In critical care medicine,sepsis is a dangerous systemic condition that is highly prevalent and is associated with high morbidity and mortality rates^([1]).The high mortality rate associated with sepsis is closely rel...In critical care medicine,sepsis is a dangerous systemic condition that is highly prevalent and is associated with high morbidity and mortality rates^([1]).The high mortality rate associated with sepsis is closely related to multi-organ dysfunction,with heart injury being particularly critical and considered the starting point of multi-organ injury^([2]).展开更多
In order to improve target localization precision,accuracy,execution efficiency,and application range of the unmanned aerial vehicle(UAV)based on scene matching,a ground target localization method for unmanned aerial ...In order to improve target localization precision,accuracy,execution efficiency,and application range of the unmanned aerial vehicle(UAV)based on scene matching,a ground target localization method for unmanned aerial vehicle based on scene matching(GTLUAVSM)is proposed.The sugges-ted approach entails completing scene matching through a feature matching algorithm.Then,multi-sensor registration is optimized by robust estimation based on homologous registration.Finally,basemap generation and model solution are utilized to improve basemap correspondence and accom-plish aerial image positioning.Theoretical evidence and experimental verification demonstrate that GTLUAVSM can improve localization accuracy,speed,and precision while minimizing reliance on task equipment.展开更多
针对传统近邻传播聚类算法以数据点对之间的相似度作为输入度量,由于需要预设偏向参数p和阻尼系数λ,算法精度无法精确控制的问题,提出了一种跳跃跟踪麻雀搜索算法优化的交叉迭代近邻传播聚类方法.首先,针对麻雀搜索算法中发现者和加入...针对传统近邻传播聚类算法以数据点对之间的相似度作为输入度量,由于需要预设偏向参数p和阻尼系数λ,算法精度无法精确控制的问题,提出了一种跳跃跟踪麻雀搜索算法优化的交叉迭代近邻传播聚类方法.首先,针对麻雀搜索算法中发现者和加入者位置更新不足的问题,设计了一种跳跃跟踪优化策略,通过考虑偏好阻尼因子的跳跃策略设计大步长更新发现者,增加麻雀搜索算法的全局勘探能力和寻优速度,加入者设计动态小步长跟踪领头雀更新位置,同时,利用自适应种群划分机制更新发现者和加入者的比重,增加算法的后期局部开发能力和寻优速度;其次,设计基于扰动因子的Tent映射,在此基础上增加3个参数,使映射分布范围增大,并避免了陷入小周期点和不稳周期点;最后,引入轮廓系数作为评价函数,跳跃跟踪麻雀搜索算法自动寻找较优的p和λ,代替手动输入参数,并融合基于扰动因子的Tent映射优化近邻传播算法,交叉迭代确定最优簇数.使用多种算法聚类University of California Irvine数据集的10种公共数据集,仿真结果表明,本文提出的聚类算法与经典近邻传播算法、基于差分改进的仿射传播聚类算法、基于麻雀搜索算法优化的近邻传播聚类算法和进化近邻传播算法相比具有更优的搜索效率以及聚类精度.对国家信息数据进行了聚类分析,提出的方法更加准确有效合理,具有较好的应用价值.展开更多
基金supported by Jiangsu Traditional Chinese Medicine Science and Technology Development Program(MS2022099)The Postgraduate Research&Practice Innovation Program of Jiangsu Ocean University(No.KYCX2022-34)。
文摘In critical care medicine,sepsis is a dangerous systemic condition that is highly prevalent and is associated with high morbidity and mortality rates^([1]).The high mortality rate associated with sepsis is closely related to multi-organ dysfunction,with heart injury being particularly critical and considered the starting point of multi-organ injury^([2]).
基金the National Key R&D Program of China(2022YFF0604502).
文摘In order to improve target localization precision,accuracy,execution efficiency,and application range of the unmanned aerial vehicle(UAV)based on scene matching,a ground target localization method for unmanned aerial vehicle based on scene matching(GTLUAVSM)is proposed.The sugges-ted approach entails completing scene matching through a feature matching algorithm.Then,multi-sensor registration is optimized by robust estimation based on homologous registration.Finally,basemap generation and model solution are utilized to improve basemap correspondence and accom-plish aerial image positioning.Theoretical evidence and experimental verification demonstrate that GTLUAVSM can improve localization accuracy,speed,and precision while minimizing reliance on task equipment.
