Efficient and Robust Driver Fatigue Detection Framework Based on the Visual Analysis of Eye States

Fatigue detection based on vision is widely employed in vehicles due to its real-time and reliable detection results. With the coronavirus disease (COVID-19) outbreak, many proposed detection systems based on facial characteristics would be unreliable due to the face covering with the mask. In this paper, we propose a robust visual-based fatigue detection system for monitoring drivers, which is robust regarding the coverings of masks, changing illumination and head movement of drivers. Our system has three main modules: face key point alignment, fatigue feature extraction and fatigue measurement based on fused features. The innovative core techniques are described as follows: (1) a robust key point alignment algorithm by fusing global face information and regional eye information, (2) dynamic threshold methods to extract fatigue characteristics and (3) a stable fatigue measurement based on fusing percentage of eyelid closure (PERCLOS) and proportion of long closure duration blink (PLCDB). The excellent performance of our proposed algorithm and methods are verified in experiments. The experimental results show that our key point alignment algorithm is robust to different scenes, and the performance of our proposed fatigue measurement is more reliable due to the fusion of PERCLOS and PLCDB

Localization with Noisy Android Raw GNSS Measurements

Android raw Global Navigation Satellite System (GNSS) measurements are expected to bring smartphones power to take on demanding localization tasks that are traditionally performed by specialized GNSS receivers. The hardware constraints, however, make Android raw GNSS measurements much noisier than geodetic-quality ones. This study elucidates the principles of localization using Android raw GNSS measurements and leverages Moving Horizon Estimation (MHE), Extended Kalman Filter (EKF), and Rauch-Tung-Striebel (RTS) smoother for noise suppression. Experimental results show that the RTS smoother achieves the best positioning performance, with horizontal positioning errors significantly reduced by 76.4% and 46.5% in static and dynamic scenarios compared with the baseline weighted least squares (WLS) method. Our codes are available at https://github.com/ailocar/androidGnss

4-Hydr­oxy-1-oxo-1,2-dihydro­phthalazine-6,7-dicarboxylic acid dihydrate

In the crystal structure of the title compound, C10H6N2O6·2H2O, the OH and NH groups each serve as a hydrogen-bond donor to one acceptor site whereas the water mol­ecules each serve as a hydrogen-bond donor to two acceptor sites. The hydrogen-bonding scheme gives rise to a three-dimensional network

Undoped gallium antimonide studied by positron annihilation spectroscopy

Positron lifetime spectroscopy has been used to study the vacancy type defects in undoped gallium antimonide. Temperature dependent positron trapping into the VGarelated defect having a characteristic lifetime of 310ps was observed in the as-grown sample. The lifetime data were well described by a model involving the thermal ionization (0/-) of the VGa-related defect and its ionization energy was found to be E(0/)=83meV. For the electron irradiated sample, the VGa-related defect with lifetime of 310ps that was found in the non-irradiated samples was also identified. Moreover, another lifetime component (280ps) was only observed in the electron irradiated sample but not in the non-irradiated sample. It was also attributed to the V Ga-related defect. The two identified VGa-related defects should have different microstructures because of their difference in characteristic lifetimes. The 280ps component remains thermally stable after the 500°C annealing while the 310ps component anneals at 300°C.published_or_final_versio

Efficient Mixed Transformer for Single Image Super-Resolution

Recently, Transformer-based methods have achieved impressive results in single image super-resolution (SISR). However, the lack of locality mechanism and high complexity limit their application in the field of super-resolution (SR). To solve these problems, we propose a new method, Efficient Mixed Transformer (EMT) in this study. Specifically, we propose the Mixed Transformer Block (MTB), consisting of multiple consecutive transformer layers, in some of which the Pixel Mixer (PM) is used to replace the Self-Attention (SA). PM can enhance the local knowledge aggregation with pixel shifting operations. At the same time, no additional complexity is introduced as PM has no parameters and floating-point operations. Moreover, we employ striped window for SA (SWSA) to gain an efficient global dependency modelling by utilizing image anisotropy. Experimental results show that EMT outperforms the existing methods on benchmark dataset and achieved state-of-the-art performance. The Code is available at https://github. com/Fried-Rice-Lab/EMT.git.Comment: Super-resolution, Long-range attention, Transformer, Localit

How To Introduce On-Line Agricultural Products Navigation System On Google Earth Success

In the agriculture industry many brokers exploit the benefits between farmers and customers and decrease farmers’ income. As technology has developed, the internet has become the best advertising medium for many industries. In light of this, this study based on Google Earth, has designed an on-line Agricultural Products Navigation System operated by mobile devices which can easily exclude brokers, and build the bridge between farmers and customers in order to increase farmers income and customer benefits. Moreover, based on the IS success model of DeLone and McLean, by using qualitative methodology we expect this model will be able to provide system developers with the knowledge to improve the success of their systems