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Category: robotics/AI

Built in about 24 hours, this robot is undergoing in-hospital testing for coronavirus disinfection.

UV disinfection is one of the few areas where autonomous robots can be immediately and uniquely helpful during the COVID pandemic. Unfortunately, there aren’t enough of these robots to fulfill demand right now, and although companies are working hard to build them, it takes a substantial amount of time to develop the hardware, software, operational knowledge, and integration experience required to make a robotic disinfection system work in a hospital.

Conor McGinn, an assistant professor of mechanical engineering at Trinity College in Dublin and co-leader of the Robotics and Innovation Lab (RAIL), has pulled together a small team of hardware and software engineers who’ve managed to get a UV disinfection robot into hospital testing within a matter of just a few weeks. They made it happen in such a short amount of time by building on previous research, collaborating with hospitals directly, and leveraging a development platform: the TurtleBot 2.

Over the last few years, RAIL has been researching mobile social robots for elder care applications, and during their pilot testing, they came to understand how big of a problem infection can be in environments like nursing homes. This was well before COVID-19, but it was (and still is) one of the leading causes of hospitalization for nursing home residents. Most places just wipe down surfaces with disinfectant sometimes, but these facilities have many surfaces (like fabrics) that aren’t as easy to clean, and with people coming in and out all the time, anyone with a compromised immune system is always at risk.

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Software bugs have been a concern for programmers for nearly 75 years since the day programmer Grace Murray Hopper reported the cause of an error in an early Harvard Mark II computer: a moth stuck between relay contacts. Thus the term “bug” was born.

Bugs range from slight computer hiccups to catastrophes. In the Eighties, at least five patients died after a Therac-25 radiation therapy device malfunctioned due to an error by an inexperienced programmer. In 1962, NASA mission control destroyed the Mariner I space probe as it diverted from its intended path over the Atlantic Ocean; incorrectly transcribed handwritten code was blamed. In 1982, a later alleged to have been implanted into the Soviet trans-Siberian gas pipeline by the CIA triggered one of the largest non– in history.

According to data management firm Coralogix, programmers produce 70 bugs per 1,000 lines of code, with each bug solution demanding 30 times more hours than it took to write the code in the first place. The firm estimates the United States spends $113 billion a year identifying and remediating bugs.

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After testing on public roads, Tesla is rolling out a new feature of its partially automated driving system designed to spot stop signs and traffic signals.

The update of the electric car company’s cruise control and auto-steer systems is a step toward CEO Elon Musk’s pledge to convert cars to fully self-driving vehicles later this year.

But it also runs contrary to recommendations from the U.S. National Transportation Safety Board that include limiting where Tesla’s Autopilot driving system can operate because it has failed to spot and react to hazards in at least three fatal crashes.

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I got my rig in the back of my Beemer. Professional when I graze, I’m professional when I argue. 40 glass, I’m laughing at that s***, I’ma be roaring at that s***

The experiment also revealed which genres are hardest for AI songwriters to master.

The respondents struggled to spot which pop and country lyrics were written by an AI. And its rock song was so emo that they thought it was written by My Chemical Romance or Nirvana.

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Hundreds of books are now free to download.

Springer has released hundreds of free books on a wide range of topics to the general public. The list, which includes 408 books in total, covers a wide range of scientific and technological topics. In order to save you some time, I have created one list of all the books (65 in number) that are relevant to the data and Machine Learning field.

Among the books, you will find those dealing with the mathematical side of the domain (Algebra, Statistics, and more), along with more advanced books on Deep Learning and other advanced topics. You also could find some good books in various programming languages such as Python, R, and MATLAB, etc.

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This is the seventh in a series on the impact of the coronavirus on China’s technology sector.

China’s robotics market is forecast to reach US$103.6 billion by 2023, driven by manufacturing, consumer, retail, health care and resource applications.

Chinese robotics companies have seen a surge in demand since the coronavirus outbreak but some believe robot tech is not mature enough for widespread use.

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Existing electronic skin (e-skin) sensing platforms are equipped to monitor physical parameters using power from batteries or near-field communication. For e-skins to be applied in the next generation of robotics and medical devices, they must operate wirelessly and be self-powered. However, despite recent efforts to harvest energy from the human body, self-powered e-skin with the ability to perform biosensing with Bluetooth communication are limited because of the lack of a continuous energy source and limited power efficiency. Here, we report a flexible and fully perspiration-powered integrated electronic skin (PPES) for multiplexed metabolic sensing in situ. The battery-free e-skin contains multimodal sensors and highly efficient lactate biofuel cells that use a unique integration of zero- to three-dimensional nanomaterials to achieve high power intensity and long-term stability. The PPES delivered a record-breaking power density of 3.5 milliwatt·centimeter−2 for biofuel cells in untreated human body fluids (human sweat) and displayed a very stable performance during a 60-hour continuous operation. It selectively monitored key metabolic analytes (e.g., urea, NH4+, glucose, and pH) and the skin temperature during prolonged physical activities and wirelessly transmitted the data to the user interface using Bluetooth. The PPES was also able to monitor muscle contraction and work as a human-machine interface for human-prosthesis walking.

Recent advances in robotics have enabled soft electronic devices at different scales with excellent biocompatibility and mechanical properties; these advances have rendered novel robotic functionalities suitable for various medical applications, such as diagnosis and drug delivery, soft surgery tools, human-machine interaction (HMI), wearable computing, health monitoring, assistive robotics, and prosthesis (1–6). Electronic skin (e-skin) can have similar characteristics to human skin, such as mechanical durability and stretchability and the ability to measure various sensations such as temperature and pressure (7–11). Moreover, e-skin can be augmented with capabilities beyond those of the normal human skin by incorporating advanced bioelectronics materials and devices.

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Researchers at Bilkent University in Turkey have recently created a small quadruped robot called SQuad, which is made of soft structural materials. This unique robot, presented in a paper published in IEEE Robotics and Automation Letters, is more flexible than existing miniature robots and is thus better at climbing or circumventing obstacles in its surroundings.

“We have been working on for almost a decade now,” Onur Ozcan, one of the researchers who carried out the study, told TechXplore. “Even though miniature robots have many advantages, such as being cheap, as they require fewer materials, and the ability to access confined spaces, one of their major drawbacks is their lack of locomotion capabilities, especially on uneven terrain.”

Tiny robots tend to get stuck easily while moving in the surrounding environment, as their height does not allow them to climb or avoid obstacles. Ozcan and his colleagues tried to overcome this limitation by implementing a principle known as ‘body compliance.”

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The main idea of artificial neural networks (ANN) is to build up representations for complicated functions using compositions of relatively simple functions called layers.

A deep neural network is one that has many layers, or many functions composed together.

Although layers are typically simple functions(e.g. relu(Wx + b)) in general they could be any differentiable functions.

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