Institution
University of Waterloo
Education•Waterloo, Ontario, Canada•
About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.
Papers published on a yearly basis
Papers
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TL;DR: The relationship between IoV and big data in vehicular environment is investigated, mainly on how IoV supports the transmission, storage, computing and computing of the big data, and in returnHow IoV benefits frombig data in terms of IoV characterization, performance evaluation andbig data assisted communication protocol design is investigated.
Abstract: As the rapid development of automotive telematics, modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real time and long term information processing, the traditional Vehicular Ad- Hoc Networks U+0028 VANETs U+0029 are evolving to the Internet of Vehicles U+0028 IoV U+0029, which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which are referred to as Big Data. In this article, we first investigate the relationship between IoV and big data in vehicular environment, mainly on how IoV supports the transmission, storage, computing of the big data, and in return how IoV benefits from big data in terms of IoV characterization, performance evaluation and big data assisted communication protocol design. We then investigate the application of IoV big data for autonomous vehicles. Finally the emerging issues of the big data enabled IoV are discussed.
463 citations
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07 Aug 2005TL;DR: A general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered, which generalizes the spectral clustering approach for undirected graphs.
Abstract: We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered. The time complexity of the algorithm derived from this framework is nearly linear due to recently developed numerical techniques. In the absence of labeled instances, this framework can be utilized as a spectral clustering method for directed graphs, which generalizes the spectral clustering approach for undirected graphs. We have applied our framework to real-world web classification problems and obtained encouraging results.
463 citations
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TL;DR: Data suggest that increasing seatbelt use, reducing speed, and reducing the number and severity of driver-side impacts may prevent fatalities, and the specific safety needs of older and female drivers may need to be addressed separately from those of men and younger drivers.
462 citations
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University of Leeds1, National Institute of Amazonian Research2, Forestry Commission3, Wageningen University and Research Centre4, University of St Andrews5, James Cook University6, Indiana University7, Paul Sabatier University8, Forest Research Institute9, University of São Paulo10, University of Edinburgh11, University of Waterloo12, University of New Hampshire13, Hokkaido University14, Universiti Brunei Darussalam15, Forest Research Institute Malaysia16, United States Forest Service17, Oregon State University18, University of Twente19, Universidade do Estado de Mato Grosso20, University of York21, Commonwealth Scientific and Industrial Research Organisation22, National University of Colombia23, University of Cambridge24, University of Yaoundé I25
TL;DR: In this article, the authors developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries, and used this database to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap).
Abstract: . Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.
462 citations
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01 Jan 1997TL;DR: Solid phase microextraction (SPME) as mentioned in this paper uses a small volume of sorbent dispersed typically on the surface of small fibres, to isolate and concentrate analytes from sample matrix.
Abstract: Solid Phase Microextraction (SPME) uses a small volume of sorbent dispersed typically on the surface of small fibres, to isolate and concentrate analytes from sample matrix. After contact with sample, analytes are absorbed or adsorbed by the fibre phase (depending on the nature of the coating) until an equilibrium is reached in the system. The amount of an analyteextracted by the coating at equilibrium is determined by the magnitude of the partition coefficient of the analyte between the sample matrix and the coating material. After the extraction step, the fibres are transferred, with the help of a syringe-like handling device, to analytical instrument, for separation and quantitation of target analytes. This technique integrates sampling, extraction and sample introduction and is a simple way of facilitating on-site monitoring. Applications of this technique include environmental monitoring, industrial hygiene, process monitoring, clinical, forensic, food, flavour, fragrance and drug analyses, in laboratory and on-site analysis.
462 citations
Authors
Showing all 36498 results
Name | H-index | Papers | Citations |
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John J.V. McMurray | 178 | 1389 | 184502 |
David A. Weitz | 178 | 1038 | 114182 |
David Taylor | 131 | 2469 | 93220 |
Lei Zhang | 130 | 2312 | 86950 |
Will J. Percival | 129 | 473 | 87752 |
Trevor Hastie | 124 | 412 | 202592 |
Stephen Mann | 120 | 669 | 55008 |
Xuan Zhang | 119 | 1530 | 65398 |
Mark A. Tarnopolsky | 115 | 644 | 42501 |
Qiang Yang | 112 | 1117 | 71540 |
Wei Zhang | 112 | 1189 | 93641 |
Hans-Peter Seidel | 112 | 1213 | 51080 |
Theodore S. Rappaport | 112 | 490 | 68853 |
Robert C. Haddon | 112 | 577 | 52712 |
David Zhang | 111 | 1027 | 55118 |