In the fields of databases and transaction processing (transaction management), a schedule (or history) of a system is an abstract model to describe execution of transactions running in the system. Often it is a list of operations (actions) ordered by time, performed by a set of transactions that are executed together in the system. If the order in time between certain operations is not determined by the system, then a partial order is used. Examples of such operations are requesting a read operation, reading, writing, aborting, committing, requesting a lock, locking, etc. Not all transaction operation types should be included in a schedule, and typically only selected operation types (e.g., data access operations) are included, as needed to reason about and describe certain phenomena. Schedules and schedule properties are fundamental concepts in database concurrency control theory. (Wikipedia).
Computer Science Basics: Programming Languages
We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hop
From playlist Computer Science Basics
Computer Science Basics: Sequences, Selections, and Loops
We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hop
From playlist Computer Science Basics
Preparing for a Computer Science Degree
Let's go over a few points to help you prepare yourself for your computer science degree. Any further computer science topic videos can be found in the playlist below, or if I haven't gone over a particular topic, ask me in the comment section. I've also left some practical, interesting re
From playlist Computer Science
Computer Science Basics: Algorithms
We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hop
From playlist Computer Science Basics
2.6.5 Time versus Processors: Video
MIT 6.042J Mathematics for Computer Science, Spring 2015 View the complete course: http://ocw.mit.edu/6-042JS15 Instructor: Albert R. Meyer License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.042J Mathematics for Computer Science, Spring 2015
Welcome to part one of computer science terminology, where we take a dive into understanding some of the terms used in computer science and software development. We've started with the basics and will continue to get more complex as this series progresses. --------------------------------
From playlist Computer Science
Conquering Math as a Computer Science Student
Math is one of the most important aspects of your Computer Science Degree. Let's discuss how to get better at math, what math is related to computer science, and a few theoretical and practical examples on how to improve your math skills during college. MIT Math for CS YouTube —- https://
From playlist Computer Science
A Day in the Life of a Computer Science Student
I take you for a typical day as a computer science student. As you may guess, it isn't quite the glamorous lifestyle so it was a bit difficult to make it entertaining lol I hope you got some information at the very least! Enjoy. ----------------------------- PRODUCTS ---------------------
From playlist Computer Science
We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hop
From playlist Computer Science Basics
GRCon20 - Enabling Performance Portability of GNU Radio on Heterogeneous Systems
Presented by Seth Hitefield, Jeffrey Vetter and Seyong Lee at GNU Radio Conference 2020 https://gnuradio.org/grcon20 Future heterogeneous computing systems, such as those planned by the DSSoC program, will be extraordinarily complex in terms of processors, memory hierarchies, and intercon
From playlist GRCon 2020
Scheduling your Script using cronR | Automated Web Scraping in R Part 2
In part two of our automated web scraping in R series, we’ll set up our script to run every hour using cronR, so that text is scraped and analyzed periodically to capture changing events and commentary, or analyze trends in real time. Watch Part 1: https://tutorials.datasciencedojo.com/r-
From playlist Introduction to Web Scraping in R
How to Stay Productive & Motivated When Learning Data Science
In this video I give you 5 tips on how to stay motivated when learning data science. Data science takes a significant amount of time and effort to learn. You need to understand computer science, math, and various different platforms. I distilled these tips from a few different books that I
From playlist Learning, Productivity, and Motivation
Peter Couvares - Computing Challenges in Gravitational-Wave Data Analysis - IPAM at UCLA
Recorded 14 September 2021. Peter Couvares of the California Institute of Technology presents "Computing Challenges in Gravitational-Wave Data Analysis" at IPAM's Mathematical and Computational Challenges in the Era of Gravitational Wave Astronomy Tutorial. Abstract: * Summary of computing
From playlist Tutorials: Math & Computational Challenges in the Era of Gravitational Wave Astronomy
DSC - Tutorial on Using FutureGrid - Craig Stewart
Craig Stewart gives a Tutorial on Using FutureGrid at the Big Data for Science workshop held at the Pervasive Technology Institute, Indiana University. This event was put on by PTI's Digital Science Center July 26th - July 30th, 2010. Please view the Overview of FutureGrid with Geoffrey
From playlist Digital Science Center (DSC)
AIUK: AI in Action (Session 4)
Chaired by Researcher and One HealthTech Co-founder, Maxine Mackintosh, this session will feature lively demonstrations from the UK’s leading AI researchers showcasing their work across a range of topics. Join the audience to put your questions to the researchers live. You will hear from:
From playlist AIUK 2021
Automated Web Scraping in R using rvest
How to automatically web scrape periodically so you can analyze timely/frequently updated data. There are many blogs and tutorials that teach you how to scrape data from a bunch of web pages once and then you’re done. But one-off web scraping is not useful for many applications that requi
From playlist Introduction to Web Scraping
DSI | Diagrammatic Differential Equations in Physics Modeling and Simulation
Abstract: I’ll discuss some results from a recent paper on applying categories of diagrams for specifying multiphysics models for PDE-based simulations. We developed a graphical formalism inspired by the graphical approach to physics pioneered by the late Enzo Tonti. We will discuss the gr
From playlist DSI Virtual Seminar Series
CERIAS Security: Exploiting Opportunistic Scheduling in Cellular Data Networks 1/5
Clip 1/5 Speaker: Hao Chen · Assistant Professor · University of California, Davis Third Generation (3G) cellular networks utilize time-varying and location-dependent channel conditions to provide broadband services. They employ opportunistic scheduling to efficiently utilize spectrum un
From playlist The CERIAS Security Seminars 2008
Things New Computer Science Students Need to Know
🎥 Mentioned videos: My Regrets as a Computer Science Student: https://youtu.be/xa6me8wou_k Everything You Need to Know as a Computer Science Student: https://youtu.be/aDfqRbGk_Yk COMPUTER SCIENCE TERMINOLOGY https://youtu.be/akmQlDsU4xc COMPUTER SCIENCE TERMINOLOGY 2 https://youtu.be/PzLPC
From playlist Computer Science
Data Science with Mathematica -- Parallelism
In this video of the Data Science with Mathematica track I demonstrate several features of the parallelism framework of the Mathematica system. I start with basic theory on parallelism itself and then show it can be used very efficiently in the Mathematica system. The playlist for the Da
From playlist Data Science with Mathematica