This proceedings volume documents the contributions presented at the CONIAPS XXVII international Conference on Recent Advances in Pure and Applied Algebra. The entries focus on modern trends and techniques in various branches of pure and applied Algebra and highlight their applications in coding theory, cryptography, graph theory, and fuzzy theory.

This book gives a systematic investigation of convection in systems comprised of liquid layers with deformatable interfaces.

This new edition includes completely updated and new material on flows in ultra thin films and brings up to date progress made in the technology on micro and nano scales. Also, this revised edition will reflect progress in thedynamics of complex fluids."

This proceedings volume gathers selected, revised papers presented at the X International Meeting on Lorentzian Geometry (GeLoCor 2021), virtually held at the University of Cordoba, Spain, on February 1-5, 2021. It includes surveys describing the state-of-the-art in specific areas, and a selection of the most relevant results presented at the conference. Taken together, the papers offer an invaluable introduction to key topics discussed at the conference and an overview of the main techniques in use today. This volume also gathers extended revisions of key studies in this field. Bringing new results and examples, these unique contributions offer new perspectives to the original problems and, in most cases, extend and reinforce the robustness of previous findings. Hosted every two years since 2001, the International Meeting on Lorentzian Geometry has become one of the main events bringing together the leading experts on Lorentzian geometry. In this volume, the reader will find studies on spatial and null hypersurfaces, low regularity in general relativity, conformal structures, Lorentz-Finsler spacetimes, and more. Given its scope, the book will be of interest to both young and experienced mathematicians and physicists whose research involves general relativity and semi-Riemannian geometry.

The theory of complex functions is a strikingly beautiful and powerful area of mathematics. Some particularly fascinating examples are seemingly complicated integrals which are effortlessly computed after reshaping them into integrals along contours, as well as apparently difficult differential and integral equations, which can be elegantly solved using similar methods. To use them is sometimes routine but in many cases it borders on an art. The goal of the book is to introduce the reader to this beautiful area of mathematics and to teach him or her how to use these methods to solve a variety of problems ranging from computation of integrals to solving difficult integral equations. This is done with a help of numerous examples and problems with detailed solutions.

Over the last forty years, Stafford Beer has published a steady stream of books and papers in which he has applied cybernetic science to organizational problems. In all of these he has explained underlying principles and developed new theories and recorded a great variety of practical applications. He has now invented and demonstrated Team Syntegrity. Syntegrity is a powerful invention in the organization of normative, directional, and strategic planning, and other creative decision processes. The underlying model is a regular icosahedron (20 sides). This has 30 edges, each of which represents a person. An internal network of interactions is created by a set of protocols. A group organized like this is an ultimate statement of participatory democracy, since each role is indistinguishable from any other. There is no hierarchy, no top, no bottom, no sideways. Beer illustrates how continued dynamic interaction between persons causes ideas and resolutions to hum around the sphere, which reverberates into a kind of group consciousness. Mathematical analysis of the structure shows how the process is determined by the even spread of synergy. The aim of the book is to provide managers and their advisors with a new planning method that captures the native genius of the organization in a non-political and non-hierarchical way. The book includes an enquiry into Beer’s concept of recursive consciousness, based on this model, that is relevant to both neurocybernetics and the social systems sciences.

The International Symposium on Computational & Applied PDEs was held at Zhangjiajie National Park of China from July 1-7, 2001. The main goal of this conference is to bring together computational, applied and pure mathematicians on different aspects of partial differential equations to exchange ideas and to promote collaboration. Indeed, it attracted a number of leading scientists in computational PDEs including Doug Arnold (Minnesota), Jim Bramble (Texas A & M), Achi Brandt (Weizmann), Franco Brezzi (Pavia), Tony Chan (UCLA), Shiyi Chen (John Hopkins), Qun Lin (Chinese Academy of Sciences), Mitch Luskin (Minnesota), Tom Manteuffel (Colorado), Peter Markowich (Vienna), Mary Wheeler (Texas Austin) and Jinchao Xu (Penn State); in applied and theoretical PDEs including Weinan E (Princeton), Shi Jin (Wisconsin), Daqian Li (Fudan) and Gang Tian (MIT). It also drew an international audience of size 100 from Austria, China, Germany, Hong Kong, Iseael, Italy, Singapore and the United States. The conference was organized by Yunqing Huang of Xiangtan University, Jinchao Xu of Penn State University, and Tony Chan of UCLA through ICAM (Institute for Computational and Applied Mathematics) of Xiangtan university which was founded in January 1997 and directed by Jinchao Xu. The scientific committee of this conference consisted of Randy Bank of UCSD, Tony Chan of UCLA, K. C.

