This book is a journey through almost forty years of practice. Each chapter is independent of the others and develops around a specific theme: psychoanalysis in France, the transference, fathers today, psychic bisexuality, the sick body, human destructivity, and so on. The underlying thread is none the less the question of knowing how the drive operates between the biological body and mental functioning consisting of representations and affects, and, especially, how it gives rise to thinking. If thinking is an "act of the flesh", as the author asserts, how can we refine our understanding of the vicissitudes of the "mysterious leap from the mind to the body"? Furthermore, how does Freudian metapsychology still help us today in our encounters with patients? Contemporary clinical practice is sometimes bewildering: acts, violence, pain, and somatization often replace neurotic conflicts and speech. The clinical stories related here have the aim of showing that a psychoanalysis rooted in the Freudian corpus is still alive and can continue to offer creative responses today.

This book contains a wealth of inequalities used in linear analysis, and explains in detail how they are used. The book begins with Cauchy's inequality and ends with Grothendieck's inequality, in between one finds the Loomis-Whitney inequality, maximal inequalities, inequalities of Hardy and of Hilbert, hypercontractive and logarithmic Sobolev inequalities, Beckner's inequality, and many, many more. The inequalities are used to obtain properties of function spaces, linear operators between them, and of special classes of operators such as absolutely summing operators. This textbook complements and fills out standard treatments, providing many diverse applications: for example, the Lebesgue decomposition theorem and the Lebesgue density theorem, the Hilbert transform and other singular integral operators, the martingale convergence theorem, eigenvalue distributions, Lidskii's trace formula, Mercer's theorem and Littlewood's 4/3 theorem. It will broaden the knowledge of postgraduate and research students, and should also appeal to their teachers, and all who work in linear analysis.

You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.

The remarkable woman at heart of the smash New York Times bestseller and Oscar-winning film Hidden Figures tells the full story of her life, including what it took to work at NASA, help land the first man on the moon, and live through a century of turmoil and change. In 2015, at the age of 97, Katherine Johnson became a global celebrity. President Barack Obama awarded her the prestigious Presidential Medal of Freedom—the nation’s highest civilian honor—for her pioneering work as a mathematician on NASA’s first flights into space. Her contributions to America’s space program were celebrated in a blockbuster and Academy-award nominated movie. In this memoir, Katherine shares her personal journey from child prodigy in the Allegheny Mountains of West Virginia to NASA human computer. In her life after retirement, she served as a beacon of light for her family and community alike. Her story is centered around the basic tenets of her life—no one is better than you, education is paramount, and asking questions can break barriers. The memoir captures the many facets of this unique woman: the curious “daddy’s girl,” pioneering professional, and sage elder. This multidimensional portrait is also the record of a century of racial history that reveals the influential role educators at segregated schools and Historically Black Colleges and Universities played in nurturing the dreams of trailblazers like Katherine. The author pays homage to her mentor—the African American professor who inspired her to become a research mathematician despite having his own dream crushed by racism. Infused with the uplifting wisdom of a woman who handled great fame with genuine humility and great tragedy with enduring hope, My Remarkable Journey ultimately brings into focus a determined woman who navigated tough racial terrain with soft-spoken grace—and the unrelenting grit required to make history and inspire future generations.

Assuming 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 and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.

Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

This book introduces readers to essential technology assessment and forecasting tools, demonstrating their use on the basis of multiple cases. As organizations in the high-tech industry need to be able to assess emerging technologies, the book presents cases in which formal decision-making models are developed, providing a framework for decision-making in the context of technology acquisition and development. Applications of different technology forecasting tools are also discussed for a range of technologies and sectors, providing a guide to keep R&D organizations abreast of technological trends that affect their business. As such, the book offers a valuable the theoretical and practical reference guide for R&D managers responsible for emerging and future technologies.