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Ten Helpful Ideas for Teaching English to Young Learners
(American English, 2006)This article contains some helpful ideas to incorporate into the Teaching English to Young Learners (TEYL) classroom. These ideas come from the discussions and assignments done in an online English as a Foreign Language ... -
Detecting Adversarial Examples in Deep Neural Networks using Normalizing Filters
(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
(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
(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 ... -
Effects of exposure to ¹²C and ⁴He particles on cognitive performance of intact and ovariectomized female rats
(Elsevier Ltd., 2019-07-10)Exposure to the types of radiation encountered outside the magnetic field of the earth can disrupt cognitive performance. Exploratory class missions to other planets will include both male and female astronauts. Because ... -
Bosons Outperform Fermions – The Thermodynamic Advantage of Symmetry
(2019-10-11)We examine a quantum Otto engine with a harmonic working medium consisting of two particles to explore the use of wave function symmetry as an accessible resource. It is shown that the bosonic system displays enhanced ... -
Large Deflections of Inextensible Cantilevers: Modeling, Theory, and Simulation
(2019-10-16)A recent large deflection cantilever model is considered. The principal nonlinear effects come through the beam’s inextensibility—local arc length preservation—rather than traditional extensible effects attributed to ... -
Benchmarking Parallel K-Means Cloud Type Clustering from Satellite Data
(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 ... -
Studies in Feminist Activism
(2019-05-21) -
Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans
(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
(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 ... -
Anomaly Detection: Under the [data] hood in Smart Cars
(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 ... -
Why do females sing?—pair communication and other song functions in eastern bluebirds
(Oxford University Press, 2019-08-03)Female bird song has been underappreciated and understudied, especially in temperate species. Birdsong was originally thought to be a trait used primarily by male songbirds for mate attraction and male/male contest. However, ... -
An overview of online trust: Concepts, elements, and implications
(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 ... -
Generating photon-added states without adding a photon
(The American Physical Society, 2019-10-02)We show that a continuous range of nonclassical states of light can be generated using conditional measurements on the idler mode of an optical parametric amplifier. The output state is prepared by introducing a coherent ... -
Learning from Observations Using a Single Video Demonstration and Human Feedback
(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. ... -
Mitigating Demographic Biases in Social Media-Based Recommender Systems
(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 ... -
The Accretion History of AGN: A Newly Defined Population of Cold Quasars
(2019-08-15)Quasars are the most luminous of active galactic nuclei (AGN), and are perhaps responsible for quenching star formation in their hosts. The Stripe 82X catalog covers 31.3 deg² of the Stripe 82 field, of which the 15.6 deg² ... -
An implicit P-multigrid flux reconstruction method for simulation of locally preconditioned unsteady Navier–Stokes equations at low Mach numbers
(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
(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 ...
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