Machine Learning Applications In Software Engineering

The first text to integrate behavioral and cognitive approaches to learning and memory, this engaging textbook emphasizes human research, reflecting the field's evolution. Learning and Memory also recognizes the vital contribution of animal research, covering all historically important studies. Written in a lively and conversational style, this second edition encourages students to think critically. One example is its exploration of the Rescorla-Wagner model, the most important theory of conditioning, now further streamlined to improve student comprehension. Another is the addition of critical-thinking questions, which encourage students to evaluate their reactions to the material they've read, and relate findings to their own lives. Research includes an emphasis on practical applications such as treatments for phobias, addictions, and autism; the arguments for and against corporal punishment; whether recovered memories and eyewitness testimony should be believed; and effective techniq

The first text to integrate behavioral and cognitive approaches to learning and memory, this engaging textbook emphasizes human research, reflecting the field's evolution. Learning and Memory also recognizes the vital contribution of animal research, covering all historically important studies. Written in a lively and conversational style, this second edition encourages students to think critically. One example is its exploration of the Rescorla-Wagner model, the most important theory of conditioning, now further streamlined to improve student comprehension. Another is the addition of critical-thinking questions, which encourage students to evaluate their reactions to the material they've read, and relate findings to their own lives. Research includes an emphasis on practical applications such as treatments for phobias, addictions, and autism; the arguments for and against corporal punishment; whether recovered memories and eyewitness testimony should be believed; and effective techniq

Origami, the art of paper folding, has a rich mathematical theory. Early investigations go back to at least the 1930s, but the twenty-first century has seen a remarkable blossoming of the mathematics of folding. Besides its use in describing origami and designing new models, it is also finding real-world applications from building nano-scale robots to deploying large solar arrays in space. Written by a world expert on the subject, Origametry is the first complete reference on the mathematics of origami. It brings together historical results, modern developments, and future directions into a cohesive whole. Over 180 figures illustrate the constructions described while numerous 'diversions' provide jumping-off points for readers to deepen their understanding. This book is an essential reference for researchers of origami mathematics and its applications in physics, engineering, and design. Educators, students, and enthusiasts will also find much to enjoy in this fascinating account of th

Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-p

Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.

This volume offers a historical and critical analysis of the emerging field of the learning sciences, which takes an interdisciplinary approach to understanding and improving how children and adults learn. It features a wide range of authors, including established scholars who founded and guided the learning sciences through the initial turbulence of forming a new line of academic inquiry, as well as newcomers who are continuing to shape the field. This diversity allows for a broad yet selective perspective on what the learning sciences are, why they came to be, and how contributors conduct their work. Reflections on the Learning Sciences serves both as a starting point for discussion among scholars familiar with the discipline and as an introduction for those interested in learning more. It will benefit graduate students and researchers in computer science, educational psychology, instructional technology, science, engineering, and mathematics.

Discover the subject of optimization in a new light with this modern and unique treatment. Includes a thorough exposition of applications and algorithms in sufficient detail for practical use, while providing you with all the necessary background in a self-contained manner. Features a deeper consideration of optimal control, global optimization, optimization under uncertainty, multiobjective optimization, mixed-integer programming and model predictive control. Presents a complete coverage of formulations and instances in modelling where optimization can be applied for quantitative decision-making. As a thorough grounding to the subject, covering everything from basic to advanced concepts and addressing real-life problems faced by modern industry, this is a perfect tool for advanced undergraduate and graduate courses in chemical and biochemical engineering.

Metamaterials have established themselves as one of the most important topics in physics and engineering, and have found practical application across a wide variety of fields including photonics, condensed matter physics, materials science, and biological and medical physics. This modern and self-contained text delivers a pedagogical treatment of the topic, rooted within the fundamental principles of nanophotonics. A detailed and unified description of metamaterials and metasurfaces is developed, beginning with photonic crystals and their underlying electromagnetic properties before introducing plasmonic effects and key metamaterial configurations. Recent developments in research are also presented along with cutting-edge applications in the field. This advanced textbook will be invaluable to students and researchers working in the fields of optics and nanophotonics.

