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and tracking systems based on the international standard ISO/IEC 18305. We are interested in hybrid localization methods for solving this challenging problem using a variety of sensors and technologies
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of traditional scientific intelligence with artificial intelligence (AI) to provide humans with actionable intelligence. Augmented intelligent solutions use on-machine sensors for measurements before and during
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sensors for measurements before and during manufacturing processes, analyze the data with a fusion of metrological approaches and machine learning, and monitor and predict the performance of machines and
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boundary effects are of particular interest. Applications include MRAM, field sensors, and nanoparticle systems. key words Magnetic systems; Micromagnetic modeling; Mathematical software; Reference problems
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that the interaction between polymers and a single nanopore provides the physical basis of a multi-analyte sensor. Work is also underway to determine whether this system could be used as tool to rapidly sequence long
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RAP opportunity at National Institute of Standards and Technology NIST Discrete Photon Detection Location Physical Measurement Laboratory, Sensor Science Division opportunity location 50.68.51
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RAP opportunity at National Institute of Standards and Technology NIST Metrology for Semiconductor Manufacturing Location Physical Measurement Laboratory, Sensor Science Division opportunity
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assessed by biomarkers, in situ electrochemical sensors and tissue morphology. key words Organ on chip; Biomechanics; Microfluidics; Bio tissue constructs; Bone; Vascular; Eligibility citizenship Open to U.S
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. Interpretable Deep Learning for Firefighter Health and Sudden Cardiac Death Prevention Develop advanced, interpretable deep-learning models using wearable sensor data (e.g., ECG, heart rate, activity, thermal
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resource constrained devices such as RFID tags, sensors, and medical devices are widely used to transmit sensitive data through wireless interfaces, which need to be protected using cryptographic methods