Reaching 99.999999999997 Percent Safety: Computer Scientists Present Their Concept for a Wireless Bicycle Brake

Computer scientists at Saarland University have developed a wireless bicycle brake and demonstrated its efficiency on a so-called cruiser bike. They further confirmed the brake system’s reliability through mathematical calculations that are also used in control systems for aircraft or chemical factories.

To brake with the wireless brake, a cyclist has just to clench the rubber grip on the right handle. It seems as if a ghost hand is in play, but a combination of several electronic components enables the braking. Integrated in the rubber grip is a pressure sensor, which activates a sender if a specified pressure threshold is crossed. The sender is integrated in a blue plastic box which is the size of a cigarette packet and is attached to the handlebar. Its radio signals are sent to a receiver attached at the end of the bicycle’s fork. The receiver forwards the signal to an actuator, transforming the radio signal into the mechanical power by which the disk brake is activated.

To enhance reliability, there are additional senders attached to the bicycle. These repeatedly send the same signal. In this way, the scientists hope to ensure that the signal arrives at the receiver in time, even if the connection causes a delay or fails. The computer scientists at Saarland University found that increasing the number of senders does not result in increased reliability.

After first talks with bicycle brake manufacturers, Hermanns is looking for engineers who will realize the concept of a wireless bicycle brake.




Computer Scientists Develop ‘Mathematical Jigsaw Puzzles’ To Encrypt Software

A team of researchers have designed a system to encrypt software so that it only allows someone to use a program as intended while preventing any deciphering of the code behind it. This is known as “software obfuscation,” and it is the first time it has been accomplished.

Sahai, a science professor who specializes in cryptography at UCLA’s Henry Samueli School of Engineering and Applied Science, previously developed techniques for obfuscation presented only a “speed bump,” forcing an attacker to spend some effort, perhaps a few days, trying to reverse-engineer the software. The new system, he said, puts up an “iron wall,” making it impossible for an adversary to reverse-engineer the software without solving mathematical problems that take hundreds of years to work out on today’s computers — a game-change in the field of cryptography.

The researchers said their mathematical obfuscation mechanism can be used to protect intellectual property by preventing the theft of new algorithms and by hiding the vulnerability a software patch is designed to repair when the patch is distributed.

The key to this successful obfuscation mechanism is a new type of “multilinear jigsaw puzzle.” Through this mechanism, attempts to find out why and how the software works will be thwarted

The new technique for software obfuscation led to the emergence of functional encryption. With functional encryption, instead of sending an encrypted message, an encrypted function is sent in its place. This offers a much more secure way to protect information, Sahai said. Previous work on functional encryption was limited to supporting very few functions; the new work can handle any computable function.

“Through functional encryption, you only get the specific answer, you don’t learn anything else,” Sahai said.




Brain-Like Computers Moving Closer to Cracking Codes

A new discovery has been made by the U.S. Army Research Laboratory scientists about brain-like computer architectures for an age-old number-theoretic problem known as integer factorization.

This takes away the traditional computing architectures and embracing devices that are able to operate within extreme size-, weight-, and power-constrained environments. These devices can process information and solve computationally-hard problems quicker.

Simply the problem can be sated as: take a composite integer N and express it as the product of its prime components. For example, 100 can be 10×10 or 5x5x4.  What many didn’t realize is they were performing a task that if completed quickly enough for large numbers, could break much of the modern day internet.

The security of the RSA algorithm relies on the difficulty of factoring a large composite integer N, the public key, which is distributed by the receiver to anyone who wants to send an encrypted message. If N can be factored into its prime components, then the private key, can be recovered. However, the difficulty in factoring large integers quickly becomes apparent. This difficulty underlies the security of the RSA algorithm.

The scientists demonstrated how brain-like computers lend a speedup to the currently best known algorithms for factoring integers. So they devised a way to factor large composite integers by harnessing the massive parallelism of novel computer architectures that mimic the functioning of the mammalian brain.

As emerging devices shift to integrate massive parallelism and harness material physics to computer, the computational hardness underlying some security protocols may still be challenged. This study opens the door to new research areas of emerging computer architectures, in terms of algorithm design and function representation, alongside low-power machine learning and artificial intelligence applications.



Mathematical Solver for Analog Computers

Your computer performs most tasks well, but, with its style of mathematics that relies on the binary code system of “on” and “off” 1s and 0s, isn’t ideal for solving every problem.

That’s why researchers are interested in reviving analog computing at a time when digital computing has reached its maximum potential.

Zoltán Toroczkai, professor in the Department of Physics and concurrent professor in the Department of Computer Science and Engineering at the University of Notre Dame, and collaborators have been working toward developing a novel mathematical approach that can potentially find the best solution to NP-hard problems.

Analog computers were used to predict tides from the early to mid-20th century, guide weapons on battleships and launch NASA’s first rockets into space, among other uses. However, analog computers were cumbersome and prone to “noise” — disturbances in the signals — and were difficult to re-configure to solve different problems, so they fell out of favor.

Digital computers emerged after transistors and integrated circuits were reliably mass produced, and for many tasks they are accurate and sufficiently flexible.

A challenge for analog computing rests with the design of continuous algorithms. Unlike digital computing, which has a long history in algorithm development, algorithms for analog computers lack a similar knowledge base and thus are very difficult to design.

The next step is to design and build devices that would be built for specific tasks, and not for everyday computing needs. However, there are engineering problems that need to be solved at this point, such as spurious capacities and better noise control, but it’s going to get there.



Computer Science Could Lead to Change of Mindset for the Students Who Perform Poorly in Mathematics

Most students would walk into a mathematics class with an already formed opinion of how they will perform in the subject, most how poor they will perform. This is the attitude of most students who have looked at themselves as very poor in mathematics and are only in class because it is a must that they should attend the class. However, computer science has proved to be a real game-changer for this mindset. Without knowledge, the same students with the same attitude have drastically improved in the subject. What was the secret? Introduction of computer science in school. This is an account of one teacher of mathematics who shifted from teaching mathematics to computer science and was able to observe the change of behaviour among his students.

This teacher has discovered that computer science provides a special and unique opportunity and environment for students to change the way they perceive things especially as it relates to their abilities and capabilities. One thing that this teacher did is that he gave an equal opportunity to all kinds of students who come to his computer science classes to discover things on their own. He ensured that in his class no one attends thinking that he/she is incapable or will fail. All of them are meant to believe that either individually or as a group, they are able to solve the problem.

He has gone ahead and exposed these students to many problems which he has allowed them to wrestle with them until they have cracked them. Students have had to meet many algorithmic challenges and puzzles and try to solve individually or as a team until they have solved whatever the problem it is. With this same attitude, the initially week students in mathematics have risen and now they perform very well. The magic was in computer science.



Rebekah Loving from University of Hawai’i at Hilo Earns Awarded a Finalist for National Fellowship

During this year’s award for the finalist students that qualify for the national PhD fellowship for the year, The Fannie and John Hertz foundation named Rebekah Loving. Loving is a computer science and mathematics students at UH at Hilo who successfully was mentioned among other 41 graduate students for the award nationwide. This award is one of the most competitive awards which she was able to secure out of more than 840 students that applied. Any of the recipients of the award will receive academic support for about five years that is worth about $250,000. According to the chair of UH Hilo Department of Computer Science, Rebekah is known to be an outstanding student who deserves the honour.

Loving is known to have grown up at Hamakua Coast in the Island of Hawai’i together with her siblings and has really done a lot. To begin with, she was among the participants that carried out three research programs first at Harvard University, then at California Institute of Technology and finally at the University of California. She also participated in Heidelberg Laureate Forum, a conference held in Germany last year and brought together many highly innovative and creative young researchers worldwide.

As a result of her outstanding performance, Loving has received several acceptance letters from various universities in the world offering her full funding for her PhD program, just to mention a few, Caltech, Harvard, Columbia University, UC Berkeley and many more. All these are offering her a scholarship to study biostatistics, computational biology and computer science. She is so excited at the offers because she is sure to continue with her career that she loves so much in order to improve lives of many by helping them to have a deeper understanding of various biological processes through analysis of data, development of computational methods and software engineering.


Automated animal identification in wildlife research

Scientists have come up with a new automated method to prepare digital photos of animals to help in the analysis done by wildlife researchers. Frequently, these researchers depend on photographs in identifying individual animals by their unique markings. Together with scientists from Microsoft Azure, wildlife biologists from Penn state they improved how photos are turned to usable data through a cloud computing service and machine learning

Derek Lee, an associate research professor of biology, said that researchers require to identify and collect data for their work hence instead of human-applied markings and tags which could interfere with the animal’s behavior, these researchers take photographs of the animals. As much as there are software used to analyze the photo, they, however, need to be manually prepared for analysis which is time-consuming.

Lee uses photographs to understand births, deaths, and movement of more than 3,000 giraffes in East Africa. He collaborated with the scientists from Microsoft who provided him with a new image processing machine services. The service was essential for automating the time-consuming process that Lee and his team had to go through, by using machine learning technology on the Microsoft Azure cloud.

By using a computer algorithm for objective detection, the team trained a program to recognize some of the giraffe’s torsos through using the existing photos. The program improved using an active learning process whereby the system was able to show predicted cropping squares on new images to a human who could immediately verify or correct results.

The new images were fed back into the training algorithm for further improvement and updating of the programme. The system could identify the location of giraffe torsos win the picture with higher accuracy even if the giraffe is a small portion of the photo or its torso is semi-blocked by vegetation.



Smartphones Help in Improving Civil Infrastructure

A recent report done by the American Society of Civil Engineering rated the civil infrastructure systems available with a D+ rating. This is because civil infrastructure systems are aging in the United States. With that, scientists from the University of Missouri have developed a smartphone technology that can screen civil infrastructure systems like aging bridges, crumbling roads in order to save lives.

According to estimations, scientists say that the civil infrastructure system failure like roads and bridges could lead to a 1 percent drop in the US GDP. The number was $200 billion in 2017. The problem of these aging civil infrastructure systems suggests that there is a need from developing an innovative monitoring solution.

Through the use of various sensors on smartphones like a gyroscope, an accelerator measuring speed and camera or a small external sensor like the infrared sensor, scientists will be able to determine the precise makeup and worsening of a road surface in real time. When the sensor is plugged into a platform, any individual can effortlessly transfer data collected through crowdsourcing this technology will allow better-informed decisions about the conditions of the road and bridge

According to Amir Alavi, the assistant professor of civil and environmental engineering in the MU College of engineering, the existing methods of monitoring civil infrastructure systems have technical issues, and at the same time, they are not user-centered. He says that people are looking for smart, scalable, cost-effective and user-centered approaches.

With the development in technology, people can assist in monitoring or detecting problems by using their own devices and smartphone technology allows people to achieve that. The professor partnered with Bill Buttlar, the Glen Barton Chair of Flexible Pavement Technology to create an innovative solution for monitoring bridges and roads. According to Buttlar, a smartphone can put together many reasonable measures to accurately assess things like degradation of a road surface.



AI Capable Of Identifying Microscopic Marine Organisms

Researchers have ventured into the developing of an artificial intelligence program which can assist in providing information about species-level identification of microscopic organisms in the ocean. They are yet to instill the program into a robotic system which will enable the understanding of the ocean from the past to present.

The program invented has so far been able to identify six species of the forams organisms also known as foraminifera that are mostly found in the Earth’s ocean for the last 100 million years. Foraminiferas are neither plants nor animals also known as protists such that when they die, they leave tiny shells behind. These shells are not more than a millimeter wide.

The shells are used by scientists to get information about the characteristics of the oceans as it was when they were still alive. A good example is whereby a number of forams exist in different types of chemical measurements and ocean environments. Studying the shells can give researchers all the details from the temperature and the chemistry of the ocean when the shell was formed.

The process of evaluating foram shells and their fossils can be very time consuming and tedious. To make this easier, a team of researchers and expertise form the fields of robotics and paleoceanography are working to turning it to an automated process.

According to Edgar Lobaton, an associate professor of electrical and computer engineering from the University of North Carolina, the AI can accurately identify the forams 80 percent of the time which is way better than trained humans.

The system currently works by placing a foram under a microscope, and a LED ring shines on the foram, and 16 directions at a time while taking images of the foram. The 16 images are put together to form geometric information, and the AI uses this to identify the species of the forum.



Describing Science as an Action Draws More Girls to It

It has been noted that whenever you ask girls to ‘do science’ instead of asking them to ‘be scientists,’ they display greater persistence in any science-related activities. Marjorie Rhodes, an associate professor of NYU Department of Psychology, said that when describing science as an action, more engagement and interest in science takes place than giving it an identity.

The effect of describing science as an action is apparent in children who in most cases are the target of stereotypes whereby they may end up not being those people who succeed in science especially in the case of girls.

A study was carried out, and the findings showed the efforts of pushing girls to enter science by describing it as an action rather than telling them to adopt scientific traits. In most cases, girls are often underrepresented in the science field.

According to Rhodes, the beginning of gender disparity in science starts at the early stages of childhood. She added that research carried out was able to identify elements of a children’s environment which can be targeted to reduce the disparity in science among young ones.

Together with Princeton’s Sarah Jane Leslie, Rhodes noted that the information children often receive through the television focus more on identity rather than action. An example was in 2017; an analysis was carried out whereby in children’s television shows, Rhodes was able to find many programs referring to a scientist as a type of person more than they describe science as an activity. It showed how television shows are not using language entirely to encourage girls to practice science.

The study carried out involved children aged four to nine whereby they were introduced to science as an identity and as an action. It was noted that girls who were asked to do science were more persistence in science games than those asked to be scientists.