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

Based on interdisciplinary research into 'Directional Change', a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic

Shigley's Mechanical Engineering Design isintended for students beginning the study of mechanical engineering design.Students will find that the text inherently directs them into familiarity withboth the basics of design decisions and the standards of industrial components.It combines the straightforward focus on fundamentals that instructors havecome to expect with a modern emphasis on design and new applications. Thisedition maintains the well-designed approach that has made this book thestandard in machine design for nearly 50 years. McGraw Hill Education's Connectis also available as an optional add on item.Connect is the only integratedlearning system that empowers students by continuously adapting to deliverprecisely what they need when they need it how they need it so that class timeis more effective. Connect allows the professor to assign homework quizzes andtests easily and automatically grades and records the scores of the student'swork. Problems are randomized to prevent sha

This book covers over two decades research on Spherical Nucleic Acids and their anisotropic analogues, including synthesis and fundamental properties, and applications in colloidal crystallization, ad

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with po

Electronic skins are critical for many applications in human-machine-environment interactions. Tactile sensitivity over large areas can be especially applied to prosthetics. Moreover, the potential for wearables, interactive surfaces, and human robotics have propelled research in this area. In this Element, we provide an account and directional atlas of the progress in materials and devices for electronic skins, in the context of sensing principles and skin-like features. Additionally, we give an overview of essential electronic circuits and systems used in large-area tactile sensor arrays. Finally, we present the challenges and provide perspectives on future developments.

This book introduces artificial neural networks to students and professionals. It covers the theory and applications in statistical learning methods with concrete Python code examples.

This comprehensive and timely book, New Age Analytics: Transforming the Internet through Machine Learning, IoT, and Trust Modeling, explores the importance of tools and techniques used in machine lear

It will soon be impossible to tell what is real and what is fake. Recent advances in AI mean that by scanning images of a person (for example using Facebook), a powerful machine learning system can

A multitude of processes in hydrology and environmental engineering are either random or entail random components which are characterized by random variables. These variables are described by frequency distributions. This book provides an overview of different systems of frequency distributions, their properties, and applications to the fields of water resources and environmental engineering. A variety of systems are covered, including the Pearson system, Burr system, and systems commonly applied in economics, such as the D'Addario, Dagum, Stoppa, and Esteban systems. The latter chapters focus on the Singh system and the frequency distributions deduced from Bessel functions, maximum entropy theory, and the transformations of random variables. The final chapter introduces the genetic theory of frequency distributions. Using real-world data, this book provides a valuable reference for researchers, graduate students, and professionals interested in frequency analysis.

Understand the theoretical principles, key technologies and applications of UDNs with this authoritative survey. Theory is explained in a clear, step-by-step manner, and recent advances and open research challenges in UDN physical layer design, resource allocation and network management are described, with examples, in the context of B5G and 6G standardization. Topics covered include NOMA-based physical layer design, physical layer security. Interference management, 3D base station deployment, software defined UDNs, wireless edge caching in UDNs, UDN-based UAVs and field trials and tests. A perfect resource for graduate students, researchers and professionals who need to get up to speed on the state of the art and future opportunities in UDNs.

Learning to program isn't just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

Do you have the tools to address recent challenges and problems in modern computer networks? Discover a unified view of auction theoretic applications and develop auction models, solution concepts, and algorithms with this multidisciplinary review. Devise distributed, dynamic, and adaptive algorithms for ensuring robust network operation over time-varying and heterogeneous environments, and for optimizing decisions about services, resource allocation, and usage of all network entities. Topics including cloud networking models, MIMO, mmWave communications, 5G, data aggregation, task allocation, user association, interference management, wireless caching, mobile data offloading, and security. Introducing fundamental concepts from an engineering perspective and describing a wide range of state-of-the-art techniques, this is an excellent resource for graduate and senior undergraduate students, network and software engineers, economists, and researchers.

