Abstract: An area selection-based document object model element inspector is described. A dragging input that defines a selection area of a digital content document having a plurality of elements is received via an area selection-based inspector tool. A set of elements of the plurality of elements that is positioned within the selection area is selected. Details of the selected set of elements are broadcast for display.

Abstract: Apparatus and techniques for an integrated circuit (IC) package to automatically detect, through an input/out pin, external component parameters and parasitics. An example IC package generally includes a pin for coupling to a component external to the IC package, and at least one of a resistance detector, an inductance detector, or a capacitance detector coupled to the pin, and configured to detect at least one of a resistance, an inductance, or a capacitance, respectively, of a lumped parameter model for the component external to the IC package. The resistance detector, inductance detector, or capacitance detector may also be configured to detect parasitics associated with at least one of the component, the pin, or a connection between the component and the pin.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums which provide summaries of topics determined within a corpus of documents. These summaries may be used by customer service associates, analysts, or other users to quickly determine both topics discussed and contexts of those topics over a large corpus of text. For example, a corpus of documents may be related to customer complaints and the topics may be summarized to produce summaries such as “credit report update due to stolen identity.” These summarizations may be used to efficiently spot trends and issues.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums which provide summaries of topics determined within a corpus of documents. These summaries may be used by customer service associates, analysts, or other users to quickly determine both topics discussed and contexts of those topics over a large corpus of text. For example, a corpus of documents may be related to customer complaints and the topics may be summarized to produce summaries such as “credit report update due to stolen identity.” These summarizations may be used to efficiently spot trends and issues.