一种面向对象的超媒体代数视频数据模型

本文根据视频信息的特点,通过对代数视频数据模型和面向对象的超媒体数据模型的整合,给出了一种面向对象的超媒体代数视频数据模型。该模型可进一步有利于数据库系统的操作和视频数据的处理。     

一种面向对象的超媒体代数视频数据模型

本文根据视频信息的特点,通过对代数视频数据模型和面向对象的超媒体数据模型的整合,给出了一种面向对象的超媒体代数视频数据模型.该模型可进一步有利于数据库系统的操作和视频数据的处理.     

一种面向对象的超媒体代数视频数据模型

本文根据视频信息的特点,通过对代数视频数据模型和面向对象的超媒体数据模型的整合,给出了一种面向对象的超媒体代数视频数据模型。该模型可进一步有利于数据库系统的操作和视频数据的处理。     

一种面向对象的超媒体代数初步数据模型

本文根据视频信息的特点,通过对代数视频数据模型和面向对象的超媒体数据模型的整合,给出了一种面向对象的超媒体代数模型,该模型可进一步有利于数据库系统的听任和视频数据的处理。     

传统E-R模型到面向对象数据模型转换的研究

首先介绍了面向对象数据模型的概念，然后指出传统E-R模型与面向对象数据模型的区别，在对二种模型客观分析的基础上提出了一种传统E-R模型到面向对象数据模型的转换方法，最后尝试使用Oracle 9i对象关系数据库实现转换后得到的数据模型。     

嵌套的关系查询及优化

基于面向对象数据模型的查询同关系数据模型查询具有相似的特性和一些明显不同。这些差别表现在面向对象数据库查询、计值的复杂性和实施策略。论文提出一种嵌套的关系数据模型，并用来构造面向对象的数据模型。在此基础上研究了一种基于面向对象数据模型的查询模式，在等价的基础上给出了面向对象的查询与关系查询的转换方式。     

关系数据模型与面向对象数据模型的关系探讨

面向对象数据模型的应用打破了油田单一关系数据库体系架构。如何在面向对象数据模型和关系数据模型并存条件下构建和优化协调统一的数据库体系架构,是油田数据库建设的重要技术方向之一。本文从油田数据库应用的角度概要对比了关系数据模型和面向对象数据模型的特点,对关系数据模型和面向对象数据模型共存条件下建立油田数据库体系架构的可能性进行了探讨。     

面向对象数据库的安全模型及其应用

近年来,数据库安全模型一直是数据库方面研究的热点。由于关系数据模型是建立在良好的数学模型的基础上,因而成熟的关系数据安全模型已经被提出。而面向对象数据模型本身尚未找到坚实的数学基础,针对面向对象数据库的安全模型研究不多,文章在这方面做了一些尝试,它提出了一种基于视图的面向对象数据库的信息过滤模型。该模型以多级数据模型为基础,综合了视图模型和信息过滤模型的优点;然后给出该模型的评价及其应用。     

地下空间三维数据模型分析与设计

三维空间数据模型是地下空间三维建模的基础。讨论了地下空间三维数据模型设计的实体依赖性、数据依赖性、需求依赖性和实现依赖性等特性,并分析了当前地下空间建模的三维数据模型存在的不足,提出了一种新的面向对象的地下空间三维矢量拓扑数据模型。初步实验结果表明,该模型在地下空间对象的存储管理、查询分析以及模型动态编辑等方面都表现出较好的性能。     

映射对象到关系数据库

面向对象技术是当今最流行的软件开发方法,关系模型是最常用的一种数据模型。如何用关系数据库实现持久对象的存储成为信息系统成功的关键。本文对映射对象模型到存储数据的关系模型的方法进行了探讨。     

