Module quadcopter yang saya prepare dengan kerjasama Petrosains akan dilancarkan pada bulan Disember ini bersempena dengan cuti sekolah. Jadi, kepada sahabat-sahabat yang ada anak berumur 16-19 tahun boleh lah join untuk belajar cara-cara membina quadcopter & terbangkan ia di Petrosains.
p/s: InsyaAllah saya akan hadir pada sesi 11 Disember 2014 🙂
At the center of any good product design is a whole lot of heart. Mladen Barbaric, the founder and CEO of Pearl Studios, explained at Gigaom’s Roadmap conference Wednesday why design is a “deeply human and profoundly emotional” process, and design projects created with love have a better chance to resonate with the general populace.
“I think that creating brands and products is something that requires us to reach deep inside and it’s a very emotional endeavor,” said Barbaric.
During his session, Barbaric interwove tales from his childhood with examples about how the specific lessons he learned over the years could be seen in some of the companies his design firm works with.
As a kid, Barbaric’s love for art drove him to draw all over the place–including the walls and ceilings of his house, much to his father’s chagrin. When Barbaric’s mom showed she was impressed with how he…
There was a question posted on StackOverflow that captures my attention, regarding mapping x/y pixel from long/lat data. But first, given a *.jpg or a *.png photo, some preliminary processing needs to be done before reasonable pixel-coordinates can be obtained.
In order to achieve your goal, you first must know two things about your data:
The projection your maps are in. If they are purely derived from Google Maps, then chances are they are using a spherical Mercator projection.
The geographic coordinate system your latitude/longitude coordinates are using. This can vary, because there are different ways of locating lat/longs on the globe. The most common GCS, used in most web-mapping applications and for GPS’s, is WGS84.
I’m assuming your data is in these coordinate systems.
The spherical Mercator projection defines a coordinate pair in meters, for the surface of the earth. This means, for every lat/long coordinate there is a matching meter/meter coordinate. This enables you to do the conversion using the following procedure:
Find the WGS84 lat/long of the corners of the image.
Convert the WGS lat/longs to the spherical Mercator projection. There conversion tools out there, my favorite is to use the cs2cs tool that is part of the PROJ4 project.
You can safely do a simple linear transform to convert between points on the image, and points on the earth in the spherical Mercator projection, and back again.
In order to go from a WGS84 point to a pixel on the image, the procedure is now:
Project lat/lon to spherical Mercator. This can be done using the proj4js library.
Transform spherical Mercator coordinate into image pixel coordinate using the linear relationship discovered above.