An anonymous reader writes "Going beyond the usual soundbites about Ada Lovelace, Amy Jollymore explores the life of the worlds first programmer: 'When I heard that Ada Lovelace Day was coming, I questioned myself, "What do I actually know about Ada Lovelace?" The sum total of my knowledge: Ada was the first woman programmer and the Department of Defense honored her contributions to computation in 1979 by naming its common programming language Ada.
A few Ada biographies later, I know Augusta Ada Lovelace to be an incredibly complex woman with a painful life story, one in which math, shame, and illness were continuously resurfacing themes. Despite all, Ada tirelessly pursued her passion for mathematics, making her contributions to computing undeniable and her genius all the more clear. Her accomplishments continue to serve as an inspiration to women throughout the world.'"

Okian Warrior writes "As a followup to Linus's opinion about people skeptical of the Linux random number generator, a new paper analyzes the robustness of /dev/urandom and /dev/random . From the paper: 'From a practical side, we also give a precise assessment of the security of the two Linux PRNGs, /dev/random and /dev/urandom. In particular, we show several attacks proving that these PRNGs are not robust according to our definition, and do not accumulate entropy properly. These attacks are due to the vulnerabilities of the entropy estimator and the internal mixing function of the Linux PRNGs. These attacks against the Linux PRNG show that it does not satisfy the "robustness" notion of security, but it remains unclear if these attacks lead to actual exploitable vulnerabilities in practice.'" Of course, you might not even be able to trust hardware RNGs. Rather than simply proving that the Linux PRNGs are not robust thanks to their run-time entropy estimator, the authors provide a new property for proving the robustness of the entropy accumulation stage of a PRNG, and offer an alternative PRNG model and proof that is both robust and more efficient than the current Linux PRNGs.

An anonymous reader writes "According to Wired, 'Today's big data is noisy, unstructured, and dynamic rather than static. It may also be corrupted or incomplete. ... researchers need new mathematical tools in order to glean useful information from the data sets. "Either you need a more sophisticated way to translate it into vectors, or you need to come up with a more generalized way of analyzing it," [Mathematician Jesse Johnson] said. One such new math tool is described later: "... a mathematician at Stanford University, and his then-postdoc ... were fiddling with a badly mangled image on his computer ... They were trying to find a method for improving fuzzy images, such as the ones generated by MRIs when there is insufficient time to complete a scan. On a hunch, Candes applied an algorithm designed to clean up fuzzy images, expecting to see a slight improvement. What appeared on his computer screen instead was a perfectly rendered image. Candes compares the unlikeliness of the result to being given just the first three digits of a 10-digit bank account number, and correctly guessing the remaining seven digits. But it wasn't a fluke. The same thing happened when he applied the same technique to other incomplete images. The key to the technique's success is a concept known as sparsity, which usually denotes an image's complexity, or lack thereof. It's a mathematical version of Occam's razor: While there may be millions of possible reconstructions for a fuzzy, ill-defined image, the simplest (sparsest) version is probably the best fit. Out of this serendipitous discovery, compressed sensing was born.'"

New submitter Norwell Bob sends this excerpt from an Associated Press report: "It's long been known that America's school kids haven't measured well compared with international peers. Now, there's a new twist: Adults don't either. In math, reading and problem-solving using technology – all skills considered critical for global competitiveness and economic strength – American adults scored below the international average on a global test, according to results (PDF) released Tuesday."

KentuckyFC writes "The idea that every physical event is a computation has spread like wildfire through science. That has triggered an unprecedented interest in unconventional computing such as quantum computing, DNA computing and even the ability of a single-celled organism, called slime mold, to solve mazes. However, that may need to change now that physicists have worked out a formal way of distinguishing between systems that compute and those that don't. One key is the ability to encode and decode information. 'Without the encode and decode steps, there is no computation; there is simply a physical system undergoing evolution,' they say. That means computers must be engineered systems based on well understood laws of physics that can be used to predict the outcome of an abstract evolution. So slime mold fails the test while most forms of quantum computation pass."

