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
This paper presents a usability evaluation of a companion application for managing older adults' physical activity sessions in an immersive multiuser virtual environment. The companion application was designed to facilitate the trainer ' s role and enhance the overall user experience in the virtual multiuser environment. Four trainers were recruited to participate in the study, they performed two tasks to prepare and manage training sessions with older adults using the companion application. Researchers used an open-ended questionnaire to interview the participants. The results revealed a high satisfaction and appreciation for the application features used to prepare and manage the training sessions. Participants found the application useful and intuitive, and they also recommended a list of future desirable features related to the application ' s feedback and help mechanisms, as well as its content. In addition to the necessity to provide mobile and tablet versions of the application. A few usability problems were detected related to information presentation and navigation. The future design of the companion application will consider all the detected usability problems and desired features.

Abstract
Coronary artery calcium is a good indicator of coronary artery disease and can be used for cardiovascular risk stratification. Over the years, different deep learning approaches have been proposed to automatically segment coronary calcifications in computed tomography scans and measure their extent through calcium scores. However, most methodologies have focused on using 2D architectures which neglect most of the information present in those scans. In this work, we use a 3D convolutional neural network capable of leveraging the 3D nature of computed tomography scans and including more context in the segmentation process. In addition, the selected network is lightweight, which means that we can have 3D convolutions while having low memory requirements. Our results show that the predictions of the model, trained on the COCA dataset, are close to the ground truth for the majority of the patients in the test set obtaining a Dice score of 0.90 +/- 0.16 and a Cohen's linearly weighted kappa of 0.88 in Agatston score risk categorization. In conclusion, our approach shows promise in the tasks of segmenting coronary artery calcifications and predicting calcium scores with the objectives of optimizing clinical workflow and performing cardiovascular risk stratification.

Abstract

Abstract
Data management solutions became highly expensive and ineffective mainly due to the lack of transparent processes and procedures to measure and provide clear guidance on the steps needed to implement them. The organizations and specialists agree that the only manner solve the data management issues requires the implementation of data governance. Many of those attempts had failed previously because they were based only on IT, with rigid processes and activities frequently split by systems or the areas supported by systems and their data. It shows that Data governance has been acquiring significant relevance. However, a consensus or even a holist approach was not achieved so far. This paper that is part of an ongoing thesis research that aims to identify the main gaps and opportunities by summarizing and study the literature consistently and as result at the end of the research it will propose a standard framework for data governance measuring its impact on the Data Governance maturity level before and after its implementation and thus as contribute to the community by trying to mitigate the problems found.

Abstract
This systematic literature review investigates the factors influencing cloud computing adoption within both educational and organizational settings. By synthesizing a comprehensive body of research, this study finds and analyzes the determinants that shape the decision-making process about cloud technology adoption. Security, cost-effectiveness, scalability, interoperability, and regulatory compliance are examined across educational institutions and organizational contexts. Additionally, socio-economic, political, and technological factors specific to each context are explored to provide a nuanced understanding of the challenges and opportunities associated with cloud computing adoption. The review reveals commonalities and differences in adoption drivers and barriers between education and organizational environments, offering insights into tailored strategies for effective implementation. This research contributes to the existing literature by shedding light on the multifaceted nature of cloud adoption and offering valuable guidance for educators, organizational leaders, policymakers, and technology providers looking to use cloud computing to enhance operations and services.