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Application and Theory of Petri Nets and Concurrency: 37th International Conference, PETRI NETS 2016, Toruń, Poland, June 19-24, 2016. Proceedings (Lecture Notes in Computer Science #9698)
by Fabrice Kordon Daniel MoldtThis book constitutes the proceedings of the 37th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2016, held in Toruń, Poland, in June 2016. Petri Nets 2016 was co-located with the Application of Concurrency to System Design Conference, ACSD 2016.The 16 papers including 3 tool papers with 4 invited talks presented together in this volume were carefully reviewed and selected from 42 submissions. Papers presenting original research on application or theory of Petri nets, as well as contributions addressing topics relevant to the general field of distributed and concurrent systems are presented within this volume.
Application and Theory of Petri Nets and Concurrency: 38th International Conference, PETRI NETS 2017, Zaragoza, Spain, June 25–30, 2017, Proceedings (Lecture Notes in Computer Science #10258)
by Wil Van der Aalst Eike BestThis book constitutes the proceedings of the 38th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2017, held in Zaragoza, Spain, in June 2017. Petri Nets 2017 is co-located with the Application of Concurrency to System Design Conference, ACSD 2017. The 16 papers, 9 theory papers, 4 application papers, and 3 tool papers, with 1 short abstract and 3 extended abstracts of invited talks presented together in this volume were carefully reviewed and selected from 33 submissions. The focus of the conference is on following topics: Simulation of Colored Petri Nets, Petri Net Tools. - Model Checking, Liveness and Opacity, Stochastic Petri Nets, Specific Net Classes, and Petri Nets for Pathways.
Application-Inspired Linear Algebra (Springer Undergraduate Texts in Mathematics and Technology)
by Heather A. Moon Thomas J. Asaki Marie A. SnipesThis textbook invites students to discover abstract ideas in linear algebra within the context of applications. Diffusion welding and radiography, the two central applications, are introduced early on and used throughout to frame the practical uses of important linear algebra concepts. Students will learn these methods through explorations, which involve making conjectures and answering open-ended questions. By approaching the subject in this way, new avenues for learning the material emerge: For example, vector spaces are introduced early as the appropriate setting for the applied problems covered; and an alternative, determinant-free method for computing eigenvalues is also illustrated. In addition to the two main applications, the authors also describe possible pathways to other applications, which fall into three main areas: Data and image analysis (including machine learning); dynamical modeling; and optimization and optimal design. Several appendices are included as well, one of which offers an insightful walkthrough of proof techniques. Instructors will also find an outline for how to use the book in a course. Additional resources can be accessed on the authors’ website, including code, data sets, and other helpful material. Application-Inspired Linear Algebra will motivate and immerse undergraduate students taking a first course in linear algebra, and will provide instructors with an indispensable, application-first approach.
Application of Clinical Bioinformatics (Translational Bioinformatics #11)
by Xiangdong Wang Christian Baumgartner Denis C. Shields Hong-Wen Deng Jacques S. BeckmannThis bookelucidates how genetic, biological and medical information can be applied tothe development of personalized healthcare, medication and therapies. Focusingon aspects of the development of evidence-based approaches in bioinformaticsand computational medicine, including data integration, methodologies, toolsand models for clinical and translational medicine, it offers an essentialintroduction to clinical bioinformatics for clinical researchers andphysicians, medical students and teachers, and scientists working with human disease-based omics and bioinformatics. Dr. XiangdongWang is a distinguished Professor of Medicine. He is Director of ShanghaiInstitute of Clinical Bioinformatics, Director of Fudan University Center forClinical Bioinformatics, Deputy Director of Shanghai Respiratory ResearchInstitute, Director of Biomedical Research Center, Fudan University ZhongshanHospital, Shanghai, China; Dr. Christian Baumgartner is a Professor of HealthCare and Biomedical Engineering at Institute of Health Care Engineering withEuropean Notified Body of Medical Devices, Graz University of Technology, Graz,Austria; Dr. Denis Shields is a Professor of ClinicalBioinformatics at Conway Institute, Belfield, Dublin, Ireland; Dr. Hong-Wen Dengis a Professor at Department of Biostatistics and Bioinformatics, Tulane UniversitySchool of Public Health and Tropical Medicine, USA; Dr. Jacques SBeckmann is a Professor and Director of Section of Clinical Bioinformatics,Swiss Institute of Bioinformatics, Switzerland.
