Reality, Reactivity, Relevance and Repeatability in Java Application Profiling
this product from JInspired appears to support runtime profiling of java apps with < 5% performance impact
(tags: profiling performance java coding measurement)
You Lookin’ At Me? Reflections on Google Glass
ex-Nokia product design guru Jan Chipchase on Google Glass
(tags: google privacy technology google-glass pervasive-computing life future)
Not the ‘best in the world’ – The Medical Independent
Debunking this prolife talking point:
‘Our maternity services are amongst the best in the world’. This phrase has been much hackneyed since the heartbreaking death of Savita Halappanavar was revealed in mid October. James Reilly and other senior politicians are particularly guilty of citing this inaccurate position. So what is the state of Irish maternity services and how do our figures compare with other comparable countries? Let’s start with the statistics.
The bottom line:Eight deaths per 100,000 is not bad, but it ranks our maternity services far from the best in world and below countries such as Slovakia and Poland.
(tags: pro-choice ireland savita medicine health maternity morbidity statistics)
How Kaggle Is Changing How We Work – Thomas Goetz – The Atlantic
Founded in 2010, Kaggle is an online platform for data-mining and predictive-modeling competitions. A company arranges with Kaggle to post a dump of data with a proposed problem, and the site’s community of computer scientists and mathematicians — known these days as data scientists — take on the task, posting proposed solutions. […] On one level, of course, Kaggle is just another spin on crowdsourcing, tapping the global brain to solve a big problem. That stuff has been around for a decade or more, at least back to Wikipedia (or farther back, Linux, etc). And companies like TaskRabbit and oDesk have thrown jobs to the crowd for several years. But I think Kaggle, and other online labor markets, represent more than that, and I’ll offer two arguments. First, Kaggle doesn’t incorporate work from all levels of proficiency, professionals to amateurs. Participants are experts, and they aren’t working for benevolent reasons alone: they want to win, and they want to get better to improve their chances of winning next time. Second, Kaggle doesn’t just create the incidental work product, it creates a new marketplace for work, a deeper disruption in a professional field. Unlike traditional temp labor, these aren’t bottom of the totem pole jobs. Kagglers are on top. And that disruption is what will kill Joy’s Law. Because here’s the thing: the Kaggle ranking has become an essential metric in the world of data science. Employers like American Express and the New York Times have begun listing a Kaggle rank as an essential qualification in their help wanted ads for data scientists. It’s not just a merit badge for the coders; it’s a more significant, more valuable, indicator of capability than our traditional benchmarks for proficiency or expertise. In other words, your Ivy League diploma and IBM resume don’t matter so much as my Kaggle score. It’s flipping the resume, where your work is measurable and metricized and your value in the marketplace is more valuable than the place you work.
(tags: academia datamining economics data kaggle data-science ranking work competition crowdsourcing contracting)
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a good reference, with lots of sample output. Not clear if it takes 1.6/1.7 differences into account, though