Digital library
Textbooks, references and open learning resources.
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An Introduction to Computer Networks
Peter Dordal · Peter L Dordal · 2014
An Introduction to Computer Networksis a free and open general-purpose computer-networking textbook, complete with diagrams and exercises.It covers the LAN, internetworking and transport layers, focusing primarily on TCP/IP. Particular attention is paid to congestion; other special topics include queuing, real-time traffic, network management, security and the ns simulator. The book is suitable as the primary text for an undergraduate or introductory graduate course in computer networking, as a supplemental text for a wide variety of network-related courses, and as a reference work.
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Computer Networking : Principles, Protocols and Practice
Olivier Bonaventure · Saylor Foundation · 2011
This open textbook aims to fill the gap between the open-source implementations and the open-source network specifications by providing a detailed but pedagogical description of the key principles that guide the operation of the Internet.
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Graphic Design and Print Production Fundamentals
Wayne Collins; Alex Haas; Ken Jeffery; Alan Martin · BCcampus · 2015
This textbook -- written by a group of select experts with a focus on different aspects of the design process, from creation to production -- addresses the many steps of creating and then producing physical, printed, or other imaged products that people interact with on a daily basis. It covers the concept that, while most modern graphic design is created on computers using design software, the ideas and concepts don't stay on the computer. The ideas need to be completed in the computer software, then progress to an imaging (traditionally referred to as printing) process. Keywords are highlighted throughout and summarized in a Glossary at the end of the book, and each chapter includes exercises and suggested readings.
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Python for Everybody: Exploring Data Using Python 3
Charles Severance · Charles Severance · 2016
I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning. Chapters 2–10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word “recursion”1 does not appear in the book at all. In chapters 1 and 11–16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data. The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one choose
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Signal Computing: Digital Signals in the Software Domain
Michael Stiber; Bilin Stiber; Eric Larson · Michael Stiber, Eric Larson · 2020
In this book, you will learn how digital signals are captured, represented, processed, communicated, and stored in computers. The specific topics we will cover include: physical properties of the source information (such as sound or images), devices for information capture (microphones, cameras), digitization, compression, digital signal representation (JPEG, MPEG), digital signal processing (DSP), signal analysis and feature extraction via re-representation as functions of frequency, and network communication. By the end of this book, you should understand the problems and solutions facing signal computing systems development in the areas of data structures and algorithms, data analytics, feature extraction, information retrieval, user interfaces, and communications.
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Introduction to Autonomous Robots
Nikolaus Correll · Nikolaus Correll · 2016
This book introduces concepts in mobile, autonomous robotics to 3rd-4th year students in Computer Science or a related discipline. The book covers principles of robot motion, forward and inverse kinematics of robotic arms and simple wheeled platforms, perception, error propagation, localization and simultaneous localization and mapping. The cover picture shows a wind-up toy that is smart enough to not fall off a table just using intelligent mechanism design and illustrate the importance of the mechanism in designing intelligent, autonomous systems. This book is open source, open to contributions, and released under a creative common license.
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Deep into Pharo
Alexandre Bergel; Damien Cassou; Stéphane Ducasse; Jannik Laval · Square Bracket Associates · 2013
Pharo is a clean, innovative, open-source, live-programming environment. Deep into Pharois the second volume of a series of books covering Pharo. Whereas the first volume is intended for newcomers, this second volume covers deeper topics.You will learn about Pharo frameworks and libraries such as Glamour, PetitParser, Roassal, FileSystem, Regex, and Socket. You will explore the language with chapters on exceptions, blocks, small integers, and floats. You will discover tools such as profilers, Metacello and Gofer.
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Pharo by Example 5.0
Stéphane Ducasse; Dmitri Zagidulin; Nicolai Hess; Dimitris Chloupis · Stéphane Ducasse · 2016
Pharo is an open-source, elegant and pure object-oriented language that supports truly immersive and life programming experience. Pharo offers excellent tools such as hot-debuggers and on the fly code update that change the programming experience. More at http://www.pharo.org.Pharo is a powerful language and IDE that companies use to deliver complex business-effective applications. More at: http://www.pharo.org/success In Pharo everything is an object, and anything can change at run-time under your fingers. Pharo is written in itself you can explore a complete world. You can feel and talk to objects. But Pharo does not stop there, with Pharo you can improve your object-oriented skills by rediscovering the essence of object-oriented programming. Pharo by Example 50, intended for both students and developers, will guide you gently through the Pharo language and environment by means of a series of examples and exercises. This book is available under the Creative Commons Attribution-ShareAlike 3.0 license.
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Squeak by Example
Andrew Black; Stéphane Ducasse; Oscar Nierstrasz; Damien Pollet · University of Bern · 2009
Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time. Squeak by Example, intended for both students and developers, will guide you gently through the Squeak language and environment by means of a series of examples and exercises. The book helps you get started with A Quick Tour of Squeak and guides you through A First Application. The Smalltalk language is introduced in three chapters on Syntax in a Nutshell, Understanding Message Syntax and The Smalltalk Object Model. Development with Squeak is covered in The Squeak Programming Environment and SUnit. Several of the key classes are presented in chapters on Basic Classes, Collections, Streams and Morphic. The first edition of the book concludes with chapters on Classes and Metaclasses and Frequently Asked Questions.
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Think DSP: Digital Signal Processing in Python
Allen Downey · Green Tea Press · 2012
Think DSP is an introduction to Digital Signal Processing in Python. The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. The author is writing this book because he thinks the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the material bottom-up, starting with mathematical abstractions like phasors.
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Think Complexity: Exploring Complexity Science with Python
Allen Downey · Green Tea Press · 2018
Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you're an intermediate-level Python programmer or a student of computational modeling, you'll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
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Think Bayes: Bayesian Statistics Made Simple
Allen Downey · Green Tea Press · 2012
Think Bayes is an introduction to Bayesian statistics using computational methods. The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics. Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops. I think this presentation is easier to understand, at least for people with programming skills. It is also more general, because when we make modeling decisions, we can choose the most appropriate model without worrying too much about whether the model lends itself to conventional analysis. Also, it provides a smooth development path from simple examples to real-world problems.
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Think Stats: Probability and Statistics for Programmers
Allen Downey · Green Tea Press · 2014
Think Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
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Think Java: How To Think Like a Computer Scientist
Chris Mayfield; Allen Downey · Green Tea Press · 2020
Think Java is a hands-on introduction to computer science and programming used by many universities and high schools around the world. Its conciseness, emphasis on vocabulary, and informal tone make it particularly appealing for readers with little or no experience. The book starts with the most basic programming concepts and gradually works its way to advanced object-oriented techniques. In this fully updated and expanded edition, authors Allen Downey and Chris Mayfield introduce programming as a means for solving interesting problems. Each chapter presents material for one week of a college course and includes exercises to help you practice what you’ve learned. Along the way, you’ll see nearly every topic required for the AP Computer Science A exam and Java SE Programmer I certification.
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Fast Fourier Transforms
C. Sidney Burrus · OpenStax CNX · 2012
This book focuses on the discrete Fourier transform (DFT), discrete convolution, and, particularly, the fast algorithms to calculate them. These topics have been at the center of digital signal processing since its beginning, and new results in hardware, theory and applications continue to keep them important and exciting. This book uses an index map, a polynomial decomposition, an operator factorization, and a conversion to a filter to develop a very general and efficient description of fast algorithms to calculate the discrete Fourier transform (DFT). The work of Winograd is outlined, chapters by Selesnick, Pueschel, and Johnson are included, and computer programs are provided.
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Spatial Thinking in Planning Practice: An Introduction to GIS
Yiping Fang; Vivek Shandas; Eugenio Cordero · Portland State University Library · 2014
The goals of this textbook are to help students acquire the technical skills of using software and managing a database, and develop research skills of collecting data, analyzing information and presenting results. We emphasize that the need to investigate the potential and practicality of GIS technologies in a typical planning setting and evaluate its possible applications. GIS may not be necessary (or useful) for every planning application, and we anticipate these readings to provide the necessary foundation for discerning its appropriate use. Therefore, this textbook attempts to facilitate spatial thinking focusing more on open-ended planning questions, which require judgment and exploration, while developing the analytical capacity for understanding a variety of local and regional planning challenges. While this textbook provides the background for understanding the concepts in GIS as applicable to urban and regional planning, it is best when accompanied by a hands-on tutorial, which will enable readers to develop an in-depth understanding of the specific planning applications of GIS. In the end of each chapter, we also provided several discussion questions, together with contextual applications through some web links.
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Introduction to the Modeling and Analysis of Complex Systems
Hiroki Sayama · Open SUNY · 2015
Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs. Python sample codes are provided for each modeling example.
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Java, Java, Java: Object-Oriented Problem Solving
Ralph Morelli; Ralph Walde · Ralph Morelli, Ralph Walde · 2016
We have designed this third edition of Java, Java, Java to be suitable for a typical Introduction to Computer Science (CS1) course or for a slightly more advanced Java as a Second Language course. This edition retains the “objects first” approach to programming and problem solving that was characteristic of the first two editions. Throughout the text we emphasize careful coverage of Java language features, introductory programming concepts, and object-oriented design principles. The third edition retains many of the features of the first two editions, including: Early Introduction of Objects Emphasis on Object Oriented Design (OOD) Unified Modeling Language (UML) Diagrams Self-study Exercises with Answers Programming, Debugging, and Design Tips. From the Java Library Sections Object-Oriented Design Sections End-of-Chapter Exercises Companion Web Site, with Power Points and other Resources The In the Laboratory sections from the first two editions have been moved onto the book's Companion Web Site. Table 1 shows the Table of Contents for the third edition.
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The Missing Link: An Introduction to Web Development and Programming
Michael Mendez · Open SUNY · 2014
Web development is an evolving amalgamation of languages that work in concert to receive, modify, and deliver information between parties using the Internet as a mechanism of delivery. While it is easy to describe conceptually, implementation is accompanied by an overwhelming variety of languages, platforms, templates, frameworks, guidelines, and standards. Navigating a project from concept to completion often requires more than mastery of one or two complementing languages, meaning today's developers need both breadth, and depth, of knowledge to be effective. This text provides the developer with an understanding of the various elements of web development by focusing on the concepts and fundamentals through the examples within, providing a foundation that allows easier transition to other languages and a better understanding of how to approach their work. The reader will be introduced to topics in a manner that follows most project development methods, from initial conceptualization and design through front end development, back end development, and introducing additional concepts like accessibility and security, while focusing on responsive design techniques. Each section of the text includes opportunities to practice the material and assess increased knowledge after examining the topics.
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Open Data Structures: An Introduction
Pat Morin · Athabasca University Press · 2013
Offered as an introduction to the field of data structures and algorithms, Open Data Structures covers the implementation and analysis of data structures for sequences (lists), queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs. Focusing on a mathematically rigorous approach that is fast, practical, and efficient, Morin clearly and briskly presents instruction along with source code. Analyzed and implemented in Java, the data structures presented in the book include stacks, queues, deques, and lists implemented as arrays and linked-lists; space-efficient implementations of lists; skip lists; hash tables and hash codes; binary search trees including treaps, scapegoat trees, and red-black trees; integer searching structures including binary tries, x-fast tries, and y-fast tries; heaps, including implicit binary heaps and randomized meldable heaps; graphs, including adjacency matrix and adjacency list representations; and B-trees. A modern treatment of an essential computer science topic, Open Data Structures is a measured balance between classical topics and state-of-the art structures that will serve the needs of all undergraduate students or self-directed learners.