Right Side, Left Side Latest blog posts http://rightsideleftside.teddriver.net/post/barbara-kingsolver http://rightsideleftside.teddriver.net/post/barbara-kingsolver ted Barbara Kingsolver I was introduced to Barbara Kingsolver today.  I'm sorry it took this long. Sun, 06 Aug 2023 13:11:31 -0400 2023-08-06T13:41:17-04:00 I heard about Barbara Kingsolver through advertisements of her novel Demon Copperhead. Such a unique title and, as I found out, it related to David Copperfield.<br />I put a few of her books in digital form on hold, and received the first; her book of short stories titled <u>Homeland and Other Stories.</u> I opened it up and read the first paragraph of the first story, Homeland, and I'm hooked. This is it below. I stopped and had to write something here. I cannot WAIT to read more.<br /><div style="text-align:center"><img src="/posts/files/3d6af38d-bc98-46c7-bea7-f12b302c3f4a.png" alt="" style="font-size:1.8em" /></div> http://rightsideleftside.teddriver.net/post/supreme-court-decision-on-affirmative-action http://rightsideleftside.teddriver.net/post/supreme-court-decision-on-affirmative-action ted Supreme Court Decision on Affirmative Action How about this instead... Sat, 01 Jul 2023 00:03:23 -0400 2023-08-06T13:41:38-04:00 The universities look at the ratio of races of people that submit applications, and they admit the same ratio to their universities each year. http://rightsideleftside.teddriver.net/post/quantitative-analytics-for-bvlos-oras http://rightsideleftside.teddriver.net/post/quantitative-analytics-for-bvlos-oras ted Quantitative Analytics for BVLOS ORAs In May 2021, I presented new research on quantifying Operational Risk Assessments (ORAs) with my colleagues Matt Petry and Garrett McKelvey. ORAs are a necessary part of gaining approval to fly drones Beyond Visual Line of Sight (BVLOS).  Currently, ORAs take a lot of time and can be a complicated task. Wed, 07 Sep 2022 01:43:30 -0400 2023-08-06T13:41:55-04:00 In May 2021, I presented new research on quantifying Operational Risk Assessments (ORAs) with my colleagues Matt Petry and Garrett McKelvey. ORAs are a necessary part of gaining approval to fly drones Beyond Visual Line of Sight (BVLOS).<br />Currently, ORAs take a lot of time and can be a complicated task.<br />In this paper, we discuss methods for quantifying risk likelihood, and show how this information can be automated and visualized for quick decision making.<br /><br />The presentation can be viewed here: <a href="https://teddriver.net/Papers/Quantitative%20Analytics%20For%20BVLOS%20ORAs%20-%20Presentation.pdf">Presentation: Quantitative Analytics for BVLOS ORAs</a><a href="~/Papers/Quantitative Analytics For BVLOS ORAs - Presentation.pdf">.</a><br /><br />The full paper is available here: <a href="https://teddriver.net/Papers/Quantitative%20Analytics%20for%20Beyond%20Visual%20Line%20of%20Sight%20Operational%20Risk%20Assessments.pdf">Paper: Quantitative Analytics for Beyond Visual Line of Sight Operational Risk Assessments</a> http://rightsideleftside.teddriver.net/post/understanding-gps-in-contested-environments http://rightsideleftside.teddriver.net/post/understanding-gps-in-contested-environments ted Understanding GPS in Contested Environments In April 2020, I presented a talk on understanding GPS in contested environments. Topics included the following:Understanding GPS position error, dilution of precision and user range errors, physical and radio visibility, terrain heights and field results, mitigation techniques and alternative navigation technologies. Fri, 07 May 2021 03:20:04 -0400 2023-08-06T13:42:58-04:00 <blockquote style="margin:0 0 0 40px;border:none;padding:0"><p style="font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px">In April 2020, I presented a talk on understanding GPS in contested environments. Topics included the following:</p></blockquote><ul style="font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px"><ul><li>Understanding GPS position error</li><li>Dilution of precision and user range errors</li><li>Physical and radio visibility</li><li>Terrain heights and field results</li><li>Mitigation techniques</li><li>Alternative navigation technologies</li></ul></ul><blockquote style="margin:0 0 0 40px;border:none;padding:0"><div><p style="text-align:left;font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px">I presented this talk again at the AUVSI XPONENTIAL conference, on October 8, 2020. The presentation below is slightly updated, and is from this later presentation.