Abstract
Handheld controllers are standard in immersive virtual reality (iVR), but the rise of natural hand-based interactions exposes the limitations of hand gestures, especially for point-and-click tasks with graphical user interfaces (GUI). This shows the need to explore alternative hands-free selection methods. Unlike most studies focusing on the selection task itself, this work evaluates the impact of such methods on multiple dimensions when selections occur alongside another primary task. The tested methods were: head gaze + dwell, leaning, and voice; eye gaze + dwell, leaning, blinking, and voice; and voice-only. Controllers served as the baseline. Methods were further analyzed by pointing and confirming mechanisms. Four dimensions were analyzed: (1) iVR experience, (2) user satisfaction, (3) usability, and (4) efficiency and effectiveness. With 72 participants, results show hands-free methods provide comparable experiences to controllers, suggesting selection methods have a lower impact on the user experience when users focus on a primary task.

Abstract
In the field of gaming artificial intelligence, selecting the appropriate machine learning approach is essential for improving decision-making and automation. This paper examines the effectiveness of deep reinforcement learning (DRL) within interactive gaming environments, focusing on complex decision-making tasks. Utilizing the Unity engine, we conducted experiments to evaluate DRL methodologies in simulating realistic and adaptive agent behavior. A vehicle driving game is implemented, in which the goal is to reach a certain target within a small number of steps, while respecting the boundaries of the roads. Our study compares Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) in terms of learning efficiency, decision-making accuracy, and adaptability. The results demonstrate that PPO successfully learns to reach the target, achieving higher and more stable cumulative rewards. Conversely, SAC struggles to reach the target, displaying significant variability and lower performance. These findings highlight the effectiveness of PPO in this context and indicate the need for further development, adaptation, and tuning of SAC. This research contributes to developing innovative approaches in how ML can improve how player agents adapt and react to their environments, thereby enhancing realism and dynamics in gaming experiences. Additionally, this work emphasizes the utility of using games to evolve such models, preparing them for real-world applications, namely in the field of vehicles' autonomous driving and optimal route calculation.

Abstract
[No abstract available]

Abstract
The Web of Things (WoT) is an essential component within the Internet of Things (IoT) domain, offering a standardized method for describing, consuming, and orchestrating the functions of IoT devices. WoT plays a crucial role in promoting interoperability and streamlining the development of applications for IoT solutions. Recent research focusing on IoT solutions for ambient assisted living (AAL) has highlighted WoT as a key framework for integrating diverse smart devices and services to enhance the quality of life for older adults and individuals with specific health conditions. However, a closer look at recent literature reviews reveals a deficiency in comprehensive research regarding the interplay between WoT, AAL, and the health and wellbeing of older adults. To address this question, a comprehensive mapping review is performed to delve into the existing literature and pinpoint the most pertinent themes and topics within WoT. This analysis aims to uncover evidence of the correlation between WoT, AAL, and active and healthy aging (AHA) to support future research in this area.

Abstract
With industry evolution and the development of Industry 4.0, manufacturers are trying to leverage it and find a way to increase productivity. Digital Twins (DT) technologies allow them to achieve this objective and revolutionize Product Life-cycle Management as they provide real-time information and insights for companies, allowing real-time product monitoring. Virtual Reality (VR) is a technology that permits users to interact with virtual objects in immersive environments; even under constant development, VR has proven efficient and effective in enhancing training. DT integration into immersive VR environments is constantly developing, with many challenges ahead. This study aims the development of an immersive virtual world for training integrated with DT technologies to handle all users' input using the simulator. Those were subject to a performance evaluation to understand how the application handles different input types, which confirmed the viability and reliability of this integration.