Doing any sort of large-scale computational fluid dynamics or finite element simulations may require a great many cores. For example, you might want to conduct a very detailed simulation of the air flow around a vehicle, airplane, structure, etc. to have a basic understanding of its aerodynamics before spending time and money testing an actual prototype in a wind tunnel. You might also want to look at how very complicated, soft-body structures deform due to a variety of external stimuli. Such information would be crucial for certain materials science applications. Chemical reaction and acoustic simulations may also require a great deal of computing power, especially if you want to have a high spatio-temporal resolution.
Essentially, there are plenty of physical and theoretical science applications that can benefit from massive processing capabilities. There is a lot of fundamental science that is also performed in simulation before any actual tests occur.
I spoke about engineers in general. And as you know, as someone who apparently lives at the end of a bell curve, when speaking in general there are always edge-cases that can seemingly contradict the general statement being made, but that doesn't stop that statement from being true.
Your generalization would be true if I was just one of a handful of students who worked up to general engineering principles from rudimentary physics knowledge. However, I can point to hundreds of my peers at MIT who did the same thing, many of whom likely have a much deeper understanding than I do. Given my exposure to the curriculum at CalTech and Stanford, I feel rather confident in stating that engineering students at those schools weren't just given equations and told to memorize them. Instead, they slogged through a series of derivations of those principles and had to build up their own understanding of the meaning behind those derivations. I'm sure that others can chime in about their experiences at other top-tier institutions, such as Berkeley, CMU, and the Ivies.
As an aside, undergraduate research assistantships are becoming more commonplace at some institutions. I agree that most undergraduates will probably not come out publishing papers in prestigious journals or conferences. However, that does not mean that they don't enhance their knowledge and understanding of various concepts.
In short, there are thousands, if not tens of thousands, of engineers out there with educational experiences that either partly or fully mirror my own. Consequently, you really need to be cautious when you make sweeping generalizations like engineers only spend their time memorizing formulas without reflecting on how those formulas came to be.
That's because engineers are not smart, they're dogmatic. They spend their entire university career learning formulas and recipes (excuse me, algorithms) without questioning them the way physicists or philosophers do. They spend the time, and they know their science, but they don't know why what they know is right, they just know that what they know IS right. [...] And because they only learn the results, not the history and argumentation that led up to the result, they're not as well prepared to deal with the barrage of idiocy that is spewed by people like anti-vaxxers.
There are plenty of incorrect assertions and generalizations made in this post. It honestly reads like a dogmatic diatribe.
As EE/CS undergraduate students, my classmates and I learned the fundamental physics behind various phenomena, not just the high-level equations. That is, we learned why, for example, transistors function they way that they do and why we can rely on simplified equations to characterize their behavior. Most of what we were taught is still covered in the MIT undergraduate curriculum (see courses 6.002, 6.012, 8.012, 8.04, and 8.044).
As EE/CS graduate students, my lab partners and I were responsible for furthering the state of the art. During these years, we had to understand why, for example, our experimental results diverged from our model predictions and how to revise those models accordingly. In some cases, we invalided long-standing, widely taught models and proposed new ones. If we didn't understand the fundamental physics behind these models, we wouldn't have made the contributions that we did. We also wouldn't have had our work published in Science, Nature, and PNAS.
I don't even need to lengthily address your comment that engineers aren't smart. There are plenty of people on Slashdot that can thoroughly invalidate that claim.
God, you're an entitled prick. As far as arguments for not paying for software goes, your [argument] is by far one of the stupidest.
The child poster who first replied to your comment was not me, the parent poster.
To expand upon my original comment: I am not interested in paying for and using software that is tied to platforms and services that I do not want or need. In my opinion, Origin is a good example of such a platform for two reasons. The first is that it is a glorified game-launcher application. If I've purchased a physical copy of the game, I should not need to install and use Origin to simply run the game, especially if its integration with Origin is minimal. Secondly, Origin is a digital storefront dedicated solely to a small catalog of EA products.
In contrast, I find platforms like Steam to be useful. For the most part, I'm able to launch and play games outside of the Steam service. As well, Steam offers a broad selection of products from a number of publishers. The fact that they offer massive sales throughout the year is also appealing, though tangential to the discussion.
