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Advancements of Grey Systems Theory in Economics and Social Sciences (Series on Grey System)

by Camelia Delcea Liviu-Adrian Cotfas

This book focuses on the main advancements made in the economics and social sciences field through the use of grey systems theory. As a result, it addresses both the state of the art and the applications of grey systems theory in economics and social sciences. The book is structured in eight main chapters, covering the following topics: the state of the art in the grey systems theory research in economics and social sciences, which includes a bibliometric analysis, a selection of the most well-cited papers in the field, and a selection of applications in which the grey systems theory is used in the areas of suppliers selection, risk assessment, public opinion assessment, linear programming, complex projects management, social media analysis, and natural language processing Each chapter gives an overview of a particular economic or social sciences topic, providing an explanation on the main terms and methods used for solving the problem, including the notations, terminology, and the needed steps to solve it. A practical application is presented in most of the chapters, while in the others, a series of case studies are presented from the literature and discussed in depth in terms of methods used and advantages brought by each of these methods. The last chapter discusses the hybridization cases in which the grey systems theory has been or can be successfully used along with other artificial intelligence methods and techniques for a more advanced analysis in the economics and social sciences field. The reasoning and the explanations used in the book are easy to understand for the interested persons who are not familiar to the field and want to learn more related on how the grey systems theory can be applied to economics and social sciences. As for the experts in this field, this book can be a good referral point for developing new areas of research by combining the advantages of the grey systems theory with other theories within the field.

Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data: Proceedings of the 2015 International Symposium in Statistics (Lecture Notes in Statistics #218)

by Brajendra C. Sutradhar

This proceedings volume contains eight selected papers thatwere presented in the International Symposium in Statistics (ISS) 2015 OnAdvances in Parametric and Semi-parametric Analysis of Multivariate, TimeSeries, Spatial-temporal, and Familial-longitudinal Data, held in St. John's,Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was thediscussion on advances and challenges in parametric and semi-parametric analysisfor correlated data in both continuous and discrete setups. Thus, as areflection of the theme of the symposium, the eight papers of this proceedingsvolume are presented in four parts. Part I is comprised of papers examiningElliptical t Distribution Theory. In Part II, the papers cover spatial andtemporal data analysis. Part III is focused on longitudinal multinomial modelsin parametric and semi-parametric setups. Finally Part IV concludes with apaper on the inferences for longitudinal data subject to a challenge ofimportant covariates selection from a set of large number of covariatesavailable for the individuals in the study.

Advances and Challenges in Space-time Modelling of Natural Events (Lecture Notes in Statistics #207)

by José–maría Montero Emilio Porcu Martin Schlather

This book arises as the natural continuation of the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place in Toledo (Spain) in March 2010. This Spring School above all focused on young researchers (Master students, PhD students and post-doctoral researchers) in academics, extra-university research and the industry who are interested in learning about recent developments, new methods and applications in spatial statistics and related areas, and in exchanging ideas and findings with colleagues.

Advances and Innovations in Statistics and Data Science (ICSA Book Series in Statistics)

by Wenqing He Liqun Wang Jiahua Chen Chunfang Devon Lin

This book highlights selected papers from the 4th ICSA-Canada Chapter Symposium, as well as invited articles from established researchers in the areas of statistics and data science. It covers a variety of topics, including methodology development in data science, such as methodology in the analysis of high dimensional data, feature screening in ultra-high dimensional data and natural language ranking; statistical analysis challenges in sampling, multivariate survival models and contaminated data, as well as applications of statistical methods. With this book, readers can make use of frontier research methods to tackle their problems in research, education, training and consultation.

