Fluid catalytic cracking (FCC) salty wastewaters, containing quaternary ammonium compounds (QACs), are very difficult to treat by biochemical process. Anoxic/oxic (A/O) biochemical system, based on nitrification and d...Fluid catalytic cracking (FCC) salty wastewaters, containing quaternary ammonium compounds (QACs), are very difficult to treat by biochemical process. Anoxic/oxic (A/O) biochemical system, based on nitrification and denitrification reactions, was used to assess their possible biodegradation. Because of the negative effects of high salt concentration (3%), heavy metals and toxic organic matter on microorganisms’ activities, some techniques consisting of dilution, coagulation and flocculation, and ozonation pretreatments, were gradually tested to evaluate chemical oxygen demand (COD), ammonia-nitrogen (ammonia-N) and total nitrogen (TN) removal rates. In this process of FCC wastewater, starting with university-domesticated sludge, the ammonia-N and TN removal rates were worst. However, when using domesticated SBR’s sludge and operating with five-fold daily diluted influent (thus reducing salt concentration), the ammonia-N removal reached about 57% while the TN removal rate was less than 37% meaning an amelioration of the nitrification process. However, by reducing the dilution factors, these results were inflected after some days of operation, with ammonia-N removal decreasing and TN barely removed meaning a poor nitrification. Even by reducing heavy metals concentration with coagulation/flocculation process, the results never changed. Thereafter, by using ozonation pre-treatment to degrade the detected organic matter of di-tert-butylphenol and certain isoparaffins, COD, ammonia-N and TN removal rates reached 92%, 62% and 61%, respectively. These results showed that the activities of the microorganisms were increased, thus indicating a net denitrification and nitrification reactions improvement.展开更多
针对现有三维目标检测算法对存在遮挡及距离较远目标检测效果差的问题,以基于点云的三维目标检测算法(3D object proposal generation and detection from point cloud,PointRCNN)为基础,对网络进行改进,提高三维目标检测精度。对区域...针对现有三维目标检测算法对存在遮挡及距离较远目标检测效果差的问题,以基于点云的三维目标检测算法(3D object proposal generation and detection from point cloud,PointRCNN)为基础,对网络进行改进,提高三维目标检测精度。对区域生成网络(region proposal network,RPN)获取的提议区域(region of interest,ROI)体素化处理,同时构建不同尺度的区域金字塔来捕获更加广泛的兴趣点;加入点云Transformer模块来增强对网格中心点局部特征的学习;在网络中加入球查询半径预测模块,使得模型可以根据点云密度自适应调整球查询的范围。最后,对所提算法的有效性进行了试验验证,在KITTI数据集下对模型的性能进行评估测试,同时设计相应的消融试验验证模型中各模块的有效性。展开更多
文摘Fluid catalytic cracking (FCC) salty wastewaters, containing quaternary ammonium compounds (QACs), are very difficult to treat by biochemical process. Anoxic/oxic (A/O) biochemical system, based on nitrification and denitrification reactions, was used to assess their possible biodegradation. Because of the negative effects of high salt concentration (3%), heavy metals and toxic organic matter on microorganisms’ activities, some techniques consisting of dilution, coagulation and flocculation, and ozonation pretreatments, were gradually tested to evaluate chemical oxygen demand (COD), ammonia-nitrogen (ammonia-N) and total nitrogen (TN) removal rates. In this process of FCC wastewater, starting with university-domesticated sludge, the ammonia-N and TN removal rates were worst. However, when using domesticated SBR’s sludge and operating with five-fold daily diluted influent (thus reducing salt concentration), the ammonia-N removal reached about 57% while the TN removal rate was less than 37% meaning an amelioration of the nitrification process. However, by reducing the dilution factors, these results were inflected after some days of operation, with ammonia-N removal decreasing and TN barely removed meaning a poor nitrification. Even by reducing heavy metals concentration with coagulation/flocculation process, the results never changed. Thereafter, by using ozonation pre-treatment to degrade the detected organic matter of di-tert-butylphenol and certain isoparaffins, COD, ammonia-N and TN removal rates reached 92%, 62% and 61%, respectively. These results showed that the activities of the microorganisms were increased, thus indicating a net denitrification and nitrification reactions improvement.
文摘针对现有三维目标检测算法对存在遮挡及距离较远目标检测效果差的问题,以基于点云的三维目标检测算法(3D object proposal generation and detection from point cloud,PointRCNN)为基础,对网络进行改进,提高三维目标检测精度。对区域生成网络(region proposal network,RPN)获取的提议区域(region of interest,ROI)体素化处理,同时构建不同尺度的区域金字塔来捕获更加广泛的兴趣点;加入点云Transformer模块来增强对网格中心点局部特征的学习;在网络中加入球查询半径预测模块,使得模型可以根据点云密度自适应调整球查询的范围。最后,对所提算法的有效性进行了试验验证,在KITTI数据集下对模型的性能进行评估测试,同时设计相应的消融试验验证模型中各模块的有效性。
