瓦斯突出预测敏感指标的确定方法研究

通过模糊数学与概率论相结合分析,提出确定预测敏感指标的数学模型,把抽象的敏感指标确定问题通过具体的数值表示出来。实践证明,该模型预测的结果与实际相吻合,该模型的建立对突出矿井确定其敏感指标具有一定的参考价值。     

基于复小波的彩色光流估计

利用色彩恒常性假设,将RGB色彩分量光流基本方程映射至小波域,通过复小波构建的过定线性方程组进行多分辨率光流估计,避免实小波相位震荡带来的光流求解误差,并利用各颜色分量组成的线性方程组的系数矩阵条件数判断求解的可靠性,选择各颜色分量中最可靠的解最为该点最终的光流解。数值实验结果证明了该算法的有效性。     

基于掩模金字塔的高精度全局运动估计算法

在视频序列的全局运动估计中,前景运动对象的存在常常会大幅度地降低估计的精度,为此提出一种对前景对象自适应的高精度全局运动估计算法.该算法以像素块为单位,利用块内外点的比重判定前景区域,同时引入马尔可夫聚类方法进行后处理,有效地提高了运动对象的定位精度;通过对目标函数引入权重系数增强对残差的鲁棒性,以进一步提高算法的估计精度.此外,基于像素掩模的3层金字塔构建序列图像,并将改进的梯度方法引入到优化过程中,提高了算法的实时性.对不同运动类型的标准视频序列的实验结果表明,该算法有效地提高了全局运动估计的精度和速度.     

基于Matlab参数辨识的纯迟延系统预估控制在火电厂的应用

在探讨Smith预传器的控制原理的基础上,针对制约其工程应用的参数估计问题阐述了一种用Matlab软件计算的工程案例.在分析其应用前景的同时,提出将DCS控制系统、Matlab软件和Smith控制有机结合的思路.     

Dempster-Shafer证据理论在目标意图预测中的应用

为了准确对目标意图进行预测,以便我方及时合理地作出战术决策,采用D-S证据理论对目标意图进行预测。首先提取出影响目标意图预测的各个态势因素,然后分析每个因素的影响效果。在此基础上建立目标意图预测的数学模型,利用D-S合成法则将所有因素的影响进行综合,并计算出各个可能命题的概率赋值并给出相应决策。最后,通过仿真实例验证了该方法在目标意图预测中的可行性和实用性。     

改进Informer网络的风电功率短期预测

准确预测风电功率对于提高电力系统的效率和安全性具有重要意义, 而风能的间歇性和随机性特点导致风电功率难以准确预测. 因此, 提出一种改进Informer的风电功率预测模型PCI-Informer (PATCH-CNN-IRFFN-Informer). 将序列数据划分为子序列级补丁, 并进行特征提取和整合, 提高模型对序列数据的处理能力和效果; 采用多尺度因果卷积自注意力机制, 实现多尺度局部特征融合, 提高模型对局部信息的理解和建模能力; 引入反向残差前馈网络 (IRFFN), 增强模型对局部结构信息的提取和保留能力. 某风电场数据实验结果表明, 与主流预测模型相比, PCI-Informer模型在不同预测步长下均取得了更好的预测效果, 在MAE指标上相比Informer模型平均降低了11.1%, 有效提高了短期风电功率的预测精度.     

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.     

Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes

Pathogenic/likely pathogenic variants in susceptibility genes that interrupt RNA splicing are a well-documented mechanism of hereditary cancer syndromes development. However, if RNA studies are not performed, most of the variants beyond the canonical GT-AG splice site are characterized as variants of uncertain significance (VUS). To decrease the VUS burden, we have bioinformatically evaluated all novel VUS detected in 732 consecutive patients tested in the routine genetic counseling process. Twelve VUS that were predicted to cause splicing defects were selected for mRNA analysis. Here, we report a functional characterization of 12 variants located beyond the first two intronic nucleotides using RNAseq in APC, ATM, FH, LZTR1, MSH6, PALB2, RAD51C, and TP53 genes. Based on the analysis of mRNA, we have successfully reclassified 50% of investigated variants. 25% of variants were downgraded to likely benign, whereas 25% were upgraded to likely pathogenic leading to improved clinical management of the patient and the family members.     

基于改进GMM与帧差法的运动棉杂率分析算法研究

针对清梳棉流程中产出棉含杂高、质量差的问题,结合改进高斯混合模型(Gaussian mixed model,GMM)与帧差法,提出一种局部运动棉杂率控制优化方法。首先针对清棉机除杂原理及棉杂特性进行分析;其次通过提取视频关键帧并改进GMM与帧差法对图像序列“与”运算实现目标的精确提取,进而通过设计GMM分类器获得棉杂率并进行分析;最后与传统的检测算法作对比验证。实验表明,改进后的算法在有效性以及实用性方面优于传统算法。同时,通过引入闭环控制能满足工业高精度、实时性的需求。     

DInSAR监测地表三维形变的方法

本文介绍了几种利用DInSAR技术监测地表三维形变的方法,并深入分析了它们各自的优缺点,对它们的使用条件和使用中的应注意的事项进行了讨论。对于DInSAR监测地表三维形变方法的选择,应取决于数据条件,地质情况以及精度等几个因素。文章的最后展望了DInSAR监测地表三维形变方法的发展趋势。