Search for “woman” on virtually any stock photo site and you’ll get plenty of options.

Women in skimpy dresses. Women in bikinis. Half-naked women. Fully naked women posed so that it’s not technically pornography. Women working out in what basically amounts to underwear. Women in wedding dresses. Women indulging themselves in a massage, or chocolate-covered strawberries, or at the salon. You might even come across an image of a princess or two.

Sure, you might find an image of a woman working. But she undoubtedly looks stressed out, at her wits end, and ready to call it quits. To find a stock photo of a woman who actually looks in control at work is equivalent to finding a unicorn in the wild.

Stressed woman image via Shutterstock.

Take a look at stock themes pretty much anywhere online—even a lot designed by women—and you’ll find examples of these kinds of stock photos, if a woman even appears in the photos at all. Of course, there are exceptions, but they’re few and far between when you look at the overall numbers.

Why is this the norm?

Of course, part of the explanation for this may have to do with the abysmal numbers of women in the technology industries. While it’s hard to find concrete numbers, what is available is pretty disheartening.

Pinterest engineer Tracy Chou has created a public Google spreadsheet that details how many female engineers are employed by some leading tech companies. Out of companies with more than 10 employees, only 9 out of the 86 companies listed have more than 25% female engineers. That’s barely over 10%, and barely higher than the number who have no female engineers. Not a single one of those companies has over 35% female engineers.

The world of design isn’t much better. Instead of roundups of the best female web designers out there, we get roundups like this one that instead tell us who the 20 hottest female designers are. Their head shots are given much more prominence than their work. After all, a talented female designer isn’t nearly as valuable as a hot female designer. And the saddest part? That link is the first one that shows up when you search Google for “female web designers”. (FYI, the second link is also about “hot” female designers, though at least that one leaves out the head shots.)

According to some numbers I’ve seen, the ratio of male to female web designers is somewhere along the lines of 3:1. That’s a big disparity. And no one is quite sure why it exists.

The lack of women in the tech industry is obviously one part of the problem, though it’s just one aspect. What might be even more relevant when it comes to the reasoning behind the prevalence of these stock images is one of the oldest sales rules in the book…

Sex sells

We all know that sex sells. Or at least it’s supposed to. So using sexy, provocative imagery in our designs kind of makes sense.

But at the same time, you’re potentially alienating a lot of people. There are a ton of women out there who don’t like to see images that objectify them (no surprise there). There are a growing number of men who are also sick of being bombarded with these images. And honestly, a stock photo of a woman in a bikini should not be necessary when you’re trying to sell a website theme.

I don’t know about you, but all the offices I’ve ever worked in, I’ve never seen any of my colleagues dressed like this:

Business woman image via Shutterstock.

The same goes for these images of women who look entirely stressed out by technology and work life. There are plenty of women out there, myself included, who work with tech on a daily basis, without getting any more stressed out than our male colleagues. So why do we feel the need to show women as unable to cope with these daily demands?

Finally, an alternative

While it’s all well and good to complain about the portrayal of women in stock photography, there wasn’t much we could do about it. We were stuck with what was available. Not many projects have the kind of budget necessary for a photoshoot to get images that better represent women. It’s just not feasible.

Thankfully, there are people and organizations in the industry who recognize this. Getty Images is one such company. They’ve partnered with Lean In to create a collection of more than 2500 powerful images showing women, girls and the people who support them.

These images are fantastic. There are women from all walks of life, from all sorts of professions, doing all sorts of things. But the key here is that all of these women appear perfectly capable. They are not buckling under pressure; they are living their lives and doing their things, and are confident in that position.

Plenty of the images in this collection also include men, in the roles of partner, colleague, father, and more. It is by no means an anti-male collection, and in no way does it show women in a positive light at the expense of men.

There is a huge amount of diversity in the images, with women from around the world featured. There are women of all ages, too. It’s a really wonderful cross-section of what it means to be a woman, and gives designers and others using stock photos a wealth of options. It’s a welcome change to the industry, and hopefully other companies will follow suit.

Create Special Effects Like a Pro with Photo Effect Studio – only $14!

In this article we're going to look at the Generate theme, powered by the Genesis Framework. This theme was chosen because it offers a great deal of flexibility, not only for creating a blog, but for building landing pages and squeeze pages.

From Terabyte-Sized Stem Cell Images to Knowledge

Peter Bajcsy, PhD
Information technology Laboratory
National Institute of Standards and Technology

10:00am Monday, 10 March 2014, ITE 346, UMBC

This talk will present the computational challenges and approaches to knowledge discovery from terabyte-sized images. The motivation comes from experimental systems for imaging and analyzing human pluripotent stem cell cultures at the spatial and temporal coverage of colonies that lead to terabyte-sized image data. The objective of such an unprecedented cell study is to characterize pluripotency of stem cell colonies over time at high statistical significance in order to understand the stem cell culture quality parameters and guide a repeatable growth of high quality stem cell colonies. The terabyte- sized images represented a stem cell line that was engineered to produce green fluorescent protein (GFP) under the influence of Oct4 promoter and then imaged in a mosaic of contiguous frames covering approximately 180 square millimeters, over five days under both phase contrast and GFP channels.

