Multiuser Diversity Management for Multicast/Broadcast Services in 5G and Beyond Networks

The envisaged fifth-generation (5G) and beyond networks represent a paradigm shift for global communications, offering unprecedented breakthroughs in media service delivery with novel capabilities and use cases. Addressing the critical research verticals and challenges that characterize the International Mobile Telecommunications (IMT)-2030 framework requires a compelling mix of enabling radio access technologies (RAT) and native softwarized, disaggregated, and intelligent radio access network (RAN) conceptions. In such a context, the multicast/broadcast ser vice (MBS) capability is an appealing feature to address the ever-growing traffic demands, disruptive multimedia services, massive connectivity, and low-latency applications. Embracing the MBS capability as a primary component of the envisaged 5G and beyond networks comes with multiple open challenges. In this research, we contextualize and address the necessity of ensuring stringent quality of service (QoS)/quality of experience (QoE) requirements, multicasting over millimeter-wave (mmWave) and sub-Terahertz (THz) frequencies, and handling complex mobility behaviors. In the broad problem space around these three significant challenges, we focus on the specific research problems of effectively handling the trade-off between multicasting gain and multiuser diversity, along with the trade-off between optimal network performance and computational complexity. In this research, we cover essential aspects at the intersection of MBS, radio resource management (RRM), machine learning (ML), and the Open RAN (O-RAN) framework. We characterize and address the dynamic multicast multiuser diversity through low-complexity RRM solutions aided by ML, orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques in 5G MBS and beyond networks. We characterize the performance of the multicast access techniques conventional multicast scheme (CMS), subgrouping based on OMA (S-OMA), and subgrouping based on NOMA (S-NOMA). We provide conditions for their adequate selection regarding the specific network conditions (Chapter 4). Consequently, we propose heuristic methods for the dynamic multicast access technique selection and resource allocation, taking advantage of the multiuser diversity (Chapter 5.1). Moreover, we proposed a multicasting strategy based on fixed pre-computed multiple-input multiple-output (MIMO) multi-beams and S-NOMA (Chapter 5.2). Our approach tackles specific throughput requirements for enabling extended reality (XR) applications attending multiple users and handling their spatial and channel quality diversity. We address the computational complexity (CC) associated with the dynamic multicast RRM strategies and highlight the implications of fast variations in the reception conditions of the multicast group (MG) members. We propose a low complexity ML-based solution structured by a multicast-oriented trigger to avoid overrunning the algorithm, a K-Means clustering for group-oriented detection and splitting, and a classifier for selecting the most suitable multicast access technique (Chapter 6.1). Our proposed approaches allow addressing the trade-off between optimal network performance and CC by maximizing specific QoS parameters through non-optimal solutions, considerably reducing the CC of conventional exhaustive mechanisms. Moreover, we discuss the insertion of ML-based multicasting RRM solutions into the envisioned disaggregated O-RAN framework (Chapter 6.2.5). We analyze specific MBS tasks and the importance of a native decentralized, softwarized, and intelligent conception. We assess the effectiveness of our proposal under multiple numerical and link level simulations of recreated 5G MBS use cases operating in μWave and mmWave. We evaluate various network conditions, service constraints, and users’ mobility behaviors

Organic transformation of ERP documentation practices: Moving from archival records to dialogue-based, agile throwaway documents

Implementing enterprise resource planning (ERP) systems remains challenging and requires organizational changes. Given the scale and complexity of ERP projects, documentation plays a crucial role in coordinating operational details. However, the emergence of the agile approach raises the question of how adequate lightweight documentation is in agile ERP implementation. Unfortunately, both academia and industry often overlook the natural evolution of documentation practices. This study examines current documentation practices through interviews with 23 field experts to address this oversight. The findings indicate a shift in documentation practices from retrospective approaches to dialogue-based, agile throwaway documents, including audiovisual recordings and informal emails. Project managers who extensively engage with throwaway documents demonstrate higher situational awareness and greater effectiveness in managing ERP projects than those who do not. The findings show an organic transformation of ERP documentation practices. We redefine documentation to include unstructured, relevant information across different media, emphasizing searchability. Additionally, the study offers two vignettes for diverse organizational contexts to illustrate the best practices of agile ERP projects.Organic transformation of ERP documentation practices: Moving from archival records to dialogue-based, agile throwaway documentspublishedVersionPaid open acces

User Perceptions of Different Vital Signs Monitor Modalities During High-Fidelity Simulation: Semiquantitative Analysis

Background: Patient safety during anesthesia is crucially dependent on the monitoring of vital signs. However, the values obtained must also be perceived and correctly classified by the attending care providers. To facilitate these processes, we developed Visual-Patient-avatar, an animated virtual model of the monitored patient, which innovatively presents numerical and waveform data following user-centered design principles. After a high-fidelity simulation study, we analyzed the participants' perceptions of 3 different monitor modalities, including this newly introduced technique. Objective: The aim of this study was to collect and evaluate participants' opinions and experiences regarding 3 different monitor modalities, which are Visual-Patient-avatar, Split Screen (avatar and Conventional monitor alongside each other), and Conventional monitor after using them during simulated critical anesthetic events. Methods: This study was a researcher-initiated, single-center, semiquantitative study. We asked 92 care providers right after finishing 3 simulated emergency scenarios about their positive and negative opinions concerning the different monitor modalities. We processed the field notes obtained and derived the main categories and corresponding subthemes following qualitative research methods. Results: We gained a total of 307 statements. Through a context-based analysis, we identified the 3 main categories of "Visual-Patient-avatar," "Split Screen," and "Conventional monitor" and divided them into 11 positive and negative subthemes. We achieved substantial interrater reliability in assigning the statements to 1 of the topics. Most of the statements concerned the design and usability features of the avatar or the Split Screen mode. Conclusions: This study semiquantitatively reviewed the clinical applicability of the Visual-Patient-avatar technique in a high-fidelity simulation study and revealed the strengths and limitations of the avatar only and Split Screen modality. In addition to valuable suggestions for improving the design, the requirement for training prior to clinical implementation was emphasized. The responses to the Split Screen suggest that this symbiotic modality generates better situation awareness in combination with numerical data and accurate curves. As a subsequent development step, a real-life introduction study is planned, where we will test the avatar in Split Screen mode under actual clinical conditions. Keywords: avatar; patient monitoring; semiquantitative research; simulation study; situation awareness; user-centered design; visual-patient-avata

Multimodal Large Language Models: A Survey

The exploration of multimodal language models integrates multiple data types, such as images, text, language, audio, and other heterogeneity. While the latest large language models excel in text-based tasks, they often struggle to understand and process other data types. Multimodal models address this limitation by combining various modalities, enabling a more comprehensive understanding of diverse data. This paper begins by defining the concept of multimodal and examining the historical development of multimodal algorithms. Furthermore, we introduce a range of multimodal products, focusing on the efforts of major technology companies. A practical guide is provided, offering insights into the technical aspects of multimodal models. Moreover, we present a compilation of the latest algorithms and commonly used datasets, providing researchers with valuable resources for experimentation and evaluation. Lastly, we explore the applications of multimodal models and discuss the challenges associated with their development. By addressing these aspects, this paper aims to facilitate a deeper understanding of multimodal models and their potential in various domains.Comment: IEEE BigData 2023. 10 page

Emulating Home Automation Installations through Component-based Web Technology

The Internet of Things mechanisms enable the management of home environments since they can be developed as IoT based information systems. From standard smart homes to automated buildings, including other kind of domotics and inmotics solutions, every system must be tested and validated before its installation. The current tools offered by IoT and home automation vendors lack in emulation features close to the real behavior of the devices. In many cases, delaying the verification actions until the hardware is acquired and installed may cause some drawbacks, for example, from the economic point of view. This paper presents a solution for emulating home automation environments which are based on the KNX standard and can be represented by architectures of devices. The emulation consist of developing virtual implementations of real devices which operate and communicate through web technology. The technology implementing these virtual devices allows us to develop components which can provide different type of data related to the installation (audio, video, text, animations, images, etc.). The architectures can be managed using web services and their behavior can be tested through web user interfaces showing the mentioned data. Furthermore, virtual and physical devices are connected to validate the interoperability between the real installation and the emulation

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

Beyond traditional manuals: A comparative analysis of instruction manual effectiveness in handheld consumer products

Modern consumer products often come with instruction manuals that play a crucial role in guiding users through their complexities. However, a widespread lack of enthusiasm among consumers to engage with these manuals is rooted in negative experiences. This research evaluated the usability and effectiveness of traditional paper-based instruction manuals versus the redesigned version, using the HS210 drone as a case study. Employing a dual-phase methodology, this study first conducted a thorough analysis of the HS210 drone's existing paper manual, identifying its strengths, weaknesses, and user perceptions. The subsequent phase entailed the creation and evaluation of an improved manual informed by initial findings. This comparative analysis sought to measure user performance, experience, and preference regarding both the original and redesigned instruction manuals, aiming to enhance engagement and effectiveness in drone operational guides. Data collection utilized a comprehensive methodological approach, incorporating contextual inquiry, think-aloud protocols during usability tests, a pre-test survey, and post-test semi-structured interviews. The findings revealed a pronounced preference for multimedia instruction manuals, showcasing higher levels of user satisfaction, better engagement with the manuals, and significantly enhanced usability. This research underscored the potential of innovative instructional design in improving user interaction with complex consumer products. This research holds substantial potential to advance our understanding of instructional materials' effectiveness in the context of technological products. As technology becomes increasingly integrated into everyday life, the ability to effectively use and understand technological products is crucial. This study will contribute to this understanding by identifying the most effective ways to guide users in navigating new technologies, thereby reducing the frustration and time often associated with learning new devices. Moreover, the findings from this research could significantly benefit businesses and educators by providing evidence-based recommendations for instructional material design. For businesses, this means creating more user-friendly manuals that could lead to increased customer satisfaction and reduced the need for customer support

Project SAM: Developing an app to provide self-help for anxiety

An interdisciplinary team at the University of the West of England (UWE) was commissioned and funded to develop a mobile phone app which would provide self-help options for the management of mild to moderate anxiety. The completed app would extend the range and availability of psychological support for student well-being at UWE and other higher education institutions.The project team consisted of two computer scientists and one psychologist who were responsible for the technical, functional and clinical specification of the app. A local mobile app development company was appointed and the teams collaborated on the design, build and evaluation of the app. The self-help structure and components were developed in consultation with therapeutic practitioners, in and out of UWE. The developer team advised on and constructed multi-media features to realise the self-help aims of the app.The UWE project team promoted an iterative approach to development, evaluating each stage of development through trials with expert users, practitioners and students. The app, named SAM (Self-help for Anxiety Management), was developed for Apple and Android operating systems, to be usable on smartphones and tablets. SAM was launched in the app stores in July 2013, globally available and free to download for the first year of operation. It was promoted to students, educational institutions, mental health organisations and charities as well as a range of professional and informal contacts. A UWE-based Advisory Board was convened to oversee the maintenance and development of the university’s investment in SAM. Members include the project team, researchers, therapists and other staff with an interest in its use to support student well-being. Three key tasks of the Board are to ensure SAM’s financial sustainability, to oversee developments in its usability and self-help components, and to obtain funding for the evaluation of its therapeutic impact