I am designing a delivery app, where the delivery boy has to handle more than 1 process(Going for delivery destinations), so I need to find the best route for
him from the source and round trip is not required .
Thanks in Advance
You can easily find many node-module implementations:
node-tspsolver (link)
algotithmbox (link)
genetic (link)
above options seems does not work for me for some reason. i end up using code here, it works in my cases. thanks.
https://github.com/lovasoa/salesman.js
Related
I know how to use already made haarcascades for face,eyes detection etc. But I wanted to create a haarcascade to recognize a ceiling fan(both when it is turned ON or OFF). Can anyone give me some good suggestions on how can I make such a haarcascade?Thanks in advance!
I followed this video and made Haarcascades for bikes and heavy vehicle detection and it was helpful
SentDex Making our own HaarCascades
I am looking for real world examples of DAAST tags being trafficked. Anyone know of any audio players that have adopted the new standard yet?
I'm looking at Pandora, iHeartRadio and I'm still seeing VAST tags for advertisements (4-22-2015).
http://www.iab.net/DAAST
I know it's not a great question, but please if any information let me know it's appreciated.
EDIT: Doesn't look like anyone is using DAAST yet will keep this updated. Tried: Pandora, Tunein, iheartRadio, triton, spotify, radio.com, rdio. Triton on their website says they are DAAST compliant, but no DAAST observed there.
I think this it is extremely new format.
Date of publication of official article is 22.01.2015
I can't found any implementation in real web-players in this time :(
Triton Digital did support DAAST day 1... players need to specifically request this format as the default is VAST (and remained as such for backwards compatibility). Most of the advantages of DAAST are leveraged in server-to-server interfaces.
I want to make a web app that uses a UI similar to Google Keep. I want to be able to have chips of the same size that can be dynamically added/removed that expand into larger cards with more options. What kind of layout should I use in Polymer?
Here are some quick sketches of what I want to accomplish.
There's likely a number of ways you can go, probably best you just try some things & find the approach you like. To help get started I think some of the core-animated-pages demos would help. Here are a couple that you may be able to leverage to get sort of close to your design:
https://www.eecs.berkeley.edu/~gongliang13/polymer/polymer-tutorial-master/components/core-animated-pages/demos/grid.html
https://www.eecs.berkeley.edu/~gongliang13/polymer/polymer-tutorial-master/components/core-animated-pages/demos/music.html
I'm looking forward to implement something like google direct answers which uses knowledge graph, is there any useful resource can I read ? also Where can I find data for that?
Thanks in advance
From the semantic web aspect of your question i guess an interesting starting point for you is the DBpedia (example queries) dataset, maybe in combination with the strings to Wikipedia concepts dataset.
I am excited for this free class: Probabilistic Graphical Models - Daphne Koller, Professor. I would look her up and watch her youtube videos in the mean time.
How do you determine which onsets are beats? I am using Spectral Flux for Note Onset Detection and a Running Mean for peak-picking/thresholding.
I am just working with the guitar instrument so the presence of percussions may not help with this. Any ideas?
Thanks!
EDIT: Wow...just realized this question is 3 years old...sorry to resurrect an old post.
My Master's thesis was in beat detection and the main advantage of my method over all other published methods of beat detection was in resolution, both in the time domain and frequency (beat) domain. You can find my thesis here. What it basically boils down to (after alot of filtering) is a comb-filter convolution. My code is an adaptation of this project, which contains Matlab files for you to see how it works.
My code (both in C++ and the Matlab port) is not publicly available due to possible copywrite issues with my university, but if you email me at dberm22[at]gmail[dot]com, I'd be more than willing to ahem::discuss my work with you.
Try using a beat tracking algorithm. Beat tracking is a distinct problem from onset detection.
I think there's a good algorithm in the Queen Mary plugin set for Sonic Visualizer. The plugins are open source, so you can have a look at the code to figure out how they work.
Or do a search on google scholar for "beat tracking". There are a number of effective approaches. Dan Ellis' is a good one to start with. It's intuitive, and there's code available in Matlab and Java.