Advances in Acoustics and Vibration IV: Proceedings of the Fourth International Conference on Acoustics and Vibration (ICAV2022), December 19-21, 2022, Sousse, Tunisia (Applied Condition Monitoring #22)

by Ali Akrout Moez Abdennadher Nabih Feki Mohamed Slim Abbes Fakher Chaari Mohamed Haddar

The book provides readers with a snapshot of recent research and industrial trends in field of industrial acoustics and vibration. Each chapter, accepted after a rigorous peer-review process, reports on a selected, original piece of work presented and discussed at the Fourth International Conference on Acoustics and Vibration (ICAV2022), which was organized by the Tunisian Association of Industrial Acoustics and Vibration (ATAVI) and held in hybrid format on December 19–21, 2022, in and from Sousse, Tunisia. The contributions cover advances in both theory and practice in a variety of subfields, such as structural and machine dynamics and vibrations, fault diagnosis and prognosis, nonlinear dynamics, and vibration control of mechatronic systems. Further topics include fluid–structure interaction, computational vibro-acoustics, vibration field measurements, and dynamic behavior of materials. This book provides a valuable resource for both academics and professionals dealing with diverse issues in applied mechanics. By combining advanced theories with industrial issues, it is expected to facilitate communication and collaboration between different groups of researchers and technology users.

Advances in Algebra: SRAC 2017, Mobile, Alabama, USA, March 17-19 (Springer Proceedings in Mathematics & Statistics #277)

by Jörg Feldvoss Lauren Grimley Drew Lewis Andrei Pavelescu Cornelius Pillen

This proceedings volume covers a range of research topics in algebra from the Southern Regional Algebra Conference (SRAC) that took place in March 2017. Presenting theory as well as computational methods, featured survey articles and research papers focus on ongoing research in algebraic geometry, ring theory, group theory, and associative algebras. Topics include algebraic groups, combinatorial commutative algebra, computational methods for representations of groups and algebras, group theory, Hopf-Galois theory, hypergroups, Lie superalgebras, matrix analysis, spherical and algebraic spaces, and tropical algebraic geometry. Since 1988, SRAC has been an important event for the algebra research community in the Gulf Coast Region and surrounding states, building a strong network of algebraists that fosters collaboration in research and education. This volume is suitable for graduate students and researchers interested in recent findings in computational and theoretical methods in algebra and representation theory.

Advances in Algebra and Model Theory

by M. Droste R. Gobel

Contains 25 surveys in algebra and model theory, all written by leading experts in the field. The surveys are based around talks given at conferences held in Essen, 1994, and Dresden, 1995. Each contribution is written in such a way as to highlight the ideas that were discussed at the conferences, and also to stimulate open research problems in a form accessible to the whole mathematical community. The topics include field and ring theory as well as groups, ordered algebraic structure and their relationship to model theory. Several papers deal with infinite permutation groups, abelian groups, modules and their relatives and representations. Model theoretic aspects include quantifier elimination in skew fields, Hilbert's 17th problem, (aleph-0)-categorical structures and Boolean algebras. Moreover symmetry questions and automorphism groups of orders are covered. This work contains 25 surveys in algebra and model theory, each is written in such a way as to highlight the ideas that were discussed at Conferences, and also to stimulate open research problems in a form accessible to the whole mathematical community.

Advances in Antiviral Research (Livestock Diseases and Management)

by Naveen Kumar Yashpal Singh Malik Shailly Tomar Sayeh Ezzikouri

This book illustrates advancements in the sophisticated tools and techniques for discovering and designing new antiviral drugs, identifying approved drugs against new and emerging viruses through large-scale computational virtual screening or drug repurposing approaches, and their evaluation in various in vitro and in vivo models. The chapters also cover the challenges associated with the emergence of antiviral drug resistance and possible ways to counter them. It discusses bioinformatics tools and software and computational approaches for the discovery of antivirals. The books also outline approaches for designing broad-spectrum antivirals effective against viruses by epigenetic- and epitranscriptomic-targeted reprogramming. Further, it provides vital details on the procedures for drug applications, clinical trials, and their regulations. Finally, the book provides a comprehensive yet representative description of advances in antiviral research protocols and methodologies suitablefor antiviral researchers at all career stages, including graduate and postgraduate students and policy-makers. ​

Advances in Applications of Data-Driven Computing (Advances in Intelligent Systems and Computing #1319)

by Jagdish Chand Bansal Lance C. C. Fung Milan Simic Ankush Ghosh

This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today’s software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book.

Advances in Applied Mathematical Analysis and Applications

by Mangey Ram Tadashi Dohi

In recent years, applied mathematics has been used in all novel disciplines of scientific development. Advances in Applied Mathematical Problems summarizes interdisciplinary work within the field of applied mathematics.The topics discussed in the book include:• Similarity Solutions of Spherical Shock Waves in a Self-Gravitating Ideal Gas• Dual Solutions for Finite Element Analysis of Unsteady Hydromagnetic Stagnation Point Flow of Water Nanofluid Generated by Stretching Sheet• Multiparametric modeling of carbon cycle in temperate wetlands for regional climate change analysis using satellite data• An Intelligent Neuro Fuzzy System for Pattern Classification• Fuzzy inventory model with demand, deterioration and inflation: a comparative study through NGTFN and CNTFN• Summability and its application for the stability of the system• Design Of Manufacturing, Control, And Automation Systems• SEIR - Application for Crop through Water and Soil Texture• Advances in radial basis functions• Modeling For Time Period Of Natural Frequency For Non-Homogeneous Square Plate With Variable Thickness And Temperature Effect• A Study On Metric Fixed Point Theorems Satisfying Integral Type Contractions • Objective Function – In Radiometric Studies –Application to Agrs Surveys Associated With Radon• Modelling Kernel Function in Black body Radiation Inversion

Advances in Applied Mathematics (Springer Proceedings in Mathematics & Statistics #87)

by Ali R. Ansari

This volume contains contributions from the Gulf International Conference in Applied Mathematics, held at the Gulf University for Science & Technology. The proceedings reflects the three major themes of the conference. The first of these was mathematical biology, including a keynote address by Professor Philip Maini. The second theme was computational science/numerical analysis, including a keynote address by Professor Grigorii Shishkin. The conference also addressed more general applications topics, with papers in business applications, fluid mechanics, optimization, scheduling problems and engineering applications, as well as a keynote by Professor Ali Nayfeh.

Advances in Applied Mathematics and Approximation Theory: Contributions from AMAT 2012 (Springer Proceedings in Mathematics & Statistics #41)

by George A. Anastassiou Oktay Duman

Advances in Applied Mathematics and Approximation Theory: Contributions from AMAT 2012 is a collection of the best articles presented at "Applied Mathematics and Approximation Theory 2012," an international conference held in Ankara, Turkey, May 17-20, 2012. This volume brings together key work from authors in the field covering topics such as ODEs, PDEs, difference equations, applied analysis, computational analysis, signal theory, positive operators, statistical approximation, fuzzy approximation, fractional analysis, semigroups, inequalities, special functions and summability. The collection will be a useful resource for researchers in applied mathematics, engineering and statistics.

Advances in Applied Mathematics, Modeling, and Computational Science (Fields Institute Communications #66)

by Roderick Melnik Ilias S. Kotsireas

The volume presents a selection of in-depth studies and state-of-the-art surveys of several challenging topics that are at the forefront of modern applied mathematics, mathematical modeling, and computational science. These three areas represent the foundation upon which the methodology of mathematical modeling and computational experiment is built as a ubiquitous tool in all areas of mathematical applications. This book covers both fundamental and applied research, ranging from studies of elliptic curves over finite fields with their applications to cryptography, to dynamic blocking problems, to random matrix theory with its innovative applications. The book provides the reader with state-of-the-art achievements in the development and application of new theories at the interface of applied mathematics, modeling, and computational science. This book aims at fostering interdisciplinary collaborations required to meet the modern challenges of applied mathematics, modeling, and computational science. At the same time, the contributions combine rigorous mathematical and computational procedures and examples from applications ranging from engineering to life sciences, providing a rich ground for graduate student projects.

Advances in Applied Strategic Mine Planning

by Roussos Dimitrakopoulos

This book presents is a collection of papers in the field of strategic mine planning, including orebody modelling, mine planning optimization and the optimization of mining complexes. The work includes papers (a) describing the newest technologies and related research; and (b) applications of a range of related technologies in diverse industrial applications elaborating upon the state of the art in the field.

Advances in Architectural Geometry 2014

by Philippe Block Jan Knippers Niloy J. Mitra Wenping Wang

This book contains 24 technical papers presented at the fourth edition of the Advances in Architectural Geometry conference, AAG 2014, held in London, England, September 2014. It offers engineers, mathematicians, designers, and contractors insight into the efficient design, analysis, and manufacture of complex shapes, which will help open up new horizons for architecture. The book examines geometric aspects involved in architectural design, ranging from initial conception to final fabrication. It focuses on four key topics: applied geometry, architecture, computational design, and also practice in the form of case studies. In addition, the book also features algorithms, proposed implementation, experimental results, and illustrations. Overall, the book presents both theoretical and practical work linked to new geometrical developments in architecture. It gathers the diverse components of the contemporary architectural tendencies that push the building envelope towards free form in order to respond to multiple current design challenges. With its introduction of novel computational algorithms and tools, this book will prove an ideal resource to both newcomers to the field as well as advanced practitioners.

Advances in Artificial Economics (Lecture Notes in Economics and Mathematical Systems #676)

by Benoit Gaudou Frédéric Amblard Francisco J. Miguel Adrien Blanchet

The book presents a peer-reviewed collection of papers presented during the 10th issue of the Artificial Economics conference, addressing a variety of issues related to macroeconomics, industrial organization, networks, management and finance, as well as purely methodological issues. The field of artificial economics covers a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The grounding principle of artificial economics is the analysis of aggregate properties of simulated systems populated by interacting adaptive agents that are equipped with heterogeneous individual behavioral rules. These macroscopic properties are neither foreseen nor intended by the artificial agents but generated collectively by them. They are emerging characteristics of such artificially simulated systems.

Advances in Artificial Intelligence – IBERAMIA 2022: 17th Ibero-American Conference on AI, Cartagena de Indias, Colombia, November 23–25, 2022, Proceedings (Lecture Notes in Computer Science #13788)

by Ana Cristina Bicharra Garcia Mariza Ferro Julio Cesar Rodríguez Ribón

This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022. The 33 full and 4 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: applications of AI; ethics and smart city; green and sustainable AI; machine learning; natural language processing; robotics and computer vision; simulation and forecasting.

Advances in Artificial Intelligence and Machine Learning in Big Data Processing: First International Conference, AAIMB 2023, Chennai, India, August 17–18, 2023, Proceedings, Part-II (Communications in Computer and Information Science #2203)

by R. Geetha Nhu-Ngoc Dao Saeed Khalid

This book constitutes the refereed proceedings of the First International Conference on Advances in Artificial Intelligence & Machine Learning in Big Data Processing, AAIMB 2023, held in Chennai, India, during August 17–18, 2023. The 51 full papers presented were carefully reviewed and selected from 183 submissions. They were organized in the following topical sections: Part I- artificial intelligence and data analytics; deep learning. Part II- artificial intelligence and data analytics; machine learning.

Advances in Artificial Intelligence and Machine Learning in Big Data Processing: First International Conference, AAIMB 2023, Chennai, India, August 17–18, 2023, Proceedings, Part-I (Communications in Computer and Information Science #2202)

by R. Geetha Nhu-Ngoc Dao Saeed Khalid

This book constitutes the refereed proceedings of the First International Conference on Advances in Artificial Intelligence & Machine Learning in Big Data Processing, AAIMB 2023, held in Chennai, India, during August 17–18, 2023. The 51 full papers presented were carefully reviewed and selected from 183 submissions. They were organized in the following topical sections: Part I- artificial intelligence and data analytics; deep learning. Part II- artificial intelligence and data analytics; machine learning.

Advances in Artificial Intelligence, Computation, and Data Science: For Medicine and Life Science (Computational Biology #31)

by Tuan D. Pham Hong Yan Folke Sjöberg Muhammad W. Ashraf

Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity—in both time and memory requirements—for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society.This edited book attempts to report recent advances in the complementary domains of AI, computation, and data science with applications in medicine and life science. The benefits to the reader are manifold as researchers from similar or different fields can be aware of advanced developments and novel applications that can be useful for either immediate implementations or future scientific pursuit. Features:Considers recent advances in AI, computation, and data science for solving complex problems in medicine, physiology, biology, chemistry, and biochemistryProvides recent developments in three evolving key areas and their complementary combinations: AI, computation, and data scienceReports on applications in medicine and physiology, including cancer, neuroscience, and digital pathologyExamines applications in life science, including systems biology, biochemistry, and even food technology This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education.

