Effects of Climate Change on Canadian Forest Fires
This study aimed to determine the effects of climate change on forest fire trends in Canada by measuring correlations between weather conditions and the frequency and size of forest fires. Upon identifying the correlations, a model was created to understand future forest fire trends. The purpose of this study was to prevent the increasing trend of forest fires and devise solutions to reduce their damages. The data obtained from the Canadian National Fire Database underwent a linear regression and a machine learning algorithm to respectively predict and correlate weather conditions with future forest fire trends. It was concluded that temperature and wind speed experienced a positive correlation with forest fire frequency and size and precipitation experienced a negative correlation. To reduce the harmful effects of forest fires, cloud seeding can be used to create more precipitation and wind farms can be built to lower wind speed and attract lightning. However, more research and stricter policies directly targeting climate change are necessary for long term stability or decrease in forest fire trends.
Leon Chen, Curtis Chong, Emily Huang, Nathan Lo
Analysis Of Using Social Network On Higher Education
The Internet has become the broadest area in which to exchange information and communicate.Some use this function in a positive way, whilst others do so negatively. With the growth of the Internet, social networks have also grown. Social networks are used in different fields and for different proposes. They are used in higher education to enhance training and collaborative learning and exchange knowledge in an interaction environment.
This paper aims at finding the 10 best universities by measuring the use of social networks in education.Universities are selected for this experiment from the Academic Influence Ranking website for the domain of computer science overall (type A) (for more information about the selected universities please visit this link: http://pubstat.org/).
Operative Systems Midterm Project
In this paper, we measure the memory performance throughout the Phoronix test "RAMspeed SMP". We decide to test this specific benchmark because we know how important is the memory for the system performance. This document shows how much the memory performance could change if we modify some variables in the linux kernel.
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.
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.
N-gram Frequency Discounts
A short note on the motivation for n-gram frequency discounts in the context of the Katz backoff algorithm.