</p></div><div><p style="text-align:left;font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px">The presentation can be viewed here: <a href="https://teddriver.net/Papers/Understanding%20GPS%20in%20Contested%20Environments%20October%202020%20Presentation.pdf" style="color:rgb(51,122,183)">Presentation: Understanding GPS in Contested Environments</a></p></div><div><p style="text-align:left;font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px">The full paper is available here: <a href="https://teddriver.net/Papers/Understanding%20GPS%20Navigation%20in%20Contested%20Environments.pdf" style="color:rgb(51,122,183)">Paper: Understanding GPS in Contested Environments</a></p></div><div><p style="text-align:left;font-family:&quot;Helvetica Neue&quot;,Helvetica,Arial,sans-serif;font-size:14px">You can view the April 2020 webinar <a href="https://auvsievents.webex.com/recordingservice/sites/auvsievents/recording/a2a7dab260d544d2819a8280e10a2a6e" style="color:rgb(51,122,183)">on this link</a>.</p></div></blockquote> http://rightsideleftside.teddriver.net/post/norms-values-mores http://rightsideleftside.teddriver.net/post/norms-values-mores ted Norms, Values, Mores What ever you call them; truisms, mores, rules to live by, golden rules, the feeling is the same.  These are simple guidelines. They can be followed easily, but not without courage, strength and the ability to see beyond yourself, for the good of all.All laws must be based on a set of values that work for individuals and large societies. Thu, 24 Dec 2020 05:07:01 -0500 2023-08-06T23:39:26-04:00 <div><span style="color:rgb(0,0,0)">What ever you call them; truisms, mores, rules to live by, golden rules, the feeling is the same. These are simple guidelines. They can be followed easily, but not without courage, strength and the ability to see beyond yourself, for the good of all.</span></div><div><span style="color:rgb(0,0,0)">All laws must be based on a set of values that work for individuals and large societies.</span></div><div><font color="#000000"><br /></font><ol><li><b>Do no harm to others (physical, emotional, or psychological)</b><br /> <span style="font-size:17.5px">If this is happening to you and you disagree with it, and can change it - do. See #4</span></li><li><b>Do not oppress others, or make them act against their will</b> (violates #1)</li><li><b>Be completely open, honest and transparent</b> (no hidden agendas, or covert ways to violate #2)</li>This let's us try to persuade others, show our true feelings and thoughts, and lets other issues that may end up violating #2 and #1 be dealt with early<li><b>Live your life as you please<br /></b>Be free to do what you please, while not encroaching on others or violating 1, 2 or 3.</li></ol><div><br /></div></div> http://rightsideleftside.teddriver.net/post/thank-god http://rightsideleftside.teddriver.net/post/thank-god ted Thank God The national nightmare is over, we have a new president. Sun, 08 Nov 2020 03:51:46 -0500 2023-08-06T13:43:19-04:00 Thank God this national nightmare is over. The unbelievable idiocy, gas-lighting, lying and division that has come from the White House of the United States has been appalling. Trump has lost the election, Joe Biden and Kamala Harris have won. We can finally start to breathe.<br /><br /> http://rightsideleftside.teddriver.net/post/we-are-not-alone http://rightsideleftside.teddriver.net/post/we-are-not-alone ted We are not alone We live in the woods here.  We are not alone. Sat, 22 Aug 2020 15:52:55 -0400 2023-08-06T13:43:43-04:00 We have lots of animals visiting us here in the woods. We live in a Ponderosa Pine forest rife with squirrels, brown and black. Many varieties of birds too, from Stellar Jays to pygmy nuthatches. Occasionally, we also get larger creatures, rarely foxes anymore, less rare are coyotes, but more common this year are bears. They are only around in the Summer, and only every few years. There is one in particular that has shown up this year, and he has made our house a semi-regular stop on his rounds. Let's call him Charlie. <br /><br />Here he is strolling through.<img src="/posts/files/1a1117ba-2ded-4dbf-9f6e-8a4bcf16e076.jpeg" alt="" /><br /><br />Sadly, some of our neighbors don't keep their trash in the garage, so Charlie feasts at their places. It's important not to feed the bears. They become habituated to the food and forget how to forage. Also, human food and garbage is not good for them nutritionally.<br /><br />Here's Charlie looking at my empty bird feeder platform.<br /><img src="/posts/files/f97d5d83-0084-435e-8ea1-0553f53d97d7.jpeg" alt="" /><br /><br />And another empty bird feeder check.<br /><img src="/posts/files/bd32927a-51d3-48b7-a0c0-9f423d51d4d9.jpeg" alt="" /><br /><br />I like having bears around. Many of our neighbors fear them, but Charlie is not menacing, he's just hungry, and will take any opportunity to eat. <br /><br />I did get some videos of him too. <a href="https://youtu.be/amF5oxctU64">Charlie surveying the greenhouse</a> and <a href="https://youtu.be/pAE0B7-VH_k">Charlie stopping by</a> are the two best ones.<br /> http://rightsideleftside.teddriver.net/post/some-older-short-stories http://rightsideleftside.teddriver.net/post/some-older-short-stories ted Some older short stories I used to write stories. I haven't had the desire to write in quite a while, but I feel it starting to come back.  Hopefully these won't be the last ones I'll write. Wed, 19 Aug 2020 04:03:03 -0400 2023-08-06T13:43:59-04:00 This first story I've rewritten a few times. I submitted this to a local writing contest - it did not place. I'm not surprised. It takes a lot of practice to understand the timing, characters and their dynamics and scene development. I still like the story though.<br /><p style="text-align:left"><a href="http://rightsideleftside.teddriver.net/docs/The%20nine%20day%20war.pdf">The Nine Day War</a></p><p style="text-align:left">I wrote this next story in 2004. As it turns out, it was somewhat prescient. I was looking into the future a bit, extrapolating on some good ideas and some bad. Note that the iPod was first released in 2003 and the iPhone in 2007.</p><p style="text-align:left"><a href="http://rightsideleftside.teddriver.net/docs/The%20Reservation.pdf">The Reservation</a></p><p style="text-align:left">I'm always happy to get comments, let me know what you think.</p> http://rightsideleftside.teddriver.net/post/how-long-can-you-use-a-gps-almanac http://rightsideleftside.teddriver.net/post/how-long-can-you-use-a-gps-almanac How Long Can You Use a GPS Almanac? When you turn on your GPS receiver - what happens? Well, lots of stuff. But primarily, GPS receivers work in a two stage process: 1) Look for available satellites to track 2) Do everything else.  In this article, I want to focus on step 1, we'll get to step 2 later. Sat, 20 May 2017 15:50:29 -0400 2023-08-06T13:44:21-04:00 <p><i>Note: A longer more detailed version of this article appeared in the December 2008 issue of <a href="http://www.insidegnss.com/">InsideGNSS</a>. That article can be found <a href="http://teddriver.net/Papers/novdec08-gnss-sol-v1.pdf">here</a>.</i></p><p>When you turn on your GPS receiver - what happens? Well, lots of stuff. But primarily, GPS receivers work in a two stage process:</p><ol><li>Look for available satellites to track</li><li>Do everything else</li></ol><p>In this article, I want to focus on step 1, we'll get to step 2 later. This is probably common knowledge, but for the record I want to state it. The GPS receiver uses an almanac downloaded from a single GPS satellite to help it determine what satellites are above the horizon as it searches for signals. It makes sense to not look for satellite signals that aren't even visible - it decreases your <a href="http://en.wikipedia.org/wiki/Time_to_first_fix" target="_blank">time to first fix</a> (TTFF).