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Security Requirements Engineering

Designing Secure Socio-Technical Systems
By , and

Security requirements engineering is especially challenging because designers must consider not just the software under design but also interactions among people, organizations, hardware, and software. Taking this broader perspective means designing a secure socio-technical system rather than a merely technical system. This book presents a novel, model-driven approach to designing secure socio-technical systems.

Programming Models for Parallel Computing

Edited by Pavan Balaji

With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today.

Managing Risk and Uncertainty

A Strategic Approach
By

This book offers a framework for making decisions under risk and uncertainty. Synthesizing research from economics, finance, decision theory, management, and other fields, the book provides a set of tools and a way of thinking that determines the relative merits of different strategies. It takes as its premise that we make better decisions if we use the whole toolkit of economics and related fields to inform our decision making.

Analytical Methods for Dynamic Modelers

Edited by Hazhir Rahmandad, Rogelio Oliva and Nathaniel D. Osgood

Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling.

Capital Markets, Fifth Edition

Institutions, Instruments, and Risk Management
By

Over the last fifty years, an extensive array of instruments for financing, investing, and controlling risk has become available in financial markets, with demand for these innovations driven by the needs of investors and borrowers. The recent financial crisis offered painful lessons on the consequences of ignoring the risks associated with new financial products and strategies. This substantially revised fifth edition of a widely used text covers financial product innovation with a new emphasis on risk management and regulatory reform.

Modern Macroeconomics

By

The modern study and analysis of macroeconomics begins by considering how microeconomic units—consumers and firms—make decisions, and then investigates how these choices interact to yield economy-wide outcomes. This innovative textbook takes this “modern” approach, teaching macroeconomics through its microeconomic foundations. It does so by adopting the representative agent paradigm. By modeling the representative consumer and the representative firm, students will learn to describe macroeconomic outcomes and consider the effects of macroeconomic policies.

Fundamentals of Machine Learning for Predictive Data Analytics

Algorithms, Worked Examples, and Case Studies
By , and

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Decision Making Under Uncertainty

Theory and Application
By

Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective.

Thinking Things Through, Second Edition

An Introduction to Philosophical Issues and Achievements
By

Thinking Things Through offers a broad, historical, and rigorous introduction to the logical tradition in philosophy and its contemporary significance. It is unique among introductory philosophy texts in that it considers both the historical development and modern fruition of a few central questions. It traces the influence of philosophical ideas and arguments on modern logic, statistics, decision theory, computer science, cognitive science, and public policy.

The Little Prover

By and

The Little Prover introduces inductive proofs as a way to determine facts about computer programs. It is written in an approachable, engaging style of question-and-answer, with the characteristic humor of The Little Schemer (fourth edition, MIT Press). Sometimes the best way to learn something is to sit down and do it; the book takes readers through step-by-step examples showing how to write inductive proofs.

  • Page 3 of 58