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I have such a problem with organizing a non-automated warehouse (with forklifts). In the start of the day, there are some pallets in pallet racks in warehouse and during the day there are some specific number of lorries importing / exporting pallets to / from warehouse. And I want to minimize travel distances of forklifts during the day and (or) minimize waiting time of lorries that are processing outgoing deliveries (they are waiting for filling up their lorry with pallets).
I have suggested some quite intuitive algorithms, but they are not producing good results if I compare them to most intuitive method - putting imported pallets to the nearest free rack in warehouse. I tried to convert this problem to linear programming, but I didnt succeed - I know how to find minimized forklift paths for individual lorry, but then I dont know how to put it together because each time lorry export/import some pallets the warehouse state is changed (different pallet layout in warehouse). I also tried brute-force method for finding the best result by systematically checking every possibility, but this isnt producing results in a reasonable time...
Does anyone have some idea please (about converting the problem to linear programming)?
Some ideas.
It sounds like you may not be able to cast this problem into LP canonical form. Recall, the canonical form of a LP is
If you want to optimize the travel distance of the forklifts, then -c is a vector of costs for operating each forklift, A will be the matrix of size #lorries x #forklifts that contain the optimal distances that you are able to calculate, and the solution x will assign some fraction of the work to each forklift.
You will have to figure out the vector b based on system constraints, i.e. b[i] could be the maximum distance a forklift can drive based on its average speed.
Hopefully you can convert the real number solutions to some reasonable integer solution, otherwise you will need to use Integer Linear Programming, which is a much more difficult optimization problem.
Finally, if moving the palettes around in the warehouse changes the cost of the system, then LP will not be applicable and you will have to use some sort of state-space search (best-first, A*, or some other variant) where the state is defined by the location of the palettes, forklifts and lorries.
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So this might be a bit of a strange one, but I'm trying to find a tool that would help me visualize real time data in a form of a table rather than a graph/chart. There are a lot of tools out there like Grafana, Kibana, Tableau that kind of fit a similar purpose, but for a very different application and they're primarily made for aggregated data visualization.
I am essentially looking to build something like what a departure board is at an airport. You got flight flight AAA that landed 20 minutes ago, XXX departing in 50 minutes, once flight AAA is clear it disappears from the departure board etc. Only I want to have that real-time, as the input will be driven by actions users are performing on the shop floor on their RF guns.
I'd be connecting to a HANA database for this. I know it's definitely possible to build it using HTML5, Ajax and Websocket but before I get on the journey of building it myself I want to see if there's anything out there that somebody else has already done better.
Surely there's something there already - especially in the manufacturing/warehousing space where having real-time information on big screens is of big benefit?
Thanks,
Linas M.
Based on your description I think you might be looking for a dashboard solution.
Dashboards are used in many scenarios, especially where an overview of the past/current/expected state of a process is required.
This can be aggregated data (e.g. how long a queue is, how many tellers are occupied/available, what the throughput of your process is, etc.) or individual data (e.g. which cashier desk is open, which team player is online, etc.).
The real-time part of your question really boils down to what you define to be real-time.
Commonly, it’s something like “information delivery that is quick enough to be able to make a difference”.
So, if, for example, I have a dashboard that tells me that I will likely be short of, say, service staff tomorrow evening (based on my reservations) then to make a difference I need to know this as soon as possible (so I can call more staff for tomorrows shift). It won’t matter much if the data takes 5 or 10 minutes from the system entry to the dashboard, but when I only learn about it tomorrow afternoon, that’s too late.
Thus, if you’re after a dashboard solution, then there are in fact many tools available and you already mentioned some of them.
Others would be e.g. SAP tools like Business Objects Platform or SAP Cloud Analytics. To turn those into “real-time” all you need to do is to define how soon the data needs to be present in the dashboard and set the auto-refresh period accordingly.
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The TensorFlow home page describes its purpose as 'a software library for numerical computation'. Looking through the sample problems it looks like a problem is always formulated as follows:
Input
Model parameters
Desired output
Given some training data for 1) and 3), 2) can be computed.
I can see how this can be used to create bots, self-driving cars, image classifiers etc.
Given the broad definition of 'numerical computation', am I missing a class of other problems this can be used for? Can this be used for, say, more classical numerical computations such as the airflow around an aircraft or deformation of a structure under stress? Do you have any examples of how these classical problems would have to be formulated to fit the form above?
A nice discussion on what artificial neural networks could do, the fact that our brain is a neural network might imply that eventually an artificial neural network will be able to to the same tasks.
Some more examples of artificial neural networks used today: music creation, image based location, page rank, google voice, stock trade predictions, nasa star classifiaction, traffic management
Some fields i know of but do not have a good reference for:
optical quantum mechanics test set-up generator
medical diagnosis, reference only about safety
The Sharp LogiCook microwave oven, wiki, nasa mention
I think there are many millions of "problems" that can be solved with an ANN, deciding on the data representation (input,output) will be a challenge for some of these. some useful and useless examples i have been thinking about:
home thermostat that learns your wishes with certain weather types.
bakery production prediction
recognize go-stones on a board and map their locations
personal activity guesser and turn on appropriate device.
recognize person based on mouse movement
Given the right data and network these examples will work.
Dad has a pc controlling the heating system back home, i trained a network based on his 10years of heating data (outside temp, inside temp, humidity etc.) unfortunately i am not allowed to hook it up.
My aunt and uncle have a bakery, based on 6years of sales data i trained a network predicting how many breads and buns they should make. It showed me how important the correct inputs are. first i used the day of the year but when i switched to day of the week i saw a 15% increase in accuracy.
Currently i am working on a network that will detect a go board in a given image and map all 361 locations telling me if there is a black, white or no stone present.
Two examples that showed me how much information can be stored in a single neuron and of different ways to represent data:
Image example, neuron example (unfortunately you have to train both examples yourself so give them a little time.)
On to your example airflow around an aircraft.
I know none to nothing about airflow calculations and my try would be a really huge 3D input layer where you can "draw" an airplane and the direction and speed of the airflow.
It might work but it will require a tremendous amount of computation power, somebody knowing more about this specific topic probably knows a more abstract way of representing the data resulting in a more manageable network.
This nasa paper talks about a neural network for calculating airflow around a wing. Unfortunately i do not understand what kind of input they use, maybe it is more clear to you.
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I am not sure about an implementation. I've a multiplexer 8 input, 1 output and 3 select signal. One of these selects signal sequentialy acquires all value of a bit vector. Now I can choose 2 way.
The first way is to use another multiplexer where the input is the bit vector and the select signal is a counter log2 of the input.
The second way is to use a shift register and take the LSB bit of the vector.
What is the best solution in terms of area in a FPGA ?
Lets (for a incorrect start) assume that the FPGA only provides plain logical elements and flip-flops, and that the bit vector is N bits and holds the value while the used bit is selected, then the resources used by the two solutions are:
Shift solution:
N flip-flops for the shifting
N 2-1 muxes for flip-flop loading
Mux solution:
(N - 1) 2-1 muxes for the larger N-1 mux
log2(N) flip-flops for the counter
So this weights towards the mux solution, since the both needs almost the same number of 2-1 muxes due to the required initial loading of the N bit shift register, but the mux solution requires less flip-flops.
However, FPGAs depends heavily on LUTs which are usually based on small memory, and an additional feature is that these small memories can often be used as shift registers also. FPGAs with this feature allows LUT memory to be written directly, and then shifted, and this can be done without any 2-1 muxes for loading. So in this case the resources used for the shift solution are:
Shift solution with LUT for shifting:
? LUT for the loading and shifting
So the conclusion is that the best way to determine and achieve an optimal solution for an FPGA, is to know and utilize the feature of the specific target FPGA, and then try the implementing to be sure the synthesis tool maps the design correctly.
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I'm looking for a way to determine whether a picture is explicit (is Safe For Work ) or not.
I am currently looking for an API that is capable of doing it, but so far I didn't have any success.
One of the ideas I had was to use the google search API and provide a URL to a picture, and looking whether or not it is in the results when safeSearch is enabled, but it will fail on a picture that was added before the crawler got to it.
Alternatively, I'm looking for pointers regarding what to look for in an image to determine how SFW it is. Any suggestions regarding shapes, colors or patterns?
As promised, a SFW paper from Google researchers and a patent for your study procured from this blog entry.
One of my colleagues led the development of the porn classification technology at one of the largest web companies. I will share what he told me about the development of the filter.
The definition of what is explicit varying greatly among jurisdictions so what is considered explicit in the US might not be in other parts of the world and vice-versa. So models need to take into account the users origin.
A purely imaged based approach is almost impossible to use effectively at web scale. The feature space is very complex in terms of how humans judge what is explicit and what is not and developing appropriate feature extraction technology for images proved to be exceedingly difficult.
