基于动力学的头发造型方法

通过对现有头发造型方法的研究,提出一种基于动力学的头发造型方法,采用基于速度的Verlet积分器对头发所处的力场进行模拟,从而对头发进行快速简捷的造型;同时进一步对约束算法进行改进,从而提高了速度.这种方法相比传统的基于几何和基于图像的头发造型方法具有人工交互少、造型速度快的优点.     

基于UML的软件建模概述

UML建模就是利用UML所提供的标准模型元素,并通过一定的扩展机制来组建整个系统的模型。本文结合我们在软件工程高端人才培养模式方面的研究和探索,并针对软件工程相关课程的实践知识体系的设置,对UML在结构建模、用例和行为建模、数据建模、Web建模、设计模式建模及嵌入式系统建模方面的应用进行全面概述,希望对该应用领域的读者有所启发。     

用户建模算法的适应性及多算法用户建模研究

研究用户建模算法在不同条件下的适应性问题,并通过实验分析对比同一种用户建模算法在不同学科、学科相同但主题不同、主题相同但训练集不同的务件下的性能表现.进而提出一种将多种建模方法集成到一起的多算法动态用户建模方法.     

Modeling with light

The problem of making solid objects appear as they are—three-dimensional—is largely a matter of lighting. The subject occurs in the education of children, in the illumination of statuary, in photography, and in television; and the treatment has been almost entirely qualitative and empirical.This paper attempts to raise the problem to the quantitative level by introducing a numerical modeling ratio and by showing how the lighting can be predetermined by calculation to give any desired modeling, without recourse to the cut-and-try methods prevalent in the past.     

ARCH建模研究初探

本文主要介绍了可以为波动性建模的AECH模型族.出于分析金融时间序列领域资产受益率异方差问题的目的,文章较详细地介绍了ARCH模型族的发展和各自的特点,并就ARCH模型建模的步骤进行讲解.     

Structured queries,language modeling,and relevance modeling in cross-language information retrieval

Two probabilistic approaches to cross-lingual retrieval are in wide use today, those based on probabilistic models of relevance, as exemplified by INQUERY, and those based on language modeling. INQUERY, as a query net model, allows the easy incorporation of query operators, including a synonym operator, which has proven to be extremely useful in cross-language information retrieval (CLIR), in an approach often called structured query translation. In contrast, language models incorporate translation probabilities into a unified framework. We compare the two approaches on Arabic and Spanish data sets, using two kinds of bilingual dictionaries––one derived from a conventional dictionary, and one derived from a parallel corpus. We find that structured query processing gives slightly better results when queries are not expanded. On the other hand, when queries are expanded, language modeling gives better results, but only when using a probabilistic dictionary derived from a parallel corpus.We pursue two additional issues inherent in the comparison of structured query processing with language modeling. The first concerns query expansion, and the second is the role of translation probabilities. We compare conventional expansion techniques (pseudo-relevance feedback) with relevance modeling, a new IR approach which fits into the formal framework of language modeling. We find that relevance modeling and pseudo-relevance feedback achieve comparable levels of retrieval and that good translation probabilities confer a small but significant advantage.     

LISREL与PLS建模方法的分析与比较

LISREL与PLS建模方法是目前结构方程建模最流行的两种方法。详细分析两种建模方法,尤其是PLS建模方法;并在此基础上对两种建模方法进行比较,给出各自的应用条件。     

胜任力模型构建方法综述

回顾国内外胜任力模型构建方法,一般被划分为五类:行为事件访谈法(行为法)、职能分析法、情景法、绩效法和多维度法。文章对这五种建模方法进行了介绍,同时对这五种方法进行了简要的对比与分析。     

Composite modeling of nonstationary signals

Most temporal signals of practical interest are nonstationary and need to be modeled using time-varying systems. In this paper a composite model for these signals is proposed which accounts for nonstationarities in the mean and the autocorrelation functions. Unbiased and consistent time-varying estimators for the mean and the variance functions are studied and used to produce zero-mean, constant-variance signals that can be modeled using autoregressive systems with time-varying coefficients. The identification of the coefficients is implemented recursively using the parameterization of the coefficients by a set of basis functions. We illustrate the application of the composite model in the analysis and synthesis of speech and in the estimation of instantaneous frequencies in radar return signals.     

Agent-based modeling of knowledge dynamics

Knowledge is distributed unevenly through most enterprises. Hence, flows of knowledge (e.g., across time, people, locations, organizations) are critical to organizational efficacy and performance under a knowledge-based view of the firm. However, supported principally by narrative textual theory in the emerging knowledge management (KM) field, the researcher has difficulty describing how different kinds of knowledge will flow through various parts of an organization. This causes difficulty also for predicting the effects of alternate approaches to dispersing knowledge that ‘clumps’ in various areas. This problem is also manifest for the KM professional, who lacks clear theory or tools to anticipate how any particular information technology or other managerial intervention may enhance or impede specific knowledge flows in the enterprise. In this expository article, we build upon a steady stream of research in computational organization theory to develop agent-based models of knowledge dynamics. This work draws from emerging theory for multidimensional representation of the knowledge-flow phenomenon, which enables the dynamics of enterprise knowledge flows to be formalized and emulated through computational models. This approach provides the means for knowledge-flow processes to be visualized and analyzed in new ways. Computational experimentation enables the performance of many alternate process designs and technological interventions to be compared through examination of dynamic models, before committing to a specific approach in practice. We illustrate this research method and modeling environment through semi-formal representation and agent-based emulation of several knowledge-flow processes from the domain of software development. We also outline key directions for the new kinds of KM research and practice elucidated by this work.     

一种开放式的知识工作建模方法

知识工作的不确定性和复杂性相对较高,这给知识工作建模方法的研究带来了相当的难度,为此,提出一种开放式的知识工作建模方法。基于对知识工作基本特征的理解,确定知识工作模型的组成要素、各要素的属性及其关联关系;通过对各组成要素状态转换方式的分析,说明知识工作模型的动态运行机制。这种开放式的知识工作建模方法更切合知识工作的特征和本质,有助于知识工作的管理实践。     

企业业务问题解决方案的建模方法研究

为实现企业知识与经验的提炼与重用,通过案例挖掘得到业务问题解决方案并进行标准化建模,提出了业务问题的表达模型及其解决方案的多视图建模方法,提出基于业务问题解决方案的知识服务体系框架,不再局限于以往基于案例捆绑的知识与经验表达方法,在案例层次解析的基础上对业务问题解决方案进行分析,从而实现更小粒度的业务案例经验与知识的重用,有利于企业知识的沉淀及企业知识管理系统的集成。     

Improving semistatic compression via phrase-based modeling

In recent years, new semistatic word-based byte-oriented text compressors, such as Tagged Huffman and those based on Dense Codes, have shown that it is possible to perform fast direct search over compressed text and decompression of arbitrary text passages over collections reduced to around 30–35% of their original size. Much of their success is due to the use of words as source symbols and a byte-oriented target alphabet. This approach broke with traditional statistical compressors, which use characters as source symbols and a bit-oriented target alphabet.     

基于配置理论的可复用业务流程建模

为快速、准确地对复杂多变的企业业务流程进行有效管理,提出了基于配置理论的可复用业务流程建模方法.借鉴产品配置的思想,提出在设计时通过对业务流程进行保留目标的多途径分解,进而建立其非精确模型;在执行时,根据配置的范围与参数不同,采用相应的配置规则得到精确模型并给出其UML描述;对业务流程模型中结构相同的部分进行重复有用性、复用粒度及复用成本等几个方面的可复用性综合评价,以利于新业务流程建模的复用选择;最后给出了应用实例.     

高校数学建模课程教学探讨

随着全国大学生建模竞赛的蓬勃发展,很多高校都陆续开设了建模教学课程。参考各高校的教学模式,总结近几年授课教学经验及调研材料,从建模课程自身特点出发,针对目前建模教学过程中存在的一些问题,提出"因知施教"、"平易近人"等一些教学教改方法,目的能更快更稳更科学的进行建模教学、提高教学质量、提高学生潜力,希望对从事建模教学的教育工作者有一定参考价值。     

基于分形的树木生长建模方法

针对树木生长建模的复杂性和挑战性,采用分形的方法对树木的生长过程进行建模。根据树木枝干和叶片的自然生长特点,模拟叶片的生长过程,采用分形的算法生成树木的主要枝干,并采用Logistic模型模拟树木的生长过程。通过改变树叶的大小、树的深度、弯曲度以及树的大小等参数实现交互式动态生长模型,能够较为逼真地展现树的生长过程。