Lung cancer diagnosis with quantitative DIC microscopy and support vector machine

We report the study of lung squamous cell carcinoma diagnosis using the TI-DIC microscopy and the scattering-phase theorem. The spatially resolved optical properties of tissue are computed from the 2D phase map via the scattering-phase theorem. The scattering coefficient, the reduced scattering coefficient, and the anisotropy factor are all found to increase with the grade of lung cancer. The retrieved optical parameters are shown to distinguish cancer cases from the normal cases with high accuracy. This label-free microscopic approach applicable to fresh tissues may be promising for in situ rapid cancer diagnosis. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

Design and implementation of an RFID-based customer shopping behavior mining system

Shopping behavior data is of great importance in understanding the effectiveness of marketing and merchandising campaigns. Online clothing stores are capable of capturing customer shopping behavior by analyzing the click streams and customer shopping carts. Retailers with physical clothing stores, however, still lack effective methods to comprehensively identify shopping behaviors. In this paper, we show that backscatter signals of passive RFID tags can be exploited to detect and record how customers browse stores, which garments they pay attention to, and which garments they usually pair up. The intuition is that the phase readings of tags attached to items will demonstrate distinct yet stable patterns in a time-series when customers look at, pick out, or turn over desired items. We design ShopMiner, a framework that harnesses these unique spatial-temporal correlations of time-series phase readings to detect comprehensive shopping behaviors. We have implemented a prototype of ShopMiner with a COTS RFID reader and four antennas, and tested its effectiveness in two typical indoor environments. Empirical studies from two-week shopping-like data show that ShopMiner is able to identify customer shopping behaviors with high accuracy and low overhead, and is robust to interference.Department of Computing2016-2017 > Academic research: refereed > Publication in refereed journalbcr