We overview multiple computer and computational science problems related to correcting (flat-field, dark current and background), stitching, segmenting, tracking, re-projecting and then representing large images for interactive visualization and sampling in a web browser. We researched extensions to Amdahl’s law for Map-Reduce computations, established benchmarks for image processing on a Hadoop platform, and introduced cluster node utilization coefficients for modeling memory demanding computations running on a computer cluster/cloud. The theoretical aspects of algorithmic complexity and cluster utilization at terabyte scale are extended to the experimental aspects of efficient image representation and client-server workload distribution in the context of visualization interactivity and image sampling. We report such experimental results for the NIST extensions to the Deep Zoom paradigm. The presentation will conclude with illustrations of enabled stem cell discoveries and collaboration opportunities to create a reference resource not only for cell biologists but also for computer scientists focusing on terabyte scale image analyses.

Peter Bajcsy received his Ph.D. in Electrical and Computer Engineering in 1997 from the University of Illinois at Urbana-Champaign and a M.S. in Electrical and Computer Engineering in 1994 from the University of Pennsylvania. He worked for machine vision, government contracting, and research and educational institutions before joining the National Institute of Standards and Technology (NIST) in 2011. At NIST, he has been leading a project focusing on the application of computational science in biological metrology, and specifically stem cell characterization at very large scales. Peter’s area of research is large-scale image-based analyses and syntheses using mathematical, statistical and computational models while leveraging computer science fields such as image processing, machine learning, computer vision, and pattern recognition. He has co-authored more than more than 24 journal papers and eight books or book chapters, and close to 100 conference papers.

Host: Yelena Yesha (Sorry, you need javascript to view this email address. )

From Terabyte-Sized Stem Cell Images to Knowledge

Peter Bajcsy, PhD
Information technology Laboratory
National Institute of Standards and Technology

10:00am Monday, 10 March 2014, ITE 346, UMBC

This talk will present the computational challenges and approaches to knowledge discovery from terabyte-sized images. The motivation comes from experimental systems for imaging and analyzing human pluripotent stem cell cultures at the spatial and temporal coverage of colonies that lead to terabyte-sized image data. The objective of such an unprecedented cell study is to characterize pluripotency of stem cell colonies over time at high statistical significance in order to understand the stem cell culture quality parameters and guide a repeatable growth of high quality stem cell colonies. The terabyte- sized images represented a stem cell line that was engineered to produce green fluorescent protein (GFP) under the influence of Oct4 promoter and then imaged in a mosaic of contiguous frames covering approximately 180 square millimeters, over five days under both phase contrast and GFP channels.

We overview multiple computer and computational science problems related to correcting (flat-field, dark current and background), stitching, segmenting, tracking, re-projecting and then representing large images for interactive visualization and sampling in a web browser. We researched extensions to Amdahl’s law for Map-Reduce computations, established benchmarks for image processing on a Hadoop platform, and introduced cluster node utilization coefficients for modeling memory demanding computations running on a computer cluster/cloud. The theoretical aspects of algorithmic complexity and cluster utilization at terabyte scale are extended to the experimental aspects of efficient image representation and client-server workload distribution in the context of visualization interactivity and image sampling. We report such experimental results for the NIST extensions to the Deep Zoom paradigm. The presentation will conclude with illustrations of enabled stem cell discoveries and collaboration opportunities to create a reference resource not only for cell biologists but also for computer scientists focusing on terabyte scale image analyses.

Peter Bajcsy received his Ph.D. in Electrical and Computer Engineering in 1997 from the University of Illinois at Urbana-Champaign and a M.S. in Electrical and Computer Engineering in 1994 from the University of Pennsylvania. He worked for machine vision, government contracting, and research and educational institutions before joining the National Institute of Standards and Technology (NIST) in 2011. At NIST, he has been leading a project focusing on the application of computational science in biological metrology, and specifically stem cell characterization at very large scales. Peter’s area of research is large-scale image-based analyses and syntheses using mathematical, statistical and computational models while leveraging computer science fields such as image processing, machine learning, computer vision, and pattern recognition. He has co-authored more than more than 24 journal papers and eight books or book chapters, and close to 100 conference papers.

Host: Yelena Yesha (Sorry, you need javascript to view this email address. )

JavaScript frameworks alternative, GSS is geared towards boosting Web UI development by fixing CSS's intrinsic layout problems when developing with that type of style sheets.

froglogic GmbH today announced its release of Squish Coco 3.0, a complete C, C++, C# and Tcl code coverage tool chain for Windows, Linux, Mac OS X, Unix and embedded systems.

Mark Otto "derping around with measuring CSS performance". Nothing looks particularly concerning to me, to the point where I would change how I do things. The most surprising numbers were in background vs background-color, but Paul Irish debunks that a bit.

There must be something in the water as Ben Frain has dug in a little bit on CSS performance as well. I like Ben's soundbite:

With CSS, architecture is outside the braces; performance is inside

This is mine.

Direct Link to Article — Permalink

css perf is a post from CSS-Tricks

It's worth noting that the srcset attribute for the img element has landed in Chromium (Chrome will get it in 34, Opera 21). Their example: <img alt="A rad wolf." src="pic1x.jpg" srcset="pic1x.jpg 1x, pic2x.jpg 2x, pic4x.jpg 4x"> And:

Stay tuned for the <picture> element

We needed this. The fight was arduous. The solution is good. Other browsers will be on the way. This is notable as once a browser supports something, the tendency is for it to always be supported. Plus now polyfills can be true polyfills.

Direct Link to Article — Permalink

srcset in Chrome is a post from CSS-Tricks