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)

Abstract
Slight variations in user interface response times can significantly impact the user experience provided by an interface. Load testing is used to evaluate how an application behaves under increasing loads. For interactive applications, load testing can be done by directly calling services at the business logic or through the user interface. In modern web applications, there is a considerable amount of control logic on the browser side. The impact of this logic on applications' behaviour is only fully considered if the tests are done through the user interface. Capture reply tools are used for this, but their use can become costly. Leveraging an existing model-based testing tool, we propose an approach to automate load testing done through the user interface.

Abstract
In recent years, several regulatory initiatives have been carried out at the European Commission level to ensure the ethical use of Artificial Intelligence, including the General Data Protection Regulation, Data Governance Act, or the Artificial Intelligence Act. However, there is also a need for technological solutions that effectively enable the implementation of this regulation in a realistic and efficient way. The main goal of this work is to propose and implement such a technological solution, relying on the notion of observability. The hypothesis is that a set of ethics metrics can be implemented along a domain-agnostic Data Science/Artificial Intelligence pipeline. These metrics, when observed in real time, will allow not only to assess the level of compliance of the pipeline with ethics standards at different levels, but also allow for a timely reaction by the organization when the data, the model or any other artifact in the pipeline exhibits undesired behavior. In this way, some of the most important ethical principles of AI are guaranteed: responsibility and prevention of harm. This work aims to identify a large group of ethics metrics, implement them, map them onto the different stages of a typical Data Science / AI process, and determine whether the presence of these metrics ensures or contributes to the development of AI solutions that can be considered ethical according to the latest European regulation.

Abstract
This study explores the role of talent in the processes of innovation, intrapreneurship, and internationalisation of startups. For this purpose, an empirical study was conducted with 226 Portuguese startups, and the impact of these components was analysed using the structural equation model. The findings indicate that talent attraction, development, and retention practices have a positive impact on innovation. However, the same correlation was not verified for intrapreneurship practices. Furthermore, both innovation and intrapreneurship are two determining elements in startups’ internationalisation activities. This study offers pertinent contributions to the establishment of policies to support the internationalisation processes of startups, in which talent management emerges as a determining factor for its sustainable growth. Copyright © 2023 Inderscience Enterprises Ltd.

Abstract
Companies are increasingly focusing on audiovisual content as part of their strategy, and YouTube being a massive video hosting platform that makes content sharing possible has been the most successful platform for reaching their consumers products and services. Researches have proven that user-generated content impacts brand engagement, loyalty and firm revenue. Therefore, it is necessary to determine what factors stimulate the creation of consumers perceived value from user-generated content, on social media. We analyze the driving factors of user-generated content on YouTube and its influence on consumers perceived value. The sample data consists of 282 YouTube users’ responses collected through an electronic survey. This research contributes toward the digital content marketing literature by complementing existing research exploring consumer behavior on social media, assessing the driving factors of user-generated content and its impacts on customer perceived value. The study findings provide academic contributions and several challenges for firm and user-generated content, on actions they can tackle. Finally, based on the study limitations, we discuss future research in generated content in social media, providing insights for future research directions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Abstract
With the recent advancements in wireless networks, Joint Communication and Sensing (JCAS) has become a growing field that is expected to be included in next-generation standards. However, not only is the current performance of the sensing ability still lacking to be used in real-world scenarios, proper security of such privacy-invasive technology has not been fully explored. To this end, we propose the creation of a more robust framework, capable of cross-domain detection and long-term analysis for improved detection, which will also serve as the basis for a security and privacy analysis of the threat landscape and solutions in this field.