Students mark on the continuum where they think their persona's cognitive styles are likely to fall.
What are your facet values when using software? What's one situation when your facet values might change? How did identifying your facet values affect your understanding of how you use software?
In this project, students will start by discussing the strengths and weaknesses of existing activity trackers and determining the variables that affect the accuracy of these trackers. Students will then conduct interviews with people who wear activity trackers or wear a tracker themselves for a week to determine the pros, cons, and accuracies of the trackers. Then, codes and algorithms will be used to determine what should count as the threshold for a step to achieve maximum tracker accuracy by using Sparkfun Inventor's Kit, Raspberry Pi, and Linux.
An overview of Adding an event listener
Learn how to add event listeners in jQuery so that your JavaScript can respond to events on the page, like when a user clicks a button or drags an image.
Adding folder resource to moodle course page. This is a step by step guide to add a folder resource to the Moodle course Page.
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This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms. It is especially designed for doctoral students interested in theoretical computer science.
This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.
The course aims at providing the fundamental tools for effective C++ programming in the context of high-performance computing. The tools include generic programming techniques, API development, and specific C++-11/14/17 constructs. Starting from a basic knowledge of C++, the attendees should be able to start using C++ language to engineer durable abstractions to develop and optimize applications. Example usage of modern C++ concepts and features are taken from scientific applications used by the HPC community, giving the attendees the opportunity to see the presented tools in action in real world cases. Exercises are provided from a GitHub repository. This material is meant to reflect the current state of the current C++ standard. As the standard changes, some aspects of this course may become outdated.This course is an integral part of the ESiWACE-2 project, and we acknowledge the partial funding from that project. The contact person is william.sawyer@cscs.ch.
This graduate-level course focuses on current research topics in computational complexity theory. Topics include: Nondeterministic, alternating, probabilistic, and parallel computation models; Boolean circuits; Complexity classes and complete sets; The polynomial-time hierarchy; Interactive proof systems; Relativization; Definitions of randomness; Pseudo-randomness and derandomizations;Interactive proof systems and probabilistically checkable proofs.
Data structures play a central role in modern computer science. You interact with data structures even more often than with algorithms (think Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course covers major results and current directions of research in data structure.
Acknowledgments
Thanks to videographers Martin Demaine and Justin Zhang.
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ISBN: 978-1-55195-451-6
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This course is a graduate introduction to natural language processing - the study of human language from a computational perspective. It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms. It also covers applications of these methods and models in syntactic parsing, information extraction, statistical machine translation, dialogue systems, and summarization. The subject qualifies as an Artificial Intelligence and Applications concentration subject.
The topics covered in this course include interactive proofs, zero-knowledge proofs, zero-knowledge proofs of knowledge, non-interactive zero-knowledge proofs, secure protocols, two-party secure computation, multiparty secure computation, and chosen-ciphertext security.
This course will cover an introduction to XML and it provides a hands-on experience of creating XML Documents using Schema, Namespaces, XSLT and XPath. It covers how to work with JQuery and implementation of AJAX using XML and JSON.
This course covers concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Substantial weekly programming assignments are an integral part of the subject.
There will be extensive programming assignments, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or some other “functional” language.
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More advice to new writers.