Sustainable Statistical And Data Science Methods And Practices
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Sustainable Statistical And Data Science Methods And Practices
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Author : O. Olawale Awe
language : en
Publisher: Springer Nature
Release Date : 2024-01-05
Sustainable Statistical And Data Science Methods And Practices written by O. Olawale Awe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-05 with Computers categories.
This volume gathers papers presented at the LISA 2020 Sustainability Symposium in Kumasi, Ghana, May 2–6, 2022. They focus on sustainable methods and practices of using statistics and data science to address real-world problems. From utilizing social media for statistical collaboration to predicting obesity among rural women, and from analyzing inflation in Nigeria using machine learning to teaching data science in Africa, this book explores the intersection of data, statistics, and sustainability. With practical applications, code snippets, and case studies, this book offers valuable insights for researchers, policymakers, and data enthusiasts alike. The LISA 2020 Global Network aims to enhance statistical and data science capability in developing countries through the creation of a network of collaboration laboratories (also known as “stat labs”). These stat labs are intended to serve as engines for development by training the next generation of collaborative statisticians and data scientists, providing research infrastructure for researchers, data producers, and decision-makers, and enabling evidence-based decision-making that has a positive impact on society. The research conducted at LISA 2020 focuses on practical methods and applications for sustainable growth of statistical capacity in developing nations.
Practical Statistical Learning And Data Science Methods
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Author : O. Olawale Awe
language : en
Publisher: Springer Nature
Release Date : 2024-12-27
Practical Statistical Learning And Data Science Methods written by O. Olawale Awe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Computers categories.
This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science. Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike. The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as “stat labs.” These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers.
Big Data Science And Analytics For Smart Sustainable Urbanism
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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-05-30
Big Data Science And Analytics For Smart Sustainable Urbanism written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Social Science categories.
We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holisticand integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Methods In Sustainability Science
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Author : Jingzheng Ren
language : en
Publisher: Elsevier
Release Date : 2021-08-12
Methods In Sustainability Science written by Jingzheng Ren and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-12 with Business & Economics categories.
Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization presents cutting edge, detailed methodologies needed to create sustainable growth in any field or industry, including life cycle assessments, building design, and energy systems. The book utilized a systematic structured approach to each of the methodologies described in an interdisciplinary way to ensure the methodologies are applicable in the real world, including case studies to demonstrate the methods. The chapters are written by a global team of authors in a variety of sustainability related fields. Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization will provide academics, researchers and practitioners in sustainability, especially environmental science and environmental engineering, with the most recent methodologies needed to maintain a sustainable future. It is also a necessary read for postgraduates in sustainability, as well as academics and researchers in energy and chemical engineering who need to ensure their industrial methodologies are sustainable. Provides a comprehensive overview of the most recent methodologies in sustainability assessment, prioritization, improvement, design and optimization Sections are organized in a systematic and logical way to clearly present the most recent methodologies for sustainability and the chapters utilize an interdisciplinary approach that covers all considerations of sustainability Includes detailed case studies demonstrating the efficacies of the described methods
Proceedings Of The 6th International Conference On Deep Learning Artificial Intelligence And Robotics Icdlair 2024
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Author : Priyanka Ahlawat
language : en
Publisher: Springer Nature
Release Date : 2025-07-26
Proceedings Of The 6th International Conference On Deep Learning Artificial Intelligence And Robotics Icdlair 2024 written by Priyanka Ahlawat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-26 with Computers categories.
This is an open access book. The proposed conference ICDLAIR 2024 represents key ingredients for the 5G. The extensive application of AI and DL is dramatically changing products and services, with a large impact on labour, economy and society at all. ICDLAIR 2024, organized by NIT Kurukshetra, India in collaboration with International Association of Academicians (IAASSE), Emlyon Business School France and CSUSB USA, aims at collecting scientific and technical contributions with respect to models, tools, technologies and applications in the field of modern artificial intelligence and robotics, covering the entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations. Through sharing and networking, ICDLAIR 2024 will provide an opportunity for researchers, practitioners and educators to exchange research evidence, practical experiences and innovative ideas on issues related to the Conference theme. ICDLAIR 2024 intends to publish the post-conference work in order to give authors the opportunity to collect feedback during the presentation.