基于抽象和组合方法的网络协议验证

由于模型检测存在状态爆炸问题,多主体的网络协议组合模型检测往往难以进行。为了缓解该问题,分析了通信主体数量增加对状态数量的影响,提出了组合式的抽象验证方法。首先根据所需验证的LTL性质,建立各个通信主体的Kripke结构,再对该Kripke结构进行抽象;然后组合抽象模型;最后运用Spin对组合抽象模型进行检验。为验证该方法的有效性,对NSPK协议进行了检测,结果表明,该方法所需的状态空间向量长度、搜索深度、存贮和遍历的状态数都有明显减少,有利于缓解状态爆炸问题。     

ICOMDT:一个面向动态任务的交互计算模型

近年来,包含动态任务的交互式系统得到了广泛的应用.基于现有对用户与动态任务交互的研究,提出一个面向动态任务的定量化可计算的交互模型ICOM^DT,用于解释用户与动态任务的交互行为,并实现用户意图预测.更具体地,将ICOM^DT应用于运动目标选择任务,设计了两个实验以验证模型的有效性.实验1收集用户数据对模型进行拟合并预测用户选择的错误率,实验结果表明,能够很好地拟合且预测值也与真实值接近;实验2将模型对用户意图的理解拓展为一种辅助运动目标选择技术ICOMPointer,通过在具体的游戏场景中与Windows原本的选择技术及两种现有的增强目标选择技术对比,发现使用ICOMPointer选中目标的平均完成时间更短,完成速度更快.ICOM^DT模型的提出对计算机理解用户意图,提高用户与动态任务的交互效率有着重要意义.     

An iterative scheme for a geodynamo system

In this paper we propose an iterative scheme for a nonlinear spherical geodynamo model and carry out convergence analysis of this scheme. Our model is a coupled system of fluid velocity u , total kinematic pressure P and magnetic field B . They are governed by the Navier–Stokes equations and the dynamo equations. Using the mathematical induction method and energy estimates, it is concluded that our iterative scheme converges in the L ^∞(0, T; H ¹) sense and in the L ²(0, T; H ²) sense.     

A cellular topology-based approach to generating progressive solid models from feature-centric models

Progressive mesh representation and generation have become one of the most important issues in network-based computer graphics. However, current researches are mostly focused on triangular mesh models. On the other hand, solid models are widely used in industry and are applied to advanced applications such as product design and virtual assembly. Moreover, as the demand to share and transmit these solid models over the network is emerging, how to effectively stream the solid models has been considered as one of the major research issues. In this paper, we present a cellular topology-based approach to generating progressive solid models (PSM) from feature-based models. The proposed approach introduces a new scheme for storing and transmitting solid models over the network. The cellular topology (CT) approach makes it possible to effectively generate PSMs and to efficiently transmit the models over the network with compact model size. Thus, an arbitrary solid model SM designed by a set of design features is stored as a much coarser solid model SM⁰ together with a sequence of n detail records that indicate how to incrementally refine SM⁰ exactly back into the original solid model SM=SMⁿ.     

Stability of an equilibrium state in a multiinfectious-type SIS model on a truncated network

In a homogeneous constant population, the basic SIS model potentially has an epidemic equilibrium state with global asymptotic stability since it can be reduced to the logistic equation. On the basic SIS model with a nonhomogeneous constant population, viewed as a multitype SIS model, the global or local asymptotic stability of an epidemic equilibrium state has also been studied.^1–4 However, this kind of analysis in other models with nonhomogeneous populations has rarely been developed, even though the corresponding models with homogeneous populations are well known. In addition, recent studies of complex networks have revealed that heterogeneity of the link number of vertices drastically changes the epidemic thresholds.^5–9 For these reasons, figuring out the roles of heterogeneity is a major topic in epidemic modeling. Here, we consider a multiinfectious-type SIS model on a network, and show the (local or global) asymptotic stability of an epidemic equilibrium state whenever it exists. This work was presented in part at the 11th International Symposium of Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

非等间隔GM(1, 1, ????) 幂次时间项模型及其应用

GM(1, 1, ??^??) 幂次时间项模型是灰色GM(1, 1) 模型的推广. 在灰色GM(1, 1) 模型和等间隔GM(1, 1, ??^??) 幂次时间项模型的基础上提出非等间隔GM(1, 1, ??^??) 幂次时间项模型, 并对模型进行求解. 讨论了GM(1, 1, ????) 幂次时间项模型的曲线形状、发展系数以及幂指数间的关系, 研究了非等间隔GM(1, 1, ??^??) 幂次时间项模型的参数空间. 将平均相对误差看成幂指数的函数, 根据序列形状判断幂指数的范围, 并利用粒子群算法求解幂指数. 实际应用验证了所提出模型的有效性.

