Abstract: The present invention is to accurately obtain a vehicle element response data under a desired driving environment by simulation without performing actual road driving and is a vehicle element response learning method for generating a trained model related to a response of a vehicle element that is a vehicle or a part of the vehicle, and the method includes: (1) an input step of giving an input including parameters related to a vehicle speed, a load, and a temperature assuming actual road driving, to the vehicle element; (2) an acquisition step of acquiring response data of the vehicle element and acquiring, as training data, input data representing the input and the response data; and (3) a generation step of generating the trained model related to the response of the vehicle element, from the training data by using machine learning.

Abstract: Graphene-impregnated microfiber fabrics and methods for producing such fabrics are disclosed. In one example, a method of producing a graphene-impregnated microfiber fabric comprises providing a microfiber substrate comprising polymer fibers. Graphene is mixed into a polymer-based dispersion to create a graphene-impregnated polymer-based dispersion. The graphene-impregnated microfiber fabric is formed by immersing the microfiber substrate in the graphene-impregnated polymer-based dispersion to coat the polymer fibers of the substrate with the graphene and the polymer of the polymer-based dispersion. The fabric is removed from the dispersion and dried.

Abstract: Electronic devices that include fabric surfaces can periodically require cleaning. Methods and tools for safely and reliably cleaning such surfaces are disclosed. The method includes application of a cleaning pad impregnated with a cleaning agent for a predetermined period of time. The cleaning pad is configured to remove stains and contaminants from the surface through a measured approach.