secondary use of health data is a valuable source of knowledge that boosts observational studies, leading to important discoveries in the medical and biomedical sciences. The fundamental guiding principle for performing a successful observational study is the research question and the approach in advance of executing a study. However, in multi-centre studies, finding suitable datasets to support the study is challenging, time-consuming, and sometimes impossible without a deep understanding of each dataset. METHODS: We propose a strategy for retrieving biomedical datasets of interest that were semantically annotated, using an interface built by applying a methodology for transforming natural language questions into formal language queries. The advantages of creating biomedical semantic data are enhanced by using natural language interfaces to issue complex queries without manipulating a logical query language. RESULTS: Our methodology was validated using Alzheimer's disease datasets published in a European platform for sharing and reusing biomedical data. We converted data to semantic information format using biomedical ontologies in everyday use in the biomedical community and published it as a FAIR endpoint. We have considered natural language questions of three types: single-concept questions, questions with exclusion criteria, and multi-concept questions. Finally, we analysed the performance of the question-answering module we used and its limitations. The source code is publicly available at https://bioinformatics-ua.github.io/BioKBQA/. CONCLUSION: We propose a strategy for using information extracted from biomedical data and transformed into a semantic format using open biomedical ontologies. Our method uses natural language to formulate questions to be answered by this semantic data without the direct use of formal query languages.

Over the last two years, the COVID-19 pandemic has affected hundreds of millions of people around the world. As in many crises, people turn to social media platforms, like Twitter, to communicate and share information. Twitter datasets have been used over the years in many research studies to extract valuable information. Therefore, several large COVID-19 Twitter datasets have been released over the last two years. However, none of these datasets contains only Portuguese Tweets, despite the Portuguese Language being reported as one of the top five languages used on Twitter. In this paper, we present the first large-scale Portuguese COVID-19 Twitter dataset. The dataset contains over 19 million Tweets spanning 2020 and 2021, allowing the entire pandemic to be analyzed. We also conducted a sentiment analysis on the dataset and correlated the various spikes in Tweet count and sentiment scores to various news articles and government announcements in Portugal and Brazil. The dataset is available at: https://github.com/bioinformatics-ua/Portuguese-Covid19-Dataset

Today, medical studies enable a deeper understanding of health conditions, diseases and treatments, helping to improve medical care services. In observational studies, an adequate selection of datasets is important, to ensure the study's success and the quality of the results obtained. During the feasibility study phase, inclusion and exclusion criteria are defined, together with specific database characteristics to construct the cohort. However, it is not easy to compare database characteristics and their evolution over time during this selection. Data comparisons can be made using the data properties and aggregations, but the inclusion of temporal information becomes more complex due to the continuous evolution of concepts over time. In this paper, we propose two visualisation methods aiming for a better description of data evolution in clinical registers using biomedical standard vocabularies.

The problem of choosing a specialty and direction when entering higher education, is now more and more urgent. Every year, according to statistics in Kazakhstan, more than 60% of university graduates do not work in their speciality of choice. This problem is more often associated with the fact that students choose a speciality and apply for a grant, and in the process of learning they understand that they do not want to work as a engineer for example and tries to find another work. Some of that problem could have been prevented if professional orientation in secondary education had been conducted in schools of Kazakhstan. Career guidance is a number of activities that need to be carried out systematically in primary and high schools. There is a lot of information available in the Internet, but being a schoolboy, a student of grade 9-10, it is very difficult to find reliable information. Consciously make an admission plan and go step by step to the goal. In my application there will be one centralized database, which would allow you to first undergo diagnostics, then make the right choice of direction and speciality. As a result, get a plan for admission to a university in any country. This article reviews the information and reference material, analyzes the market and current specialties in Kazakhstan for further employment, as well as all the necessary information to diagnose their abilities and build an individual plan for admission to university.

In early childhood education, there are several techniques to understand children’s development in kindergarten. One of these techniques is based on Portfolios that, in early childhood education, allows the understanding of the progress of the child, allowing a shared reflection with the child, teachers, and the child’s parents towards the understanding on the child’s learning process. The work described in this paper has as its main objective the development of a web application, which allows support for the construction of a platform for the storage and sharing of digital portfolios for early childhood education. In addition, it is intended that an access control of users be made so that it is possible to manage access to certain portfolios or sub-parts of them. The system has features such as: creating portfolios, creating notes, and managing user permissions. After the application was implemented, usability tests were carried out, with the participation of teachers. Through the techniques and methodologies used, it was possible to create a web tool to aid in the creation of portfolios for early childhood education, allowing the registering of audio, video, or image files. In addition, the system allows the sharing of portfolios with different users of the system who, in turn, can perform actions in the portfolio according to their role in the system.

Abstract Over the years, a growing number of semantic data repositories have been made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user’s expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this difficulty have suggested using question answering (QA) systems to provide user‐friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full‐text articles published since 2015 on methods and systems for KBQAs. Sixty‐six articles were reviewed to describe their underlying reference architectures.

