Information Technology

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https://oerrepository.ntt.edu.vn/handle/298300331/491

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Đang hiển thị 1 - 20 trong tổng số 38

Making Games with Python & Pygame
(Albert Sweigart, 2012) Sweigart, Al
This book will teach you how to make graphical computer games in the Python programming language using the Pygame library.This book assumes you know a little bit about Python or programming in general. If you don’t know how to program, you can learn by downloading the free book "Invent Your Own Computer Games with Python" from http://inventwithpython.com. Or you can jump right into this book and mostly pick it up along the way. This book is for the intermediate programmer who has learned what variables and loops are, but now wants to know, "What do actual game programs look like?" There was a long gap after I first learned programming but didn’t really know how to use that skill to make something cool. It’s my hope that the games in this book will give you enough ideas about how programs work to provide a foundation to implement your own games.
Open Data Structures: An Introduction
(Athabasca University Press, 2013) Morin, Pat
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.
The Discipline of Organizing: 4th Professional Edition
(University of California, Berkeley, 2013) Glushko, Robert J.
We organize things, we organize information, we organize information about things, and we organize information about information. But even though “organizing” is a fundamental and ubiquitous challenge, when we compare these activities their contrasts are more apparent than their commonalities. We propose to unify many perspectives about organizing with the concept of an Organizing System, defined as an intentionally arranged collection of resources and the interactions they support. Every Organizing System involves a collection of resources, a choice of properties or principles used to describe and arrange resources, and ways of supporting interactions with resources. By comparing and contrasting how these activities take place in different contexts and domains, we can identify patterns of organizing. We can create a discipline of organizing in a disciplined way. The 4th edition builds a bridge between organizing and data science. It reframes descriptive statistics as organizing techniques, expands the treatment of classification to include computational methods, and incorporates many new examples of data-driven resource selection, organization, maintenance, and personalization. It introduces a new “data science” category of discipline-specific content, both in the chapter text and in endnotes, marked with [DS] in editions that contain endnotes.
Database Design - 2nd Edition
(BCcampus, 2014) Watt, Adrienne
This second edition of Database Design book covers the concepts used in database systems and the database design process. Topics include: The history of databases Characteristics and benefits of databases Data models Data modelling Classification of database management systems Integrity rules and constraints Functional dependencies Normalization Database development process New to this edition are more examples, highlighted and defined key terms, both throughout and at the end of each chapter, and end-of-chapter review exercises. Two new chapters have been added on SQL, along with appendices that include a data model example, sample ERD exercises and SQL lab with solutions.
Linear Regression Using R: An Introduction to Data Modeling
(University of Minnesota Libraries Publishing, 2016) Lilja, David J.
Linear Regression Using R: An Introduction to Data Modeling presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models. Key modeling and programming concepts are intuitively described using the R programming language. All of the necessary resources are freely available online.
Discrete Mathematics: An Open Introduction
(2016) Levin, Oscar
The text began as a set of lecture notes for the discrete mathematics course at the University of Northern Colorado. This course serves both as an introduction to topics in discrete math and as the "introduction to proofs" course for math majors. The course is usually taught with a large amount of student inquiry, and this text is written to help facilitate this. Four main topics are covered: counting, sequences, logic, and graph theory. Along the way, proofs are introduced, including proofs by contradiction, proofs by induction, and combinatorial proofs. An introductory chapter covering mathematical statements, sets, and functions helps students gain familiarity with the language of mathematics, and two additional topics (generating functions and number theory) are also included. While the book began as a set of lecture notes, it now contains a number of features that should support its use as a primary textbook: 473 exercises, including 275 with solutions and another 109 with hints. Exercises range from easy to quite involved, with many problems suitable for homework. Investigate! activities throughout the text to support active, inquiry based learning. A full index and list of symbols. Consistent and helpful page layout and formatting (i.e., examples are easy to identify, important definitions and theorems in boxes, etc.).
Think Java: How to Think Like a Computer Scientist
(O'Reilly, 2016) Mayfield, Chris; Downey, Allen
Think Java is an introduction to computer science and programming intended for people with little or no experience. The authors provide a well thought out, logical progression of concepts, from the most basic to recursion and object-oriented programming. All terms are defined when they are first used.
Python for Everybody: Exploring Data Using Python 3
(Charles Severance, 2016) Severance, Charles
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 chooses not to become a professional programmer.
A Tale of Two Systems
(Oregon State University, 2017) Reitsma, René; Krueger, Kevin
