Other

“Video Demo” provides the video demo of the implemented prototype system as stated in our manuscript "Blockchain and IoT for Insurance: A Case Study and Cyberinfrastructure Solution on Fine-grained Transportation Insurance"

This data-set was used for the localization of an emitter based on Time Difference of Arrival (TDoA). 

The classical least-squares (LS) algorithm, with a limited number of TDoA measurements, has been utilized for obtaining a closed-form solution to the source localization problem. 

An extension of the classical LS algorithm has been employed in an attempt to improve the precision of the localization technique by using a larger set of TDoA estimates.

A new approach for fabricating spot size converters (SSCs), using self-written tapered pillars, is reported.  The method uses a UV-curable resin and mask transfer technique in order to fabricate pillar structures. These structures are designed to couple from Si-wire waveguides to silica single mode fiber (SMF).The technique improvises upon classic single shot fabrication, previously reported using an aperture-limited self-written waveguide (SWW) approach. Design optimization of the SSC was inferred through using a beam propagation method (BPM).

The presented dataset has been used as a basis for CAO - a system for analysis of emoticons in Japanese online communication, developed by Ptaszynski et al. (2010). Emoticons are strings of symbols widely used in text-based online communication to convey user emotions. The database contains: 1) a predetermined raw emoticon database containing over ten thousand emoticon samples extracted from the Web, 2) emoticon parts automatically divided from raw emoticons into semantic areas representing “mouths” or “eyes”.