Data Science Applied to Sustainability Analysis

Data Science Applied to Sustainability Analysis
Author: Jennifer Dunn,Prasanna Balaprakash
Publsiher: Elsevier
Total Pages: 310
Release: 2021-05-11
ISBN 10: 0128179775
ISBN 13: 9780128179772
Language: EN, FR, DE, ES & NL

Data Science Applied to Sustainability Analysis Book Review:

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

Computational Intelligent Data Analysis for Sustainable Development

Computational Intelligent Data Analysis for Sustainable Development
Author: Ting Yu,Nitesh Chawla,Simeon Simoff
Publsiher: CRC Press
Total Pages: 440
Release: 2016-04-19
ISBN 10: 1439895953
ISBN 13: 9781439895955
Language: EN, FR, DE, ES & NL

Computational Intelligent Data Analysis for Sustainable Development Book Review:

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present

CIGOS 2021 Emerging Technologies and Applications for Green Infrastructure

CIGOS 2021  Emerging Technologies and Applications for Green Infrastructure
Author: Cuong Ha-Minh,Anh Minh Tang,Tinh Quoc Bui,Xuan Hong Vu,Dat Vu Khoa Huynh
Publsiher: Springer Nature
Total Pages: 1958
Release: 2021-10-28
ISBN 10: 9811671605
ISBN 13: 9789811671609
Language: EN, FR, DE, ES & NL

CIGOS 2021 Emerging Technologies and Applications for Green Infrastructure Book Review:

This book highlights the key role of green infrastructure (GI) in providing natural and ecosystem solutions, helping alleviate many of the environmental, social, and economic problems caused by rapid urbanization. The book gathers the emerging technologies and applications in various disciplines involving geotechnics, civil engineering, and structures, which are presented in numerous high-quality papers by worldwide researchers, practitioners, policymakers, and entrepreneurs at the 6th CIGOS event, 2021. Moreover, by sharing knowledge and experiences around emerging GI technologies and policy issues, the book aims at encouraging adoption of GI technologies as well as building capacity for implementing GI practices at all scales. This book is useful for researchers and professionals in designing, building, and managing sustainable buildings and infrastructure.

Research Handbook on Big Data Law

Research Handbook on Big Data Law
Author: Roland Vogl
Publsiher: Edward Elgar Publishing
Total Pages: 544
Release: 2021-05-28
ISBN 10: 1788972821
ISBN 13: 9781788972826
Language: EN, FR, DE, ES & NL

Research Handbook on Big Data Law Book Review:

This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.

Environmental Data Analysis with MatLab

Environmental Data Analysis with MatLab
Author: William Menke,Joshua Ephraim Menke
Publsiher: Elsevier
Total Pages: 263
Release: 2012
ISBN 10: 0123918863
ISBN 13: 9780123918864
Language: EN, FR, DE, ES & NL

Environmental Data Analysis with MatLab Book Review:

Environmental Data Analysis with MatLab is for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. This book teaches the basics of the underlying theory of data analysis, and then reinforces that knowledge with carefully chosen, realistic scenarios. MatLab, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. The book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial. Author's website: http://www.ldeo.columbia.edu/users/menke/edawm/index.htm Well written and outlines a clear learning path for researchers and students Uses real world environmental examples and case studies MatLab software for application in a readily-available software environment Homework problems help user follow up upon case studies with homework that expands them

Artificial Intelligence and Data Science in Environmental Sensing

Artificial Intelligence and Data Science in Environmental Sensing
Author: Mohsen Asadnia,Amir Razmjou,Amin Beheshti
Publsiher: Academic Press
Total Pages: 324
Release: 2022-02-24
ISBN 10: 0323905072
ISBN 13: 9780323905077
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Data Science in Environmental Sensing Book Review:

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

Applied Statistics for Environmental Science with R

Applied Statistics for Environmental Science with R
Author: Abbas F. M. Al-Karkhi,Wasin A. A. Alqaraghuli
Publsiher: Elsevier
Total Pages: 240
Release: 2019-09-13
ISBN 10: 0128186232
ISBN 13: 9780128186237
Language: EN, FR, DE, ES & NL