Phopojijo writes "OpenGL and DirectX have been the dominant real-time graphics APIs for decades. Both are catalogs of functions which convert geometry into images using predetermined mathematical algorithms (scanline rendering, triangles, etc.). Software rendering engines calculate colour values directly from the fundamental math. Reliance on OpenGL and DirectX could diminish when GPUs are utilized as general 'large batches of math' solvers which software rendering engines offload to. Developers would then be able to choose their algorithms for best suits their project, even native to web browsers with the upcoming WebCL."

pacopico writes "About 30 years ago, a young Marine and math savant named Ramona Pierson was out for a run when she got hit by a drunk driver and had her body shattered. As Businessweek reports, Pierson ended up in coma for 18 months, came out blind and emaciated and was sent to live in an old folks home. Her remarkable story takes off from there to include bike racing through Russia, a PhD in neuroscience, a stint fixing Seattle's public schools, and now Declara, a social network run by Pierson and funded by billioniare Peter Thiel, who put the original money into Facebook. One of the more original start-up tales to have ever come out of Silicon Valley or really anywhere."

nbauman writes "According to Gina Kolata in the New York Times, The Institute of Education Sciences in the Department of Education Sciences, U.S. Department of Education, has supported 175 randomized controlled studies, like the studies used in medicine, to find out what works and doesn't work, which are reported in the What Works Clearinghouse. Surprisingly, the choice of instructional materials — textbooks, curriculum guides, homework, quizzes — can affect achievement as much as teachers; poor materials have as much effect as a bad teacher, and good materials can offset a bad teacher's deficiencies. One popular math textbook was superior to 3 competitors. A popular computer-assisted math program had no benefit. Most educators, including principals and superintendents, don't know the data exists. 42% of school districts had never heard of the clearinghouse. Up to 90% of programs that seemed promising in small studies had no effect or made achievement scores worse. For example a program to increase 7th-grade math teachers' understanding of math increased their understanding but had no effect on student achievement. Upward Bound had no effect."

cartechboy writes "Lets just say Elon Musk may need to go battery shopping, like, big-time. Here's some little-understood Tesla math that could turn the global market for cylindrical lithium-ion cells upside down by 2015. It turns out the massive Model S battery takes almost 2,000 times the number of cells a basic laptop does. Assume Tesla just doubles production from its current 21K cars/year to 40K cars/year. (Something it expects to do by 2015). At that point, Tesla would require the *entire* existing global capacity for 18650 commodity cells. That assumes no other growth, no next gen model, nada. What should Elon do? Better get on the horn to Panasonic and Samsung."

theodp writes "Forget the dire predictions of a looming shortfall of scientists, technologists, engineers, and mathematicians, advises IEEE Spectrum contributing editor Robert Charette — the STEM crisis is a myth. In investigating the simultaneous claims of both a shortage and a surplus of STEM workers, Charette was surprised by 'the apparent mismatch between earning a STEM degree and having a STEM job. Of the 7.6 million STEM workers counted by the Commerce Department, only 3.3 million possess STEM degrees. Viewed another way, about 15 million U.S. residents hold at least a bachelor's degree in a STEM discipline, but three-fourths of them — 11.4 million — work outside of STEM.' So, why would universities, government, and tech companies like Facebook, IBM, and Microsoft cry STEM-worker-shortage-wolf? 'Clearly, powerful forces must be at work to perpetuate the cycle,' Charette writes. 'One is obvious: the bottom line. Companies would rather not pay STEM professionals high salaries with lavish benefits, offer them training on the job, or guarantee them decades of stable employment. So having an oversupply of workers, whether domestically educated or imported, is to their benefit...Governments also push the STEM myth because an abundance of scientists and engineers is widely viewed as an important engine for innovation and also for national defense. And the perception of a STEM crisis benefits higher education, says Ron Hira, because as 'taxpayers subsidize more STEM education, that works in the interest of the universities' by allowing them to expand their enrollments. An oversupply of STEM workers may also have a beneficial effect on the economy, says Georgetown's Nicole Smith, one of the coauthors of the 2011 STEM study. If STEM graduates can't find traditional STEM jobs, she says, 'they will end up in other sectors of the economy and be productive.'"

An anonymous reader writes "Professors at the Ohio State University are embracing MOOCs, with a Massive Open Online Calculus Course — it is completely open source; everything is on github. There is are free videos, free online assessment system, and a free textbook!"

ananyo writes "Facebook can lose a few users and remain a perfectly stable network, but where the national grid is concerned, simple geography dictates that it is always just a few transmission lines from collapse, according to a mathematical study of spatial networks. The upshot of the study is that spatial networks are necessarily dependent on any number of critical nodes whose failure can lead to abrupt — and unpredictable — collapse. The warning comes ten years after a blackout that crippled parts of the midwest and northeastern United States and parts of Canada. In that case, a series of errors resulted in the loss of three transmission lines in Ohio over the course of about an hour. Once the third line went down, the outage cascaded towards the coast, cutting power to some 50 million people. The authors say that this outage is an example of the inherent instability the study describes. But others question whether the team's conclusions can really be extrapolated to the real world. 'The problem is that this doesn't reflect the physics of how the power grid operates,' says Jeff Dagle, an electrical engineer at the Pacific Northwest National Laboratory in Richland, Washington, who served on the government task force that investigated the 2003 outage."

slew writes "Apparently none of the 24K+ students who sat for the 2013 Liberia University entrance exam got a passing mark, and fewer than a hundred managed to pass either the english (pass level 70%) or math (pass level 50%) sections required to qualify to be part of the normal class of 2k-3k students admitted every year... Historically, the pass rate has been about 20-30% and in recent years, the test has been in multiple-guess format to facilitate grading. The mathematics exam generally focuses on arithmetic, geometry, algebra, analytical geometry and elementary statistic and probability; while the English exam generally focuses on grammar, sentence completion, reading comprehension and logical reasoning. However, as a testament to the over-hang of a civil war, university over-crowding, corruption, social promotion, the admission criteria was apparently temporarily dropped to 40% math and 50% English to allow the provisional admission of about 1.6K students. And people are calling foul."

the_newsbeagle writes "Japanese researchers are trying to develop an artificial intelligence program that can pass the standardized test required of all college-bound high school students. Interestingly, the AI is showing good progress in the history portion of the exam, because it's fairly adept at looking up answers in a vast textual database. But the so-called Todai Robot is having trouble with math, 'because the questions are presented as word problems, which the Todai Robot must translate into equations that it can solve,' as well as with physics, which 'presumes that the robot understands the rules of the universe.' If the AI does succeed in mastering the general university exam, researchers will next tackle the notoriously difficult University of Tokyo entrance exam, which will require the bot to write essays."

A group of researchers from MIT and the University of Ireland has presented a paper (PDF) showing that one of the most important assumptions behind cryptographic security is wrong. As a result, certain encryption-breaking methods will work better than previously thought. "The problem, Médard explains, is that information-theoretic analyses of secure systems have generally used the wrong notion of entropy. They relied on so-called Shannon entropy, named after the founder of information theory, Claude Shannon, who taught at MIT from 1956 to 1978. Shannon entropy is based on the average probability that a given string of bits will occur in a particular type of digital file. In a general-purpose communications system, that’s the right type of entropy to use, because the characteristics of the data traffic will quickly converge to the statistical averages. ... But in cryptography, the real concern isn't with the average case but with the worst case. A codebreaker needs only one reliable correlation between the encrypted and unencrypted versions of a file in order to begin to deduce further correlations. ... In the years since Shannon’s paper, information theorists have developed other notions of entropy, some of which give greater weight to improbable outcomes. Those, it turns out, offer a more accurate picture of the problem of codebreaking. When Médard, Duffy and their students used these alternate measures of entropy, they found that slight deviations from perfect uniformity in source files, which seemed trivial in the light of Shannon entropy, suddenly loomed much larger. The upshot is that a computer turned loose to simply guess correlations between the encrypted and unencrypted versions of a file would make headway much faster than previously expected. 'It’s still exponentially hard, but it’s exponentially easier than we thought,' Duffy says."

