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e-book
"A Brief Introduction to Engineering Computation with MATLAB is specifically designed for students with no programming experience. However, students are expected to be proficient in First Year Mathematics and Sciences and access to good reference books are highly recommended. Students are assumed to have a working knowledge of the Mac OS X or Microsoft Windows operating systems. The strategic goal of the course and book is to provide learners with an appreciation for the role computation plays in solving engineering problems. MATLAB specific skills that students are expected to be proficient at are: write scripts to solve engineering problems including interpolation, numerical integration and regression analysis, plot graphs to visualize, analyze and present numerical data, and publish reports."--BC Campus website.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mechanical Engineering
- Keywords:
- Systems engineering Textbooks
- Resource Type:
- e-book
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e-book
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.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Textbooks Data structures (Computer science) Computer algorithms
- Resource Type:
- e-book
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e-book
This grammar provides the first comprehensive grammatical description of Yakkha, a Sino-Tibetan language of the Kiranti branch. Yakkha is spoken by about 14,000 speakers in eastern Nepal, in the Sankhuwa Sabha and Dhankuta districts. The grammar is based on original fieldwork in the Yakkha community. Its primary source of data is a corpus of 13,000 clauses from narratives and naturally-occurring social interaction which the author recorded and transcribed between 2009 and 2012. Corpus analyses were complemented by targeted elicitation. The grammar is written in a functional-typological framework. It focusses on morphosyntactic and semantic issues, as these present highly complex and comparatively under-researched fields in Kiranti languages. The sequence of the chapters follows the well-established order of phonological, morphological, syntactic and discourse-structural descriptions. These are supplemented by a historical and sociolinguistic introduction as well as an analysis of the complex kinship terminology. Topics such as verbal person marking, argument structure, transitivity, complex predication, grammatical relations, clause linkage, nominalization, and the topography-based orientation system have received in-depth treatment. Wherever possible, the structures found were explained in a historical-comparative perspective in order to shed more light on how their particular properties have emerged.
- Subjects:
- Foreign Language Learning
- Keywords:
- Language languages -- Grammars Yakha language Kiranti languages Textbooks
- Resource Type:
- e-book
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e-book
The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses. The first part of the book introduces the scientific method, then covers research design, measurement, descriptive statistics, probability, inference, and basic measures of association. The second part of the book covers bivariate and multiple linear regression using the ordinary least squares, the calculus and matrix algebra that are necessary for understanding bivariate and multiple linear regression, the assumptions that underlie these methods, and then provides a short introduction to generalized linear models.The book fully embraces the open access and open source philosophies. The book is freely available in the SHAREOK repository; it is written in R Markdown files that are available in a public GitHub repository; it uses and teaches R and RStudio for data analysis, visualization and data management; and it uses publically available survey data (from the Meso-Scale Integrated Socio-geographic Network) to illustrate important concepts and methods. We encourage students to download the data, replicate the examples, and explore further! We also encourage instructors to download the R Markdown files and modify the text for use in different courses.
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e-book
This is a complete college textbook, including a detailed Table of Contents, seventeen Chapters (each with a set of relevant homework problems), a list of References, two Appendices, and a detailed Index. The book is intended to enable students to: Solve first-, second-, and higher-order, linear, time-invariant (LTI) ordinary differential equations (ODEs) with initial conditions and excitation, using both time-domain and Laplace-transform methods; Solve for the frequency response of an LTI system to periodic sinusoidal excitation and plot this response in standard form; Explain the role of the time constant in the response of a first-order LTI system, and the roles of natural frequency, damping ratio, and resonance in the response of a second-order LTI system; Derive and analyze mathematical models (ODEs) of low-order mechanical systems, both translational and rotational, that are composed of inertial elements, spring elements, and damping devices; Derive and analyze mathematical models (ODEs) of low-order electrical circuits composed of resistors, capacitors, inductors, and operational amplifiers; Derive (from ODEs) and manipulate Laplace transfer functions and block diagrams representing output-to-input relationships of discrete elements and of systems; Define and evaluate stability for an LTI system; Explain proportional, integral, and derivative types of feedback control for single-input, single-output (SISO), LTI systems; Sketch the locus of characteristic values, as a control parameter varies, for a feedback-controlled SISO, LTI system; Use MATLAB as a tool to study the time and frequency responses of LTI systems. The book's general organization is: Chapters 1-10 deal primarily with the ODEs and behaviors of first-order and second-order dynamic systems; Chapters 11 and 12 discuss the ODEs and behaviors of mechanical systems