They are vehicles, a series of hypothetical, self-operating machines that exhibit increasingly intricate if not always successful or civilized behavior. Each of the vehicles in the series incorporates the essential features of all the earlier models and along the way they come to embody aggression, love, logic, manifestations of foresight, concept formation, creative thinking, personality, and free will. In a section of extensive biological notes, Braitenberg locates many elements of his fantasy in current brain research.

    Boundless works with subject matter experts to select the best open educational resources available on the web, review the content for quality, and create introductory, college-level textbooks designed to meet the study needs of university students.<br><br>This textbook covers:<br><br><b>Human Anatomy and Physiology Introduction</b> -- Anatomy and Physiology Overview, Life, Homeostasis, Anatomical Terms, Clinical Cases<br><br><b>General Chemistry</b> -- Matter and Energy, Element Properties: Atomic structure, Chemical Bonds, Chemical Reactions, Inorganic Compounds, Organic Compounds<br><br><b>Cellular Structure and Function</b> -- the study of cells, Cell membranes and the fluid mosaic model, Transport across membranes, How reception works in cell signaling, Nucleus and Ribosomes, Organelles, The Cytoskeleton, External cellular components, Cell division: process and importance, The cell cycle, Transcription and translation, RNA processing, Translation to a polypeptide, Transcription, Apoptosis signals an orderly cell death<br><br><b>Tissues</b> -- Epithelial Tissue, Cell Junctions, Clinical Cases, Tissue Repair, Tissue Development, Cancer, Connective Tissue, Membranes, Nervous Tissue<br><br><b>The Integumentary System</b> -- The Skin, Accessory Structures of the Skin, Functions of the Integumentary System, Wound Healing, Integumentary System Development, Skin Disorders, Imbalances, Diseases, and Clinical Cases<br><br><b>Skeletal Tissue</b> -- Cartilage, Bone Classification, Bone Formation, Bone and Calcium, Bone Development, Bone Diseases, Disorders, Imbalances, and Clinical Cases<br><br><b>The Skeletal System</b> -- Overview of the Musculoskeletal system, Divisions of the Skeletal System, The Axial Skeleton, Skull, Hyoid Bone, Vertebral Column, Thorax, Clinical Cases of the Axial Skeleton, The Appendicular Skeleton, The Pectoral (Shoulder) Girdle, Upper Limb, The Pelvic (Hip) Girdle, Lower Limb, Skeletal System Development, Clinical Cases of the Appendicular Skeleton<br><br><b>Joints</b> -- Classification of Joints, Synovial Joints, Joint Development, Clinical Cases<br><br><b>Muscle Tissue</b> -- Overview of Muscle Tissue, Skeletal Muscle, Control of Muscle Tension, Muscle Metabolism, Exercise and Skeletal Muscle Tissue, Smooth Muscle, Clinical Cases: Muscle Disorders, Development of Muscle<br><br><b>The Muscular System</b> -- Overview of the Muscular System, Head And Neck Muscles, Trunk Muscles, Muscles of the Upper Limb, Muscles of the Lower Limb, Clinical Cases and Muscular System Disorders<br><br><b>Nervous Tissue</b> -- Overview of the Nervous System, Neuroglia, Neurons, Collections of Nervous Tissue, Neurophysiology<br><br><b>Central Nervous System (CNS)</b> -- The Brain, Consciousness, Sleep, Language, and Memory, Protection of the Brain, Parts of The Brain Stem, The Cerebellum, The Diencephalon, Cerebral Cortex (or Cerebral Hemispheres), Functional Systems of the Cerebral Cortex, Development of the CNS, Brain Disorders and Clinical Cases, The Spinal Cord, Spinal Cord Anatomy, Disorders and Clinical Cases of the Spinal Cord<br><br><b>Peripheral Nervous System (PNS)</b> -- Sensation, Sensory Receptors, Somatosensory System, Nerves, Cranial Nerves, Spinal Nerves, Distribution of Spinal Nerves, Motor Activity, Motor Pathways, Reflexes, Pain, Development of the Nervous System, Disorders of Spinal Nerves and Clinical Cases<br><br><b>Autonomic Nervous System (ANS)</b> -- Autonomic Nervous System, ANS Anatomy, Physiology of ANS,

    This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

    The kernel handles all interactions between the CPU and the external world, and determines which programs will share processor time, in what order. It manages limited memory so well that hundreds of processes can share the system efficiently, and expertly organizes data transfers so that the CPU isn't kept waiting any longer than necessary for the relatively slow disks.The third edition of Understanding the Linux Kernel takes you on a guided tour of the most significant data structures, algorithms, and programming tricks used in the kernel. Probing beyond superficial features, the authors offer valuable insights to people who want to know how things really work inside their machine. Important Intel-specific features are discussed. Relevant segments of code are dissected line by line. But the book covers more than just the functioning of the code; it explains the theoretical underpinnings of why Linux does things the way it does.This edition of the book covers Version 2.6, which has seen significant changes to nearly every kernel subsystem, particularly in the areas of memory management and block devices. The book focuses on the following topics:Memory management, including file buffering, process swapping, and Direct memory Access (DMA)The Virtual Filesystem layer and the Second and Third Extended FilesystemsProcess creation and schedulingSignals, interrupts, and the essential interfaces to device driversTimingSynchronization within the kernelInterprocess Communication (IPC)Program executionUnderstanding the Linux Kernel will acquaint you with all the inner workings of Linux, but it's more than just an academic exercise. You'll learn what conditions bring out Linux's best performance, and you'll see how it meets the challenge of providing good system response during process scheduling, file access, and memory management in a wide variety of environments. This book will help you make the most of your Linux system.

    This bookpresents an introductory survey of computer science. It explores thebreadth of the subject while including enough depth to convey anhonest appreciation for the topics involved. The new edition includesreorganization of some key material for enhanced clarity (SoftwareEngineering and Artificial Intelligence chapters), new and expandedmaterial on Security and Data Abstractions, more on ethics anddifferent ethical theories in Chapter 0. Anyone interested in gaining athorough introduction to Computer Science.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    That’s why Facebook, Google, and Microsoft invented gradual static type layers for their dynamically typed JavaScript and Python code. This practical book shows you how one such type layer, TypeScript, is unique among them: it makes programming fun with its powerful static type system.If you’re a programmer with intermediate JavaScript experience, author Boris Cherny will teach you how to master the TypeScript language. You’ll understand how TypeScript can help you eliminate bugs in your code and enable you to scale your code across more engineers than you could before.In this book, you’ll: Start with the basics: Learn about TypeScript’s different types and type operators, including what they’re for and how they’re used Explore advanced topics: Understand TypeScript’s sophisticated type system, including how to safely handle errors and build asynchronous programs Dive in hands-on: Use TypeScript with your favorite frontend and backend frameworks, migrate your existing JavaScript project to TypeScript, and run your TypeScript application in production

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layerperceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.

    They bring a conceptual approach to chemistry and integrate problem-solving skills throughout, helping students transition from theory to practice. A strong emphasis on models, real-world applications, and visual learning prevails throughout the text. The Seventh Edition seamlessly integrates the strengths of the Zumdahl approach through a comprehensive and interwoven print and technology program. Enhanced Sample Exercises, online homework problems, and Classroom Response System content help instructors assess conceptual understanding and problem-solving skills, while new animations and images support visual learning. In addition, Houghton Mifflin offers implementation services through our TeamUP program to help instructors and students get the most out of the text and its supplements.

    Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.

    Developed by computer science instructors, books in the For the absolute beginner series teach the principles of programming through simple game creation. You will acquire the skills that you need for more practical Python programming applications and you will learn how these skills can be put to use in real-world scenarios. Best of all, by the time you finish this book you will be able to apply the basic principles you've learned to the next programming language you tackle.Features Fun approach to a difficult topic Readers will create games with Python as they learn the fundamentals of this programming language The CD will include games that readers can cut and paste into their own Web site The author provides challenges at the end of chapters to push readers to program on their own.

    In this unique collection, you'll learn about the processes that led to specific design decisions, including the goals they had in mind, the trade-offs they had to make, and how their experiences have left an impact on programming today. Masterminds of Programming includes individual interviews with:Adin D. Falkoff: APL Thomas E. Kurtz: BASIC Charles H. Moore: FORTH Robin Milner: ML Donald D. Chamberlin: SQL Alfred Aho, Peter Weinberger, and Brian Kernighan: AWK Charles Geschke and John Warnock: PostScript Bjarne Stroustrup: C++ Bertrand Meyer: Eiffel Brad Cox and Tom Love: Objective-C Larry Wall: Perl Simon Peyton Jones, Paul Hudak, Philip Wadler, and John Hughes: Haskell Guido van Rossum: Python Luiz Henrique de Figueiredo and Roberto Ierusalimschy: Lua James Gosling: Java Grady Booch, Ivar Jacobson, and James Rumbaugh: UML Anders Hejlsberg: Delphi inventor and lead developer of C# If you're interested in the people whose vision and hard work helped shape the computer industry, you'll find Masterminds of Programming fascinating.