Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights

Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights PDF Author: Ilias S. Kotsireas
Publisher: Springer
ISBN: 3319437097
Category : Mathematics
Languages : en
Pages : 369

View

Book Description
This volume results from the “Second International Conference on Dynamics of Disasters” held in Kalamata, Greece, June 29-July 2, 2015. The conference covered particular topics involved in natural and man-made disasters such as war, chemical spills, and wildfires. Papers in this volume examine the finer points of disasters through: Critical infrastructure protection Resiliency Humanitarian logistic Relief supply chains Cooperative game theory Dynamical systems Decision making under risk and uncertainty Spread of diseases Contagion Funding for disaster relief Tools for emergency preparedness Response, and risk mitigation Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

Dynamics of Disasters

Dynamics of Disasters PDF Author: Ilias S. Kotsireas
Publisher: Springer
ISBN: 3319974424
Category : Mathematics
Languages : en
Pages : 202

View

Book Description
This book surveys new algorithmic approaches and applications to natural and man-made disasters such as oil spills, hurricanes, earthquakes and wildfires. Based on the “Third International Conference on Dynamics of Disasters” held in Kalamata, Greece, July 2017, this Work includes contributions in evacuation logistics, disaster communications between first responders, disaster relief, and a case study on humanitarian logistics. Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

Nonlinear Analysis and Global Optimization

Nonlinear Analysis and Global Optimization PDF Author: Themistocles M. Rassias
Publisher: Springer Nature
ISBN: 3030617327
Category : Mathematics
Languages : en
Pages : 486

View

Book Description
This contributed volume discusses aspects of nonlinear analysis in which optimization plays an important role, as well as topics which are applied to the study of optimization problems. Topics include set-valued analysis, mixed concave-convex sub-superlinear Schroedinger equation, Schroedinger equations in nonlinear optics, exponentially convex functions, optimal lot size under the occurrence of imperfect quality items, generalized equilibrium problems, artificial topologies on a relativistic spacetime, equilibrium points in the restricted three-body problem, optimization models for networks of organ transplants, network curvature measures, error analysis through energy minimization and stability problems, Ekeland variational principles in 2-local Branciari metric spaces, frictional dynamic problems, norm estimates for composite operators, operator factorization and solution of second-order nonlinear difference equations, degenerate Kirchhoff-type inclusion problems, and more.

Disaster Relief Aid

Disaster Relief Aid PDF Author: Bimal Kanti Paul
Publisher: Springer
ISBN: 3319772821
Category : Science
Languages : en
Pages : 262

View

Book Description
Disaster Relief Aid: Changes and Challenges provides a comprehensive analysis of disaster relief efforts undertaken globally during the last several decades, and examines the changes and challenges that have emerged over time. The book evaluates the current state of disaster relief and discusses how it may be improved. The author examines salient features of disaster relief operations and provides an overview of the development of global humanitarian assistance programs. The book also explores how disaster aid is channelled from non-affected areas to affected areas. Using five major natural and man-made disasters as case studies, the book analyses the nature and extent of emergency relief efforts undertaken for each. The final chapter covers the post-disaster convergence phenomenon; outlines the major challenges of international disaster relief operation and finally, posits recommendations on how to improve future disaster relief efforts. This is an essential interdisciplinary text on disaster response for both undergraduate and graduate students as well as an invaluable resource for disaster researchers, managers, and numerous international and national non-governmental organizations (NGOs) and international agencies.

Accelerating Monte Carlo methods for Bayesian inference in dynamical models

Accelerating Monte Carlo methods for Bayesian inference in dynamical models PDF Author: Johan Dahlin
Publisher: Linköping University Electronic Press
ISBN: 9176857972
Category :
Languages : en
Pages : 139

View

Book Description
Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. In this thesis, we make use of Bayesian statistics to construct probabilistic models given prior information and historical data, which can be used for decision support and predictions. The main obstacle with this approach is that it often results in mathematical problems lacking analytical solutions. To cope with this, we make use of statistical simulation algorithms known as Monte Carlo methods to approximate the intractable solution. These methods enjoy well-understood statistical properties but are often computational prohibitive to employ. The main contribution of this thesis is the exploration of different strategies for accelerating inference methods based on sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC). That is, strategies for reducing the computational effort while keeping or improving the accuracy. A major part of the thesis is devoted to proposing such strategies for the MCMC method known as the particle Metropolis-Hastings (PMH) algorithm. We investigate two strategies: (i) introducing estimates of the gradient and Hessian of the target to better tailor the algorithm to the problem and (ii) introducing a positive correlation between the point-wise estimates of the target. Furthermore, we propose an algorithm based on the combination of SMC and Gaussian process optimisation, which can provide reasonable estimates of the posterior but with a significant decrease in computational effort compared with PMH. Moreover, we explore the use of sparseness priors for approximate inference in over-parametrised mixed effects models and autoregressive processes. This can potentially be a practical strategy for inference in the big data era. Finally, we propose a general method for increasing the accuracy of the parameter estimates in non-linear state space models by applying a designed input signal. Borde Riksbanken höja eller sänka reporäntan vid sitt nästa möte för att nå inflationsmålet? Vilka gener är förknippade med en viss sjukdom? Hur kan Netflix och Spotify veta vilka filmer och vilken musik som jag vill lyssna på härnäst? Dessa tre problem är exempel på frågor där statistiska modeller kan vara användbara för att ge hjälp och underlag för beslut. Statistiska modeller kombinerar teoretisk kunskap om exempelvis det svenska ekonomiska systemet med historisk data för att ge prognoser av framtida skeenden. Dessa prognoser kan sedan användas för att utvärdera exempelvis vad som skulle hända med inflationen i Sverige om arbetslösheten sjunker eller hur värdet på mitt pensionssparande förändras när Stockholmsbörsen rasar. Tillämpningar som dessa och många andra gör statistiska modeller viktiga för många delar av samhället. Ett sätt att ta fram statistiska modeller bygger på att kontinuerligt uppdatera en modell allteftersom mer information samlas in. Detta angreppssätt kallas för Bayesiansk statistik och är särskilt användbart när man sedan tidigare har bra insikter i modellen eller tillgång till endast lite historisk data för att bygga modellen. En nackdel med Bayesiansk statistik är att de beräkningar som krävs för att uppdatera modellen med den nya informationen ofta är mycket komplicerade. I sådana situationer kan man istället simulera utfallet från miljontals varianter av modellen och sedan jämföra dessa mot de historiska observationerna som finns till hands. Man kan sedan medelvärdesbilda över de varianter som gav bäst resultat för att på så sätt ta fram en slutlig modell. Det kan därför ibland ta dagar eller veckor för att ta fram en modell. Problemet blir särskilt stort när man använder mer avancerade modeller som skulle kunna ge bättre prognoser men som tar för lång tid för att bygga. I denna avhandling använder vi ett antal olika strategier för att underlätta eller förbättra dessa simuleringar. Vi föreslår exempelvis att ta hänsyn till fler insikter om systemet och därmed minska antalet varianter av modellen som behöver undersökas. Vi kan således redan utesluta vissa modeller eftersom vi har en bra uppfattning om ungefär hur en bra modell ska se ut. Vi kan också förändra simuleringen så att den enklare rör sig mellan olika typer av modeller. På detta sätt utforskas rymden av alla möjliga modeller på ett mer effektivt sätt. Vi föreslår ett antal olika kombinationer och förändringar av befintliga metoder för att snabba upp anpassningen av modellen till observationerna. Vi visar att beräkningstiden i vissa fall kan minska ifrån några dagar till någon timme. Förhoppningsvis kommer detta i framtiden leda till att man i praktiken kan använda mer avancerade modeller som i sin tur resulterar i bättre prognoser och beslut.

Advances in Cross-Cultural Decision Making

Advances in Cross-Cultural Decision Making PDF Author: Dylan Schmorrow
Publisher: CRC Press
ISBN: 1439834962
Category : Technology & Engineering
Languages : en
Pages : 643

View

Book Description
The primary focus of the Cross Cultural Decision Making field is specifically on the intersections between psychosocial theory provided from the social sciences and methods of computational modeling provided from computer science and mathematics. While the majority of research challenges that arise out of such an intersection fall quite reasonably under the rubric of "human factors", although these topics are broad in nature, this book is designed to focus on crucial questions regarding data acquisition as well as reconciliation of mathematical and psychosocial modeling methodologies. The utility of this area of research is to aid the design of products and services which are utilized across the globe in the variety of cultures and aid in increasing the effectiveness of cross-cultural group collaboration. To aid a researcher in defining the requirements and metrics for this complex topic applications and use cases of CCDM can be found in sections: I. Applications of Human, Social, Culture Behavioral Modeling Technology IV. Cross Cultural Decision Making: Implications for Individual and Team Training X. Tactical Culture Training: Narrative, Personality, and Decision-Making XII. Use Cases of Cross Cultural Decision Making Theories and techniques for understanding, capturing, and modeling the components of Culture are covered in these sections: II. Assessing and Developing Cross-Cultural Competence III. Civilizational Change: Ideological, Economic, and Historical Change V. Cultural Models for Decision Making VI. Extracting Understanding from Diverse Data Sources VII. Hybrid & Multi-Model Computational Techniques for HSCB Applications IX. Socio-cultural Models and Decision-Making VIII. Sense Making in Other Cultures: Dynamics of Interaction XI. Understanding The science and technology provided in this book represents the latest available from the international community. It is hoped that this content can be used to tackle two of the biggest challenges in this area: 1) Unification and standardization of data being collected for CCDM applications/research so these data can support as many different thrusts under the CCDM umbrella as possible; and 2) Validation and verification with respect to utility and underlying psychosocial theory. Solutions for both of these must be in the context of, and will require, sound methods of integrating a complex array of quite different behavioral models and modeling techniques. This book would of special value to researchers and practitioners in involved in the design of products and services which are marketed and utilized in a variety of different countries Seven other titles in the Advances in Human Factors and Ergonomics Series are: Advances in Human Factors and Ergonomics in Healthcare Advances in Applied Digital Human Modeling Advances in Cognitive Ergonomics Advances in Occupational, Social and Organizational Ergonomics Advances in Human Factors, Ergonomics and Safety in Manufacturing and Service Industries Advances in Ergonomics Modeling & Usability Evaluation Advances in Neuroergonomics and Human Factors of Special Populations

Understanding and Reducing Landslide Disaster Risk

Understanding and Reducing Landslide Disaster Risk PDF Author: Nicola Casagli
Publisher: Springer Nature
ISBN: 3030603113
Category : Nature
Languages : en
Pages : 361

View

Book Description
This book is a part of ICL new book series “ICL Contribution to Landslide Disaster Risk Reduction” founded in 2019. Peer-reviewed papers submitted to the Fifth World Landslide Forum were published in six volumes of this book series. This book contains the followings: • One theme lecture and one keynote lecture• Monitoring and remote sensing for landslide risk mitigation, including one keynote lecture• Landslide early warning systems, forecasting models and time prediction of landslides Prof. Nicola Casagli is a Vice President and President-elect of the International Consortium on Landslides (ICL) for 2021–2023. He is Professor of engineering geology at the Department of Earth Sciences, University of Florence, and President of the National Institute of Oceanography and Applied Geophysics – OGS, Trieste, Italy. Dr. Veronica Tofani is an Associate Professor at the Department of Earth Sciences, University of Florence, and Program Coordinator of the UNESCO Chair on Prevention and Sustainable Management of Geo-hydrological hazards, University of Florence. Prof. Kyoji Sassa is the Founding President and the Secretary-General of the International Consortium on Landslides (ICL). He has been the Editor-in-Chief of International Journal Landslides since its foundation in 2004. Prof. Peter Bobrowsky is the President of the International Consortium on Landslides. He is a Senior Scientist of Geological Survey of Canada, Ottawa, Canada. Prof. Kaoru Takara is the Executive Director of the International Consortium on Landslides. He is a Professor and Dean of Graduate School of Advanced Integrated Studies (GSAIS) in Human Survivability (Shishu-Kan), Kyoto University.

Model-Based Predictive Control

Model-Based Predictive Control PDF Author: J.A. Rossiter
Publisher: CRC Press
ISBN: 135198859X
Category : Technology & Engineering
Languages : en
Pages : 344

View

Book Description
Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.

Accident and Emergency Informatics

Accident and Emergency Informatics PDF Author: T.M. Deserno
Publisher: IOS Press
ISBN: 164368275X
Category : Medical
Languages : en
Pages : 180

View

Book Description
Time is short in emergency situations; the need for action becomes imperative. Biomedical Informatics can be invaluable in supporting the management of emergency medicine, and the need for the creation of Accident and Emergency Informatics (A&EI) as a novel subfield became obvious. As in all areas of Biomedical Informatics, A&EI must deal with issues such as relevant data collection, the management of data extracted from accident sites, health records or sensors, wearables and apps, and appropriate data processing, with the dual purpose of preventing harm and decision support. This book is an introduction to the research and application domain of A&EI, and is the product of three years’ work by the Working Group in A&EI of the International Medical Informatics Association (IMIA). The book presents ten chapters organized in four sections. The first section explores the framework for achieving an emergency-informatics health information infrastructure; the second focuses on the gathering of critical clinical data related to the building up of a smart environment for A&EI; the third introduces state-of-the-art technologies for integration into virtual emergency registries; and the final part considers the delicate issues of patient safety raised by the introduction of surveillance technologies into clinical care, along with other issues presenting challenges to the domain of A&EI for the future. The book is an important contribution to the field of A&EI, and will be of interest to healthcare professionals, informaticians, and all those who want a better understanding of the domain of Accident and Emergency Informatics.

Smart Technologies for Emergency Response and Disaster Management

Smart Technologies for Emergency Response and Disaster Management PDF Author: Liu, Zhi
Publisher: IGI Global
ISBN: 1522525769
Category : Technology & Engineering
Languages : en
Pages : 312

View

Book Description
Disaster management is an imperative area of concern for society on a global scale. Understanding how to best utilize information and communication technology to help manage emergency and disaster situations will lead to more effective advances and innovations in this important field. Smart Technologies for Emergency Response and Disaster Management is a pivotal reference source that overviews current difficulties, challenges, and solutions that technology must adapt to in crisis situations. Highlighting pertinent topics such as network recovery, evacuation design, sensing technologies, and video technology, this publication is ideal for engineers, professionals, academicians, and researchers interested in discovering more about emerging technologies in crisis management.