Abstract: A medical equipment distribution assembly includes a housing, an electronic control unit (ECU), a camera assembly, a thermal imaging unit, and/or at least one medical kit. The ECU may be electrically connected with the camera assembly and/or the thermal imaging unit. The ECU may be configured to receive identifying information via the camera assembly and/or the thermal imaging unit. The ECU may be configured to identify an individual substantially proximate the housing and/or the camera assembly; determine if said individual is experiencing a fever; and/or distribute a medical kit to said individual.

Abstract: A system predicts die loss for a semiconductor wafer by using a method referred to as universal in-line metric (UILM). A wafer inspection tool detects defects on the wafer and identifies the defects by various defect types. The UILM method applies to various ways of classification of the defect types and takes into account the impact of each defect type on the die loss.

Abstract: A portable display arrangement for the display of graphics at a conference or like event includes a plurality of flexible display panels. The plurality of flexible display panels wrap around a common axis to form a roll. A shipping container defines a storage cavity receives and supports the roll. A plurality of tubular members for suspending the plurality of flexible display panels from one or more trusses or other suspension structure are disposed in the storage cavity.

Abstract: A test method provides a sample of wafer level defects most likely to cause yield loss on a semiconductor wafer subdivided into a plurality of integrated circuits (ICs). Defect size and location data from an inspection tool is manipulated in an algorithm based on defect sizes and geometry parameters. The defects are classified by defect size to form size based populations. The contribution of each size range of defect population to yield loss is calculated and random samples for review are selected from each defect size population. The number of samples from each size defect population is proportional to the predicted yield impact of each sample. The method is rapid and permits on-line process modification to reduce yield losses.