The textbook discusses risk management in capital markets and presents various techniques of portfolio optimization. Special attention is given to risk measurement and credit risk management. Furthermore, the author discusses optimal investment problems and presents various examples. In the last section, the book includes numerous case studies based on the author's own work as a fund manager, court-appointed expert and consultant in the field of quantitative finance. This book is the third volume of the quantitative finance trilogy by the author and builds on the theoretical groundwork introduced in the previous books. The volume presents real-life examples of the successful application of the introduced techniques and methods in financial services and capital markets.

This book facilitates both the theoretical background and applications of fuzzy, intuitionistic fuzzy and rough, fuzzy rough sets in the area of data science. This book provides various individual, soft computing, optimization and hybridization techniques of fuzzy and intuitionistic fuzzy sets with rough sets and their applications including data handling and that of type-2 fuzzy systems. Machine learning techniques are effectively implemented to solve a diversity of problems in pattern recognition, data mining and bioinformatics. To handle different nature of problems, including uncertainty, the book highlights the theory and recent developments on uncertainty, fuzzy systems, feature extraction, text categorization, multiscale modeling, soft computing, machine learning, deep learning, SMOTE, data handling, decision making, Diophantine fuzzy soft set, data envelopment analysis, centrally measures, social networks, Volterra–Fredholm integro-differential equation, Caputo fractional derivative, interval optimization, decision making, classification problems. This book is predominantly envisioned for researchers and students of data science, medical scientists and professional engineers.

• Introduces the dynamics, principles and mathematics behind ten macroeconomic models allowing students to visualise the models and understand the economic intuition behind them. • Provides a step-by-step guide, and the necessary MATLAB codes, to allow readers to simulate and experiment with the models themselves.

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research.

While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization. Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.

This brilliant CGP book covers all the maths skills needed in AS and A-Level Physics (the use of maths is required for up to 40% of the marks in the final exams and assessments). It explains Calculations, Geometry, Trigonometry, Graph Skills and Handling Date, with clear study notes and step-by-step examples in the context of Physics. And to make sure you've really got to grips with it all, there are practice questions for each topic - with answers included at the back of the book.

This pioneering work deals with the parameterization of rockfalls in the context of 3D run-out modelling at a study site in the Bavarian Alps. The main objective was to cover not only low-magnitude, high-frequency rockfalls (<10 m3) but also Mid-Magnitude events, which involve rock volumes of between 10 and 100 m3 (boulder falls) and between 100 and 10,000 m3 (block falls). As Mid-Magnitude events have been insufficiently covered in terms of rockfall modelling up to now, a geomechanical approach has been developed to characterize those events by means of a case study. For a 200 m3 limestone block a potential failure scenario was analysed by combining a deterministic failure analysis with a numerical process-based run-out model. To model potential run-out scenarios of the 200 m3 block, the beta version of the code RAMMS::Rockfall, developed by the Swiss Institute for Snow and Avalanche Research (SLF), was applied. RAMMS::Rockfall makes it possible to include the block shape and thus consider the effects of varying block shapes on the run-out distance. The run-out modelling for the entire project site was performed using the scientific code Rockyfor3D (Dorren/ecorisQ). To provide quantitative information in terms of input parameters, a field recording of block sizes at the talus slope, as well as a detailed discontinuity analysis at the source area, were conducted. The book successfully demonstrates how detailed and quantitative field investigation can contribute to 3D rockfall modelling.

Measuring productive efficiency for nonprofit organizations has posed a great challenge to applied researchers today. The problem has many facets and diverse implications for a number of disciplines such as economics, applied statistics, management science and information theory. This monograph discusses four major areas, which emphasize the applied economic and econometric as. pects of the production frontier analysis: A. Stochastic frontier theory, B. Data envelopment analysis, C. Clustering and estimation theory, D. Economic and managerial applications Besides containing an up-to-date survey of the mos. t recent developments in the field, the monograph presents several new results and theorems from my own research. These include but are not limited to the following: (1) interface with parametric theory, (2) minimax and robust concepts of production frontier, (3) game-theoretic extension of the Farrell and Johansen models, (4) optimal clustering techniques for data envelopment analysis and (5) the dynamic and stochastic generalizations of the efficiency frontier at the micro and macro levels. In my research work in this field I have received great support and inspiration from Professor Abraham Charnes of the University of Texas at Austin, who has basically founded the technique of data envelopment analysis, developed it and is still expanding it. My interactions with him have been most fruitful and productive. I am deeply grateful to him. Finally, I must record my deep appreciation to my wife and two children for their loving and enduring support. But for their support this work would not have been completed.