Since EA has refused to release any of its newer games on Steam or other distribution platforms, there four options: (i) don't play the game, (ii) pirate the game and use a crack to get around the Origin requirement, (iii) pay for the game and crack it to get around the Origin requirement, or (iv) pay for the game and install/use Origin. Option (iv) is unappealing, as I do not wish to use Origin. Option (iii) is the one with the best intent; however, it is an unlawful choice due to circumventing the application protections. Moreover, in giving money to EA, I am reinforcing their use of Origin. Option (ii) is also unlawful. In this case, there are three possible side effects: (i) EA starts more tightly integrating their games with Origin, making cracking much more difficult or impossible, (ii) EA stops targeting computer gamers, or (iii) EA opens up their catalog to compensate for lost sales. This last side effect, while appealing, is unlikely.
Since EA started bundling their games with Origin, I have consistently chosen option (i) and will continue to do so in the future. If I had an overwhelming desire to play the game, which is not likely to happen, I would either go with option (ii) or an altered version of option (iii). I don't disagree with your assertion that this is an entitled viewpoint. However, it is not one on which I have acted.
You're not in IT, then, because they're salaried. No extra pay for extra hours.
You're correct: I'm currently not a salaried employee. I also hope to never be salaried again, let alone work for a company that bars me from overtime simply because I'm considered a "computer professional" in the eyes of the government.
As an aside, I can definitely empathize with those who are salaried employees. I had to deal with being labeled a salaried employee all throughout graduate school, despite my contract saying otherwise, and basically miss out on $100k to $125k/year (USD) in overtime; pretty much everyone else in the EECS department was in a similar situation. Suffice to say, when I had the chance to join a start-up company as a fairly compensated employee, I jumped at the opportunity.
The whole image of the 60 hour a week death-marching 'murican worker is a fiction.
When I was a graduate student, a 50- to 60-hour work week was basically a vacation, given that I routinely put in 70 to 85 hours per week. Moreover, it wasn't unheard of for students to basically not leave the lab for an entire week, let alone only sleep 5 hours per day on a couch during that time, while some important experiment was being conducted.
Nowadays, a 60-hour work week is the norm for me, and I've come to enjoy it. I have around three "productive" days where I work a total of 39 hours, two "semi-productive" days where I work a total of 18 hours, and an additional 3 hours that I spread out over the week for administrative tasks and meetings. While it would be nice to cut back to just 40 hours per week, I nearly double my salary by working those additional 20 hours.
The base Model S is $69,990 (USD) according to Tesla's website and Wikipedia, not $35,000 to $40,000 (USD). With federal tax credits, the base price comes down to $63,570 (USD). With state incentives, it becomes a bit more difficult to qualify the final price: essentially, you can either get a $2,500 (USD) rebate (California), a $6,000 (USD) income tax credit (Colorado), a $5,000 (USD) income tax credit (Georgia), or a $4,000 (USD) rebate for the car and a $3,000 (USD) rebate to offset the cost of electric vehicle charging stations (Illinois).
Considering what I paid for the Model S P85+, I do wish that the base price had been as low as what you originally claimed.
As an academic, part of the problem with starting wonderful open journals and conferences is the fact that there are very few incentives for us to spend our time to build up the reputation of the publication. Although being editor-in-chief or associate editor of a journal is nice to have for a tenure review, some universities weight it less than the number of publications produced, the prestige of the publication venue, how many students you have advised, how much grant money has been brought to the university, and how much publicity your work has received. Since so many of my colleagues are focused on maximizing these metrics, they have very little time for much else when starting their careers. Moreover, even when they have tenure, they still have to chase grant money to sponsor all of the students in their labs; when I was in graduate school, my adviser seemed to be flying around every two or three weeks to meet with program managers to get even more money.
Another item of note is that it is much easier to get support to start a conference if you align yourself with one of the major academic publishers, e.g., IEEE or Springer. Provided you can meet your attendance quota, these publishers provide much of the infrastructure and initial funding to host such events.
If you're using Word or OpenOffice, that might be a problem. If you're using LaTeX, it's not, provided that you're a reasonably quick typist and have memorized the standard mathematical commands. I ended up typing all of my lecture notes for my statistics Ph.D. classes without much of a hassle. In fact, most of the students in my classes came to me for portions of my lecture notes, as I was able to capture all of the important comments that the professors would make in haste while continuing on with a derivation or proof.
As for a comment on the article, since very little information was given about their testing protocols there may be some inherent bias in their findings. Specifically, their testing methodology seems to hinge on showing that short-term conceptual recall rates decrease when using laptops. That is, the authors don't bother addressing long-term retention and generalization.
