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A Person-Centered Guide to Demystifying Technology: Working together to observe, question, design, prototype, and implement/reject technology in support of people's valued beings and doings

Martin Wolske · University of Illinois Library - Urbana · 2023

Digital technologies old and new are not objects that can be packed inside a box. They are a seamless, indivisible combination of people, organizations, policies, economies, histories, cultures, knowledge, and material things that are continuously shaped and reshaped. Every one of us innovates-in-use our everyday technologies; we just do not always know it. We are shaped by the networked information tools in our midst, and we shape them and thereby shape others. While many of the chapters in this book can be approached as standalone explorations, as many around the world have done, its full potential comes when collaboratively taken as a journey through twelve sessions. Each session in this second, revised edition includes two thematically linked chapters, one more socially oriented and one more technically oriented. Sessions are brought together into three larger generative themes that are built from three decades of participatory design in and with community, and from the teaching of these concepts and practices in courses and workshops. Approached within a community of practice, learning outcomes include discovering ways to advance power, both power within and power with others; advancing our technical skills, but also and even more, our progressive community engagement skills, our critical sociotechnical skills, and our cognitive, information, and social-emotional skills; and progressing our culturally competent collective leadership through social justice storytelling within a framing of reciprocity. In so doing, this textbook seeks to address the call placed by the Rev. Dr. Martin Luther King, Jr. – to rapidly shift from a ‘thing-oriented’ society to a ‘person-oriented’ society.

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The Crystal Ball Instruction Manual

Stephen Davies · University of Mary Washington · 2020

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.

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The Discipline of Organizing: 4th Professional Edition

Robert Glushko · University of California, Berkeley · 2013

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.

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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 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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Pro Git: Everything You Need to Know About Git (Ukranian)

Scott Chacon; Ben Straub · Apress · 2014

The entire Pro Git book, written by Scott Chacon and Ben Straub and published by Apress, is available here. All content is licensed under the Creative Commons Attribution Non Commercial Share Alike 3.0 license. Print versions of the book are available on Amazon.com. The version found here has been updated with corrections and additions from hundreds of contributors. If you see an error or have a suggestion, patches and issues are welcome in its GitHub repository.