Abstract: Methods and semiconductor devices are provided. A method includes determining a location of a polyimide opening (PIO) corresponding to an under-bump metallization (UBM) feature in a die. The die includes a substrate and an interconnect structure over the substrate. The method also includes determining a location of a stacked via structure in the interconnect structure based on the location of the PIO. The method further includes forming, in the interconnect structure, the stacked via structure comprising at most three stacked contact vias at the location of the PIO.

Abstract: The present disclosure provides a battery charging system and method. The battery charging method includes: determining a degree of healthy of a battery module according to an evaluation mechanism; setting a charging standard according to the degree of healthy; by handshaking with a charger, setting a charging voltage for the charger according to the charging standard to charge the battery module; and by the charger, perform a charging operation on the battery module until a fully charged condition is satisfied.

Abstract: One aspect of the invention is generating for a client (a marketer) a measure of relevance of online creative content for online marketing to a set of target users. Another is an interactive user interface for displaying such a measure. Another aspect of the invention is determining a signature of creative content and of components thereof. The measure of relevance is based on profiles of the targeted users and on the signature of the creative content. Another aspect of the invention providing a mechanism to improve the relevance by modifying one or more components of the creative content with respective alternate components, thus suggesting to the client modifications to the content together with a measure of how such modification changes the relevance. Another aspects is providing for an operator the user interface for viewing in real time the effect of such modifications.

Abstract: A method and system provides for: training at least one machine-learning method of predicting psychometric profiles of individual users in an online population based on automatically collected records of their online behavior; using the resulting predicted psychometric profiles and engagement data on users to learn an engagement model of likelihood of engaging with a stimulus based on psychometric dimensions; and using the engagement model on a population to determine audiences for the stimulus ranked according to predicted likelihood of engagement. The method and system are able to maintain anonymity of the users.