As an actual researcher, let me state that your post has little to no bearing on reality. That is, open-access journals do not prevent an individual or group of individuals from artificially inflating various publication metrics. Moreover, agencies look at much more than those metrics, e.g., research output, research impact, past publication venues, and the number of students who are supported and are expected to graduate under a grant, when deciding how to dole out funding.
In an age where you can patent a rectangle, is it really about innovation anymore?
I just wanted to notify you, informally, that you've infringed upon my patent that details a process for complaining about patents. I'll make sure that my lawyers send you the appropriate notice paperwork by the end of next week.
Actual research is a wholly unintended side effect of academia. Only naive fools even attempt real research and inevitably fail.
Come tomorrow, I guess I should stop by the Department Chair's office and let him know that he should revoke my endowed scholar position, let alone the positions of my colleagues, as we're all apparently fools.
Good, their work is best done by private contractors anyway.
Private entities rarely, if at all, focus a majority of their efforts into pure research, unlike the national labs. Funding pure research, which is one of the few actions that the US Government at least does halfway correctly, is ultimately essential if we are to progress the state of the art and thus create new fields and products that are ripe for commercialization.
It's also important to remember, as in any major discipline, that mathematics has numerous components, some of which aren't commodious for many real-world problems; as such, it could take a fair amount of time to train someone so that they would be able to make a worthwhile contribution.
As one example, I have a friend and colleague who focused entirely on abstract algebraic topics for his research and enrolled in an ordinate number of analysis, topology, and algebra classes whilst eschewing ones deemed more practical, like those dealing with differential equations, optimization, numerical analysis, and applied probability; further, despite graduating from an Ivy League institution, let alone being incredibly smart, he has yet to find employment, as most of his knowledge does not translate well to solutions for any of the burgeoning fields, such as data analysis, computer vision, or robotics/autonomous systems. Consequently, in order to even consider a position out in industry, he's looking at spending the next two years diving into a sea of applied math.
I'm normally not one for coarse language and insults, but, given that the atypical neurogenic tic disorder that the individual suffers from can lead to both life-threatening asphyxia and tachycardia, I would have to say that you are a massively apathetic twat. I hope that you never become afflicted by any debilitating condition, let alone wind up in a similar situation and encounter someone insouciant who denies you access to medicine or necessary sustenance, as I doubt you'd have the fortitude to stand up to your ilk.
Fortunately, your pococurante attitude served some purpose beyond broadcasting your own inadequacies: it spurred me to pledge several thousand dollars for this guy's legal fund.
As you noted, the project was fun to undertake, even though it was only a sub-component to a much larger endeavor. I may yet go back, visit it, and submit an extension as a nice stand-alone article.
To answer your questions, though, I relied on a pool of around seventy subjects, equally distributed across genders and with a tri-modal distribution for age, many of whom were nudists that had heard about the data collection through some friends of mine. I also had a couple of adventurous fellow students and peers sign up to contribute; even my girlfriend at the time had no qualms about being filmed.
In any event, while there was some inherent selection bias in who I chose, mainly because I needed footage of as many different body types as I could capture, so as to allow the underlying model to generalize well, I do admit to being elated whenever people with certain body types were incredibly eager to help. Granted, I did, at the later stages, have to turn some people away, since I was spending too much time acquiring data.
For the experiments themselves, people had multiple options for what to wear for the various training phases, aside from the different changes of loose- and tight-fitting clothes that I'd ask them to bring and don. I did my best to provide multi-sex body suits of different sizes, which provided more than sufficient constraints when coupled with manually-derived measurements of quantities such as chest circumference, stomach circumference, and so forth. Others opted to strip down to their undergarments and a fair amount, surprisingly many of them women, wore nothing at all.
Regardless of what they wore or didn't wear, each subject executed a series of actions, such as walking, sitting down, standing up, skipping, and climbing. I used six pairs of stereo vision cameras to record the events. I had hoped to use Vicon cameras for the ground truth, but the professor that had them in her lab, even though they hadn't been turned on in a year or so, was aghast over my intended application and barred me from borrowing them.
What you proposed isn't that far-fetched, as I ended up having to contrive and implement the equivalent of this, i.e., passive, automated estimation of body shape under clothing, either from a single image or from multiple video frames, for some work I did in action recognition that required a fairly accurate representation of the person's proportions. Others, e.g., A. O. Balan and M. J. Black, "The naked truth: Estimating body shape under clothing," in Proceedings of the European Conference on Computer Vision (ECCV), 2008, pp. 15–29, have come up with solutions too.
Unless you are even older then me, I call bullshit.
I matriculated when I was fourteen, about two years before the turn of the second millennium, and finished both degrees before I turned twenty. Despite starting early, I was far from the youngest graduate, as one of my peers managed to complete an S.B./M.Eng. CS by the time he was sixteen.
In any event, in both my situation and his, let alone those of others I have encountered, we all had little prior experience dealing with electronics and computers yet plenty of natural aptitude for and budding interest in the subject. In my case, I was fascinated, and still am, about the possibility of furthering statistical machine vision and managed to find the perfect adviser to not only spur my creativity, but also put up with my astounding initial ignorance. In his, he wanted to advance computer graphics and wound up submitting some excellent, now heavily-cited papers to SIGGRAPH and Eurographics.
It's hard to believe that he could really be that oblivious to how the real world works.
There are more than a handful of people who grow up in affluence or are sheltered most of their lives from the denizens of seedy places that might prey on others. Ergo, they have little recourse, mostly in the form of previous experience or tales from their associates, to guide them in such matters.
I know that, in my case, it was not immediately apparent that I was a potential drug mule target, when I was accosted, late one evening, by a buxom, beautiful, crying woman in Ybor City. The only factors that ultimately saved me from helping her were that: (i) I had never been anywhere near the Central/South Florida area and hence was lost looking for a sushi restaurant at which I was to meet some fellow research conference attendees and (ii) I was incredibly late due to having canvassed the area on foot several times without finding the restaurant.
If your [sic] going into college and you haven't coded anything yet, give up on CS or EE. You can likely do both, but you will never be really good. You don't love it enough. You better be open to being a better coder though.
For EE I'd raise the bar some more. If you don't already know how to use basic bench equipment don't go into EE.
What a crock of shit. I hadn't programmed or played around with circuits before heading to university, yet managed to leave, the first time around, with an S.B./S.M. EECS, either sole or first authorship on more than ten top-tier journal papers, a handful of patents, and more than enough money on which to retire from having worked at and propped up a start-up company.
For those who might come across HornWumpus' comment, do not, even for a brief moment, feel discouraged. Anyone, regardless of his or her background, can go into EE or CS and make fantastic contributions to either field. All that ultimately matters is finding the right environment to nurture your innate talents, the tenacity to see your ideas come to fruition, and the willingness to learn, even if it takes more than one try.
Developers/publishers need to fight back against pre-owned, as game retailers really started to take the piss, and it's really been hurting the people who make the games. [...] This directly hurts publishers and developers, who need the new sales and make no revenue from pre-owned. Publishers have been way to slow and scared to respond, they should have clamped down much earlier.
By this logic, you should be all for contractors demanding and receiving a percentage of the sale price for any building they constructed, car companies forbidding the use of any second-hand vehicle, and all other sorts of wonderful nonsense.
Well, that's fine. The interns don't have any useful skills anyway, they're not even up to the level of entry-level fresh grad. And 99.9% of them think programming is all about social apps or other web sites. If they go somewhere else to get trained at someone else's expense then there's no problem. Interns are a major pain to hire, you have to hand hold them the entire time because they have little idea how a corporation works, how their computer works, how to work independently without bothering everyone else. Or you get an EE intern doing a job requiring some programming and you have to waste time telling them why their program doesn't compile.
I interned at a start-up while working toward my S.B. EE/dual Ph.D. and left a self-made millionaire before completing the latter due, in no small part, to all of the contributions I had made, ideas I handed out, and so forth; one of the other interns there, who was also from my alma mater and working toward her Ph.D., also left a millionaire for the same reasons. Suffice to say, your comment about interns being worthless and having no skills is utter nonsense. Moreover, I'm sure there are plenty of students from places like MIT, CMU, Cornell, UIUC, Princeton, GaTech, Stanford, and Berkeley who could corroborate this assertion.
