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Quantum Finance: Intelligent Forecast and Trading Systems
by Raymond S. LeeWith the exponential growth of program trading in the global financial industry, quantum finance and its underlying technologies have become one of the hottest topics in the fintech community. Numerous financial institutions and fund houses around the world require computer professionals with a basic understanding of quantum finance to develop intelligent financial systems. This book presents a selection of the author’s past 15 years’ R&D work and practical implementation of the Quantum Finance Forecast System – which integrates quantum field theory and related AI technologies to design and develop intelligent global financial forecast and quantum trading systems. The book consists of two parts: Part I discusses the basic concepts and theories of quantum finance and related AI technologies, including quantum field theory, quantum price fields, quantum price level modelling and quantum entanglement to predict major financial events. Part II then examines the current, ongoing R&D projects on the application of quantum finance technologies in intelligent real-time financial prediction and quantum trading systems. This book is both a textbook for undergraduate & masters level quantum finance, AI and fintech courses and a valuable resource for researchers and data scientists working in the field of quantum finance and intelligent financial systems. It is also of interest to professional traders/ quants & independent investors who would like to grasp the basic concepts and theory of quantum finance, and more importantly how to adopt this fascinating technology to implement intelligent financial forecast and quantum trading systems. For system implementation, the interactive quantum finance programming labs listed on the Quantum Finance Forecast Centre official site (QFFC.org) enable readers to learn how to use quantum finance technologies presented in the book.
Dynamical Systems, Bifurcation Analysis and Applications: Penang, Malaysia, August 6–13, 2018 (Springer Proceedings in Mathematics & Statistics #295)
by Mohd Hafiz Mohd Norazrizal Aswad Abdul Rahman Nur Nadiah Abd Hamid Yazariah Mohd YatimThis book is the result of Southeast Asian Mathematical Society (SEAMS) School 2018 on Dynamical Systems and Bifurcation Analysis (DySBA). It addresses the latest developments in the field of dynamical systems, and highlights the importance of numerical continuation studies in tracking both stable and unstable steady states and bifurcation points to gain better understanding of the dynamics of the systems. The SEAMS School 2018 on DySBA was held in Penang from 6th to 13th August at the School of Mathematical Sciences, Universiti Sains Malaysia.The SEAMS Schools are part of series of intensive study programs that aim to provide opportunities for an advanced learning experience in mathematics via planned lectures, contributed talks, and hands-on workshop.This book will appeal to those postgraduates, lecturers and researchers working in the field of dynamical systems and their applications. Senior undergraduates in Mathematics will also find it useful.
Electronic Filters: Theory, Numerical Recipes, and Design Practice based on the RM Software (Lecture Notes in Electrical Engineering #596)
by Vančo LitovskiThis book provides a comprehensive overview of signal filtering, including an introduction, definitions of the terms and algorithms for numerical calculation of the properties of the transfer function in frequency and time domains. All the chapters discuss the theoretical background and explain the underlying algorithms including the iterative numerical procedures necessary to obtain the solutions. It starts by considering polynomial filters, offering a broad range of solutions and introducing critical monotonic passband amplitude characteristics (CMAC). It also describes modifications to the classical Chebyshev and elliptic filters to overcome their limitations. In the context linear phase low-pass prototypes, it presents filters approximating constant group delay in the equi-ripple manner for the first time. Further, it discusses new procedures to improve the selectivity of all polynomial filters by introducing transmission zeros, such as filters with multiple transmission zeros on the omega axis, as well as phase correction of selective filters for both low-pass and band-pass filters. Other topics explored include linear phase all-pass (exhibiting low-pass group delay approximation) filters; all-pass filters (exhibiting band-pass group delay approximation) with linear and parabolic phase synthesized directly as band-pass; high-pass, and band-stop amplitude characteristic frequency transformations to produce band-pass; and direct synthesis of linear and parabolic phase selective band-pass filters synthesized directly as band-pass. Lastly, for system (physical) synthesis, the book describes the algorithms and procedures for the following: cascade passive LC; active cascade RC; active parallel RC (for the first time); active parallel SC; Gm-C based on LC prototypes; and parallel IIR based on bilinear transformation of analog prototypes. Every algorithm, be it in transfer function synthesis or in system synthesis, is accompanied by a proper nontrivial comprehensive example produced by the RM software.
Wavelet Solutions for Reaction–Diffusion Problems in Science and Engineering (Forum for Interdisciplinary Mathematics)
by G. HariharanThe book focuses on how to implement discrete wavelet transform methods in order to solve problems of reaction–diffusion equations and fractional-order differential equations that arise when modelling real physical phenomena. It explores the analytical and numerical approximate solutions obtained by wavelet methods for both classical and fractional-order differential equations; provides comprehensive information on the conceptual basis of wavelet theory and its applications; and strikes a sensible balance between mathematical rigour and the practical applications of wavelet theory. The book is divided into 11 chapters, the first three of which are devoted to the mathematical foundations and basics of wavelet theory. The remaining chapters provide wavelet-based numerical methods for linear, nonlinear, and fractional reaction–diffusion problems. Given its scope and format, the book is ideally suited as a text for undergraduate and graduate students of mathematics and engineering.
Advanced Optimization and Operations Research (Springer Optimization and Its Applications #153)
by Asoke Kumar Bhunia Laxminarayan Sahoo Ali Akbar ShaikhThis textbook provides students with fundamentals and advanced concepts in optimization and operations research. It gives an overview of the historical perspective of operations research and explains its principal characteristics, tools, and applications. The wide range of topics covered includes convex and concave functions, simplex methods, post optimality analysis of linear programming problems, constrained and unconstrained optimization, game theory, queueing theory, and related topics. The text also elaborates on project management, including the importance of critical path analysis, PERT and CPM techniques. This textbook is ideal for any discipline with one or more courses in optimization and operations research; it may also provide a solid reference for researchers and practitioners in operations research.
Evolutionary Machine Learning Techniques: Algorithms and Applications (Algorithms for Intelligent Systems)
by Seyedali Mirjalili Hossam Faris Ibrahim AljarahThis book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
Lattice-Based Public-Key Cryptography in Hardware (Computer Architecture and Design Methodologies)
by Sujoy Sinha Roy Ingrid VerbauwhedeThis book describes the efficient implementation of public-key cryptography (PKC) to address the security challenges of massive amounts of information generated by the vast network of connected devices, ranging from tiny Radio Frequency Identification (RFID) tags to powerful desktop computers. It investigates implementation aspects of post quantum PKC and homomorphic encryption schemes whose security is based on the hardness of the ring-learning with error (LWE) problem. The work includes designing an FPGA-based accelerator to speed up computation on encrypted data in the cloud computer. It also proposes a more practical scheme that uses a special module called recryption box to assist homomorphic function evaluation, roughly 20 times faster than the implementation without this module.
Order and Fluctuations in Collective Dynamics of Swimming Bacteria: Experimental Exploration of Active Matter Physics (Springer Theses)
by Daiki NishiguchiThis thesis focuses on experimental studies on collective motion using swimming bacteria as model active-matter systems. It offers comprehensive reviews of state-of-the-art theories and experiments on collective motion from the viewpoint of nonequilibrium statistical physics. The author presents his experimental studies on two major classes of collective motion that had been well studied theoretically. Firstly, swimming filamentous bacteria in a thin fluid layer are shown to exhibit true, long-range orientational order and anomalously strong giant density fluctuations, which are considered universal and landmark signatures of collective motion by many numerical and theoretical works but have never been observed in real systems. Secondly, chaotic bacterial turbulence in a three-dimensional dense suspension without any long-range order as described in the first half is demonstrated to be capable of achieving antiferromagnetic vortex order by imposing a small number of constraints with appropriate periodicity. The experimental results presented significantly advance our fundamental understanding of order and fluctuations in collective motion of motile elements and their future applications.
Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs (SpringerBriefs in Applied Sciences and Technology)
by Manasvi Aggarwal M.N. MurtyThis book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein–protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties.
Evolutionary Data Clustering: Algorithms and Applications (Algorithms for Intelligent Systems)
by Ibrahim Aljarah Hossam Faris Seyedali MirjaliliThis book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.
Quantum f-Divergences in von Neumann Algebras: Reversibility of Quantum Operations (Mathematical Physics Studies)
by Fumio HiaiRelative entropy has played a significant role in various fields of mathematics and physics as the quantum version of the Kullback–Leibler divergence in classical theory. Many variations of relative entropy have been introduced so far with applications to quantum information and related subjects. Typical examples are three different classes, called the standard, the maximal, and the measured f-divergences, all of which are defined in terms of (operator) convex functions f on (0,∞) and have respective mathematical and information theoretical backgrounds. The α-Rényi relative entropy and its new version called the sandwiched α-Rényi relative entropy have also been useful in recent developments of quantum information.In the first half of this monograph, the different types of quantum f-divergences and the Rényi-type divergences mentioned above in the general von Neumann algebra setting are presented for study. While quantum information has been developing mostly in the finite-dimensional setting, it is widely believed that von Neumann algebras provide the most suitable framework in studying quantum information and related subjects. Thus, the advance of quantum divergences in von Neumann algebras will be beneficial for further development of quantum information. Quantum divergences are functions of two states (or more generally, two positive linear functionals) on a quantum system and measure the difference between the two states. They are often utilized to address such problems as state discrimination, error correction, and reversibility of quantum operations. In the second half of the monograph, the reversibility/sufficiency theory for quantum operations (quantum channels) between von Neumann algebras via quantum f-divergences is explained, thus extending and strengthening Petz' previous work.For the convenience of the reader, an appendix including concise accounts of von Neumann algebras is provided.
Modern Classification Theory of Superconducting Gap Nodes (Springer Theses)
by Shuntaro SumitaThis book puts forward a modern classification theory for superconducting gap nodes, whose structures can be observed by experiments and are essential for understanding unconventional superconductivity. In the first part of the book, the classification method, based on group theory and K theory, is introduced in a step-by-step, pedagogical way. In turn, the latter part presents comprehensive classification tables, which include various nontrivial gap (node) structures, which are not predicted by the Sigrist-Ueda method, but are by the new method. The results obtained here show that crystal symmetry and/or angular momentum impose critical constraints on the superconducting gap structures. Lastly, the book lists a range of candidate superconductors for the nontrivial gap nodes. The classification methods and tables presented here offer an essential basis for further investigations into unconventional superconductivity. They indicate that previous experimental studies should be reinterpreted, while future experiments should reflect the new excitation spectrum.
Passivity of Complex Dynamical Networks: Analysis, Control and Applications
by Jin-Liang Wang Huai-Ning Wu Shun-Yan RenThis book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.
Essential Tools for Water Resources Analysis, Planning, and Management (Springer Water)
by Omid Bozorg-HaddadThis book describes concepts and tools needed for water resources management, including methods for modeling, simulation, optimization, big data analysis, data mining, remote sensing, geographical information system, game theory, conflict resolution, System dynamics, agent-based models, multiobjective, multicriteria, and multiattribute decision making and risk and uncertainty analysis, for better and sustainable management of water resources and consumption, thus mitigating the present and future global water shortage crisis. It presents the applications of these tools through case studies which demonstrate its benefits of proper management of water resources systems. This book acts as a reference for students, professors, industrial practitioners, and stakeholders in the field of water resources and hydrology.
Design of Experiments for Pharmaceutical Product Development: Volume II : Applications and Practical Case studies
by Sarwar BegThis book volume provides complete and updated information on the applications of Design of Experiments (DoE) and related multivariate techniques at various stages of pharmaceutical product development. It discusses the applications of experimental designs that shall include oral, topical, transdermal, injectables preparations, and beyond for nanopharmaceutical product development, leading to dedicated case studies on various pharmaceutical experiments through illustrations, art-works, tables and figures. This book is a valuable guide for all academic and industrial researchers, pharmaceutical and biomedical scientists, undergraduate and postgraduate research scholars, pharmacists, biostatisticians, biotechnologists, formulations and process engineers, regulatory affairs and quality assurance personnel.
Proceedings of First International Conference on Mathematical Modeling and Computational Science: ICMMCS 2020 (Advances in Intelligent Systems and Computing #1292)
by Sheng-Lung Peng Rong-Xia Hao Souvik PalThis book presents the most recent scientific and technological advances in the fields of engineering mathematics and computational science, to strengthen the links in the scientific community. It is a collection of high-quality, peer-reviewed research papers presented at the First International Conference on Mathematical Modeling and Computational Science (ICMMCS 2020), held in Pattaya, Thailand, during 14–15 August 2020. The topics covered in the book are mathematical logic and foundations, numerical analysis, neural networks, fuzzy set theory, coding theory, higher algebra, number theory, graph theory and combinatory, computation in complex networks, calculus, differential educations and integration, application of soft computing, knowledge engineering, machine learning, artificial intelligence, big data and data analytics, high-performance computing, network and device security, and Internet of things (IoT).
Motions of Ice Hydrometeors in the Atmosphere: Numerical Studies and Implications (Atmosphere, Earth, Ocean & Space)
by Pao K. WangThis book summarizes unique research findings on the hydrodynamic behavior of ice particles (ice crystals, snow, graupel and hailstones) in the atmosphere. The fall behavior of ice hydrometeors determines how and how fast a mixed-phase cloud can grow or dissipate. The book discusses how the authors used computational fluid dynamics (CFD) methods and numerical simulations to determine these behaviors, and presents these computations along with numerous detailed tables and illustrations of turbulent flow fields. It also examines the implications of the results for the general atmospheric sciences as well as for climate science (since the cloud problem is the source of the greatest uncertainty in model-based climate predictions). As such it allows readers to gain a clear and comprehensive understanding of how particles fall in clouds and offers insights into cloud physics and dynamics and their impact on the climate..
Advanced Fixture Design Method and Its Application
by Guohua QinThis book uses kinematics, mechanics, mathematics, and so on, to systematically propose the fixturing performance evaluation and fixturing layout planning method. The proposed method is a novel method, including the analysis method of locating determination, the analysis method of workpiece stability, the analysis method of clamping reasonability, the analysis method of workpiece attachment/detachment, the analysis method of locating accuracy, and the planning algorithm of locating point layout, the planning algorithm of clamping force, and so forth. It can enrich and develop the basic theory of computer aided fixture design, change the empirical method of fixture design. The combination of theoretical analysis and mathematical modeling technology can resolve the key problems in the process of fixture design, which will play a certain role in promoting the progress of manufacturing technology, improving the precision and level of product manufacturing, and meeting the higher and higher requirements of mechanical manufacturing industry.
Distributed Optimization, Game and Learning Algorithms: Theory and Applications in Smart Grid Systems
by Huiwei Wang Huaqing Li Bo ZhouThis book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
Mathematical Analysis and Computing: ICMAC 2019, Kalavakkam, India, December 23–24 (Springer Proceedings in Mathematics & Statistics #344)
by R. N. Mohapatra S. Yugesh G. Kalpana C. KalaivaniThis book is a collection of selected papers presented at the International Conference on Mathematical Analysis and Computing (ICMAC 2019) held at Sri Sivasubramaniya Nadar College of Engineering, Chennai, India, from 23–24 December 2019. Having found its applications in game theory, economics, and operations research, mathematical analysis plays an important role in analyzing models of physical systems and provides a sound logical base for problems stated in a qualitative manner. This book aims at disseminating recent advances in areas of mathematical analysis, soft computing, approximation and optimization through original research articles and expository survey papers. This book will be of value to research scholars, professors, and industrialists working in these areas.
