- Table View
- List View
The GETMe Mesh Smoothing Framework: A Geometric Way to Quality Finite Element Meshes
by Dimitris Vartziotis Joachim WipperHigh quality meshes play a key role in many applications based on digital modeling and simulation. The finite element method is a paragon for such an approach and it is well known that quality meshes can significantly improve computational efficiency and solution accuracy of this method. Therefore, a lot of effort has been put in methods for improving mesh quality. These range from simple geometric approaches, like Laplacian smoothing, with a high computational efficiency but possible low resulting mesh quality, to global optimization-based methods, resulting in an excellent mesh quality at the cost of an increased computational and implementational complexity. <P><P>The geometric element transformation method (GETMe) aims to fill the gap between these two approaches. It is based on geometric mesh element transformations, which iteratively transform polygonal and polyhedral elements into their regular counterparts or into elements with a prescribed shape. GETMe combines a Laplacian smoothing-like computational efficiency with a global optimization-like effectiveness. The method is straightforward to implement and its variants can also be used to improve tangled and anisotropic meshes. <P><P>This book describes the mathematical theory of geometric element transformations as foundation for mesh smoothing. It gives a thorough introduction to GETMe-based mesh smoothing and its algorithms providing a framework to focus on effectively improving key mesh quality aspects. It addresses the improvement of planar, surface, volumetric, mixed, isotropic, and anisotropic meshes and addresses aspects of combining mesh smoothing with topological mesh modification. <P><P>The advantages of GETMe-based mesh smoothing are demonstrated by the example of various numerical tests. These include smoothing of real world meshes from engineering applications as well as smoothing of synthetic meshes for demonstrating key aspects of GETMe-based mesh improvement. Results are compared with those of other smoothing methods in terms of runtime behavior, mesh quality, and resulting finite element solution efficiency and accuracy. <P><P>Features: <li>Helps to improve finite element mesh quality by applying geometry-driven mesh smoothing approaches. <li>Supports the reader in understanding and implementing GETMe-based mesh smoothing. <li>Discusses aspects and properties of GETMe smoothing variants and thus provides guidance for choosing the appropriate mesh improvement algorithm. <li>Addresses smoothing of various mesh types: planar, surface, volumetric, isotropic, anisotropic, non-mixed, and mixed. <li>Provides and analyzes geometric element transformations for polygonal and polyhedral elements with regular and non-regular limits. <li>Includes a broad range of numerical examples and compares results with those of other smoothing methods.
Getting: Practice and Principles of Data Visualisation (Chapman & Hall/CRC Data Science Series)
by Antony UnwinData graphics are used extensively to present information. Understanding graphics is a lot about understanding the data represented by the graphics, having a feel not just for the numbers themselves, the reliability and uncertainty associated with them, but also for what they mean. This book presents a practical approach to data visualisation with real applications front and centre.The first part of the book is a series of case studies, each describing a graphical analysis of a real dataset. The second part pulls together ideas from the case studies and provides an overview of the main factors affecting understanding graphics.Key Features: Explains how to get insights from graphics. Emphasises the value of drawing many graphics. Underlines the importance for analysis of background knowledge and context. Readers may be data scientists, statisticians or people who want to become more visually literate. A knowledge of Statistics is not required, just an interest in data graphics and some experience of working with data. It will help if the reader knows something of basic graphic forms such as barcharts, histograms, and scatterplots.
Getting Acquainted with Homogenization and Multiscale (Compact Textbooks in Mathematics)
by Leonid Berlyand Volodymyr RybalkoThe objective of this book is to navigate beginning graduate students in mathematics and engineering through a mature field of multiscale problems in homogenization theory and to provide an idea of its broad scope. An overview of a wide spectrum of homogenization techniques ranging from classical two-scale asymptotic expansions to Gamma convergence and the rapidly developing field of stochastic homogenization is presented. The mathematical proofs and definitions are supplemented with intuitive explanations and figures to make them easier to follow. A blend of mathematics and examples from materials science and engineering is designed to teach a mixed audience of mathematical and non-mathematical students.
Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy
by William A. BarnettA leading economist contends that the recent financial crisis was caused not by the failure of mainstream economics but by corrupted monetary data constructed without reference to economics.Blame for the recent financial crisis and subsequent recession has commonly been assigned to everyone from Wall Street firms to individual homeowners. It has been widely argued that the crisis and recession were caused by “greed” and the failure of mainstream economics. In Getting It Wrong, leading economist William Barnett argues instead that there was too little use of the relevant economics, especially from the literature on economic measurement. Barnett contends that as financial instruments became more complex, the simple-sum monetary aggregation formulas used by central banks, including the U.S. Federal Reserve, became obsolete. Instead, a major increase in public availability of best-practice data was needed. Households, firms, and governments, lacking the requisite information, incorrectly assessed systemic risk and significantly increased their leverage and risk-taking activities. Better financial data, Barnett argues, could have signaled the misperceptions and prevented the erroneous systemic-risk assessments.When extensive, best-practice information is not available from the central bank, increased regulation can constrain the adverse consequences of ill-informed decisions. Instead, there was deregulation. The result, Barnett argues, was a worst-case toxic mix: increasing complexity of financial instruments, inadequate and poor-quality data, and declining regulation.Following his accessible narrative of the deep causes of the crisis and the long history of private and public errors, Barnett provides technical appendixes, containing the mathematical analysis supporting his arguments.
Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy
by William A. BarnettBlame for the recent financial crisis and subsequent recession has commonly been assigned to everyone from Wall Street firms to individual homeowners. It has been widely argued that the crisis and recession were caused by "greed" and the failure of mainstream economics. In Getting It Wrong, leading economist William Barnett argues instead that there was too little use of the relevant economics, especially from the literature on economic measurement. Barnett contends that as financial instruments became more complex, the simple-sum monetary aggregation formulas used by central banks, including the U. S. Federal Reserve, became obsolete. Instead, a major increase in public availability of best-practice data was needed. Households, firms, and governments, lacking the requisite information, incorrectly assessed systemic risk and significantly increased their leverage and risk-taking activities. Better financial data, Barnett argues, could have signaled the misperceptions and prevented the erroneous systemic-risk assessments. When extensive, best-practice information is not available from the central bank, increased regulation can constrain the adverse consequences of ill-informed decisions. Instead, there was deregulation. The result, Barnett argues, was a worst-case toxic mix: increasing complexity of financial instruments, inadequate and poor-quality data, and declining regulation. Following his accessible narrative of the deep causes of the crisis and the long history of private and public errors, Barnett provides technical appendixes, containing the mathematical analysis supporting his arguments.
Getting Ready for the Smarter Balanced Assessment Grade 4
by Houghton Mifflin HarcourtMath practice tests for Grade 4
Getting Started in Mathematical Life Sciences: From MATLAB Programming to Computer Simulations (Theoretical Biology)
by Makoto SatoThis book helps the reader make use of the mathematical models of biological phenomena starting from the basics of programming and computer simulation. Computer simulations based on a mathematical model enable us to find a novel biological mechanism and predict an unknown biological phenomenon. Mathematical biology could further expand the progress of modern life sciences. Although many biologists are interested in mathematical biology, they do not have experience in mathematics and computer science. An educational course that combines biology, mathematics, and computer science is very rare to date. Published books for mathematical biology usually explain the theories of established mathematical models, but they do not provide a practical explanation for how to solve the differential equations included in the models, or to establish such a model that fits with a phenomenon of interest. MATLAB is an ideal programming platform for the beginners of computer science. This book starts from the very basics about how to write a programming code for MATLAB (or Octave), explains how to solve ordinary and partial differential equations, and how to apply mathematical models to various biological phenomena such as diabetes, infectious diseases, and heartbeats. Some of them are original models, newly developed for this book. Because MATLAB codes are embedded and explained throughout the book, it will be easy to catch up with the text. In the final chapter, the book focuses on the mathematical model of the proneural wave, a phenomenon that guarantees the sequential differentiation of neurons in the brain. This model was published as a paper from the author’s lab (Sato et al., PNAS 113, E5153, 2016), and was intensively explained in the book chapter “Notch Signaling in Embryology and Cancer”, published by Springer in 2020. This book provides the reader who has a biological background with invaluable opportunities to learn and practice mathematical biology.
