A survey of parallel execution strategies for transitive closure and logic programs

An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods. Recommended by: Patrick Valduriez     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Design of minimax robust LQG controllers under parameter and noise uncertainties

The problem of design of minimax robust LQG controllers for linear systems with parameter and noise uncertainties is considered in this paper. Necessary and sufficient conditions for converting this problem to a two-person, zero-sum continuous game problem are presented. A simple procedure for design of a suboptimal minimax robust LQG controller, i.e., the LQG controller for least-favourable model, is proposed. Necessary and sufficient conditions for the existence of a saddle point are established. Under these conditions, the controller obtained is exactly the minimax LQG controller. When there does not exist a saddle point, the worst-case error between the controller obtained and the minimax robust LQG controllers under described uncertainties is bounded.     

银河－Ⅱ气象应用并行库

本文着重介绍“银河－Ⅱ气象应用并行库”的设计思想、技术特点和使用方法。     

三峡水库减淤增容调度方式研究——多汛限水位调度方案

本文建议在汛期中小流量时（Q<35000m3/s），将坝前水位维持在148～151m；出现汛情且流量更较大后，将坝前水位降低到143m；入库流量大于35000m3/s且短期预报将出现大于十年一遇洪水时，预泄洪水到135m.按这一调度，汛期约80％时间可以维持在较高水位，一般洪水期。汛限水位143m不影响坝区通航，135m水位迎洪可大量增加防洪库客。到100年后可减淤30亿m3，增加防洪库容约40亿m3.变动回水区减淤40%，优化了坝区水沙搭配，可改善通航条件。降低库区洪水位，缓解防洪与移民的矛盾。可对发电带来较大好处：提高发电效益，减少粗沙过机。初期水库排沙比大于原方案，可减轻下游冲刷。同时，可减小三峡汛初泄水与鄱阳湖防洪的矛盾。     

中低品位硅钙质胶磷矿富集技术探讨

过去的正反浮选工艺具有产生的磷精矿中MgO含量低，产品脱水性能好的优点，但选矿成本较高，直接经济效益不显著，为此对“矿浆无需加温”、正浮选作业“无碱”、“无碳酸盐抑制剂”、反浮选“无需添加磷酸”的“四无”正反浮选新工艺进行了研究，结果表明：该新工艺具有技术指标先进，选矿成本低的优点。     

加强项目前期工程造价管理的主要措施

介绍了工程造价管理的定义、特点、内容及对象。阐述了项目前期工程造价管理的重要性 ,并就目前项目前期工程造价管理中投资估算编制存在的问题 ,提出了几点建议     

涡轮钻具在高陡构造的应用及展望

介绍了涡轮钻具在秋参1井的应用情况,详细叙述了涡轮钻具在山前高陡构造快速钻进及防斜打直方面的优点,与常规钻井相比,机械钻速明显提高,钻井周期明显缩短,钻井成本明显下降,经济效益显著。     

基于过程能量综合优化的延迟焦化装置扩大生产能力改造策略

根据延迟焦化流程的特点，分析了延迟焦化装置扩大生产能力的瓶颈，探讨了基于能量综合优化的装置扩能解除瓶颈的策略方法，基于过程能量综合优化，运用流程模拟技术，通过配套的加热炉优化，分馏塔操作优化，换热网络柔性设计等手段，实现了装置扩大生产能力的目的，并运用所提出的策略对某延迟焦化装置进行了基于能量系统优化的扩能改造，在原流程与设备的基础上，装置处理量增大18．2％，装置物耗，能耗大幅度降低，改造设备投资少，说明能量综合优化对工艺装置扩能改造具有重要意义。     

一种高效的硬布线控制CPU的设计方法

文章提出了一种硬布线逻辑CPU的设计流程，即以CPU设计工具软件LDF为核心的设计方法，其主要目的的提高硬布线逻辑CPU的设计效率。定义了一种用于描述硬布线控制逻辑的语言-MCDL，对总线优化问题进行了研究，并且给出了解决总线优化问题的近似算法。