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Seshaiyer Padmanabhan: Quantitative
Biology

Quantitative Biology

This book covers complex analysis (the study of boundary behaviors of analytic functions) and its applications with engineering problems, especially control theory from the viewpoint of boundary functions. The metascience part is rather unique and illustrates a metascientific way of thinking engineering problems by examples of batteries which are cores of electric vehicles.This book gives a way of looking at the phenomena from a higher and brighter point of view through the windows of boundary behavior and metascience. In Chapter 1 which is meant for mathematics-oriented readers, we state materials in standard complex analysis with emphasis on similarity and Laurent expansions. Non-mathematical readers can also benefit by browsing through many examples and worked-out exercises. Chapter 2 gives some concrete examples of invoking novel ideas in the heap of stereo-typed contributions to a field. Possible replacement of LIB by ECaSS(R) is a typical example through which the reader can learn basics of electromagnetism and electrochemistry. The book also provides hints for a deeper understanding of environmental problems as well as how to manage and create a sustainable society.

From Complex Analysis To Metascience: A Stroll Around Boundary Behavior, Similarity And Duality

Advances In Pattern Analysis And Intelligent Sensing

In brief, this book provides the advanced sensing technologies including multi-sensor collaborative sensing for pulse signal acquisition, sensor array design for breath odor perception, and voice signal acquisition. Besides, this book summarizes the advances about pulse feature extraction with improved Gabor function, odor feature extraction based on de-convolution methods. This book also presents the latest recognition methods including evolutionary ensemble model to handle the imbalance problem, multi-feature complementary methods for face image, tongue images, and pulse analysis. Multi-modal hybrid fusion and self-adaptive score fusion for disease classification are proposed and proved effective for medical biometrics.Medical biometrics achieves disease detection and health monitor by sensing and recognizing multi-modal body surface information. It is believed that body surface information, e.g., face, tongue, breath odor, voice, and wrist pulse, is one of the most important biometric features that contains rich pathological information and can be used for health assessments or disease detection. Focusing on the latest progresses in medical biometrics, this book systematically presents advanced signal acquisition techniques, feature extraction methods, and recognition algorithms.Both researchers and engineers in pattern recognition and medical diagnosis will benefit from this book as it offers comprehensive understanding of the advanced signal acquisition techniques, related feature extraction methods, and state-of-the-art analysis methods.

Advanced Medical Biometrics

Volume II

Cryptocurrency Forensics and Investigation using Open Source Intelligence Techniques (OSINT)

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools-just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

The aim of this textbook is to improve students' ability to formulate economic problems and provide essential mathematical tools for analysis across various contexts. This book presents the author's current understanding of mathematics, shaped by several years of teaching this subject as well as enriched through interactions with his students. To aid students in their learning, the book is written in a manner that better highlights key concepts and provides additional clarity when possible. In this way, it is hoped that students will feel more guided in their study of mathematics and its applications in microeconomics.

Essential Mathematics For Microeconomics: A Student's Guide To Key Mathematical Techniques

Selected Topics

Quantum Modelling of Economic and Financial Systems

Scaling (zooming in or out) is taking a close or distant view of an object. Infinite scaling (the scaling parameter tends to zero or infinity) may lead to a limit which is self-similar and much simpler than the original object. For instance, the classical Donsker's theorem says that all weakly dependent stationary processes with finite variance scale to Brownian motion at large scales. In the case of a random field indexed by two-dimensional parameter, both types of scaling can be anisotropic, meaning that the horizontal and vertical axes are scaled at different rate determined by the ratio γ&gt;0 of the scaling exponents along the axes. The natural questions under such scaling are whether the scaling limits exist for any γ&gt;0, and what are these limits are. The book tries to answer these questions. It introduces the concept of scaling transition and discusses its existence for a natural class of planar random fields including Gaussian, linear and some nonlinear ones. The scaling limits are identified and exhibit a surprising trichitomy at a critical point γ0, with 'unbalanced' limits having unusual path properties and dependence structure along one of the coordinate axes. Scaling transition occurs in applied sciences (telecommunications and econometrics) when aggregating independent processes with long-range dependence in which case 'unbalanced' limits are classical Gaussian or stable random fields.

Anisotropic Scaling Of Random Fields With Long-range Dependence: Scaling Limits Of Random Fields With Applications

Healthcare Applications of Neuro-Symbolic Artificial Intelligence provides a comprehensive introduction to the field of neuro-symbolic (NS) artificial intelligence (AI), presenting the most recent advances in deep learning and integration of NS systems and large language models (LLMs). This book evaluates traditional approaches, current approaches, as well as the author’s own approach to NS, to create hybrid architectures and reasoning techniques to overcome the limitations of most existing AI systems such as deep learning, neural networks, and symbolic AI. This book will be a welcome resource for researchers and graduate students in AI, natural language processing, and biomedical informatics, as well as professionals in software development looking to redesign current systems to leverage LLMs through the health application of NS architecture.

Healthcare Applications of Neuro-Symbolic Artificial Intelligence

An Introduction to String Algorithms

Intelligence-Based Medicine: Subspecialty Series

Artificial Intelligence Based Primary Care: Artificial Intelligence and Human Cognition in General Practice and Family Medicine provides a comprehensive look into the integration of artificial intelligence within primary care. This book aims to bridge the gap between data scientists and primary care clinicians by presenting potential AI applications, implementation challenges, and real-world clinical scenarios in an accessible manner. Comprised of 5 sections and 20 chapters, it offers both theoretical insights and practical guidance for family medicine practitioners. Additionally, the book includes a chapter dedicated to a day in the life of a General Practitioner, showcasing the practical impact of AI. It also features an extra compendium listing the Top 100 articles and best books on Artificial Intelligence. This resource is invaluable for academics, researchers, and clinicians eager to expand their knowledge in this emerging field.

Artificial Intelligence and Human Cognition in General Practice and Family Medicine

Artificial Intelligence Based Primary Care

De Gruyter Studies in Mathematical Physics

Mirror symmetry is one of the most exciting ideas in mathematics to emerge in the last two decades. It was introduced in physics as a duality between superconformal field theories. This book discusses this rapidly developing aspect of string theory.

Laurent Polynomials in Mirror Symmetry

Why Not Nonlinear Algebra: Math, Science, Applications And Funding

Quantitative Biology

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