Researchers have been using semantic technologies as essential tools to structure knowledge. This is particularly relevant in the biomedical domain, where large dataset are continuously generated. Semantic technologies offer the ability to describe data and to map and linking distributed repositories, creating a network where the searching interface is a single entry point. However, the increasing number of semantic data repositories that are publicly available is creating new challenges related to its exploration. Despite being human and machine-readable, these technologies are much more challenging for end-users. Querying services usually require mastering formal languages and that knowledge is beyond the typical user's expertise, being a critical issue in adopting semantic web information systems. In particular, the questioning of biomedical data presents specific challenges for which there are still no mature proposals for production environments. This paper presents a solution to query biomedical semantic databases using natural language. The system is at the intersection between semantic parsing and the use of templates. It makes it possible to extract information in a friendly way for users who are not experts in semantic queries.

Oral health in the daily lives of individuals allows health promotion and prevention. Oral health literacy is fundamental to enable people to have the knowledge and be aware of its importance, enabling them to process, evaluate and apply information on this topic. Serious games, in the educational domain, can be used to assist in this literacy. This article carries out systematic mapping of these games in the field of oral health. The mapping included work carried out in the last 5 years and indexed in four repositories. As result it was found that there are few serious games for oral health, and few have a well-defined process for learning.

Lifelong learning implies that people are willing to change their attitude, way of thinking or acting, usually based on some objective. For that, a decision game was developed for iOS and Android devices, using the Unity Game Engine. The premise of the game puts the player in the role of a business manager facing situations that require a decision. The game presents a card based mechanics, allowing the player to choose between two options, sliding the card to the right or to the left, influencing the outcome of the game. The game allows to use different decks of cards. The experience was assessed with the assistance of three instruments: closed questions questionnaire, written exams before and after playing the game and observation.

The SeMI - Interactive Musical Setting, explores the possibilities of joining machine learning, the physical and the sound world. In this context, a machine learning algorithm and model was used to identify physical objects through image processing. Each physical object is associated with a student’s produced musical texture that starts playing when the object is recognized by the device. This allows defining use cases in which students have to develop diverse although interrelated sound textures and combine them with a physical world, in both a fake orchestra, that reacts to people and objects in front of it, and mood rooms, for example. The application was developed for iPad and iPhone, using Swift programming language and the iOS operating system and used in the classes of the masters on Teaching of Musical Education in the Basic School.

Learning Management Systems (LMS) are mainly used as a didactic support for the presential classes. However, because of the tools they provide, they are also essential to support b-learning and e-learning process. Because of this, most universities rely on some LMS through many or all of the courses. This paper describes a study performed in two different universities regarding the students’ perception about the usefulness and the usability of two different LMS: Moodle and Sakai. Through a focus group, students shared their opinion and discussed about their experience. In addition, data from the log of the platforms was also analysed, to assess how teachers use the LMS tools. In general, it can be stated that when the teacher knows how to use the LMS, students feel more comfortable using it and have a better learning experience. Regarding the tools, teachers mostly rely on the repository of documents.

Quality in education depend heavily on the teachers’ professional development, as a mean for pedagogical methodologies and practice improvement. In this sense, learning is enhanced by sharing and working in a community of practice, a learning organization that generate knowledge and allow members to innovate. In this context, children observation is fundamental, allowing a sound basis for reflection and action around learning experiences and teaching environments. Specific guidelines and programs, such as the EEL/DQP, can help reducing the inherent subjectivity, providing a common base for teachers and the preschool education community. In this paper we propose an online, web based community to improve the observation process as well as the communication between researchers. The social relations are identified and the security issues are discussed.

Children observation is a time consuming and complex process that involves time and knowledge. However, when performed adequately, it is fundamental for both child and professionals development, allowing a sound basis for reflection and action around learning experiences and teaching environments. Following specific guidelines and programs can help the teachers reduce inherent subjectivity. The EEL/DQP was developed to evaluate and improve quality in preschool education. This program is enhanced by using a rigorous observation process of children and adults. In this paper we propose an unified data model to structure the information from the thirteen steps of the EEL/DQP. Moreover, we also describe a smartphone application to assist the observer, recording notes, sound, photos and video.

In this paper we describe the architecture, the development and the assessment results of an SNMP agent that allows MASIF (mobile agent system interoperability facilities) compliant platforms to be managed through SNMP. The major outcome of this work is a simple integration of mobile agent technology with any well-established commercial network management system.

A wireless network with metropolitan coverage was created to fulfill the data communication requirements for the Braganca Digital City program, part of the Portuguese Digital Cities initiative. The wireless metropolitan area network, based on IEEE 802.11b, still provides both a performant and an economical solution, tailored to the application scenario. Performance measurements have been done in order to apprehend the real network throughput under typical user applications and to have insight into other network characteristics, typical of the wireless medium. A comparison with a wired counterpart is also provided.