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Ken Dunham. Peter A. Dictionary of Computer Terms. Students' Academy. A Survival Guide. Matthew S. Digital Video Surveillance and Security. Anthony C. Lucio Di Jasio. David Watson. Implementing a Cpu using Fpga. Othman Ahmad. Zigbee Wireless Networking. Drew Gislason. Jonathan A Titus. Emgu CV Essentials. Shin Shi. Introduction to Computer Fundamentals.
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Paul Martz. PC Based Instrumentation and Control. Mike Tooley. An Informative Guide on Operating Systems.
Rafael Shelton. Internet of Things for Architects. Perry Lea. Ata Elahi.
Programming with STM Donald Norris. Video Systems in an IT Environment. Al Kovalick. Wireless Hacking: Projects for Wi-Fi Enthusiasts. Lee Barken. History of Computer Graphics.
Dan Ryan. Implementing Mobile TV. Amitabh Kumar. George Rouse. Programming FPGAs: Getting Started with Verilog. Simon Monk. Nivedita Majumdar. Photographer's Guide to the Digital Lifecycle. Ben Greisler. Raspberry Pi IoT Projects.
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Behzad Ehsani. Computer Fundamentals. Kids naturally do wonder why the sky is blue, why sunsets are more red, why heat travels along metal but not wood, and why stars twinkle.
But in introductory classes, students already use a computer without problems. They may not see enough of real computing to wonder about how it works. The teacher has to generate a problem, inculcate curiosity — be a provocateur.
We should only teach something when it solves a problem for the student. A lecture on variables and types should be motivated by a problem that the variables and types solve.
Nobody remembers things they will need in the future. Learning results when you need new knowledge to resolve the current problem, disequilibria, or conflict. There is no public data on trans workers or other gender minorities. For black workers, the picture is even worse. For example, only 2. Given decades of concern and investment to redress this imbalance, the current state of the field is alarming.
Without a doubt, those percentages do not match the distribution of gender and ethnicity in the population at large. But we already know that participation in CS does not match the population.
How do the AI distributions match the distribution of gender and ethnicity among CS researchers? A sample to compare to is the latest graduates with CS PhDs. Only 1.
From an ethnicity perspective, Google, Facebook, and Microsoft are doing surprisingly well. The AI Now Institute report is concerned about intersectionality. The issues of women are not identical across ethnicities. The other direction of intersectionality is also a concern.
AI and particularly the sub-field of machine learning is growing in importance. We know that having more diversity in the design team makes it more likely that a broader range of issues are considered in the design process. We also know that biased AI technologies are already being developed and deployed see the Algorithmic Justice League. A new Brookings Institute Report identifies many of the biases and suggests ways of avoiding them see report here. AI is one of the sub-fields of computer science where developing greater diversity is particularly important.
Come hang out with Wil and me to talk about new research ideas! You will save: Ela Kumar Number of Pages Available. Snapshot About the book. Audience of the Book: Key Features: The main features of the book are as follows: Pactice and familiarity with various possible questions 2. Covering the full length and breadth of the subject is essential for helping the aspiring individuals Table of Contents: Computer Fundamentals 2.
Digital Electronics and Microprocessor 3. C-Programming 4. Data Structure and Algorithms 5. Computer Organization 6. Parallel Processing 7. Theory of Computation 8.