How to tell if your child has a future in computer science

Are you smarter than a supercomputer? 4-year-olds are

New research from the University of Illinois pitted an advance AI against children's IQ test

Microsoft CEO Announces $75 Million for Computer Science education expansion

West Seattle and Sealth High Schools will benefit from TEALS program

Microsoft CEO Satya Nadella announced on Sept. 16 a new commitment of $75 million in community investments over the next three years to increase access to computer science (CS) education for all youth, and especially for those from under-represented backgrounds.

This new investment has a significant impact in Washington State, particularly in West Seattle:
· As part of this investment, Microsoft will expand its Technology Education and Literacy in Schools (TEALS) program to 11 new schools in Washington state this fall, including Chief Sealth High School and West Seattle High School. This brings Washington’s number of TEALS schools to 57, up from 46 last school year.

· The program’s local growth is part of Microsoft’s nationwide expansion of TEALS. The U.S. program, which started in 2009, aims to grow five-fold over the next three years, with the goal of working with 2,000 tech industry volunteers to reach 30,000 students in nearly 700 schools across 33 states.

TEALS is a Microsoft YouthSpark program that recruits, trains, mentors and places high-tech professionals who are passionate about bringing computer science education into high schools as volunteer teachers in a team teaching model.

· TEALS provides schools with both curricula and highly qualified volunteer teachers for computer science courses without any training or development costs to the schools themselves.

· Because TEALS teachers always team teach with a school teacher, the school teachers can learn the course material and further down the line, teach some of the courses by themselves.

· In Washington:
o During the TEALS pilot year in Washington state, 10 TEALS volunteers partnered with four Puget Sound area high schools, reaching 250 students.
o Today, TEALS is in 57 Washington state high schools.

Theory of Automata. Introduction To The Theory of Computation

Recommended book from ahmad hussain sir
Click here to download the book

How to delete Microsoft’s unwanted Windows 10 download files

Yesterday, we discussed how Microsoft now downloads Windows 10 to local devices whether users have chosen to do so or not. Here, we’ll walk you through the process of reclaiming that space. The surest way to tell if you’ve been affected by the stealth download is to navigate to your C:\Windows directory. Once there, you’ll want to configure Explorer to show hidden files and folders.

In Windows 7, you do this by clicking on “Tools,” then “Folder Options,” and finally “Show Hidden Files and Folders,” as shown below. In Windows 8/8.1, click on the View tab and then select the “Hidden items” check box.

Once this is done, check your Windows directory for a directory named $WINDOWS.~BT. The icon may be translucent, since the folder is normally hidden, so check carefully. You can delete this folder if you wish, but doing so won’t actually prevent Microsoft from downloading the setup program again. Once the OS has decided that you’re going to install Windows 10, it’s downright pushy about having the data locally. The only solution, according to various sources, is to actually remove a specific Windows Update: KB3035583.

KB3035583 is described by Microsoft as installing “the Get Windows 10 app, which helps users understand their Windows 10 upgrade options and device readiness.” It can be uninstalled by navigating to Windows Update from within the Control Panel, choosing “Programs and Features,” and then selecting the “View Installed Updates” option. Remove this update and then delete the folder, and you’ll reclaim your lost disk space.

KB 3035583 can then be blocked from installing again by hiding the update from within the Windows Update setting in Control Panel.

An uncertain situation

There are facets to this situation that aren’t fully understood as yet. My own Windows Update history shows that I installed KB3035583 on the 26th of July, as shown below.

Despite this, there’s no sign that my system ever downloaded Windows 10, and I have no record of failed W10 installations (another reported commonality) in my own Windows Update history. In some cases, this MS update clearly triggers a download process, but in others, it does not seem to do so. I personally run Windows 7 Professional, but IE11 and Windows Update have both been incessantly nagging me to upgrade.

One potential reason for this is that I keep Windows set to “Check for updates but let me choose whether to download and install them.” It’s possible that this setting keeps Windows 10 from downloading whether you’ve installed KB 3035583 or not.

Why we cover topics like this

Several readers have asked why we continue to cover topics like this and implied that ET (or myself) have a bias against Windows 10. I won’t deny that I disagree with Microsoft’s new approach to privacy controls, patch disclosure, and software updates, but that’s not why we’ve continued covering these topics. Whether you agree or disagree that some of Microsoft’s new policies are problematic, the fact is, they represent a marked change from the status quo.

A 6GB OS download isn’t a big deal if you have a 500GB drive, but if you’re running an older Windows installation on a 128-256GB SSD, that can wind up being a significant chunk of space. More to the point, however, it’s something Microsoft hasn’t previously done. The thinking, in this case, is obvious — by downloading Windows 10 behind-the-scenes, Microsoft guarantees a faster upgrade process for end users.

The problem, once again, isn’t that Microsoft is evil. The problem is that Microsoft either failed to consider the needs of its users or dismissed them as unimportant. We’ve already heard from people who went over their metered bandwidth for the month because of background Windows 10 downloads. One of our staff had an HTPC surprise-upgrade itself to Windows 10 while he was on vacation. These are problems that Microsoft could address with a simple checkbox asking users if they’d like to download Windows 10 now so they can start the upgrade process immediately when they choose to do so.

Graphics processors accelerate pattern discovery

Repeating patterns in complex biological networks can now be found hundreds of times faster using an algorithm that exploits the parallel computing capacity of modern graphics adapters1. The A*STAR-led breakthrough opens the possibility of rapid genome scans for discrete molecular structures.

A network motif is a statistically significant connection of nodes that appears more frequently than chance would allow. In the gene transcription network for the bacteria Escherichia coli, for example, a simple network motif arises in the process by which atranscription factor responds to itself, known as negative auto-regulation. Such a motif occurs repeatedly in the transcriptome.

“This negative auto-regulation process has essential biological functions,” explains Wenqing Lin from the A*STAR Institute for Infocomm Research. “Searching for these repeating ‘graphs’ is of particular importance in the study of network functionality.”

These searches, however, are a significant computational drain and increasing the rate of motif discovery is a steep mathematical challenge. “Even state-of-the-art solutions require several days to derive network motifs from networks with only a few thousand vertices,” says Lin.

The research team harnessed the capabilities of the modern computer graphics processors to overcome the limitations of existing network motif search algorithms. Graphics processing units often comprise thousands of computing cores, allowing Lin’s team to adapt a large number of the computational tasks involved in graph mining. This can significantly reduce computation time.

By developing a parallelized code that utilizes the capabilities of graphical processing units (GPUs), including simultaneous execution of code on multiple GPU cores and efficient memory access patterns, the team was able to expedite the search by up to 100 times — the improved rate was confirmed through extensive experiments on a variety of biological networks.

The study demonstrates the feasibility of using GPUs for network motif search tasks. GPUs are also around 20 times cheaper than computer processors for equivalent performance, highlighting the potential for large-scale search projects.

Network motif discovery has many applications beyond biology, including pattern detection in digital circuits and other non-random networks. “Our research results can also be applied to solving the problems of enumerating all subgraphs of a large network, and finding the matches for a given subgraph in a large network,” says Lin. “Both of these problems are fundamental aspects of graph mining and graph databases.”

The A*STAR-affiliated researchers contributing to this research are from the Institute for Infocomm Research

Reference

1. Lin, W., Xiao, X., Xie, X. & Li, X.-L. Network motif discovery: A GPU approach. IEEE 31st International Conference on Data Engineering (ICDE), 831–842 (2015).

Building computers from DNA?

New research from the University of East Anglia could one day help build computers from DNA.

Scientists have found a way to 'switch' the structure of DNA using copper salts and EDTA (Ethylenediaminetetraacetic acid) -- an agent commonly found in shampoo and other household products.

It was previously known that the structure of a piece of DNA could be changed using acid, which causes it to fold up into what is known as an 'i-motif'.

But new research published today in the journal Chemical Communications reveals that the structure can be switched a second time into a hair-pin structure using positively-charged copper (copper cations). This change can also be reversed using EDTA.

The applications for this discovery include nanotechnology -- where DNA is used to make tiny machines, and in DNA-based computing -- where computers are built from DNA rather than silicon.

It could also be used for detecting the presence of copper cations, which are highly toxic to fish and other aquatic organisms, in water.

Lead researcher Dr Zoë Waller, from UEA's school of Pharmacy, said: "Our research shows how the structure of our genetic material -- DNA -- can be changed and used in a way we didn't realise.

"A single switch was possible before -- but we show for the first time how the structure can be switched twice.

"A potential application of this finding could be to create logic gates for DNA based computing. Logic gates are an elementary building block of digital circuits -- used in computers and other electronic equipment. They are traditionally made using diodes or transistors which act as electronic switches.

"This research expands how DNA could be used as a switching mechanism for a logic gate in DNA-based computing or in nano-technology."

---

Story Source:

The above post is reprinted from materials provided byUniversity of East Anglia. Note: Materials may be edited for content and length.

---

Journal Reference:

1. Henry Albert Day, Elisé Patricia Wright, Colin John MacDonald, Andrew James Gates, Zoë Ann Ella Waller.Reversible DNA i-motif to hairpin switching induced by copper(ii) cations. Chem. Commun., 2015; DOI:10.1039/C5CC05111H

First functioning carbon nanotube computer developed

Major breakthrough lays groundwork for future computing revolution

The next step towards the computers of the future has been taken, after engineers from Stanford University built the first working computer that uses carbon nanotube transistors (CNTs).

