Comparative Experiments on the Effect of Radar Data Assimilation and Increasing Horizontal Resolution on Short-term Numerical Weather Prediction

To examine the effect of radar data assimilation and increasing horizontal resolution on the short-term numerical weather prediction, comparative numerical experiments are conducted for a Huabei （North China） torrential rainfall event by using the Advanced Regional Prediction System （ARPS） and ARPS Data Anal- ysis System （ADAS）. The experiments use five different horizontal grid spacings, i.e., 18, 15, 9, 6, and 3 km,respectively, under the two different types of analyses： one with radar data, the other without. Results show that, when radar data are not used in the analysis （i.e., only using the conventional observation data）, increasing horizontal resolution can improve the short-term prediction of 6 h with better representation of the frontal structure and higher scores of the rainfall prediction, particularly for heavy rain situations. When radar data are assimilated, it significantly improves the rainfall prediction for the first 6 h, especially the locality and intensity of precipitation. Moreover, using radar data in the analysis is more effective in improving the short-term prediction than increasing horizontal resolution of the model alone, which is demonstrated by the fact that by using radar data in the analysis and a coarser resolution of the 18-km grid spacing, the predicted results are as good as that by using a higher resolution of the 3-km grid spacing without radar data. Further study of the results under the radar data assimilation with grid spacing of 18-3 km reveals that the rainfall prediction is more sensitive to the grid spacing in heavy rain situations （more than 40 mm） than in ordinary rain situations （less than 40 mm）. When the horizontal grid spacing reduces from 6 to 3 km, there is no obvious improvement to the prediction results. This suggests that there is a limit to how far increasing horizontal resolution can do for the improvement of the prediction. Therefore, an effective approach to improve the short-term numerical prediction is to combine the radar data assimilation with an optimal horizontal resolution.

A Comparative Experimental Study on the Blast-Resistant Performances of Single and Multi-Layered Thin Plates Under Close-Range Airblast Loading

The performance of multilayered thin steel plates subjected to close-range air blasts has been experimentally studied and compared with that of monolithic plates made of the same material and having equal mass. In present experiments, multilayered plates are in-contact four-layered thin steel plates and two types of deformation/failure modes were observed for them. Comparisons concerning deformation/failure modes, strain distributions and energy absorptions between the multilayered plate and its monolithic counterpart were conducted. It is found that the multilayered plate is much superior to its monolithic counterpart in the ability to deform against blast loading. Furthermore, under intense airblast loading, the multilayered plate can not only absorb much more energy but also effectively reduce the secondary destruction ability of structural fragments in comparison with its monolithic counterpart.

Squat,Stoop,or Semi-squat:A Comparative Experiment on Lifting Technique

There are actually no sufficient data for lifting technique assessment.A laboratory study was undertaken to determine the effect of 3 regular lifting techniques on erector muscle activation,cardiovascular strain and subjective response.Thirty student volunteers participated in the study,and were required to lift a weight with different techniques.Stoop-,squat-,semi-squat-lifting resulted in 3,2 and 1 time of the highest percentage of the maximum voluntary electrical activation(MVE%) respectively.In the same order,the lowest median frequency(MF) existed 1,1 and 2 times.Muscle fatigue was 4 times in squat,36 in semi-squat and 43 in stoop lifting.Heart rate was the highest in squat and lowest in stoop respectively,with a middle level in semi-squat lifting.It may be recommended to adopt mainly the semi-squat technique for daily lifting works.For heavy lifting,it should use the squat technique.Stoop lifting may also be used alternatively but for light things.

Comparative Experiment of Ground Cucumber Varieties for Open Field Cultivation

Seven ground cucumber varieties were cultivated in open field for the comparative experiment. The results showed that Texuan cucumber and Yantai ground cucumber had good commodity characters,good taste and high yield,and their output value exceeded 16 000 yuan/666. 7 m2,so they are more suitable for open cultivation in Yantai region. The next ones are Meiyu Diguawang and Aweishi ground cucumber.

A Comparative Study on Two Techniques of Reducing the Dimension of Text Feature Space

With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension has become a practical problem in the field. Here we present two clustering methods, i.e. concept association and concept abstract, to achieve the goal. The first refers to the keyword clustering based on the co occurrence of

Adaptive Multi-modal Fusion Instance Segmentation for CAEVs in Complex Conditions:Dataset,Framework and Verifications

Current works of environmental perception for connected autonomous electrified vehicles(CAEVs)mainly focus on the object detection task in good weather and illumination conditions,they often perform poorly in adverse scenarios and have a vague scene parsing ability.This paper aims to develop an end-to-end sharpening mixture of experts(SMoE)fusion framework to improve the robustness and accuracy of the perception systems for CAEVs in complex illumination and weather conditions.Three original contributions make our work distinctive from the existing relevant literature.The Complex KITTI dataset is introduced which consists of 7481 pairs of modified KITTI RGB images and the generated LiDAR dense depth maps,and this dataset is fine annotated in instance-level with the proposed semi-automatic annotation method.The SMoE fusion approach is devised to adaptively learn the robust kernels from complementary modalities.Comprehensive comparative experiments are implemented,and the results show that the proposed SMoE framework yield significant improvements over the other fusion techniques in adverse environmental conditions.This research proposes a SMoE fusion framework to improve the scene parsing ability of the perception systems for CAEVs in adverse conditions.