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Design007-June2021

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JUNE 2021 I DESIGN007 MAGAZINE 81 References 1. Ohmega Technologies has been acquired by Quantic Electronics, a business unit of Arcline Investments which focuses on specialty component materials. More recently, Quantic also acquired Ticer Technologies. The company stated that it plans to maintain multi-plant resistive foil opera- tions for both OhmegaPly and Ticer TCR materials. 2. For more information refer to the Power Dis- sipation Guidelines contained within the Resistor Calculators on both Ticer's and Ohmega's websites. Vern Solberg is an independent technical consultant, special- izing in SMT and microelectron- ics design and manufacturing technology. Read part one of this column, "The 'New and Growing' Embedded Resistors." To read past columns or contact Solberg, click here. Implementation Issues and Concerns Formed passive resistor element values and tolerance that range between 5–10% will likely meet the operational criteria of the final product but altering the value aer lamination will not be an option. Due to the physical stresses experienced during PCB lamination and assembly processing, target values of resistors may dri outside the speci- fied resistance target, and laser trimming will not be practical. When the specified values of the resistor elements require tolerance in the 1-2% range, I strongly advise the circuit bo ard designer to retain these higher precision resis- tors as discrete surface mount components for placement onto the circuit board's outer surface(s). DESIGN007 A major challenge for fully autonomous vehicles is navigating bad weather. Snow especially con- founds crucial sensor data that helps a vehicle gauge depth, find obstacles, and keep on the cor- rect side of the yellow line, assuming it is visible. Averaging more than 200 inches of snow every winter, Michigan's Keweenaw Peninsula is the per- fect place to push autonomous vehicle tech to its limits. In two papers presented at SPIE Defense + Commercial Sensing 2021, researchers from Michi- gan Technological University discuss solutions for snowy driving scenarios that could help bring self- driving options to snowy cities like Chicago, Detroit, Minneapolis and Toronto. Since artificial brains aren't around yet, task- specific AI algorithms must take the wheel—which means autonomous vehicles must rely on multiple sensors. Fisheye cameras widen the view while other cameras act much like the human eye. Infra- red picks up heat signatures. Radar can see through the fog and rain. Light detection and ranging (lidar) pierces through the dark and weaves a neon tap- estry of laser beam threads. Using sensor fusion, Rawashdeh and Bos want autonomous sensors to collectively figure out the answer—be it elephant, deer, or snowbank. As Bos puts it, "Rather than strictly voting, by using sensor fusion we will come up with a new estimate." While navigating a Keweenaw blizzard is a ways out for autonomous vehicles, their sensors can get better at learning about bad weather and, with advances like sensor fusion, will be able to drive safely on snowy roads one day. (Source: Michigan State University) Driving in the Snow is a Team Effort for AI Sensors

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