Criminals look to machine-learning to mount cyber attacks | SC Magazine UK

"Artificial intelligence will increasingly be used by hackers to create new forms of attack" says Rene Millman, SC Magazine UK.

Photo: Storyblocks.com

Cyber-criminals will use artificial intelligence and machine learning to outwit IT security and mount new forms of cyber-attacks, according to predictions made by McAfee.

Speaking at the launch of the IT security company's threats predictions report, launched at its MPower conference held in Amsterdam, McAfee chief scientist Raj Samani said in an interview that criminals will increasingly use machine learning to create attacks, experiment with combinations of machine learning and artificial intelligence (AI), and expand their efforts to discover and disrupt the machine learning models used by defender.

He said that machine learning will “help criminals to speak in a native language when carrying out a phishing attack”. This would improve their social engineering—making phishing attacks more difficult to recognise.

In response, those charged with defending IT infrastructure will need to combine machine learning, AI, and game theory to probe for vulnerabilities in both software and the systems they protect, to plug holes before criminals can exploit them.

Samani also predicted that ransomware will evolve from its main purpose of extortion to something different.

“The growth of ransomware has been much discussed. But in reality, it has blended and morphed into something else. Threat vectors can be a smoke screen. Ransomware [in some attacks] was used to distract the IT department. What we see is a growth of pseudo-ransomware.”

He added that whatever the attack may be, “we'll always be able to tell the motivation, but not immediately”. This distraction attack will be done in much the same way as DDoS attacks have been used to obscure other real aspects of attacks. These could be “spectacular” proof-of-concept with the aim of engaging large organisation with mega-extortion demands in future.
Read more... 

Source: SC Magazine UK

The (virtual) reality of training | Offshore Technology

Lloyd’s Register has developed a Virtual Reality (VR) Safety Simulator to help support training and knowledge transfer in the energy industry and illustrate the need for a continued focus on safety and risk assessment. Patrick Kingsland spoke to LR’s VP of Marketing and Communications, Peter Richards and Global Academy Training Manager, Luis De La Fuente, about how it works.

With VR we can bring some of that hands-on practical experience into the classroom.
Photo: Offshore Technology

Patrick Kingsland: What are the key challenges the offshore industry faces today in terms of safety training? 

Luis De La Fuente: The oil and gas industry is very cyclical. During downturns you have skilled people leaving and companies can be left with a knowledge gap with only a handful of experienced people. Challenging times often result in less training as training budgets get reduced or are transferred elsewhere. During boom periods you often get a sudden influx of new talent who are often less experienced. And some of the more skilled personnel who were let go during the downturn leave the industry and decide not to come back. This means you lose quite a bit of hands-on knowledge and experience. For us, the whole goal is to work out how to reduce that learning gap, and get a person to a competent, senior level in as short amount of time as possible.

PK: How could virtual reality help reduce that learning gap in your opinion? 

LF: Well one good way is to introduce as much theory as possible so that when staff get onto the job sites they are familiar with what they are doing. But you still have a gap there between theory and practice. With VR we can bring some of that hands-on practical experience into the classroom without necessarily having to put guys out there where it’s more dangerous.

Peter Richards: It’s about making the training environment more immersive so that you can really start to understand the potential hazards you are going to be exposed to. VR also provokes a reaction from individuals on the implication their actions will have in an offshore environment. And because it’s interactive people are coming away from our VR experience and actually talking about safety training in a positive way. Bear in mind this is not a subject that generally generates that level of enthusiasm.

PK: How has VR technology improved over the past few years and where did you look for inspiration?  

PR: I think we’re now at a stage where VR is at a tipping point. The technology has got a lot better and the cost has come down. It’s more viable to look at it as a realistic mainstream application as opposed to where I think we were four years ago when everybody was talking about virtual reality but it was really just an overgrown 3D video.

During this gestation period we were closely following the technology to see how it was developing. In conjunction with a number of agencies we looked at gaming technology in particular. The hardware we are now using deploys handsets as well as head-sets. This gives us the ability to interact more with the environment as opposed to the initial development of VR which was just a headset.
Read more... 

Source: Offshore Technology

Anderson University to offer minor in coding through partnership with Apple | Anderson Independent Mail

Follow on Twitter as @gsilvarole

"Through its partnership with Apple as an Apple Distinguished School, AU is adopting the tech giant's Everyone Can Code curriculum" inform Georgie Silvarole, Anderson Independent Mail.  

Anderson University is a is a comprehensive Christian university offering bachelors, masters and doctoral degrees on campus, in Greenville and online. A photo taken on Nov. 27, 2017 shows AU's Alumni Lawn awash in late-afternoon sunlight.
Photo: Georgie Silvarole

Beginning next semester, Anderson University will offer students the chance to pursue a minor in computer coding.

Through its partnership with Apple as an Apple Distinguished School, Anderson University is adopting the tech giant's "Everyone Can Code" curriculum, the university said in a news release. 

The minor, which is open to all students pursuing any major, will focus on iOS app design, web management, computer coding and product development, according to the release. 

The curriculum — designed by AU's College of Arts and Sciences, AU's Center for Innovation and Digital Learning and Apple engineers — is geared toward equipping students with skills in information technology and software development through coding and app creation experience, according to the release.

“We believe this opportunity will allow us to do something truly unique in liberal arts education,” AU President Evans Whitaker said in the release. “Our goal is to fully prepare our students for their careers, and having them learn a marketable and highly sought-after skill like coding will help them in whatever field they choose.”

Read more... 

Source: Anderson Independent Mail

UNL is working to improve computer science education in schools | NTV

"The University of Nebraska-Lincoln's College of Education and Human Sciences is partnering with Code.org to improve computer science education for Nebraska K-12 students" reports KHGI Nebraska TV. 

Computer
Photo: MGN

The university is joining a nationwide network of regional partners that provide high-quality professional development to K-12 educators through local school district collaborations and work to build local communities of computer science educators statewide.

"The goal of our regional partnership with Code.org is to establish the university as a regional hub for K-12 computer science," said Guy Trainin, professor in the Department of Teaching, Learning and Teacher Education. "We will use our existing strong relationships with school districts and educators across the state to build the knowledge and capacity of K-12 teachers so they can better teach computer science to their students."

According a press release from UNL, the Code.org regional partnership will be part of the department's Tech EDGE program, which Trainin directs. Through Tech EDGE, Trainin has posted more than 300 video podcasts and hosted 20 conferences to help teachers bring technology instruction to their classrooms.

As a regional partner, Tech EDGE will leverage its expertise in hosting professional learning workshops for K-12 educators. Through the partnership, the university will host a number of daylong computer science workshops, a five-day summer experience for educators, and workshops for counselors and administrators of teachers participating or interested in Code.org professional learning programs.
Read more...

Source: NTV

Scaling Deep Learning for Science | Newswise

The DOE Science News Source is a Newswise initiative to promote research news from the Office of Science of the DOE to the public and news media.

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Photo: Jonathan Hines

"ORNL-designed algorithm leverages Titan to create high-performing deep neural networks" writes Jonathan Hines, Science writer at Oak Ridge National Laboratory.

Inspired by the brain’s web of neurons, deep neural networks consist of thousands or millions of simple computational units. Leveraging the GPU computing power of the Cray XK7 Titan, ORNL researchers were able to auto-generate custom neural networks for science problems in a matter of hours as opposed to the months needed using conventional methods.
Photo: iStock

Deep neural networks—a form of artificial intelligence—have demonstrated mastery of tasks once thought uniquely human. Their triumphs have ranged from identifying animals in images, to recognizing human speech, to winning complex strategy games, among other successes.

Now, researchers are eager to apply this computational technique—commonly referred to as deep learning—to some of science’s most persistent mysteries. But because scientific data often looks much different from the data used for animal photos and speech, developing the right artificial neural network can feel like an impossible guessing game for nonexperts. To expand the benefits of deep learning for science, researchers need new tools to build high-performing neural networks that don’t require specialized knowledge.

Using the Titan supercomputer, a research team led by Robert Patton of the US Department of Energy’s(DOE’s) Oak Ridge National Laboratory (ORNL) has developed an evolutionary algorithm capable of generating custom neural networks that match or exceed the performance of handcrafted artificial intelligence systems. Better yet, by leveraging the GPU computing power of the Cray XK7 Titan—the leadership-class machine managed by the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility at ORNL—these auto-generated networks can be produced quickly, in a matter of hours as opposed to the months needed using conventional methods.

The research team’s algorithm, called MENNDL (Multinode Evolutionary Neural Networks for Deep Learning), is designed to evaluate, evolve, and optimize neural networks for unique datasets. Scaled across Titan’s 18,688 GPUs, MENNDL can test and train thousands of potential networks for a science problem simultaneously, eliminating poor performers and averaging high performers until an optimal network emerges. The process eliminates much of the time-intensive, trial-and-error tuning traditionally required of machine learning experts.

“There’s no clear set of instructions scientists can follow to tweak networks to work for their problem,” said research scientist Steven Young, a member of ORNL’s Nature Inspired Machine Learning team. “With MENNDL, they no longer have to worry about designing a network. Instead, the algorithm can quickly do that for them, while they focus on their data and ensuring the problem is well-posed.”

Pinning down parameters  
Inspired by the brain’s web of neurons, deep neural networks are a relatively old concept in neuroscience and computing, first popularized by two University of Chicago researchers in the 1940s. But because of limits in computing power, it wasn’t until recently that researchers had success in training machines to independently interpret data.

Today’s neural networks can consist of thousands or millions of simple computational units—the “neurons”—arranged in stacked layers, like the rows of figures spaced across a foosball table. During one common form of training, a network is assigned a task (e.g., to find photos with cats) and fed a set of labeled data (e.g., photos of cats and photos without cats). As the network pushes the data through each successive layer, it makes correlations between visual patterns and predefined labels, assigning values to specific features (e.g., whiskers and paws). These values contribute to the weights that define the network’s model parameters. During training, the weights are continually adjusted until the final output matches the targeted goal. Once the network learns to perform from training data, it can then be tested against unlabeled data.

Although many parameters of a neural network are determined during the training process, initial model configurations must be set manually. These starting points, known as hyperparameters, include variables like the order, type, and number of layers in a network.
Read more...

Source: Newswise (press release)

How you can help American students improve in science | Island Packet - Opinion

"Science fair projects are one of the best learning experiences a student can undertake. They have the potential to get students interested in science, engineering and mathematics" inform Chris Clayton, retired engineer.

Form left to right, judges Carolyn Ogren, Walt Ding and Scott Hamlin look over a science project...

Read more here: http://www.islandpacket.com/news/local/community/beaufort-news/article33407988.html#storylink=cpy

Photo: File

Every year, Beaufort County high school and middle school students compete in regional science fairs. The winners are eligible to enter the Intel International Science and Engineering Fair. This is an excellent way to earn significant prizes, qualify for scholarships, and distinguish a college application.

It is also important for America’s future. Today, America ranks 28th in the world for science and 35th for mathematics. If we are to maintain our competitive edge on the world stage, we have to put more emphasis on science — and science fairs are an especially motivating way to interest students.

The public and private schools in this area do emphasize the importance of science fairs and indeed lead the state in promoting student participation. The teachers involved are dedicated and spend many hours supporting their students in preparation for the competitions. It is essential that we as a community support the teachers and volunteers who give their time to foster scholastic excellence in the sciences.

Science fair projects are an important part of the learning process and develop analytical abilities and critical thinking. They provide the opportunity to interface with experienced experts in a wide range of scientific fields.

The fairs are supported by a nonprofit, volunteer organization called the Sea Island Regional Science Fairs. Its members spend many hours judging students projects. Most are retired professionals from the engineering, scientific and medical fields, with support from dedicated teachers...

...If you are interested in using your knowledge and experience to help stimulate the study of science and engineering in our schools, or if you know someone who may be interested, please email me at: claytonicx@gmail.com.

Prospective judges will be invited to attend an orientation meeting to provide details of judging criteria and protocols. I guarantee you will enjoy the experience.

The Coastal Discovery Museum is very of supportive, allowing us to use its facilities and helping us recruit new judges.

Please visit our web site at www.sciencefairsbftsc.org.
Read more...

Source: Island Packet

5 tips to overcome machine learning adoption barriers in the enterprise | TechRepublic - Innovation

Photo: Alison DeNisco Rayome

Alison DeNisco Rayome, Staff Writer for TechRepublic summarizes, "Machine learning offers a powerful computing tool, but most companies are not taking advantage of it, according to Deloitte."

Photo: iStockphoto/agsandrew

While machine learning offers advantages for nearly every industry, very few companies have actually adopted this artificial intelligence (AI) technology, and face several common barriers to entry, according to a new Deloitte report.

Less than 10% of executives said that their companies were investing in machine learning, according to a recent SAP survey, and many cite barriers to adoption including qualified staff, still-evolving tools and frameworks, and a lack of large datasets required to train algorithms. Many people also face the "black box" problem, in that they understand that machine learning models generate valuable information, but are reluctant to deploy them in production, because their inner workings are not immediately clear. 

To lower the barriers to entry, Deloitte researchers identified five "vectors of progress" that make it easier, faster, and less expensive to deploy machine learning in the enterprise:

1. Automate data science  
Developing machine learning solutions requires data science skills, a field in which practitioners are in large demand and short supply. However, as much as 80% of the work of data scientists can be fully or partially automated, according to Deloitte, including data wrangling, exploratory data analysis, feature engineering and selection, and algorithm selection and evaluation.

"Automating these tasks can make data scientists not only more productive but more effective," the report stated. A growing number of tools from both established companies and startups can help reduce the time required to execute a machine learning proof of concept from months to days, Deloitte noted. This also means augmenting data scientists' productivity, so that even with a talent shortage, enterprises can still expand their machine learning adoption.

2. Reduce the need for training data  
Training a machine learning model can require up to millions of data elements, and acquiring and labeling this data can be time consuming and costly for enterprises.

However, we've seen a number of techniques emerging for reducing the amount of training data required for machine learning. Some use synthetic data, generated with algorithms to mimic the characteristics of the real data, and have seen strong results: A Deloitte LLP team tested a tool that allowed it to build an accurate model with only a fifth of the training data previously required by synthesizing the remaining 80%. 
Read more...

Source: TechRepublic

How schools prepare the next generation to enter a digital workforce | Seattle Times

Provided by Microsoft Philanthropies 

Just four in 10 schools in the U.S. offer a computer science course, according to Code.org.

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When Sierra Acy was in high school she knew she was interested in computer science. Luckily, her high school was an exception in the U.S.— it offered computer science courses. “I took Intro Computer Science and the following year I took AP Computer Science,” Acy says.

Shuyi Ma works as a postdoctoral scientist at the Center for Infectious Disease Research in Seattle.
Photo: Courtesy of Center for Infectious Disease Research

Early on at Disney, Acy heard about a volunteer program where people working in the tech industry could go into high schools and help teach computer science courses, giving students a chance to interact with people who actually use the content they’re teaching every day and to help classroom teachers gain better understanding of the subject matter to improve the computer science offerings in the future. She leapt at the chance.

“During my high school experience, neither of the computer science courses I took were as well done or put together as they could have been,” she says. “As is the case a lot of the time, the teachers weren’t actually trained in the computer science industry or any of the technical aspects of the field, they were just kind of put into the position and told to go.”

Women who try AP Computer Science in high school are 10 times more likely to major in it in college, according to a 2007 research study by the College Board.

Acy is now volunteering approximately 10 hours a week, along with a small team of others at Disney, to co-teach the AP Computer Science course at Walla Walla High School in southeastern Washington through the TEALS (Technology Education and Literacy in Schools) program.

Kevin Wang founded TEALS in 2009. At the time, he had been volunteering part time as a computer science teacher at a Seattle high school in addition to his work as an engineer at Microsoft. “When I was sent to a College Board AP Computer Science workshop, I expected to meet a lot of other AP Computer Science teachers with a similar background to my own, but I was shocked to find that most of the other teachers were not computer science people at all. I was maybe the only computer science major there, the rest of these teachers had about four days to learn a college semester’s worth of computer science well enough to teach it, which is incredibly tough.”

Wang knew there were plenty of other computer science folks like him in the industry who could help these teachers, and students, have a more effective educational experience. So he decided to do something about it. Today, Wang runs TEALS full time, funded by Microsoft’s philanthropy arm. They’re operating in 348 schools in 29 different states and Washington, D.C. Here in Washington State, TEALS is partnered with 86 schools — that’s 10 percent of all Washington high schools.

Wang suggests that the reach is even further than those numbers suggest since the program is modeled to help get classroom teachers prepared to teach computer science on their own after two years of co-teaching with volunteers who know the material by heart.
Read more...

Source: Seattle Times  

Parents search for toys that make learning math, science fun | KGO-TV - Technology

Photo: Michael Finney

Toys that combine a STEM education with a child's fascination and imagination are gaining in popularity. As Michael Finney, 7 On Your Side Reporter and KGO Radio Host, reports, toymakers are counting on parents shelling out big bucks for their child's education.

Photo: Storyblocks.com

Playing with robots is only half the fun for UB Tech.

Its creators hope kids find building them is just as exciting.

"They can actually learn to assemble and build their own robot using 3D instructions," said Max Mai of UB Tech.

This computer kit from San Francisco-based Piper comes with hours worth of games.

But those games are just a means to an end.

"This is a computer kit that kids build themselves to learn about programming," said Tommy Gibbons of Piper.

Games such as these are gaining in popularity largely due to demand from parents.

"Right now everyone wants their kids to learn how to know how to build hardware," said Jeff Lee of Tech Bargains. "They want their kids to know how to build products, code. All in the hopes of getting their kids a better paying job."

Kids learn how to build robots by first snapping pieces into place on an animated model.

They then duplicate their efforts with the actual robot parts.
These robots can also be programmed to mimic various human emotions.
That's the expression of being angry, " said Mai as the Robot lowers his head and snaps its jaws.
Read more...

Source: KGO-TV

Learning to be a mentor | Science - From the Magazine

"My early experiences mentoring undergraduate students didn't go well. My first attempt came during the second year of my Ph.D." says Aditi Deshpande, scientist at Allena Pharmaceuticals in Newton, Massachusetts.
 

Photo: Robert Neubecker

I was still trying to learn some lab techniques myself, and I wasn't sure whether I would be able to invest the time needed to train a student. But I was interested in developing my mentoring skills, and my adviser encouraged me to give it a try. The student required hand-holding and close monitoring, and it quickly became evident that the collaboration wasn't working. After similar false starts with a few more students, I ended up being reluctant to work with undergraduate researchers at all—until a new student helped me realize what is required to mentor undergraduates, and the rewards it can bring.

“It has been a joy to watch Karina mature as an able scientist.”

I met Karina when she was a sophomore, and I ended up working with her until she defended her senior thesis. She was smart and eager to learn, asking all the right questions, and I felt she might finally be the right fit. Moreover, the timing was right. My experiences with previous undergraduates had prepared me to set appropriate expectations and gradually build on them. As a third-year student, I was also ready to delegate and give her room to grow. Here are the lessons that working with Karina taught me.

SHOW THE BIG PICTURE. 

Most undergraduates are completely new to research, so it is crucial to explain the broader context for the work and justify its importance. This will provide an overall goal, which will help get students interested and keep them focused as they learn the ropes. In my first meeting with Karina, I talked through a highly simplified slide deck about the project, explaining its goals and getting her excited about working on it. Describing my research in this simplified manner also helped me develop my own communication and storytelling skills. During my job interview at my current company, I used a similar approach.

INTRODUCE THE LITERATURE. 

Keeping up with the scientific literature is crucial for any researcher. But undergraduate students may not know this. Even if they do, they may feel overwhelmed by the volume and technical language. To help Karina start building her literature knowledge and confidence, I sent her relevant papers and followed up with discussions. These conversations also helped me deepen my understanding of my research and think about it in new ways.

Read more... 

Additional resources 
Science  24 Nov 2017:
Vol. 358, Issue 6366, pp. 1098
DOI: 10.1126/science.358.6366.1098 

Source: Science

Science education: It's not just for kids at the Michigan Science Center | Model D

Photo: David Sands

"STEM jobs are being touted as critically important in the U.S., which is one reason why the Michigan Science Center offers programs targeted at audiences of all ages" according to David Sands, Detroit-based freelance writer.
 

An After Dark gaming event
Photo: courtesy of the Michigan Science Center.

 
Ever notice how young children are fascinated by dinosaurs, rocket ships and nature hikes? There's a reason for that; kids possess a natural curiosity about the world around them that makes science and technology appealing fields of exploration. Unfortunately, many people lose their sense of wonder for these topics as they grow older.

According to the National Center for STEM (Science, Technology, Engineering and Math) Elementary Education at St. Catherine University in St. Paul, Minnesota, a third of all children have lost their interest in science by the time they reach the fourth grade. It's even worse by eighth grade, when research shows a staggering 50 percent of students have lost interest in science or consider it irrelevant to their education or future plans. 
 

Visitors look at an exhibit from "1001 Inventions"
Photo: courtesy of the Michigan Science Center.

With STEM jobs being touted as critically important in the U.S. for the foreseeable future, that's bad news. But at the Michigan Science Center, programs targeted at audiences of all ages are changing the conversation in Metro Detroit.

"People tend to think that we focus on elementary school programs," says Charles Gibson, Director of Innovation and Outreach with the Detroit-based institution. "But we also look for interactive ways to engage middle school students, teens and young adults."

The center's current special exhibit, "1001 Inventions: Untold Stories from a Golden Age of Innovation," is a wonderful example of this hands-on approach. The exhibit educates visitors about an exciting period of technological innovation in the 7th through 17th centuries with a combination of films, video games, hands-on activities and live actors. Open through January 7, the award-winning exhibit is free with paid general admission.
Read more...

Source: Model D

What Can Science Gain From Computers That Learn? | Newswise

The DOE Science News Source is a Newswise initiative to promote research news from the Office of Science of the DOE to the public and news media.

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Photo: Shannon Brescher Shea

"Machine learning and deep learning programs provide a helping hand to scientists analyzing images" reports Shannon Brescher Shea, Senior Writer/Editor in the Office of Science

Photo: Image courtesy of Greg Stewart/SLAC National Accelerator Laboratory

Physicists on the MINERvA neutrino experiments at the Department of Energy’s Fermilab faced a conundrum. Their particle detector was swamping them with images. The detector lights up every time a neutrino, a tiny elementary particle, breaks into other particles. The machine then takes a digital photo of all of the new particles’ movements. As the relevant interactions occur very rarely, having a huge amount of data should have been a good thing. But there were simply too many pictures for the scientists to be able to analyze them as thoroughly as they would have liked to.

Enter a new student eager to help. In some ways, it was an ideal student: always attentive, perfect recall, curious to learn. But unlike the graduate students who usually end up analyzing physics photos, this one was a bit more – electronic. In fact, it wasn’t a person at all. It was a computer program using machine learning. Computer scientists at DOE’s Oak Ridge National Laboratory (ORNL) brought this new student to the table as part of a cross-laboratory collaboration. Now, ORNL researchers and Fermilab physicists are using machine learning together to better identify how neutrinos interact with normal matter.  

“Most of the scientific work that’s being done today produces a tremendous amount of data where basically, you can’t get human eyes on all of it,” said Catherine Schuman, an ORNL computer scientist. “Machine learning will help us discover things in the data that we’re collecting that we would not otherwise be able to discover.”

Fermilab scientists aren’t the only ones using this technique to power scientific research. A number of scientists in a variety of fields supported by DOE’s Office of Science are applying machine learning techniques to improve their analysis of images and other types of scientific data.

Teaching a Computer to Think
In traditional software, a computer only does what it’s told. But in machine learning, tools built into the software enable it to learn through practice. Like a student reading books in a library, the more studying it does, the better it gets at finding patterns that can help it solve a big-picture problem.

“Machine learning gives us the ability to solve complex problems that humans can’t solve ourselves, or complex problems that humans solve well but don’t really know why,” said Drew Levin, a researcher who works with DOE’s Sandia National Laboratories.

Recognizing images, like those from experiments like MINERvA, is one such major problem. While humans are great at identifying and grouping photos, it’s difficult to translate that knowledge into equations for computer programs...

What Machine Learning Can Do For You
Grouping and identifying images is one of the most promising uses for machine learning. Back in 2012, a deep-learning program could identify photos in a specific database of images with a 20 percent error rate. Over the course of only three years, scientists improved deep-learning programs so much that a similar program in 2015 beat the average human error rate of 5 percent.

“There’s a lot of image-based science that can benefit from deep learning,” said Tom Potok, leader of ORNL’s Computational Data Analytics group.

For image recognition that requires special expertise, machine learning can provide even bigger benefits. “These techniques are extremely efficient at finding subtle signals” like small shifts in particle tracks, said Gabe Perdue, a Fermilab physicist on the MINERvA experiment.

While Fermilab physicists are using deep learning to understand neutrinos, other scientists are using it to understand images from sources as diverse as telescopes and light sources...

Whether in neutrino experiments or cancer research, machine learning offers a new way for both researchers and their electronic students to better understand our world and beyond.

Photo: Prasanna Balaprakash, Computer Scientist.

As Prasanna Balaprakash, a computer scientist at DOE’s Argonne National Laboratory, said, “Machine learning has applications all the way from subatomic levels up to the universe. Wherever we have data, machine learning is going to play a big role.”
Read more...

Source: Newswise (press release)

Teachers’ meet in December to bridge learning gaps | Times of India - Schools & Colleges

"Teaching of science and mathematics has been a problem in the state with various assessments by both the government and private bodies reflecting low levels of understanding of both subjects among students" continues Times of India.

Photo: Storyblocks.com

About 75 teachers from the state will participate and imbibe innovative methods for evaluation of science learning in classroom.

Apurva Barve, centre coordinator of the Centre of Excellence in Science and Mathematics Education (COESME) at IISER, Pune, said three or four teachers who are selected will get a month's internship and exposure to new-age technologies. 

"The state government also organises conferences but in those, a few speak and the rest merely listen . At this congress in IISER, we give a platform to science and mathematics teachers to communicate their ideas, and share new experiments in teaching methodology and science education," A P Deshpande, secretary of the parishad, said.  
Read more... 

Source: Times of India 

Four strategies for remembering everything you learn | The Independent

Drake Baer, Correspondent, Business Inside summarizes, "Because there's learning and there's knowing how to learn."

Many struggle to retain facts they learn
Photo:  Getty Images/iStockphoto

If you're going to learn anything, you need two kinds of prior knowledge:

• knowledge about the subject at hand, like math, history, or programming
• knowledge about how learning actually works

The bad news: Our education system kinda skips one of them, which is terrifying, given that your ability to learn is such a huge predictor of success in life, from achieving in academics to getting ahead at work. It all requires mastering skill after skill.

“Parents and educators are pretty good at imparting the first kind of knowledge,” shares psych writer Annie Murphy Paul. “We're comfortable talking about concrete information: names, dates, numbers, facts. But the guidance we offer on the act of learning itself - the 'meta-cognitive' aspects of learning - is more hit-or-miss, and it shows.”

To wit, new education research shows that low-achieving students have “substantial deficits” in their understanding of the cognitive strategies that allow people to learn well. This, Paul says, suggests that part of the reason students perform poorly is that they don't know a lot about how learning actually works.

It's a culture-wide issue.

Henry Roediger and Mark McDaniel, psychologists at Washington University in St. Louis  and coauthors of Make It Stick: The Science Of Successful Learning, say that “how we teach and study is largely a mix of theory, lore, and intuition.”

So let's cut through that lore. Here are learning strategies that really work.

Force yourself to recall 
The least-fun part of effective learning is that it's hard. In fact, the “Make It Stick” authors contend that when learning if difficult, you're doing your best learning, in the same way that lifting a weight at the limit of your capacity makes you strongest.

It's simple, though not easy, to take advantage of this: force yourself to recall a fact. Flashcards are a great ally in this, since they force you to supply answers.

Don't fall for fluency
When you're reading something and it feels easy, what you're experiencing is fluency.

It'll only get you in trouble. 

Example: Say, for instance, you're at the airport and you're trying to remember which gate your flight to Chicago is waiting for you at. You look at the terminal monitors — it's B44. You think to yourself, oh, B44, that's easy. Then you walk away, idly check your phone, and instantly forget where you're going. 
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Source: The Independent

Students learn the science behind Star Wars | Warrington Guardian

"HOW much of the action in Star Wars could happen in the real world?" continues Warrington Guardian.

Students from St Gregory's RC learned about Star Wars.

Well students from St Gregory's High School in Warrington found out during an event today.

Chapelford resident Professor Carsten Welsch, head of physics at the University of Liverpool and head of communication for the Cockcroft Institute, explored the 'Physics of Star Wars' in an event on Monday designed to introduce cutting-edge science to hundreds of secondary school children, undergraduate and PhD students, as well as university staff. 

Professor Welsch said: “I selected iconic scenes from the movies that everybody will immediately recognise, and used real world physics to explain what is possible and what is fiction.

"For example, a lightsabre, as shown in the film, wouldn’t be possible according to the laws of physics, but there are many exciting applications that are possible, such as laser knives for high precision surgery controlled by robot arms and adaptive manufacturing using lasers for creating complex structures in metals.

“A short scene from Star Wars was just the introduction, the appetizer, to make the participants curious, but then I linked what I had just shown in the film to ongoing research here in the department and in particular our accelerator science projects at the Cockcroft Institute.

“In the first movie from 1977, the rebels have used proton torpedoes that make the Death Star explode as their lasers wouldn’t penetrate the shields. I linked that to our use of ‘proton torpedoes’ in cancer therapy. Within the pan-European OMA project we are using proton beams to target something that is hidden very deep inside the body and very difficult to target and destroy...

Professor Welsch and members of his QUASAR Group had the permission of Lucasfilm to use film excerpts; these were complemented by Lego Star Wars models, a real cantina as found in the movie, storm troopers and even Darth Vader himself. 
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Source: Warrington Guardian