露天铝土矿山粉尘治理措施

介绍了露天矿山铝土生产流程、产尘源及产尘设备。针对各产尘源的治理进行了分步分析。提出了治理措施。从而有效降低了铝土露天矿山生产过程中外排及岗位粉尘浓度。     

Continuous-time orbit problems are decidable in polynomial-time

We place the continuous-time orbit problem in P$\mathsf{P}$, sharpening the decidability result shown by Hainry [7].     

多个水下机器人动态任务分配和路径规划的信度自组织算法

针对多个水下机器人(autonomous underwater vehicles,AUVs)动态任务分配和路径规划速度跳变问题,引入栅格信度函数概念,给出一种改进的栅格信度自组织(belief function self-organizing map,BFSOM)算法.目的是控制一组AUV有效地到达所有指定的目标位置,同时保证AUV能够自动的避开障碍物.首先,自组织神经网络(self-organizing map,SOM)算法对多AUV系统进行任务分配,使得每个目标位置都有一个AUV去访问.整个分配过程包括定义SOM神经网络的初始权值、获胜者选择、邻域函数的计算3个步骤;其次,根据栅格信度函数和环境信息更新SOM获胜神经元的权值,使得每个AUV在访问对应目标的过程中能够自动避障并且克服速度跳变,实现AUV自动有效路径规划.最后,通过仿真实验证明了本文提及算法的有效性.     

高效动态存储再分配方案与实现

为提高大小和数量都不确定的数据动态存储的空间利用率和处理速度,针对常规系统动态存储分配存在的问题,提出一种高效的动态存储再分配方案。通过减少系统动态存储分配的执行次数,在有效提高存储空间利用率的同时,提高存储空间动态分配的速度,给出动态存储再分配方案的具体实现算法,用实际数据对其性能进行测试。测试结果表明,该方案能节省36％至75％的系统存储空间,分配速度提高了20至50倍。     

基于优先级队列的分布式多主题爬虫

在分布式环境中,为提高资源利用率和网页抓取效率,提出一种基于优先级队列的分布式多主题爬虫调度算法PQ‐MCSA。利用基于缓存的扩展式哈希算法对整体任务集进行切割,按照URL逻辑二级节点哈希映射法,将分割后的子任务集均匀地分配到各处理节点中;利用单处理节点的计算能力结合构建的任务优先级队列进行不同主题任务的调度。该算法改善了传统分布式爬虫对单节点的处理资源调度不充分、多主题任务爬取不均匀等缺点。实际项目的应用结果表明,使用该方法能够有效地提高各主题爬取结果的均衡度,具有较强的实用性。     

考虑时序约束的多智能体协同任务分配

研究多智能体系统的多目标多任务分配问题, 考虑任务之间的时序关系, 建立分布式任务分配模型. 扩展了一致性包算法(CBBA), 按优先级将目标任务归入不同层级, 各智能体在构建任务包和任务路径时, 只将分配过高阶段任务的目标添加至相应的任务包和任务路径中, 从而保证目标任务时序约束的同时, 保持了CBBA算法的特性. 与多任务分配问题经典算法的比对实验表明, 所提出的改进算法求解结果稳定可靠, 运行时间优于经典算法.

     

大规模定制环境下基于产品结构复杂度的工时定额制定研究

针对大规模定制环境下产品种类多、工时制定困难的特点,为了能够快速且准确获取产品工时,研究了产品结构复杂度与工时之间的关系,提出了一种基于产品结构复杂度的工时估算方法.综合考虑影响产品结构复杂度的各种因素后,针对决策结果的排序向量决定决策者权重,引入灰色关联理论,建立了产品结构复杂度计算模型.基于数据库中的工时信息,运用MATLAB软件进行编程确定产品结构复杂度和工时之间的函数关系.最后,以某企业产品加工工时估算实例,证明了所提出的估算方法的可行性.     

基于局部复杂度的环境遮挡

为了提高基于屏幕空间的环境遮挡算法(SSAO)的渲染速度,利用局部复杂度的帧间连续性,提出一种SSAO加速算法.首先为每个像素定义局部复杂度,其中局部复杂度相似的像素会有近似的环境遮挡(AO)值;在此基础上,利用帧间相关性,对于当前帧的像素p,若能在前几帧中找到与它有近似局部复杂度的某个像素,则可以直接复用前面帧的像素的AO值而无需重新计算;最后针对AO复用过程中产生的累积误差提出一种避免误差的方法.实验结果表明,在不影响效果的情况下,该算法可以将SSAO的渲染速度提高10%~40%.     

Coordinate descent with arbitrary sampling I: algorithms and complexity†

We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we call ALPHA. Our method at every iteration updates a random subset of coordinates, following an arbitrary distribution. No coordinate descent methods capable to handle an arbitrary sampling have been studied in the literature before for this problem. ALPHA is a very flexible algorithm: in special cases, it reduces to deterministic and randomized methods such as gradient descent, coordinate descent, parallel coordinate descent and distributed coordinate descent—both in nonaccelerated and accelerated variants. The variants with arbitrary (or importance) sampling are new. We provide a complexity analysis of ALPHA, from which we deduce as a direct corollary complexity bounds for its many variants, all matching or improving best known bounds.     

Doing a Good Job—the Effect of Primary Task Quality on Well‐Being and Job Satisfaction

This paper investigates whether employees’ assessment of their primary task quality has a significant impact on their well‐being and job satisfaction, respectively. Furthermore, the paper hypothesizes that professional values and norms affect employees’ quality expectations on their work tasks and thus their assessment of primary task quality. The paper proposes a measure for primary task quality and uses it in the analyses of responses from 1,247 preschool teachers and teaching assistants in 94 public daycare centers in Denmark. The results indicate that an important factor for employees is their experience of quality in the job they perform. Moreover, quality expectations can differ between employees performing the same task due to, for example, difference in professional training. This leads us to propose a new research direction for job design theory that addresses employees’ assessment of the quality of their primary task job performance.