Getting Started with Business Analytics: Insightful Decision-Making
by David Roi Hardoon Galit ShmueliAssuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts
Getting Started with Grafana: Real-Time Dashboards for IT and Business Operations
by Ronald McCollamBegin working with the Grafana data visualization platform. This book is a “how-to manual” for deploying and administering Grafana, creating real-time dashboards and alerts, exploring the data you have, and even synthesizing new data by combining and manipulating data from multiple different sources. You’ll be able to see and manage data on any scale, from your laptop or a Raspberry Pi to a production datacenter or even a multi-region cloud environment!Getting Started with Grafana takes a hands-on approach. You’ll learn by doing with easy-to-follow examples along with pointers to more resources to help you go deeper. The skills you’ll learn will help you provide business value by monitoring your operations in real time and reacting to changing circumstances as they occur. You’ll be able to derive new insights from your existing data through Grafana’s powerful and beautiful graphing capabilities, and you’ll be able to share your dashboards with colleagues so everyone in your organization can benefit. What You Will LearnConnect to data "where it lives” and work with multiple sources of dataBuild beautiful and informative dashboards that show real-time statusDeploy Grafana at any scale and manage it efficientlyIntegrate with other enterprise systems such as LDAP or Active DirectoryAutomate creation and deployment of Grafana, dashboards, and alertsUnderstand what is available in the Enterprise version of GrafanaWho This Book Is ForAnyone who has data that they want to understand visually, IT professionals who work with multiple sources of data on a regular basis and need to make sense of the confusion that this data sprawl causes, and people who learn best by doing and want to get hands-on experience quickly with a project and then grow their knowledge
Getting Started with Julia Programming
by Ivo BalbaertThis book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby.
Getting Started with Python Data Analysis
by Phuong VothihongIf you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.
Getting Started with ResearchKit
by Edward Cessna Dhanush BalachandranEnter the era of medical research using mobile devices with the help of this guide on ResearchKit! About This Book * Create a simple clinical research app using most aspects of ResearchKit * Build a simple survey with various data types with the results printed on the screen. * A step-by-step guide introducing Apple's ResearchKit and techniques to incorporate it into various apps. Who This Book Is For This book is aimed at medical researchers with basic iOS coding knowledge and iOS developers looking to create clinical research apps. What You Will Learn * Learn to create customized consent form * Get introduced to two backend services: a simple backend server using Sinatra and Sage Bridge * Build a custom task (a conditional survey example) and a navigable task * Get an Overview of ResearchKit's open source repository and App Core * Interaction with the hardware of the device including the gyro and the motion sensors * Learn the basics of this revolutionary technology * Get introduced to the barebones app and learn to write your first code In Detail ResearchKit is an open source software development framework from Apple that lets you easily create mobile applications for clinical research studies. ResearchKit provides you the ability to orchestrate the administration of tasks and recording of the results. ResearchKit provides tasks in order to perform informed consent, active tasks, and surveys. Starting with the basics of the ResearchKit framework, this books walks you through the steps of creating iOS applications that could serve as the basis of a clinical research mobile app. This book will introduce readers to ResearchKit and how to turn your iPhone into into a clinical research tool. The book will start off by installing and building the research framework in line with the researcher's needs; during this, the reader will learn to embed ResearchKit in the application and create a small task. After this, the book will go a little deeper into creating modules for surveys, consents, and so on. The book will also cover the various aspects of privacy and security with regard to participant data, and how to build dashboards for visualizing medical data and results in line with the researcher's requirements: data backends, JSON serialization and deserialization, and so on. Readers will be able to fully utilize ResearchKit for medical research, will be able to get more and more patients to participate in their surveys, and will gain insights from the surveys using the dashboards created. Style and approach A hands-on guide with ample screenshots for you to follow and learn about ResearchKit. Each topic is explained sequentially and placed in context so that you can get a better understanding of every step in the process of creating clinical research apps.
