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Applied Machine Learning and Data Analytics: 6th International Conference, AMLDA 2023, Lübeck, Germany, November 9–10, 2023, Revised Selected Papers (Communications in Computer and Information Science #2047)
by Sven Groppe M. A. Jabbar Sanju Tiwari Fernando Ortiz-Rodríguez Tasneem Bano RehmanThis book constitutes the refereed conference proceedings of the 6th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2023, held in Lübeck, Germany, during November 9–10, 2023.The 17 full papers and 2 short papers presented in this book were carefully reviewed and selected from 76 submissions. The main conference AMLDA 2023 is renowned for presenting cutting-edge research on all aspects of machine learning as well as important application areas such as healthcare and medical imaging informatics, biometrics, forensics, precision agriculture, risk management, robotics, and satellite imaging.
Applied Machine Learning and High-Performance Computing on AWS: Accelerate the development of machine learning applications following architectural best practices
by Shreyas Subramanian Trenton Potgieter Mani Khanuja Farooq SabirBuild, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMakerKey FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook DescriptionMachine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles.This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases.By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle.What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is forThe book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.
Applied Machine Learning for Assisted Living
by Zia UddinUser care at home is a matter of great concern since unforeseen circumstances might occur that affect people's well-being. Technologies that assist people in independent living are essential for enhancing care in a cost-effective and reliable manner. Assisted care applications often demand real-time observation of the environment and the resident’s activities using an event-driven system. As an emerging area of research and development, it is necessary to explore the approaches of the user care system in the literature to identify current practices for future research directions. Therefore, this book is aimed at a comprehensive review of data sources (e.g., sensors) with machine learning for various smart user care systems. To encourage the readers in the field, insights of practical essence of different machine learning algorithms with sensor data (e.g., publicly available datasets) are also discussed. Some code segments are also included to motivate the researchers of the related fields to practically implement the features and machine learning techniques. It is an effort to obtain knowledge of different types of sensor-based user monitoring technologies in-home environments. With the aim of adopting these technologies, research works, and their outcomes are reported. Besides, up to date references are included for the user monitoring technologies with the aim of facilitating independent living.Research that is related to the use of user monitoring technologies in assisted living is very widespread, but it is still consists mostly of limited-scale studies. Hence, user monitoring technology is a very promising field, especially for long-term care. However, monitoring of the users for smart assisted technologies should be taken to the next level with more detailed studies that evaluate and demonstrate their potential to contribute to prolonging the independent living of people. The target of this book is to contribute towards that direction.
Applied Machine Learning for Data Science Practitioners
by Vidya SubramanianA single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Applied Machine Learning for Health and Fitness: A Practical Guide to Machine Learning with Deep Vision, Sensors and IoT
by Kevin AshleyExplore the world of using machine learning methods with deep computer vision, sensors and data in sports, health and fitness and other industries. Accompanied by practical step-by-step Python code samples and Jupyter notebooks, this comprehensive guide acts as a reference for a data scientist, machine learning practitioner or anyone interested in AI applications. These ML models and methods can be used to create solutions for AI enhanced coaching, judging, athletic performance improvement, movement analysis, simulations, in motion capture, gaming, cinema production and more.Packed with fun, practical applications for sports, machine learning models used in the book include supervised, unsupervised and cutting-edge reinforcement learning methods and models with popular tools like PyTorch, Tensorflow, Keras, OpenAI Gym and OpenCV. Author Kevin Ashley—who happens to be both a machine learning expert and a professional ski instructor—has written an insightful book that takes you on a journey of modern sport science and AI. Filled with thorough, engaging illustrations and dozens of real-life examples, this book is your next step to understanding the implementation of AI within the sports world and beyond. Whether you are a data scientist, a coach, an athlete, or simply a personal fitness enthusiast excited about connecting your findings with AI methods, the author’s practical expertise in both tech and sports is an undeniable asset for your learning process. Today’s data scientists are the future of athletics, and Applied Machine Learning for Health and Fitness hands you the knowledge you need to stay relevant in this rapidly growing space.What You'll LearnUse multiple data science tools and frameworksApply deep computer vision and other machine learning methods for classification, semantic segmentation, and action recognitionBuild and train neural networks, reinforcement learning models and moreAnalyze multiple sporting activities with deep learningUse datasets available today for model trainingUse machine learning in the cloud to train and deploy modelsApply best practices in machine learning and data scienceWho This Book Is ForPrimarily aimed at data scientists, coaches, sports enthusiasts and athletes interested in connecting sports with technology and AI methods.