Air Traffic Management and Systems IV: Selected Papers of the 6th ENRI International Workshop on ATM/CNS (EIWAC2019) (Lecture Notes in Electrical Engineering #731)
by Electronic Navigation Research InstituteThis book provides novel concepts and techniques for air traffic management (ATM) and communications, navigation, and surveillance (CNS) systems. The book consists of selected papers from the 6th ENRI International Workshop on ATM/CNS (EIWAC2019) held in Tokyo in October 2019, the theme of which was “Exploring Ideas for World Aviation Challenges”. Included are key topics to realize safer and more efficient skies in the future, linked to the integrated conference theme consisting of long-term visions based on presentations from various fields. The book is dedicated not only to researchers, academicians, and university students, but also to engineers in the industry, air navigation service providers (ANSPs), and regulators of aviation.
Theory of Generation and Conversion of Phonon Angular Momentum (Springer Theses)
by Masato HamadaThis book presents a theoretical study of the generation and conversion of phonon angular momentum in crystals.Recently, rotational motions of lattice vibrations, i.e., phonons, in crystals attract considerable attentions. As such, the book theoretically demonstrate generations of phonons with rotational motions, based on model calculations and first-principle calculations. In systems without inversion symmetry, the phonon angular momentum is shown to be caused by the temperature gradient, which is demonstrated in crystals such as wurtzite gallium nitride, tellurium, and selenium using the first-principle calculations. In systems with neither time-reversal nor inversion symmetries, the phonon angular momentum is shown to be generated by an electric field. Secondly, the book presents the microscopic mechanisms developed by the author and his collaborator on how these microscopic rotations of nuclei are coupled with electron spins. These predictions serve as building blocks for spintronics with phonons or mechanical motions.
Design of Experiments for Pharmaceutical Product Development: Volume I : Basics and Fundamental Principles
by Sarwar BegThis book volume provides complete and updated information on the applications of Design of Experiments (DoE) and related multivariate techniques at various stages of pharmaceutical product development. It discusses the applications of experimental designs that shall include oral, topical, transdermal, injectables preparations, and beyond for nanopharmaceutical product development, leading to dedicated case studies on various pharmaceutical experiments through illustrations, art-works, tables and figures. This book is a valuable guide for all academic and industrial researchers, pharmaceutical and biomedical scientists, undergraduate and postgraduate research scholars, pharmacists, biostatisticians, biotechnologists, formulations and process engineers, regulatory affairs and quality assurance personnel.
Proceedings of International Conference on Big Data, Machine Learning and Applications: BigDML 2019 (Lecture Notes in Networks and Systems #180)
by Ripon Patgiri Sivaji Bandyopadhyay Valentina Emilia BalasThis book covers selected high-quality research papers presented at the International Conference on Big Data, Machine Learning, and Applications (BigDML 2019). It focuses on both theory and applications in the broad areas of big data and machine learning. It brings together the academia, researchers, developers and practitioners from scientific organizations and industry to share and disseminate recent research findings.
Nonlinear Partial Differential Equations for Future Applications: Sendai, Japan, July 10–28 and October 2–6, 2017 (Springer Proceedings in Mathematics & Statistics #346)
by Shigeaki Koike Hideo Kozono Takayoshi Ogawa Shigeru SakaguchiThis volume features selected, original, and peer-reviewed papers on topics from a series of workshops on Nonlinear Partial Differential Equations for Future Applications that were held in 2017 at Tohoku University in Japan. The contributions address an abstract maximal regularity with applications to parabolic equations, stability, and bifurcation for viscous compressible Navier–Stokes equations, new estimates for a compressible Gross–Pitaevskii–Navier–Stokes system, singular limits for the Keller–Segel system in critical spaces, the dynamic programming principle for stochastic optimal control, two kinds of regularity machineries for elliptic obstacle problems, and new insight on topology of nodal sets of high-energy eigenfunctions of the Laplacian. This book aims to exhibit various theories and methods that appear in the study of nonlinear partial differential equations.