Machine Learning Based Prediction: Health Behavior on BP


Source: UC San Diego Jacobs School of Engineering, Po-Han Chiang and Sujit Dey, Mobile Systems Design Lab, Dept. of Electrical and Computer Engineering Using wearable off-the-shelf technology and machine learning, UC San Diego researchers have developed a method to predict an individual’s blood pressure and provide personalized recommendations to lower it based on this data. The resea... » read more

System Bits: Oct. 9


Sensing with light pulses In a development expected to be useful in applications including distance measurement, molecular fingerprinting and ultrafast sampling, EPFL researchers have found a way to implement an optical sensing system by using spatial multiplexing, a technique originally developed in optical-fiber communication, which produces three independent streams of ultrashort optical pu... » read more

Power/Performance Bits: Aug. 28


Multilayer stretchable electronics Researchers at UC San Diego, the University of Electronic Science and Technology of China, and the Air Force Research Laboratory developed an approach to creating stacked, stretchable electronics with complex functionality. "Rigid electronics can offer a lot of functionality on a small footprint--they can easily be manufactured with as many as 50 layers of... » read more

Making Organic Semiconductors Plastic


Plastic. The very word implies deformability, the ability to bend and flex without damage in response to stress. In applications from biomedical sensors to solar cells, the potential advantages of organic semiconductors depend almost entirely on their deformability—are they flexible enough for inexpensive roll-to-roll processing? Able to tolerate flexion in use? Able to do without the bulky a... » read more

System Bits: May 29


Ultra-low-power sensors carrying genetically engineered bacteria to detect gastric bleeding In order to diagnose bleeding in the stomach or other gastrointestinal problems, MIT researchers have built an ingestible sensor equipped with genetically engineered bacteria. [caption id="attachment_24134598" align="alignleft" width="300"] MIT engineers have designed an ingestible sensor equipped with... » read more

System Bits: May 15


Navigating with GPS and sensors According to MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers, navigating roads less traveled in self-driving cars is a difficult task mainly because self-driving cars are usually only tested in major cities where countless hours have been spent meticulously labeling the exact 3D positions of lanes, curbs, off-ramps, and stop signs... » read more

System Bits: Nov. 14


Tracking cyber attacks According to Georgia Tech, assessing the extent and impact of network or computer system attacks has been largely a time-consuming manual process, until now since a new software system being developed by cybersecurity researchers here will largely automate that process, allowing investigators to quickly and accurately pinpoint how intruders entered the network, what data... » read more

Using Machine Learning In EDA


Machine learning is beginning to have an impact on the EDA tools business, cutting the cost of designs by allowing tools to suggest solutions to common problems that would take design teams weeks or even months to work through. This reduces the cost of designs. It also potentially expands the market for EDA tools, opening the door to even new design starts and more chips from more compan... » read more

Machine Learning Popularity Grows


Machine learning and deep learning are showing a sharp growth trajectory in many industries. Even the semiconductor industry, which generally has resisted this technology, is starting to changing its tune. Both [getkc id="305" kc_name="machine learning"] (ML) and deep learning (DL) have been successfully used for image recognition in autonomous driving, speech recognition in natural langua... » read more

The Darker Side Of Machine Learning


Machine learning can be used for many purposes, but not all of them are good—or intentional. While much of the work underway is focused on the development of machine learning algorithms, how to train these systems and how to make them run faster and do more, there is a darker side to this technology. Some of that involves groups looking at what else machine learning can be used for. So... » read more

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