</p><p>Since the receiver is simply determining whether a satellite is above the horizon, the almanacs don't have to be very accurate. They are typically a coarser version of the precise ephemeris broadcast by each individual satellite. So, given that lack of accuracy, how long you can use an almanac for analysis? Your receiver will usually download a new almanac when it sees that a new one is available, so it always has the freshest data. When you do analysis though, sometimes you may not have the latest almanac (or the one correct for the time of analysis - a related problem). So, is it ok to use any old almanac for analysis? Since they are not the most accurate ephemeris representations, should I even be using them for analysis at all? I'll answer these questions and show some interesting graphics that bring the point home.</p><p>For analysis sake, let's say we're interested in Position Dilution of Precision (PDOP) prediction. PDOP is calculated from standard formulas and requires a source of ephemeris for the satellites. You can calculate PDOP from precise, actual ephemeris, or almanac generated ephemeris. I'll compare the PDOP calculated using the almanac to 'true' PDOP - that calculated from the precise ephemeris.</p><p>For our first analysis, let's look at 24 hours of PDOP values - using a precise ephemeris for the actual PDOP and a three week old almanac to generate the ephemeris for the predicted PDOP.</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/aa586bea-6c36-4fd1-8c99-b9d81cc31111.png" target="_blank"><img title="3 Week PDOP" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="3 Week PDOP" src="http://rightsideleftside.teddriver.net/posts/files/2df7496c-975d-4ed2-a65c-2f220b07658a.png" width="409" height="317" /></a></p><p>The actual PDOP is in blue, with the almanac predicted PDOP in green. We can see some differences here, though in general the predicted PDOP follows the same curves as the actual PDOP. The areas of trouble will be where the blue lines are above the green lines. In that case, the actual PDOP is greater than the predicted PDOP, and relying on your prediction can cause trouble. Let's take a look at the differences in PDOP values for a 6 week time span. I used an almanac to predict PDOP starting on the day the almanac was produced (0 days of almanac age) up to 6 weeks in the future (almanac age of 6 weeks), and <em>differenced</em> those predicted PDOP values against the actual PDOP values.</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/dcae3f71-fe26-420e-b0b2-bb36901244e6.png" target="_blank"><img title="6weekalmanacpredictionLT" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="6weekalmanacpredictionLT" src="http://rightsideleftside.teddriver.net/posts/files/8c5358d5-da3f-454c-8ffc-85421cdaa659.png" width="407" height="307" /></a></p><p>This graph shows something interesting. Despite an occasional spike, it looks like almanacs can be faithfully used for about two weeks to predict PDOP. The differences are essentially zero for that time span. After about two weeks, things start to go down hill. We saw hints of this in the three week old graph above. Differences in PDOP value start to increase, with the major spikes occurring more often and secondary spikes beginning to occur. Note that the negative values here are the most dangerous - when actual PDOP values are greater than predicted values. It's nice to see that the spikes appear with a greater magnitude in the positive direction than the negative.</p><p>What happens if we go longer with an almanac? Here's a PDOP plot for a day, using an almanac that is 21 weeks old.</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/2eb474d2-a919-441d-9f06-fe91b1b52e99.png" target="_blank"><img title="21weekpredictedpdopLT" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="21weekpredictedpdopLT" src="http://rightsideleftside.teddriver.net/posts/files/40f955f0-8a86-4466-bbad-ec2ec46f87fb.png" width="395" height="298" /></a></p><p>We start to see some serious problems here. The biggest problem happens around hour 8, where the actual PDOP is roughly 2.08 and the predicted is roughly 1.5. Another more stealthy error occurs at hour 20. Here, the predicted PDOP shows a drop in value, from roughly 1.93 to 1.6. These PDOP drops are associated with additional satellites coming into view and denote good times to get GPS position measurements. The actual PDOP here is rising though - indicating a failing prediction and completely incorrect information.</p><p>How does the difference graph look at this time span?</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/82982e30-2be3-4080-a693-cae462066a86.png" target="_blank"><img title="22weekalmanacpredictionLT" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="22weekalmanacpredictionLT" src="http://rightsideleftside.teddriver.net/posts/files/4a52bed9-b83f-4a85-a3cb-3281fc2ecda9.png" width="387" height="292" /></a></p><p>Yep - lots of problems in this regime. As the almanac ages, the negative values increase in magnitude, meaning hazardous prediction conditions. <strong><font color="#ff0000">Do not use an almanac this old for operations!</font></strong> I want to show two more graphs that will drive this point home. The first is a PDOP difference variance graph - basically how bad the PDOP values vary from each other as a function of time.</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/5970db2e-4e69-4d54-8363-16e40f24a8ae.png" target="_blank"><img title="pdoppredictedvarianceLT" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="pdoppredictedvarianceLT" src="http://rightsideleftside.teddriver.net/posts/files/ef4921d4-e6ac-457b-9e78-8a77139a7f9c.png" width="382" height="288" /></a></p><p>As we saw above, the first two weeks, show essentially zero variance. After that, the variance increases linearly. This shows us again that almanacs should not be used after the two week mark. Maybe almanacs should come with an expiration date. If only you could tell they were bad by smelling them like you can with bad Nog. Oh well.</p><p>The last graph shows how well the predicted PDOP values correlate to actual PDOP values. This is a cross-correlation analysis and essentially compares the PDOP values at each point in time (in this case, every 15 minutes), and determines how well they compare to one another. A high value means they are well correlated, a low value means there is little correlation between them. There are over 14700 correlations done here; one each 15 minutes for 22 weeks. We expect the correlations to be high at the same time every day.</p><p><a href="http://rightsideleftside.teddriver.net/posts/files/7c03166b-11f1-4e86-aaa7-14b18d7c990b.png" target="_blank"><img title="almanaccrosscorrelationLT" style="border-top:0;border-right:0;background-image:none;border-bottom:0;float:none;padding-top:0;padding-left:0;margin-left:auto;border-left:0;display:block;padding-right:0;margin-right:auto" border="0" alt="almanaccrosscorrelationLT" src="http://rightsideleftside.teddriver.net/posts/files/68eb8e93-2e3e-47de-aa1e-2e248631aa78.png" width="373" height="285" /></a></p><p>We see correlation spikes at the same time each day, indicating that the PDOPs do correlate then. Over time however, we see that the correlations decrease, until at 22 weeks, there is no correlation between predicted PDOPS and actual PDOPs. The first two week period is denoted by lags up to 1344. Looking at this graph, you can see that even in the first two weeks, the PDOP correlation begins to degrade. Using the most current almanac will keep you on the left side of this graph, and allow your PDOP predictions to correlate best.</p><p>To summarize, you can <em><strong>use almanacs to predict PDOP well for up to two weeks</strong></em>. Almanacs should not be used after that time period, as dangerous prediction conditions can arise. Also, to get the best performance from an almanac, use the latest one available.</p><p>So we've seen how you can use almanacs to predict PDOP, and if you've surfed around the Nog, you've probably noticed this analysis defines how well you can predict GPS accuracy as well. PDOP is a good indicator of GPS position accuracy but it's not the only player in the game. For a more in-depth analysis of predicting GPS accuracy, look at my paper on the subject here: <a href="http://teddriver.net/Papers/Long%20term%20prediction%20of%20GPS%20accuracy%20-%20Understanding%20the%20Fundamentals.pdf">Long term prediction of GPS accuracy - Understanding the Fundamentals</a>.</p> http://rightsideleftside.teddriver.net/post/the-first-law-was-broken http://rightsideleftside.teddriver.net/post/the-first-law-was-broken The First Law Was Broken The day Dr. David Dao was dragged off of a United plane so United employees could get to their next destination was significant for another, possibly longer-lived reason that the sheer brutality it portrayed. Tue, 18 Apr 2017 01:50:21 -0400 2023-08-06T13:44:32-04:00 <p>The day Dr. David Dao was dragged off of a United plane so United employees could get to their next destination was significant for another, possibly longer-lived reason that the sheer brutality it portrayed. Those familiar with the science fiction genre and more specifically Isaac Asimov will have heard of his three laws of robotics. These laws were created as a plot device but their validity in our time of increasingly sentient AI is becoming more apparent. <a href="https://futurism.com/2-expert-thinks-ai-will-undoubtably-wipe-out-humanity/" target="_blank">Elon Musk and Stephan Hawking</a> are warning us about advancing AI. AI is making its way into our lives at a decent pace and so far, we've been very accepting of it.</p><p>The Dao incident however may be the first time the 1st law of robotics was broken. For those not familiar with <a href="https://en.wikipedia.org/wiki/Three_Laws_of_Robotics" target="_blank">these laws</a> , I'll list them here.</p><ol><li>A robot may not injure a human being or, through inaction, allow a human being to come to harm.</li><li>A robot must obey orders given it by human beings except where such orders would conflict with the First Law.</li><li>A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.</li></ol><p>In our current time, the 3rd law doesn't yet apply - there is no way for a robot to protect itself, except possibly in advanced research facilities where <a href="https://www.youtube.com/user/BostonDynamics" target="_blank">walking, running and rolling robots</a> are the norm.</p><p>In the case or Dr. Dao, United employees first asked for volunteers to deplane. When no one volunteered, they said they'd let the computer pick four seats that people would have to vacate. This step has a human asking a machine to pick four other humans at random. At this point, only the United employees know what will happen to passengers that refuse to deplane, based on company training. When Dr. Dao refused to deplane, United called police to “assist him” to the floor of the aircraft and drag him off. So, a computer unwittingly aided a human decision to harm a human thereby breaking the first law of robotics.</p><p>You may find this point a bit of a stretch, but I'll argue that even if it is, the actual, un-stretched case is not too far off. This is because of an even more striking human behavior in this situation.</p><p>United asked for volunteers to deplane. When they didn't, a United employee said they would have a computer do it - removing their culpability and ascribing it to the “computer” and in Thurman Merman's <a href="http://www.imdb.com/character/ch0044756/quotes" target="_blank">words</a> from Bad Santa – “so it wouldn't be [their] bad thing”. The fact that a human was easily moved to allow a computer to decide random passenger's fate is troubling.</p><p>This attribute (defect?) in humans is <a href="https://en.wikipedia.org/wiki/Milgram_experiment" target="_blank">well known</a> and has been shown experimentally. In another experiment, when one randomly selected group of individuals (who have done no wrong) is imprisoned and the other half of the group become the imprisoners, the <a href="http://www.prisonexp.org/" target="_blank">results are startling</a>. In this case, United employees would certainly feel like they “own” the plane, because they have been told they have control over the passengers in certain situations. Even though the passengers are not doing anything wrong, aspects of this behavior are obvious. With so few emergency situations on planes, (thankfully) an outlet for employee's training is not readily available and this builds a level of stress.</p><p>Because humans will act this way, and because AI is becoming more and more prevalent, we have a compelling argument for implementing robotic laws – or in a more modern frame of reference – <a href="https://futureoflife.org/ai-safety-research/" target="_blank">AI safety</a>.</p>