Abstract: Techniques are provided for enhancing the targeting, selection, review, and presentation of online social network (OSN) data pertinent to an evidence context. In one formulation, a concept taxonomy is determined from a request frame relating to targeted OSN data. The concept taxonomy is transformed into query terms for searching targeted OSN data stored in an OSN data collection; a review set of OSN data entities aligned with the request frame is formulated. In another formulation, a presentation model is generated corresponding to an evidence context which is populated with OSN data entities in a review set; the presentation model is displayed on a user interface. Indications of relevance by a user on the user interface change content or properties of the OSN data entities in the review set.

Abstract: A test system for testing a plurality of devices under test is disclosed. The test system includes a tester and a plurality of processors. The tester is used for providing a plurality of control signals and determining a plurality of test results for the devices under test according to a plurality of measurement results. Each processor coupled to the tester is used for generating a plurality of test signals according to the plurality of control signals. The plurality of devices under test respectively generates the plurality of test results according to the plurality of test signals.

Abstract: A technique for analyzing affect in which ambiguity in both emotion and natural language is explicitly represented and processed through fuzzy logic. In particular, textual information is processed to i) isolate a vocabulary of words belonging to an emotion, ii) represent the meaning of each word belonging to that emotion using multiple categories and scalar metrics, iii) compute profiles for text documents based on the categories and scores of their component words, and iv) manipulate the profiles to visualize the texts. The representation vehicle in the system is a set of fuzzy semantic categories (affect categories) followed by their respective centralities (degrees of relatedness between lexicon entries and their various categories) and intensities (representative of the strength of the affect level described by that word) called an affect set. A graphical representation of the affect set can also be used as a tool for decision making.