Author: Irfan Awan Publisher: Springer Nature ISBN: 3031160355 Category : Technology & Engineering Languages : en Pages : 140
Book Description
Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications. This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to): Deep/Machine learning based models Statistical models and learning Data analysis, insights and hidden pattern Data visualisation Security threat detection Data classification and clustering Blockchain security and trust Blockchain data management
Author: Muhammad Younas Publisher: Springer Nature ISBN: 3031423178 Category : Technology & Engineering Languages : en Pages : 148
Book Description
This book constitutes refereed articles which present research work on new and emerging topics such as distributed ledger technology, blockchains and architectures, smart cities, machine learning and deep learning techniques and application areas such as flight pricing, energy demand and healthcare. The intended readership of the book include researchers, developers and practitioners in the areas of deep learning, big data and blockchains technologies and their applications.
Author: Shubham Mahajan Publisher: John Wiley & Sons ISBN: 1394272561 Category : Computers Languages : en Pages : 421
Book Description
This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable resource for professionals and enthusiasts at the forefront of technological innovation. Deep Reinforcement Learning (DRL) represents one of the most dynamic and impactful areas of research and development in the field of artificial intelligence. Bridging the gap between decision-making theory and powerful deep learning models, DRL has evolved from academic curiosity to a cornerstone technology driving innovation across numerous industries. Its core premise—enabling machines to learn optimal actions within complex environments through trial and error—has broad implications, from automating intricate decision processes to optimizing operations that were previously beyond the reach of traditional AI techniques. “Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications” is an essential guide for anyone eager to understand the nexus between cutting-edge artificial intelligence techniques and practical industrial applications. This book not only demystifies the complex theory behind deep reinforcement learning (DRL) but also provides a clear roadmap for implementing these advanced algorithms in a variety of industries to solve real-world problems. Through a careful blend of theoretical foundations, practical insights, and diverse case studies, the book offers a comprehensive look into how DRL is revolutionizing fields such as finance, healthcare, manufacturing, and more, by optimizing decisions in dynamic and uncertain environments. This book distills years of research and practical experience into accessible and actionable knowledge. Whether you’re an AI professional seeking to expand your toolkit, a business leader aiming to leverage AI for competitive advantage, or a student or academic researching the latest in AI applications, this book provides valuable insights and guidance. Beyond just exploring the successes of DRL, it critically examines challenges, pitfalls, and ethical considerations, preparing readers to not only implement DRL solutions but to do so responsibly and effectively. Audience The book will be read by researchers, postgraduate students, and industry engineers in machine learning and artificial intelligence, as well as those in business and industry seeking to understand how DRL can be applied to solve complex industry-specific challenges and improve operational efficiency.
Author: Sabine Kuhlmann Publisher: Springer Nature ISBN: 3030536971 Category : Political Science Languages : en Pages : 415
Book Description
This open access book presents a topical, comprehensive and differentiated analysis of Germany’s public administration and reforms. It provides an overview on key elements of German public administration at the federal, Länder and local levels of government as well as on current reform activities of the public sector. It examines the key institutional features of German public administration; the changing relationships between public administration, society and the private sector; the administrative reforms at different levels of the federal system and numerous sectors; and new challenges and modernization approaches like digitalization, Open Government and Better Regulation. Each chapter offers a combination of descriptive information and problem-oriented analysis, presenting key topical issues in Germany which are relevant to an international readership.
Author: Rafael Sacks Publisher: John Wiley & Sons ISBN: 1119287553 Category : Architecture Languages : en Pages : 779
Book Description
Discover BIM: A better way to build better buildings Building Information Modeling (BIM) offers a novel approach to design, construction, and facility management in which a digital representation of the building product and process is used to facilitate the exchange and interoperability of information in digital format. BIM is beginning to change the way buildings look, the way they function, and the ways in which they are designed and built. The BIM Handbook, Third Edition provides an in-depth understanding of BIM technologies, the business and organizational issues associated with its implementation, and the profound advantages that effective use of BIM can provide to all members of a project team. Updates to this edition include: Information on the ways in which professionals should use BIM to gain maximum value New topics such as collaborative working, national and major construction clients, BIM standards and guides A discussion on how various professional roles have expanded through the widespread use and the new avenues of BIM practices and services A wealth of new case studies that clearly illustrate exactly how BIM is applied in a wide variety of conditions Painting a colorful and thorough picture of the state of the art in building information modeling, the BIM Handbook, Third Edition guides readers to successful implementations, helping them to avoid needless frustration and costs and take full advantage of this paradigm-shifting approach to construct better buildings that consume fewer materials and require less time, labor, and capital resources.
Author: Anil Sawhney Publisher: Routledge ISBN: 0429675119 Category : Architecture Languages : en Pages : 527
Book Description
Modelled on the concept of Industry 4.0, the idea of Construction 4.0 is based on a confluence of trends and technologies that promise to reshape the way built environment assets are designed, constructed, and operated. With the pervasive use of Building Information Modelling (BIM), lean principles, digital technologies, and offsite construction, the industry is at the cusp of this transformation. The critical challenge is the fragmented state of teaching, research, and professional practice in the built environment sector. This handbook aims to overcome this fragmentation by describing Construction 4.0 in the context of its current state, emerging trends and technologies, and the people and process issues that surround the coming transformation. Construction 4.0 is a framework that is a confluence and convergence of the following broad themes discussed in this book: Industrial production (prefabrication, 3D printing and assembly, offsite manufacture) Cyber-physical systems (actuators, sensors, IoT, robots, cobots, drones) Digital and computing technologies (BIM, video and laser scanning, AI and cloud computing, big data and data analytics, reality capture, Blockchain, simulation, augmented reality, data standards and interoperability, and vertical and horizontal integration) The aim of this handbook is to describe the Construction 4.0 framework and consequently highlight the resultant processes and practices that allow us to plan, design, deliver, and operate built environment assets more effectively and efficiently by focusing on the physical-to-digital transformation and then digital-to-physical transformation. This book is essential reading for all built environment and AEC stakeholders who need to get to grips with the technological transformations currently shaping their industry, research, and teaching.
Author: Russell Kenley Publisher: Routledge ISBN: 1134573480 Category : Business & Economics Languages : en Pages : 298
Book Description
This professional text provides a considered analysis of the tools and techniques of project financial management in construction, notably it covers cash flow modelling and provides the first detailed investigation of cash farming.
Author: Irfan Awan Publisher: Springer Nature ISBN: 3030843378 Category : Technology & Engineering Languages : en Pages : 182
Book Description
The role of deep learning for the analysis and learning of massive amounts of data from all aspects of daily-life has dramatically changed over the last few years. It is increasingly helping uncover trends leading to great successes. This book includes a collection of research manuscripts presenting state-of-the-art work in the areas of deep learning, blockchain and big data. All the manuscripts included in this book have been peer-reviewed based on aspects of novelty, originality and rigour. The main topics covered in the book include machine learning and time series, blockchain technologies and applications, data security, deep learning, and Internet of Things.
Author: Irfan Awan
Author: Muhammad Younas
Author: Shubham Mahajan
Author: Muhammad Younas
Author: Ana Fred
Author: Sabine Kuhlmann
Author: Rafael Sacks
Author: Anil Sawhney
Author: Russell Kenley
Author: Irfan Awan