Accurate and budget-efficient text, image, and video analysis systems powered by the crowd

Crowdsourcing systems empower individuals and companies to outsource labor-intensive tasks that cannot currently be solved by automated methods and are expensive to tackle by domain experts. Crowdsourcing platforms are traditionally used to provide training labels for supervised machine learning algorithms. Crowdsourced tasks are distributed among internet workers who typically have a range of skills and knowledge, differing previous exposure to the task at hand, and biases that may influence their work. This inhomogeneity of the workforce makes the design of accurate and efficient crowdsourcing systems challenging. This dissertation presents solutions to improve existing crowdsourcing systems in terms of accuracy and efficiency. It explores crowdsourcing tasks in two application areas, political discourse and annotation of biomedical and everyday images. The first part of the dissertation investigates how workers' behavioral factors and their unfamiliarity with data can be leveraged by crowdsourcing systems to control quality. Through studies that involve familiar and unfamiliar image content, the thesis demonstrates the benefit of explicitly accounting for a worker's familiarity with the data when designing annotation systems powered by the crowd. The thesis next presents Crowd-O-Meter, a system that automatically predicts the vulnerability of crowd workers to believe \enquote{fake news} in text and video. The second part of the dissertation explores the reversed relationship between machine learning and crowdsourcing by incorporating machine learning techniques for quality control of crowdsourced end products. In particular, it investigates if machine learning can be used to improve the quality of crowdsourced results and also consider budget constraints. The thesis proposes an image analysis system called ICORD that utilizes behavioral cues of the crowd worker, augmented by automated evaluation of image features, to infer the quality of a worker-drawn outline of a cell in a microscope image dynamically. ICORD determines the need to seek additional annotations from other workers in a budget-efficient manner. Next, the thesis proposes a budget-efficient machine learning system that uses fewer workers to analyze easy-to-label data and more workers for data that require extra scrutiny. The system learns a mapping from data features to number of allocated crowd workers for two case studies, sentiment analysis of twitter messages and segmentation of biomedical images. Finally, the thesis uncovers the potential for design of hybrid crowd-algorithm methods by describing an interactive system for cell tracking in time-lapse microscopy videos, based on a prediction model that determines when automated cell tracking algorithms fail and human interaction is needed to ensure accurate tracking

Teaching with Big Data: Report from the 2016 Society for Neuroscience Teaching Workshop

As part of a series of workshops on teaching neuroscience at the Society for Neuroscience annual meetings, William Grisham and Richard Olivo organized the 2016 workshop on Teaching Neuroscience with Big Data. This article presents a summary of that workshop. Speakers provided overviews of open datasets that could be used in teaching undergraduate courses. These included resources that already appear in educational settings, including the Allen Brain Atlas (presented by Joshua Brumberg and Terri Gilbert), and the Mouse Brain Library and GeneNetwork (presented by Robert Williams). Other resources, such as NeuroData (presented by William R. Gray Roncal), and OpenFMRI, NeuroVault, and Neurosynth (presented by Russell Poldrack) have not been broadly utilized by the neuroscience education community but offer obvious potential. Finally, William Grisham discussed the iNeuro Project, an NSF-sponsored effort to develop the necessary curriculum for preparing students to handle Big Data. Linda Lanyon further elaborated on the current state and challenges in educating students to deal with Big Data and described some training resources provided by the International Neuroinformatics Coordinating Facility. Neuroinformatics is a subfield of neuroscience that deals with data utilizing analytical tools and computational models. The feasibility of offering neuroinformatics programs at primarily undergraduate institutions was also discussed

The natverse, a versatile toolbox for combining and analysing neuroanatomical data.

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community

PROGRAM and PROCEEDINGS THE NEBRASKA ACADEMY OF SCIENCES: 139th Anniversary Year, One Hundred-Twenty-Ninth Annual Meeting, April 12, 2019, NEBRASKA WESLEYAN UNIVERSITY, LINCOLN, NEBRASKA

PROGRAM AT-A-GLANCE FRIDAY, APRIL 12, 2019 7:30 a.m. REGISTRATION OPENS - Lobby of Lecture Wing, Olin Hall 8:00 Aeronautics and Space Science, Session A – Acklie 109 Aeronautics and Space Science, Session B – Acklie 111 Collegiate Academy; Biology, Session B - Olin B Biological and Medical Sciences, Session A - Olin 112 Biological and Medical Sciences, Session B - Smith Callen Conference Center Chemistry and Physics; Chemistry - Olin A 8:00 “Teaching and Learning the Dynamics of Cellular Respiration Using Interactive Computer Simulations” Workshop – Olin 110 9:30 “Life After College: Building Your Resume for the Future” Workshop – Acklie 218 8:25 Collegiate Academy; Chemistry and Physics, Session A – Acklie 007 8:36 Collegiate Academy; Biology, Session A - Olin 111 9:00 Chemistry and Physics; Physics – Acklie 320 9:10 Aeronautics and Space Science, Poster Session – Acklie 109 & 111 10:30 Aeronautics and Space Science, Poster Session – Acklie 109 & 111 11:00 MAIBEN MEMORIAL LECTURE: Dr David Swanson - OLIN B Scholarship and Friend of Science Award announcements 12:00 p.m. LUNCH – WESLEYAN CAFETERIA Round-Table Discussion – “Assessing the Academy: Current Issues and Avenues for Growth” led by Todd Young – Sunflower Room 12:50 Anthropology – Acklie 109 1:00 Applied Science and Technology - Olin 111 Biological and Medical Sciences, Session C - Olin 112 Biological and Medical Sciences, Session D - Smith Callen Conference Center Chemistry and Physics; Chemistry - Olin A Collegiate Academy; Biology, Session B - Olin B Earth Science – Acklie 007 Environmental Sciences – Acklie 111 Teaching of Science and Math – Acklie 218 1:20 Chemistry and Physics; Physics – Acklie 320 4:30 BUSINESS MEETING - OLIN B NEBRASKA ASSOCIATION OF TEACHERS OF SCIENCE (NATS) The 2019 Fall Conference of the Nebraska Association of Teachers of Science (NATS) will be held at the Younes Conference Center, Kearney, NE, September 19-21, 2019. President: Betsy Barent, Norris Public Schools, Firth, NE President-Elect: Anya Covarrubias, Grand Island Public Schools, Grand Island, NE AFFILIATED SOCIETIES OF THE NEBRASKA ACADEMY OF SCIENCES, INC. 1. American Association of Physics Teachers, Nebraska Section Web site: http://www.aapt.org/sections/officers.cfm?section=Nebraska 2. Friends of Loren Eiseley Web site: http://www.eiseley.org/ 3. Lincoln Gem & Mineral Club Web site: http://www.lincolngemmineralclub.org/ 4. Nebraska Chapter, National Council for Geographic Education 5. Nebraska Geological Society Web site: http://www.nebraskageologicalsociety.org Sponsors of a $50 award to the outstanding student paper presented at the Nebraska Academy of Sciences Annual Meeting, Earth Science /Nebraska Chapter, Nat\u27l Council Sections 6. Nebraska Graduate Women in Science 7. Nebraska Junior Academy of Sciences Web site: http://www.nebraskajunioracademyofsciences.org/ 8. Nebraska Ornithologists’ Union Web site: http://www.noubirds.org/ 9. Nebraska Psychological Association http://www.nebpsych.org/ 10. Nebraska-Southeast South Dakota Section Mathematical Association of America Web site: http://sections.maa.org/nesesd/ 11. Nebraska Space Grant Consortium Web site: http://www.ne.spacegrant.org

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE