时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度...时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度优化.针对此不足,本文以非线性工艺为优化对象提出了三层虚拟工作流模型Three-VMG(Three-virtual model graph)及其优化算法Three-OVMG(Three-optimal virtual model graph).该模型和算法首先建立非线性工作流,采用虚拟技术寻找虚拟结点进行重构,将其改造为虚拟线性工作流;其次结合工艺特点对模型进行分段,采用逆向分层串归约来实现段内最优解,采用累积最优解来衔接各段间的值;最后根据优化结果自顶向下完成各层资源的优化调度.实验表明,该过程较传统时间最小化优化调度算法具有显著的优化效果,其性能及可操作性也能满足工程要求.展开更多
为建立检测美洲型猪繁殖与呼吸综合征病毒(PRRSV)的荧光定量PCR方法,在本实验室前期试验筛选到扩增效果相对最好的3对引物(扩增基因区域对应ORF6)的基础上,本研究以PRRSV CH-1R株cDNA作为模板,利用这3对引物进行PCR扩增,将扩增产物克隆...为建立检测美洲型猪繁殖与呼吸综合征病毒(PRRSV)的荧光定量PCR方法,在本实验室前期试验筛选到扩增效果相对最好的3对引物(扩增基因区域对应ORF6)的基础上,本研究以PRRSV CH-1R株cDNA作为模板,利用这3对引物进行PCR扩增,将扩增产物克隆至pMD18-T载体,构建3个重组质粒标准品。采用方阵法对荧光定量PCR反应条件优化,最终建立了3对引物的SYBR Green Ⅰ荧光定量PCR检测方法。结果显示,标准曲线Ct值均与相应质粒标准品浓度存在良好的线性关系,相关系数(R~2)分别为0.992、0.999、0.999;该方法除对美洲型PRRSV有特异性扩增外,对猪圆环病毒2型(PCV2)、伪狂犬病毒(PRV)、猪瘟病毒(CSFV)、欧洲型PRRSV等病原的基因组DNA或cDNA均无扩增,特异性强;对3种质粒标准品的检测下限均为1.228×10^(1)拷贝/μL,敏感性高;组内与组间重复性试验变异系数均小于2%,重复性较好。利用该方法检测6份经预检的PRRS临床样品,3对引物的阳性检出率均为100%,与国标荧光定量PCR方法检出率相当,高于常规PCR(50%、50%和83.3%)的阳性检出率。尽管该方法的3对引物和国标方法均能检出,但部分样品不同引物检测的Ct值有差异。本研究通过利用多对引物并提高引物覆盖面,可减少因引物结合位点突变引起的检测不准确问题,3对引物中,若有1对引物检测样品的结果呈阳性,则该样品判为阳性样品,本研究为PRRSV的快速和定量检测提供了思路和方法。展开更多
Due to the coupling of model parameters, most spatial mixture models for image segmentation can not directly computed by EM algorithm. The paper proposes an evolutional learning algorithm based on weighted likelihood ...Due to the coupling of model parameters, most spatial mixture models for image segmentation can not directly computed by EM algorithm. The paper proposes an evolutional learning algorithm based on weighted likelihood of mixture models for image segmentation. The proposed algorithm consists of multiple generations of learning algorithm, and each stage of learning algorithm corresponds to an EM algorithm of spatially constraint independent mixture model. The smoothed EM result in spatial domain of each stage is considered as the supervision information to guide the next stage clustering. The spatial constraint information is thus incorporated into the independent mixture model. So the coupling problem of the spatial model parameters can be avoided at a lower computational cost. Experiments using synthetic and real images are presented to show the efficiency of the proposed algorithm.展开更多
文摘时间、生产质量和成本是加工制造中相互制约的重要参数,平衡此参数使制造工艺最优是一个NP(Non-deterministic polynomial)难题,对此出现了许多优秀的调度方法.然而这些方法的优化对象均为线性工艺,对于普遍存在的非线性工艺却无法调度优化.针对此不足,本文以非线性工艺为优化对象提出了三层虚拟工作流模型Three-VMG(Three-virtual model graph)及其优化算法Three-OVMG(Three-optimal virtual model graph).该模型和算法首先建立非线性工作流,采用虚拟技术寻找虚拟结点进行重构,将其改造为虚拟线性工作流;其次结合工艺特点对模型进行分段,采用逆向分层串归约来实现段内最优解,采用累积最优解来衔接各段间的值;最后根据优化结果自顶向下完成各层资源的优化调度.实验表明,该过程较传统时间最小化优化调度算法具有显著的优化效果,其性能及可操作性也能满足工程要求.
文摘为建立检测美洲型猪繁殖与呼吸综合征病毒(PRRSV)的荧光定量PCR方法,在本实验室前期试验筛选到扩增效果相对最好的3对引物(扩增基因区域对应ORF6)的基础上,本研究以PRRSV CH-1R株cDNA作为模板,利用这3对引物进行PCR扩增,将扩增产物克隆至pMD18-T载体,构建3个重组质粒标准品。采用方阵法对荧光定量PCR反应条件优化,最终建立了3对引物的SYBR Green Ⅰ荧光定量PCR检测方法。结果显示,标准曲线Ct值均与相应质粒标准品浓度存在良好的线性关系,相关系数(R~2)分别为0.992、0.999、0.999;该方法除对美洲型PRRSV有特异性扩增外,对猪圆环病毒2型(PCV2)、伪狂犬病毒(PRV)、猪瘟病毒(CSFV)、欧洲型PRRSV等病原的基因组DNA或cDNA均无扩增,特异性强;对3种质粒标准品的检测下限均为1.228×10^(1)拷贝/μL,敏感性高;组内与组间重复性试验变异系数均小于2%,重复性较好。利用该方法检测6份经预检的PRRS临床样品,3对引物的阳性检出率均为100%,与国标荧光定量PCR方法检出率相当,高于常规PCR(50%、50%和83.3%)的阳性检出率。尽管该方法的3对引物和国标方法均能检出,但部分样品不同引物检测的Ct值有差异。本研究通过利用多对引物并提高引物覆盖面,可减少因引物结合位点突变引起的检测不准确问题,3对引物中,若有1对引物检测样品的结果呈阳性,则该样品判为阳性样品,本研究为PRRSV的快速和定量检测提供了思路和方法。
基金The paper is supported by the National Science Foundation of Heilongjiang province numbered QC2013C060
文摘Due to the coupling of model parameters, most spatial mixture models for image segmentation can not directly computed by EM algorithm. The paper proposes an evolutional learning algorithm based on weighted likelihood of mixture models for image segmentation. The proposed algorithm consists of multiple generations of learning algorithm, and each stage of learning algorithm corresponds to an EM algorithm of spatially constraint independent mixture model. The smoothed EM result in spatial domain of each stage is considered as the supervision information to guide the next stage clustering. The spatial constraint information is thus incorporated into the independent mixture model. So the coupling problem of the spatial model parameters can be avoided at a lower computational cost. Experiments using synthetic and real images are presented to show the efficiency of the proposed algorithm.