Applied Machine Learning for Healthcare and Life Sciences Using AWS: Transformational AI implementations for biotech, clinical, and healthcare organizations
by Ujjwal RatanBuild real-world artificial intelligence apps on AWS to overcome challenges faced by healthcare providers and payers, as well as pharmaceutical, life sciences research, and commercial organizationsKey FeaturesLearn about healthcare industry challenges and how machine learning can solve themExplore AWS machine learning services and their applications in healthcare and life sciencesDiscover practical coding instructions to implement machine learning for healthcare and life sciencesBook DescriptionWhile machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics. This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You'll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications. By the end of this book, you'll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence.What you will learnExplore the healthcare and life sciences industryFind out about the key applications of AI in different industry segmentsApply AI to medical images, clinical notes, and patient dataDiscover security, privacy, fairness, and explainability best practicesExplore the AWS ML stack and key AI services for the industryDevelop practical ML skills using code and AWS servicesDiscover all about industry regulatory requirementsWho this book is forThis book is specifically tailored toward technology decision-makers, data scientists, machine learning engineers, and anyone who works in the data engineering role in healthcare and life sciences organizations. Whether you want to apply machine learning to overcome common challenges in the healthcare and life science industry or are looking to understand the broader industry AI trends and landscape, this book is for you. This book is filled with hands-on examples for you to try as you learn about new AWS AI concepts.
Applied Machine Learning for Smart Data Analysis (Computational Intelligence in Engineering Problem Solving)
by Nilanjan Dey Sanjeev Wagh Parikshit Mahalle Mohd. PathanThe book focusses on how machine learning and Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results.
Applied Macroeconomics: A Practical Introduction
by Christian A. ConradThis textbook provides a comprehensive overview of macroeconomic relationships and explains the most important macroeconomic variables in an easy-to-understand manner. The reader is introduced to important macroeconomic variables such as inflation and aggregate demand in chapters that build on one another. They learn, among other things, how economic crises arise or the role and functioning of money, capital and goods markets. The aim is to provide the reader with economic knowledge that can be applied in business practice. The economics material has been deliberately selected so that business studies content is usefully supplemented. However, detailed explanations and both application-oriented and practice-related examples and exercises make it easy for non-economists to understand the complex economic topics. Well-founded knowledge presented in an immediately comprehensible way!
Applied Magic
by Dion FortunePractical applications of occultism, the group mind, the psychology of ritual, the circuit of force, 3 kinds of reality, non-humans, black magic, including an esoteric glossary
Applied Malting and Brewing Science: A Weihenstephan Compendium
by Werner Back Martin Zarnkow Martina Gastl Ludwig NarzißApplied Malting and Brewing Science The landmark guide to malting and brewing science is available in English for the first time Humans have been producing fermented beverages for at least ten thousand years. Chief among them is beer, which has arguably never been more popular than it is at this point in history. The United States alone boasts more than 9,500 breweries, a number which has risen steadily as the market for craft beer continues to grow in that country. Thus, maltsters and brewers there and around the world are constantly looking for ways to hone their skills to create products of the highest quality as consistently as possible. With the detailed information presented in this book, they will not only be able to reacquaint themselves with the basic tenets of their profession but will also acquire an in-depth scientific foundation and a wide range of practical knowledge in all aspects of advanced malting and brewing. This landmark work on malting and brewing, originally entitled Abriss der Bierbrauerei, is currently in its eighth edition and has hitherto only been offered in the German language. However, it is now finally available for the first time in translation, as an unabridged and updated English edition. Applied Malting and Brewing Science is a reference for those interested in any facet of malt and beer production, including all of the most recent technical innovations in equipment and processes. This book represents the collective knowledge amassed over many decades of research by Ludwig Narziß in his tenure as Professor at the Chair for Brewing Technology at Weihenstephan. Readers of Applied Malting and Brewing Science will find the following: Comprehensive treatment of topics covering raw materials, malt and wort production, fermentation, packaging and much more A team of authors with decades of experience in the fields of malting and brewing science, both in academia and in their application in the industry A design which facilitates use of the book as both a student textbook and as a practical guide Written by the late Ludwig Narziß and his team, Applied Malting and Brewing Science is an indispensable source for students at any level in related scientific disciplines and for anyone working in the malting and brewing industry.
