Recent Submissions

  • The Acidity of Atmospheric Particles and Clouds 

    Pye, Havala O. T.; Nenes, Athanasios; Alexander, Becky; Ault, Andrew P.; Barth, Mary C.; Clegg, Simon L.; Collett, Jeffrey L. Jr.; Fahey, Kathleen M.; Hennigan, Christopher J.; Herrmann, Hartmut; Kanakidou, Maria; Kelly, James T.; Ku, I-Ting; McNeill, V. Faye; Riemer, Nicole; Schaefer, Thomas; Shi, Guoliang; Tilgner, Andreas; Walker, John T.; Wang, Tao; Weber, Rodney; Xing, Jia; Zaveri, Rahul A.; Zuend, Andreas (EGU, 2019-10-18)
    Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semi-volatile ...
  • Detecting Adversarial Examples in Deep Neural Networks using Normalizing Filters 

    Gu, Shuangchi; Yi, Ping; Zhu, Ting; Yao, Yao; Wang, Wei (ScitePress, 2019)
    Deep neural networks are vulnerable to adversarial examples which are inputs modified with unnoticeable but malicious perturbations. Most defending methods only focus on tuning the DNN itself, but we propose a novel ...
  • Evaluation of Data-Driven Causality Discovery Approaches among Dominant Climate Modes 

    Hussung, Steve; Mahmud, Suhail; Sampath, Akila; Wu, Mengxi; Guo, Pei (HPCF UMBC, 2019)
    Identification of causal networks in atmospheric teleconnection patterns has applications in many climate studies. We evaluate and compare three data-driven causal discovery methods in locating and linking causation of ...
  • Dust Detection in Satellite Data using Convolutional Neural Networks 

    Cai, Changjie; Lee, Jangho; Shi, Yingxi Rona; Zerfas, Camille; Guo, Pei (HPCF UMBC, 2019)
    Atmospheric dust is known to cause health ailments and impacts earth’s climate and weather patterns. Due to the many issues atmospheric dust contributes to, it is important to study dust patterns and how it enters the ...
  • Benchmarking Parallel K-Means Cloud Type Clustering from Satellite Data 

    Barajas, Carlos; Guo, Pei; Mukherjee, Lipi; Hoban, Susan; Wang, Jianwu; Jin, Daeho; Gangopadhyay, Aryya; Gobbert, Matthias K. (Springer, Cham, 2019-10-08)
    The study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. Clustering is a common machine learning technique used in atmospheric science to ...
  • Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans 

    Noury, Erfan; Mannil, Suria S.; Chang, Robert T.; Ran, An Ran; Cheung, Carol Y.; Thapa, Suman S.; Rao, Harsha L.; Dasari, Srilakshmi; Riyazuddin, Mohammed; Nagaraj, Sriharsha; Zadeh, Reza (2019-10-14)
    We propose developing and validating a three-dimensional (3D) deep learning system using the entire unprocessed OCT optic nerve volumes to distinguish true glaucoma from normals in order to discover any additional imaging ...
  • Engineering of Large Third-Order Nonlinearities in Atomic Layer Deposition Grown Nitrogen-Enriched TiO₂ 

    Kuis, Robinson; Gougousi, Theodosia; Basaldua, Isaac; Burkins, Paul; Kropp, Jaron A.; Johnson, Anthony M. (ACS Publications, 2019-10-17)
    The third-order nonlinear optical properties of Nitrogen-enriched TiO₂ films deposited by Atomic Layer Deposition (ALD) at a temperature between 100 – 300°C on quartz substrates were studied using thermally managed Z-scan ...
  • Where Does Work End and Home Life Begin? 

