Vehicle Speed Prediction using Deep Learning

Global optimization of the energy consumption of dual power source vehicles such as hybrid electric vehicles, plug-in hybrid electric vehicles, and plug in fuel cell electric vehicles requires knowledge of the complete route characteristics at the beginning of the trip. One of the main characteristics is the vehicle speed profile across the route. The profile will translate directly into energy requirements for a given vehicle. However, the vehicle speed that a given driver chooses will vary from driver to driver and from time to time, and may be slower, equal to, or faster than the average traffic flow. If the specific driver speed profile can be predicted, the energy usage can be optimized across the route chosen. The purpose of this paper is to research the application of Deep Learning techniques to this problem to identify at the beginning of a drive cycle the driver specific vehicle speed profile for an individual driver repeated drive cycle, which can be used in an optimization algorithm to minimize the amount of fossil fuel energy used during the trip

Shot Noise Suppression in Avalanche Photodiodes

We identify a new shot noise suppression mechanism in a thin (~100 nm) heterostructure avalanche photodiode. In the low-gain regime the shot noise is suppressed due to temporal correlations within amplified current pulses. We demonstrate in a Monte Carlo simulation that the effective excess noise factors can be <1, and reconcile the apparent conflict between theory and experiments. This shot noise suppression mechanism is independent of known mechanisms such as Coulomb interaction, or reflection at heterojunction interfaces.Comment: Phys. Rev. Lett., accepted for publicatio

Microscopically Visible Internal Surface Area of Earlywood and Latewood of Loblolly Pine

Microscopically visible internal surface (MVIS) areas of earlywood and latewood of loblolly pine were estimated. Steps of calculation for MVIS area described. For the study tree, there was no difference in MVIS area between earlywood and latewood for the same volume in spite of difference in specific gravity. However, on a unit-weight basis, MVIS area decreased with increasing specific gravity

Poverty Reduction—A Vincentian Initiative in Higher Education: The All Hallows Experience

The development of the commitment of All Hallows College to poverty reduction is recounted. From its founding in 1842, All Hallows was focused on training seminarians for ministry in impoverished areas worldwide. Faced with a decline in candidates for the priesthood, it began offering lay ministry training in the early 1980s, with a special emphasis on the home mission in Ireland. It became renowned for its pastoral ministry education. The college instituted a justice/service element in all its courses and has created a postgraduate program in Social Justice and Public Policy The genesis of the latter, its requirements, and goals are described

In vitro identification and in silico utilization of interspecies sequence similarities using GeneChip(® )technology

BACKGROUND: Genomic approaches in large animal models (canine, ovine etc) are challenging due to insufficient genomic information for these species and the lack of availability of corresponding microarray platforms. To address this problem, we speculated that conserved interspecies genetic sequences can be experimentally detected by cross-species hybridization. The Affymetrix platform probe redundancy offers flexibility in selecting individual probes with high sequence similarities between related species for gene expression analysis. RESULTS: Gene expression profiles of 40 canine samples were generated using the human HG-U133A GeneChip (U133A). Due to interspecies genetic differences, only 14 ± 2% of canine transcripts were detected by U133A probe sets whereas profiling of 40 human samples detected 49 ± 6% of human transcripts. However, when these probe sets were deconstructed into individual probes and examined performance of each probe, we found that 47% of human probes were able to find their targets in canine tissues and generate a detectable hybridization signal. Therefore, we restricted gene expression analysis to these probes and observed the 60% increase in the number of identified canine transcripts. These results were validated by comparison of transcripts identified by our restricted analysis of cross-species hybridization with transcripts identified by hybridization of total lung canine mRNA to new Affymetrix Canine GeneChip(®). CONCLUSION: The experimental identification and restriction of gene expression analysis to probes with detectable hybridization signal drastically increases transcript detection of canine-human hybridization suggesting the possibility of broad utilization of cross-hybridizations of related species using GeneChip technology

AR Fantasia: An Augmented Reality Musical Experience

In 1940, Walt Disney Pictures released their third full length animated feature film, the classic film Fantasia. The concept and challenge behind Fantasia was simple: To merge music and visuals, using the media of animation, to provide an integrated backdrop for, and interpretation of, classical music. The complete film consisted of eight such animated sequences, each providing a visual landscape as a setting for a classical musical piece (Granata 2002)

Agreement between bioelectrical impedance and dual energy X-ray absorptiometry in assessing fat, lean and bone mass changes in adults after a lifestyle intervention

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A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution

Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invoke higher sensitivities and lower specificities. A generalized linear mixed model (GLMM) is currently recommended to synthesize diagnostic test accuracy studies. We propose a copula mixed model for bivariate meta-analysis of diagnostic test accuracy studies. Our general model includes the GLMM as a special case and can also operate on the original scale of sensitivity and specificity. Summary receiver operating characteristic curves are deduced for the proposed model through quantile regression techniques and different characterizations of the bivariate random effects distribution. Our general methodology is demonstrated with an extensive simulation study and illustrated by re-analysing the data of two published meta-analyses. Our study suggests that there can be an improvement on GLMM in fit to data and makes the argument for moving to copula random effects models. Our modelling framework is implemented in the package CopulaREMADA within the open source statistical environment R