0:00:07my name is in line with the department of systems and computer engineering and my
0:00:14close to talk today is about what research with sensors champion sensors in the vitamins
0:00:20in palliative care to we looked at putting
0:00:23sensors into palliative care under the bed mattress is we put twenty four types of
0:00:27sensors in order to monitor people comfortably in a way that interfere with their comfort
0:00:33and we're of the first time we have our we had this study going where
0:00:37we have been able to monitor palliative care patients at the end
0:00:39the end of like what we found from that is that we can monitor how
0:00:44much they're in bad how much the rolling in bad and getting their respiration and
0:00:49breathing signals out from that we're looking at predictors of mortality and do we know
0:00:54can we tell interest rate
0:00:55operation signals that within the next couple weeks disparity field i and can we then
0:01:00be able to make better decisions are transferring them or not based on that are
0:01:07valuable spectrum part of computer engineering university
0:01:12and this is my thesis called towards personalised towards personalise interact tones
0:01:17and basically what that means is that when you're given and individuals are sequenced genome
0:01:23so their list of genes that they have in their body
0:01:26we wanna be able to predict the effects that and individuals mutations have on the
0:01:31protein interactions
0:01:36so the current bill this system we need a lot of input data so a
0:01:41lot of individuals sequence you know the test to test our system and to build
0:01:45our system
0:01:46and as a project called d thousand genome switch five sequenced and may be available
0:01:51a bunch of anonymous individuals sequence data
0:01:54and this told about how to twenty five terabytes
0:01:58which is pretty huge amount huge amount of data is we need to operate on
0:02:02this and identify candy mutations and things would like to test again some users as
0:02:08a as a system to build our
0:02:11our own system
0:02:13hi my name is alex the as and i am a graduate student at carleton
0:02:17currently studying statistics and i do the project on analysing national hockey league play by
0:02:22play data so the national hockey league keeps track of all sorts plays like a
0:02:26one during the game displays are defined the stuff like face off
0:02:29thoughts a periods beginning and ending shots shot blocks penalties goals and all that sort
0:02:34of and stuff and i decided this to take a look at some of the
0:02:36most important events and see what kind of information i could get out of it
0:02:40so when the big one big arguments right now in the n h l is
0:02:44whether or not we can measure
0:02:45measured success based on how long they possess about so the energy really tract this
0:02:50but luckily we can track shots or in shots against and there's pretty good relationship
0:02:55that says if you team takes more shots and i have shots against them then
0:02:58they probably have the pack more often and are probably more successful
0:03:01so this is essentially what i looked at and upon the relationship in general hold
0:03:05across the we got wraps up here and in them you can see that teams
0:03:09that have a higher percentage of the time ten to ten or more points over
0:03:13the course of the year and the teams or more points tend to get the
0:03:16playoffs and win championships