Abstract
Technology has profoundly changed the way we learn and live. Indeed, such relationship appears to be quite complex, within IT contexts, and especially in socially and technologically rich learning environments, where related skills and learning are progressively required and fostered. Thus, if a satisfactory level of intellectual performance and social competence of a primary school pupil is indeed highly dependent on the type of participation that parents offer their children, IT, in general, and Internet, in particular, may well provide a new paradigm, setting forth that education and communication approach is truly more complex than ever before. It is on the basis of such paradigm that we therefore present a case study where a set of multimedia exercises were used in order to possibly improve the mathematical skills of pupils, one with mental retardation and another with cerebral palsy. Being part of a Web-based system to support students' learning, the referred set of multimedia exercises proved to be the children's favorite, rather than exercises in paper form, which also led the children to show a fair more positive attitude towards learning. Also, we observed that through the mentioned multimedia exercises, the children became far more autonomous, interested, persistent, happy, and able to easily absorb the material as well as more willingly to continue on working.

Abstract

Abstract
The manual monitoring of refilling stations in industrial environments can lead to inefficiencies and errors, which can impact the overall performance of the production line. In this paper, we present an unsupervised detection pipeline for identifying refilling stations in industrial environments. The proposed pipeline uses a combination of image processing, pattern recognition, and deep learning techniques to detect refilling stations in visual data. We evaluate our method on a set of industrial images, and the findings demonstrate that the pipeline is reliable at detecting refilling stations. Furthermore, the proposed pipeline can automate the monitoring of refilling stations, eliminating the need for manual monitoring and thus improving industrial operations’ efficiency and responsiveness. This method is a versatile solution that can be applied to different industrial contexts without the need for labeled data or prior knowledge about the location of refilling stations. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

Abstract
This study presents a novel approach to cope with the human behaviour uncertainty during Human-Robot Collaboration (HRC) in dynamic and unstructured environments, such as agriculture, forestry, and construction. These challenging tasks, which often require excessive time, labour and are hazardous for humans, provide ample room for improvement through collaboration with robots. However, the integration of humans in-the-loop raises open challenges due to the uncertainty that comes with the ambiguous nature of human behaviour. Such uncertainty makes it difficult to represent high-level human behaviour based on low-level sensory input data. The proposed Fuzzy State-Long Short-Term Memory (FS-LSTM) approach addresses this challenge by fuzzifying ambiguous sensory data and developing a combined activity recognition and sequence modelling system using state machines and the LSTM deep learning method. The evaluation process compares the traditional LSTM approach with raw sensory data inputs, a Fuzzy-LSTM approach with fuzzified inputs, and the proposed FS-LSTM approach. The results show that the use of fuzzified inputs significantly improves accuracy compared to traditional LSTM, and, while the fuzzy state machine approach provides similar results than the fuzzy one, it offers the added benefits of ensuring feasible transitions between activities with improved computational efficiency.

Abstract
The use of technology applied in sports comes each year becoming a great tool to help athletes train. Moreover, the post-pandemic world is undergoing dramatic changes in the way of thinking and acting, with new ways of exercising emerging, but without leaving home. Thus this paper describes the development of a platform for training, focusing on Kendo practitioners (Japanese fencing) using virtual reality tools to allow athletes and training the distance. Through the use of a HMD (Head Mounted Device), kendokas will be able to practice blows and improve their reflex by a gamified experience in a virtual environment. © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)