Slashdot Mirror
Doing any sort of large-scale computational fluid dynamics or finite element simulations may require a great many cores. For example, you might want to conduct a very detailed simulation of the air flow around a vehicle, airplane, structure, etc. to have a basic understanding of its aerodynamics before spending time and money testing an actual prototype in a wind tunnel. You might also want to look at how very complicated, soft-body structures deform due to a variety of external stimuli. Such information would be crucial for certain materials science applications. Chemical reaction and acoustic simulations may also require a great deal of computing power, especially if you want to have a high spatio-temporal resolution.
Essentially, there are plenty of physical and theoretical science applications that can benefit from massive processing capabilities. There is a lot of fundamental science that is also performed in simulation before any actual tests occur.
I spoke about engineers in general. And as you know, as someone who apparently lives at the end of a bell curve, when speaking in general there are always edge-cases that can seemingly contradict the general statement being made, but that doesn't stop that statement from being true.
Your generalization would be true if I was just one of a handful of students who worked up to general engineering principles from rudimentary physics knowledge. However, I can point to hundreds of my peers at MIT who did the same thing, many of whom likely have a much deeper understanding than I do. Given my exposure to the curriculum at CalTech and Stanford, I feel rather confident in stating that engineering students at those schools weren't just given equations and told to memorize them. Instead, they slogged through a series of derivations of those principles and had to build up their own understanding of the meaning behind those derivations. I'm sure that others can chime in about their experiences at other top-tier institutions, such as Berkeley, CMU, and the Ivies.
As an aside, undergraduate research assistantships are becoming more commonplace at some institutions. I agree that most undergraduates will probably not come out publishing papers in prestigious journals or conferences. However, that does not mean that they don't enhance their knowledge and understanding of various concepts.
In short, there are thousands, if not tens of thousands, of engineers out there with educational experiences that either partly or fully mirror my own. Consequently, you really need to be cautious when you make sweeping generalizations like engineers only spend their time memorizing formulas without reflecting on how those formulas came to be.
That's because engineers are not smart, they're dogmatic. They spend their entire university career learning formulas and recipes (excuse me, algorithms) without questioning them the way physicists or philosophers do. They spend the time, and they know their science, but they don't know why what they know is right, they just know that what they know IS right. [...] And because they only learn the results, not the history and argumentation that led up to the result, they're not as well prepared to deal with the barrage of idiocy that is spewed by people like anti-vaxxers.
There are plenty of incorrect assertions and generalizations made in this post. It honestly reads like a dogmatic diatribe.
As EE/CS undergraduate students, my classmates and I learned the fundamental physics behind various phenomena, not just the high-level equations. That is, we learned why, for example, transistors function they way that they do and why we can rely on simplified equations to characterize their behavior. Most of what we were taught is still covered in the MIT undergraduate curriculum (see courses 6.002, 6.012, 8.012, 8.04, and 8.044).
As EE/CS graduate students, my lab partners and I were responsible for furthering the state of the art. During these years, we had to understand why, for example, our experimental results diverged from our model predictions and how to revise those models accordingly. In some cases, we invalided long-standing, widely taught models and proposed new ones. If we didn't understand the fundamental physics behind these models, we wouldn't have made the contributions that we did. We also wouldn't have had our work published in Science, Nature, and PNAS.
I don't even need to lengthily address your comment that engineers aren't smart. There are plenty of people on Slashdot that can thoroughly invalidate that claim.
God, you're an entitled prick. As far as arguments for not paying for software goes, your [argument] is by far one of the stupidest.
The child poster who first replied to your comment was not me, the parent poster.
To expand upon my original comment: I am not interested in paying for and using software that is tied to platforms and services that I do not want or need. In my opinion, Origin is a good example of such a platform for two reasons. The first is that it is a glorified game-launcher application. If I've purchased a physical copy of the game, I should not need to install and use Origin to simply run the game, especially if its integration with Origin is minimal. Secondly, Origin is a digital storefront dedicated solely to a small catalog of EA products.
In contrast, I find platforms like Steam to be useful. For the most part, I'm able to launch and play games outside of the Steam service. As well, Steam offers a broad selection of products from a number of publishers. The fact that they offer massive sales throughout the year is also appealing, though tangential to the discussion.