Gewöhnliche Differentialgleichungen
by Jürgen ScheurleDas vorliegende Lehrbuch enthält eine kompakte, in Vorlesungen erprobte Einführung in diese moderne Sichtweise der GDGn, wobei der klassische Stoff nicht vernachlässigt wird. Einerseits behandelt es auf mathematisch sehr gründliche Weise die wichtigsten analytischen Methoden und Resultate der klassischen Theorie für allgemeine Anfangswertprobleme, inklusive von Sätzen zur Existenz, Eindeutigkeit, stetigen bzw. glatten Abhängigkeit und Fortsetzung von Lösungen. Auch lineare Rand- und Eigenwertprobleme werden betrachtet. Andererseits werden geometrische Konzepte wie Phasenraum, Phasenfluss, Orbit, Äquivalenz und Stabilität eingeführt sowie ausführlich diskutiert. Es wird lediglich Vertrautheit mit dem an Universitäten in Grundvorlesungen gelehrten Stoff der Analysis und der Linearen Algebra vorausgesetzt. Die Anordnung des Stoffs ist so gewählt, dass das Lehrbuch in Vorlesungen unterschiedlicher mathematischer Tiefe im Rahmen von Bachelor- und Masterstudiengängen einsetzbar ist, wobei es insbesondere eine ideale Grundlage für weiterführende Lehrveranstaltungen über dynamische Systeme ist.
Gewöhnliche Differenzialgleichungen leicht gemacht!
by Jochen BallaDas vorliegende Buch bietet eine leicht lesbare Einführung in Theorie und Praxis gewöhnlicher Differenzialgleichungen. Es richtet sich an Studierende der Natur- und Ingenieurwissenschaften, der Wirtschaftswissenschaften und allgemein aller Fachgebiete, die Differenzialgleichungen benötigen. Auch Mathematikstudierende, die einen gut verständlichen Zugang suchen, werden angesprochen. Es werden gewöhnliche Differenzialgleichungen erster Ordnung, Differenzialgleichungssysteme, Differenzialgleichungen höherer Ordnung und lineare Differenzialgleichungen mit konstanten Koeffizienten behandelt. Auch ein Ausblick in partielle Differenzialgleichungen wird gegeben.Viele Beispiele und Übungsaufgaben ermutigen den Leser, sofort selbst „loszurechnen“, und Programmierbeispiele helfen dabei, Differenzialgleichungen auch numerisch zu bewältigen. Das Lehrbuch bietet verschiedene Hilfestellungen, die den Zugang erleichtern:Lesehilfen helfen über schwierige Stellen hinwegZwischenfragen mit Antworten regen zum Nachdenken anÜbungsaufgaben mit ausführlichen Lösungen motivieren zum praktischen Umgang mit Differenzialgleichungen„Das Wichtigste in Kürze“ fasst am Ende eines jeden Kapitels den Stoff zusammenEin Anhang bietet eine kurze Einführung in komplexe Zahlen Prof. Dr. rer. nat. Jochen Balla ist theoretischer Physiker. Seit 2004 unterrichtet er Mathematik für Ingenieure in verschiedenen Bachelor- und Master-Studiengängen der Hochschule Bochum.
GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists
by Weikai Yan Manjit S. KangResearch data is expensive and precious, yet it is seldom fully utilized due to our ability of comprehension. Graphical display is desirable, if not absolutely necessary, for fully understanding large data sets with complex interconnectedness and interactions. The newly developed GGE biplot methodology is a superior approach to the graphical analys
ggplot2
by Hadley WickhamThis new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e. g. , importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.
Ghidra Software Reverse Engineering for Beginners: Analyze, identify, and avoid malicious code and potential threats in your networks and systems
by A. P. DavidDetect potentials bugs in your code or program and develop your own tools using the Ghidra reverse engineering framework developed by the NSA projectKey FeaturesMake the most of Ghidra on different platforms such as Linux, Windows, and macOSLeverage a variety of plug-ins and extensions to perform disassembly, assembly, decompilation, and scriptingDiscover how you can meet your cybersecurity needs by creating custom patches and toolsBook DescriptionGhidra, an open source software reverse engineering (SRE) framework created by the NSA research directorate, enables users to analyze compiled code on any platform, whether Linux, Windows, or macOS. This book is a starting point for developers interested in leveraging Ghidra to create patches and extend tool capabilities to meet their cybersecurity needs.You'll begin by installing Ghidra and exploring its features, and gradually learn how to automate reverse engineering tasks using Ghidra plug-ins. You'll then see how to set up an environment to perform malware analysis using Ghidra and how to use it in the headless mode. As you progress, you'll use Ghidra scripting to automate the task of identifying vulnerabilities in executable binaries. The book also covers advanced topics such as developing Ghidra plug-ins, developing your own GUI, incorporating new process architectures if needed, and contributing to the Ghidra project.By the end of this Ghidra book, you'll have developed the skills you need to harness the power of Ghidra for analyzing and avoiding potential vulnerabilities in code and networks.What you will learnGet to grips with using Ghidra's features, plug-ins, and extensionsUnderstand how you can contribute to GhidraFocus on reverse engineering malware and perform binary auditingAutomate reverse engineering tasks with Ghidra plug-insBecome well-versed with developing your own Ghidra extensions, scripts, and featuresAutomate the task of looking for vulnerabilities in executable binaries using Ghidra scriptingFind out how to use Ghidra in the headless modeWho this book is forThis SRE book is for developers, software engineers, or any IT professional with some understanding of cybersecurity essentials. Prior knowledge of Java or Python, along with experience in programming or developing applications, is required before getting started with this book.
