Institution
Carleton University
Education•Ottawa, Ontario, Canada•
About: Carleton University is a education organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 15852 authors who have published 39650 publications receiving 1106610 citations.
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Papers
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23 Apr 2018TL;DR: Fractional path integrals over the paths of the Levy flights are defined and it is shown that if the fractality of the Brownian trajectories leads to standard quantum and statistical mechanics, then the fractal paths leads to fractional quantum mechanics and fractional statistical mechanics.
Abstract: A path integral approach to quantum physics has been developed. Fractional path integrals over the paths of the Levy flights are defined. It is shown that if the fractality of the Brownian trajectories leads to standard quantum and statistical mechanics, then the fractality of the Levy paths leads to fractional quantum mechanics and fractional statistical mechanics. The fractional quantum and statistical mechanics have been developed via our fractional path integral approach. A fractional generalization of the Schrodinger equation has been found. A relationship between the energy and the momentum of the nonrelativistic quantum-mechanical particle has been established. The equation for the fractional plane wave function has been obtained. We have derived a free particle quantum-mechanical kernel using Fox's H function. A fractional generalization of the Heisenberg uncertainty relation has been established. Fractional statistical mechanics has been developed via the path integral approach. A fractional generalization of the motion equation for the density matrix has been found. The density matrix of a free particle has been expressed in terms of the Fox's H function. We also discuss the relationships between fractional and the well-known Feynman path integral approaches to quantum and statistical mechanics.
631 citations
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TL;DR: In this article, the authors used the ATLAS detector to detect dijet asymmetry in the collisions of lead ions at the Large Hadron Collider and found that the transverse energies of dijets in opposite hemispheres become systematically more unbalanced with increasing event centrality, leading to a large number of events which contain highly asymmetric di jets.
Abstract: By using the ATLAS detector, observations have been made of a centrality-dependent dijet asymmetry in the collisions of lead ions at the Large Hadron Collider. In a sample of lead-lead events with a per-nucleon center of mass energy of 2.76 TeV, selected with a minimum bias trigger, jets are reconstructed in fine-grained, longitudinally segmented electromagnetic and hadronic calorimeters. The transverse energies of dijets in opposite hemispheres are observed to become systematically more unbalanced with increasing event centrality leading to a large number of events which contain highly asymmetric dijets. This is the first observation of an enhancement of events with such large dijet asymmetries, not observed in proton-proton collisions, which may point to an interpretation in terms of strong jet energy loss in a hot, dense medium.
630 citations
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TL;DR: In this paper, the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools.
629 citations
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TL;DR: In this article, a 6-year balance computed from continuous net ecosystem CO2 exchange (NEE), regular instantaneous measurements of methane (CH4) emissions, and export of dissolved organic C (DOC) from a northern ombrotrophic bog is presented.
Abstract: Northern peatlands contain up to 25% of the world’s soil carbon (C) and have an estimated annual exchange of CO2-C with the atmosphere of 0.1–0.5 Pg yr � 1 and of CH4-C of 10–25 Tg yr � 1 . Despite this overall importance to the global C cycle, there have been few, if any, complete multiyear annual C balances for these ecosystems. We report a 6-year balance computed from continuous net ecosystem CO2 exchange (NEE), regular instantaneous measurements of methane (CH4) emissions, and export of dissolved organic C (DOC) from a northern ombrotrophic bog. From these observations, we have constructed complete seasonal and annual C balances, examined their seasonal and interannual variability, and compared the mean 6-year contemporary C exchange with the apparent C accumulation for the last 3000 years obtained from C density and agedepth profiles from two peat cores. The 6-year mean NEE-C and CH4-C exchange, and net DOC loss are � 40.2 � 40.5 (� 1 SD), 3.7 � 0.5, and 14.9 � 3.1 g m � 2 yr � 1 , giving a 6-year mean balance of � 21.5 � 39.0 g m � 2 yr � 1 (where positive exchange is a loss of C from the ecosystem). NEE had the largest magnitude and variability of the components of the C balance, but DOC and CH4 had similar proportional variabilities and their inclusion is essential to resolve the C balance. There are large interseasonal and interannual ranges to the exchanges due to variations in climatic conditions. We estimate from the largest and smallest seasonal exchanges, quasi-maximum limits of the annual C balance between 50 and � 105 g m � 2 yr � 1 . The net C accumulation rate obtained from the two peatland cores for the interval 400–3000 BP (samples from the anoxic layer only) were 21.9 � 2.8 and 14.0 � 37.6 g m � 2 yr � 1 , which are not significantly different from the 6-year mean con
627 citations
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TL;DR: Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced.
Abstract: Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.
627 citations
Authors
Showing all 16102 results
Name | H-index | Papers | Citations |
---|---|---|---|
George F. Koob | 171 | 935 | 112521 |
Zhenwei Yang | 150 | 956 | 109344 |
Andrew White | 149 | 1494 | 113874 |
J. S. Keller | 144 | 981 | 98249 |
R. Kowalewski | 143 | 1815 | 135517 |
Manuella Vincter | 131 | 944 | 122603 |
Gabriella Pasztor | 129 | 1401 | 86271 |
Beate Heinemann | 129 | 1085 | 81947 |
Claire Shepherd-Themistocleous | 129 | 1211 | 86741 |
Monica Dunford | 129 | 906 | 77571 |
Dave Charlton | 128 | 1065 | 81042 |
Ryszard Stroynowski | 128 | 1320 | 86236 |
Peter Krieger | 128 | 1171 | 81368 |
Thomas Koffas | 128 | 942 | 76832 |
Aranzazu Ruiz-Martinez | 126 | 783 | 71913 |