The Cycle of Prosperity – YouTube.
Month: May 2014
I used my new macro lens extender, the Canon 70-300mm lens, a tripod, and DSLR Controller from Chainfire*, and post processing in Lightroom 5 to create this photo.
note DSLR Controller requires a USB “on the go” cable adapter to hook up to your Android device’s USB port.
Full size image here, warning: large
Crop Factor with ISO & Aperture: How Sony, Olympus & Panasonic Cheat You
Here’s my PSA for today – if you buy one of those small sensor mirror less digital cameras or any other crop factor sensor camera then you really need to pay attention to the math & logic in this video before you buy any expensive lenses. If you don’t you can get really screwed.
Crop Factor with ISO & Aperture: How Sony, Olympus & Panasonic Cheat You – YouTube.
Test of an Animated GIF
Intensity of Tropical Cyclones Shifting Poleward: New Study in Nature
Tropical expansion, most likely due to anthropogenic global warming, is causing hurricanes and cyclones to stray further from the equator in both hemispheres. The consequences of the Northward drift in the Americas and Asia could be huge as hurricanes and associated tropical storms will be more likely to hit the heavily populated US Eastern seaboard and high population coasts in China and Japan more often. New York better prepare for future storms like Sandy in other words.
According to the study, the latitude at which tropical cyclones reach their greatest intensity is gradually shifting from the tropics toward the poles at rates of about 33 to 39 miles per decade.
The new study was led by Jim Kossin, a National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center scientist stationed at the University of Wisconsin-Madison’s Cooperative Institute for Meteorological Satellite Studies.
The research documents a poleward migration of storm intensity in both the Northern and Southern Hemispheres through an analysis of 30 years of global historical tropical cyclone data.
More: Intensity of Tropical Cyclones Shifting Poleward: Study
More regarding this study from Andrew Freedman at Mashable:
The new study examines a metric known as a storm’s “lifetime-maximum intensity” during the period from 1982 to 2012, which is a timeframe that is not complicated by changes in storm observations. The metric refers to the point where storms max out in strength.
By examining storm data using this metric, the researchers found a strikingly apparent poleward shift in the locations where storms are reaching their peak intensity. Although the changes varied from ocean basin to ocean basin, with the greatest migration seen in the western North Pacific Ocean, which is the most active area for tropical cyclones, the shift was found in both the Northern and Southern Hemispheres.
In the Northern Hemisphere, the lifetime-maximum intensity point is moving north at 33 miles per decade, whereas in the Southern Hemisphere, that point is moving south at 39 miles per decade.
Also note that the full data set on storm tracks is here, however the earlier parts of last century’s data is less reliable, which is why the paper is based on more recent storm data.
Securing That Internet of Things While Keeping it Useful
The other day I sat in on the The Cisco Security Grand Challenge webinar for the Internet of Things. I listened not because I am joining the very worth while challenge, but because I wanted to make sure I am in touch with the latest directions and concerns about the Internet of Things.
Some IoT changes to come are almost master-of- the-obvious apparent while others are so complex that almost all predictions will fail. We are standing on the verge of tremendous change – the Internet of Things is exploding – e.g. in my household we’ve grown from 5 things on the internet to over 20 in just the past two years, and projections are that within ten years +50 billion devices will be connected.
During the webinar I found that their concerns match many of mine however so that was good news. As we progress into the new personal and business M2M universe of smart devices with smart sensors we will discover that they need to rely on being able to network both with the cloud and each other to compare notes and to gain and share user context. They will need to do this to make intelligent decisions and recommendations for us and to power our applications to do so as well.
So how the heck do you make that secure while keeping it easy to use? How do you keep the code open, and how do you patch code in a world of critical devices like autonomous cars and pacemakers that we also cannot afford to have exploitable by hackers?
How do we keep the devices flexible and tailored to individual or business needs while also keeping them hardened? What happens if an autonomous car gets fed tire sensor data that makes it think it had a flat when it’s rolling down the freeway? How can you prevent that? What about battlefield robots, who should they trust & how is that trust established?
When your devices have to talk about you how do we keep your data private, and when we do have to share to the cloud, how do we keep it anonymized?
How do we recognize just your devices, how do we keep your cloud of things discrete from your neighbor’s cloud of things? How do we hand you the keys, but keep your neighbor locked out?