Giants vs. Dodgers: The Coast-to-Coast History of the Rivalry Heard ?Round the World
by Steve Dilbeck Joe Konte Bruce JenkinsGames between the Dodgers and Giants are never just another day at the ballpark. Dating back to the late nineteenth century-when the teams embodied the competitive spirit of rival metropolises of New York and Brooklyn-the Giants-Dodgers rivalry gained intensity throughout the early twentieth century. The cheering and jeering continued unabated until 1957, when the clubs backed the moving vans up to the Polo Grounds and Ebbets Field, and took their rivalry to new venues in Los Angeles and San Francisco.Indeed, Brooklyn-New York baseball was a tough act to follow, but the West Coast version didn’t take long to fire up the emotions. Only six games into the first West Coast season, the clubs had their first beanball dustup. The venue had changed but the venom remained, and the rivalry became author Joe Konte’s obsession. Fifty-eight years ago, he attended one of the first Giants-Dodgers games ever played outside of New York. A longtime newspaper editor and baseball fiend, Konte understands what is so special about this storied rivalry. And so-via statistical analysis, game summaries, roster scrutiny, manager matchups, season recaps, and more-he has put together a rivalry bible. Revised and updated to include the events of the last three seasons-from the Giants’ 2014 World Series win and the Dodgers’ playoff runs-Giants vs. Dodgers captures the spirit and intensity of one of the greatest rivalries in American sports.
Gifts to the Sad Country: Essays on the Chinese Diaspora
by Souchou YaoThis book is a study of an ethnic-Chinese family in Malaysia as it struggled with the upheavals in China during the Land Reform (1945-1953) and the Great Leap Forward (1958-1962). Based on fieldwork in Malaysia and in a village in Dabu County, Southern China, it tells a story of a family whose existence straddled two nations, two political systems. Emigration is shown to be both a positive experience and a source of despair. The study redefines the conventional narrative about the Chinese diaspora as economically driven and politically expedient; mobility, personal freedom and transnational journeying were a part of their cultural history. The book highlights the fact that Chinese homeland, even under communist rule, offered the people a means of identification under difficult circumstances. During the time of radical reform, the diaspora adapted themselves to the conditions in the homeland, and for some China remained a place of longing and emotional attachment.
Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Elements in Structure and Dynamics of Complex Networks)
by Naoki Masuda Christian L. VestergaardMany multiagent dynamics can be modeled as a stochastic process in which the agents in the system change their state over time in interaction with each other. The Gillespie algorithms are popular algorithms that exactly simulate such stochastic multiagent dynamics when each state change is driven by a discrete event, the dynamics is defined in continuous time, and the stochastic law of event occurrence is governed by independent Poisson processes. The first main part of this volume provides a tutorial on the Gillespie algorithms focusing on simulation of social multiagent dynamics occurring in populations and networks. The authors clarify why one should use the continuous-time models and the Gillespie algorithms in many cases, instead of easier-to-understand discrete-time models. The remainder of the Element reviews recent extensions of the Gillespie algorithms aiming to add more reality to the model (i.e., non-Poissonian cases) or to speed up the simulations. This title is also available as open access on Cambridge Core.