Since EA has refused to release any of its newer games on Steam or other distribution platforms, there four options: (i) don't play the game, (ii) pirate the game and use a crack to get around the Origin requirement, (iii) pay for the game and crack it to get around the Origin requirement, or (iv) pay for the game and install/use Origin. Option (iv) is unappealing, as I do not wish to use Origin. Option (iii) is the one with the best intent; however, it is an unlawful choice due to circumventing the application protections. Moreover, in giving money to EA, I am reinforcing their use of Origin. Option (ii) is also unlawful. In this case, there are three possible side effects: (i) EA starts more tightly integrating their games with Origin, making cracking much more difficult or impossible, (ii) EA stops targeting computer gamers, or (iii) EA opens up their catalog to compensate for lost sales. This last side effect, while appealing, is unlikely.
Since EA started bundling their games with Origin, I have consistently chosen option (i) and will continue to do so in the future. If I had an overwhelming desire to play the game, which is not likely to happen, I would either go with option (ii) or an altered version of option (iii). I don't disagree with your assertion that this is an entitled viewpoint. However, it is not one on which I have acted.
You're not in IT, then, because they're salaried. No extra pay for extra hours.
You're correct: I'm currently not a salaried employee. I also hope to never be salaried again, let alone work for a company that bars me from overtime simply because I'm considered a "computer professional" in the eyes of the government.
As an aside, I can definitely empathize with those who are salaried employees. I had to deal with being labeled a salaried employee all throughout graduate school, despite my contract saying otherwise, and basically miss out on $100k to $125k/year (USD) in overtime; pretty much everyone else in the EECS department was in a similar situation. Suffice to say, when I had the chance to join a start-up company as a fairly compensated employee, I jumped at the opportunity.
The whole image of the 60 hour a week death-marching 'murican worker is a fiction.
When I was a graduate student, a 50- to 60-hour work week was basically a vacation, given that I routinely put in 70 to 85 hours per week. Moreover, it wasn't unheard of for students to basically not leave the lab for an entire week, let alone only sleep 5 hours per day on a couch during that time, while some important experiment was being conducted.
Nowadays, a 60-hour work week is the norm for me, and I've come to enjoy it. I have around three "productive" days where I work a total of 39 hours, two "semi-productive" days where I work a total of 18 hours, and an additional 3 hours that I spread out over the week for administrative tasks and meetings. While it would be nice to cut back to just 40 hours per week, I nearly double my salary by working those additional 20 hours.
The base Model S is $69,990 (USD) according to Tesla's website and Wikipedia, not $35,000 to $40,000 (USD). With federal tax credits, the base price comes down to $63,570 (USD). With state incentives, it becomes a bit more difficult to qualify the final price: essentially, you can either get a $2,500 (USD) rebate (California), a $6,000 (USD) income tax credit (Colorado), a $5,000 (USD) income tax credit (Georgia), or a $4,000 (USD) rebate for the car and a $3,000 (USD) rebate to offset the cost of electric vehicle charging stations (Illinois).
Considering what I paid for the Model S P85+, I do wish that the base price had been as low as what you originally claimed.
As an academic, part of the problem with starting wonderful open journals and conferences is the fact that there are very few incentives for us to spend our time to build up the reputation of the publication. Although being editor-in-chief or associate editor of a journal is nice to have for a tenure review, some universities weight it less than the number of publications produced, the prestige of the publication venue, how many students you have advised, how much grant money has been brought to the university, and how much publicity your work has received. Since so many of my colleagues are focused on maximizing these metrics, they have very little time for much else when starting their careers. Moreover, even when they have tenure, they still have to chase grant money to sponsor all of the students in their labs; when I was in graduate school, my adviser seemed to be flying around every two or three weeks to meet with program managers to get even more money.
Another item of note is that it is much easier to get support to start a conference if you align yourself with one of the major academic publishers, e.g., IEEE or Springer. Provided you can meet your attendance quota, these publishers provide much of the infrastructure and initial funding to host such events.
If you're using Word or OpenOffice, that might be a problem. If you're using LaTeX, it's not, provided that you're a reasonably quick typist and have memorized the standard mathematical commands. I ended up typing all of my lecture notes for my statistics Ph.D. classes without much of a hassle. In fact, most of the students in my classes came to me for portions of my lecture notes, as I was able to capture all of the important comments that the professors would make in haste while continuing on with a derivation or proof.
As for a comment on the article, since very little information was given about their testing protocols there may be some inherent bias in their findings. Specifically, their testing methodology seems to hinge on showing that short-term conceptual recall rates decrease when using laptops. That is, the authors don't bother addressing long-term retention and generalization.
