This book offers a timely snapshot of soft computing methodologies and their applications to various problems related to sustainability, including electric energy consumption; fault diagnosis; vessel fuel consumption; determining the best sites for new malls; maritime port projects; and ad-hoc vehicular networks. Further, it demonstrates how metaheuristics and machine learning methods, fuzzy linear programming, neural networks, computing with words, linguistic models and other soft computing methods can be efficiently used to solve real-world problems. Intended as a practice-oriented guide for students, researchers, and professionals working at the interface between computer science, industrial engineering, naval engineering, agriculture, and sustainable development / climate change research, it provides readers with a set of intelligent solutions, helping them answer a range of emerging questions related to sustainability.

This book focuses on software sustainability, regarded in terms of how software is or can be developed while taking into consideration environmental, social, and economic dimensions. The sixteen chapters cover various related issues ranging from technical aspects like energy-efficient programming techniques, formal proposals related to energy efficiency measurement, patterns to build energy-efficient software, the role of developers on energy efficient software systems and tools for detecting and refactoring code smells/energy bugs; to human aspects like its impact on software sustainability or the adaptation of ACM/IEEE guidelines for student and professional education and; and an economics-driven architectural evaluation for sustainability. Also aspects as the elements of governance and management that organizations should consider when implementing, assessing and improving Green IT or the relationship between software sustainability and the Corporate Social Responsibility of software companies are included. The chapters are complemented by usage scenarios and experience reports on several domains as cloud applications, agile development or e-Health, among others. As a whole, the chapters provide a complete overview of the various issues related to sustainable software development. The target readership for this book includes CxOs, (e.g. Chief Information Officers, Chief Executive Officers, Chief Technology Officers, etc.) software developers, software managers, auditors, business owners, and quality professionals. It is also intended for students of software engineering and information systems, and software researchers who want to know the state of the art regarding software sustainability.

Examines the integration of hardware with stand-alone PV panels and real time monitoring of factors affecting the efficiency of the photovoltaic panels Offers the real time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation

Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses

Understanding sustainability is vital to resolving and managing many of today's problems, on a global as well as local scale. Sustainability science is an emerging field of research that comprises concepts and methodologies from different disciplines in a problem-oriented manner. Research efforts are often concentrated in a variety of sectoral domains. The heterogeneity of scientific tasks involved here and the complexity of environmental and social systems call for specific research strategies which are generally a compromise between high-precision analysis and educated guesswork. For understanding of global change, which embraces a variety of processes on several scales, information needs to be refined and compressed rather than amplified. This book aims at presenting advanced methods and techniques to make them available to a wider scientific community involved in global change and sustainability research. The contributions describe novel schemes to study the relationship between the socio-economic and the natural sphere and/or the social dimensions of climate and global change. The methodological approaches can be useful in the design and management of environmental systems, for policy development, environmental risk reduction, and prevention/mitigation strategies. In this context, a variety of environmental and sustainability aspects can be addressed, e.g. changes in the natural environment and land use, environmental impacts on human health, economics and technology, institutional interactions, human activities and behaviour.

Soft Computing Techniques in Solid Waste and Wastewater Management is a thorough guide to computational solutions for researchers working in solid waste and wastewater management operations. This book covers in-depth analysis of process variables, their effects on overall efficiencies, and optimal conditions and procedures to improve performance using soft computing techniques. These topics coupled with the systematic analyses described will help readers understand various techniques that can be effectively used to achieve the highest performance. In-depth case studies along with discussions on applications of various soft-computing techniques help readers control waste processes and come up with short-term, mid-term and long-term strategies. Waste management is an increasingly important field due to rapidly increasing levels of waste production around the world. Numerous potential solutions for reducing waste production are underway, including applications of machine learning and computational studies on waste management processes. This book details the diverse approaches and techniques in these fields, providing a single source of information researchers and industry practitioners. It is ideal for academics, researchers and engineers in waste management, environmental science, environmental engineering and computing, with relation to environmental science and waste management. - Provides a comprehensive reference on the implementation of soft computing techniques in waste management, drawing together current research and future implications - Includes detailed algorithms used, enabling authors to understand and appreciate potential applications - Presents relevant case studies in solid and wastewater management that show real-world applications of discussed technologies

Comprehensive, yet concise, 3D Printing for the Radiologist presents an overview of three-dimensional printing at the point of care. Focusing on opportunities and challenges in radiology practice, this up-to-date reference covers computer-aided design principles, quality assurance, training, and guidance for integrating 3D printing across radiology subspecialties. Practicing and trainee radiologists, surgeons, researchers, and imaging specialists will find this an indispensable resource for furthering their understanding of the current state and future outlooks for 3D printing in clinical medicine. - Covers a wide range of topics, including basic principles of 3D printing, quality assurance, regulatory perspectives, and practical implementation in medical training and practice. - Addresses the challenges associated with 3D printing integration in clinical settings, such as reimbursement, regulatory issues, and training. - Features concise chapters from a team of multidisciplinary chapter authors, including practicing radiologists, researchers, and engineers. - Consolidates today's available information on this timely topic into a single, convenient, resource.

As the climate and environment continue to fluctuate, researchers are urgently looking for new ways to preserve our limited resources and prevent further environmental degradation. The answer can be found through computer science, a field that is evolving at precisely the time it is needed most. Soft Computing Applications for Renewable Energy and Energy Efficiency brings together the latest technological research in computational intelligence and fuzzy logic as a way to care for our environment. This reference work highlights current advances and future trends in environmental sustainability using the principles of soft computing, making it an essential resource for students, researchers, engineers, and practitioners in the fields of project engineering and energy science.

The ever-increasing awareness and growing focus on environmental issues such as climate change and energy use is bringing about an urgency in expanding research to provide possible solutions to these problems. Through current engineering research and emerging technologies, scientists work to combat modern environmental and ecological problems plaguing the globe. Advanced Methodologies and Technologies in Engineering and Environmental Science provides emerging research on the current and forthcoming trends in engineering and environmental sciences to resolve several issues plaguing researchers such as fossil fuel emission and climate change. While highlighting these challenges, including chemical toxicity environmental responsibility, readers will learn how engineering applications can be used across disciplines to aid in reducing environmental hazards. This book is a vital resource for engineers, researchers, professors, academicians, and environmental scientists seeking current research on how engineering tools and technologies can be applied to environmental issues.