Gini Inequality Index: Methods and Applications
by Nitis Mukhopadhyay"Prof. Nitis Mukhopadhyay and Prof. Partha Pratim Sengupta, who edited this volume with great attention and rigor, have certainly carried out noteworthy activities." - Giovanni Maria Giorgi, University of Rome (Sapienza) "This book is an important contribution to the development of indices of disparity and dissatisfaction in the age of globalization and social strife." - Shelemyahu Zacks, SUNY-Binghamton "It will not be an overstatement when I say that the famous income inequality index or wealth inequality index, which is most widely accepted across the globe is named after Corrado Gini (1984-1965). ... I take this opportunity to heartily applaud the two co-editors for spending their valuable time and energy in putting together a wonderful collection of papers written by the acclaimed researchers on selected topics of interest today. I am very impressed, and I believe so will be its readers." - K.V. Mardia, University of Leeds Gini coefficient or Gini index was originally defined as a standardized measure of statistical dispersion intended to understand an income distribution. It has evolved into quantifying inequity in all kinds of distributions of wealth, gender parity, access to education and health services, environmental policies, and numerous other attributes of importance. Gini Inequality Index: Methods and Applications features original high-quality peer-reviewed chapters prepared by internationally acclaimed researchers. They provide innovative methodologies whether quantitative or qualitative, covering welfare economics, development economics, optimization/non-optimization, econometrics, air quality, statistical learning, inference, sample size determination, big data science, and some heuristics. Never before has such a wide dimension of leading research inspired by Gini's works and their applicability been collected in one edited volume. The volume also showcases modern approaches to the research of a number of very talented and upcoming younger contributors and collaborators. This feature will give readers a window with a distinct view of what emerging research in this field may entail in the near future.
The Gini Methodology
by Edna Schechtman Shlomo YitzhakiGini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
Giovanni Battista Guccia: Pioneer of International Cooperation in Mathematics
by Benedetto Bongiorno Guillermo P. CurberaThis book examines the life and work of mathematician Giovanni Battista Guccia, founder of the Circolo Matematico di Palermo and its renowned journal, the Rendiconti del Circolo matematico di Palermo. The authors describe how Guccia, an Italian geometer, was able to establish a mathematical society in Sicily in the late nineteenth century, which by 1914 would grow to become the largest and most international in the world, with one of the most influential journals of the time. The book highlights the challenges faced by Guccia in creating an international society in isolated Palermo, and places Guccia’s activities in the wider European context through comparisons with the formation of the London Mathematical Society and the creation of Mittag-Leffler’s Acta Mathematica in Stockholm. Based on extensive searches in European archives, this scholarly work follows both historical and scientific treads, and will appeal to those interested in the history of mathematics and science in general.
Girls Get Curves: Geometry Takes Shape
by Danica McKellarNew York Times bestselling author Danica McKellar makes it a breeze to excel in high school geometry!Hollywood actress and math whiz Danica McKellar has completely shattered the &“math nerd&” stereotype. For years, she&’s been showing girls how to feel confident and ace their math classes—with style! With Girls Get Curves, she applies her winning techniques to high school geometry, giving readers the tools they need to feel great and totally &“get&” everything from congruent triangles to theorems, and more. Inside you&’ll find:• Time-saving tips and tricks for homework and tests• Illuminating practice problems (and proofs!) with detailed solutions• Totally relateable real-world examples• True stories from Danica&’s own life as an actress and math student• A Troubleshooting Guide, for getting unstuck during even the trickiest proofs!With Danica as a coach, girls everywhere can stop hiding from their homework and watch their scores rise!
Girmitiya Culture and Memory: Navigating Identity, Tradition, and Resilience across Continents
by Priyanka Chaudhary Neha SinghThis book explores the multifaceted dimensions of the Girmitya diaspora and post-memory. The intersections of dis/re-location and memory have always been a focus of scholarly interest and the volume envisages the roots of migration and culture, life stories, narratives, and personal anecdotes. It further accentuates Girmitiya struggles, politics of displacement, relationships with the homeland and host land, oral traditions, repercussions, and retention of the archival sites. The cross-examination of memories helps in building a framework to study the varied experiences of the Girmitiya community. In this volume, through a blend of historical and scholarly discourse, we embark on a journey to unearth the layers of meaning embedded within the Girmitya experience. The tales of Girmitya migration amplifies marginalized voices and illuminates the enduring resilience. By chronicling the experiences of the indentured migration, we pay homage to the pioneers, recognize the intricacy of their toils, and commemorate the continuing legacy.