As an actual researcher, let me state that your post has little to no bearing on reality. That is, open-access journals do not prevent an individual or group of individuals from artificially inflating various publication metrics. Moreover, agencies look at much more than those metrics, e.g., research output, research impact, past publication venues, and the number of students who are supported and are expected to graduate under a grant, when deciding how to dole out funding.
All that's missing is some mention of hosts files.
In an age where you can patent a rectangle, is it really about innovation anymore?
I just wanted to notify you, informally, that you've infringed upon my patent that details a process for complaining about patents. I'll make sure that my lawyers send you the appropriate notice paperwork by the end of next week.
Actual research is a wholly unintended side effect of academia. Only naive fools even attempt real research and inevitably fail.
Come tomorrow, I guess I should stop by the Department Chair's office and let him know that he should revoke my endowed scholar position, let alone the positions of my colleagues, as we're all apparently fools.
Mac is also not very stable with heavy applications like photoshop, after effects, 3dsmax, etc.
I chuckled heartily over this, especially considering that Autodesk hasn't released a native 3DS Max binary for OS X.
Good, their work is best done by private contractors anyway.
Private entities rarely, if at all, focus a majority of their efforts into pure research, unlike the national labs. Funding pure research, which is one of the few actions that the US Government at least does halfway correctly, is ultimately essential if we are to progress the state of the art and thus create new fields and products that are ripe for commercialization.
It's also important to remember, as in any major discipline, that mathematics has numerous components, some of which aren't commodious for many real-world problems; as such, it could take a fair amount of time to train someone so that they would be able to make a worthwhile contribution.
As one example, I have a friend and colleague who focused entirely on abstract algebraic topics for his research and enrolled in an ordinate number of analysis, topology, and algebra classes whilst eschewing ones deemed more practical, like those dealing with differential equations, optimization, numerical analysis, and applied probability; further, despite graduating from an Ivy League institution, let alone being incredibly smart, he has yet to find employment, as most of his knowledge does not translate well to solutions for any of the burgeoning fields, such as data analysis, computer vision, or robotics/autonomous systems. Consequently, in order to even consider a position out in industry, he's looking at spending the next two years diving into a sea of applied math.
I'm normally not one for coarse language and insults, but, given that the atypical neurogenic tic disorder that the individual suffers from can lead to both life-threatening asphyxia and tachycardia, I would have to say that you are a massively apathetic twat. I hope that you never become afflicted by any debilitating condition, let alone wind up in a similar situation and encounter someone insouciant who denies you access to medicine or necessary sustenance, as I doubt you'd have the fortitude to stand up to your ilk.
Fortunately, your pococurante attitude served some purpose beyond broadcasting your own inadequacies: it spurred me to pledge several thousand dollars for this guy's legal fund.
As you noted, the project was fun to undertake, even though it was only a sub-component to a much larger endeavor. I may yet go back, visit it, and submit an extension as a nice stand-alone article.
To answer your questions, though, I relied on a pool of around seventy subjects, equally distributed across genders and with a tri-modal distribution for age, many of whom were nudists that had heard about the data collection through some friends of mine. I also had a couple of adventurous fellow students and peers sign up to contribute; even my girlfriend at the time had no qualms about being filmed.
In any event, while there was some inherent selection bias in who I chose, mainly because I needed footage of as many different body types as I could capture, so as to allow the underlying model to generalize well, I do admit to being elated whenever people with certain body types were incredibly eager to help. Granted, I did, at the later stages, have to turn some people away, since I was spending too much time acquiring data.
For the experiments themselves, people had multiple options for what to wear for the various training phases, aside from the different changes of loose- and tight-fitting clothes that I'd ask them to bring and don. I did my best to provide multi-sex body suits of different sizes, which provided more than sufficient constraints when coupled with manually-derived measurements of quantities such as chest circumference, stomach circumference, and so forth. Others opted to strip down to their undergarments and a fair amount, surprisingly many of them women, wore nothing at all.
Regardless of what they wore or didn't wear, each subject executed a series of actions, such as walking, sitting down, standing up, skipping, and climbing. I used six pairs of stereo vision cameras to record the events. I had hoped to use Vicon cameras for the ground truth, but the professor that had them in her lab, even though they hadn't been turned on in a year or so, was aghast over my intended application and barred me from borrowing them.