     

Time domain identification for robust control

In this paper, we are concerned with a problem of robust control-oriented system identification in the time domain. Based on the well-known Schur-Takagi-AAK Theorem, we propose a linear algorithm to obtain the nominal model of the plant to be identified and the minimal bound of the uncertainty of the nominal model error which is measured by H^∞-norm. It is also shown that, in the model set defined by the nominal model and the uncertainty bound, there exists at least one model which matches the prescribed input-output data given in the time domain.     

A parallel sorting algorithm for a novel model of computation

The computational complexity of a parallel algorithm depends critically on the model of computation. We describe a simple and elegant rule-based model of computation in which processors apply rules asynchronously to pairs of objects from a global object space. Application of a rule to a pair of objects results in the creation of a new object if the objects satisfy the guard of the rule. The model can be efficiently implemented as a novel MIMD array processor architecture, the Intersecting Broadcast Machine. For this model of computation, we describe an efficient parallel sorting algorithm based on mergesort. The computational complexity of the sorting algorithm isO(nlog² n), comparable to that for specialized sorting networks and an improvement on theO(n ^1.5) complexity of conventional mesh-connected array processors.     

Machine learning technique based extremely broadband small‐signal behavioral model for InP DHBTs

A novel modeling methodology for indium phosphide (InP) double heterojunction bipolar transistors (DHBTs) based on the theory of Bayesian inference, a well‐known method from the field of machine learning, is presented in this article. An extremely broadband small‐signal behavioral model, from 200 MHz to 325 GHz, is built, tested, and validated in this work, with excellent agreement obtained between the extracted model and the experimental data in the form of S‐parameters. A single finger InP DHBT device, with emitter size of 0.5 × 5 μm² exhibiting an ft of over 550 GHz, is used in the verification example. Taking advantage of regression techniques based on machine learning concepts, the proposed black‐box behavioral model can more accurately predict the behavior of the device compared with the traditional equivalent circuit modeling method. Several sets of measured vs modeled data are shown, indicating the efficacy of the method.     

A topic-based term frequency normalization framework to enhance probabilistic information retrieval

Many well-known probabilistic information retrieval models have shown promise for use in document ranking, especially BM25. Nevertheless, it is observed that the control parameters in BM25 usually need to be adjusted to achieve improved performance on different data sets; additionally, the assumption in BM25 on the bag-of-words model prevents its direct utilization of rich information that lies at the sentence or document level. Inspired by the above challenges with respect to BM25, we first propose a new normalization method on the term frequency in BM25 (called BM25_QL in this paper); in addition, the method is incorporated into CRTER₂, a recent BM25-based model, to construct CRTER₂^QL. Then, we incorporate topic modeling and word embedding into BM25 to relax the assumption of the bag-of-words model. In this direction, we propose a topic-based retrieval model, TopTF, for BM25, which is then further incorporated into the language model (LM) and the multiple aspect term frequency (MATF) model. Furthermore, an enhanced topic-based term frequency normalization framework, ETopTF, based on embedding is presented. Experimental studies demonstrate the great effectiveness and performance of these methods. Specifically, on all tested data sets and in terms of the mean average precision (MAP), our proposed models, BM25_QL and CRTER₂^QL, are comparable to BM25 and CRTER₂ with the best b parameter value; the TopTF models significantly outperform the baselines, and the ETopTF models could further improve the TopTF in terms of the MAP.