Some of the most predictive features are the text on pages that link to the images. These are among the easiest features to develop also.
Building labeled training sets is very difficult since classifying porn and other explicit content for 8 hours a day tends to take a toll on the labelers. Because of this the turn over is fairly high with almost no one lasting a year.
Getting a high accuracy from the classifiers is still very, very difficult. They worked on it with several PhD's and a very experienced team and still did not achieve the accuracy that you are probably looking for.
If you have a more constrained problem space you can probably achieve a higher accuracy. If you are using image features only the algorithm or model will probably not generalize well and will have a high false positive rate. Best of luck.
See papers:
Detection of Pornographic Digital Images
Jorge A. Marcial-Basilio, Gualberto Aguilar-Torres, Gabriel Sánchez-Pérez, L. Karina Toscano-
Medina, and Héctor M. Pérez-Meana
Pornography Detection Using Support Vector Machine
Yu-Chun Lin (林語君) Hung-Wei Tseng (曾宏偉) Chiou-Shann Fuh
Image-Based Pornography Detection
Rigan Ap-apid
De La Salle University, Manila, Philippines
You can also take some hints from existing implementations e.g.:
"The Porn Detection Stick uses advanced image analyzing algorithms that categorize images as potentially harmful by identifying facial features, flesh tone colors, image back grounds, body part shapes, and more."
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Background:
Some time ago, I built a system for recording and categorizing application crashes for one of our internal programs. At the time, I used a combination of frequency and aggregated lost time (the time between the program launch and the crash) for prioritizing types of crashes. It worked reasonably well.
Now, The Powers That Be want solid numbers on the cost of each type of crash being worked on. Or at least, numbers that look solid. I suppose I could use the aggregate lost time, multiplied by some plausible figure, but it seems dodgy.
Question:
Are there any established methods of calculating the real-world cost of application crashes? Or failing that, published studies speculating on such costs?
Consensus
Accuracy is impossible, but an estimate based on uptime should suffice if it is applied consistently and its limitations clearly documented. Thanks, Matt, Orion, for taking time to answer this.
The Powers That Be want solid numbers on the cost of each type of crash being worked on
I want to fly in my hot air balloon to Mars, but it doesn't mean that such a thing is possible.
Seriously, I think you have a duty to tell them that there is no way to accurately measure this. Tell them you can rank the crashes, or whatever it is that you can actually do with your data, but that's all you've got.
Something like "We can't actually work out how much it costs. We DO have this data about how long things are running for, and so on, but the only way to attach costs is to pretend that X minutes equals X dollars even though this has no basis in reality"
If you just make some bullcrap costing algorithm and DON'T push back at all, you only have yourself to blame when management turns around and uses this arbitrary made up number to do something stupid like fire staff, or decide not to fix any crashes and instead focus on leveraging their synergy with sharepoint portal internet web sharing love server 2013
Update: To clarify, I'm not saying you should only rely on stats with 100% accuracy, and just give up on everything else.
What I think is important is that you know what it is you're measuring. You're not actually measuring cost, you're measuring uptime. As such, you should be upfront about it. If you want to estimate the cost that's fine, but I believe you need to make this clear..
If I were to produce such a report, I'd call it the 'crash uptime report' and maybe have a secondary field called "Estimated cost based on $5/minute." The managers get their cost estimate, but it's clear that the actual report is based on the uptime, and cost is only an estimate, and how the estimate works.
I've not seen any studies, but a reasonable heuristic would be something like :
( Time since last application save when crash occurred + Time to restart application ) * Average hourly rate of application operator.
The estimation gets more complex if the crashes have some impact on external customers such, or might delay other things (i.e. create a bottle neck such that another person winds up sitting around waiting because some else's application crashed).
That said, your 'powers that be' may well be happy with a very rough estimate so long as it's applied consistently and they can see how it is changing over time.
There is a missing factor here .. most applications have a 'buckling' factor where crashes suddenly start "costing" a lot more because people loose confidence in the service your app is providing. Once that happens then it can be very costly to get users back to trusting and using the system.
It depends...
In terms of cost, the only thing that matters is the business impact of the crash, so it rather depends on the type of application.
For may applications, it may not be possible to determine business impact. For others, there may be meaninful measures.
Demand-based measures may be meaningful - if sales are steady then down-time for a sales app may be useful. If sales fluctuate unpredictable, then such measures are less useful.
Cost of repair may also be useful.