Did you build the ICs? Though so.

That's a good point, however driverless cars are still being used in very controlled situations, and for the moment require a huge, expensive array of sensors coupled with fragile, powerful and expensive computers. Even if we wanted we could not replace a significant number of cars on the road with driverless ones. The problem is not some kind of legal or administrative red tape, the problem is to make the technology simple enough, robust enough and cheap enough that it comes by default on most new cars like electronic injection did a few years back. Then it is a problem of waiting for a number of years for these cars to replace the old ones on the road.

This is still a ways off.

Actually, searching for "Reduction of inter-block artifact in DWT" should produce IEEE articles, most probably from the Transactions on Image Processing journal or Transactions on Signal Processing.

And indeed they do. My technical searches always include at the very top the most relevant academic papers from scholar.google.com

Blocking-artifact reduction in block-coded images using wavelet-based subband decomposition
H Choi, T Kim - Circuits and Systems for Video Technology, , 2000 - ieeexplore.ieee.org

Inter-frame wavelet transform coder for color video compression

S Zafar, YQ Zhang - US Patent 5,495,292, 1996 - Google Patents

Embedded image coding using zerotrees of wavelet coefficients
JM Shapiro - Signal Processing, IEEE Transactions on, 1993 - ieeexplore.ieee.org

Blocking artifact detection and reduction in compressed data
GA Triantafyllidis, D Tzovaras - Circuits and Systems for , 2002 - ieeexplore.ieee.org

Perhaps the solution is for you to make a Google Scholar profile and you will get those as well?

This is not so insightful.

1- Foreigners who do come to America and then leave after a short period (a few years) do not take long-term jobs away from Americans. Clearly the jobs these undertake are like internships, post docs and other temp positions, these jobs are not meant as career jobs who would be of interest to an American.
2- Foreigners who come to America, get some training and then leave are *good* for America. These people will know and like America, will speak english, will have a network of friends and people they know back in America. If they start companies, maybe these companies will be friendly to America as well: import stuff from there, rely on American technology, and whatnot. The importance of creating goodwill cannot be overestimated.

How people who come on a H1B for a non-training job, and then stay by being sponsored for a green card, this is a different story. But notice that these people eventually become American. This has been a recognised way to extend the power and importance of the USA for a long time, because the best and brightest come to America to the detriment of the country they leave.

In reality the job situation in the USA is not nearly as dire as some people make it, compared with most other countries around the world. What is not so nice is that unemployed people have it very tough, very quickly. Better not fall sick.

Exactly. Also the NSA doesn't even need warrants. How convenient for them that everyone is leaving these fine files in the same place for them to search...

So then what happened to your dad?

Won't work, because most employees would rather use the cash than save it. Then society would have a massive influx of destitute, retirement-age people, which *would be* a problem. It's been done in the past with catastrophic results.

1) Roulez p'tit bolide

2) En avant, Guingamp

Your reply is very interesting and outlines the fact that one should not stop learning after school, but instead revisit past and new subjects with a different eye and different tools. Also motivation is the prime mover here.

Computer programming can be seen as more rigorous than mathematics because if the written program is not correct, the executable will not run; whereas a mathematical proof may contain elements that are not completely described but part of mathematical lore. However we do not possess a compiler for mathematics. Conversely language may be more abstract than mathematics because language, in addition to mathematics, may express information that is not mathematics, e.g. poetry, imagerie, etc. However mathematical abstraction is also very rigorous, which is not the case of poetry or other literary constructs.

Mathematics is unique in requiring both a high level of abstraction and rigour at the same time, yet this must be performed without any artificial help like a debugger or compilers. In addition, creative mathematics require a high level of intuition and the capacity to concentrate on a specific problem for long periods of time (months, sometimes). Altogether, mathematics requires specific talents that are fairly rare and not necessarily found in programmers or writers.

Fortunately we are not all alike.

Grant money is given preferably to teams that already publish a lot. Even "starting grants" in the EU require a single principal investigator (PI) with a lot of well-cited publication under their belt. This can only be achieved if the PI has done their initial research in a well-heeled lab, with a well-known head of the lab who is well-connected, and so on. This encourages a pyramidal structure with a lot of grunt students at the bottom, supervised by post-docs, supervised by assistant professors, and so on. Success encourages visibility, which encourages grants, which ensures money, which ensures good grunt students can be hired, and so on.

This is not the only possible successful structure, but one of the most common. A single researcher, however brilliant, cannot usually keep up with the outpouring of landmark papers the pyramidal structure can achieve. On the other hand, if everybody does their job, meritocracy in the pyramidal structure ensures that the best grunt students get promoted to post docs, and so on, usually in a different pyramidal structure.

The big drawback of the pyramidal structure is that the prof at the top usually doesn't know exactly what is going on at the bottom, even though they put their name on most of the papers that the structure produces.

Disclaimer: I'm a tenured prof. I do have a reasonable number of students, but I work with them directly. All my students are co-supervised with at least one other prof. Occasionally I do have a few post-docs but the structure is always collaborative. This is not the standard but this works well enough also as long as there isn't any ego-driven fights in the lab. This means choosing your collaborators well. I've made a few mistakes, but so far so good.

If you look at just about anybody's success story, the first thing that is of utmost importance is being in the right place at the right time. In other words, luck. The American dream has always been a dream. I'm not convinced that anything much has changed in the last 70 years about this, i.e. since about the end of WWII. Sure hard work is a factor but by no means the only one.

Not all libraries. OpenCV for instance.

Inefficient (two interpreters), inelegant (two syntaxes), and there is usually no point to it. Both languages are roughly as capable.

Only the really cheap stuff is particle board. They also have plenty of real wood stuff. What they really do well is the non-particle, real wood, cheap shelves like the Ivar brand. These are everywhere and there is essentially no alternative.