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Video
Two-thirds of the world may not have access to the latest smartphone, but local electronic shops are adept at fixing older tech using low-cost parts. Vinay Venkatraman explains his work in "technology crafts," through which a mobile phone, a lunchbox and a flashlight can become a digital projector for a village school, or an alarm clock and a mouse can be melded into a medical device for local triage.
- Subjects:
- Technology
- Keywords:
- Digital divide Industries Primitive Technology -- Social aspects
- Resource Type:
- Video
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Video
TED Fellow Lucy McRae is a body architect -- she imagines ways to merge biology and technology in our own bodies. In this visually stunning talk, she shows her work, from clothes that recreate the body's insides for a music video with pop-star Robyn, to a pill that, when swallowed, lets you sweat perfume.
- Subjects:
- Biomedical engineering and Biology
- Keywords:
- Synthetic biology Bioengineering
- Resource Type:
- Video
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Video
As we move through the world, we have an innate sense of how things feel -- the sensations they produce on our skin and how our bodies orient to them. Can technology leverage this? In this fun, fascinating TED-Ed lesson, learn about the field of haptics, and how it could change everything from the way we shop online to how dentists learn the telltale feel of a cavity.
- Subjects:
- Electronic and Information Engineering and Biology
- Keywords:
- Haptic devices Touch
- Resource Type:
- Video
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Video
This channel contains a complete list of physics videos, as well as hundreds of chemistry, astronomy, math, and mechanical engineering videos. The physics videos explain the fundamental concepts of physics with some easy to follow examples on how to solve physics problems. The chemistry videos cover all the basic topics of chemistry, the astronomy videos explain the wonders of Earth and our Universe, and the math videos cover many topics in algebra, trigonometry, pre-calculus, calculus and differential equations.
- Subjects:
- Chemistry, Mathematics and Statistics, Cosmology and Astronomy, Physics, Mechanical Engineering, and Electrical Engineering
- Keywords:
- Chemistry Astronomy Electrical engineering Physics Mathematics Mechanical engineering Kalman filtering
- Resource Type:
- Video
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e-book
This book deals with an introduction to the flow of compressible substances (gases). The main difference between compressible flow and almost incompressible flow is not the fact that compressibility has to be considered. Rather, the difference is in two phenomena that do not exist in incompressible flow. The first phenomenon is the very sharp discontinuity (jump) in the flow in properties. The second phenomenon is the choking of the flow. Choking is when downstream variations don't effect the flow. Though choking occurs in certain pipe flows in astronomy, there also are situations of choking in general (external) flow.
- Subjects:
- Aeronautical and Aviation Engineering and Mechanical Engineering
- Keywords:
- Fluid dynamics Gas dynamics Textbooks
- Resource Type:
- e-book
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e-book
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.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer games Python (Computer program language) Textbooks Programming languages (Electronic computers)
- Resource Type:
- e-book
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e-book
The goal of this book is to teach you to think like a computer scientist. I like the way computer scientists think because they combine some of the best features of Mathematics, Engineering, and Natural Science. Like mathematicians,computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating trade offs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions.The single most important skill for a computer scientist is problem-solving. By that I mean the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That’s why this chapter is called “The way of the program.”
- Subjects:
- Computing
- Keywords:
- Computer programming C++ (Computer program language) Programming languages (Electronic computers) Textbooks
- Resource Type:
- e-book
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e-book
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.
- Subjects:
- Electrical Engineering and Computing
- Keywords:
- Signal processing -- Digital techniques -- Data processing Python (Computer program language) Textbooks
- Resource Type:
- e-book
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e-book
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. For example, a dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, but mapping from values to keys is generally slower. An algorithm is a mechanical process for performing a computation. Designing efficient programs often involves the co-evolution of data structures and the algorithms that use them. For example, the first few chapters are about graphs, a data structure that is a good implementation of a graph---nested dictionaries---and several graph algorithms that use this data structure. Python programming: This book picks up where Think Python leaves off. I assume that you have read that book or have equivalent knowledge of Python. As always, I will try to emphasize fundmental ideas that apply to programming in many languages, but along the way you will learn some useful features that are specific to Python. Computational modeling: A model is a simplified description of a system that is useful for simulation or analysis. Computational models are designed to take advantage of cheap, fast computation. Philosophy of science: The models and results in this book raise a number of questions relevant to the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, holism and reductionism, and Bayesian epistemology. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. That's what this book is about.
- Subjects:
- Computing
- Keywords:
- Computational complexity Python (Computer program language) Textbooks
- Resource Type:
- e-book
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e-book
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.
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Bayesian statistical decision theory Python (Computer program language) Textbooks
- Resource Type:
- e-book