文科《多媒体技术与应用》课程设置与教学研究

多媒体技术是以数字技术为基础的综合技术。本文结合文科学生的特点,探讨了《多媒体技术与应用》课程设置与教学。     

云关系模式及其应用*

在云变换的基础上,结合非经典关系数据库理论提出了云关系模式,给出了云关系模式的定义,探讨了云关系模式的意义,并将它应用于学生成绩数据库中,改进了目前学生定性评定方法,克服了其中的主观因素,实例证明该方法具有可行性.     

工作流技术在ASP公共服务平台中的应用研究*

根据项目特点,建立了适合ASP平台的基于协调理论和反馈机制的扩展活动网络模型,采用XML模式的XPDL规范实现过程定义;然后通过DOM解析XML数据文档和J2EE的技术支持实现了系统的轻量级工作流引擎.详细介绍了系统实现中解决的两个关键问题:事务型操作的处理和并发控制,并提出了基于优先级的锁绑定机制.     

含硫氰酸盐、硫化物固体废物中总氰化合物测定方法

实验建立了含硫氰酸盐、硫化物固体废物中总氰化合物的测定方法,采用硝酸银滴定法、异烟酸-吡唑啉酮分光光度法分别测定总氰化合物含量高、低的样品。通过条件实验优化了前处理方式、称样量和干扰去除方法。该方法测定结果的相对标准偏差为0.43%～1.33%,加入标准物质回收率为91.5%～101.5%,精密度和准确度良好,符合测定要求。     

Cationic ring-opening polymerization of 2-phenyl-1,3,6,2-trioxaphosphocane

Summary The ring-opening polymerization of 2-phenyl-1,3,-6,2-trioxaphosphocane (4), an eight-membered cyclic phosphonite, has been investigated. Cationic initiators of PhCH₂-Cl and MeOTf gave polymers, whereas anionic and radical initiators did not yield polymer. The structure of polymer was examined by IR, ¹H, ³¹P, and ³¹C NMR spectroscopy of polymers and elemental analysis as well as the alkaline hydrolysis products. The polymer consisted of two different units, i.e., the major part is the normal phosphinate structure 5 and the minor part is the isomerized unit 6 in 7% with PhCH₂Cl initiation and in 34% with MeOTf initiator. The difference in nature of propagating species from these two initiators are discussed in connection with their reactivities.On leave from the Institute of Chemistry, Academia Sinica, Beijing, China     

Change of short-term memory effect in acute ischemic ventricular myocardium: A computational study

The ionic mechanism of change in short-term memory (STM) during acute myocardial ischemia has not been well understood. In this paper, an advanced guinea pig ventricular model developed by Luo and Rudy was used to investigate STM property of ischemic ventricular myocardium. STM response was calculated by testing the time to reach steady-state action potential duration (APD) after an abrupt shortening of basic cycling length (BCL) in the pacing protocol. Electrical restitution curves (RCs), which can simultaneously visualize multiple aspects of APD restitution and STM, were obtained from dynamic and local S1S2 restitution portrait (RP), which consist of a longer interval stimulus (S1) and a shorter interval stimulus (S2). The angle between dynamic RC and local S1S2 RC reflects the amount of STM. Our results indicated that compared with control (normal) condition, time constant of STM response in the ischemic condition decreased significantly. Meanwhile the angle which reflects STM amount is less in ischemic model than that in control model. By tracking the effect of ischemia on intracellular ion concentration and membrane currents, we declared that changes in membrane currents caused by ischemia exert subtle influences on STM; it is only the decline of intracellular calcium concentration that give rise to the most decrement of STM.     

A resource-aware scheduling algorithm with reduced task duplication on heterogeneous computing systems

To satisfy the high-performance requirements of application executions, many kinds of task scheduling algorithms have been proposed. Among them, duplication-based scheduling algorithms achieve higher performance compared to others. However, because of their greedy feature, they duplicate parents of each task as long as the finish time can be reduced, which leads to a superfluous consumption of resource. However, a large amount of duplications are unnecessary because slight delay of some uncritical tasks does not affect the overall makespan. Moreover, these redundant duplications would occupy the resources, delay the execution of subsequent tasks, and increase the schedule makespan consequently. In this paper, we propose a novel duplication-based algorithm designed to overcome the above drawbacks. The proposed algorithm is to schedule tasks with the least redundant duplications. An optimizing scheme is introduced to search and remove redundancy for a schedule generated by the proposed algorithm further. Randomly generated directed acyclic graphs and two real-world applications are tested in our experiments. Experimental results show that the proposed algorithm can save up to 15.59  % resource consumption compared with the other algorithms. The makespan has improvement as well.     

Approximate inference for dynamic Bayesian networks: sliding window approach

Dynamic Bayesian networks (DBNs) are probabilistic graphical models that have become a ubiquitous tool for compactly describing statistical relationships among a group of stochastic processes. A suite of elaborately designed inference algorithms makes it possible for intelligent systems to use a DBN to make inferences in uncertain conditions. Unfortunately, exact inference or even approximation in a DBN has been proved to be NP-hard and is generally computationally prohibitive. In this paper, we investigate a sliding window framework for approximate inference in DBNs to reduce the computational burden. By introducing a sliding window that moves forward as time progresses, inference at any time is restricted to a quite narrow region of the network. The main contributions to the sliding window framework include an exploration of its foundations, explication of how it operates, and the proposal of two strategies for adaptive window size selection. To make this framework available as an inference engine, the interface algorithm widely used in exact inference is then integrated with the framework for approximate inference in DBNs. After analyzing its computational complexity, further empirical work is presented to demonstrate the validity of the proposed algorithms.     

A Framework for Moving Least Squares Method with Total Variation Minimizing Regularization

In this paper, we propose a computational framework to incorporate regularization terms used in regularity based variational methods into least squares based methods. In the regularity based variational approach, the image is a result of the competition between the fidelity term and a regularity term, while in the least squares based approach the image is computed as a minimizer to a constrained least squares problem. The total variation minimizing denoising scheme is an exemplary scheme of the former approach with the total variation term as the regularity term, while the moving least squares method is an exemplary scheme of the latter approach. Both approaches have appeared in the literature of image processing independently. By putting schemes from both approaches into a single framework, the resulting scheme benefits from the advantageous properties of both parties. As an example, in this paper, we propose a new denoising scheme, where the total variation minimizing term is adopted by the moving least squares method. The proposed scheme is based on splitting methods, since they make it possible to express the minimization problem as a linear system. In this paper, we employed the split Bregman scheme for its simplicity. The resulting denoising scheme overcomes the drawbacks of both schemes, i.e., the staircase artifact in the total variation minimizing based denoising and the noisy artifact in the moving least squares based denoising method. The proposed computational framework can be utilized to put various combinations of both approaches with different properties together.     

基于海量搜索历史数据的用户兴趣模型

针对互联网搜索引擎环境中,基于海量搜索历史数据分析用户兴趣的问题,提出一种改进的用户兴趣模型。该模型根据用户搜索的历史数据,结合向量空间模型（ VSM ）和TF-IDF算法,递归地回溯出用户兴趣权重列表。为解决用户兴趣变化和时间性能的问题,该模型引入时间遗忘机制进行动态更新,并在Hadoop分布式系统架构下利用MapReduce分布式编程模型进行实现。实验结果表明,改进的用户兴趣模型的查准率和召回率都能达到50',具有较好的可行性和可用性。