Abstract: Due to design variations, process variations, manufacturing variations, and other factors, memory of a certain type manufactured by one manufacturer often exhibits a unique pattern of performance characteristics relative to the patterns of the same type of performance characteristics exhibited by memory from other manufacturers. A system for identifying counterfeit memory is trained to learn the different patterns of performance characteristics for different manufacturers of memory. Thereafter, the system may analyze the performance of a given memory device to determine whether the memory device has been manufactured by a particular manufacturer. Thus, the system is capable of determining whether the memory device is counterfeit (e.g., has been manufactured by an unexpected manufacturer).

Abstract: A system for testing memory includes logic that is configured to perform various normal memory operations (e.g., erase, read and write operations) on a memory device and to determine operational parameters associated with the memory operations. As an example, the amount of time to perform one or more memory operations may be measured, or a number of errors resulting from the memory operations may be counted or otherwise determined. One or more of the operational parameters may then be analyzed to determine whether they are in a range expected for counterfeit memory. If so, the logic determines that the memory under test is counterfeit (e.g., is recycled or counterfeit) and provides a notification about the authenticity of the memory. The logic may also estimate the age of the memory based on the operational parameters.

Abstract: Due to design variations, process variations, manufacturing variations, and other factors, memory of a certain type manufactured by one manufacturer often exhibits a unique pattern of performance characteristics relative to the patterns of the same type of performance characteristics exhibited by memory from other manufacturers. A system for identifying counterfeit memory is trained to learn the different patterns of performance characteristics for different manufacturers of memory. Thereafter, the system may analyze the performance of a given memory device to determine whether the memory device has been manufactured by a particular manufacturer. Thus, the system is capable of determining whether the memory device is counterfeit (e.g., has been manufactured by an unexpected manufacturer).

Abstract: A system is provided that predicts eating events for a user. The system includes a set of sensors each of which is configured to continuously measure a different physiological variable associated with the user and output a time-stamped data stream that includes the current value of this variable. A set of features is periodically extracted from the data stream output from each of the sensors, where these features have been determined to be specifically indicative of an about-to-eat moment. This set of features is then input into an about-to-eat moment classifier that has been trained to predict when the user is in an about-to-eat moment based on this set of features. Whenever an output of the classifier indicates that the user is currently in an about-to-eat moment, the user is notified with a just-in-time eating intervention.

Abstract: Methods, systems, and devices are disclosed for implementing mobile sensing of non-speech sounds from a human. In one aspect, a mobile sensing system includes a microphone to capture a diverse set of body sounds while dampening external sounds and ambient noises, wherein the captured diverse set of body sounds are not speech. The mobile sensing system includes a micro-controller in communication with the microphone to perform an algorithm for signal processing and machine learning using the captured diverse set of body sounds.