Laser speckle contrast imaging(LSCI)is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo,but its applications are limited by shallow penetration depth under reflective imaging configuratio...Laser speckle contrast imaging(LSCI)is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo,but its applications are limited by shallow penetration depth under reflective imaging configuration.The traditional LSCI setup has been used in transmissive imaging for depth extension up to 2l_(t)–3l_(t)(l_(t)is the transport mean free path),but the blood flow estimation is biased due to the depth uncertainty in large depth of field(DOF)images.In this study,we propose a transmissive multifocal LSCI for depth-resolved blood flow in thick tissue,further extending the transmissive LSCI for tissue thickness up to 12lt.The limited-DOF imaging system is applied to the multifocal acquisition,and the depth of the vessel is estimated using a robust visibility parameter V_(r)in the coherent domain.The accuracy and linearity of depth estimation are tested by Monte Carlo simulations.Based on the proposed method,the model of contrast analysis resolving the depth information is established and verified in a phantom experiment.We demonstrated its effectiveness in acquiring depth-resolved vessel structures and flow dynamics in in vivo imaging of chick embryos.展开更多
Similarity measurement is one of key operations to retrieve “desired” images from an image database. As a famous psychological similarity measure approach, the Feature Contrast (FC) model is defined as a linear comb...Similarity measurement is one of key operations to retrieve “desired” images from an image database. As a famous psychological similarity measure approach, the Feature Contrast (FC) model is defined as a linear combination of both common and distinct features. In this paper, an adaptive feature contrast (AdaFC) model is proposed to measure similarity between satellite images for image retrieval. In the AdaFC, an adaptive function is used to model a variable role of distinct features in the similarity measurement. Specifically, given some distinct features in a satellite image, e.g., a COAST image, they might play a significant role when the image is compared with an image including different semantics, e.g., a SEA image, and might be trivial when it is compared with a third image including same semantics, e.g., another COAST image. Experimental results on satellite images show that the proposed model can consistently improve similarity retrieval effectiveness of satellite images including multiple geo-objects, for example COAST images.展开更多
Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a com...Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. We investigate the effectiveness of using wavelet analysis in color models, taking into account the preliminary change in the contrast of the input image. We consider the HSV color model and the image contrast modification procedure, which is based on the histogram change in the specified range with gamma correction. As a criterion for choosing parameters for changing the contrast of the image, we consider the entropy of the image. We also showed the advisability of using the value of the entropy index for the subsequent improvement of image analysis based on the wavelet ideology. We examined the general sequence of action for the analysis of image of megaloblastic anemia cells. This sequence is based on the choice of parameters for changing the contrast of the image and application of wavelet ideology.展开更多
阵风的预报误差检验对实际工作中的精细化预报订正具有一定的指导意义,同时对精细化预报中如何消除误差日变化的影响提供了借鉴。选取2017—2019年3~72 h逐日逐3 h欧洲中期天气预报中心(European Centre for Medium-Range Weather Forec...阵风的预报误差检验对实际工作中的精细化预报订正具有一定的指导意义,同时对精细化预报中如何消除误差日变化的影响提供了借鉴。选取2017—2019年3~72 h逐日逐3 h欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecast,ECMWF)细网格10 m阵风和10 m平均风预报资料,基于大连地区9个国家气象观测站实况逐3 h极大风资料进行预报误差检验分析。结果表明:按预报风级和实况风级分类的预报误差对比检验均表明ECMWF细网格预报整体偏大,平均误差为0.96 m·s-1,但具体到各风级时两种分类的预报误差统计结论并不一致,按预报风级分类的检验更符合基于模式预报开展的实际预报工作。以预报为基准统计,各风向、各风级、各站的预报误差均差异明显,风级越大预报偏大的程度越高,风向也表现出随风级增大误差增大的趋势。阵风预报的平均误差具有明显日变化,08:00(北京时,下同)前后误差最大,20:00前后误差最小,主要由10 m平均风的平均误差日变化所致。全部预报个例与实况各时效预报相关系数均在0.7以上,具体到各风级、风向时,各风向相关性均较好,而各风级的相关系数则明显降低,8级及以上风力预报的可信度大幅下降。展开更多
大规模在线开放课程(massive open online courses,MOOCs)中,知识概念推荐旨在分析和提取平台上的学习记录,进而为用户推荐个性化的知识概念,避免主观盲目地挑选学习内容导致的低效性.然而,现有的知识概念推荐方法缺乏对用户行为数据的...大规模在线开放课程(massive open online courses,MOOCs)中,知识概念推荐旨在分析和提取平台上的学习记录,进而为用户推荐个性化的知识概念,避免主观盲目地挑选学习内容导致的低效性.然而,现有的知识概念推荐方法缺乏对用户行为数据的多维度利用,例如序列信息和复杂类型交互.鉴于此,提出了一种基于序列感知与多元行为数据的MOOCs知识概念推荐方法,提取知识概念的序列信息,并与图卷积网络输出的特征通过注意力机制进行聚合,参与用户下一个感兴趣知识概念的预测.此外,利用多元对比学习,将用户兴趣偏好与不同的交互关系融合,准确学习到复杂交互中的个性化特征.在MOOCCube数据集上的实验结果表明,所提出的方法在多项指标上优于现有的基线模型,验证了其在知识概念推荐中的有效性和实用性.展开更多
基金supported by National Natural Science Foundation of China(NSFC No.61876108)the National Key Research&Development Program of Ministry of Science and Technology of the People's Republic of China(Grant Nos.2018YFC2002300,2018YFC2002303).
