Online MapReduce scheduling problem of minimizing the makespan

MapReduce system is a popular big data processing framework, and the performance of it is closely related to the efficiency of the centralized scheduler. In practice, the centralized scheduler often has little information in advance, which means each job may be known only after being released. In this paper, hence, we consider the online MapReduce scheduling problem of minimizing the makespan, where jobs are released over time. Both preemptive and non-preemptive version of the problem are considered. In addition, we assume that reduce tasks cannot be parallelized because they are often complex and hard to be decomposed. For the non-preemptive version, we prove the lower bound is \(\frac{m+m(\Psi (m)-\Psi (k))}{k+m(\Psi (m)-\Psi (k))}\), higher than the basic online machine scheduling problem, where k is the root of the equation \(k=\big \lfloor {\frac{m-k}{1+\Psi (m)-\Psi (k)}+1 }\big \rfloor \) and m is the quantity of machines. Then we devise an \((2-\frac{1}{m})\)-competitive online algorithm called MF-LPT (Map First-Longest Processing Time) based on the LPT. For the preemptive version, we present a 1-competitive algorithm for two machines.     

我国异质性产业体系低碳化发展的实现路径及其影响因素

本文建立了一个异质性产业体系低碳化发展路径选择的分析框架,通过超越对数形式的随机前沿生产函数,测算了我国29个省区产业体系生产技术及其效率和生产规模效率,以及能源使用技术及其效率和碳减排技术及其效率,并针对不同类型产业体系的低碳化发展提出政策建议.结果表明,我国异质性产业体系可以通过不同的结构升级和技术进步的选择形成适合于自身产业体系特征的低碳化发展路径.     

An adaptive-to-model test for partially parametric single-index models

Residual marked empirical process-based tests are commonly used in regression models. However, they suffer from data sparseness in high-dimensional space when there are many covariates. This paper has three purposes. First, we suggest a partial dimension reduction adaptive-to-model testing procedure that can be omnibus against general global alternative models although it fully use the dimension reduction structure under the null hypothesis. This feature is because that the procedure can automatically adapt to the null and alternative models, and thus greatly overcomes the dimensionality problem. Second, to achieve the above goal, we propose a ridge-type eigenvalue ratio estimate to automatically determine the number of linear combinations of the covariates under the null and alternative hypotheses. Third, a Monte-Carlo approximation to the sampling null distribution is suggested. Unlike existing bootstrap approximation methods, this gives an approximation as close to the sampling null distribution as possible by fully utilising the dimension reduction model structure under the null model. Simulation studies and real data analysis are then conducted to illustrate the performance of the new test and compare it with existing tests.     

模糊变权组合预测方法研究

在不确定环境组合预测中,用模糊权重系数更能体现各单项预测方法的客观表现.文章提出一种新的权重系数为三角模糊数的组合预测方法.首先建立以组合预测精确度指数最小为准则的模糊加权组合预测模型,为了避免样本数据中极端值对模型的影响,对模型进行改进,提出带有0-1变量的模糊加权组合预测模型.进一步考虑到单项预测方法在不同时刻的表现有所差异,建立基于诱导有序模糊加权平均(IOFWA)算子的模糊变权组合预测模型,该模型不仅能克服极端值的影响,而且具有更高的预测精确度.并实证验证了该方法的适用性和灵活性.     

A Bayesian sequential design with binary outcome

Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha‐spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha‐spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.     

论毛泽东教育思想及其当代价值

毛泽东教育思想是我国教育事业改革发展的指导思想。毛泽东教育思想的主要内容包括：教育与生产劳动相结合的原则;教育教学改革的思想;德、智、体全面发展的素质教育观;教育为人民大众服务的思想等等。毛泽东教育思想对加快我国教育事业的改革发展,培养适应社会主义现代化建设全面发展的高素质人才具有重要的现实意义。     

论构建社会主义和谐社会的理论贡献

社会和谐是中国特色社会主义的本质属性,是国家富强、民族振兴、人民幸福的保障。构建社会主义和谐社会,是我们党对马克思主义关于社会主义建设理论的丰富和发展;是对中国特色社会主义本质认识的深化;实现了社会主义现代化建设总体布局的新飞跃;丰富了中国社会主义现代化建设目标的思想。总之,构建社会主义和谐社会,是对中国特色社会主义理论的重要贡献。     

树立发展性评价理念 改进高校教师考评工作

高校教师绩效考核是评定与促进教师工作业绩、提高高等教育质量的主要措施。我国高校教师绩效考评已取得很大成就的同时,也存在着不少问题,最大的问题就是现行的评价制度是一种奖惩性评价而非发展性评价。高校教师绩效考核必需坚持在以人为本的科学发展观指导下,实行发展性教师评价,并把着眼点放在教师自身的专业发展和素质的提高上,促进学生、教师和学校的共同发展。     

论文化建设与城市可持续发展

在市场逻辑的背景下,城市化变成物化的单线过程,精神上的城市化却被忽略了。客观分析文化建设的问题和不足,积极探索文化建设的有效途径,才能推动城市可持续发展。     

转型期市场秩序中政府与经营者的博弈分析

当前中国处于转型期,转型初期市场秩序混乱是因为政府与经营者之间的博弈是一种非完全博弈,政府在博弈中居强势地位。随着转型的深入,这种非完全博弈正在也必须向完全博弈转化。政府与经营者之间的博弈趋势应从三个路径突破,才有利于市场秩序的稳定和完善。