The Web of Things (WoT) is a concept that describes approaches, programming tools and software architectural systems, which interface networks of real-world objects with the World Wide Web. The book is organized into 11 chapters, each focusing on a unique wireless technological aspect of the Web of Things, and it aims to comprehensively cover each of its various applications, including:A strong emphasis on WoT problems and solutions, identifying the main open issues, innovations and latest technologies behind WoTA blend of theoretical and simulation-based problems for better understanding of the concepts behind WoTVarious exemplifying applications in which the use of WoT is very attractive and an inspiration for future applicationsThe book will be useful to researchers, software developers and undergraduate and postgraduate students, as well as practitioners.

Master simple to advanced biomaterials and structures with this essential text. Featuring topics ranging from bionanoengineered materials to bio-inspired structures for spacecraft and bio-inspired robots, and covering issues such as motility, sensing, control and morphology, this highly illustrated text walks the reader through key scientific and practical engineering principles, discussing properties, applications and design. Presenting case studies for the design of materials and structures at the nano, micro, meso and macro-scales, and written by some of the leading experts on the subject, this is the ideal introduction to this emerging field for students in engineering and science as well as researchers.

This third edition capitalizes on the success of the previous editions and leverages the important advancements in visualization, data analysis, and sharing capabilities that have emerged in recent years. It serves as an accelerated guide to decision support designs for consultants, service professionals and students. This 'fast track' enables a ramping up of skills in Excel for those who may have never used it to reach a level of mastery that will allow them to integrate Excel with widely available associated applications, make use of intelligent data visualization and analysis techniques, automate activity through basic VBA designs, and develop easy-to-use interfaces for customizing use. The content of this edition has been completely restructured and revised, with updates that correspond with the latest versions of software and references to contemporary add-in development across platforms. It also features best practices in design and analytical consideration, including methodical

Written with the verve of such works as The Big Short, The History of the Future, and The Spider Network, here is the fascinating, true story of the rise of Ethereum, the second-biggest digital asset in the world, the growth of cryptocurrency, and the future of the internet as we know it. Everyone has heard of Bitcoin, but few know about the second largest cryptocurrency, Ethereum, which has been heralded as the "next internet."The story of Ethereum begins with Vitalik Buterin, a supremely gifted nineteen-year-old autodidact who saw the promise of blockchain when the technology was in its earliest stages. He convinced a crack group of coders to join him in his quest to make a super-charged, global computer.The Infinite Machine introduces Vitalik's ingenious idea and unfolds Ethereum's chaotic beginnings. It then explores the brilliant innovation and reckless greed the platform-an infinitely adaptable foundation for experimentation and new applications-has unleashed and the consequences

Microeconomics is a classroom-tested resource for learning the key concepts, essential tools, and applications of microeconomics. This leading textbook enables students to recognize and analyze significant data, patterns, and trends in real markets through its integrated, student-friendly approach to the subject — providing practice problems, hands-on exercises, illustrative examples, and engaging applications that ground theory firmly in the real world. Each chapter, opening with a set of clearly defined learning goals based on the Bloom Taxonomy, features numerous Learning-by-Doing (LBD) problems, mathematical and graphical data, and varied problem sets focused on current events.Now in its sixth edition, the text offers extensive new and revised content throughout. All applications reflect current data and important new developments in the field of economics, including behavioral economics, randomized controlled trials (RCTs) in policy evaluation and design, and computational-based m

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramificatio

This text is geared toward students who have an undergraduate degree or extensive coursework in engineering or the physical sciences and who wish to develop their understanding of the essential topics of applied mathematics. The methods covered in the chapters form the core of analysis in engineering and the physical sciences. Readers will learn the solutions, techniques, and approaches that they will use as academic researchers or industrial R&D specialists. For example, they will be able to understand the fundamentals behind the various scientific software packages that are used to solve technical problems (such as the equations describing the solid mechanics of complex structures or the fluid mechanics of short-term weather prediction and long-term climate change), which is crucial to working with such codes successfully. Detailed and numerous worked problems help to ensure a clear and well-paced introduction to applied mathematics. Computational challenge problems at the end of eac

This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinic

This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinic

Graphene is one of the most intensively studied materials, and has unusual electrical, mechanical and thermal properties, which provide almost unlimited potential applications. This book provides an introduction to the electrical and transport properties of graphene and other two-dimensional nanomaterials, covering ab-initio to multiscale methods. Updated from the first edition, the authors have added chapters on other two-dimensional materials, spin-related phenomena, and an improved overview of Berry phase effects. Other topics include powerful order N electronic structure, transport calculations, and ac transport and multiscale transport methodologies. Chapters are complemented with concrete examples and case studies, questions and exercises, detailed appendices and computational codes. It is a valuable resource for graduate students and researchers working in physics, materials science or engineering who are interested in the field of graphene-based nanomaterials.

This fully revised fifth edition provides comprehensive coverage of flexible multibody system dynamics. Including an entirely new chapter on the integration of geometry, durability analysis, and design, it offers clear explanations of spatial kinematics, rigid body dynamics, and flexible body dynamics, and uniquely covers the basic formulations used by the industry for analysis, design, and performance evaluation. Included are methods for formulating dynamic equations, the floating frame of reference formulation used in small deformation analysis, and the absolute nodal coordinate formulation used in large deformation analysis, as well as coverage of industry durability investigations. Illustrated with a wealth of examples and practical applications throughout, it is the ideal text for single-semester graduate courses on multibody dynamics taken in departments of aerospace and mechanical engineering, and for researchers and practicing engineers working on a wide variety of flexible mul

Anchored in simple and familiar physics problems, the author provides a focused introduction to mathematical methods in a narrative driven and structured manner. Ordinary and partial differential equation solving, linear algebra, vector calculus, complex variables and numerical methods are all introduced and bear relevance to a wide range of physical problems. Expanded and novel applications of these methods highlight their utility in less familiar areas, and advertise those areas that will become more important as students continue. This highlights both the utility of each method in progressing with problems of increasing complexity while also allowing students to see how a simplified problem becomes 're-complexified'. Advanced topics include nonlinear partial differential equations, and relativistic and quantum mechanical variants of problems like the harmonic oscillator. Physics, mathematics and engineering students will find 300 problems treated in a sophisticated manner. The insig

Bringing together contributions on a diverse range of topics, this text explores the relationship between discrete and continuum mechanics as a tool to model new and complex metamaterials. Providing a comprehensive bibliography and historical review of the field, it covers mechanical, acoustic and pantographic metamaterials, discusses Naive Model Theory and Lagrangian discrete models, and their applications, and presents methods for pantographic structures and variational methods for multidisciplinary modeling and computation. The relationship between discrete and continuous models is discussed from both mathematical and engineering viewpoints, making the text ideal for those interested in the foundation of mechanics and computational applications, and innovative viewpoints on the use of discrete systems to model metamaterials are presented for those who want to go deeper into the field. An ideal text for graduate students and researchers interested in continuum approaches to the study

The finite element method (FEM) is indispensable in modeling and simulation in various engineering and physical systems, including structural analysis, stress, strain, fluid mechanics, heat transfer, dynamics, eigenproblems, design optimization, sound propagation, electromagnetics, and coupled field problems. This textbook integrates basic theory with real-life, design-oriented problems using ANSYS, the most commonly used computational software in the field. For students as well as practicing engineers and designers, each chapter is highly illustrated and presented in a step-by-step manner. Fundamental concepts are presented in detail with reference to easy to understand worked examples that clearly introduce the method before progressing to more advanced content. Included are step-by-step solutions for project type problems using modelling software, special chapters for modelling and the use of ANSYS and Workbench programs, and extensive sets of problems and projects round out each ch

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.