Monday, February 28, 2011

Bee Removal Phase 3: The Box is Back

It took about eleven contiguous hours of work, but my screech owl nest box is back in business, and not as a bee hive.

The nest box had to be disassembled to properly clean all of the bee grunge out of it. That meant breaking it down into its major components: (1) the frame, which includes the back wall visible in the photos, (2) the fold-down front with integrated infrared entryway sensor assembly, (3) the side compartment with thermometer and perch, (4) the side camera compartment, and (5) the roof, which includes the ceiling-camera assembly. Components 1, 2 and 3 were thoroughly cleaned using a combination of a putty knife, a garden hose with a high-pressure nozzle on it, a bucket of soapy water, and a heavy-duty scrub brush. Spray, scrape, scrub with soapy water, rinse, repeat. The technique worked well, and—apart from the beeswax, which must be a permanent part of the wood at this point—provided the fastest and most effective cleaning of all the methods I used.

The roof component didn’t need cleaning, because the glass window, which separates its camera, infrared illuminators and other electronics from the interior of the nest box proper, kept the bees out. However, that window was the attachment point for most of the combs, so cleaning it took quite a bit of work. For that I used careful handling, hot water, dish soap, a putty knife, and a Scotch-Brite Heavy Duty Scour Pad. That did the trick and, after a few iterations, took every last trace of the comb off of the window. (As I would later learn, it also scratched the window, in a manner that was only evident when light hit it at just the right angle. Those scouring pads are like plastic sandpaper, so I should have guessed, but didn’t. Do not make this mistake yourself.)

Unfortunately, I couldn’t use the garden hose technique with the side camera compartment, because its interior wall, which was the part that needed cleaning, was only designed to keep out insects and owls. It wasn’t designed to be water-tight, so the garden hose technique, or any similar technique, would have leaked water into the electronics inside. So, I had to disassemble the compartment enough to take off its interior wall (which is how I access the internal electronics for modifications and repairs). Unfortunately, in this case, though it’s absolutely necessary in order to get good illumination, the infrared illuminator LEDs are integrated into the interior wall, so washing that wall would have meant pouring water over the LEDs and into all of their wiring. It’s all carefully insulated with heat shrink tubing, but I couldn’t help but wonder whether water finding its way into one of the stranded wires that join the LEDs in series would have caused a problem.

In any case, I started-off with the goal of cleaning the side camera compartment’s interior wall without disassembling anything. That almost worked. A couple of problems cropped-up, however. One was that I found that the bees had sealed the tiny gaps around, well, absolutely everything, including each LED where it projected through the wall. That meant that I could no longer use the small gap between the LEDs and the walls of the holes they stick out of to tweak their angles to optimize box lighting. Also, the bees found the other hole in the wall, the one that is covered with a screen to keep insects out (an especially good design decision under the circumstances, if I do say so myself) and is positioned directly in front of the microphone which is mounted further back in the compartment, thus providing a straight-line air path to the microphone. The bees, however, in their instinctive zeal to seal their hive, had descended into the hole and filled in every last gap in the screen. So, no direct air path, anymore. And no hole, for that matter. Finally, my efforts to get all traces of the bee comb off of the camera window, resulted in my using the same technique I thought had worked so well on the ceiling camera compartment’s window: the scouring pad. This time the pad not only scratched the window, but came close to fogging portions of the glass before I happened to look at the glass at just the right angle to see the scratches and noticed that I'd just ruined the window. (That’s when I went back and checked the ceiling camera compartment’s window and found that it was scratched to, though not nearly as seriously.)

At that point, cleaning the interior wall of the side camera compartment went from tedious to a huge time sink. I had to disassemble the interior wall into its five (or six) components, in order to replace the window. Fortunately, I’ve often made spares of owl box components, and in this case I had about six more windows of the same size on hand. Unfortunately, after finding them, cleaning one with great care, and sitting down to install it, I found that the hardware store glass cutting fellow had not made all of the windows to precisely the same dimensions, whereas I had routed into the wood a socket of precisely the right dimensions (and the first window I tried happened to fit). Now that the first window was history, I found that the other windows were a few millimeters too large to fit in the socket, and ripping the interior wall assembly apart completely so I could put the sheet of wood containing the window socket on my router table and fix the socket, wasn’t an appealing option. There ensued a period of careful, awkward work with a wood chisel until window no. 2 eventually fit.

With the interior wall already fully disassembled, I then took great care with a tiny pick to remove every bit of bee sealant (propolis) from the LED sockets and the microphone hole. After reassembling the whole interior wall, adjusting the LED angles, and making a few more cleaning passes to try to get every trace of bee gunk off of the aluminum walls, I cleaned an accumulation of dust out of the underlying camera compartment containing the camera, microphone, and the bulk of other electronics. Then I reinstalled its interior wall and carefully sealed it.

At long last it was time to put the whole box back together again. That went smoothly enough, and the nice, clean box with fresh bedding material, adjusted lighting, and the elegant new beeswax coating on its interior woodwork, was hoisted back into its mount in the nest box tree.

The box is ready and waiting, so now all I need is for my pair of owls (or some other desperate pair) to choose it as a nest site. It may be too late to attract an initial nesting attempt in this part of the country, but I’d blame myself mightily for not trying, so at least I’m off that hook. Now we’ll wait and see if owls appear sometime in March. Nest Box Cam’ followers, cross your fingers, knock on wood, etc., because I’m certain that I should have done all of this at least a month ago, and, at this late stage, we either need last year’s pair to prove that they’re highly dedicated to this nest site, or we need luck.

P.S. Now that I know how to kill invading bee swarms, I promise not to let the screech owl nest box be co-opted again. In the future, I’ll either have the swarm moved more-or-less immediately, or I’ll kill it shortly after arrival, before it can do any significant harm.

Sunday, February 27, 2011

Bee Removal Phase 2: The Smell of Honey and Death

Yesterday (Saturday), it was misting heavily when I would like to have begun the nest box cleanup, and, under those circumstances, just handling the plastic covered steel cable that runs through a block and tackle to raise and lower the box would have been a challenge. Also, I’d’ve either had to stifle in a rain suit, or be soaked during the time it would take to get the box down and begin the cleanup. So, cleaning didn’t start until this (Sunday) afternoon. As you may gather from the photos below, this won’t be a quick cleanup job. Unfortunately, time is of the essence, so I have to find some way to get it all done very soon.

Since it died in 2009 from the combined effects of the 2008 and 2009 droughts, the nest box tree has been falling apart more and more with every set of strong winds that move through the area. That didn’t get underway until the wood had had a chance to dry out and become brittle, which fortunately didn’t occur until after the 2010 nesting season, but it did begin occurring shortly after the bees had moved into the owl box in the Spring of 2010. Unfortunately, the work of cutting away major broken limbs could, it seemed to me, run the risk of provoking the bees, so I hadn’t attempted to remove any of the mess until now. Just cutting away enough of the broken limbs to clear the patches of ground beneath the tree where I needed to work was a major undertaking, so most of this mess remains as you see it above, prior to the start of today’s work.

The nest box on the ground and opened. The bees’ combs nearly fill the entire interior, and the layer of black material on the floor of the box is composed entirely of dead bees. The smell was strong and vile – a combination, I presume, of the cloying scent of a large amount of raw honey, and the odor of hundreds of dead bees. I had hoped that I could accomplish the removal of the combs with hand tools, starting with a small pruning saw to sever their connections to the ceiling. Unfortunately, they were well connected to the back wall, too, and that meant hand removal. For some reason, I'd expected the combs to be stiff, but, in fact, they turned out to be flexible, soggy, heavy, dripping with honey, and, of course, reeking with that smell I found so vile. That olfactory and tactile combination made for repugnant work. Just to make the experience perfect, the removal distributed honey throughout the interior of the box, adding an extra dimension to the mess I still have to clean-up.

The front wall of the nest box, which is also the fold-down access door. It’s never been that color before. Beeswax, I presume.

The nest box interior after the initial comb removal. Observe that there’s still plenty of comb to remove where it attached to the ceiling (not directly visible, but the cut-off comb hanging from it can be seen in the shadows). The back wall also needs a good bit of attention. So, the honey running down the back wall is only the first of the cleanup problems I have to tackle there.

Comb remnants and honey on the aluminum walls, infrared illuminators, and glass window of the side camera compartment. Unfortunately, I can’t just hose it off as a first step in cleaning, because the compartment’s inner wall isn’t water tight. (It only needed to keep out owls and bugs, not rain, and letting its interior breathe a bit is, ordinarily, a good thing.)

The interior’s left wall with the thermometer and experimental perch. The comb hadn’t yet been built into this area, so it is less affected than most of the interior. All the same, it’s a mess, too. Fortunately, it can be hosed down.

Friday, February 25, 2011

Bees Dead. Next Step: Cleanup.

I've just pulled the No-Pest Strip from the entry hole of the screech owl nest box. It was full of dead bees, and there were no signs of live ones, so I think that a little more than two days of exposure to the fumes from the Strip has ensured that the hive is dead. There's no time to begin cleaning-out the box now. That’ll have to start (and, I hope, finish) this weekend. Perhaps, in the meantime, the squirrels will decide to check-out the box and do me the favor of helping themselves to the honey and comb, as they have in the past. One thing I don't know is whether the fumes from the Strip may have made any of that potential squirrel food toxic. Squirrels have an amazing sense of smell, however, and, with luck, if things don’t smell right to them, they’ll move on to their usual business of raiding my bird feeder.

Wednesday, February 23, 2011

Bee Removal Commences

Well, I couldn’t have put it off any longer without absolutely guaranteeing failure, but I’ve finally begun the process of removing the bees from my screech owl nest box. It’s a very simple, but ugly process: stuff a Hot Shot No-Pest Strip in the entry hole and get away fast. Of course, you have to find a safe way to do that. If you do it in freezing weather, the bees are incapacitated by the cold and you have options. But I let this year’s amazing cold-spell pass by un-utilized. Faced with warm, bee-friendly weather I had to do something a little complex to keep some distance between me and the bees: hose-clamp a long pole and a vise-grip together such that the vise-grip is horizontal when the pole is vertical and the release handle is on the underside of the grip, hang a very light, loose loop of rope around the release handle, close the vise-grip on the wide end of the No-Pest Strip, then go out and shove that Strip into the entry hole of the nest box in one quick motion—it’ll just fit through a 3" hole—then pull the rope to release the grip and go away at once.

That’s done now. Unfortunately, I have nothing against bees, Africanized, or otherwise. Apart from their habit of taking over my screech owl nest box (this is the third time it has happened over the years), and distracting people from the importance of our native pollinators, I like bees, and I don’t even bother them for their honey. At one point I’d hoped to get a local beekeeper to remove the hive, but I put off making the arrangements long enough that I’ve run out of time. So now I’m killing a perfectly nice, if poorly placed, hive of bees. Ugly.

I’m told by people with experience of this technique that it’ll kill the entire hive in a day. I think I’ll give it two. But then I have to rush to clean out the mess this’ll’ve left behind (unless I’m very lucky and the squirrels get in there PDQ and do most of the work for me), make any necessary repairs, and hope that my local owls have not given up on the box and found another nest site. It’s not quite time for nesting (that’s for early March around here), but a pre-condition of mating seems to be that the male owl secure a nest site, and mating has probably already happened. So, unless my female gave her mate the benefit of the doubt about the nest box being available in time for nesting, they may have already selected another nest site.

I have no idea what’ll happen. Stay tuned.

Monday, February 21, 2011

White-Tailed Deer Amid Zexmenia

White-tailed deer, Odocoileus virginianus, amid blooming Zexmenia,
Wedelia hispida. Bamberger Ranch Preserve, June 9, 2007.
Photo ©2007-2011 by Chris W. Johnson.

I keep telling David Bamberger that he should share random photos of interest from around the ranch with his blog readers, even if he has nothing to say about the photos, both because it gives the readers a chance to see something of the ranch they might otherwise never see, and because it will fill-in the gaps between his lengthier posts, which should please his readership. I think I have him convinced, but he hasn’t done it yet. In this case, I’m taking my own advice. Enjoy.

Thursday, February 17, 2011

Now Playing on Radio Paradise, My Photos

Radio Paradise, an Internet radio station, that also happens to have been my favorite radio station since a friend (thanks Brendan) introduced me to it many years ago, is now offering a high definition video feed to accompany their music. They’re accepting photos from anyone, provided that the photos meet their admittedly subjective criteria.

I’d been meaning to submit some of my own photos for a while. Unfortunately, I found it surprisingly tough to extract a satisfying 16 X 9 image from my 36 X 11 panoramas, and second-guessed myself into believing that none of the results were good enough. (Some of my favorite panoramas simply had no section to be extracted that was interesting by itself – the completeness of the full panorama turned-out to be essential, at least to my eyes, to the composition and appeal of the image.) However, a few nights back I took a fresh look at the candidate images I'd extracted, discarded more than half of them and submitted the rest just to see what would happen. Late the next day I received a flock of emails from Radio Paradise’s proprietors (one for each image), and, to my amazement, every image was accepted.

So, somewhere within the innumerable images that must compose Radio Paradise’s collection by now, are a few handfuls of mine. The odds of anyone seeing them must be exceedingly small, but tune in and enjoy the music (and everyone else’s photos), and you just might see a familiar name go by.


