I Got (Business) Schooled!

Last year I and 9 other scientists were awarded a UK Newton Fund-DOST Leaders in Innovation Fellowship. The fellowship gave us and tech transfer officers  crash courses in research commercialization in London, Oxford and at the Asian Institute of Management. We were taught how to make business plans, pitch a product in under 3 minutes, negotiate, estimate market size, and project revenues.

Coming from Science all of the lessons were new to me and I enjoyed every bit of it for the novel and unique insights. I'd like to remember all the lessons I learned so I'm writing them down.

1. From Nieves Confesor of AIM - information is the currency of negotiation. In most cases, the more you openly share information the more you can negotiate better terms for your company.

2. From Richard Cruz of Ideaspace -  Scientists and engineers tend to think that their solution to a problem is the best for the end-user. But does it really address the customer pain? Stripped down to essentials our solution might not be answering their actual pain at all. Gather deep market insights by getting feedback from your end user.

3. From Maoi Arroyo of Hybridigm - the end-user is not necessarily the one who pays. Marketing should be directed at the one who holds the purse strings. Innovation = Invention x Revenues. If it doesn't earn its just an invention.

4. From Ricardo Lim of AIM - the former AIM dean introduced us to Design Thinking. Empathizing is the first step.

This is not the last in the list. I will add as I remember some more, since, hey, its been a year. I'll end with an advice that is somewhat antithetical to how we do science but which makes sense when we are developing solutions for an end user- Fail fast. Fail often. Iterate.

Me and my LIF Cohorts together with Tech Transfer officers holding up our business plans. This was at the Royal Academy of Engineering in London last March 2015.

With THE Nieves Confesor at the Asian Institute of Management. Photo by KM Magtubo.

Putting subtitles in video

Recently, our new VIP graduate student member Henry Lee, Jr. started a machine learning course in our lab. Some of our alumni like Francis and BA expressed interest in attending but couldn't come. So upon Francis' suggestion we took a video of Henry's lecture.

Pizza to go with the lectures. Photo by Elexis Mae Torres.

The video turned out great but the audio was terrible. I'm sure going to buy a directional microphone for the succeeding lectures but for the meantime I thought of annotating his talk by putting subtitles to the video. So onto Google to search for a subtitle editor.

Surprisingly, every forum I read recommended Subtitle Edit, a free, open source software to do just that.  So I tried it.

First, our movie was captured by an HD Panasonic video camera and the file format is .MTS. The lecture ran a little over an hour so the video file came out in two files, the first set was 4GB the second 1.4GB. I converted the MTS file into MP4 using Avidemux (oh, that's another topic. The proper setting can be found here.).

At first the file won't open in SE, its error message says the video codecs are not around. It suggested a link for downloading codecs. I just clicked and installed away and Voila! MP4's now open.

The SE interface is very easy to use. Five stars. And I've started adding subtitles.

Le Subtitle Edit interface.

But into the 50th second of the video I got lazy, so the complete annotations will have to wait for another day. Meanwhile, we will just have to wear earphones when we watch the video.

How to Install Image Processing Design Toolbox in Scilab without using Atoms

Besides SIVP - or Scilab Image and Video Processing Toolbox, I'm a great fan of Harald Galda's Image Processing Design. It has morphological operations and blob analysis functions not found in SIVP. These functions are great for automating analysis of several regions of interest in a scene at once.

However, as of posting, IPD does not show up in Scilab's ATOMS Module Manager. So I looked for ways to install IPD bypassing ATOMS. Anyone who has done this in Linux or MacOS let me know. Here's what works for Windows:

1. Download IPD.
2. Open Scilab and type SCIHOME. SCIHOME gives the path where the modules are stored.
3. In Windows Explorer copy paste the SCIHOME path to open the folder. You should see a folder named 'atom'.
4. Unzip the IPD module in the 'atom' folder. The unzipped folder should have the name IPD and not the zip filename.
5. Search for 'loader.sce' in the IPD folder, open and execute in Scilab.
6. Check your Scilab console it should show something like:

Start IPD - Image Processing Design
Load macros
Load dependencies
Load gateways
Load help
Load demos

And that's how you know you've succesfully loaded IPD toolbox in your Scilab.