This is the story of a web-based information system rebuild. The system in question is www.teachengineering.org, a digital library of K-12 engineering curriculum that was built from the ground up with established technology and which for 13 years enjoyed lasting support from its growing user community and its sponsors. These 13 years, however, cover the period during which smart phones and tablets became commonplace, during which the Internet of Things started replacing the Semantic Web, during which NoSQL databases made their way out of the research labs and into everyday development shops, during which we collectively started moving IT functions and services into ‘the cloud,’ and during which computing performance doubled a few times, yet again. During this same period, TeachEngineering’s user base grew from a few hundred to more than 3 million users annually, its collection size quadrupled, it went through several user interface renewals, and significant functionality was added while having an exemplary service record, and it enjoyed continued financial support from its sponsors. In this monograph we provide a side-by-side of this rebuild. We lay out the choices made in the old architecture —we refer to it as TE 1.0— and compare and contrast them with the choices made for TE 2.0. We explain why both the 1.0 and 2.0 choices were made and discuss the advantages and disadvantages associated with them.
Foundations of Trusted Autonomy
(SpringerLink, 2018) Abbass, Hussein A.; Scholz, Jason; Reid, Darryn J.
This book is open access under a CC BY 4.0 license. This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cybersecurity, defence and space.
Foundations of Software Science and Computation Structures
(SpringerLink, 2018) Baier, Christel; Lago, Ugo Dal
This book constitutes the proceedings of the 21st International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2018, which took place in Thessaloniki, Greece, in April 2018, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2018. The 31 papers presented in this volume were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections named: semantics; linearity; concurrency; lambda-calculi and types; category theory and quantum control; quantitative models; logics and equational theories; and graphs and automata.
Nanoinformatics
(SpringerOpen, 2018) Tanaka, Isao
This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.
The Crystal Ball Instruction Manual - version 1.1 Volume One: Introduction to Data Science
(University of Mary Washington, 2020) Davies, Stephen
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.
Evidence-based Software Engineering
(Knowledge Software, 2020) Jones, Derek M.
This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available. The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster. The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.
How to Think Like a Computer Scientist: Learning with Python
(Green Tea Press, 2021) Downey, Allen; Elkner, Jeff; Meyers, Chris
How to Think Like a Computer Scientist: Learning with Python is an introduction to programming using Python. Table of Contents: Chapter 1: The way of the program Chapter 2: Variables, expressions and statements Chapter 3: Functions Chapter 4: Conditionals and recursion Chapter 5: Fruitful functions Chapter 6: Iteration Chapter 7: Strings Chapter 8: Lists Chapter 9: Tuples Chapter 10: Dictionaries Chapter 11: Files and exceptions Chapter 12: Classes and objects Chapter 13: Classes and functions Chapter 14: Classes and methods Chapter 15: Sets of objects Chapter 16: Inheritance Chapter 17: Linked lists Chapter 18: Stacks Chapter 19: Queues Chapter 20: Trees Appendix A: Debugging Appendix B: Creating a new data type Appendix D: Recommendations for further reading Index
Relational Databases and Microsoft Access 365 - Version 4.0
(Ron McFadyen, 2021) McFadyen, Ron
This text is a free introductory text that introduces MS Access and relational database design. The motivation is to support an introductory database system course which, to the student, is either a service course providing an introduction to database concepts, or, as a prerequisite for more advanced study in the field.
Programming Fundamentals
(2021) Park, Hyesung
With resources and examples for Java basics such as variables, loops, and object oriented programming, this text provides a foundation in Java programming for introductory-level programming courses. Programming Fundamentals has built-in engagement and interaction including the following: Java Tutor Visualizations Video Tutorials External Resource Links Chapter Exercises
Laboratory Manual for Computer Programming with Python and Multisim
(2022) Fiore, James
This lab manual is intended for an introductory programming course for Electrical Engineering and/or Technology students at the AAS and/or BS level. It begins with an introduction to the Multisim (tm) simulation software and progresses to programming using the Python language. Most programming assignments are based on electrical applications.
Information Security
(Georgia Gwinnett College, 2022) Khokhar, Umar; Tran, Bin
The word Information is the processed data or we can say the data in an organized form. The term that we use in industry or in the corporate sector is Information System which is the collection of the people, procedures, policies, hardware and software that all work together for smooth functioning of the organization or the system. Now a day, we live in cyber era, where the computer is the foundational block of the Information System. Typically, a computer is used for the processing and storing of the information, however the technical advancement of the computational systems and especially the integration of the Artificial Intelligence (AI) have taken the applications of the computer at next level. The cloud computing, Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Block Chaining (BC) and IoTs (Internet of Things) are some of the most prominent emerging technologies. The backbone of the all of these modernized digital systems is the Internet, where the Internet is the network of interconnected computer networks
Agile Processes in Software Engineering and Extreme Programming
(SpringerLink, 2022) Baumeister, Hubert; Lichter, Horst; Riebisch, Mattias
This book is open access under a CC BY license. The volume constitutes the proceedings of the 18th International Conference on Agile Software Development, XP 2017, held in Cologne, Germany, in May 2017. The 14 full and 6 short papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: improving agile processes; agile in organization; and safety critical software. In addition, the volume contains 3 doctoral symposium papers (from 4 papers submitted).

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