I get HRV and HR from the health kit for my app but I recently ran into a case where there was HRV but no HR data for a given time span, which doesn't really make sense since HRV is calculated from the same data as HR. Does anyone know what going on?
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i am new to carla and have one question regarding the statement (below mentioned) in carla docu:
how to understand the simulation time and time step mentioned in the statement? Is this same as rendering frame?
"There is a difference between real time, and simulation time. The simulated world has its own clock and time, conducted by the server. Computing two simulation steps takes some real time. However, there is also the time span that went by between those two simulation moments, the time-step."
Thank you for your help!
So you might set a simulation time of 5 seconds to model something - like how far the ripples progress in water when a stone hits the surface.
But the computer/processor may take 5 minutes to complete all the calculations to provide that solution.
how to decide how in advance my prediction is?
i am following the featuretools churn tutorial https://github.com/Featuretools/predict-customer-churn
what i don't quite understand how did it decide that the prediction is for one month in advance.. in previous churn examples i tried, i just get aggregated data ( it could be historical for a years or months) then i build churn model and predict but i don't know if my prediction is for a month a year or even how many days in advance how is that decided!.
does it depend on the period of aggregation or the data i didn't use. i know cut off time is the time i want to make prediction but how do i tell the system i want to make prediction for 2 month in advance do i just disregard the data for the last two months by setting the cut_off time but provide the label after the two months and say my model based on the features i get is for a 2 month advanced prediction.
for ex. cut_off date is 1/8/2010 label is the customer state on 1/10/2010
so two months period is the advance prediction? and i used all historical data previous to cut_off time?
this might be a time series problem that is turned into a simple classification but i am not sure!
You pick the amount of time in advanced (called "lead time") using your domain expertise. Depending on the real world application the lead time might be more or less. Sometimes you might even build multiple models with different lead times to apply in different situations.
You control the lead time by moving the cutoff earlier with respect to the time the label became known. So, the example you give looks correct.
I am trying to validate a district heating model I built using Dymola.
In this case, I am trying to find the mass flow during a year period. I have two models running. both with the same loads and pipes with same characteristics as this picture:
pipes
Both models are as follows:
models
My results are making sense at least regarding the time of the year my flow should be higher, I am getting very high values during January, February and March, then again by the end of the year.
However those high peaks are VERY different, the first model on the picture is giving me peaks of almost 400kg/s whereas the second one is reaching up to 70kg/s.
Can anyone suggest a way to validate the model? I have the heat loads for the year hour by hour (this is the input I am giving to Dymola), I know that the min temperature of the water is 70 and the max is 85 celsius.
But I am really struggling to validate my model. Any suggestions?
We are using Grafana to visualise some times measured with an other application. I get a data point every 5 min.
I also get a nice graph if I only visualise the last 24 or 48h.
for longer time ranges no graph is shown.
I researched a little and found that in the database there are data points each minute. which means I only get one value and 4 time NULL every 5 minutes. For a time range bigger 48h grafana starts to cumulate the values it ends up with only NULL values.
Here are two pictures which show my problem:
Timerange 24h
Timerange 7 days
Are there some settings I can make to avoid this behaviour?
Thank you for your help
Are you using graphite? If so, please make sure you configured xFilesFactor correctly.
We're keeping our backend servers in sync using NTP but are not sure how synchronized are the time stamps retrieved on the fronted (using NSDate). Can you please comment if you have experience with this issue?
In my experience, although often it can be fairly close, from time to time it can be inaccurate by several seconds, and the offset vary even over several hours.
Also, the tower time it syncs to can be off, I've seen 15 seconds, 60 seconds (for months), and once : 1 hour when daylight savings was applied when it shouldn't have been. Once it isn't syncing to the tower it can drift 10s of seconds per day, and worse when "off".