Speeding is a key contributing factor in roadway crashes in the United Arab Emirates (UAE) and elsewhere. Understanding how drivers behave towards speed management devices (i.e., speed cameras, radars, speed limits and speed warning signs) as well as factors affecting drivers' involvement in speed-related crashes might help in improving traffic safety. This study aims to identify and quantify the factors that affect drivers' compliance with speed enforcement and management devices as well as drivers' involvement in at-fault speed-related crashes in the Emirate of Abu Dhabi (AD), UAE. Two different datasets were collected from the same drivers' population in AD to provide different valuable information regarding the speeding problem. The first dataset was obtained from crashes' reports while, the second dataset was obtained from a self-reported questionnaire survey that was carried out among a total of 442 drivers in AD. Three logistic regression models were developed to identify the significant variables that affect (1) the occurrence of speed related crash (using crashes reports data), (2) drivers' compliance with speed limits (using questionnaire data), and (3) involvement in at-fault speed related crashes (using questionnaire data). The findings revealed that drivers' factors (gender, age, and nationality), vehicle factor (vehicle type), roads and environment factors (weather, road type and speed limit) were the significant factors that affect the occurrence of speed-related crashes in AD. The questionnaire findings revealed that running late, low values of posted speed limits and no sufficient police enforcement were the three main reasons that make motorists drive over the speed limits. In addition, the results indicated that drivers' characteristics (i.e., gender, education and income), drivers' responses to speed enforcement and management devices, and drivers' awareness about the importance of such devices in improving traffic safety were the main factors that affecting both drivers' compliance with speed enforcement devices and drivers' involvement in at-fault speed-related crashes. A comparison between the analysis results of traffic crashes and questionnaire datasets as well as a comparison between the findings of this study and existing literature are also provided.
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http://dx.doi.org/10.1016/j.aap.2016.10.027 | DOI Listing |
Anal Chim Acta
February 2025
Engineering Research Center of Optical Instrument and System, Ministry of Education and Shanghai Key Lab of Modern Optical System, University of Shanghai for Science and Technology, No.516 Jungong Road, Shanghai, 200093, China.
Background: Surface-enhanced Raman scattering (SERS) has attracted much attention as a powerful detection and analysis tool with high sensitivity and fast detection speed. The intensity of the SERS signal mainly depended on the highly enhanced electromagnetic field of nanostructure near the substrate. However, the fabrication of high-quality SERS nanostructured substrates is usually complicated, makes many methods unsuitable for large-scale production of SERS substrates.
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January 2025
Department of Medical Imaging, Pingyin people's Hospital, Jinan 250400, China.
Magnetic Resonance Imaging is a cornerstone of medical diagnostics, providing high-quality soft tissue contrast through non-invasive methods. However, MRI technology faces critical limitations in imaging speed and resolution. Prolonged scan times not only increase patient discomfort but also contribute to motion artifacts, further compromising image quality.
View Article and Find Full Text PDFNeural Netw
January 2025
Defense Innovation Institute, Chinese Academy of Military Science, Beijing 100071, China; Intelligent Game and Decision Laboratory, China.
The Physics-informed Neural Network (PINN) has been a popular method for solving partial differential equations (PDEs) due to its flexibility. However, PINN still faces challenges in characterizing spatio-temporal correlations when solving parametric PDEs due to network limitations. To address this issue, we propose a Physics-Informed Neural Implicit Flow (PINIF) framework, which enables a meshless low-rank representation of the parametric spatio-temporal field based on the expressiveness of the Neural Implicit Flow (NIF), enabling a meshless low-rank representation.
View Article and Find Full Text PDFGenetics
January 2025
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, USA.
Haldane's Dilemma refers to the concern that the need for many "selective deaths" to complete a substitution (i.e. selective sweep) creates a speed limit to adaptation.
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January 2025
Beijing Aerospace Automatic Control Institute, Beijing 100854, China.
The traditional method is capable of detecting and tracking stationary and slow-moving targets in a sea surface environment. However, the signal focusing capability of such a method could be greatly reduced especially for those variable-speed targets. To solve this problem, a novel tracking algorithm combining range envelope alignment and azimuth phase filtering is proposed.
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