Applied Manure and Nutrient Chemistry for Sustainable Agriculture and Environment
by Zhongqi He Hailin ZhangDue to the rapid increase in world population and improving living standards, the global agriculture sector is confronting with challenges for the sustainability of agricultural production and of the environment. Intensive high-yield agriculture is typically dependent on addition of fertilizers (synthetic chemicals, animal manure, etc. ). However, non-point nutrient losses from agricultural fields due to fertilization could adversely impact the environment. Increased knowledge on plant nutrient chemistry is required for improving utilization efficiency and minimizing loses from both inorganic and organic nutrient sources. For this purpose, the book is composed of 19 chapters that highlight recent research activities in applied nutrient chemistry geared toward sustainable agriculture and environment. Topics of interest include, but are not limited, to speciation, quantification, and interactions of various plant nutrients and relevant contributories in manure, soil, and plants. This book outlooks emerging researchable issues on alternative utilization and environmental monitoring of manure and other agricultural by products that may stimulate new research ideas and direction in the relevant fields.
Applied Marketing Analytics Using Python
by Gokhan Yildirim Raoul V. KüblerIt is vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success. Taking a very hands-on approach with the use of real-world datasets, case studies and Python, this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks. Supporting online resources include datasets and software codes and solutions as well as PowerPoint slides, a teaching guide and a testbank. This book is essential reading for advanced level marketing students and practitioners who want to become cutting-edge marketers. Dr Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London. Dr Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.
Applied Marketing Analytics Using R
by Gokhan Yildirim Raoul V. KüblerMarketing has become increasingly data-driven in recent years as a result of new emerging technologies such as AI, granular data availability and ever-growing analytics tools. With this trend only set to continue, it’s vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success. Taking a very hands-on approach with the use of real-world datasets, case studies and R (a free statistical package), this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks. Chapters include learning objectives, figures, tables and questions to help facilitate learning. Also included online with the datasets are software codes and solutions (R Markdowns, HTML files) to use with the book, as well as PowerPoint slides, a teaching guide and a testbank for instructors teaching a marketing analytics course. This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers. Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London. Dr. Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.
Applied Marketing Analytics Using R
by Gokhan Yildirim Raoul V. KüblerMarketing has become increasingly data-driven in recent years as a result of new emerging technologies such as AI, granular data availability and ever-growing analytics tools. With this trend only set to continue, it’s vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success. Taking a very hands-on approach with the use of real-world datasets, case studies and R (a free statistical package), this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks. Chapters include learning objectives, figures, tables and questions to help facilitate learning. Also included online with the datasets are software codes and solutions (R Markdowns, HTML files) to use with the book, as well as PowerPoint slides, a teaching guide and a testbank for instructors teaching a marketing analytics course. This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers. Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London. Dr. Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.
Applied Mass Communication Theory: A Guide for Media Practitioners
by Jack Rosenberry Lauren A. VickerApplied Mass Communication Theory: A Guide for Media Practitioners, Second Edition bridges a review of theory to the contemporary work of media professionals. The text provides a framework for constructing an undergraduate research project. It also presents vital chronological information on the progression of theory in mass communication, including a model that integrates mass communication theories and shows how they relate to one another. It concludes with information on media law, ethics, economics, and mass media careers, establishing a critical framework for students as they leave college and begin their first jobs. This Second Edition discusses mass communication theory and its applications in both traditional print and broadcast applications. By exploring advertising and public relations in this new digital multi-media environment, this text remains relevant, and in fact necessary, for students in the field.
Applied Mass Communication Theory: A Guide for Media Practitioners
by Jack Rosenberry Lauren A. VickerNow in its third edition, this dynamic textbook blends coverage of the major theories and research methods in mass communication to enable students to apply their knowledge in today’s media and communication careers. Maintaining a focus on modern professional application throughout, this text provides chronological coverage of the development and use of major theories, an overview of both quantitative and qualitative research methods, and a step-by-step guide to conducting a research project informed by this knowledge. It helps students bridge their academic coursework with professional contexts including public relations, advertising, and digital media contexts. It provides breakout boxes with definitions of key terms and theories, extended applied examples, and graphical models of key theories to offer a visualization of how the various concepts in the theory fit together. Applied Mass Communication Theory’s hybrid and flexible nature make it a useful textbook for both introductory and capstone courses on mass communication and media theory and research methods, as well as courses focused on media industries and professional skills. Instructors can access an online instructor’s manual, including sample exercises, test questions, and a syllabus, at www.routledge.com/9780367630362
Applied Materials Science: Applications of Engineering Materials in Structural, Electronics, Thermal, and Other Industries
by Deborah D. ChungMaterials are the foundation of technology. As such, most universities provide engineering undergraduates with the fundamental concepts of materials science, including crystal structures, imperfections, phase diagrams, materials processing, and materials properties. Few, however, offer the practical, applications-oriented background that their stud
Applied Math for Wastewater Plant Operators
by Joanne K. PriceWith many worked examples, this book provides step-by-step instruction for all calculations required for wastewater treatment. Pertinent calculations are conveniently summarized in each chapter. The text covers all the fundamental math concepts and skills needed for daily wastewater treatment plant operations. The workbook for this book can be purc
Applied Math for Wastewater Plant Operators - Workbook
by Joanne K. PriceThis workbook is a companion to Applied Math for Wastewater Plant Operators (ISBN: 9780877628095) and part of the Applied Math for Wastewater Plant Operators Set (ISBN: 9781566769891). It contains self-teaching guides for all wastewater treatment calculations, skill checks, hundreds of worked examples, and practice problems.
Applied Math for Water Plant Operators
by Joanne K. PriceWith many worked examples, this book provides a step-by-step training manual for water treatment calculations. It presents all the fundamental math concepts and skills needed for daily water treatment plant operations. The text covers volume, flow and velocity, milligrams per liter to pounds per day, loading rate, detention and retention times, eff
Applied Mathematical Analysis and Computations I: 1st SGMC, Statesboro, USA, April 2–3, 2021 (Virtual) (Springer Proceedings in Mathematics & Statistics #471)
by Divine Wanduku Shijun Zheng Haomin Zhou Zhan Chen Andrew Sills Ephraim AgyingiThis volume convenes selected, peer-reviewed research and survey articles that address the modern state-of-the-art in varied areas of applied mathematical analysis. They primarily include presentations as well as invited contributions for the 1st Southern Georgia Mathematics Conference (SGMC) that was virtually held on April 2—3, 2021 at the Georgia Southern University, Statesboro, USA. Papers in this volume incorporate both advanced theory and methods from mathematical analysis, and cover myriad topics like imaging and inverse problems, evolutionary PDEs, symbolic computation, dynamics and data analysis, data science, computational mathematics, and more. This first volume focuses on mathematical analysis theory and applications. These studies and findings contained herein will be of interest to researchers and graduate students working in the fields of mathematical analysis, modeling, data analysis and computation, with applications in many interdisciplinary applied sciences, as in statistics, physics, biology, and medical imaging. They are particularly relevant to those at the forefront of applied mathematical and statistical analysis, as well as data science and other computational science disciplines. In its first edition, the Southern Georgia Mathematics Conference brought together 74 speakers from 70 different institutions, from the USA, Canada, Austria, and Botswana. Attendees included faculty, researchers, experts, graduate and undergraduate students from all over the world.
