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Thanks for posting this link. The original link works for me (probably b/c I use university proxy which provides access to the journal; without it I get the blank page too).


Can you elaborate on why you want to blame the NRA?

I should disclose that I own a number of firearms, many of them sidearms, and don't like the NRA very much, nor have I ever donated to them or been a member. I'm just curious as to how you see them as being the source to blame.


I’m not sure what I need to elaborate. The NRA promotes wider gun ownership and more expansive concealed carry. Police use wider ownership of guns and concealed carry to justify more use of deadly force and militarization. In any other country than the US, this feedback loop would be obvious. In the US the NRA works to blur the obvious by talking about “responsible gun owners” while eliding the leakage between responsible and irresponsible owners.


Any data on police shootings of concealed carry permit holders? Also any data on how many concealed carry permit holders actually shoot police?

Hint: practically zero.

Making a correlation between concealed carry and shootings is beyond ridiculous — there is zero data supporting such conclusions.


And this led to the police militarization?


It's not the only cause (I'll save you the rant on US defense spending, you can watch Why We Fight (http://www.imdb.com/title/tt0436971/) , but it's a positive feedback loop. I don't believe I used the word "led" or suggested one caused the other. I am suggesting that once gun ownership (and concealed carry) and police militarization are established, one reinforces the other.


Ah, you said blame them. I'd assumerd that meant you felt they were the cause of both. I was pretty confused. Thanks for clearing that up.

I am a fan of responsible firearm ownership, but not the NRA - by the way. I don't know if I'd blame them, but I'd agree that they contribute to the 'gun culture' that ends up with irresponsible people wanting to own firearms.


9/11 and the two wars led to police militarization. Directly due to funding to Police departments to purchase ex-military weapons and indirectly by hyping the terrorist threat.


I am unsure what you want. But I can clear up your question.

On an electric guitar, and some acoustics, you will see a bar that they.call the whammy bar. This is often a tremolo bar by name. The truth of it is it is a vibratto bar

Vibrato modifies music by changing the pitch.It bends wires.

For reasons unknown, tremolo adjust by moving the volume. The real tremolo is inside your amp or in a pedal.

Where the confusion came from is still unknown. But, your tremolo is probably in an amp or pedal. Vibrato is by the bar they sometimes call a whammy bar.


I ordered a sandwich in Cann River and got a plate of sandwich ingredients as an unassembled sandwich. This happened again in Melbourne. I'm skeptical of your whole country's sandwich making skills.


Up here, we still consider Brunswick to be Northern Massachusetts.

Why does that matter? Nowhere in what my neighbors consider Maine actually wants Amazon. But, BNAS might be a brilliant location for it.


If my experience in highway infrastructure is any guide, this is mostly futile. If they really want to slow it down, start with an environmental impact study. The best thing about it is the government has to pay for it and they are very subjective.

You can make a project take twice as long.


> If they really want to slow it down, start with an environmental impact study.

People who care about the environment should care that environmental impact studies are what they claim to be and not red tape bombs. People are supposed to be concerned about the outcome of them, not using them as a means to an unrelated end.


I'd not be so sure. It can almost always get worse.


Sure, there could be a dictatorship, awe-inspiring corruption, brutal repression of political opposition, genocide, hyper-inflation, a famine, and stunning mismanagement of every aspect of the country.

...wait, those are all things that occurred under Mugabe. How much worse can things get? (Mind you, I have no particular reason to think the coup will make things better, inasmuch as it seems to have been conducted by close allies of Mugabe is order to maintain power, rather than a different faction looking to seize it.)


Well, they still have people living. They could address that next.


While that is true, there is more room for improvement in Zimbabwe than there is in most countries.


I thought military coups were a good thing. That's what Hollywood celebrities like Chelsea Handler and Sarah Silverman told us this year.


I wonder if it will ever get good enough to detect counterfeit bags? My understanding is that they are a prolific problem.


You shouldn't be getting downvoted for this.

Yes, this is an active area of research. There was a paper at KDD17 working on this: https://dl.acm.org/citation.cfm?id=3098186&dl=ACM&coll=DL&CF...

NVidia had a blog post about this: https://blogs.nvidia.com/blog/2017/08/03/detecting-counterfe...

There's a French company with a product: http://cypheme.com/


Neat, thanks! I could see a few valuable use cases, from customs to personal.


Maybe a certain percentage, but much of the work in detecting many counterfeit bags involves actually inspecting a lot of the work on the interior of the bag or looking for specific construction characteristics that knock-off groups don't take the time to replicate for a market that is unknowing.

source: a mom that was nuts about calling out fakes in a snarky manner.


My thinking was that one might be able to do it with their cell phone, with close up images. Then it could maybe tell things like stitching, material, precise color match, and maybe then be able to say if it is counterfeit.

I'm just not sure ML is yet that good. My thoughts were more about multiple pictures or a small video. I'd suspect that it could train itself further as the DB expands.

I'm just not sure how good it actually can be. It probably only has to be better than a layperson, though I could see more precise stuff used to scan by customs. Any percentage higher than the normal buyer of such would be better, assuming few false positives.


You could certainly do that, but you would need to create the training dataset. It would require many thousands of photos of real and counterfeit bags up close.

Image recognition has been mostly solved by ML techniques, so if you just assemble the data and train the network you can distinguish any set of things that are significantly different visually.


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