holy_calamity writes "The two encryption systems used to secure the most important connections and digital files could become useless within years, reports MIT Technology Review, due to progress towards solving the discrete logarithm problem. Both RSA and Diffie-Hellman encryption rely on there being no efficient algorithm for that problem, but French math professor Antoine Joux has published two papers in the last six months that suggest one could soon be found. Security researchers that noticed Joux's work recommend companies large and small begin planning to move to elliptic curve cryptography, something the NSA has said is best practice for years. Unfortunately, key patents for implementing elliptic curve cryptography are controlled by BlackBerry."

sciencehabit writes "Lying in bed, unable to move a muscle, so-called locked-in patients have few ways to communicate with the outside world. But researchers have now found a way to use the widening and narrowing of the pupils to send a message, potentially helping these patients break the silence. The trick is a webcam-like setup that tracks pupil dilation. When people focus on a hard problem--say a math problem--their pupils dilate. Employing the approach, some locked-in patients could answer 'yes' and 'no' questions just by dilating their eyes."

raque writes "The NY Times recently published two op-eds in their Philosophy section, The Stone, discussing how Heisenberg's Uncertainty principle is abused. The second is a followup to the first. The author struggled to make clear his point and left the impression he was creating a strawman argument. In his followup he said he was avoiding equations because he was writing for a general audience. I replied to both articles, asking whether showing some basic equations would have worked better, allowing math to illustrate where metaphors struggled. Now I'm asking the same question to everyone on Slashdot. Would Dr. Callendar have been better off just diving in and dealing with Heisenberg and quantum mechanics using the tools that were developed for it?"

theodp writes "As noted earlier, Microsoft is tackling the CS education crisis with a popularity contest that will award $100K in donations to five technology education nonprofits that help make kids technically literate. Hopefully, the nonprofits will teach kids that the contest's voting Leader Board is a particularly good example of what-not-to-do technically. In addition to cherry-picking the less-pathetic vote totals to make its Leader Board, Microsoft also uses some dubious rounding code that transforms the original voting data into misleading percentages. Indeed, developer tools reveal that the top five leaders in the Microsoft STEM education contest miraculously account for 130% of the vote. Let's hope the quality control is better for those Microsoft Surface voting machines!"

knorthern knight writes "Most major weather services (US NWS, Britain's Met Office, etc) have their own supercomputers, and their own weather models. But there are some models which are used globally. A new paper has been published, comparing outputs from one such program on different machines around the world. Apparently, the same code, running on different machines, can produce different outputs due to accumulation of differing round-off errors. The handling of floating-point numbers in computing is a field in its own right. The paper apparently deals with 10-day weather forecasts. Weather forecasts are generally done in steps of 1 hour. I.e. the output from hour 1 is used as the starting condition for the hour 2 forecast. The output from hour 2 is used as the starting condition for hour 3, etc. The paper is paywalled, but the abstract says: 'The global model program (GMP) of the Global/Regional Integrated Model system (GRIMs) is tested on 10 different computer systems having different central processing unit (CPU) architectures or compilers. There exist differences in the results for different compilers, parallel libraries, and optimization levels, primarily due to the treatment of rounding errors by the different software systems. The system dependency, which is the standard deviation of the 500-hPa geopotential height averaged over the globe, increases with time. However, its fractional tendency, which is the change of the standard deviation relative to the value itself, remains nearly zero with time. In a seasonal prediction framework, the ensemble spread due to the differences in software system is comparable to the ensemble spread due to the differences in initial conditions that is used for the traditional ensemble forecasting.'"