Raising the Standard of Living Through Educating People in District 502

Many adults living in District 502, unfortunately, lacked the opportunities to receive a quality education growing up. For this reason, they seek to get a GED diploma in hopes of increasing the standard of living for them and their families. The adult education and English Language Education classes at the College of DuPage provide the necessary resources for this. They offer five classes that differ based on the subjects tested on the GED exam, these being social studies, math, science, writing, and interpreting literature and art. The classes require no fees, are available at multiple locations including online, and can even be taken in Spanish. Although these classes are very thorough and possess high-quality curricula, many adults struggle with passing the classes, preventing them from living a better life. The People Educating People program is a volunteering component of the adult education and English Language Education classes at the College of DuPage. Volunteers attend classes and tutor students either one-on-one or in groups. The purpose of this project is to share my observations on how tutoring benefits adult learners in their continuing education. I volunteered in the program for 41 hours during the fall 2019 semester, attending a second-grade level math class twice a week

Distributed OpenGL Rendering in Network Bandwidth Constrained Environments

Display walls made from multiple monitors are often used when very high resolution images are required. To utilise a display wall, rendering information must be sent to each computer that the monitors are connect to. The network is often the performance bottleneck for demanding applications, like high performance 3D animations. This paper introduces ClusterGL; a distribution library for OpenGL applications. ClusterGL reduces network traffic by using compression, frame differencing and multi-cast. Existing applications can use ClusterGL without recompilation. Benchmarks show that, for most applications, ClusterGL outperforms other systems that support unmodified OpenGL applications including Chromium and BroadcastGL. The difference is larger for more complex scene geometries and when there are more display machines. For example, when rendering OpenArena, ClusterGL outperforms Chromium by over 300% on the Symphony display wall at The University of Waikato, New Zealand. This display has 20 monitors supported by five computers connected by gigabit Ethernet, with a full resolution of over 35 megapixels. ClusterGL is freely available via Google Code

Continuum Observations at 350 Microns of High-Redshift Molecular Emission Line Galaxies

We report observations of 15 high redshift (z = 1-5) galaxies at 350 microns using the Caltech Submillimeter Observatory and SHARC-II array detector. Emission was detected from eight galaxies, for which far-infrared luminosities, star formation rates, total dust masses, and minimum source size estimates are derived. These galaxies have star formation rates and star formation efficiencies comparable to other high redshift molecular emission line galaxies. The results are used to test the idea that star formation in these galaxies occurs in a large number of basic units, the units being similar to star-forming clumps in the Milky Way. The luminosity of these extreme galaxies can be reproduced in a simple model with (0.9-30) *10^6 dense clumps, each with a luminosity of 5 *10^5 Lsun, the mean value for such clumps in the Milky Way. Radiative transfer models of such clumps can provide reasonable matches to the overall SEDs of the galaxies. They indicate that the individual clumps are quite opaque in the far-infrared. Luminosity to mass ratios vary over two orders of magnitude, correlating strongly with the dust temperature derived from simple fits to the SED. The gas masses derived from the dust modeling are in remarkable agreement with those from CO luminosities, suggesting that the assumptions going into both calculations are reasonable.Comment: 17 pages, 8 figures. Accepted by Ap

Probing Satellite Quenching With Galaxy Clustering

Satellites within simulated massive clusters are significantly spatially correlated with each other, even when those satellites are not gravitationally bound to each other. This correlation is produced by satellites that entered their hosts relatively recently, and is undetectable for satellites that have resided in their hosts for multiple dynamical timescales. Therefore, a measurement of clustering statistics of cluster satellites may be used to determine the typical accretion redshifts of those satellites into their observed hosts. We argue that such measurements may be used to determine the fraction of satellite galaxies that were quenched by their current hosts, thereby discriminating among models for quenching of star formation in satellite galaxies.Comment: 7 page

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy

Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions

Technology has recently been recruited in the war against the ongoing obesity crisis; however, the adoption of Health & Fitness applications for regular exercise is a struggle. In this study, we present a unique demographically representative dataset of 15k US residents that combines technology use logs with surveys on moral views, human values, and emotional contagion. Combining these data, we provide a holistic view of individuals to model their physical exercise behavior. First, we show which values determine the adoption of Health & Fitness mobile applications, finding that users who prioritize the value of purity and de-emphasize values of conformity, hedonism, and security are more likely to use such apps. Further, we achieve a weighted AUROC of .673 in predicting whether individual exercises, and we also show that the application usage data allows for substantially better classification performance (.608) compared to using basic demographics (.513) or internet browsing data (.546). We also find a strong link of exercise to respondent socioeconomic status, as well as the value of happiness. Using these insights, we propose actionable design guidelines for persuasive technologies targeting health behavior modification

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively