The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distri...In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.展开更多
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small targe...Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.展开更多
A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with t...A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.展开更多
为克服单一赋权法的局限性,结合山区干线公路交通特征及交通安全评价指标的选取原则,从社会因素、驾驶因素、环境因素、管理因素和道路因素五个维度出发,选取18个综合评价指标,运用序关系分析法(Order Relation Analysis Method,G1)-指...为克服单一赋权法的局限性,结合山区干线公路交通特征及交通安全评价指标的选取原则,从社会因素、驾驶因素、环境因素、管理因素和道路因素五个维度出发,选取18个综合评价指标,运用序关系分析法(Order Relation Analysis Method,G1)-指标相关性权重确定法(Criteria Importance Through Intercriteria Correlation,CRITIC)确定各评价指标的权重,并结合折中妥协多属性决策法(VlseKriterijumska Optimizacija I Kompromisno Resenje,VIKOR)对山区干线公路交通安全进行综合评价,提出了基于G1-CRITIC-VIKOR模型的山区干线公路交通安全综合评价及比选方法。以中国西部6条山区干线公路为例进行实证研究,结果表明,G1-CRITIC-VIKOR模型的评价效果与传统的秩和比(Rank-Sum Ratio,RSR)综合评价法及加权逼近理想解排序法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)的评价结果基本一致,且评价效果明显优于后者,具有更好的辨识性,验证了该模型的可行性和科学性。展开更多
目的 :探讨疾病诊断相关分组(Diagnosis Related Groups,DRG)相关指标在护理工作量测算中的应用价值,以期构建更加科学合理的护理工作量评价模型。方法 :以北京市某三级医院31个科室为研究对象,回顾性分析2023年全年各科室11项护理工作...目的 :探讨疾病诊断相关分组(Diagnosis Related Groups,DRG)相关指标在护理工作量测算中的应用价值,以期构建更加科学合理的护理工作量评价模型。方法 :以北京市某三级医院31个科室为研究对象,回顾性分析2023年全年各科室11项护理工作量评价指标的数据,使用熵权法为各指标赋权重,利用秩和比法构建DRG和非DRG工作量评价模型,比较常规测算、DRG模型及非DRG模型3种护理工作量评价方式的优劣。结果:DRG模型和非DRG模型中护士人数、出院人次、床位周转次3个指标权重相同,权重最高的指标均为转入/转出人次,危重人日数次之。相对权重、病例组合指数、护理消耗指数分别处于第8、第5、第10顺位,病例组合指数为模型中不可忽略的重要指标。DRG模型和非DRG模型科室分档结果显示,优档有5个科室(占16%),良档有22个科室(占71%),一般档有4个科室(占13%),分档结果差异具有统计学意义(P<0.05)。结论 :基于DRG相关指标构建的护理工作量评价模型可更好地体现不同科室间的差异,对护理工作量测算具有一定借鉴意义,可为护理管理决策提供科学有效的依据。展开更多
为探究突发公共卫生事件应急能力提升路径,基于应急管理全过程理论,遵循“分析-评价-提升”的逻辑,首先,分析突发公共卫生事件特点与发展变化规律,构建包含预防与准备、监测与预警、处置与救援、恢复与重建4项一级指标,以及23项二级指...为探究突发公共卫生事件应急能力提升路径,基于应急管理全过程理论,遵循“分析-评价-提升”的逻辑,首先,分析突发公共卫生事件特点与发展变化规律,构建包含预防与准备、监测与预警、处置与救援、恢复与重建4项一级指标,以及23项二级指标的评价指标体系;然后结合主成分分析,运用熵权TOPSIS法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)和秩和比法(Rank-Sum Ratio,RSR)构建应急能力评价模型;最后,分析陕西省10个地级市2018-2022年数据,得到各地级市公共卫生事件应急能力评价等级。结果表明:陕西省应急能力分布总体呈现中部高而四周低,北部较高、东南部较低的空间格局;研究期内西安市的应急能力总体表现最优,评分均在0.65以上,其次为榆林、咸阳、铜川和宝鸡;西安市应急能力较为均衡,部分地级市恢复重建能力占比仍有待提升;卫生机构覆盖率、社区卫生服务中心覆盖率和疾病预防控制中心覆盖率为影响突发公共卫生事件管控的最有效因素。研究结果为提升突发公共卫生事件的应对能力提供了一定的实践借鉴。展开更多
Data envelopment analysis（DEA） is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit（DMU）,which is widely used in ranking DMUs.However,almost all DEA-related ran...Data envelopment analysis（DEA） is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit（DMU）,which is widely used in ranking DMUs.However,almost all DEA-related ranking approaches are based on the self-evaluation efficiencies.In other words,each DMU chooses the weights it prefers to most,so the resulted efficiencies are not suitable to be used as ranking criteria.Therefore this paper proposes a new approach to determine a bundle of common weights in DEA efficiency evaluation model by introducing a multi-objective integer programming.The paper also gives the solving process of this multi-objective integer programming,and the solution is proven a Pareto efficient solution.The solving process ensures that the obtained common weight bundle is acceptable by a great number of DMUs.Finally a numeral example is given to demonstrate the approach.展开更多
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金National Natural Science Foundation of China (Grant Nos.12061028, 71871046)Support Program of the Guangxi China Science Foundation (Grant No.2018GXNSFAA281011)。
文摘In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.