文摘针对传统近邻传播聚类算法以数据点对之间的相似度作为输入度量,由于需要预设偏向参数p和阻尼系数λ,算法精度无法精确控制的问题,提出了一种跳跃跟踪麻雀搜索算法优化的交叉迭代近邻传播聚类方法.首先,针对麻雀搜索算法中发现者和加入者位置更新不足的问题,设计了一种跳跃跟踪优化策略,通过考虑偏好阻尼因子的跳跃策略设计大步长更新发现者,增加麻雀搜索算法的全局勘探能力和寻优速度,加入者设计动态小步长跟踪领头雀更新位置,同时,利用自适应种群划分机制更新发现者和加入者的比重,增加算法的后期局部开发能力和寻优速度;其次,设计基于扰动因子的Tent映射,在此基础上增加3个参数,使映射分布范围增大,并避免了陷入小周期点和不稳周期点;最后,引入轮廓系数作为评价函数,跳跃跟踪麻雀搜索算法自动寻找较优的p和λ,代替手动输入参数,并融合基于扰动因子的Tent映射优化近邻传播算法,交叉迭代确定最优簇数.使用多种算法聚类University of California Irvine数据集的10种公共数据集,仿真结果表明,本文提出的聚类算法与经典近邻传播算法、基于差分改进的仿射传播聚类算法、基于麻雀搜索算法优化的近邻传播聚类算法和进化近邻传播算法相比具有更优的搜索效率以及聚类精度.对国家信息数据进行了聚类分析,提出的方法更加准确有效合理,具有较好的应用价值.
文摘针对无人机长期跟踪过程中尺度变换导致目标丢失和跟踪精度低的问题,提出了一种基于飞蛾扑火优化(moth-flame optimization,MFO)的尺度比例感知空间长期跟踪器。首先,设计了高斯初始化以代替飞蛾扑火优化算法的随机初始化策略,降低优化算法在跟踪过程中的计算复杂度,减少算力浪费;其次,结合快速梯度直方图特征,构建了改进的飞蛾扑火优化跟踪器;然后,为了解决无人机航拍长期跟踪中目标尺度变化的问题,设计了一种自适应尺度变换的判别尺度空间跟踪(discriminative scale space tracking,DSST)算法,进一步提出了一种尺度比例感知空间跟踪器,解决了尺度滤波器中因长宽比固定而导致的跟踪漂移;同时,分析了滤波器响应峰值在各背景下的变化情况,提出了一种能反映环境变化下跟踪置信度的指标,并通过置信度将MFO优化跟踪框架与尺度比例感知空间跟踪器相结合,解决了尺度变化与长期跟踪目标丢失的问题;最后,在无人机长期跟踪数据集上开展了性能验证。结果表明:提出的算法可有效防止漂移现象的发生,提升跟踪效率;与目前跟踪领域中12种同类文献算法进行对比可知,提出的算法精度较高,满足实时性,能够有效解决无人机长期跟踪下的尺度变化及目标丢失等问题。
文摘东极黑猪是在我国东北部发现的一种新黑猪群体,试验旨在了解东极黑猪群体结构和遗传多样性,以期更好地保护和利用东极黑猪遗传资源。通过50k SNP芯片研究426头东极黑猪进行遗传多样性、亲缘关系和家系结构,同时加入20头大白猪及20头民猪数据开展主成分分析(Principal component analysis,PCA)。结果表明,东极黑猪57466个SNPs中有47389个SNPs通过质检;PCA结果显示,3个群体分别聚类,东极黑猪与另外两个猪种区分明显;东极黑猪群体中部分个体遗传关系较近,状态同源(Identity by state,IBS)遗传距离为0.0977~0.3589,平均值为0.2752;连续性纯合片段(Runs of homozygosity,ROH)分析发现该群体平均ROH为317.3 Mb,主要分布在200~300 Mb,群体平均近交系数(FROH)为0.133,说明存在近交情况。根据基因组亲缘关系和聚类分析结果,可将东极黑猪群体分为15个家系。综合分析表明,东极黑猪群体遗传多样性丰富,品种独特,但存在近交,建议引入新血统以防遗传多样性丢失。
