I know that when anode to cathode current of thyristor drops below holding current thyristor turns off. I am actually stuck in numerical problem where i need to calculate average load current when holding current is 200mA. I will post question below and very glad if anyone could help.
Question
I want to know how to calculate the average current across load when holding current is 200mA as asked in (iv) above question.
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I'm a noob that is trying to make a good impression as I start my recent job. I am not very good at Excel, but I am trying to learn! This website has been a great resource, but I have a question.
We have a program that is like an active clock that ticks along and counts faults, rejections, product coming from an assembly line.
I would like to be able to create a graph that by the hour tells us the amounts for each so we can look at trends and set goals and stuff. My first thought was to find a macro that can take screen shots every hour, but I figure that would require manual entry for 24 times a day.
Has anyone have a better idea or know a macro I could use?
Thank you so much.
i have a booking system and i need to write a script that optimize the reservations.
When a customer book a flat, the system assigns the first flat available. The problem is that after a few reservations my "grid" become fragmented.
Grid example:
Grid example
In practice I need to minimize the white space so as I can accept the maximum number of reservations.
My question is: there are some know problem that fit my problem? I had thought to some knapsack problem variations.
I can provide more info if needed.
Thanks.
This is a scheduling problem. One very important question is: can you reassign a flat to a different number once the reservation has been made?
If the answer is yes, you will find a solution if and only if you have no day with more reservations than you have flats: simply take the first idle slot of the very first day d1, and if there is a conflict with a future reservation, reallocate the future reservation by taking the first idle slot of its very first day d2 (note that d2>d1), and your algorithm will converge because you will have a strictly increasing sequence of days where you need reallocation.
If the answer is no, we come into a tricky world where your algorithm has to guess what would be the future reservations. A good heurisic, I think, would be to score the placements. For instance, you can check how many iddle slots you leave before and after the reservation, and take the option that leaves a few empty slots as possible.
Need a little help from someone who knows a little about logistics;
I am currently working with an application known as Framework. The application is not really something that I am familiar with, but regardless I can figure out how it works. One of the tabs running in the application is for expected orders (shipping trucks). Within that, I am able to see where an outbound truck's current location is, as well as it's destination. I am trying to add functionality to the application that would allow me to see an estimated time of arrival to its current destination + the drive back to my location. This seems simple enough, but I'm trying to figure out the best way that I could calculate this. I looked into The Google Distance Matrix API, but I have no need to display a map on the application, all I want is the ETA. I am pretty inexperienced with this kind of thing, so I was hoping someone could point me in the right direction.
Thanks guys.
This may not be the best forum for this question...
It looks like Google Distance Matrix requires you to display the map. An alternative is the open source OSRM project. Natively it's a C++ engine for routing, which outputs directions and the total route information so the any map display is up to you.
There is a demo and HTTP API hosted on the project site but you will need to check if it's suitable for your usage level.
Just an idea, but depending on the size of your delivery area, and how accurate you want the estimated time, you may be able to keep it all in a database.
Let's assume your delivery area is 10 miles x 10 miles.
So that's 100 square miles. We'll use each square mile as a point.
Do a one time calculation of how long it will take to get from each
point to the rest. You can
use the Google Distance Matrix API for this since you're only doing
this once.
This will give you 10,000 records that has every point to point time.
So, if your truck is in point 25, and has to get to point 64, you do a lookup and see that it should take about 10 minutes. plus the drive from point 64 back to the warehouse (point 10) is 8 minutes. Then you'll know the truck should be back in about 18 minutes.
It's not super accurate, but it might be close enough for your needs. I would be curious if you do implement this method.
Btw, if your delivery area is 100 miles x 100 miles, then that would be 100,000,000 location points if each point is 1 square mile. If that's too much, then if you increase your point size to 2 miles x 2 miles (4 square miles), then that's about 6,000,000 records.
We're building a GIS interface to display GPS track data, e.g. imagine the raw data set from a guy wandering around a neighborhood on a bike for an hour. A set of data like this with perhaps a new point recorded every 5 seconds, will be large and displaying it in a browser or a handheld device will be challenging. Also, displaying every single point is usually not necessary since a user can't visually resolve that much data anyway.
So for performance reasons we are looking for algorithms that are good at 'reducing' data like this so that the number of points being displayed is reduced significantly but in such a way that it doesn't risk data mis-interpretation. For example, if our fictional bike rider stops for a drink, we certainly don't want to draw 100 lat/lon points in a cluster around the 7-Eleven.
We are aware of clustering, which is good for when looking at a bunch of disconnected points, however what we need is something that applies to tracks as described above. Thanks.
A more scientific and perhaps more math heavy solution is to use the Ramer-Douglas-Peucker algorithm to generalize your path. I used it when I studied for my Master of Surveying so it's a proven thing. :-)
Giving your path and the minimum angle you can tolerate in your path, it simplifies the path by reducing the number of points.
Typically the best way of doing that is:
Determine the minimum number of screen pixels you want between GPS points displayed.
Determine the distance represented by each pixel in the current zoom level.
Multiply answer 1 by answer 2 to get the minimum distance between coordinates you want to display.
starting from the first coordinate in the journey path, read each next coordinate until you've reached the required minimum distance from the current point. Repeat.
Sorry I know the question isnt as specific as it could be. I am currently working on a replenishment forecasting system for a clothing company (dont ask why it's in VBA). The module I am currently working on is distribution forecasts down to a size level. The idea is that the planners can forecast the number to sell, then can specify a ratio between the sizes.
In order to make the interface a bit nicer I was going to give them 4 options; Assess trend, manual entry, Poisson and Normal. The last two is where I am having an issue. Given a mean and SD I'd like to drop in a ratio (preferably as %s) between the different sizes. The number of the sizes can vary from 1 to ~30 so its going to need to be a calculation.
If anyone could point me towards a method I'd be etenaly greatfull - likewise if you have suggestions for a better method.
Cheers
For the sake of anyone searching this, whilst only a temporary solution I used probability mass functions to get ratios this allowed the user to modify the mean and SD and thus skew the curve as they wished. I could then use the ratios for my calculations. Poisson also worked with this method but turned out to be a slightly stupid idea in terms of choice.