These are the very serious technical challenges of the next few years since they internet of things will have +50 billion devices connected within ten years.
There are creative solutions we can use for all of these problems. Some will undoubtedly come about through the Cisco challenge, but my recommendation is that every tech company needs to put these challenges together yesterday, not tomorrow, because the internet of things is not going to wait on you if you drag your feet.
Here’s a gallery of the best photos from yesterday’s walk in no particular order. It’s really a mixed bag, I was shooting through a long telephoto with high aperture numbers, which means long shutter times for hand held telephoto shots. Each of these are instructive (to me at least,) because none are really great but could have been if…
How to create and tailor a Smart playlist in ITUNES
When I do want to listen to old stuff or tunes from a certain era I use a smart playlist, and here’s how you can create and tailor them for particular decades in ITUNES.
I listen to a lot of music, but I mostly like to keep songlist rotation to newer tunes. I think this keeps me young, forward-looking, and out of a deep nostalgia rut that can become a sucking morass that steals your soul and all of that. e.g. I know some folks who listen to nothing but old songs that are sad paeans to the joys of their lost youth, and get this: they started listening to that yearning for lost childhood song list way back while they were still young believe it or not. Their song list is about 75 tunes of total melancholic bore on endless repeat and I sure don’t want to become like that. (No! I am not talking about you my friend!) Enough of the rambling, and to the point.
I do get in a rare moods where I do want to think back, and I still have all of those old tunes on my IPOD; I just don’t listen to them as much as most people because I played the heck out of them while DJ’ing. When I do want to listen to old stuff I use a smart playlist, and here’s how you can create and tailor them for particular decades in ITUNES.
First under “File” menu Select >NEW then >Smart Playlist — once the window pops up click the Plus sign a few times to create a few programmable lines, when you finish it will look something like this but the lines will be mostly blank & the same:
The first window says “artist” but it’s a drop selection window with a ton of choices — Select “YEAR” and then move right to the next window on that line for the operator. You want to select the year prior to the year you actually want the list to start with so if you were making a playlist of Rock, Pop, and other music from 2000 – 2010 then after you select Year, next to it the operator drop down that has “is greater than” and then in the last selection window type in “1999”.
Next in the bottom line of your playlist you close your program bracket by doing the same but use “YEAR” “is less than” and put in “2011”. That brackets your decade but you aren’t done yet, you should always put in a line in that excludes “holiday” so you don’t get that Christmas tune playing in June at minimum…” To do that Select “Genre” to exclude “Holiday” by using “is not”, on those other lines you can also exclude any other genres or things you don’t like, look at those drop downs and be creative in narrowing the playlist – you can always add more lines in the script by hitting the “+”, and once you are all done you use the “-” sign to eliminate any extra lines. Click on “Live Updating” so it grabs any new songs you add that might fit the criteria and then hit save, and name it something specific like 2000-2010 or “the lost decade” or whatever. Bam! you done..
Google’s new trick: knowing where you parked.
While people worry about privacy doing tricks like this is all about your machines tracking you, and then guessing the meaning of your daily motions through the contextual sense of multiple sensors.
If Google can do this then they can know when you get to your garage, and if there were an interface API for Genie garage door openers… well you get where this is going.
Here’s a fun new trick that Google just patched into Google Now, the company’s card-based personal assistant: it can now keep track of where you parked. While there are plenty of apps out there that can help you remember your parking space, they all require you to open them and save your spot manually. In contrast, Google’s parking tracker will save your parking location automatically. First noticed by Android Police, the new feature is part of Google Search 3.4, which is rolling out to Android devices running 4.1 and above right now.
Google Now automatically detects your parking spot through Android’s Activity Recognition system, a feature Google released at Google I/O 2013. Activity Recognition uses a mashup of GPS, Wi-Fi, cell tower location, compass, accelerometer, gyro, and barometer data to figure out what the user is doing. By using all the sensor data available to a smart phone, Activity Recognition can detect if the user is walking, driving, cycling, or sitting still, and it can trigger apps to do something when a change is detected. If Google Now detects that the user has gone from driving to walking, the car has most likely been parked, and pinging the GPS to save your location would be a good idea. All of this happens silently in the background without the user having to do anything.
More: <a href=”http://arstechnica.com/gadgets/2014/05/google-now-for-android-will-automatically-remember-where-you-parked/”>Google Now for Android Will Automatically Remember Where You Parked</a>