文摘Laser speckle contrast imaging(LSCI)is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo,but its applications are limited by shallow penetration depth under reflective imaging configuration.The traditional LSCI setup has been used in transmissive imaging for depth extension up to 2l_(t)–3l_(t)(l_(t)is the transport mean free path),but the blood flow estimation is biased due to the depth uncertainty in large depth of field(DOF)images.In this study,we propose a transmissive multifocal LSCI for depth-resolved blood flow in thick tissue,further extending the transmissive LSCI for tissue thickness up to 12lt.The limited-DOF imaging system is applied to the multifocal acquisition,and the depth of the vessel is estimated using a robust visibility parameter V_(r)in the coherent domain.The accuracy and linearity of depth estimation are tested by Monte Carlo simulations.Based on the proposed method,the model of contrast analysis resolving the depth information is established and verified in a phantom experiment.We demonstrated its effectiveness in acquiring depth-resolved vessel structures and flow dynamics in in vivo imaging of chick embryos.
文摘Similarity measurement is one of key operations to retrieve “desired” images from an image database. As a famous psychological similarity measure approach, the Feature Contrast (FC) model is defined as a linear combination of both common and distinct features. In this paper, an adaptive feature contrast (AdaFC) model is proposed to measure similarity between satellite images for image retrieval. In the AdaFC, an adaptive function is used to model a variable role of distinct features in the similarity measurement. Specifically, given some distinct features in a satellite image, e.g., a COAST image, they might play a significant role when the image is compared with an image including different semantics, e.g., a SEA image, and might be trivial when it is compared with a third image including same semantics, e.g., another COAST image. Experimental results on satellite images show that the proposed model can consistently improve similarity retrieval effectiveness of satellite images including multiple geo-objects, for example COAST images.
文摘Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. We investigate the effectiveness of using wavelet analysis in color models, taking into account the preliminary change in the contrast of the input image. We consider the HSV color model and the image contrast modification procedure, which is based on the histogram change in the specified range with gamma correction. As a criterion for choosing parameters for changing the contrast of the image, we consider the entropy of the image. We also showed the advisability of using the value of the entropy index for the subsequent improvement of image analysis based on the wavelet ideology. We examined the general sequence of action for the analysis of image of megaloblastic anemia cells. This sequence is based on the choice of parameters for changing the contrast of the image and application of wavelet ideology.
文摘大规模在线开放课程(massive open online courses,MOOCs)中,知识概念推荐旨在分析和提取平台上的学习记录,进而为用户推荐个性化的知识概念,避免主观盲目地挑选学习内容导致的低效性.然而,现有的知识概念推荐方法缺乏对用户行为数据的多维度利用,例如序列信息和复杂类型交互.鉴于此,提出了一种基于序列感知与多元行为数据的MOOCs知识概念推荐方法,提取知识概念的序列信息,并与图卷积网络输出的特征通过注意力机制进行聚合,参与用户下一个感兴趣知识概念的预测.此外,利用多元对比学习,将用户兴趣偏好与不同的交互关系融合,准确学习到复杂交互中的个性化特征.在MOOCCube数据集上的实验结果表明,所提出的方法在多项指标上优于现有的基线模型,验证了其在知识概念推荐中的有效性和实用性.