基金Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202)。
文摘Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.
基金supported by the Key International Cooperation Research Project(61720106003)the National Natural Science Foundation of China(62001517)+2 种基金the Shanghai Aerospace Science and Technology Innovation Foundation(SAST2019-095)the NUPTSF(NY220111)the Foundational Research Project of Complex Electronic System Simulation Laboratory(DXZT-JC-ZZ-2019-009,DXZTJC-ZZ-2019-005).
文摘A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.
文摘为克服单一赋权法的局限性,结合山区干线公路交通特征及交通安全评价指标的选取原则,从社会因素、驾驶因素、环境因素、管理因素和道路因素五个维度出发,选取18个综合评价指标,运用序关系分析法(Order Relation Analysis Method,G1)-指标相关性权重确定法(Criteria Importance Through Intercriteria Correlation,CRITIC)确定各评价指标的权重,并结合折中妥协多属性决策法(VlseKriterijumska Optimizacija I Kompromisno Resenje,VIKOR)对山区干线公路交通安全进行综合评价,提出了基于G1-CRITIC-VIKOR模型的山区干线公路交通安全综合评价及比选方法。以中国西部6条山区干线公路为例进行实证研究,结果表明,G1-CRITIC-VIKOR模型的评价效果与传统的秩和比(Rank-Sum Ratio,RSR)综合评价法及加权逼近理想解排序法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)的评价结果基本一致,且评价效果明显优于后者,具有更好的辨识性,验证了该模型的可行性和科学性。
文摘将无人机与频谱共享技术相结合,可建立高质量通信链路,提高频谱资源利用效率。然而,由于主、次用户间交叉链路干扰的存在,实现次用户的高可达速率变得十分困难。为了解决该问题,设计了一种智能反射面(Intelligent Reflective Surface,IRS)辅助的无人机认知中继通信网络。通过联合优化无人机的位置部署、次基站的波束成形和IRS的相移矩阵,最大化频谱共享网络中次用户的加权和速率(Weighted Sum Rate,WSR)。为了解决所建立的非凸问题,将其解耦为3个子问题,然后提出了一种交替优化算法来迭代优化变量。利用连续凸逼近(Successive Convex Approxi‑mation,SCA)法对无人机的位置进行优化;利用直接分式规划(Dire ct Fractional Programming,DFP)法对次基站的波束成形进行优化;利用DFP结合交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)对IRS的相移矩阵进行优化。仿真结果表明,与基准算法相比,所提算法能实现更高的次用户WSR。
文摘为探究突发公共卫生事件应急能力提升路径,基于应急管理全过程理论,遵循“分析-评价-提升”的逻辑,首先,分析突发公共卫生事件特点与发展变化规律,构建包含预防与准备、监测与预警、处置与救援、恢复与重建4项一级指标,以及23项二级指标的评价指标体系;然后结合主成分分析,运用熵权TOPSIS法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)和秩和比法(Rank-Sum Ratio,RSR)构建应急能力评价模型;最后,分析陕西省10个地级市2018-2022年数据,得到各地级市公共卫生事件应急能力评价等级。结果表明:陕西省应急能力分布总体呈现中部高而四周低,北部较高、东南部较低的空间格局;研究期内西安市的应急能力总体表现最优,评分均在0.65以上,其次为榆林、咸阳、铜川和宝鸡;西安市应急能力较为均衡,部分地级市恢复重建能力占比仍有待提升;卫生机构覆盖率、社区卫生服务中心覆盖率和疾病预防控制中心覆盖率为影响突发公共卫生事件管控的最有效因素。研究结果为提升突发公共卫生事件的应对能力提供了一定的实践借鉴。
基金supported by the National Natural Science Foundation of China for Innovative Research Groups(70821001)and the National Natural Science Foundation of China(70801056)
文摘Data envelopment analysis（DEA） is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit（DMU）,which is widely used in ranking DMUs.However,almost all DEA-related ranking approaches are based on the self-evaluation efficiencies.In other words,each DMU chooses the weights it prefers to most,so the resulted efficiencies are not suitable to be used as ranking criteria.Therefore this paper proposes a new approach to determine a bundle of common weights in DEA efficiency evaluation model by introducing a multi-objective integer programming.The paper also gives the solving process of this multi-objective integer programming,and the solution is proven a Pareto efficient solution.The solving process ensures that the obtained common weight bundle is acceptable by a great number of DMUs.Finally a numeral example is given to demonstrate the approach.