Traditional utility theory, growing out of the ideas of von Neumann & Morgenstern and Savage, asserts that wise decision makers should maximize some form of expected utility. Decision analysis as a technology implements this prescription. But even after careful thought, people do not necessarily behave that way. The new generalized utility theories attempt to model what people actually do. This book grows out of a NSF-sponsored Conference that brought generalized utility theorists and decision analysts together to examine the normative, prescriptive, and descriptive implications of the new utility theories. The book begins with a review of the phenomena that the new utility theories are intended to explain and of the theories themselves. It then presents the old time religion' of utility maximization as a normative and prescriptive theory. It explores how utility maximization needs to be and can be amplified and supplemented for practical prescriptive purposes. The next section of the book looks at what characteristics generalized utility theories would need to have in order to be prescriptively useful. The crucial one turns out to be a form of path independence. Two chapters show that the form of path independence essentially forces the theory embodying it to be a version of traditional utility maximization. The next section of the book looks at the relation between gneralized utility theories and the data they are intended to explain. A final section contains an evaluative discussion that weaves the themes of the book together. Utility Theories: Measurements and Applications provides a definitive answer to the question about the relation between new utility theories and decisionanalysis that inspired it. It also brings into focus a number of related questions, and reports a great deal of theoretical and empirical progress on the topics to which it is addressed.

This is the fourth volume in a series which discusses advances in mathematical programming and financial planning.

This book highlights the proceedings of the International Conference on Atomic, Molecular, Optical and Nano-Physics with Applications (CAMNP 2019), organized by the Department of Applied Physics, Delhi Technological University, New Delhi, India. It presents experimental and theoretical studies of atoms, ions, molecules and nanostructures both at the fundamental level and on the application side using advanced technology. It highlights how modern tools of high-field and ultra-fast physics are no longer merely used to observe nature but can be used to reshape and redirect atoms, molecules, particles or radiation. It brings together leading researchers and professionals on the field to present and discuss the latest finding in the following areas, but not limited to: Atomic and Molecular Structure, Collision Processes, Data Production and Applications Spectroscopy of Solar and Stellar Plasma Intense Field, Short Pulse Laser and Atto-Second Physics Laser Technology, Quantum Optics and applications Bose Einstein condensation Nanomaterials and Nanoscience Nanobiotechnolgy and Nanophotonics Nano and Micro-Electronics Computational Condensed Matter Physics

In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management, and this trend will only accelerate in the coming years. Unfortunately there is a large gap between the limited treatment of portfolio construction methods that are presented in most university courses with relatively little hands-on experience and limited computing tools, and the rich and varied aspects of portfolio construction that are used in practice in the finance industry. Current practice demands the use of modern methods of portfolio construction that go well beyond the classical Markowitz mean-variance optimality theory and require the use of powerful scalable numerical optimization methods. This book fills the gap between current university instruction and current industry practice by providing a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. The computational aspect of the book is based on extensive use of S-PlusA(R), the S+NuOPTa"[ optimization module, the S-Plus Robust Library and the S]Bayesa"[ Library, along with about 100 S-Plus scripts and some CRSPA(R) sample data sets of stock returns. A special time-limited version of the S-Plus software is available to purchasers of this book.

a oeFor money managers and investment professionals in the field, optimization is truly a can of worms rather left un-opened, until now! Here lies a thorough explanation of almost all possibilities one can think of for portfolio optimization, complete with error estimationtechniques and explanation of when non-normality plays a part. A highly recommended and practical handbook for the consummate professional and student alike!a

Steven P. Greiner, Ph.D., Chief Large Cap Quant & Fundamental Research Manager, Harris Investment Management

a oeThe authors take a huge step in the long struggle to establish applied post-modern portfolio theory. The optimization and statistical techniques generalize the normal linear model to include robustness, non-normality, and semi-conjugate Bayesian analysis via MCMC. The techniques are very clearly demonstrated by the extensive use and tight integration of S-Plus software. Their book should be an enormous help to students and practitioners trying to move beyond traditional modern portfolio theory.a

Peter Knez, CIO, Global Head of Fixed Income, Barclays Global Investors

a oeWith regard to static portfolio optimization, the book gives a good survey on the development from the basic Markowitz approach to state of the art models and is in particular valuable for direct use in practice or for lectures combined with practical exercises.a

Short Book Reviews of the International Statistical Institute, December 2005

Selected Areas in Cryptography brings together in one place important contributions and up-to-date research results in this fast moving area. Selected Areas in Cryptography serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

