高校OA系统正式运行前的工作

很多高校都在进行办公自动化建设,但办公自动化(OA)系统在正式运行前一般要做什么准备工作?本文通过事例阐述了OA系统在正式运行需要经过的步骤和一些具体的实施方法,并说明了OA系统的实施,必须充分发挥各级各类人员的作用才能取得成功。最后指出,OA系统的运行并不能够彻底地废除纸质公文。     

一种细胞核内DNA物质含量准确测量及回归校正新方法

在定量细胞学研究中,细胞核内DNA物质含量的准确测量是癌症筛查与病理诊断的必要前题与最重要依据。由于算法、设备、环境等因素的影响,在对细胞核的数字显微图像进行处理与分析、测量DNA物质含量时会产生较大的误差。本文提出了一种基于数学形态学和k近邻回归算法的DNA物质含量校正新方法。该方法首先利用膨涨算法对细胞核分割掩码进行处理,从而对DNA物质含量的测量进行空间校正;然后采用k近邻回归算法,充分利用细胞核的形态、纹理等特征参数所蕴含的信息,从而对DNA物质含量进行光学回归校正。实验表明,该方法能够显著提高DNA物质含量测量的准确性和可信度,对提高病理诊断的特异性与敏感性都有积极的意义。     

粗糙集理论在选矿生产成本分析中的应用

科学地分析影响原料消耗成本变化的主要因素,才能揭示成本变动原因,为成本控制提供有效依据.因此,提出基于粗糙集理论的原料消耗成本影响因素重要度确定方法.利用分类质量来度量各因素对原料消耗成本的影响程度,应用基于可辨识矩阵和逻辑运算方法求解决策表的最小简约,找出影响原料消耗成本的确定性因素和不确定性因素,为改进生产提供辅助决策支持.实例分析表明,该方法简捷实用,可定量分析影响因素对原料消耗成本的影响程度.     

Crossing textual and visual content in different application scenarios

This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications: a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.

Automated processing for map generalization using web services

In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequences.

Chinese-based research on subject-covered information retrieval supervised by textual semantic domain

By means of analysis of artificial intervention in ready-retrieved text, training set used to compare with new texts from large-scale real texts corpus is provided. It is based on the data-originated presentation of training set that a special formula to calculate semantic cohesion between new texts and training set is devised. The semantic cohesion of new text is the average value of semantic evaluation of all elements involved, and semantic evaluation of an element depends on its semantic relevance with the training set and on the semantic ratio of its domain to synonymous domain. In terms of empirical verification a conclusion is drawn that semantic cohesion is the key measurement standard of textual retrieval. Despite the advantages of textual retrieval, limitations of formula-raised condition and analyst＇s accomplishments make the analysis involved in this paper imperfect.     

Semplore: A scalable IR approach to search the Web of Data

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.     

基于DSP的磁性材料缺陷在线监测系统

在工业制造中,常常需要对磁性材料表面质量进行检测;目前,这种检测仍然采用目视检测手段,既费时费力,又容易漏检,检测结果可靠性差;针对目前国内磁性材料缺陷检测方法比较落后、检测效果较差的情况.设计了一套基于DSP的嵌入式磁性材料表面缺陷的识别与在线检测系统,利用图像处理技术,应用模式识别方法和DSP高速处理能力实现快速无接触测量与分检;经过运行检验表明,该系统能够实时高速地采集和处理图像数据,符合系统对实时性和测量精度的要求.     

基于ART2神经网络的车辆感应波形识别的方法

在智能交通系统中,无论是在交通监控领域还是在不停车收费系统方面,对车辆进行自动分类都十分重要;环形线圈车辆检测器以其良好的适应性、稳定性和高效性在车辆监测方面得到了广泛的应用,同时利用同类型或同种车辆经过环形线圈产生轮廓相似的电磁感应波形这一特点也可以进行车型识别;对波形进行预处理,以波形轮廓的抽样、量化值作为特征向量,将特征向量作为ART2神经网络的输入向量,经ART2神经网络的自动聚类最终实现车辆感应波形的聚类与识别。     

大型动力系统的降维：基于模态截断的非线性Galerkin方法

为了有效地求解大型动力系统,现已提出了各种降维方法．根据非线性Galerkin方法的求解思路,我们将大型动力系统分解成三个子系统,即”慢子系统”、”适速子系统”和”快子系统”．在此基础上提出了改进的非线性Galerkin方法,即：在数值积分过程中将适速子系统的贡献导入慢子系统．然后,以一个含有立方非线性的5自由度强迫振动系统为例阐明了新方法的有效性．