Status of the micro-X sounding rocket x-ray spectrometer

Micro-X is a sounding rocket borne X-ray telescope that utilizes transition edge sensors to perform imaging spectroscopy with a high level of energy resolution. Its 2.1m focal length X-ray optic has an effective area of 300 cm 2 , a field of view of 11.8 arcmin, and a bandpass of 0.1-2.5 keV. The detector array has 128 pixels and an intrinsic energy resolution of 4.5 eV FWHM. The integration of the system has progressed with functional tests of the detectors and electronics complete, and performance characterization of the detectors is underway. We present an update of ongoing progress in preparation for the upcoming launch of the instrument.NASA Space Technology Research FellowshipUnited States. National Aeronautics and Space Administration (grant NNX10AE25G

Interpreting author intentions by analyzing story modulation

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 75-76).If we are to understand human intelligence, then we need to understand human story understanding competencies, including our ability to communicate. Communication can be thought of as an externalization of an inner model of the world or an attempt to shape the inner model of the world of another. To communicate effectively, humans must analyze not only what is said, but also how it is said. My goal in this work was to develop a cognitive model of how we produce a coherent argument, explain its elements, and provide a full analysis of authorial intent. In this thesis, I propose a cognitive model of Story Modulation, or how humans glean information about a communicator's intentions or attempt to shape the inner story of their audience via key characteristics of wording. The model explains how we assemble textual evidence such as passive voice, instances of harm, and use of hedging words such as alleged, to tell a coherent story of the communicator's rhetorical goals. I demonstrate this computational model with an implementation, RASHI, that recognizes and systematically highlights intentions. The implementation reads short news-like stories in simple English and identifies modulations in text that reveal the author's intent to influence three areas-sympathy, agency, and doubt. The system gathers objective evidence using a system of modular experts, interprets the evidence with culturally-specfic subjectivity models, and distills the potentially-conflicting interpretations into a short, coherent argument about the author's intentions. I argue that RASHI, as a computational model of human communication, can be used to improve discourse surrounding the media, elevate education in critical reading, facilitate political negotiations and resolutions, and help us bridge gaps across cultures by transforming stories to be more culturally appropriate.by Suri C. Bandler.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc