首页|Reports Outline Machine Learning Findings from South Dakota School of Mines and Technology (Geofingerprinting of Coltan Using Handheld Spectroscopic Devices)
Reports Outline Machine Learning Findings from South Dakota School of Mines and Technology (Geofingerprinting of Coltan Using Handheld Spectroscopic Devices)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating in Rapid City, South Dakota, by NewsRx journalists, research stated, “Following the enactment of the Dodd-Fr ank Act in 2010, specifically Sect. 1502, US companies have been required to rep ort utilizing conflict minerals from the Democratic Republic of Congo (DRC). The conflict mineral coltan, an ore consisting of elements tantalum and niobium, is central to this issue and engenders the need to track and trace the mineral’s s upply chain.”
Rapid CitySouth DakotaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningSo uth Dakota School of Mines and Technology
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