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Equipment and Worker Recognition of Construction Site with Vision Feature Detection
Qi, Shaowen,Shan, Jiazeng,Xu, Lei Council on Tall Building and Urban Habitat Korea 2020 International journal of high-rise buildings Vol.9 No.4
This article comes up with a new method which is based on the visual characteristic of the objects and machine learning technology to achieve semi-automated recognition of the personnel, machine & materials of the construction sites. Balancing the real-time performance and accuracy, using Faster RCNN (Faster Region-based Convolutional Neural Networks) with transfer learning method appears to be a rational choice. After fine-tuning an ImageNet pre-trained Faster RCNN and testing with it, the result shows that the precision ratio (mAP) has so far reached 67.62%, while the recall ratio (AR) has reached 56.23%. In other word, this recognizing method has achieved rational performance. Further inference with the video of the construction of Huoshenshan Hospital also indicates preliminary success.
Evaluation of the Damage Mechanism in CFRP Composite Using Computer Vision
Oh-Heon Kwon,Shaowen Xu,Michael Sutton 한국마린엔지니어링학회 2010 한국마린엔지니어링학회지 Vol.34 No.4
Continuing progress in high technology has created numerous industrial applications for new advanced composite materials. Among these materials, carbon fiber-reinforced plastic (CFRP) laminate composite is typically used for low-weight carrying structures that require high specific strength. In this study, the damage mechanism of a compact tension (CT) specimen of woven CFRP laminates is described in terms of strain and displacement changes and crack growth behavior. The digital image correlation (DIC) method (which is employed here as a computer vision technique) is analyzed. Acoustic emission (AE) characteristics are also acquired during fracture tests. The results demonstrate the usefulness of these methods in evaluating the damage mechanism for woven CFRP laminate composites. From the results, we show these methods are so useful in order to evaluate the damage mechanism for woven CFRP laminate composites.
Identification of pepper genes involved in the response to CO 2 enrichment using RNA-Seq analysis
Jing Zhang,Rui Bai,Mengya Shang,Xiaoyong Xu,Hongxia Song,Shaowen Zheng,Leiping Hou,Meilan Li,Guoming Xing 한국원예학회 2021 Horticulture, Environment, and Biotechnology Vol.62 No.1
Pepper is widely cultivated, and the application of CO 2 promotes photosynthesis and increases its yield. However, the molecularmechanisms underlying this are still unclear. In this study, the photosynthetic correlation indexes under elevated CO 2and control conditions were compared. The application of CO 2 increased the photosynthetic capacity of pepper. Moreover,RNA-Seq analysis was used to identify genes that were diff erentially expressed between pepper leaves grown in CO 2 -enrichedconditions and those grown in control conditions. The 149 diff erentially expressed genes (DEGs) were found to be involvedin photosynthesis and other metabolic processes. According to GO signifi cant enrichment analysis, the proteins encodedby the DEGs were mainly found to be located in the chloroplast, the chloroplast matrix, and the apoplast. According toKEGG signifi cant enrichment analysis, the DEGs were found to be involved in glutathione metabolism; starch and sucrosemetabolism; and stilbenoid, diarylheptanoid, gingerol, fl avonoid, and phenylpropanoid biosynthesis. The DEGs were alsoinvolved in the pentose phosphate pathway, carbon metabolism, and porphyrin and chlorophyll metabolism. Based on theGO annotation and the KEGG database analysis, ten of the DEGs identifi ed were suggested to be involved in photosynthesisand related processes; these genes were predicted to have roles in carbohydrate, soluble sugar, and glutathione metabolism,and in raffi nose, cysteine, nucleotide, and ABA biosynthesis. These DEGs are involved in the pentose phosphate pathwayand tricarboxylic acid cycle of carbon assimilation during photosynthesis. One of the DEGs was also found to be involved inchlorophyll biosynthesis. These results lay the foundation for further investigation of the molecular mechanisms and genesinvolved in the response to CO 2 enrichment in peppers.