What you proposed isn't that far-fetched, as I ended up having to contrive and implement the equivalent of this, i.e., passive, automated estimation of body shape under clothing, either from a single image or from multiple video frames, for some work I did in action recognition that required a fairly accurate representation of the person's proportions. Others, e.g., A. O. Balan and M. J. Black, "The naked truth: Estimating body shape under clothing," in Proceedings of the European Conference on Computer Vision (ECCV), 2008, pp. 15–29, have come up with solutions too.
How long ago? How common were computers?
Unless you are even older then me, I call bullshit.
I matriculated when I was fourteen, about two years before the turn of the second millennium, and finished both degrees before I turned twenty. Despite starting early, I was far from the youngest graduate, as one of my peers managed to complete an S.B./M.Eng. CS by the time he was sixteen.
In any event, in both my situation and his, let alone those of others I have encountered, we all had little prior experience dealing with electronics and computers yet plenty of natural aptitude for and budding interest in the subject. In my case, I was fascinated, and still am, about the possibility of furthering statistical machine vision and managed to find the perfect adviser to not only spur my creativity, but also put up with my astounding initial ignorance. In his, he wanted to advance computer graphics and wound up submitting some excellent, now heavily-cited papers to SIGGRAPH and Eurographics.
It's hard to believe that he could really be that oblivious to how the real world works.
There are more than a handful of people who grow up in affluence or are sheltered most of their lives from the denizens of seedy places that might prey on others. Ergo, they have little recourse, mostly in the form of previous experience or tales from their associates, to guide them in such matters.
I know that, in my case, it was not immediately apparent that I was a potential drug mule target, when I was accosted, late one evening, by a buxom, beautiful, crying woman in Ybor City. The only factors that ultimately saved me from helping her were that: (i) I had never been anywhere near the Central/South Florida area and hence was lost looking for a sushi restaurant at which I was to meet some fellow research conference attendees and (ii) I was incredibly late due to having canvassed the area on foot several times without finding the restaurant.
If your [sic] going into college and you haven't coded anything yet, give up on CS or EE. You can likely do both, but you will never be really good. You don't love it enough. You better be open to being a better coder though.
For EE I'd raise the bar some more. If you don't already know how to use basic bench equipment don't go into EE.
What a crock of shit. I hadn't programmed or played around with circuits before heading to university, yet managed to leave, the first time around, with an S.B./S.M. EECS, either sole or first authorship on more than ten top-tier journal papers, a handful of patents, and more than enough money on which to retire from having worked at and propped up a start-up company.
For those who might come across HornWumpus' comment, do not, even for a brief moment, feel discouraged. Anyone, regardless of his or her background, can go into EE or CS and make fantastic contributions to either field. All that ultimately matters is finding the right environment to nurture your innate talents, the tenacity to see your ideas come to fruition, and the willingness to learn, even if it takes more than one try.
A 4.0 from MIT might help when securing an interview for Google but most places are more concerned about your ability to reliably deliver. [...]
As an aside, MIT has a 5.0 scale, not a 4.0 one: http://web.mit.edu/registrar/gpacalc.html
Developers/publishers need to fight back against pre-owned, as game retailers really started to take the piss, and it's really been hurting the people who make the games. [...] This directly hurts publishers and developers, who need the new sales and make no revenue from pre-owned. Publishers have been way to slow and scared to respond, they should have clamped down much earlier.
By this logic, you should be all for contractors demanding and receiving a percentage of the sale price for any building they constructed, car companies forbidding the use of any second-hand vehicle, and all other sorts of wonderful nonsense.
Well, that's fine. The interns don't have any useful skills anyway, they're not even up to the level of entry-level fresh grad. And 99.9% of them think programming is all about social apps or other web sites. If they go somewhere else to get trained at someone else's expense then there's no problem. Interns are a major pain to hire, you have to hand hold them the entire time because they have little idea how a corporation works, how their computer works, how to work independently without bothering everyone else. Or you get an EE intern doing a job requiring some programming and you have to waste time telling them why their program doesn't compile.
I interned at a start-up while working toward my S.B. EE/dual Ph.D. and left a self-made millionaire before completing the latter due, in no small part, to all of the contributions I had made, ideas I handed out, and so forth; one of the other interns there, who was also from my alma mater and working toward her Ph.D., also left a millionaire for the same reasons. Suffice to say, your comment about interns being worthless and having no skills is utter nonsense. Moreover, I'm sure there are plenty of students from places like MIT, CMU, Cornell, UIUC, Princeton, GaTech, Stanford, and Berkeley who could corroborate this assertion.