I was hoping for some help:
I have 200 participants, each with their own GPS file. Each GPS file has 1000s of points, one for every 15 second epoch. I have already cleaned the data through PALMS and have brought the file into arcmap. I would like to merge multiple points that share the same location and trip mode type (e.g., stationary, location number 1, see table attached). The main difference is that the merging needs to be sensitive to time (e.g., there might be 4 points at location 1 as that person visited the location on 4 separate occasions). I don't have tracking analyst, so any help would be much appreciated! The end game is that I need to create 1km anchor points based on places where the track stayed in one location for a large amount of time (e.g., a minimum of two hours, at least three times per week). Could someone suggest how I might do this?
Thanking you.
Erika
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I'm currently setting up a HMI as a Project at work. The operator will create a recipe that includes the following:
General recipe data (strings) e.g. customername, comment. - Input is not restricted
Number values (real) e.g. temperature, Moisture. - Input is restricted to min and max values
Timespans (timespan) e.g. heating time, cooling time - Input is restricted to time, min and max values
A recipe would look something like this:
memberName
Value
Unit
Comment
Customername
My Customer
-
The customer name of this recipe
Product
Flour
-
Used product for this recipe
Temperature container
45
°C
Setpoint temperature in container
Target Moisture
11
%
Target product moisture
Heating time
1h 30min
time
Total heating time
Drying time
30min
time
Total drying time
So far I have managed to load a saved recipe into a datagrid like I displayed above with the help of the infosys example:
https://infosys.beckhoff.com/english.php?content=../content/1033/te2000_tc3_hmi_engineering/53218196597888701067.html&id=
I modified the ConvertToDatagrid.js function so that it also returns the min, max, comment and unit of each memberName.
The issue with this solution is that I can't figure out how to restrict and check for valid inputs in the individual cells. You shouldn't be able to enter a number higher than than the max or lower than the min value. I'd also like to display a timespanpicker when selecting a cell which needs a time input.
I thought about just replicating a Datagrid with textboxes but I don't know how to select data from the array provided by ConvertToDatagrid.js. Another option would be to just link the symbols of the recipe to the textboxes but then I would have to always activate the recipe when selecting it which doesn't really seem that clean either.
I'd be glad if someone experienced with the recipe management could help me :)
Hi and happy new year to all Optaplanner users,
we have a requirement to plan tours. These tours contain chained and time-windowed activities (deliveries) executed by a weekly changing number of trucks.
The start time of a single tour can vary and is dependent on several conditions (i.e. the goods to be delivered must be produced, before the tour can start; only a limited number of trucks can be served at the plants gates at the same time; truck must be back before starting a new tour). Means: also the order of tours can vary and time gaps between the tours of a truck can occur.
My design plan is, to annotate TourStartTime as a second planning variable in Optaplanners VRPTW-example and to assign TourStartTime to 2-hours time grains (planning horizon is 1 week and tours normally do not start during night times; so the mentioned time grains reflect a simplified calendar for possible tour starts).
The number of available trucks (from external logistic companies) can vary from week to week. Regarding this I wanted to plan with a 'unlimited' number of trucks. But the number of trucks per logistic company, that can be actually assigned with deliveries, should be controlled by a constraint (i.e. 'trucks_to_be_used_in_parallel').
Can anybody tell me, if this is a feasable design approach, or where do I have to avoid traps (ca. 1000 deliveries/week, 40-80 trucks per day) ?
Thank you
Michael
A second planning variable is possible (and might be even the best design depending on your requirements), but it will blow up the search space and maybe even custom course grained moves might become needed to get great results.
Instead, I 'd first investigate if the Truck's TourStartTime can be made a shadow variable. For example, give all trucks a unique priority number. Then make a Truck's TourStartTime a shadow variable: the soonest time a truck can leave. If there are only 3 lanes and 4 trucks want to leave, the 3 trucks with the highest priority number leave first (so get the original TourStartTime, the 4th truck gets a later one).
How do I graphically represent a time-series where entries of this graph change over time?
For example I have a database of cities and their corresponding average temperature per day. I want a graphical representation of the ten hottest cities per day, and how they change over time. Do new cities appear on this list? Which cities drop out of this list?
Normally 6/10 of these cities will always be on the “top ten hottest” list, but sometimes a particular entry may spike up and join the top ten list. Is there a way to analyze the top ten list and compare it over time?
I’m having trouble thinking of a way to graph this because of the varying entries.
Your x-axis is day, but what's on the y-axis? Temperature? If so, you can have a different series (may be called something else depending on your charting package) for each city, and just add points to the series when it is one of the top ten for that day. This may require you to do some pre-processing on your data, in order to figure out which set of cities makes the top-ten list over your time frame.
In one of our widget implementations we have a setting for the time chart to display only top-n series, ranked by avg or last value. This was done to remove clutter by hiding too many unimportant series from the chart.
In your case why not show a bar for each period where the bar would contain top-N series for the period and a grey area for the remainder?
I have a table with 10 million records. Each record indicates one person. Each record has person_id, latitude, longitude, postal-code. I want to pick one query and tell how many other people in 10 miles radius (Distance can be calculated from Latitudes and Longitudes). Searching 10 million records and calculating distance to check if inside 10 million is not a good way. So, I will search only in neighboring postal codes(I will get it somehow). How can I search entry having specific postal code(not all 10 million records)?
Why not take lat/long and create a box extending 10 miles in all four directions first?
Then issue a query looking for people with lat/long in that box. Use a WHERE that does
x > xLess10 and x < xPlus10 and y > yLess10 and y < yPlus10
Now you have a smaller list and you can calculate the actual distance with something similar to sqrt((x1 - x2)^2 + (y1 - y2)^2) for that smaller list. But it has to work on a sphere, not a grid marked off in miles.
You can try adding a and zip in (555555, 555556, etc) to see if that runs faster or not. A precomputed list of all other zip codes with locations within 10 miles of anywhere within a zip code would be pretty easy to set up in another table.
#Randy made a comment that made me realize that this doesn't work very well for locations within 10 miles of the north and south poles. Maybe that doesn't matter because the population is pretty small up there. Or use another method of just getting everyone within a cirle around the pole and 10 miles south (or north) or the x,y location.
Also, you have to find a way to convert from lat/long to miles. The longitudinal lines get closer together the farther you are from the equator.
I'm having some trouble getting a search by zip code proximity query working. I've search and searched google but everything I find is either way too slow or I can't get working. Here's the issue:
I have a database with a table with all the US Zip Codes (~70,500 of them), and I have a table of several thousand stores (~10,000+), which includes their zip code. I need to be able to provide a zip code and return a list of the closest stores to that zip code, sorted by distance.
Can anyone point me to a good resource for this that they have used and can handle this much load, or share a query they've used that works and is fairly quick about it? It would be MUCH appreciated. Thanks!
You should build a table that has each zip code with an associated latitude and longitude. When someone enters a zip and a distance, you calculate the range of latitudes and longitudes that fall within it, and then select all the zip codes that fall within that bounding box. Then you select any stores that have zip codes within that set, and calculate their distance from the provided zip and sort by it. (Use the haversine formula for calculating the distance between points on a globe)
If speed is your main concern, you might want to precompute all the distances. Have a table that contains a store zip code column, the other zip code, and a distance column. You can restrict the other zip codes to zip codes within a certain distance (say 100 miles, or what have you) if you need to cut down on rows. If you don't restrict the links based on distance, you'll have a table with > 700 million rows, but you could certainly do fast lookups.