Application of Fuzzy Logic to Social Choice Theory
by John N. Mordeson Davender S. Malik Terry D. ClarkFuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy max
Application of Geometric Algebra to Electromagnetic Scattering: The Clifford-Cauchy-Dirac Technique
by Andrew SeagarThis work presents the Clifford-Cauchy-Dirac (CCD) technique for solving problems involving the scattering of electromagnetic radiation from materials of all kinds. It allows anyone who is interested to master techniques that lead to simpler and more efficient solutions to problems of electromagnetic scattering than are currently in use. The technique is formulated in terms of the Cauchy kernel, single integrals, Clifford algebra and a whole-field approach. This is in contrast to many conventional techniques that are formulated in terms of Green's functions, double integrals, vector calculus and the combined field integral equation (CFIE). Whereas these conventional techniques lead to an implementation using the method of moments (MoM), the CCD technique is implemented as alternating projections onto convex sets in a Banach space. The ultimate outcome is an integral formulation that lends itself to a more direct and efficient solution than conventionally is the case, and applies without exception to all types of materials. On any particular machine, it results in either a faster solution for a given problem or the ability to solve problems of greater complexity. The Clifford-Cauchy-Dirac technique offers very real and significant advantages in uniformity, complexity, speed, storage, stability, consistency and accuracy.
Application of Gray System Theory in Fishery Science
by Xinjun ChenThis book reviews the gray system and combines its latest research results in fishery science. The chapters cover the basic concept and theory of gray system, original data processing and gray sequence generation, gray correlation analysis, gray cluster analysis, gray system modeling, gray prediction, gray decision-making, and gray linear programming. The theory of gray system is a new cross-sectional discipline founded in 1982 by Professor Deng Julong, a well-known scholar in China. In recent decades, it has not only been deepened and expanded in theory but also widely used in the fields of society, economy, ocean, agriculture, fishery, and other fields, and made a series of significant scientific achievements. These have laid the foundation for the important position of the gray system theory. Due to the great uncertainty of the fishery resources and the fishery environment involved in the fishery science system, which is completely different from the natural resources on the land, the data and information belong to the category of “poor information”, and the variability and uncertainty are greater than other natural resources. As an extremely effective analytical method and tool, gray system theory has been applied increasingly in fishery science. The book is developed based on well-read and practical literature and will help scientists and research units engaged in scientific research and teaching in fishery science and related fields to develop new research methods and tools.
Application of Integrable Systems to Phase Transitions
by C. B. WangThe eigenvalue densities in various matrix models in quantum chromodynamics (QCD) are ultimately unified in this book by a unified model derived from the integrable systems. Many new density models and free energy functions are consequently solved and presented. The phase transition models including critical phenomena with fractional power-law for the discontinuities of the free energies in the matrix models are systematically classified by means of a clear and rigorous mathematical demonstration. The methods here will stimulate new research directions such as the important Seiberg-Witten differential in Seiberg-Witten theory for solving the mass gap problem in quantum Yang-Mills theory. The formulations and results will benefit researchers and students in the fields of phase transitions, integrable systems, matrix models and Seiberg-Witten theory.
Application of Mathematics and Optimization in Construction Project Management
by Hêriş GolpîraThis book provides a broad overview of project and project management principles, processes, and success/failure factors. It also provides a state of the art of applications of the project management concepts, especially in the field of construction projects, based on the Project Management Body of Knowledge (PMBOK). The slate of geographically and professionally diverse authors illustrates project management as a multidisciplinary undertaking that integrates renewable and non-renewable resources in a systematic process to achieve project goals. The book describes assessment based on technical and operational goals and meeting schedules and budgets.
The Application of Neural Networks in the Earth System Sciences
by Vladimir M. KrasnopolskyThis book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN - the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. "This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods." (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) "Vladimir Krasnopolsky has been the "founding father" of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science." (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) "Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." " (Prof. Eugenia Kalnay, University of Maryland, USA)
Application of Regularized Regressions to Identify Novel Predictors in Clinical Research
by Ton J. Cleophas Aeilko H. ZwindermanThis textbook is an important novel menu for multiple variables regression entitled "regularized regression". It is a must have for identifying unidentified leading factors. Also, you get fitted parameters for your overfitted data. Finally, there is no more need for commonly misunderstood p-values. Instead, the regression coefficient, R-value, as reported from a regression line has been applied as the key predictive estimator of the regression study. With simple one by one variable regression it is no wider than -1 to +1. With multiple variables regression it can easily get > +1 or In the past two decades regularized regression has become a major topic of research, particularly with high dimensional data. Yet, the method is pretty new and infrequently used in real-data analysis. Its performance as compared to traditional null hypothesis testing has to be confirmed by prospective comparisons. Most studies published to date are of a theoretical nature involving statistical modeling and simulation studies. The journals Nature and Science published 19 and 10 papers of this sort in the past 8 years. The current edition will for the first time systematically test regularized regression against traditional regression analysis in 20 clinical data examples. The edition is also a textbook and tutorial for medical and healthcare students as well as recollection bench and help desk for professionals. Each chapter can be studied as a standalone, and, using, real as well as hypothesized data, it tests the performance of the novel methodology against traditional regressions. Step by step analyses of 20 data files are included for self-assessment. The authors are well qualified in their field. Professor Zwinderman is past-president of the International Society of Biostatistics and Professor Cleophas is past-president of the American College of Angiology. The authors have been working together for 25 years and their research can be characterized as a continued effort to demonstrate that clinical data analysis is a discipline at the interface of biology and mathematics.
Application of Soft Computing and Intelligent Methods in Geophysics (Springer Geophysics)
by Alireza Hajian Peter StylesThis book provides a practical guide to applying soft-computing methods to interpret geophysical data. It discusses the design of neural networks with Matlab for geophysical data, as well as fuzzy logic and neuro-fuzzy concepts and their applications. In addition, it describes genetic algorithms for the automatic and/or intelligent processing and interpretation of geophysical data.
Application of Surrogate-based Global Optimization to Aerodynamic Design (Springer Tracts in Mechanical Engineering)
by Emiliano Iuliano Esther Andrés PérezAerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive - this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogate and reduced-order models can provide a valuable alternative at a much lower computational cost. In this context, this volume offers advanced surrogate modeling applications and optimization techniques featuring reasonable computational resources. It also discusses basic theory concepts and their application to aerodynamic design cases. It is aimed at researchers and engineers who deal with complex aerodynamic design problems on a daily basis and employ expensive simulations to solve them.
The Application of the Chebyshev-Spectral Method in Transport Phenomena
by Ranga Narayanan Gérard Labrosse Weidong GuoTransport phenomena problems that occur in engineering and physics are often multi-dimensional and multi-phase in character. When taking recourse to numerical methods the spectral method is particularly useful and efficient. The book is meant principally to train students and non-specialists to use the spectral method for solving problems that model fluid flow in closed geometries with heat or mass transfer. To this aim the reader should bring a working knowledge of fluid mechanics and heat transfer and should be readily conversant with simple concepts of linear algebra including spectral decomposition of matrices as well as solvability conditions for inhomogeneous problems. The book is neither meant to supply a ready-to-use program that is all-purpose nor to go through all manners of mathematical proofs. The focus in this tutorial is on the use of the spectral methods for space discretization, because this is where most of the difficulty lies. While time dependent problems are also of great interest, time marching procedures are dealt with by briefly introducing and providing a simple, direct, and efficient method. Many examples are provided in the text as well as numerous exercises for each chapter. Several of the examples are attended by subtle points which the reader will face while working them out. Some of these points are deliberated upon in endnotes to the various chapters, others are touched upon in the book itself.
Application of Wavelets in Speech Processing (SpringerBriefs in Speech Technology)
by Mohamed Hesham FaroukThis book provides a survey on wide-spread of employing wavelets analysis in different applications of speech processing. The author examines development and research in different applications of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.
Application of Wavelets in Speech Processing (SpringerBriefs in Speech Technology)
by Mohamed Hesham FaroukThis book provides a survey on wide-spread of employing wavelets analysis in different applications of speech processing. The author examines development and research in different applications of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.
Applications in Reliability and Statistical Computing (Springer Series in Reliability Engineering)
by Hoang PhamThis book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.