having two degrees of freedom, i.e., fourth-order systems; Chapters 13 and 14 introduce classical feedback control; Chapter 15 presents the basic features of proportional, integral, and derivative types of classical control; Chapters 16 and 17 discuss methods for analyzing the stability of classical control systems. The general minimum prerequisite for understanding this book is the intellectual maturity of a junior-level (third-year) college student in an accredited four-year engineering curriculum. A mathematical second-order system is represented in this book primarily by a single second-order ODE, not in the state-space form by a pair of coupled first-order ODEs. Similarly, a two-degrees-of-freedom (fourth-order) system is represented by two coupled second-order ODEs, not in the state-space form by four coupled first-order ODEs. The book does not use bond graph modeling, the general and powerful, but complicated, modern tool for analysis of complex, multidisciplinary dynamic systems. The homework problems at the ends of chapters are very important to the learning objectives, so the author attempted to compose problems of practical interest and to make the problem statements as clear, correct, and unambiguous as possible. A major focus of the book is computer calculation of system characteristics and responses and graphical display of results, with use of basic (not advanced) MATLAB commands and programs. The book includes many examples and homework problems relevant to aerospace engineering, among which are rolling dynamics of flight vehicles, spacecraft actuators, aerospace motion sensors, and aeroelasticity. There are also several examples and homework problems illustrating and validating theory by using measured data to identify first- and second-order system dynamic characteristics based on mathematical models (e.g., time constants and natural frequencies), and system basic properties (e.g., mass, stiffness, and damping). Applications of real and simulated experimental data appear in many homework problems. The book contains somewhat more material than can be covered during a single standard college semester, so an instructor who wishes to use this as a one-semester course textbook should not attempt to cover the entire book, but instead should cover only those parts that are most relevant to the course objectives.
- Keywords:
- Differential equations Engineering mathematics Differential equations Partial Textbooks
- Resource Type:
- e-book
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e-book
A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Textbooks Computer science Artificial intelligence Data mining
- Resource Type:
- e-book
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e-book
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the “natural environment” of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful “pipe” operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
- Subjects:
- Biology
- Keywords:
- Computational biology Textbooks
- Resource Type:
- e-book
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e-book
Principles of Microeconomics is an adaptation of the textbook, Microeconomics: Markets, Methods, and Models by D. Curtis and I. Irvine, which provides concise yet complete coverage of introductory microeconomic theory, application and policy in a Canadian and global environment. This adaptation employs methods that use equations sparingly and do not utilize calculus. The key issues in most chapters are analyzed by introducing a numerical example or case study at the outset. Students are introduced immediately to the practice of taking a data set, examining it numerically, plotting it, and again analyzing the material in that form. The end-of-chapter problems involve numerical and graphical analysis, and a small number of problems in each chapter involve solving simple linear equations (intersecting straight lines). However, a sufficient number of questions is provided for the student to test understanding of the material without working through that subset of questions. This textbook is intended for a one-semester course, and can be used in a two-semester sequence with the companion textbook, Principles of Macroeconomics. The three introductory chapters are common to both textbooks.
- Subjects:
- Economics
- Keywords:
- Microeconomics Textbooks
- Resource Type:
- e-book
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e-book
Introduction to Financial Mathematics: Concepts and Computational Methods serves as a primer in financial mathematics with a focus on conceptual understanding of models and problem solving. It includes the mathematical background needed for risk management, such as probability theory, optimization, and the like. The goal of the book is to expose the reader to a wide range of basic problems, some of which emphasize analytic ability, some requiring programming techniques and others focusing on statistical data analysis. In addition, it covers some areas which are outside the scope of mainstream financial mathematics textbooks. For example, it presents marginal account setting by the CCP and systemic risk, and a brief overview of the model risk. Inline exercises and examples are included to help students prepare for exams on this book.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Business mathematics
- Resource Type:
- e-book
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e-book
This laboratory manual is intended for use in a biology laboratory course taken by non-science majors, pre-biology, and pre-allied health majors. Laboratory exercises provide students with experience in basic laboratory skills, gathering and organizing data, measuring and calculating, hypothesis testing, analysis of data, writing, and laboratory safety. The skill sets are designed to promote the development of critical thought and analysis. Students work with living and preserved specimens, and laboratory reagents and equipment.
- Subjects:
- Laboratory Techniques and Safety and Biology
- Keywords:
- Laboratory manuals Textbooks Biology
- Resource Type:
- e-book