Advances In The Leading Paradigms Of Urbanism And Their Amalgamation
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Author : Simon Elias Bibri
language : en
Publisher: Springer Nature
Release Date : 2020-06-20
Advances In The Leading Paradigms Of Urbanism And Their Amalgamation written by Simon Elias Bibri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-20 with Science categories.
This book explores the recent advances in the leading paradigms of urbanism, namely compact cities, eco-cities, and data–driven smart cities, and the evolving approach to their amalgamation under the umbrella term of smart sustainable cities. It addresses these advances by investigating how and to what extent the strategies of compact cities and eco-cities and their merger have been enhanced and strengthened through new planning and development practices, and are being supported and leveraged by the applied solutions pertaining to data-driven smart cities. The ultimate goal is to advance sustainability and harness its synergistic effects on multiple scales. This entails developing and implementing more effective approaches to the balanced integration of the three dimensions of sustainability, as well as to producing combined effects of the strategies and solutions of the prevailing approaches to urbanism that are greater than the sum of their separate effects in terms of the tripartite value of sustainability. Sustainable urban development is today seen as one of the keys towards unlocking the quest for a sustainable world. And the big data revolution is set to erupt in cities throughout the world, heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities and the spaces we live in thanks to the IoT. Big data and the IoT technologies are seen as powerful forces that have tremendous potential for advancing urban sustainability. Indeed, they are instigating a massive change in the way sustainable cities can tackle the kind of special conundrums, wicked problems, and significant challenges they inherently embody as complex systems. They offer a multitudinous array of innovative solutions and sophisticated approaches informed by groundbreaking research and data–driven science. As such, they are becoming essential to the functioning of sustainable cities. Besides, yet knowing to what extent we are making progress towards sustainable cities is problematic, adding to the fragmented, conflicting picture that arises of change on the ground in the face of the escalating rate and scale of urbanization and in the light of emerging ICT and its novel applications. In a nutshell, new circumstances require new responses. This timely and multifaceted book is intended for a wide readership. As such, it will appeal to researchers, academics, urban scientists, urbanists, planners, designers, policy-makers, and futurists, as well as all readers interested in sustainable cities and their ongoing and future data-driven transformation.
Artificial Intelligence And Data Science For Sustainability Applications And Methods
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Author : Syafrudin, Muhammad
language : en
Publisher: IGI Global
Release Date : 2025-02-07
Artificial Intelligence And Data Science For Sustainability Applications And Methods written by Syafrudin, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-07 with Computers categories.
The integration of artificial intelligence (AI) and data science (DS) into sustainability efforts is increasingly crucial as the world faces environmental and resource challenges. By leveraging advanced AI and DS techniques, we can create innovative solutions for sectors like energy, agriculture, and waste management, promoting long-term sustainability. These technologies have the potential to optimize processes, reduce environmental footprints, and support smarter decision-making across industries. Ultimately, AI and DS are key to advancing both the efficiency and impact of sustainability efforts, contributing to a more sustainable future for society at large. Artificial Intelligence and Data Science for Sustainability: Applications and Methods explores the application of AI and DS techniques and methodologies in addressing various sustainability challenges. It brings together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains. Covering topics such as structural optimization, drone imagery, and development financing, this book is an excellent resource for computer scientists, computer engineers, urban planners, sustainability professionals, government officials, policymakers, researchers, professionals, scholars, academicians, and more.
Promoting Statistical Practice And Collaboration In Developing Countries
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Author : O. Olawale Awe
language : en
Publisher: CRC Press
Release Date : 2022-06-07
Promoting Statistical Practice And Collaboration In Developing Countries written by O. Olawale Awe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-07 with Mathematics categories.