Tuesday, February 15, 2011

Human Face Recognition, a Presentation by Dr. Shalini Gupta

The Austin Forum, on the evening of January 4, 2011, hosted an interesting presentation by Dr. Shalini Gupta entitled “Digital Human Face Recognition,” which I attended because I find digital face recognition a fascinating technical challenge, an increasingly important social issue, and because I have an interest in a lesser, related problem: automatic face isolation (without regard to identity).

Regrettably, it does not appear to be the practice of the Forum to record video of these presentations, so you'll have to settle for her slides (PDF, 25.4 MB), and various points that seemed important at the time and therefore stuck in my head. Her results were significant, interesting, and some of them were even germane to my face isolation interests.

  • Ironically, for me at least, Dr. Gupta’s presentation did not cover one of the first problems any real-world face recognition system has to solve, and the one in which I was most immediately interested: face isolation.
  • Much of Gupta’s extremely successful “3D AnthroFace” work was performed against the “Texas 3D Face Recognition Database,” which pre-isolated the faces, consistently positioned them within every image, and used significantly higher resolution images than those I have experimented with. Also, since the photos in the recognition database are stereo and/or 3D, they provide significantly more data than 2D images. Their single deficiency, relative to photos I've worked with, is their apparent lack of color. The choice of monochromatic imagery was presumably rooted in a desire to ensure that their algorithm would work in the absence of color information, thus making it compatible with output from monochromatic cameras, like most security cameras.
  • The “Eigenfaces” algorithm, published by Turk and Pentland in 1991, made face recognition truly practical for the first time by allowing a face to be characterized by as few as five numbers, quantifying key differences between the metrics of the observed face, and a prototypical “Eigenface.” Gupta sites it as having achieved a 21% verification rate with a false acceptance rate (FAR) error of 1 in 1,000, although it is not clear what size of database was involved in the test that produced that figure. Presumably, 20 years ago, the database would have been quite limited. Nonetheless, Eigenfaces has apparently been the basis for all subsequent face recognition work, and has been dramatically advanced over the years. It has also become the basis for many other types of automated visual recognition systems; as Gupta put it, there are now Eigenbolts and Eigenscrews, etc. For a great many classes of objects that require visual recognition Eigen images can be produced which allow the Eigenfaces algorithm (and its improved descendants) to be applied essentially unchanged.
  • In the most recent standard industry test of face recognition (“Multi Biometric Evaluation” in 2009/10), which used a database of 3.6 million people and required the fully automated analysis of 8.7 million photos and videos shot in a variety of conditions, ranging from studio shots only marginally more complex than those in the “Texas 3D Face Recognition Database” (though not 3D), to real world video of moving subjects in widely varying photographic conditions, “3D AnthroFace” was not only better than any other technology, but had a recognition rate equal to, or better than, that of humans. However, the means by which the humans were tested was not specified, so it’s hard to know what to make of that claim. (It seems unlikely that any human was asked to review photos of 3.6 million people, and then search for them in 8.7 million photos and videos.)
  • With regard to human face recognition capabilities, Gupta pointed-out that in a study of prison inmates exonerated by DNA tests, 84% had been incorrectly visually identified by human witnesses. So, at least under the conditions in which crimes are committed, investigated and prosecuted, human face recognition can be so poor as to be actively misleading. This isn’t news to many of us, but given its real-world importance, it probably can’t be repeated too often.
  • Face recognition systems depend, as you’d expect, on a database of the faces they’re meant to recognize. The error rates (composed of the false rejection rate, FRR, and the false acceptance rate, FAR) of all extant, and predicted, face recognition systems increase with the number of faces in the database. This problem is regarded as intrinsic to the task, but it is widely believed that the growth in error rates can be reduced by using separate databases for storing the characteristics of faces that can be differentiated by readily identifiable gross characteristics. Race and, I believe, sex were mentioned as candidates for such characteristics. In such a system, the first step in face recognition would be to make that gross identification, and then to select the appropriate database based on it. After that, the existing face recognition approaches would be used within the selected database with significantly reduced error rates. Of course, the error rates continue to scale with database size, so the use of multiple databases only delays the point at which error rates become unacceptable, as face databases (presumably) will only grow in size for most any purpose for the foreseeable future.
  • Despite the huge strides made in digital human face recognition, it is still bedeviled by a number of quite ordinary issues including unconstrained observing environments, human aging, the poses of subjects, variations in illumination, varied facial expressions, and the poor quality of images available from video systems. The latter issue was of particular interest to me, because many of the photos I have dealt with are comparable to images that might be obtained from video in their poor resolution and quality, suggesting that even the best face recognition systems would have had difficulty with some of the same images that have been a challenge to me.
  • Dr. Gupta repeatedly refused to comment on the social implications of face recognition technology, stating that she was concerned only with the technology; what people did with it was not up to her. One wonders what the uniformed police officers, and anyone else in the audience who might have been considering operating a real-world face recognition system, took away from the presentation. While the results of Gupta’s work were truly impressive, as demonstrated in the Multi Biometric Evaluation of 2009/10, the real-world capabilities of all face recognition systems were called into question by her closing acknowledgement that a host of common issues posed major problems (see item above). Her discussion of the problem of error rates increasing as face databases grow only raised more questions. The industry’s anticipated method of mitigating the latter issue, as previously discussed, is to make an initial gross categorization of faces based on a characteristic like race, and then to search within category-specific databases. While this is a sensible technical strategy (if such gross categorization can be performed quickly and reliably), will its eventual developers and users realize that their technology is engaging in automatic racial profiling? Will they also realize that it is doing so because the more one relies on facial recognition technology, the less reliable it becomes? Either issue is significant independently, but, when considered together, they mean that being a member of one of the races that compose the largest of the category-specific databases brings a higher chance of being falsely identified (bad if the database is looking for criminals), and falsely rejected (bad if the database is supposed to grant someone access to their bank account, or confirm to border officials that they are who their passport says they are).

That’s everything I can think of to report. I hope some of it was of interest, and that I’ve done justice to Dr. Gupta’s impressive work.

Friday, February 11, 2011

A Dog I Did Know

My family passed along very few stories to me, or, at least, very few that proved memorable. One of them was Grandpa Johnson’s bacon, to which I was not a witness, though I choose to believe it. There’s another story I choose to believe, one to which I must have been a witness, though, to my sorrow, I’ll never, ever remember it. And I kind of hate to share it (it’s my story, and, in that special sense, not something for the world), but it’s a story I like a lot, and I suspect that one or two members of the world will appreciate it, too, so I also hate not sharing it. In any case, it’s short, and it goes like this:

My family acquired me and a very young puppy within a month of each other. I came first. The puppy came next. Like any human infant, I was useless and tended to sleep a lot. Like any puppy, ours tended to explore and sleep a lot. In the course of its explorations, it soon discovered me and my crib, and quickly concluded that the best place in the world to sleep was with a nice warm baby, in a nice comfy crib. And so it would slip between the bars of the crib and sleep with me. When the family couldn’t find the puppy, they always knew where to look first. This continued for some time, during which, as the particulars of our species demand, the puppy grew rapidly, while I grew slowly. One sad day, as the story goes, the family rushed to the nursery to investigate a piteous whining. They found my young friend crying for help, her head stuck between the bars of the crib. It seems that as she’d slept with me that day, her head had grown that last iota which made the difference between fitting and sticking between the crib’s bars. And so, after her nap, on her way out, she’d become trapped. She was freed easily enough, of course, no harm done, but ever after had to settle for some other, second-best place in the world to sleep.

When I sleep, so many decades later, when I am lucky enough to dream well, she, above all the other dogs I’ve loved, is the one who still comes to see me once in a while. I’d pay good money to forget just about every part of my childhood, but not if it meant losing her.

* * *

When random conversations turn to dogs, and I tell people that I grew up with dogs—which, broadly speaking, is a common enough experience to be unremarkable—none, I think, would guess just how literally that was true. And something about the way I grew up with dogs left a mark: Some friends tell me that their dogs approach me and play with me as if I were another dog, something they never do with any other person.

Of course, I wouldn’t have it any other way.

Wednesday, February 9, 2011

A Dog I Don’t Know

I was sure I’d included this story here at some point in the past, but I went looking for it yesterday and couldn’t find it. Therefore, I now pass along the following story from Mark Twain’s autobiography, as edited by Charles Neider, pg. 256:

Doctor John [Brown] was very fond of animals, and particularly of dogs. No one needs to be told this who has read that pathetic and beautiful masterpiece, Rab and His Friends. After his death his son, Jock, published a brief memorial of him which he distributed privately among friends; and in it occurs a little episode which illustrates the relationship that existed between Doctor John and the other animals. It is furnished by an Edinburgh lady whom Doctor John used to pick up and carry to school or back in his carriage frequently at a time when she was twelve years old. She said that they were chatting together tranquilly one day, when he suddenly thrust his head out of the carriage window eagerly—then resumed his place with a disappointed look on his face. The girl said: “Who is it? Some one you know?” He said, “No, a dog I don't know.”

I know exactly how he felt.