    Berge, Zane L.; Bichy, Cassie; Grayson, Candice; Johnson, Anthony; Macadoff, Stephen; Nee, Kathryn (IGI Global Disseminator of Knowledge, 2009)
    Many years ago, it was a commonly held belief that technology would improve industries and service professions, which means that people could work shorter hours and their employers would make just as much money. Essentially, ...
  • Unfolding the Structure of a Document using Deep Learning 

    Rahman, Muhammad Mahbubur; Finin, Tim (2019-09-29)
    Understanding and extracting of information from large documents, such as business opportunities, academic articles, medical documents and technical reports, poses challenges not present in short documents. Such large ...
  • Anomaly Detection: Under the [data] hood in Smart Cars 

    Quader, Faisal; Janeja, Vandana P. (IEEE, 2019-08-01)
    This research focuses on discovering baseline models for driving behavior and vehicle functioning from data in smart cars. This facilitates detection of anomalous behaviors that deviate from such baselines. Human behavioral ...
  • An overview of online trust: Concepts, elements, and implications 

    Wang, Ye Diana; Emurian, Henry H. (Elsevier Ltd., 2004-02-18)
    Lack of trust has been repeatedly identified as one of the most formidable barriers to people for engaging in e-commerce, involving transactions in which financial and personal information is submitted to merchants via the ...
  • Learning from Observations Using a Single Video Demonstration and Human Feedback 

    Gandhi, Sunil; Oates, Tim; Mohsenin, Tinoosh; Waytowich, Nicholas (2019-09-29)
    In this paper, we present a method for learning from video demonstrations by using human feedback to construct a mapping between the standard representation of the agent and the visual representation of the demonstration. ...
  • A distributed active subspace method for scalable surrogate modeling of function valued outputs 

    Guy, Hayley; Alexanderian, Alen; Yu, Meilin (2019-08-08)
    Abstract We present a distributed active subspace method for training surrogate models of complex physical processes with high-dimensional inputs and function valued outputs. Specifically, we represent the model output ...
  • Mitigating Demographic Biases in Social Media-Based Recommender Systems 

    Islam, Rashidul; Keya, Kamrun Naher; Pan, Shimei; Foulds, James (Association for Computing Machinery, 2019-08-04)
    As a growing proportion of our daily human interactions are digitized and subjected to algorithmic decision-making on social media platforms, it has become increasingly important to ensure that these algorithms behave in ...
  • A Bayesian Data Analytics Approach to Buildings’ Thermal Parameter Estimation 

    Pathak, Nilavra; Foulds, James; Roy, Nirmalya; Banerjee, Nilanjan; Robucci, Ryan (Association for Computing Machinery, 2019-06-28)
    Modeling buildings’ heat dynamics is a complex process which depends on various factors including weather, building thermal capacity, insulation preservation, and residents’ behavior. Gray-box models offer an explanation ...
  • An implicit P-multigrid flux reconstruction method for simulation of locally preconditioned unsteady Navier–Stokes equations at low Mach numbers 

    Wang, Lai; Yu, Meilin (2019-08)
    We develop a P-multigrid solver to simulate locally preconditioned unsteady compressible Navier–Stokes equations at low Mach numbers with implicit high-order methods. Specifically, the high-order flux reconstruction/correction ...
  • Social Media-based User Embedding: A Literature Review 

    Pan, Shimei; Ding, Tao (2019-06)
    Automated representation learning is behind many recent success stories in machine learning. It is often used to transfer knowledge learned from a large dataset (e.g., raw text) to tasks for which only a small number ...
  • Trends in PM2.5 transition metals in urban areas across the United States 

    Hennigan, Christopher J.; Mucci, Aidan; Reed, Brian E. (IOP Publishing, 2019-10-04)
    Using data from the Environmental Protection Agency's Chemical Speciation Network, we have characterized trends in PM2.5 transition metals in urban areas across the United States for the period 2001–2016. The metals included ...
  • Biomimetic Strategies To Treat Traumatic Brain Injury by Leveraging Fibrinogen 

    Brown, Ashley C.; Lavik, Erin; Stabenfeldt, Sarah E. (ACS Publications, 2019-06-27)
    There were over 27 million new cases of traumatic brain injuries (TBIs) in 2016 across the globe. TBIs are often part of complicated trauma scenarios and may not be diagnosed initially because the primary clinical focus ...
  • In silico dermoscopy with detailed subsurface scattering 

    Seipp, B.; Olano, M.; Badano, A. (The Eurographics Association, 2019)
    We describe an approach to modeling dermoscopy, the imaging modality for the examination of skin lesions, using accurate subsurface scattering in human skin. We make use of an open-source, path-tracing program with advanced ...

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