"Rarely, but just often enough to rebuild hope, something happens to confound my pessimism about the recent unprecedented happenings in the world. This book is the most recent instance, and I think that all its readers will join me in rejoicing at the good it seeks to do. It is an example of the kind of international comity and collaboration that we could and should undertake to solve various societal problems. This book is a beautiful example of the power of the possible. [It] provides a blueprint for how the LISA 2020 model can be replicated in other fields. Civil engineers, or accountants, or nurses, or any other profession could follow this outline to share expertise and build capacity and promote progress in other countries. It also contains some tutorials for statistical literacy across several fields. The details would change, of course, but ideas are durable, and the generalizations seem pretty straightforward. This book shows every other profession where and how to stand in order to move the world. I urge every researcher to get a copy!" —David Banks from the Foreword Promoting Statistical Practice and Collaboration in Developing Countries provides new insights into the current issues and opportunities in international statistics education, statistical consulting, and collaboration, particularly in developing countries around the world. The book addresses the topics discussed in individual chapters from the perspectives of the historical context, the present state, and future directions of statistical training and practice, so that readers may fully understand the challenges and opportunities in the field of statistics and data science, especially in developing countries. Features • Reference point on statistical practice in developing countries for researchers, scholars, students, and practitioners • Comprehensive source of state-of-the-art knowledge on creating statistical collaboration laboratories within the field of data science and statistics • Collection of innovative statistical teaching and learning techniques in developing countries Each chapter consists of independent case study contributions on a particular theme that are developed with a common structure and format. The common goal across the chapters is to enhance the exchange of diverse educational and action-oriented information among our intended audiences, which include practitioners, researchers, students, and statistics educators in developing countries.
Exploring The Impact Of Extended Reality Xr Technologies On Promoting Environmental Sustainability
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Author : Shashi Kant Gupta
language : en
Publisher: Springer Nature
Release Date : 2025-06-11
Exploring The Impact Of Extended Reality Xr Technologies On Promoting Environmental Sustainability written by Shashi Kant Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-11 with Computers categories.
This book offers a groundbreaking exploration of how Extended Reality (XR) technologies can drive environmental sustainability. By integrating virtual, augmented, and mixed realities, it provides innovative solutions to enhance understanding and inspire action on environmental issues. The text is meticulously curated to cover the multifaceted applications of XR, from revolutionizing environmental practices with deep learning to leveraging quantum computing for sustainable solutions. It highlights the synergy between XR and artificial intelligence in optimizing supply chains and enhancing data analytics. Aimed at researchers, practitioners, and policymakers, this resource underscores the critical role of XR in environmental advocacy, emphasizing its potential in effective communication and behavior change. The book also delves into immersive education, fostering a culture of environmental stewardship through experiential learning. Ultimately, it calls for interdisciplinary collaboration to address pressing environmental challenges, envisioning a future where XR technologies are pivotal in safeguarding our planet.
Harnessing Data Science For Sustainable Agriculture And Natural Resource Management
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Author : Mehul S. Raval
language : en
Publisher: Springer Nature
Release Date : 2024-12-19
Harnessing Data Science For Sustainable Agriculture And Natural Resource Management written by Mehul S. Raval and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-19 with Computers categories.
This book is a comprehensive resource that handles the issues of sustainable agriculture and natural resource management, aligned with the United Nations' Sustainable Development Goals (SDGs). The book is organized into five sections, Understanding the Problem, Data Collection and Cleaning, Exploratory Data Analysis and Visualization, Model Building, and Model Deployment. Each section covers a critical aspect of data science in this context and addresses specific SDGs 2—zero hunger, 6—clean water and sanitation, 12—responsible consumption and production, 13—climate action, and 15—Life on land. The organized sections are arranged to seamlessly follow the data science pipeline and provide practical guidance from problem understanding to its model deployment and stakeholder management. The book is useful for researchers, students, practitioners, and policymakers.