Applied Statistics for Environmental Science with R Book Review:

Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems. Includes step-by-step tutorials to aid in understanding the process and implementation of unique data Presents statistical theory in a simple way without complex mathematical proofs Shows how to analyze data using R software and provides R scripts for all examples and figures

Sustainability Analysis

Sustainability Analysis
Author: S. Shmelev,I. Shmeleva
Publsiher: Springer
Total Pages: 335
Release: 2012-01-27
ISBN 10: 0230362435
ISBN 13: 9780230362437
Language: EN, FR, DE, ES & NL

Sustainability Analysis Book Review:

Sustainability Analysis provides a detailed exploration of current environmental thinking from a variety of perspectives, including institutional and psychological angles. Primarily focusing on macroeconomic policies and green national accounting, this book provides a strong basis for further study in sustainable development.

Statistical Data Analysis Explained

Statistical Data Analysis Explained
Author: Clemens Reimann,Peter Filzmoser,Robert Garrett,Rudolf Dutter
Publsiher: John Wiley & Sons
Total Pages: 362
Release: 2011-08-31
ISBN 10: 1119965284
ISBN 13: 9781119965282
Language: EN, FR, DE, ES & NL

Statistical Data Analysis Explained Book Review:

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.

Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19

Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19
Author: Victor Chang,Mohamed Abdel-Basset,Muthu Ramachandran,Nicolas Green,Gary Wills
Publsiher: Academic Press
Total Pages: 298
Release: 2022-04-05
ISBN 10: 0323903789
ISBN 13: 9780323903783
Language: EN, FR, DE, ES & NL

Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19 Book Review:

Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus outbreaks. Moreover, it provides guidelines on how governments and institutions should prepare and quickly respond to drastic situations using technology to support their communities in order to maintain life and functional as efficiently as possible. The book discusses topics such as AI-driven histopathology analysis for COVID-19 diagnosis, bioinformatics for subtype rational drug design, deep learning-based treatment evaluation and outcome prediction, sensor informatics for monitoring infected patients, and machine learning for tracking and prediction models. In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities. This is a valuable source for medical informaticians, bioinformaticians, clinicians and other healthcare workers and researchers who are interested in learning more on how recently developed technologies can help us fight and minimize the effects of global pandemics. Discusses AI advancements in predictive and decision modeling and how to design mobile apps to track contagion spread Presents the smart contract concept in blockchain and cryptography technology to guarantee security and privacy of people’s data once their information has been used to fight the pandemic Encompasses guidelines for emergency preparedness, planning, recovery and continuity management of communities to support people in emergencies like a virus outbreak

Data Driven Quality Improvement and Sustainability in Health Care

Data Driven Quality Improvement and Sustainability in Health Care
Author: Patricia L. Thomas, PhD, RN, FAAN, FNAP, FACHE, NEA-BC, ACNS-BC, CNL,James L. Harris, PhD, APRN-BC, MBA, CNL, FAAN,Brian J. Collins, BS, MA
Publsiher: Springer Publishing Company
Total Pages: 380
Release: 2020-11-19
ISBN 10: 0826139442
ISBN 13: 9780826139443
Language: EN, FR, DE, ES & NL

Data Driven Quality Improvement and Sustainability in Health Care Book Review:

Data-Driven Quality Improvement and Sustainability in Health Care: An Interprofessional Approach provides nurse leaders and healthcare administrators of all disciplines with a solid understanding of data and how to leverage data to improve outcomes, fuel innovation, and achieve sustained results. It sets the stage by examining the current state of the healthcare landscape; new imperatives to meet policy, regulatory, and consumer demands; and the role of data in administrative and clinical decision-making. It helps the professional identify the methods and tools that support thoughtful and thorough data analysis and offers practical application of data-driven processes that determine performance in healthcare operations, value- and performance-based contracts, and risk contracts. Misuse or inconsistent use of data leads to ineffective and errant decision-making. This text highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls. In addition, chapters feature key points, reflection questions, and real-life interprofessional case exemplars to help the professional draw distinctions and apply principles to their own practice. Key Features: Provides nurse leaders and other healthcare administrators with an understanding of the role of data in the current healthcare landscape and how to leverage data to drive innovative and sustainable change Offers frameworks, methodology, and tools to support quality improvement measures Demonstrates the application of data and how it shapes quality and safety initiatives through real-life case exemplars Highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls

Computational Intelligent Data Analysis for Sustainable Development

Computational Intelligent Data Analysis for Sustainable Development
Author: Ting Yu,Nitesh Chawla,Simeon Simoff
Publsiher: CRC Press
Total Pages: 440
Release: 2013-04-04
ISBN 10: 1439895945
ISBN 13: 9781439895948
Language: EN, FR, DE, ES & NL

Computational Intelligent Data Analysis for Sustainable Development Book Review:

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.

Methods in Sustainability Science

Methods in Sustainability Science
Author: Jingzheng Ren
Publsiher: Elsevier
Total Pages: 444
Release: 2021-08-05
ISBN 10: 012824240X
ISBN 13: 9780128242407
Language: EN, FR, DE, ES & NL

Methods in Sustainability Science Book Review:

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

Advanced Information Networking and Applications

Advanced Information Networking and Applications
Author: Leonard Barolli,Isaac Woungang,Tomoya Enokido
Publsiher: Springer Nature
Total Pages: 797
Release: 2021-04-26
ISBN 10: 3030750752
ISBN 13: 9783030750756
Language: EN, FR, DE, ES & NL

Advanced Information Networking and Applications Book Review:

​This book covers the theory, design and applications of computer networks, distributed computing and information systems. Networks of today are going through a rapid evolution, and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low-power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations is emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnections problems. To fulfill their large range of applications, different kinds of networks need to collaborate, and wired and next-generation wireless systems should be integrated in order to develop high-performance computing solutions to problems arising from the complexities of these networks. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Achieving Water Energy Food Nexus Sustainability A Science and Data Need or a Need for Integrated Public Policy

Achieving Water Energy Food Nexus Sustainability  A Science and Data Need or a Need for Integrated Public Policy
Author: Richard George Lawford,Rabi Mohtar,Jill A. Engel-Cox
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2020-10-27
ISBN 10: 2889661059
ISBN 13: 9782889661053
Language: EN, FR, DE, ES & NL

Achieving Water Energy Food Nexus Sustainability A Science and Data Need or a Need for Integrated Public Policy Book Review:

Advances and New Trends in Environmental Informatics

Advances and New Trends in Environmental Informatics
Author: Andreas Kamilaris,Volker Wohlgemuth,Kostas Karatzas,Ioannis N. Athanasiadis
Publsiher: Springer Nature
Total Pages: 270
Release: 2020-12-16
ISBN 10: 3030619699
ISBN 13: 9783030619695
Language: EN, FR, DE, ES & NL

Advances and New Trends in Environmental Informatics Book Review:

This book is an outcome of the 34th International Conference EnviroInfo 2020, hosted virtually in Nicosia, Cyprus by the Research Centre on Interactive Media, Smart Systems and Emerging Technologies (RISE). It presents a selection of papers that describe innovative scientific approaches and ongoing research in environmental informatics and the emerging field of environmental sustainability, promoted and facilitated by the use of information and communication technologies (ICT). The respective articles cover a broad range of scientific aspects including advances in core environmental informatics-related technologies such as earth observation, environmental modelling, big data and machine learning, robotics, smart agriculture and food solutions, renewable energy-based solutions, optimization of infrastructures, sustainable industrial processes, and citizen science, as well as applications of ICT solutions intended to support societal transformation processes toward the more sustainable management of resource use, transportation and energy supplies. Given its scope, the book is essential reading for scientists, experts and students in these fields of research. Chapter “Developing a Configuration System for a Simulation Game in the Domain of Urban CO2 Emissions Reduction” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing
Author: Ni-Bin Chang,Kaixu Bai
Publsiher: CRC Press
Total Pages: 528
Release: 2018-02-21
ISBN 10: 1351650637
ISBN 13: 9781351650632
Language: EN, FR, DE, ES & NL

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Book Review:

Combining versatile data sets from multiple satellite sensors with advanced thematic information retrieval is a powerful way for studying complex earth systems. The book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing offers complete understanding of the basic scientific principles needed to perform image processing, gap filling, data merging, data fusion, machine learning, and feature extraction. Written by two experts in remote sensing, the book presents the required basic concepts, tools, algorithms, platforms, and technology hubs toward advanced integration. By merging and fusing data sets collected from different satellite sensors with common features, we are enabled to utilize the strength of each satellite sensor to the maximum extent. The inclusion of machine learning or data mining techniques to aid in feature extraction after gap filling, data merging and/or data fusion further empowers earth observation, leading to confirm the whole is greater than the sum of its parts. Contemporary applications discussed in this book make all essential knowledge seamlessly integrated by an interdisciplinary manner. These case-based engineering practices uniquely illustrate how to improve such an emerging field of importance to cope with the most challenging real-world environmental monitoring issues.

Resource Efficiency Sustainability and Globalization

Resource Efficiency  Sustainability  and Globalization
Author: Manoranjan Mishra,Manoj Kumar Dash,Dinoj Kumar Upadhyay,Raj Kishor Kampa
Publsiher: CRC Press
Total Pages: 292
Release: 2021-12-23
ISBN 10: 100029224X
ISBN 13: 9781000292244
Language: EN, FR, DE, ES & NL

Resource Efficiency Sustainability and Globalization Book Review:

The EU is a major trade partner with India, and economic linkages continue to deepen. India and the EU have increased their political interactions and are crucial partners in promoting sustainable development. Recent trends in India-EU relations show that New Delhi and Brussels are keen to expand their partnership in multiple areas, including sustainable development and natural resources management. This volume takes a unique approach to exploring the efficient management of resources in the era of resource depletion due to climate changes and business expansion, in conjunction with considering the multiple dimensions of India-European Union cooperation. It analyzes regional and global trends in the process of globalization and sustainable development, particularly in the context of natural resource management and resource efficiency. It offers a variety of perspectives through useful and current information in this field, providing a concise and holistic understanding of the issues and challenges faced when exploiting natural resources for sustainable and efficient resource utilization.

Sustainability Metrics and Indicators of Environmental Impact

Sustainability Metrics and Indicators of Environmental Impact
Author: Eduardo Jacob-Lopes,Leila Queiroz Zepka,Mariany Costa Depra
Publsiher: Elsevier
Total Pages: 212
Release: 2021-07-16
ISBN 10: 0128236043
ISBN 13: 9780128236048
Language: EN, FR, DE, ES & NL

Sustainability Metrics and Indicators of Environmental Impact Book Review:

Sustainability Metrics and Indicators of Environmental Impact: Industrial and Agricultural Life Cycle Assessment covers trending topics on the environmental impact of systems of production, putting emphasis on lifecycle assessment (LCA). This methodology is one of the most important tools of analysis, as mathematical models are applied that will quantify the systematic inputs and outputs of the processes in order to evaluate the sustainability of industrial processes and products. In this sense, LCA is mainly a tool to support environmental decision-making that analyzes the environmental impacts of products and technologies from a lifecycle perspective. The emergence of ever-larger global issues, such as the energy dilemma, the changing climate and the scarcity of natural resources, such as water, has boosted the search for tools capable of ensuring the reliability of the results published by the industries, and has become an important tool in order to achieve sustainability and environmental preservation. Thus, lifecycle assessment (LCA), including carbon footprint valuation is necessary to ensure better internal management. Provides guidance on environmental impacts and the carbon footprint of industrial processes Features guidelines in lifecycle assessment to support a sustainable approach, along with quantifiable data to support proposed solutions Includes a companion website with slides and graphics to quantity environmental impact and other metrics of lifecycle assessment

Strategic Engineering for Cloud Computing and Big Data Analytics

Strategic Engineering for Cloud Computing and Big Data Analytics
Author: Amin Hosseinian-Far,Muthu Ramachandran,Dilshad Sarwar
Publsiher: Springer
Total Pages: 226
Release: 2017-02-13
ISBN 10: 3319524917
ISBN 13: 9783319524917
Language: EN, FR, DE, ES & NL

Strategic Engineering for Cloud Computing and Big Data Analytics Book Review:

This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy.