Lifeboat Foundation

Smile! You’re on camera — or you were at some point in the past few years — and now your face is public domain.

Facial recognition technology is everywhere, and only becoming more pervasive. It’s marketed as a security feature by companies like Apple and Google to prevent strangers from unlocking your iPhone or front door.

It’s also used by government agencies like police departments. More than half of adult Americans’ faces are logged in police databases, according to a study by Georgetown researchers. Facial recognition technology is used by governments across the globe to identify and track dissidents, and has been deployed by police against Hong Kong protesters.

Something called the fast Fourier transform is running on your cell phone right now. The FFT, as it is known, is a signal-processing algorithm that you use more than you realize. It is, according to the title of one research paper, “an algorithm the whole family can use.”

Alexander Stoytchev – an associate professor of electrical and computer engineering at Iowa State University who’s also affiliated with the university’s Virtual Reality Applications Center, its Human Computer Interaction graduate program and the department of computer science – says the FFT algorithm and its inverse (known as the IFFT) are at the heart of signal processing.

And, as such, “These are algorithms that made the digital revolution possible,” he said.

Semiconductors are the basic building blocks of today’s digital, electronic age, providing us a multitude of devices that benefit our modern life, including computer, smartphones and other mobile devices. Improvements in semiconductor functionality and performance are likewise enabling next-generation applications of semiconductors for computing, sensing and energy conversion. Yet researchers have long struggled with limitations in our ability to fully understand the electronic charges inside semiconductor devices and advanced semiconductor materials, limiting our ability to drive further advances.

In a new study in the journal Nature, an IBM Research-led collaboration describes an exciting breakthrough in a 140-year-old mystery in physics—one that enables us to unlock the physical characteristics of semiconductors in much greater detail and aid in the development of new and improved semiconductor materials.

To truly understand the physics of semiconductors, we first need to know the fundamental properties of the charge carriers inside the materials, whether those particles are positive or negative, their speed under an applied electric field and how densely they are packed in the material. Physicist Edwin Hall found a way to determine those properties in 1879, when he discovered that a magnetic field will deflect the movement of electronic charges inside a conductor and that the amount of deflection can be measured as a voltage perpendicular to the flow of charge as shown in Fig. 1a. This voltage, known as the Hall voltage, unlocks essential information about the charge carriers in a semiconductor, including whether they are negative electrons or positive quasi-particles called “holes,” how fast they move in an electric field or their “mobility” (µ) and their density (n) inside the semiconductor.

The 2019 Nobel Prize in Chemistry was awarded to John B. Goodenough (The University of Texas at Austin), M. Stanley Whittingham (Binghamton University, State University of New York), and Akira Yoshino (Asahi Kasei Corporation and Meijo University) “for the development of lithium-ion batteries”. With the creation and subsequent optimization of lithium-ion batteries to make them more powerful, lighter, and more robust, the seminal work of Goodenough, Whittingham, and Yoshino has had a profound impact on our modern society. This ubiquitous technology has revolutionized our daily lives by paving the way for portable electronics and made renewable energy sources more viable. While attempts to improve the performance of batteries continue, the lithium-ion battery has remained the world’s most reliable battery system for more than 40 years. The three winners will each receive an equal share of the roughly $1 million award. At 97, Goodenough is now the oldest person ever to win the Nobel Prize.

“A long-awaited recognition for the creators of lithium-ion batteries has come true. The electrochemistry and material science communities – and the greater chemistry community as a whole – are excited to hear the news of the 2019 Nobel Prize award to John B. Goodenough, M. Stanley Whittingham, and Akira Yoshino for their pioneering contribution to lithium-ion batteries,” said ACS Energy Letters Editor-in-Chief Prashant Kamat. “As we all know, the lithium-ion battery has revolutionized our modern-day activities. From mobile phones to laptops and from electronic gadgets to electric cars, these storage batteries have become part of our everyday life. We at ACS Publications are excited to be part of this celebration.”

Whittingham laid the foundation of the lithium-ion battery while working at Exxon in the 1970s. During that time, the oil crisis in the United States was ongoing, and there was a strong drive to develop methods of energy storage and transport that did not rely on fossil fuels. Whittingham developed a 2V lithium-ion battery based on a titanium disulfide cathode and lithium metal anode. While a seminal contribution to the advancement of the lithium battery, adopting Whittingham’s system for everyday use would be limiting due to the high reactivity of lithium metal and risk of explosion.

Something called the fast Fourier transform is running on your cell phone right now. The FFT, as it is known, is a signal-processing algorithm that you use more than you realize. It is, according to the title of one research paper, “an algorithm the whole family can use.”

Alexander Stoytchev—an associate professor of electrical and computer engineering at Iowa State University who’s also affiliated with the university’s Virtual Reality Applications Center, its Human Computer Interaction graduate program and the department of computer science—says the FFT algorithm and its inverse (known as the IFFT) are at the heart of signal processing.

And, as such, “These are algorithms that made the digital revolution possible,” he said.

Researchers have found a way to marry human creativity and artificial intelligence (AI) creativity to dramatically boost the performance of deep learning.

A team led by Alexander Wong, a Canada Research Chair in the area of AI and a professor of systems design engineering at the University of Waterloo, developed a new type of compact family of neural networks that could run on smartphones, tablets, and other embedded and mobile devices.

Our first encounter with E.T. technology could be as baffling to us as a smartphone would have been to a Neandertal.

A team of researchers from Baylor University, with assistance from staff at the Massachusetts Eye and Ear Infirmary, Harvard Medical School and the Dana-Farber Cancer Institute has developed and tested a smartphone app that is able to detect “white eye” in children by analyzing stored photographs. In their paper published in the journal Science Advances, the group describes how the app was developed and tested, and how well it works.

Most everyone has seen pictures of people seemingly possessed by the devil because their pupils glow red—this is caused by light bouncing off their retinas. However, such pictures sometimes produce white instead of red retinas. Sometimes it can happen due to ambient lighting conditions, but other times, it can indicate an eye ailment. Such problems can include retinoblastoma, a type of eye cancer, retinopathy, or even cataracts.

The idea for an app that could detect white eye came from the experience of one of the researchers, Brian Shaw, and his son, who developed retinoblastoma and subsequently lost an eye. The team developed the app and made it available to the public back in 2014, but it was not until more recently that the team decided to test the app to see how well it works.

Washington — Researchers have developed a new microwave imager chip that could one day enable low-cost handheld microwave imagers, or cameras. Because microwaves can travel through certain opaque objects, the new imagers could be useful for imaging through walls or detecting tumors through tissue in the body.

In Optica, The Optical Society’s (OSA) journal for high-impact research, the researchers describe how they used a standard semiconductor fabrication process to make a microwave imager chip containing more than 1,000 photonic components. The square chip measures just over 2 millimeters on each side, making it about half the width of a pencil eraser.

“Today’s practical microwave imagers are bench-top systems that are bulky and expensive,” said research team leader Firooz Aflatouni from the University of Pennsylvania, USA. “Our new near-field imager uses optical, rather than electronic, devices to process the microwave signal. This enabled us to make a chip-based imager similar to the optical camera chips in many smartphones.”