Early Recognition of Human Activities from First-Person Videos Using Onset Representations

In this paper, we propose a methodology for early recognition of human activities from videos taken with a first-person viewpoint. Early recognition, which is also known as activity prediction, is an ability to infer an ongoing activity at its early stage. We present an algorithm to perform recognition of activities targeted at the camera from streaming videos, making the system to predict intended activities of the interacting person and avoid harmful events before they actually happen. We introduce the novel concept of 'onset' that efficiently summarizes pre-activity observations, and design an approach to consider event history in addition to ongoing video observation for early first-person recognition of activities. We propose to represent onset using cascade histograms of time series gradients, and we describe a novel algorithmic setup to take advantage of onset for early recognition of activities. The experimental results clearly illustrate that the proposed concept of onset enables better/earlier recognition of human activities from first-person videos

Development of Ocular Inserts for Cattle

Ring shaped ocular inserts have been developed to administer a therapeutic level of tylosin tartrate throughout a five day period to treat pinkeye in cattle. The inserts are based on polyvinyl chloride rings which are dip coated with a copolymer containing the antibiotic (tylosin tartrate). Scanning electron microscope (SEM) characterization of surfaces has been of value to evaluate the presence and extent of surface flaws in the hydrogel coating, and to contribute to improvement in fabrication of the rings to insure the establishment of satisfactory seals at joints, uniformity of microporosity and cross sections, and the absence of significant cracking or flaking. In vitro release rates were determined using-thin layer chromatography techniques, and rates were seen to be above a few micrograms of antibiotic per hour for experiments as long as nine days at simulated tear rates as high as 2 milliliters per hour

Variability of subtropical upper tropospheric humidity

International audienceAnalysis of Atmospheric Infrared Sounder (AIRS) measurements for five northern winters shows significant longitudinal variations in subtropical upper tropospheric relative humidity (RH), not only in the climatological mean values but also in the local distributions and temporal variability. The largest climatological mean values in the northern subtropics occur over the eastern Pacific and Atlantic oceans, where there is also large day-to-day variability. In contrast, there are smaller mean values, and smaller variability that occurs at lower frequency, over the Indian and western Pacific oceans. These differences in the distribution and variability of subtropical RH are related to differences in the key transport processes in the different sectors. The large variability and intermittent high and low RH over the Eastern Pacific and Atlantic oceans, and to a smaller extent over the Indian ocean, are due to intrusions of high potential vorticity air into the subtropics. Intrusions seldom occur over the eastern Indian and western Pacific oceans, and here the subtropical RH is more closely linked to the location and strength of subtropical anticyclones. In this region there are eastward propagating features in the subtropical RH that are out of phase with the tropical RH, and are caused by modulation of the subtropical anticyclones by the Madden-Julian Oscillation

Identifying First-person Camera Wearers in Third-person Videos

We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wearing body-worn cameras while a third-person static camera also captures the scene. To do this, we need to establish person-level correspondences across first- and third-person videos, which is challenging because the camera wearer is not visible from his/her own egocentric video, preventing the use of direct feature matching. In this paper, we propose a new semi-Siamese Convolutional Neural Network architecture to address this novel challenge. We formulate the problem as learning a joint embedding space for first- and third-person videos that considers both spatial- and motion-domain cues. A new triplet loss function is designed to minimize the distance between correct first- and third-person matches while maximizing the distance between incorrect ones. This end-to-end approach performs significantly better than several baselines, in part by learning the first- and third-person features optimized for matching jointly with the distance measure itself

A note on q-Bernoulli numbers and polynomials

By using p-adic q-integrals, we study the q-Bernoulli numbers and polynomials of higher order.Comment: 8 page

Four Years of Airborne Measurements of Wildfire Emissions in California, with a Focus on the Evolution of Emissions During the Soberanes Megafire

Biomass burning is an important source of trace gases and particles which can influence air quality on local, regional, and global scales. With wildfire events increasing due to changes in land use, increasing population, and climate change, characterizing wildfire emissions and their evolution is vital. In this work we report in situ airborne measurements of carbon dioxide (CO2), methane (CH4), water vapor (H2O), ozone (O3), and formaldehyde (HCHO) from nine wildfire events in California between 2013 and 2016, which were sampled as part of the Alpha Jet Atmospheric eXperiment (AJAX) based at NASA Ames Research Center. One of those fires, the Soberanes Megafire, began on 22 July 2016 and burned for three months. During that time, five flights were executed to sample emissions near and downwind of the Soberanes wildfire. In situ data are used to determine enhancement ratios (ERs), or excess mixing ratio relative to CO2, as well as assess O3 production from the fire. Changes in the emissions as a function of fire evolution are explored. Air quality impacts downwind of the fire are addressed using ground-based monitoring site data, satellite smoke products, and the Community Multiscale Air Quality (CMAQ) photochemical grid model

Reframing “Failure” in Making: The Value of Play, Social Relationships, and Ownership

Building on grit and growth mindset literature, the “maker mindset” celebrates persistence through failure as key to inspiring creativity in making education. Yet, moving beyond examinations of individual persistence and assumptions that all people have the same wealth of resources to persevere, when is it worthwhile to work through challenging projects? What supports are necessary for youth to feel safe working through challenges in science, technology, engineering, math, and computing (STEM+C) activities? Using sociocultural theory as a lens, this ethnographic study analyzed observation field notes, videos, photos, student work, and interviews from an after-school making program for high school girls during the 2014-15 school year. Through a comparison of 2 groups—one that persisted through challenging moments and one that did not—this paper reveals the centrality of playfulness, teamwork, and ownership of projects in order to persist through challenges that arise in inquiry-based projects