Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering

In this paper, the answer selection problem in community question answering (CQA) is regarded as an answer sequence labeling task, and a novel approach is proposed based on the recurrent architecture for this problem. Our approach applies convolution neural networks (CNNs) to learning the joint representation of question-answer pair firstly, and then uses the joint representation as input of the long short-term memory (LSTM) to learn the answer sequence of a question for labeling the matching quality of each answer. Experiments conducted on the SemEval 2015 CQA dataset shows the effectiveness of our approach.Comment: 6 page

Coupling light to superconductive photon counters

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 65-66).Superconductive nanowire single-photon detectors (SNSPDs) are an emerging, ultrasensitive photon counting technology which may enable fiber-based, long-haul quantum key distribution. Our group has successfully developed a robust process to fabricate SNSPDs, and has demonstrated device-detection-efficiency above 50% at near infrared wavelengths. However, one remaining challenge must be taken - efficiently coupling light into the detector. This step is difficult because of the small active area of the SNSPD and its low temperature operation. In this thesis, I have designed two experimental setups to couple the light from fiber to the detector at a cryogenic temperature of 4 K: one is for immersion device-testing in a dewar; another is for packaging the detector inside a cryocooler. In addition, I have designed and fabricated SNSPDs suitable for the coupling with single-mode fiber, based on my theoretical calculation of the system detection-efficiency. Some important parameters to characterize the detectors such as system-detection-efficiency, dark-count rate, and counting rate vs. optical input power have been measured.by Xiaolong Hu.S.M

Semi-analytical stochastic study of radionuclide transport in the saturated zone below Yucca Mountain

The objective of this study is to predict radionuclide solute transport process in the saturated zone below the Yucca Mountain project area. Based on a stochastic perturbation approach, a numerical method of moments has been developed and used to predict the mean, variance and upper bound of the radionuclide mass flux through a control plane 5-km downstream of the footprint of the repository. This study enhances the analysis of the effect of medium’s heterogeneity on solute transport prediction, especially on prediction uncertainty