Applications in Statistical Computing: From Music Data Analysis to Industrial Quality Improvement (Studies in Classification, Data Analysis, and Knowledge Organization)
by Nadja Bauer Katja Ickstadt Karsten Lübke Gero Szepannek Heike Trautmann Maurizio VichiThis volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
Applications of Advanced Optimization Techniques in Industrial Engineering (Information Technology, Management and Operations Research Practices)
by Abhinav Goel Anand Chauhan A. K. MalikThis book provides different approaches used to analyze, draw attention, and provide an understanding of the advancements in the optimization field across the globe. It brings all of the latest methodologies, tools, and techniques related to optimization and industrial engineering into a single volume to build insights towards the latest advancements in various domains. Applications of Advanced Optimization Techniques in Industrial Engineering includes the basic concept of optimization, techniques, and applications related to industrial engineering. Concepts are introduced in a sequential way along with explanations, illustrations, and solved examples. The book goes on to explore applications of operations research and covers empirical properties of a variety of engineering disciplines. It presents network scheduling, production planning, industrial and manufacturing system issues, and their implications in the real world. The book caters to academicians, researchers, professionals in inventory analytics, business analytics, investment managers, finance firms, storage-related managers, and engineers working in engineering industries and data management fields.
Applications of Ant Colony Optimization and its Variants: Case Studies and New Developments (Springer Tracts in Nature-Inspired Computing)
by Nilanjan DeyThis book explains the basic ideas behind several variants of ant colony optimization (ACO) and shows how they may be used in real-world settings like manufacturing, engineering design, and health care. Marco Dorigo proposed ACO for the first time, and it has been used to solve a variety of optimization problems. This book presents the latest developments of ACO.
Applications of Artificial Intelligence and Neural Systems to Data Science (Smart Innovation, Systems and Technologies #360)
by Anna Esposito Marcos Faundez-Zanuy Francesco Carlo Morabito Eros PaseroThis book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users.
Applications of Artificial Intelligence in Business, Education and Healthcare (Studies in Computational Intelligence #954)
by Aboul Ella Hassanien Allam Hamdan Anjum Razzaque Bahaaeddin Alareeni Reem Khamis Bahaa AwwadThis book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.
Applications of Artificial Intelligence in Tunnelling and Underground Space Technology (SpringerBriefs in Applied Sciences and Technology)
by Aydin Azizi Danial Jahed ArmaghaniThis book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field. In addition, a critical review of the available TBM performance predictive models will be discussed in details. Then, this book introduces several predictive models i.e., statistical and intelligent techniques which are applicable, powerful and easy to implement, in estimating TBM performance parameters. The introduced models are accurate enough and they can be used for prediction of TBM performance in practice before designing TBMs.
Applications of Big Data and Machine Learning in Galaxy Formation and Evolution (Series in Astronomy and Astrophysics)
by Tsutomu T. TakeuchiAs investigations into our Universe become more complex, in-depth, and widespread, galaxy surveys are requiring state-of-the-art data scientific methods to analyze them. This book provides a practical introduction to big data in galaxy formation and evolution, introducing the astrophysical basics, before delving into the latest techniques being introduced to astronomy and astrophysics from data science. This book helps translate the cutting-edge methods into accessible guidance for those without a formal background in computer science. It is an ideal manual for astronomers and astrophysicists, in addition to graduate students and postgraduate students in science and engineering looking to learn how to apply data-science to their research.Key Features: Introduces applications of data-science methods to the exciting subject of galaxy formation and evolution Provides a practical guide to understanding cutting-edge data-scientific methods, as well as classical astrostatistical methods Summarises a vast range of statistical and informatics methods in one volume, with concrete applications to astrophysics
Applications of Block Chain technology and Artificial Intelligence: Lead-ins in Banking, Finance, and Capital Market (Financial Mathematics and Fintech)
by Mohammad Irfan Khan Muhammad Muhammad Attique Khan Nader NaifarToday, emerging technologies offer a new pathway for advancing the economy in the fields of banking, finance, and capital markets. Blockchain applications play a crucial role in ensuring trust and security within these industries by relying on transparency and visibility through peer-to-peer networks. The banking industry has also witnessed increased operations speed, better transparency, efficiency enhancement, fraud extenuation at less cost while sharing real-time data between various parties. Thus, the adoption of blockchain in the Banking and Insurance industry is developing very fast. It has emerged as the commonly accepted default platform for the banking and insurance industry. This book explores how blockchain technology optimizes and integrates transactions and operations, facilitating easier access to information. This, in turn, has the potential to reduce communication costs and minimize minor data transfer errors. Additionally, the book delves into the current applications of blockchain technology in the financial industry, discusses its limitations, and outlines its future prospects for broader accessibility. This book is aimed at students and researchers in financial engineering and fintech and it can serve as a reference for identifying problem areas and their possible solutions.