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- 저자 : Zechao (검색결과 4 건)
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A significant improvement of foam performance using Pluronic in molybdenum flotation
Zechao Huangfu,Wei Sun,Yue-hua Hu,Chen Chen,Sultan Ahmed Khoso,Qingpeng Zhang,Jiande Gao,Jianhua Kang 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.61 No.-
In present study, a significant improvement of molybdenum recovery was obtained through improving foam performance using Pluronics (L-61 and L-65), which were used as foam conditioner. The solution properties of L-61 and L-65, such as foamability, bulk rheology, and foam stabilities, on the flotation, were investigated through surface tension and rheological measurements. Results showed that the foam performance of fusel/L-65 composite system was better than those of fusel and fusel/L-61. Moreover, it was forever confirmed by bench-scale flotation that the recovery was increased by 5%, indicating that the foam performance could be improved with addition of L-65.
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KNN-based Image Annotation by Collectively Mining Visual and Semantic Similarities
( Qian Ji ),( Liyan Zhang ),( Zechao Li ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.9
The aim of image annotation is to determine labels that can accurately describe the semantic information of images. Many approaches have been proposed to automate the image annotation task while achieving good performance. However, in most cases, the semantic similarities of images are ignored. Towards this end, we propose a novel Visual-Semantic Nearest Neighbor (VS-KNN) method by collectively exploring visual and semantic similarities for image annotation. First, for each label, visual nearest neighbors of a given test image are constructed from training images associated with this label. Second, each neighboring subset is determined by mining the semantic similarity and the visual similarity. Finally, the relevance between the images and labels is determined based on maximum a posteriori estimation. Extensive experiments were conducted using three widely used image datasets. The experimental results show the effectiveness of the proposed method in comparison with state-of-the-arts methods.
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Hybrid CSA optimization with seasonal RVR in traffic flow forecasting
( Zhangguo Shen ),( Wanliang Wang ),( Qing Shen ),( Zechao Li ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.10
Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.
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In situ observation of mesophase transformation behaviour and mechanistic analysis in β-resin
Liu Ben,Yan Xi,Tao Zechao,Li Xiangfen,Lei Shiwen,Zhang Dongqing,Yang Zonghe,Liu Zhanjun 한국탄소학회 2024 Carbon Letters Vol.34 No.1
β-Resin was extracted by solvent separation of refined coal tar pitch. Several analytical methods revealed that β-resin had a better aromatic plane packing structure and a higher number of carbon residues, making it ideal for mesophase transformation. The mesophase transformation process of β-resin (the formation of liquid-crystalline spheres, the growth of mesophase spheres, and the coalescence and disintegration of mesophase spheres) was observed in situ using a polarizing microscope with a hot stage. Moreover, the mesophase transformation mechanism of β-resin was investigated at each transformation stage. The mesophase content and mesophase transformation kinetics were analyzed based on the area method and quinoline insoluble (QI) substitution method. Both methods revealed changes in the mesophase content of β-resin. However, the test results of the two methods were slightly different at the initial stage of mesophase transformation and tended to be consistent during the later stage.
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