비만아 부모의 돌봄 경험: q 방법론

Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokemon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have bought us various degrees of digital transformation. The term `metaverse' has been coined to further facilitate the digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalysed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital `big bang' of our cyberspace is not far away. This survey paper presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems, and illustrates the possibility of the digital `big bang'. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously - Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, IoT and Robotics, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors -- Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for the development of the metaverse.

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda

Roles of artificial intelligence in construction engineering and management: A critical review and future trends

Materials informatics provides the foundations for a new paradigm of materials discovery. It shifts our emphasis from one of solely searching among large volumes of data that may be generated by experiment or computation to one of targeted materials discovery via high-throughput identification of the key factors (i.e., “genes”) and via showing how these factors can be quantitatively integrated by statistical learning methods into design rules (i.e., “gene sequencing”) governing targeted materials functionality. However, a critical challenge in discovering these materials genes is the difficulty in unraveling the complexity of the data associated with numerous factors including noise, uncertainty, and the complex diversity of data that one needs to consider (i.e., Big Data). In this article, we explore one aspect of materials informatics, namely how one can efficiently explore for new knowledge in regimes of structure-property space, especially when no reasonable selection pathways based on theory or clear...

Materials Informatics: The Materials ``Gene'' and Big Data

The fields of machining learning and artificial intelligence are rapidly expanding, impacting nearly every technological aspect of society Many thousands of published manuscripts report advances over the last 5 years or less Yet materials and structures engineering practitioners are slow to engage with these advancements Perhaps the recent advances that are driving other technical fields are not sufficiently distinguished from long-known informatics methods for materials, thereby masking their likely impact to the materials, processes, and structures engineering (MPSE) Alternatively, the diverse nature and limited availability of relevant materials data pose obstacles to machine-learning implementation The glimpse captured in this overview is intended to draw focus to selected distinguishing advances, and to show that there are opportunities for these new technologies to have transformational impacts on MPSE Further, there are opportunities for the MPSE fields to contribute understanding to the emerging machine-learning tools from a physics basis We suggest that there is an immediate need to expand the use of these new tools throughout MPSE, and to begin the transformation of engineering education that is necessary for ongoing adoption of the methods

/pdf/perspectives-on-the-impact-of-machine-learning-deep-learning-3iryuf1s3z.pdf

Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering

A digital twin (DT) refers to a digital replica of physical assets, processes, and systems. DTs integrate artificial intelligence, machine learning, and data analytics to create living digi...

/pdf/developing-a-digital-twin-at-building-and-city-levels-case-2as39xd4jk.pdf

Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus

Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance

Design and development of BIM models to support operations and maintenance

With the rising adoption of Building Information Model (BIM) for asset management within architecture, engineering, construction and owner-operated (AECO) sector, BIM-enabled asset management has been increasingly attracting more attentions in both research and practice. This study provides a comprehensive review and analysis of the state-of-the-art latest research and industry standards development that impact upon BIM and asset management within the operations and maintenance (O&M) phase. However, BIM is not always enough in whole-life cycle asset management, especially in the O&M phase. Therefore, a framework for future development of smart asset management is proposed, integrating the concept of Digital Twin (DT). DT integrates artificial intelligence, machine learning and data analytics to create dynamic digital models that are able to learn and update the status of the physical counterpart from multiple sources. The findings will contribute to inspiring novel research ideas and promote widespread adoption of smart DT-enabled asset management within the O&M phase.

/pdf/from-bim-towards-digital-twin-strategy-and-future-53xkrigmsr.pdf

From BIM Towards Digital Twin: Strategy and Future Development for Smart Asset Management

This paper demonstrates that a shift from a purely technical to a more socio-technical perspective has significant implications for the conceptualization, design, and implementation of smart city t...

https://www.tandfonline.com/doi/pdf/10.1080/10630732.2020.1798177

Jennifer Schooling

Papers

Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus

Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance

Design and development of BIM models to support operations and maintenance

From BIM Towards Digital Twin: Strategy and Future Development for Smart Asset Management

A Socio-Technical Perspective on Urban Analytics: The Case of City-Scale Digital Twins