LaTeX Assignment 4
This was an assignment for a college physics course. Please let me know what you think! :)
Running Realtime Scheduling Analysis
The Linux kernel controls the way tasks (or processes) are managed in the running system. The task scheduler, sometimes called process scheduler, is the part of the kernel that decides which task to run next. In this project its analyzed the behavior of scheduler by changing a default value from the runtime scheduling. The default value is 950000µs, or 0.95 seconds for the sched\_rt\_runtime\_us or scheduler realtime running variable. Meaning that 5% of the CPU time is reserved for processes that don't run under a real-time or deadline scheduling policy. This value in this file specifies how much of the "period" time can be used by all real-time and deadline scheduled processes on the system. The AIO-Stress which shows the obtained results in the different tests is an a-synchronous I/O benchmark created by SuSE which is is a German Linux distribution provider and business unit of Novell, Inc.
Why it's good that Soulstealer Vayne is so hard to get - a statistical Analysis
I analyzed the Hextech-Crafting in a Stochastic Simulation with 10 Million Players and found that you're going to make more Riot Points than you spend (in value) and thats without counting Champs. I've made some assumptions, which can be found down in the paper itself for those interested. For everyone else: If you're trying to maximize your RP-Net-Worth stack up on Hextech Chests.
WORST BRUISER EU
In this paper we try to make an improvement for the Linux kernel, by modifying kernel variables.
Daniel Contreras and Itzel Cordero
Multi-Tagging for Transition-based Dependency Parsing
This project focuses on a modification of a greedy transition based dependency parser. Typically a Part-Of-Speech (POS) tagger models a probability distribution over all the possible tags for each word in the given sentence and chooses one as its best guess. This is then pass on to the parser which uses this information to build a parse tree. The current state of the art for POS tagging is about 97% word accuracy, which seems high but results in a around 56% sentence accuracy. Small errors at the POS tagging phase can lead to large errors down the NLP pipeline and transition based parsers are particularity sensitive to these types of mistakes. A maximum entropy Markov model was trained as a POS multi-tagger passing more than its 1-best guess to the parser which was thought could make a better decision when committing to a parse for the sentence. This has been shown to give improved accuracy in other parsing approaches. We shown there is a correlation between tagging ambiguity and parsers accuracy and in fact the higher the average tags per word the higher the accuracy.
N-gram Frequency Discounts
A short note on the motivation for n-gram frequency discounts in the context of the Katz backoff algorithm.
Template Term Paper
This is a template for an empirical term paper at the university. It comes with a nice folder structure that allows a good overview of the different text parts.
It includes various options that are customizable (e.g. cover page/no cover page; including/excluding table of content, list of figures/tables) and also gives a quick introduction into the very basics of LaTeX such as highlighting, citing, writing, including tables, figures, and mathematical equations.