Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at d...Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at decreasing the time consumed on I/O operations, several improved methods are introduced, including a processing flow based on the boundary growing model, which can reduce the database query operations; a concept of the biggest growing block and its determination which can improve the performance of task partition and resolve data-sparse problem; and a fast bitwise algorithm to compute the index numbers of the neighboring blocks, which is a significant efficiency guarantee. Experiments show that the methods can effectively speed up cross-matching on both sparse datasets and high-density datasets.展开更多
目的观察血小板自身抗体与同种抗体对血小板交叉配型难易程度及输注效果的影响。方法选择2021年7月—2023年9月在本实验室完成血小板抗体鉴定的106例血小板输注无效(PTR)患者,根据血小板抗体类型将患者分为两组,20例自身抗体阳性患者为...目的观察血小板自身抗体与同种抗体对血小板交叉配型难易程度及输注效果的影响。方法选择2021年7月—2023年9月在本实验室完成血小板抗体鉴定的106例血小板输注无效(PTR)患者,根据血小板抗体类型将患者分为两组,20例自身抗体阳性患者为观察组,86例同种抗体阳性患者为对照组。比较两组患者配型相合次数百分率、配型相合供者百分率、输注交叉配型相合血小板及随机血小板的24 h血小板计数增加指数(CCI)值及输注有效率的差异,并对观察组自身抗体变化情况进行追踪。结果观察组的配型相合次数百分率及配型相合供者百分率均高于对照组(P<0.05)。观察组患者输注交叉配型相合血小板与随机血小板的24 h CCI值及输注有效率均无显著性差异(P>0.05),对照组患者输注交叉配型相合血小板的24 h CCI值及输注有效率均高于输注随机血小板(P<0.001),对照组患者输注交叉配型相合血小板后24 h CCI值及输注有效率比观察组高(P<0.05),对照组和观察组输注随机血小板后24 h CCI值及输注有效率无显著性差异(P>0.05)。观察组多数患者的自身抗体强度呈下降趋势。结论血小板自身抗体对血小板交叉配型难易程度及输注效果的影响比同种抗体小。血小板自身抗体强度随时间推移呈现逐渐下降乃至消失的规律。在临床实践中,对于自身抗体患者的治疗,应当首先查找病因,并进行针对性治疗,如果需要输注血小板,可以选择输注随机血小板。展开更多
视差不连续区域和重复纹理区域的误匹配率高一直是影响双目立体匹配测量精度的主要问题,为此,本文提出一种基于多特征融合的立体匹配算法。首先,在代价计算阶段,通过高斯加权法赋予邻域像素点的权值,从而优化绝对差之和(Sum of Absolute...视差不连续区域和重复纹理区域的误匹配率高一直是影响双目立体匹配测量精度的主要问题,为此,本文提出一种基于多特征融合的立体匹配算法。首先,在代价计算阶段,通过高斯加权法赋予邻域像素点的权值,从而优化绝对差之和(Sum of Absolute Differences,SAD)算法的计算精度。接着,基于Census变换改进二进制链码方式,将邻域内像素的平均灰度值与梯度图像的灰度均值相融合,进而建立左右图像对应点的判断依据并优化其编码长度。然后,构建基于十字交叉法与改进的引导滤波器相融合的聚合方法,从而实现视差值再分配,以降低误匹配率。最后,通过赢家通吃(Winner Take All,WTA)算法获取初始视差,并采用左右一致性检测方法及亚像素法提高匹配精度,从而获取最终的视差结果。实验结果表明,在Middlebury数据集的测试中,所提SAD-Census算法的平均非遮挡区域和全部区域的误匹配率为分别为2.67%和5.69%,测量200~900 mm距离的平均误差小于2%;而实际三维测量的最大误差为1.5%。实验结果检验了所提算法的有效性和可靠性。展开更多
We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions: HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union s...We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions: HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union set of the two different sets. We use the ThreadPool technique to speed up the cross-match. In this way improved accuracy can be obtained on the cross-match. Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs. We give some ideas about solving the many-for-one situation occurred in the cross-match.展开更多
基金Supported by National Natural Science Foundation of China (No.10978016)Natural Science Foundation of Tianjin (No. 08JCZDJC19700)Key Technologies Research and Development Program of Tianjin (No.09ZCKFGX00400)
文摘Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at decreasing the time consumed on I/O operations, several improved methods are introduced, including a processing flow based on the boundary growing model, which can reduce the database query operations; a concept of the biggest growing block and its determination which can improve the performance of task partition and resolve data-sparse problem; and a fast bitwise algorithm to compute the index numbers of the neighboring blocks, which is a significant efficiency guarantee. Experiments show that the methods can effectively speed up cross-matching on both sparse datasets and high-density datasets.
文摘目的观察血小板自身抗体与同种抗体对血小板交叉配型难易程度及输注效果的影响。方法选择2021年7月—2023年9月在本实验室完成血小板抗体鉴定的106例血小板输注无效(PTR)患者,根据血小板抗体类型将患者分为两组,20例自身抗体阳性患者为观察组,86例同种抗体阳性患者为对照组。比较两组患者配型相合次数百分率、配型相合供者百分率、输注交叉配型相合血小板及随机血小板的24 h血小板计数增加指数(CCI)值及输注有效率的差异,并对观察组自身抗体变化情况进行追踪。结果观察组的配型相合次数百分率及配型相合供者百分率均高于对照组(P<0.05)。观察组患者输注交叉配型相合血小板与随机血小板的24 h CCI值及输注有效率均无显著性差异(P>0.05),对照组患者输注交叉配型相合血小板的24 h CCI值及输注有效率均高于输注随机血小板(P<0.001),对照组患者输注交叉配型相合血小板后24 h CCI值及输注有效率比观察组高(P<0.05),对照组和观察组输注随机血小板后24 h CCI值及输注有效率无显著性差异(P>0.05)。观察组多数患者的自身抗体强度呈下降趋势。结论血小板自身抗体对血小板交叉配型难易程度及输注效果的影响比同种抗体小。血小板自身抗体强度随时间推移呈现逐渐下降乃至消失的规律。在临床实践中,对于自身抗体患者的治疗,应当首先查找病因,并进行针对性治疗,如果需要输注血小板,可以选择输注随机血小板。
文摘视差不连续区域和重复纹理区域的误匹配率高一直是影响双目立体匹配测量精度的主要问题,为此,本文提出一种基于多特征融合的立体匹配算法。首先,在代价计算阶段,通过高斯加权法赋予邻域像素点的权值,从而优化绝对差之和(Sum of Absolute Differences,SAD)算法的计算精度。接着,基于Census变换改进二进制链码方式,将邻域内像素的平均灰度值与梯度图像的灰度均值相融合,进而建立左右图像对应点的判断依据并优化其编码长度。然后,构建基于十字交叉法与改进的引导滤波器相融合的聚合方法,从而实现视差值再分配,以降低误匹配率。最后,通过赢家通吃(Winner Take All,WTA)算法获取初始视差,并采用左右一致性检测方法及亚像素法提高匹配精度,从而获取最终的视差结果。实验结果表明,在Middlebury数据集的测试中,所提SAD-Census算法的平均非遮挡区域和全部区域的误匹配率为分别为2.67%和5.69%,测量200~900 mm距离的平均误差小于2%;而实际三维测量的最大误差为1.5%。实验结果检验了所提算法的有效性和可靠性。
基金supported by the National Natural Science Foundation of China(Grant Nos.10973021,11078013 and 11233004)
文摘We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions: HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union set of the two different sets. We use the ThreadPool technique to speed up the cross-match. In this way improved accuracy can be obtained on the cross-match. Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs. We give some ideas about solving the many-for-one situation occurred in the cross-match.