A SAS macro for target dose estimation by reinforced urn processes in phase I clinical trials

The reinforced urn processes (RUPs) approach can estimate the target dose on the basis of the prior distribution function precisely and conveniently without the requirements about the explicit-estimated dose-response curve and the posterior complicated inference. The application of the RUPs approach was not discussed from the perspective of phase I clinical trial in the previous studies which just focused on the theory and methodology. And the modification of the traditional RUPs design should be considered for the purposes of ethnics and efficiency. A SAS macro was designed to explore the appropriate parameter settings according to the simulation outcomes in different situations and apply the RUPs approach for two state processes in phase I clinical trail with the modified RUPs design. The posterior estimation can be obtained precisely and efficiently with application of SAS program following the appropriate workflow and determination rule which were described in the example.     

User-centric query refinement and processing using granularity-based strategies

Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics–based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.     

一维云模型系统的逼近性研究

针对云模型的基本原理,提出了一类云模型系统的设计方法,并利用Stone-Weierstrass定理对在3σ 正态分布随机数条件下的云模型系统任意逼近紧集上的任意连续实函数进行了证明, 是对云模型应用于逼近任意连续非线性函数理论的创新,也是今后云模型系统用于系统辨识和控制的理论依据.     

堆场集装箱翻箱的PCNN优化控制算法

集装箱的堆存状态与理想发箱顺序很难保持一致, 翻箱操作是不可避免的. 为降低堆场的翻箱率, 提高作业效率, 在获得集装箱的取箱顺序前提下, 将每取一个集装箱所产生的可能状态视为一个状态结点, 所需的翻箱次数加一个基数作为状态结点间的连接权, 把翻箱优化问题转化为最短路径求解问题. 脉冲耦合神经网络(Pulse-coupled neural network, PCNN)具有独特的自动波并行传播的特性, 适用于求解大规模实时问题, 能一次求出源点到其他所有目标点的最短路径, 从而获得最优的翻箱方案. 其所需要的计算量仅正比于最短路径的长度, 与路径图的复杂程度及路径图中的通路总数无关. 这为建立集装箱的智能控制系统奠定了坚实的理论基础.     

新型高分辨率LCD控制器的设计与实现

为了解决ARM等嵌入式处理器驱动大屏幕LCD困难的问题,提出了一种基于FPGA的大屏幕LCD控制器解决方案.该控制器通过搭建合理的架构设计及巧妙的总线仲裁机制,解决了大屏幕显示所需的高刷新率和高更新率问题.同时,多个内部寄存器使其支持各种型号的LCD显示器,并成功地驱动了15英寸的LCD显示器.     

一种基于SVM重采样的似然粒子滤波算法

针对弱观测噪声条件下非线性、非高斯动态系统的滤波问题,提出一种基于支持向量机的似然粒子滤波算法.首先,采用似然函数作为提议分布,融入最新的观测信息,比采用先验转移密度的一般粒子滤波算法更接近状态的真实后验密度;然后,利用当前粒子及其权值,使用支持向量机估计出状态的后验概率密度模型;最后,根据此模型重采样更新粒子集,有效地克服粒子退化现象并提高状态估计精度.仿真结果表明了所提出算法的可行性和有效性.     

The Distributed Workflow Management System — FlowAgent

While mainframe or 2-tier client/server system have serious problems in flexibility and scalability for the large-scale business processes,3-tier client/server architecture and object-oriented system modeling which construct business process on service components seem to bring software system some scalability.As enabling infrastructure for object-oriented methodology,distributed WFMS(Workflow Management System)can flexibly describe business rules among autonomous service tasks,and support scalability of large-scale business process.But current distributed WFMS still have difficulty to manage a large number of distributed tasks,the Multi-Task DOmain‘architecture of FlowAgent will try to solve this problem,and bring a dynamic and distributed environment for task-scheduling.     

多变量系统的软测量建模研究

研究加氢裂化分馏塔多个产品的质量指标同时预报的一类ＭＩＭＯ软测量建模问题,采用ＲＢＦ网络和Ｆｕｚｚｙ ＡＲＴＭＡＰ网络对该ＭＩＭＯ系统进行建模,并用ＲＢＦ网络建立了每个输出的独立的ＭＩＳＯ软测量模型。应用实例表明,所研究的软测量建模为多变量系统软件测量的工业应用提供了一种有效实用的方法。     

QSAR结合人工神经网络方法研究取代芳烃分子结构与Na-K-ATP酶活性

运用函数连接型神经网络研究 3 8种取代芳烃化合物的分子结构—毒性的定量构效关系 (QSAR) ,计算结果与MLR计算结果比较 ,前者比后者好。与实验结果的线性拟合相关系数 ,FLN所得结果为 0 9561～ 0 9996,MLR所得结果为 0 869～ 0 965。     

一种面向服务的系统设计与实现方法

部件技术代表新一代软件技术的发展方向,通过部件软件集成能快速、高效和可靠地建立系统。文章讨论了基于部件软件开发系统的优势和三层结构开发模型的特点。在此基础上,提出一种面向服务的系统设计与实现方法,实际运用证明它是一种有效的系统设计与实现方法。