Images on the Web present a major accessibility issue for the visually impaired, mainly because the majority of them do not have proper captions. This paper addresses the problem of attaching proper explanatory text descriptions to arbitrary images on the Web. To this end, we introduce Phetch, an enjoyable computer game that collects explanatory descriptions of images. People play the game because it is fun, and as a side effect of game play we collect valuable information. Given any image from the World Wide Web, Phetch can output a correct annotation for it. The collected data can be applied towards significantly improving Web accessibility. In addition to improving accessibility, Phetch is an example of a new class of games that provide entertainment in exchange for human processing power. In essence, we solve a typical computer vision problem with HCI tools alone.

BackgroundElectronic cigarette (e-cigarette) is an emerging product with a rapid-growth market in recent years. Social media has become an important platform for information seeking and sharing. We aim to mine hidden topics from e-cigarette datasets collected from different social media platforms.ObjectiveThis paper aims to gain a systematic understanding of the characteristics of various types of social media, which will provide deep insights into how consumers and policy makers effectively use social media to track e-cigarette-related content and adjust their decisions and policies.MethodsWe collected data from Reddit (27,638 e-cigarette flavor-related posts from January 1, 2011, to June 30, 2015), JuiceDB (14,433 e-juice reviews from June 26, 2013 to November 12, 2015), and Twitter (13,356 “e-cig ban”-related tweets from January, 1, 2010 to June 30, 2015). Latent Dirichlet Allocation, a generative model for topic modeling, was used to analyze the topics from these data.ResultsWe found four types of topics across the platforms: (1) promotions, (2) flavor discussions, (3) experience sharing, and (4) regulation debates. Promotions included sales from vendors to users, as well as trades among users. A total of 10.72% (2,962/27,638) of the posts from Reddit were related to trading. Promotion links were found between social media platforms. Most of the links (87.30%) in JuiceDB were related to Reddit posts. JuiceDB and Reddit identified consistent flavor categories. E-cigarette vaping methods and features such as steeping, throat hit, and vapor production were broadly discussed both on Reddit and on JuiceDB. Reddit provided space for policy discussions and majority of the posts (60.7%) holding a negative attitude toward regulations, whereas Twitter was used to launch campaigns using certain hashtags. Our findings are based on data across different platforms. The topic distribution between Reddit and JuiceDB was significantly different (P<.001), which indicated that the user discussions focused on different perspectives across the platforms.ConclusionsThis study examined Reddit, JuiceDB, and Twitter as social media data sources for e-cigarette research. These mined findings could be further used by other researchers and policy makers. By utilizing the automatic topic-modeling method, the proposed unified feedback model could be a useful tool for policy makers to comprehensively consider how to collect valuable feedback from social media.

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The multi-dimensional multiplexing technology is very promising for further increasing the link capacity of optical interconnects. A 96-channel silicon-based on-chip reconfigurable optical add-drop multiplexer (ROADM) is proposed and demonstrated for the first time to satisfy the demands in hybrid mode/polarization/wavelengthdivision-multiplexing systems. The present ROADM consists of a six-channel mode/polarization de-multiplexer, a 6 × 16 array of microring-resonator (MRR)-based wavelength-selective switches, and a six-channel mode/polarization multiplexer. With such a ROADM, one can add/drop optical signals to/from any channels of the multimode bus waveguide arbitrarily. For the designed and fabricated ROADM chip, there are more than 1000 elements integrated monolithically, including 96 MRRs, 576 waveguide crossings, 192 grating couplers, 96 micro-heaters, 112 pads, six polarization-splitter-rotators (PSRs), four asymmetric adiabatic couplers and four asymmetric directional couplers. For any channel added/dropped with the fabricated ROADM, the on-chip excess loss is about 5–20 dB, the inter-mode crosstalk is <−12 dB, and the inter-wavelength crosstalk is <−24 dB. The system experiments are demonstrated by using 10-GBaud quadrature phase shift keying (QPSK) signals, showing that the observed optical signal noise ratio (OSNR) power penalties induced by the ROADM are less than 2 dB at a BER of 3.8 × 10−3.

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