Ground Plane Slot Structures for Isolation of Cosited Microstrip Antennas

Ground plane slot structures have been shown to reduce coupling between cosited antennas. Although some such structures have already been reported, no analytical model exists to describe their behavior and there are no design guidelines. In this work, the behavior of reported ground plane structures is used as a clue to obtain generalizable information about such structures' behavior. The structures' scalability and excitation behavior is investigated. Next a circuit model is derived that describes the interaction of microstrip patch antennas with a ground plane slot structure based on mutual admittances between the ground plane slots and the effective slots at the antennas' radiating edges. The circuit model leads to design guidelines for the ground plane slot structure and an approximate relationship between mutual admittances which must be satisfied in order to isolate the antennas. Finally, we present a novel ground plane slot structure that mitigates some of the disadvantages of earlier designs.

Discovery driven analysis on semi-structured text data

Discovery Driven Analysis (DDA) is a common feature of OLAP technology to analyze structured data. In essence, DDA helps analysts to discover anomalous data by highlighting 'unexpected' values in the OLAP cube. By giving indications to the analyst on what dimensions to explore, DDA speeds up the process of discovering anomalies and their causes. However, Discovery Driven Analysis (and OLAP in general) is only applicable on structured data, such as records in databases. We propose a system to extend DDA technology to semi-structured text documents, that is, text documents with a few structured data. Our system pipeline consists of two stages: first, the text part of each document is structured around user specified dimensions, using semi-PLSA algorithm; then, we adapt DDA to these fully structured documents, thus enabling DDA on text documents. We present some applications of this system in OLAP analysis and show how scalability issues are solved. Results show that our system can handle reasonable datasets of documents, in real time, without any need for pre-computation.