35,027 research outputs found
They’re Crying in the All-Gender Bathroom: Navigating Belonging in Higher Education While First Generation and Nonbinary
Maintaining the sociocultural and interpersonal supports needed
to succeed in higher education as a first-generation student can
be very difficult due to a lack of familiarity with what brings
success. When this identity intersects with a nonbinary gender
identity, it further complicates higher education’s challenges and
may make solutions impossible to come by. My experience sits at
the intersection of these two identities and their gradual collision
and connection with success in higher education. Through this
narrative, I seek to unpack potential difficulties and nuances
for the increasingly diverse body of first generation students and
bring attention to the barriers in our social systems which may
be blocking current and future students from achieving their
full potential
Destination directed packet switch architecture for a 30/20 GHz FDMA/TDM geostationary communication satellite network
Emphasis is on a destination directed packet switching architecture for a 30/20 GHz frequency division multiplex access/time division multiplex (FDMA/TDM) geostationary satellite communication network. Critical subsystems and problem areas are identified and addressed. Efforts have concentrated heavily on the space segment; however, the ground segment was considered concurrently to ensure cost efficiency and realistic operational constraints
Currency Market Reactions to Good and Bad News During the Asian Crisis
There is considerable disagreement among analysts about the extent to which the spread of the Asian crisis was based on reasonable changes in expectations about fundamentals versus pure contagion effects resulting from imperfections in the behavior of currency and financial markets. In this paper we focus specifically on the behavior of the foreign exchange market for the five Asian countries. We find little support for the hypothesis that the Asian currency crisis was dominated by panic in the markets such that investors and speculators reacted much more strongly to bad than to good news. While the strongest reactions were to home news, there were also a number of significant cross effects. Almost all of these were of the same sign, suggesting that investors typically assumed that what was good for one country was good for all. Again, there was no systematic evidence of stronger reactions to bad than to good news. The markets may have overreacted in general, pushing currencies below the levels justified by the fundamentals, but, if so, this did not undercut the markets ability to respond to good as well as bad news, nor do these responses appear to have been systematically smaller to good than to bad news. The symptoms of the blind panic that has so often been alleged do not appear in the data.
Destination-directed, packet-switching architecture for 30/20-GHz FDMA/TDM geostationary communications satellite network
A destination-directed packet switching architecture for a 30/20-GHz frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary satellite communications network is discussed. Critical subsystems and problem areas are identified and addressed. Efforts have concentrated heavily on the space segment; however, the ground segment has been considered concurrently to ensure cost efficiency and realistic operational constraints
Awareness, use, and perceptions of biodiesel: A comparison of consumers in Belgium and the United States
Belgian (N = 61) and American (N = 134) fuel consumers were interviewed in the summer of 2012 to determine their awareness, use, and perceptions of biodiesel. Consumers who were aware of biodiesel were asked their perceptions. A significantly P \u3c 0.0001) higher percentage of Belgian consumers (78.7%) reported owning or driving a diesel vehicle compared to American consumers (9.0%). Belgian and American consumers moderately agreed biodiesel is a high-quality fuel. For both Belgian and American consumers, there was no significant association between owning a diesel vehicle and being aware of biodiesel or having purchased biodiesel. Although Belgian and American consumers agreed that using non-food crops for biodiesel is justified, Belgians were significantly less supportive than American consumers of using food crops for biodiesel. Both Belgian and American consumers disagreed with the statement “I would never use biodiesel”, and the two sets of consumers moderately disagreed that diesel engines would not run properly on biodiesel. Belgian and American consumers agreed that global warming is increasing; however, American consumers were more positive about the potential of biodiesel to reduce harmful exhaust emissions and global warming. Belgian consumers moderately agreed and American consumers agreed that biodiesel is better to use because it is made from renewable resources. Belgian and American consumers generally show similar perceptions of biodiesel, with the exception that American consumers were more positive toward the environmental and renewable aspects of biodiesel use. Recommendations for further research include gaining a better understanding of the potential positive influences that impact consumers’ perceptions of biodiesel
Rectangular Hierarchical Cartograms for Socio-Economic Data
We present rectangular hierarchical cartograms for mapping socio-economic data. These density-normalising cartograms size spatial units by population, increasing the ease with which data for densely populated areas can be visually resolved compared to more conventional cartographic projections. Their hierarchical nature enables the study of spatial granularity in spatial hierarchies, hierarchical categorical data and multivariate data through false hierarchies. They are space-filling representations that make efficient use of space and their rectangular nature (which aims to be as square as possible) improves the ability to compare the sizes (therefore population) of geographical units.
We demonstrate these cartograms by mapping the Office for National Statistics Output Area Classification (OAC) by unit postcode (1.52 million in Great Britain) through the postcode hierarchy, using these to explore spatial variation. We provide rich and detailed spatial summaries of socio-economic characteristics of population as types of treemap, exploring the effects of reconfiguring them to study spatial and non-spatial aspects of the OAC classification
CDM or self-interacting neutrinos? - how CMB data can tell the two models apart
Of the many proposed extensions to the CDM paradigm, a model in
which neutrinos self-interact until close to the epoch of matter-radiation
equality has been shown to provide a good fit to current cosmic microwave
background (CMB) data, while at the same time alleviating tensions with
late-time measurements of the expansion rate and matter fluctuation amplitude.
Interestingly, CMB fits to this model either pick out a specific large value of
the neutrino interaction strength, or are consistent with the extremely weak
neutrino interaction found in CDM, resulting in a bimodal posterior
distribution for the neutrino self-interaction cross section. In this paper, we
explore why current cosmological data select this particular large neutrino
self-interaction strength, and by consequence, disfavor intermediate values of
the self-interaction cross section. We show how it is the
CMB temperature anisotropies, most recently measured by the Planck satellite,
that produce this bimodality. We also establish that smaller scale temperature
data, and improved polarization data measuring the temperature-polarization
cross-correlation, will best constrain the neutrino self-interaction strength.
We forecast that the upcoming Simons Observatory should be capable of
distinguishing between the models.Comment: 7 pages, 7 figures, comments welcome, references added, version
submitted to PR
Detecting Distracted Driving with Deep Learning
© Springer International Publishing AG 2017Driver distraction is the leading factor in most car crashes and near-crashes. This paper discusses the types, causes and impacts of distracted driving. A deep learning approach is then presented for the detection of such driving behaviors using images of the driver, where an enhancement has been made to a standard convolutional neural network (CNN). Experimental results on Kaggle challenge dataset have confirmed the capability of a convolutional neural network (CNN) in this complicated computer vision task and illustrated the contribution of the CNN enhancement to a better pattern recognition accuracy.Peer reviewe
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