The machine is rudimentary, but it is running a basic operating system, and can perform calculations, but it probably wouldn’t stand up to the rigours of GTA 5. It’s most important as proof of concept, that computers can be made of more efficient materials

Currently, computer processors are made out of silicon, an element that has so far done everything asked of it. However, as the art of miniaturisation improves, computer scientists are beginning to realise it has a limit to its abilities.

According to Moore’s Law, formulated in 1965, the density of transistors – and, effectively the processing power of computers – doubles every two years. But as silicon processors have become smaller and cheaper, so too have they become hotter.

"Energy dissipation of silicon-based systems has been a major concern," said Anantha Chandrakasan, head of electrical engineering and computer science at MIT. He described the Stanford team’s work as "a major benchmark" in moving CNTs toward practical use.

CNTs are long chains of carbon atoms that are especially efficient at conducting electricity. They are extremely thin – thousands of CNTs could fit side by side in a human hair – meaning that it takes very little energy to switch them off, and making them more suitable, in theory, to handle the heat that silicon has trouble dissipating.

There are still kinks to iron out; although CNTs have obvious advantages, they do not always grow in the neat lines that chips require, and the assembly process can sometimes produce metallic imperfections, which will cause transistors to short circuit.

These flaws have presented serious barriers to CNTs in computer manufacture in the past, so the team had to develop an new way to construct them.

"We needed a way to design circuits without having to look for imperfections or even know where they were," he said.

To eliminate the metallic nanotubes, the team developed an "imperfection-immune design", in which all the regular CNTs were switched off, before flooding the semiconductor circuit with electricity, thereby burning out the faulty, conductive nanotubes, and leaving only the usable ones.

In order to deal with the CNTs’ natural misalignment, meanwhile, researchers designed an algorithm to maps out a circuit layout that would be guaranteed to work no matter whether or where CNTs might be askew.

So while the Stanford computer might only have 178 transistors – as opposed to the 5bn that the Xbox One is threatening to house – the fact that it works is significant.

"People have been talking about a new era of carbon nanotube electronics moving beyond silicon," said Subhasish Mitra, one of the professors who lead the research. "But there have been few demonstrations of complete digital systems using this exciting technology. Here is the proof."

Using speed of video game processors to improve cancer patient care

Date:

May 2, 2014

Source:

UT Southwestern Medical Center

Summary:

The speed of video game processors are being used to promote research that is aimed at improving patient care, a new study says. In recent years, video game processors, known as graphic processing units, or GPUs, have become massively powerful as game makers support increasingly elaborate video graphics with rapid-fire processing. Now medical researchers are looking to these GPUs for inspiration. One practical application is reducing the time required to calculate the radiation dose delivered to a tumor during proton radiotherapy, for example. The faster video processors can reduce the time of the most complex calculation method from 70 hours to just 10 seconds.

Using normal graphics processors, a new program for identifying repeated patterns in complex networks significantly boosts search performance.

Repeating patterns in complex biological networks can now be found hundreds of times faster using an algorithm that exploits the parallel computing capacity of modern graphics adapters. The A*STAR-led breakthrough opens the possibility of rapid genome scans for discrete molecular structures.

A network motif is a statistically significant connection of nodes that appears more frequently than chance would allow. In the gene transcription network for the bacteria Escherichia coli, for example, a simple network motif arises in the process by which a transcription factor responds to itself, known as negative auto-regulation. Such a motif occurs repeatedly in the transcriptome.

"This negative auto-regulation process has essential biological functions," explains Wenqing Lin from the A*STAR Institute for Infocomm Research. "Searching for these repeating 'graphs' is of particular importance in the study of network functionality."

These searches, however, are a significant computational drain and increasing the rate of motif discovery is a steep mathematical challenge. "Even state-of-the-art solutions require several days to derive network motifs from networks with only a few thousand vertices," says Lin.

The research team harnessed the capabilities of the modern computer graphics processors to overcome the limitations of existing network motif search algorithms. Graphics processing units often comprise thousands of computing cores, allowing Lin's team to adapt a large number of the computational tasks involved in graph mining. This can significantly reduce computation time.

By developing a parallelized code that utilizes the capabilities of graphical processing units (GPUs), including simultaneous execution of code on multiple GPU cores and efficient memory access patterns, the team was able to expedite the search by up to 100 times -- the improved rate was confirmed through extensive experiments on a variety of biological networks.

The study demonstrates the feasibility of using GPUs for network motif search tasks. GPUs are also around 20 times cheaper than computer processors for equivalent performance, highlighting the potential for large-scale search projects.

Network motif discovery has many applications beyond biology, including pattern detection in digital circuits and other non-random networks. "Our research results can also be applied to solving the problems of enumerating all subgraphs of a large network, and finding the matches for a given subgraph in a large network," says Lin. "Both of these problems are fundamental aspects of graph mining and graph databases."

- - Computer graphics: Less computing time for sand

A digital sandcastle consists of millions of grains. Its photorealistic presentation by a computer now becomes more computation-efficient. Credit: KIT / Disney Research

Computer graphics today can produce amazingly photorealistic images. Many motives, however, require very long computation times. Researchers of KIT, Disney Research, Zurich, and Cornell University have now developed a process, by means of which granular objects made of e.g. sand, snow or sugar can be computed more quickly. It was presented recently at the renowned ACM SIGGRAPH 2015 International Conference for Computer Graphics in Los Angeles.

Objects of granular media, such as a sandcastle, consist of millions or billions of grains. The computation time needed to produce photorealistic images amounts to hundreds to thousands of processor hours," Professor Carsten Dachsbacher of the Institute for Visualization and Data Analysis of KIT explains. Materials, such as sand, salt or sugar, consist of randomly oriented grains that are visible at a closer look only. Image synthesis, the so-called rendering, is very difficult, as the paths of millions of light rays through the grains have to be simulated. "In addition, complex scattering properties of the individual grains and arrangement of the grains in a system can prevent classical acceleration techniques from being used. This makes it difficult to find efficient algorithms," doctoral student Johannes Meng adds. "In case of transparent grains and long light paths, computation time increases disproportionately."

For image synthesis, the researchers developed a new multi-scale process that adapts simulation to the structure of light transport in granular media on various scales. On the finest scale, when only few grains are imaged, geometry, size, and material properties of individual discernable grains as well as their packing density are considered. As in classical approaches, light rays are traced through the virtual grains, which is referred to as path tracing. Path tracing computes light paths from each pixel back to the light sources. This approach, however, cannot be applied to millions or billions of grains.

The new process automatically changes to another rendering technique, i.e. volumetric path tracing, after a few interactions, such as reflections on grains, provided that the contributions of individual interactions can no longer be distinguished. The researchers demonstrated that this method normally applied to the calculation of light scattering in materials, such as clouds or fog, can accurately represent and more efficiently compute light transport in granular materials on these scales
On larger scales, a diffusion approximation can be applied to produce an analytical and efficient solution for remaining light transport. This enables efficient computation of photorealistic representation in case of bright and strongly reflecting grains, such as snow or sugar.

The researchers also succeeded in demonstrating how the individual techniques have to be combined to produce consistent visual results on all scales - from individual grains to objects made of billions of grains - in images and animations. Depending on the material, the hybrid approach accelerates computation by a factor of ten up to several hundreds compared to conventional path tracing, while image quality remains the same.

Why Girls Are Less Interested In Computer Science: Classrooms Are Too 'Geeky'

Despite billions of dollars in outreach programs designed to lure women into computer programming, and companies mandating that more women be hired, most females would rather go into something involving people.

Yet a new survey of 270 high school students concludes that three times as many girls would interested in enrolling in a computer science class if the classroom was redesigned to be less "geeky" and more inviting.

So we can knock Barbie dolls and pink clothes, but they are appealing to the market that is rather than the market some academics would like it to be. The notion that women and men are the same has become passe.

"Our findings show that classroom design matters -- it can transmit stereotypes to high school students about who belongs and who doesn't in computer science," said lead author Allison Master, a post-doctoral researcher at the University of Washington's Institute for Learning&Brain Sciences (I-LABS). "This is the earliest age we've looked at to study stereotypes about computer science. It's a key age group for recruitment into this field, because girls in their later adolescence are starting to focus on their career options and aspirations."

In the study, high school boys and girls (aged 14 to 18 years) completed questions about:

• Their interest in enrolling in a computer science class
• Their sense of belonging in a computer science class
• How much they thought they personally "fit" the computer science stereotype

Then, the UW team showed the students photos of two different computer science classrooms decorated with objects that represented either the "geeky" computer science stereotype, including computer parts and "Star Trek" posters, or a non-stereotypical classroom containing items such as art and nature pictures.

Students had to say which classroom they preferred, and then answered questions about their interest in enrolling in a computer science course and their thoughts and feelings about computer science and stereotypes.

Girls (68 percent) were more likely than boys (48 percent) to prefer the non-stereotypical classroom. And girls were almost three times more likely to say they would be interested in enrolling in a computer science course if the classroom looked like the non-stereotypical one.

Boys didn't prefer one classroom's physical environment over the other, and how the classroom looked didn't change boys' level of interest in computer science.

"Stereotypes make girls feel like they don't fit with computer science," Master said. "That's a barrier that isn't there for boys. Girls have to worry about an extra level of belonging that boys don't have to grapple with."

Previously they reported that inaccurate negative cultural stereotypes about computer science deterred college-age women from the field and that altering stereotypes can increase girls' interest.

The researchers say that changing computer science stereotypes to make more students feel welcome in high school classrooms would help recruit more girls to the field, which has one of the lowest percentages of women among STEM fields.

"Our new study suggests that if schools and teachers feel they can't recruit girls into their computer science classes," Master said, "they should make sure that the classrooms avoid stereotypes and communicate to students that everyone is welcome and belongs."

The Journal of Educational Psychology published the study online August 17. Co-authors of the paper are Sapna Cheryan, a UW associate professor of psychology, and Andrew Meltzoff, co-director of I-LABS. The National Science Foundation funded the research.

Microsoft releases free computer science curriculum for new developers

It may be surprising to some, but many people are only interested in computers as a consumption device rather than a tool; for example preferring to watch YouTube rather than write a novel in Word. However, when it comes to the coding of computers to create games and apps, there is even less interest and that’s something Microsoft aims to change with their new computer science course.

The course makes coding less intimidating by using a simple programming language to develop real games and apps giving each student a sense of a achievement at the end. The coding is done usingMicrosoft Touch Develop which is a simple visual way of programming with a touch interface and it works with any browser on any Operating System.

In the past, we’ve told you about how Touch Develop can be used to develop Windows Store apps so it’s more than a capable language. Once a student has mastered it, then they can go on to consider more powerful languages. Tom Ball who worked on Touch Develop is happy to see the language used in this new course saying:

Microsoft’s new course is aimed at people with little to no experience in coding (including educators) and even people who would never consider doing it. The course can be taught using any modern web browser so it will even work on phones and tablets. It’s also a provides everything a teacher would need including lesson plans, presentations, student assignments and quizzes. The course is flexible and can accommodate the free time available in the semester.

This is a smart move by Microsoft and it would be even smarter for schools to take up the curriculum. Computers aren’t going to go away any time soon and will most likely become more prevalent so the more coders we have out in the world, the better.

You can check out the course here.

Google, Apple $415M deal with tech workers gets final approval

A court in California has approved a US$415 million settlement between tech workers and Intel, Google, Apple and Adobe Systems, who were accused of conspiring to prevent the poaching of each other's employees. The final approval has, however, reduced significantly the sums to be paid to lawyers and the class representatives who had initiated the court action. The tech workers, who filed the suit, had alleged that Google, Apple, Intel, Adobe, Intuit, Lucasfilm and Pixar had engaged in an "overarching conspiracy" to fix and suppress employee compensation and to restrict employee mobility. Intuit, Lucasfilm and Pixar had previously settled with the workers for about $20 million. Judge Lucy H. Koh of the U.S. District Court for the Northern District of California, San Jose division on Wednesday described the settlement, for which she had given a preliminary approval in March, as "fair, adequate, and reasonable." She added that the court was convinced that the settlement was arrived at after arm's length negotiations and was not the result "of fraud, overreaching, or collusion among the parties." The lawsuit was one of the more high-profile class action cases in Silicon Valley, involving as evidence emails sent between the late Apple chief Steve Jobs and other key Silicon Valley executives like Google executive chairman Eric Schmidt and cofounder Sergey Brin. Judge Koh last year rejected a proposed settlement of $324.5 million, which she found was too low. Out of 64,466 class members, only 11 or about 0.017 percent of the class submitted objections to the current settlement. In addition, only 56 class members, or less than 0.09 percent have opted out of the settlement, according to the judge. The opt-outs are also lower than the 4 percent of class members required for the companies to ask for a pro-rata reduction in the settlement amount. In the payment to lawyers, Judge Koh, however used a formula mainly based on the time spent by the counsel on the litigation, and then using a multiplier, rather than calculating payment as percentage of the settlement amount as that would amount to a windfall profit for the lawyers. The counsel for plaintiffs sought a total of over $85 million or 20.6 percent of the $415 million settlement in attorney's fees. Adding the $5 million in attorney's fees already awarded to class counsel in the earlier settlements with Pixar, Lucasfilm, and Intuit, counsel for plaintiffs in this case would be seeking a total of 20.8 percent or $90 million from both settlements, the judge wrote. The court instead awarded the counsel a total of close to $41 million, which does not include the $5 million in fees awarded in the settlements with Pixar, Lucasfilm and Intuit. The reduction in fees will increase the recovery by class members by $700 to about $5,770 per person. Judge Koh also reduced the "service awards" to class representatives. The second settlement aimed to award "reasonable service award payments of $80,000" to each of the five plaintiffs for their services. Michael Devine, a former Adobe engineer, who had opposed the earlier $324.5 million settlement, had asked that his payout from the new settlement should be doubled to $160,000 for his efforts in getting the proposed settlement amount increased. Devine appeared through his own counsel. At a hearing on preliminary approval, however, the class counsel sought the court's permission to seek up to $160,000 per class representative, which was allowed. Judge Koh has, however, awarded $120,000 to Devine and $80,000 to each of the others. They have already received $20,000 each from the settlement with Pixar, Lucasfilm and Intuit. Judge Koh said that, among other contributions, each of these persons had "risked significant workplace retaliation by serving as a named plaintiff in this high-profile lawsuit." But the high media coverage for Devine made it likely that he would find it even more difficult to get a job again in the tech industry, hence the higher payout, the judge wrote.

For future wearables, the network could be you

People who wear networked gadgets all over their bodies may someday become networks themselves. Researchers at the University of California, San Diego, have found a way for wearables to communicate through a person's body instead of the air around it. Their work could lead to devices that last longer on smaller batteries and don't give away secrets as easily as today's systems do. The proliferation of smartphones, smart watches, health monitoring devices and other gear carried close to the body has led to so-called personal area networks that link the gadgets together and provide a path to the Internet through one that has a Wi-Fi or cell radio. Today, those PANs use short-range over-the-air systems like Bluetooth. But radio technologies like Bluetooth can't transmit well through the body itself, so they have to go around it. Bluetooth signals can travel as far as 10 meters (30 feet) which increases the chance of eavesdropping and leads to high "path loss," an effect that weakens signals on the way to their destinations, the researchers said. A team led by Professor Patrick Mercier of the university's Department of Electrical and Computer Engineering has discovered a way to use the body itself as the medium for data transmission. It uses magnetic fields and shows path loss that's 10 million times lower than what happens with Bluetooth. This could make the magnetic networks much more efficient, so devices don't have to work as hard to communicate and can have smaller batteries -- or get longer useful lives with the same size batteries. The team hasn't actually tested the system's energy use yet. They envision the technology being used for networks of health sensors that monitor many parts of the body. Wireless technologies like Bluetooth radiate electrical and magnetic waves, which a human body tends to absorb, Mercier said. By contrast, his team's network transmits data over magnetic fields that are created between two coils. Those fields can easily travel through the body. The system works like NFC (near-field communications), but at a slightly longer range. It uses very low frequencies, in the range of 10MHz to 30MHz, and it can carry at least 1M bps (bit per second), enough for dedicated devices like sensors, he said. There's just one catch: Anything that goes on the network needs to be circular and wrap around a part of the body. So smartwatches or fitness bands could work, but a sensor attached to the user's chest would need to be attached to a band around the chest. The team built a prototype network and installed it on the body of Jiwoong Park, a Ph.D student in Mercier's lab, as a proof of concept. It used coils of insulated copper wire wrapped around each of his arms. The coils sent magnetic signals from one arm to another using his body as a guide. There's no serious danger to the wearer's health because the magnetic fields are so weak, the researchers said. They're far weaker than those used by a device like an MRI (magnetic resonance imaging) machine or even the effect of the Earth's magnetic field on the body, Mercier said. Though some signals may radiate out from the wearer's body, they dissipate quickly so there's not much chance of interception from nearby, Mercier said. Still, any medical data that sensors sent over the network would have to be encrypted, he added. Signals would probably flow into the body of someone that the wearer touched, but the researchers haven't tested that yet.

Canada lagging in push to teach kids computer coding

Tomorrow's workers need to know more tech than merely checking their Facebook feed

• 
  

Armed with rope, pictures and elephant headbands, it looks like this group of nine-year-olds is setting up a huge game of hopscotch. But they're really laying out the biggest thing to hit British schools in a century. As the students direct each other through the grid they've built, they're learning the basic fundamentals of computer coding, in the process moving beyond how to use computers to how computers work. Kids learn coding in class to help problem solving Google announces project to get kids coding Schools need better computer science education, group says "We're actually enabling them and empowering them with skills and capability so that they can choose how they solve problems using technology," says Peter Gaynord, a teacher at Histon and Impington Junior School near Cambridge, England. This class is far from unique. In fact, every single school in England — all 16,000 primary schools and 3,500 secondary schools — have been put firmly on a high-tech path. A new national curriculum, implemented last year, has made computer science a mandatory subject for all students, starting from the tender age of five and continuing through to the end of high school. It's arguably nothing short of an education revolution. And it stands in stark contrast to the Canadian landscape, where computer programming classes are only offered as high school electives. That is, if they're offered at all. "I'm really surprised that administrators and teachers and parents are not saying, 'But what about our kids here?'" says Chris Stephenson, an Oshawa, Ont.-raised computer science education advocate who now works for Google in Oregon. "The silence is deafening."

M.A/M.Sc Admission Notice

 M.A/M.Sc Admission Notice

It is for the information to the general public that, Admissions to M.A/ M.Sc Programs for the session 2015-16 are open in Govt: PG Jahanzeb College Swat. Last date to Apply is 15/9/2015

Discription

Departments are as under Computer Science, English, Physics, Chemistry, Botany, Economics and Mathematics. 1st Merit list will be displayed on 21-9-2015

Bs 4th Semester Result

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BS New fall 5th semester.

BS New fall 5th semester classes will resume on 2nd September 2015 at 01:30pm
 All students are to be  informed that the classes will start form 2nd September .
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BS Computer Science 4th Semester Result.

Provisional Cumulative Result of BS Computer Science 4th Semester Session 2013-17

Course/Title of Paper E-Commerce Modern Programming Language Discrete Structure English III (Technical writing and presentation skills) Computer Organization and Assembly language Software Engineering-I Remarks
Roll No Name of Student Obt Cr. Hrs value GP Obt Cr. Hrs value GP Obt Cr. Hrs value GP Obt Cr. Hrs value GP Obt Cr. Hrs value GP Obt Cr. Hrs value GP SGP SCH GPA
1361121 Owais Danish Repeat Semester
1361122 Esa Muhammad 85 3 4 12 66 3 2.5 7.5 76 3 3.3 9.9 80 3 3.5 10.5 77 3 3.3 9.9 71 3 2.9 8.7 58.5 18 3.25
1361123 Muhammad Sohail 75 3 3.2 9.6 50 3 1 3 66 3 2.5 7.5 51 3 1.1 3.3 72 3 3 9 0 3 0 0 32.4 18 1.8
1361124 Inam ul Hassan 74 3 3.2 9.6 63 3 2.3 6.9 75 3 3.2 9.6 76 3 3.3 9.9 83 3 3.8 11.4 72 3 3 9 56.4 18 3.13
1361125 Khalil Ahmad 91 3 4 12 96 3 4 12 86 3 4 12 82 3 3.7 11.1 98 3 4 12 89 3 4 12 71.1 18 3.95
1361126 Muhammad Shahid Ali 86 3 4 12 74 3 3.2 9.6 82 3 3.7 11.1 83 3 3.8 11.4 91 3 4 12 82 3 3.7 11 67.2 18 3.73
1361127 Sayed Kamran Badshah Semester Repeat
1361128 Shafiq ur Rahman Absent
1361129 Sohail Khan 93 3 4 12 96 3 4 12 86 3 4 12 87 3 4 12 89 3 4 12 91 3 4 12 72 18 4
1361130 Nawaz Khan 84 3 3.9 12 53 3 1.3 3.9 67 3 2.5 7.5 74 3 3.2 9.6 78 3 3.4 10.2 81 3 3.6 11 53.7 18 2.98
1361131 Shujat Ali 81 3 3.6 11 50 3 1 3 66 3 2.5 7.5 73 3 3.1 9.3 73 3 3.1 9.3 65 3 2.4 7.2 47.1 18 2.62
1361132 Latifullah 80 3 3.5 11 52 3 1.2 3.6 79 3 3.4 10.2 69 3 2.7 8.1 65 3 2.4 7.2 67 3 2.5 7.5 47.1 18 2.62
1361133 Haris Semester Repeat
1361134 Mushtaq Ahmad 79 3 3.4 10 57 3 1.7 5.1 87 3 4 12 76 3 3.3 9.9 70 3 2.8 8.4 74 3 3.2 9.6 55.2 18 3.07
1361135 Hassan Habib 71 3 2.9 8.7 0 3 0 0 56 3 1.6 4.8 50 3 1 3 66 3 2.5 7.5 71 3 2.9 8.7 32.7 18 1.82
1361136 Shahab Alam Khan 78 3 3.4 10 60 3 2 6 72 3 3 9 70 3 2.8 8.4 66 3 2.5 7.5 75 3 3.2 9.6 50.7 18 2.82
1361137 Ubaidullah Khan 77 3 3.3 9.9 88 3 4 12 85 3 4 12 62 3 2.2 6.6 74 3 3.2 9.6 85 3 4 12 62.1 18 3.45
1361138 Tariq Ali 72 3 3 9 68 3 2.6 7.8 79 3 3.4 10.2 54 3 1.4 4.2 66 3 2.5 7.5 57 3 1.7 5.1 43.8 18 2.43
1361139 Jawad Ali 83 3 3.8 11 68 3 2.6 7.8 80 3 3.5 10.5 79 3 3.4 10.2 73 3 3.1 9.3 70 3 2.8 8.4 57.6 18 3.2
1361140 Ikram Ali Khan 55 3 1.5 4.5 41 3 0 0 55 3 1.5 4.5 68 3 2.6 7.8 60 3 2 6 55 3 1.5 4.5 27.3 18 1.52
1361141 Imdadulah 84 3 3.9 12 60 3 2 6 80 3 3.5 10.5 54 3 1.4 4.2 60 3 2 6 66 3 2.5 7.5 45.9 18 2.55
1361142 Muhammad Abuzar 65 3 2.4 7.2 22 3 0 0 66 3 2.5 7.5 60 3 2 6 60 3 2 6 62 3 2.2 6.6 33.3 18 1.85
1361143 Muhammad Numan 75 3 3.2 9.6 63 3 2.3 6.9 78 3 3.4 10.2 81 3 3.6 10.8 64 3 2.4 7.2 74 3 3.2 9.6 54.3 18 3.02
1361144 Saif Ullah Semester Repeat
1361146 Fawad Khan s.o Absent
1361146 Asadullah 64 3 2.4 7.2 36 3 0 0 65 3 2.4 7.2 51 3 1.1 3.3 62 3 2.2 6.6 60 3 2 6 30.3 18 1.68
1361147 Barkat Ali s.o Absent
1361148 Abu Bakar Dropped
1361149 Saad Ahamd 68 3 2.6 7.8 50 3 1 3 52 3 1.2 3.6 70 3 2.8 8.4 54 3 1.4 4.2 55 3 1.5 4.5 31.5 18 1.75
1361150 Muhammad Waqas Khan 90 3 4 12 88 3 4 12 82 3 3.7 11.1 79 3 3.4 10.2 86 3 4 12 88 3 4 12 69.3 18 3.85
1361151 Abdullah Shah 76 3 3.3 9.9 72 3 3 9 85 3 4 12 72 3 3 9 82 3 3.7 11.1 75 3 3.2 9.6 60.6 18 3.37
1361152 Zahid Ali 81 3 3.6 11 69 3 2.7 8.1 76 3 3.3 9.9 85 3 4 12 82 3 3.7 11.1 81 3 3.6 11 62.7 18 3.48
1361153 Murad Ali 81 3 3.6 11 56 3 1.6 4.8 63 3 2.3 6.9 55 3 1.5 4.5 70 3 2.8 8.4 73 3 3.1 9.3 44.7 18 2.48
1361154 Imran khan Semester Repeat
1361155 Fazal Ahad 81 3 3.6 11 0 3 0 0 81 3 3.6 10.8 67 3 2.5 7.5 69 3 2.7 8.1 61 3 2.1 6.3 43.5 18 2.42
1361156 Salman Khan 83 3 3.8 11 94 3 4 12 81 3 3.6 10.8 82 3 3.7 11.1 85 3 4 12 80 3 3.5 11 67.8 18 3.77
1361157 Riaz Khan 72 3 3 9 50 3 1 3 74 3 3.2 9.6 29 3 0 0 60 3 2 6 44 3 0 0 27.6 18 1.53
1361158 Muhammad Khalid 75 3 3.2 9.6 75 3 3.2 9.6 74 3 3.2 9.6 51 3 1.1 3.3 71 3 2.9 8.7 0 3 0 0 40.8 18 2.27
1361159 Iqbal Ahmad khan Semester Repeat
1361160 Umar Khaliq 85 3 4 12 72 3 3 9 78 3 3.4 10.2 79 3 3.4 10.2 81 3 3.6 10.8 89 3 4 12 64.2 18 3.57
1361161 Fazal E Haq 91 3 4 12 90 3 4 12 85 3 4 12 89 3 4 12 91 3 4 12 94 3 4 12 72 18 4
1361162 Muhammad Shoaib 69 3 2.7 8.1 64 3 2.4 7.2 69 3 2.7 8.1 69 3 2.7 8.1 71 3 2.9 8.7 70 3 2.8 8.4 48.6 18 2.7
1361163 Nisar Ahmad 62 3 2.2 6.6 50 3 1 3 54 3 1.4 4.2 57 3 1.7 5.1 56 3 1.6 4.8 65 3 2.4 7.2 30.9 18 1.72
1361164 Ikram ullah khan Absent
1361165 Junaid 79 3 3.4 10 28 3 0 0 63 3 2.3 6.9 71 3 2.9 8.7 60 3 2 6 72 3 3 9 40.8 18 2.27
1361166 Naveed Shehzad Semester Repeat
1361167 Noman Khan 77 3 3.3 9.9 64 3 2.4 7.2 78 3 3.4 10.2 68 3 2.6 7.8 62 3 2.2 6.6 59 3 1.9 5.7 47.4 18 2.63
1361168 Tauseef Ahmad Absent
1361169 Wiqas Bahadar 89 3 4 12 94 3 4 12 89 3 4 12 91 3 4 12 93 3 4 12 94 3 4 12 72 18 4