Applied Mathematical Analysis and Computations II: 1st SGMC, Statesboro, USA, April 2–3, 2021 (Virtual) (Springer Proceedings in Mathematics & Statistics #472)
by Divine Wanduku Shijun Zheng Haomin Zhou Zhan Chen Andrew Sills Ephraim AgyingiThis volume convenes selected, peer-reviewed research and survey articles that address the modern state-of-the-art in varied areas of applied mathematical analysis. They were presented at the 1st Southern Georgia Mathematics Conference (SGMC) that was virtually held on April 2—3, 2021, at Georgia Southern University, Statesboro, USA. Papers in this volume incorporate both advanced theory and methods from mathematical analysis and cover myriad topics such as imaging and inverse problems, evolutionary PDEs, symbolic computation, dynamics and data analysis, data science, computational mathematics, and more. This second volume focuses on modeling, simulation and data analytical studies in the field of computational mathematics. These studies and findings contained herein will be of interest to researchers and graduate students working in the fields of mathematical analysis, modeling, data analysis, and computation, with applications in many interdisciplinary applied sciences, including statistics, physics, biology, and medical imaging. They are particularly relevant to those at the forefront of applied mathematical and statistical analysis, as well as data science and other computational science disciplines. In its first edition, the Southern Georgia Mathematics Conference brought together 74 speakers from 70 different institutions, including the USA, Canada, Austria, and Botswana. Attendees included faculty, researchers, experts, graduate, and undergraduate students from all over the world.
Applied Mathematical Analysis: Theory, Methods, and Applications (Studies in Systems, Decision and Control #177)
by James F. Peters Hemen DuttaThis book addresses key aspects of recent developments in applied mathematical analysis and its use. It also highlights a broad range of applications from science, engineering, technology and social perspectives. Each chapter investigates selected research problems and presents a balanced mix of theory, methods and applications for the chosen topics. Special emphasis is placed on presenting basic developments in applied mathematical analysis, and on highlighting the latest advances in this research area. The book is presented in a self-contained manner as far as possible, and includes sufficient references to allow the interested reader to pursue further research in this still-developing field. The primary audience for this book includes graduate students, researchers and educators; however, it will also be useful for general readers with an interest in recent developments in applied mathematical analysis and applications.
Applied Mathematical Modeling and Analysis in Renewable Energy (Mathematical Engineering, Manufacturing, and Management Sciences)
by Manoj Sahni Ritu SahniThis reference text introduces latest mathematical modeling techniques and analysis for renewable energy systems. It comprehensively covers important topics including study of combustion characteristics of laser ignited gasoline-air mixture, hierarchical demand response controller, mathematical modeling of an EOQ for a multi-item inventory system, and integration and modeling of small-scale pumped storage with micro optimization model (HOMER). Aimed at graduate students and academic researchers in the fields of electrical engineering, environmental engineering, mechanical engineering, and civil engineering, this text: Discusses applied mathematical modeling techniques in renewable energy. Covers effective storage and generation of power through renewable energy generation sources. Provides real life applications and problems based on renewable energy. Covers new ways of applying mathematical techniques for applications in diverse areas of science and engineering.
Applied Mathematical Problems in Geophysics: Cetraro, Italy 2019 (Lecture Notes in Mathematics #2308)
by Vincenzo Vespri Massimo ChiappiniThis CIME Series book provides mathematical and simulation tools to help resolve environmental hazard and security-related issues.The contributions reflect five major topics identified by the SIES (Strategic Initiatives for the Environment and Security) as having significant societal impact: optimal control in waste management, in particular the degradation of organic waste by an aerobic biomass, by means of a mathematical model; recent developments in the mathematical analysis of subwave resonators; conservation laws in continuum mechanics, including an elaboration on the notion of weak solutions and issues related to entropy criteria; the applications of variational methods to 1-dimensional boundary value problems, in particular to light ray-tracing in ionospheric physics; and the mathematical modelling of potential electromagnetic co-seismic events associated to large earthquakes.This material will provide a sound foundation for those who intend to approach similar problems from a multidisciplinary perspective.