Advances in Artificial Intelligence-Empowered Decision Support Systems: Papers in Honour of Professor John Psarras (Learning and Analytics in Intelligent Systems #39)

by Lakhmi C. Jain Maria Virvou George A. Tsihrintzis Haris Doukas

Decision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues. DSSs have proven to be particularly useful at the strategic level, while they usually require only limited computer-proficiency skills from their users. Although DSSs have been under development and use for several decades, recent advances in both Software Engineering technologies and Artificial Intelligence (AI) methodologies have heralded new avenues for research and development in this field. This book exposes its readers to some of the most significant Advances in Artificial Intelligence-Empowered Decision Support Systems. It consists of an editorial note and an additional sixteen (16) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. The chapters are organized into five parts, namely (i) AI-Empowered DSS in Medical Diagnosis and Biology, (ii) AI-Empowered DSS in Healthcare and Health Insurance, (iii) AI-Empowered DSS in Urban Matters, (iv) Various Applications of AI-Empowered DSS, and (v) Novel AI-Empowered Methodologies in Decision Making. Targeted toward academics, researchers, practitioners, and students in Computer Science, Artificial Intelligence, and Management, this book is also accessible to individuals from other disciplines interested in the cutting-edge developments of AI-empowered DSS technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them.

Advances in Best-Worst Method: Proceedings of the Third International Workshop on Best-Worst Method (BWM2022) (Lecture Notes in Operations Research)

by Jafar Rezaei Matteo Brunelli Majid Mohammadi

This book presents recent advances in the theory and application of the Best-Worst Method (BWM). It includes selected papers from the Third International Workshop on Best-Worst Method (BWM2022), held in Delft, the Netherlands, from 9 to 10 June 2022. The book provides valuable insights on why and how to use BWM in a diverse range of applications including health, energy, supply chain management, and engineering. Moreover, it highlights the use of BWM in different settings including individual decision-making vs group decision-making, and with complete information vs incomplete and uncertain information. Academics and practitioners whose work involves multi-criteria decision-making and decision analysis will particularly benefit from the papers gathered here.

Advances in Best-Worst Method: Proceedings of the Fourth International Workshop on Best-Worst Method (BWM2023) (Lecture Notes in Operations Research)

by Jafar Rezaei Matteo Brunelli Majid Mohammadi

This proceedings book contains selected papers from the Fourth International Workshop on Best-Worst Method (BWM2023), held in Delft, the Netherlands, from 8 to 9 June 2023. It presents recent advancements in theory and applications of the Best-Worst Method (BWM). It provides valuable insights on why and how to use BWM in a diverse set of applications including health, energy, supply chain management, and engineering. The book highlights the use of BWM in different settings including single decision-making vs group decision-making, full information vs incomplete and uncertain situations. Academics and practitioners who are involved in multi-criteria decision-making and decision analysis benefit from the papers published in this book.

Advances in Brain Inspired Cognitive Systems: 13th International Conference, BICS 2023, Kuala Lumpur, Malaysia, August 5–6, 2023, Proceedings (Lecture Notes in Computer Science #14374)

by Jinchang Ren Amir Hussain Iman Yi Liao Rongjun Chen Kaizhu Huang Huimin Zhao Xiaoyong Liu Ping Ma Thomas Maul

This book constitutes the refereed proceedings of the International Conference on Brain Inspired Cognitive Systems, BICS 2023, held in Kuala Lumpur, Malaysia, in August 2023. The 36 full papers included in this book were reviewed and selected from 58 submissions and are organized in thematic sections as follows: Bio-inspired systems and Neural Computation; Image Recognition, Detection and Classification; Vision and Object Tracking; Data Analysis and Machine Learning and Applications.

Advances in Business Statistics, Methods and Data Collection

by Ger Snijkers Mojca Bavdaž Stefan Bender Jacqui Jones Steve MacFeely Joseph W. Sakshaug Katherine J. Thompson Arnout Van Delden

ADVANCES IN BUSINESS STATISTICS, METHODS AND DATA COLLECTION Advances in Business Statistics, Methods and Data Collection delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include: Practical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector. Comprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization. Detailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic. In-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata. Methodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods. Providing a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, Advances in Business Statistics, Methods and Data Collection will also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.

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