Abstract
The massive industrialization of products in a factory environment requires testing the product at a stage before its exportation to the sales market. For example, the end-of-line tests at Continental Advanced Antenna contribute to the validation of an antenna's functionality, a product manufactured by this organization. In addition, the storage of information from the testing process allows the data manipulation through automated machine learning algorithms in search of a beneficial contribution. Studies in this area (automatic learning/machine learning) lead to the search and development of tools designed with objectives such as preventing anomalies in the production line, predictive maintenance, product quality assurance, forecast demand, forecasting safety problems, increasing resources, proactive maintenance, resource scalability, reduced production time, and anomaly detection, isolation, and correction. Once applied to the manufacturing environment, these advantages make the EOL system more productive, reliable, and less time-consuming. This way, a tool is proposed that allows the visualization and previous detection of trends associated with faults in the antenna testing system. Furthermore, it focuses on predicting failures at Continental's EOL.

Abstract
This paper presents an educational resource to support the teaching of Portuguese sign language. This educational resource emerges in response to the significant needs for the development of adequate digital tools to support deaf people in different tasks, especially in the language learning process. This work is motivated by the results and conclusions from previous studies that identify augmented reality as one of the promising solutions to improve the learning and teaching processes, and benefits from the advances already accomplished in the development and application of augmented reality solutions in several domains of the educational environment. The educational resource presented in this work is an augmented reality solution that enables associating hand gestures, representative of Portuguese sign language, to different cards, which represent different letters of the alphabet. In this way, it is possible to associate the alphabet letters with the respective gestures in a visual and straightforward way, facilitating the learning process.

Abstract
In the last 30 years, several academic and commercial projects have explored the context-awareness concept in multiple domains. Ubiquitous computing and ambient intelligence are features associated with the 4th generation industry empowering space to interact and respond appropriately according to context. In the scope of Industry 4.0, context-aware systems aim to improve productivity in smart factories and offer assistance to workers through services, applications, and devices, delivering functionalities and contextualised content. This article, through descriptive research, discusses the concepts related to context, presents and analyses projects related to ubiquitous computing and associated with Industry 4.0, and discusses the main challenges in systems and applications development to support intelligent environments for increased productivity, supporting informed decision-making in the factories of the future. The study results indicate that many research questions regarding the analysed projects remain the same, leading the research in the context-aware systems area to minimise issues related to context-aware features, improving the incorporation of Industry 4.0 paradigm concepts. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Regular video cameras shoot normally at 25/30 frames per second (fps). Actually there are available in the market equipments that allow us to acquire video at 1.000.000 fps. When we observe a video sequence it becomes noticeable that great part of the information remains unchanged regardless of the bit rate or frame rate used. One origin of discontinuity in video signals is directly related to movement. Several areas use high frame rate images to analyze and comprehend certain events or effects, biomechanical engineering is one of them. Biomechanics engineering studies the mechanics of a living body, especially the forces exerted by muscles and gravity on the skeletal structure. Some examples are athlete assessment, were images are capture and then the acquired parameters are analyzed. This article describes a new methodology to decrease the space needed to store high frame rate image sequences in the specific case of biomechanical related areas.

Abstract
With the recent expansion of services available in the Web, the Internet is becoming more and more a network of services, at a global scale. These services cover the majority of business areas, such as: bank account management, trip reservation, hotel bookings, information search portals, social networks, etc. A related subarea is the georreferencing of objects and people. The appearance of services like Google Earth and Virtual Earth has created enormous Web based service creation opportunities, allowing the interconnection of the digital and real worlds. In this work we present a project intended for locating the physical places associated with a person, based on his email address. This project implements a search portal that associates a user to an email and a set of user defined locations.

Abstract
Assistive technology enables people to achieve independence in the accomplishment of their daily tasks and enhance their quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of information or given insufficient information about their surrounding environment. With the recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities during their mobility. In this context we propose a new algorithm to recognize landmarks suitably placed on sidewalks. The proposed algorithm uses a combination of Peano-Hilbert Space Filling Curves for dimension reduction of image data and Ensemble Empirical Mode Decomposition (EEMD) to pre-process the image, resulting on a fast and efficient recognition method and revealing a promising solution.