The field of metaheuristics has been fast evolving in recent years. Techniques such as simulated annealing, tabu search, genetic algorithms, scatter search, greedy randomized adaptive search, variable neighborhood search, ant systems, and their hybrids are currently among the most efficient and robust optimization strategies to find high-quality solutions to many real-life optimization problems. A very large number of successful applications of metaheuristics are reported in the literature and spread throughout many books, journals, and conference proceedings. A series of international conferences entirely devoted to the theory, applications, and computational developments in metaheuristics has been attracting an increasing number of participants, from universities and the industry. Essays and Surveys in Metaheuristics goes beyond the recent conference-oriented volumes in Metaheuristics, with its focus on surveys of recent developments of the main metaheuristics. Well-known specialists have written surveys on the following subjects: simulated annealing (E. Aarts and J. Korst, The Netherlands), noising methods (I. Charon and O. Hudry, France), strategies for the parallel implementation of metaheuristics (V.-D. Cung and C. Roucairol, France, and S.L. Martins and C.C. Ribeiro, Brazil), greedy randomized adaptive search procedures (P. Festa, Italy, and M.G.C. Resende, USA), tabu search (M. Gendreau, Canada), variable neighborhood search (P. Hansen and N. Mladenovic, Canada), ant colonies (V. Maniezzo and A. Carbonaro, Italy), and evolutionary algorithms (H. MA1/4hlenbein and Th. Mahnig, Germany). Several further essays address issues or variants of metaheuristics, as well as innovative orsuccessful applications of metaheuristics to classical or new combinatorial optimization problems.

In this thesis, the pseudogap and the precursor superconducting state, which are of great importance in clarifying the superconductivity mechanism in high-temperature cuprate superconductors, are investigated with a c-axis optical study in YBa2(Cu1-xZnx)3Oy. Testing was performed over a wide energy range with smaller temperature intervals for several Zn-substituted samples, as well as for several carrier-doping levels. A spectral weight (SW) analysis, in which the pseudogap behavior can be separated from the superconducting condensate with the SW transfer to the high-energy region, revealed that the pseudogap is not the precursor of the superconductivity (carriers moving to the high-energy region with pseudogap opening never contribute to the superconducting condensation). Moreover, the high-energy transfer continues even below Tc for the Zn-substituted samples (in which we weaken the superconductivity), which gives evidence to the coexistence of the pseudogap and the superconducting gap below Tc. On the other hand, the analysis of optical conductivity revealed that a precursor state to superconductivity can be defined at temperatures much higher than Tc. The superconducting carrier density (ns) was calculated for each temperature (above and below Tc) and the results confirmed the existence of ns at temperatures above Tc. The observed real superconducting condensate (ns) above Tc puts a serious constraint on the theory for high- Tc superconductivity. A theory based on an inhomogeneous superconducting state, in which a microscopically phase-separated state in a doped Mott insulator can be observed, is the most plausible candidate. This theory can explain the existence of ns and the observed temperature range for the precursor superconducting state. The results obtained show that the pseudogap coexists with superconductivity below Tc and is not the precursor of superconductivity. On the other hand, it is also possible to define a precursor superconducting state that is different than the pseudogap. The temperature range and the observed superconducting condensate in this state can be explained with the help of the inhomogeneous superconducting state.

This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II). Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.

Classical mechanics is a subject that is teeming with life. However, most of the interesting results are scattered around in the specialist literature, which means that potential readers may be somewhat discouraged by the effort required to obtain them. Addressing this situation, Hamiltonian Dynamical Systems includes some of the most significant papers in Hamiltonian dynamics published during the last 60 years. The book covers bifurcation of periodic orbits, the break-up of invariant tori, chaotic behavior in hyperbolic systems, and the intricacies of real systems that contain coexisting order and chaos. It begins with an introductory survey of the subjects to help readers appreciate the underlying themes that unite an apparently diverse collection of articles. The book concludes with a selection of papers on applications, including in celestial mechanics, plasma physics, chemistry, accelerator physics, fluid mechanics, and solid state mechanics, and contains an extensive bibliography. The book provides a worthy introduction to the subject for anyone with an undergraduate background in physics or mathematics, and an indispensable reference work for researchers and graduate students interested in any aspect of classical mechanics.

This book presents the mathematical study of vortices of the two-dimensional Ginzburg-Landau model, an important phenomenological model used to describe superconductivity. The vortices, identified as quantized amounts of vorticity of the superconducting current localized near points, are the objects of many observational and experimental studies, both past and present. The Ginzburg-Landau functionals considered include both the model cases with and without a magnetic field. The book acts a guide to the various branches of Ginzburg-Landau studies, provides context for the study of vortices, and presents a list of open problems in the field.