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

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.
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).
An Introduction to Python Jupyter Notebooks for College Math Teachers
(2024) Isihara, Paul; Wagner, Claire; Jantsch, Peter; VanDrunen, Thomas
This book is an introduction to the use of Python Jupyter Notebooks (JNBs) for college math teachers and their students. The book is an evolving work in progress, but we hope this 1st Edition may already be quite useful to a college math teacher who is interested to use Jupyter Notebooks in their courses. Each section of the book has been written in the form of a Jupyter Notebook and can be downloaded using the download button at the top menu bar. In some cases, additional data files or image files may need to be downloaded as well. Each chapter contains a JNB lab with solutions. Experienced teachers can modify these labs and create new labs tailored to their courses. The chapters were written by different authors/authorship teams, and as such, vary in style. Each chapter essentially can be read independently of the others as long as one has the pre-requisite mathematical knowledge. Some effort has been made to standardize the chapter formats, and the index may help the reader find specific topics of interest. There is virtually no limit to what can be done with JNBs, and we hope this work serves as a useful starting point for teachers and students to enrich and enliven the study of mathematics using this tool. The JNBs used to create this book contain special markdown code which are needed to produce features such as indexing, referencing, and highlight boxes in the Jupyter Book. Some editing of a downloaded JNB may may make it more suitable for classroom use.
An Open Guide to Data Structures and Algorithms
(PALNI, 2023) Bible, Paul W.; Moser, Lucas; Scarlato, Mia M.
This textbook serves as a gentle introduction for undergraduates to theoretical concepts in data structures and algorithms in computer science while providing coverage of practical implementation (coding) issues. The field of computer science (CS) supports a multitude of essential technologies in science, engineering, and communication as a social medium. The varied and interconnected nature of computer technology permeates countless career paths making CS a popular and growing major program. Mastery of the science behind computer science relies on an understanding of the theory of algorithms and data structures. These concepts underlie the fundamental tradeoffs that dictate performance in terms of speed, memory usage, and programming complexity that separate novice programmers from professional practitioners.
Artificial Intelligence and Librarianship - 3rd Edition
(SoftOption, 2024) Frické, Martin
Courses on Artificial Intelligence (AI) and Librarianship in ALA-accredited Masters of Library and Information (MLIS) degrees are rare. We have all been surprised by ChatGPT and similar Large Language Models. Generative AI is an important new area for librarianship. It is also developing so rapidly that no one can really keep up. Those trying to produce AI courses for the MLIS degree need all the help they can get. This book is a gesture of support. It consists of about 100,000 words on the topic, with a 4-500 item bibliography. The third edition has changes and additions. These include: - A new Chapter 6 on evaluation and the future - New materials in Chapter 5 on current large language and multimodal models - Scattered revisions, corrections, and updates.
Building User Interfaces for Modern Web Applications: React Programming
(2024) Yang, Cheer-Sun
In this eTextbook, the prerequisite concepts about HTML/CSS, JavaScript, and Bootstrap/React-Bootstrap are introduced first, followed by the main React language features. Finally, the Software Engineering Principles are introduced from the design, development, to debugging and maintenance. The main objectives are threefold: (1) provide concepts about JavaScript Programming, (2) introduce the concepts of modularity, functional programming, and (3) teach the concept of reusable User Interface (UI) as the front-end of modern model-view-controller (MVC) web applications. Although learning other technologies in the React ecosystem is imminent, it is the hope that this book paves the groundwork for the future learning and growing in the field of modern UI development.
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.
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.).
Dynamic data processing: Recursive least-squares
(TU Delft Open, 2024) Teunissen, Peter J.G.
This book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters. When determining time-varying parameters from sequentially collected measurement data, one can discriminate between three types of estimation problems: filtering, prediction and smoothing. Filtering aims at the determination of current parameter values, while smoothing and prediction aim at the determination of respectively past and future parameter values. The emphasis in this book will be on recursive least-squares filtering. The theory is worked out for the important case of linear(ized) models. The measurement-update and time-update equations of recursive least-squares are discussed in detail. Models with sequentially collected data, but time-invariant parameters are treated first. In this case only the measurement-update equations apply. State-space models for dynamic systems are discussed so as to include time-varying parameters. This includes their linearization and the construction of the state transition matrix. Elements from the theory of random functions are used to describe the propagation laws for linear dynamic systems. The theory is illustrated by means of many worked out examples. They are drawn from applications such as kinematic positioning, satellite orbit determination and inertial navigation.
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.
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.
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.
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
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
Introduction to Computer Programming with Python
(Athabasca University Press, 2023) Wang, Harris
This introduction to computer programming with Python begins with some of the basics of computing and programming before diving into the fundamental elements and building blocks of computer programs in Python language. From the installation of Python, Python interactive programming, and integrated development environments to raising and handling exceptions, using compound data types to solve problems, and implement divide-and-conquer processes using functions, classes and modules, this textbook will set students up for success in programming and computing study and practice. The included exercises and projects are designed to hone students’ skills.
Introduction to Computer Science with Java Programming
(2025) Bergmann, Seth D.
This book is intended to be used for a first course in computer programming. No prior experience with programming should be necessary in order to use this book. But this book is intended to be used with a course that teaches more than computer programming; it is intended to be used with a course that teaches Computer Science. The distinction is subtle, but important. The author(s) believe that a breadth-first approach is the best way to introduce the concepts of Computer Science to students. Rather than isolate topics in courses (bits and bytes in a computer organization course; formal grammars and languages in a theory course; lists, sets, and maps in a data structures course; etc) we believe that topics should be introduced in a brief and simple manner at the starting level. Elaboration on these topics should occur in subsequent courses. This breadth-first approach allows the student to build on existing knowledge and retain a greater proportion of the material.
Introduction to Data Science Using Python
(West Chester University, 2024) Agah, Afrand
This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming. Basic programming concepts are discussed, explained, and illustrated with a Python program. Ample programming questions are provided for practice. The second part of the book utilizes machine-learning concepts and statistics to accomplish data-driven resolutions. Python programs are provided to apply scientific computing to conclude statistically driven results.
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.
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.
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.

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