The “2019 DigitalFUTURES — The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)” provides an international platform for advanced scientific research papers on the digital technology of architectural design and construction. The themes of the papers include, but are not limited to, architectural theories, tools, methods and procedures in material intelligence, data intelligence; computational intelligence, and robotic intelligence.

This open access book is a compilation of selected papers from 2020 DigitalFUTURES—The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020). The book focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers will encounter new ideas about understanding intelligence in architecture.

This open access book is a compilation of selected papers from 2021 DigitalFUTURES—The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021). The work focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers encounter new ideas about understanding material intelligence in architecture.

This book presents selected papers from The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019). Focusing on novel architecture theories, tools, methods, and procedures for digital design and construction in architecture, it promotes dialogs between architecture, engineer, computer science, robotics, and other relevant disciplines to establish a new way of production in the building industry in the digital age. The contents make valuable contributions to academic researchers and engineers in the industry. At the same time, it offers readers new ideas for the application of digital technology.

This book presents a novel design framework for the development of Digital Twin (DT) models for process- and motion-control applications. It is based on system-data acquisition using cutting-edge computing technologies, modelling of physical-system behavior through detailed simultaneous simulation of different aspects of the system, and optimal dynamic behavior-matching of the process. The design framework is enhanced with real-time data analytics to improve the performance of the DT’s behavior-matching with the real system or physical twin. The methods of creating a DT detailed in Digital-Twin-Enabled Smart Control Engineering make possible the study of a system for real-time controller tuning and fault detection. They also facilitate life-cycle analysis for multiple critical and dangerous conditions that cannot be explored in the corresponding real system or physical twin. The authors show how a DT can be exploited to enable self-optimizing capabilities in feedback control systems. The DT framework and the control-performance assessment, fault diagnosis and prognosis, remaining-useful-life analysis, and self-optimizing control abilities it allows are validated with both process- and motion-control systems and their DTs. Supporting MATLAB-based material for a case study and an expanded introduction to the basic elements of DTs can be accessed on an associated website. This book helps university researchers from many areas of engineering to develop new tools for control design and reliability and life-cycle assessment and helps practicing engineers working with robotic, manufacturing and processing, and mechatronic systems to maintain and develop the mechanical tools they use.

Doing research is an ever-changing challenge for social scientists. This challenge is harder than ever today as current societies are changing quickly and in many, sometimes conflicting, directions. Social phenomena, personal interactions, and formal and informal relationships are becoming more borderless and disconnected from the anchors of the offline “reality.” These dynamics are heavily marking our time and are suggesting evolutionary challenges in the ways we know, interpret, and analyze the world. Internet and computer-mediated communication (CMC) is being incorporated into every aspect of daily life, and social life has been deeply penetrated by the internet. This is due to recent technological developments that increase the scope and range of online social spaces and the forms and time of participation such as Web 2.0, which widened the opportunities for user-generated content, the emergence of an “internet of things,” and of ubiquitous mobile devices that make it possible to always be connected. This implies an adjustment to epistemological and methodological stances for conducting social research and an adaption of traditional social research methods to the specificities of online interactions in the digital society. The Handbook of Research on Advanced Research Methodologies for a Digital Society covers the different strands of methods most affected by the change in a digital society and develops a broader theoretical reflection on the future of social research in its challenge to always be fitting, suitable, adaptable, and pertinent to the society to be studied. The chapters are geared towards unlocking the future frontiers and potential for social research in the digital society. They include theoretical, epistemological, and ontological reflections about the digital research methods as well as innovative methods and tools to collect, analyze, and interpret data. This book is ideal for social scientists, practitioners, librarians, researchers, academicians, and students interested in social research methodology and its developments in the digital scenario.

Vast manpower and resources are needed to investigate cybercrimes. The use of new advanced technologies, such as machine learning combined with automation, are effective in providing significant additional support in prevention of cyber-attacks, in the speedy recovery of data, and in reducing human error. This new volume offers a comprehensive study of the advances that have been made in cybercrime investigations and digital forensics, highlighting the most up-to-date tools that help to mitigate cyber-attacks and to extract digital evidence for forensic investigations to recover lost, purposefully deleted, or damaged files. The chapters look at technological cybersecurity tools such as artificial intelligence, machine learning, data mining, and others for mitigation and investigation.