Institution
Chang'an University
Education•Xi'an, China•
About: Chang'an University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Asphalt & Groundwater. The organization has 18415 authors who have published 15102 publications receiving 125436 citations. The organization is also known as: Cháng'ān Dàxué & Changan University.
Papers published on a yearly basis
Papers
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TL;DR: A novel object detection and identification method that fuses the complementary information obtained by two types of sensors, 3D LIDAR and vision cameras, that meets the real-time demand of autonomous vehicles.
Abstract: It is vital that autonomous vehicles acquire accurate and real-time information about objects in their vicinity, which fully guarantees the safety of the passengers and vehicle in various environments. Three-dimensional light detection and ranging (3D LIDAR) sensors can directly obtain the position and geometric structure of an object within its detection range, whereas the use of vision cameras is most suitable for object recognition. Accordingly, in this paper, we present a novel object detection and identification method that fuses the complementary information obtained by two types of sensors. First, we utilise 3D LIDAR data to generate accurate object-region proposals. Then, these candidates are mapped onto the image space from which regions of interest (ROI) of the proposals are selected and input to a convolutional neural network (CNN) for further object recognition. To precisely identify the sizes of all the objects, we combine the features of the last three layers of the CNN to extract multi-scale features from the ROIs. The evaluation results obtained on the KITTI dataset demonstrate that: (1) unlike sliding windows that produce thousands of candidate object-region proposals, 3D LIDAR provides an average of 86 real candidates per frame and the minimal recall rate is better than 95%, which greatly decreases the extraction time; (2) The average processing time for each frame of the proposed method is only 66.79 ms, which meets the real-time demand of autonomous vehicles; (3) The average identification accuracies of our method for cars and pedestrians at a moderate level of difficulty are 89.04% and 78.18%, respectively, which is better than those of most previous methods.
164 citations
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TL;DR: Wang et al. as discussed by the authors studied the formation and moving characteristics of the landslide and subsequent debris flow in the southern Dagou Village of Mapaoquan Town, Tianshui City, Gansu Province of China on July 21, 2013.
163 citations
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TL;DR: The state of the science on groundwater contamination is reviewed in this paper, and the papers published in this special issue are summarized in terms of their contributions to the literature, and some key issues for advancing research on groundwater contamination are proposed.
Abstract: Groundwater contamination is a global problem that has a significant impact on human health and ecological services. Studies reported in this special issue focus on contaminants in groundwater of geogenic and anthropogenic origin distributed over a wide geographic range, with contributions from researchers studying groundwater contamination in India, China, Pakistan, Turkey, Ethiopia, and Nigeria. Thus, this special issue reports on the latest research conducted in the eastern hemisphere on the sources and scale of groundwater contamination and the consequences for human health and the environment, as well as technologies for removing selected contaminants from groundwater. In this article, the state of the science on groundwater contamination is reviewed, and the papers published in this special issue are summarized in terms of their contributions to the literature. Finally, some key issues for advancing research on groundwater contamination are proposed.
163 citations
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TL;DR: In this paper, CoO/g-C3N4 heterojunction photocatalysts were fabricated through a facile solvothermal method for overall water splitting, which exhibited remarkably higher photocatalysis performance and stability than single CoO or g-C 3N4.
Abstract: Photocatalytic hydrogen production from overall water splitting is a clean and renewable technology that can convert solar energy into chemical energy, for which developing an efficient and stable photocatalyst has been the central scientific topic. Herein, CoO/g-C3N4 heterojunction photocatalysts were fabricated through a facile solvothermal method for overall water splitting. Simultaneous evolution of H2 and O2 from pure water with the stoichiometric ratio of about 2:1 achieved with all the CoO/g-C3N4 heterojunctions as catalysts under visible light irradiation. Among of them, 30 wt.% CoO/g-C3N4 with H2 evolution rate of 2.51 μmol/h and O2 evolution rate of 1.39 μmol/h also exhibited remarkably higher photocatalytic performance and stability (over 15 cycles) than single CoO or g-C3N4. This enhanced photocatalytic activity of CoO/g-C3N4 heterojunction can be ascribed to the synergistic effect of junction and interface formed between CoO and g-C3N4. In addition, the sufficient long lifetime stability of CoO/g-C3N4 comes from the complementary advantages effect between CoO and g-C3N4, as is proved, CoO can protect g-C3N4 from H2O2 poisoning, and simultaneously the photo-induced heat from CoO during the photocatalytic process responsible for the rapid deactivation can be timely conducted to g-C3N4.
161 citations
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TL;DR: In this article, the authors examined the association between green logistics operations, social, environmental and economic indicators of SAARC (South Asian Association for Regional Cooperation) countries using GMM and FGLS two methods to tackle the problems of heterogeneity, serial correlation and heteroskedasticity.
161 citations
Authors
Showing all 18508 results
Name | H-index | Papers | Citations |
---|---|---|---|
Simon A. Wilde | 118 | 390 | 45547 |
Jian Zhang | 107 | 3064 | 69715 |
Lei Liu | 98 | 2041 | 51163 |
Lei Wang | 95 | 1486 | 44636 |
Chi Zhang | 88 | 1545 | 38876 |
Xun Wang | 84 | 606 | 32187 |
Fan Zhang | 77 | 517 | 30865 |
Xiaohong Chen | 77 | 599 | 24447 |
Hao Wu | 71 | 1153 | 23162 |
Yuliang Li | 69 | 475 | 18928 |
Yuegang Zhang | 68 | 279 | 21720 |
Bo Li | 66 | 709 | 19887 |
Tao Chen | 65 | 588 | 16704 |
Luonan Chen | 63 | 623 | 17067 |
Ning Wang | 60 | 657 | 12778 |