Can you give an example of an LED bulb installation with 50%+ luminous efficacy? Perhaps you are thinking of the raw lumens/watt coming out of lab-grade LED material without considering other system draws (cooling, power conversion)?
Summary: The FAA's B4UFLY app only tells you whether you can _fly_ a drone somewhere. It doesn't tell you whether you can _take off, operate, and land_ from there because that is up to the property owner (whether private or government owned).
May I suggest more than one magnet per train to differentiate them.
Simplest way: number of magnets corresponds to train ID. Small space between magnets (calculated from Hall sensor refresh rate and max train speed). Count number of Hall sensor trips (maybe with debounce) within some time period (calculated from the minimum train speed during crossing and the magnet spacing).
Disadvantage: Train minimum speed must be reasonable. Requires n(n+1)/2 magnets, or 36 for 8 trains.
More reliable way: two columns of magnets, slightly offset, spaced as above. Two Hall sensors in a row under the track. Col 1 is clock. Col 2 is data. Whenever Hall 1 (clock) goes high, read Hall 2 (data) (maybe for a short period for debounce). To keep things simple and stay away from speed assumptions, put the same number of clock magnets on all trains: log2(train count), rounded up, for example 4 for 16 trains.
Disadvantage: Requires twice as many Hall sensors. Requires about log2(N)1.5 magnets per train, so 96 magnets for 16 trains, as opposed to 16 for the original method. Those tiny neodymium magnet bars are cheap, though.
BONUS: Train speed measurement. Speed is the clock magnet spacing divided by time between clock Hall trips. Now you can run a Pi algorithm (e.g. PID) to move trains at a target speed regardless of load, at least in the regions with Hall sensors.
If you are willing to assume the train speed is constant while passing the sensors and do more complex signal analysis on the Pi, the intermediate clock magnets can be removed, reducing the magnet count to N(2 + log2(N)0.5)=64.
GP's point is that we give humans the benefit of the doubt. You have reinforced that notion.
>> the degree to which something can experience suffering is proportionate to the sophistication of its ability to think.
But we do not assert that human suffering is at all related to IQ or intellectual "sophistication".
>> Simple animals appear to be able to experience pain. However ... they don't appear to be able to creatively imagine and dread pain.
But we would not say that a human with a mental disorder that renders them unable to think ahead is no longer capable of suffering.
>> More sophisticated animals (e.g. dogs) appear to be able to understand suffering in a psychological sense.
By "appear to", do you mean that dogs react to suffering in a way that reminds us of other humans? That they have learned to make the right noises, to flinch, to yelp?
>> ... while it is clear that virtually every organism avoids death, it is not necessarily clear in which of these or other senses they experience suffering.
I suspect that, though you never mention humans here, you are implicitly not questioning whether humans can experience suffering.
I can give the automotive electronics perspective here. Suppose that resistor costs 2c, including the actual part cost, PCB space, pick-and-place machine time (inc. more frequent spool replacement). Further suppose you expect to sell one million of this device.
$0.02 x 1E6 = $20k
If you are the circuit designer making, say, $150k, you just justified about a month of your salary (after accounting for benefits and other overhead). Your manager may parade you in front of the team at the next big group meeting as an example of how to achieve the BOM efficiency the company need to hit profit margin targets.
>> not that long ago computing resources were a limited commodity.
They are still limited in non-phone embedded contexts these days, leading to the ironic situation that the radar in your car that can override your brakes is running a much weaker CPU than your phone. RAM measured in the low megabytes.
Source: I write code for one of those radars and this constant appears in that code, alongside several other sqrt implementations of varying resolutions (8b, 16b, float). You are expected to use the least-resolution option in your algorithm, based on your analysis/testing. Same goes for trig functions.
I have to keep computer game development textbooks from the nineties and aughts around for reference material.
Interestingly, whataboutism is specifically about cases of hypocrisy. The point is that the presence of that hypocrisy is irrelevant.
"It represents a case of tu quoque (appeal to hypocrisy), a logical fallacy that attempts to discredit the opponent's position by asserting the opponent's failure to act consistently in accordance with that position, without directly refuting or disproving the opponent's initial argument." -Wikipedia