Approach to conceptual data integration for multidimensional data analysis in e-commerce

In e-commerce the multidimensional data analysis based on the Web data needs integrating various data sources such as XML data and relational data on the conceptual level. A conceptual data description approach to multidimensional data model the UML galaxy diagram is presented in order to conduct multidimensional data analysis for multiple subjects. The approach is illuminated using a case of 2_roots UML galaxy diagram that takes marketing analysis of TV products involved one retailer and several suppliers into consideration.

Using Multiple Correspondence Analysis to Measure Multidimensional Poverty in Congo

The following analysis is based on a multidimensional understanding of poverty using a nonmonetary basic needs approach. It is ground on data from the first survey on household living conditions for poverty assessment, conducted by the National Institute of Statistics of Congo in 2005. Multiple Correspondence Analysis is applied to construct a composite indicator by aggregating several attributes likely to reflect the poverty of individuals or households. The application shows that Congolese households are not affected by the same type of poverty. Three types of non-monetary poverty are identified: infrastructure poverty, vulnerability of human existence and poverty of comfort. These households were then classified according to the composite indicator of Poverty. The results show that the incidence of poverty corresponds to the weight of poor class of about 70.67%.

A visual modeling method for spatiotemporal and multidimensional features in epidemiological analysis:Applied COVID-19 aggregated datasets

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological analysis.However,most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation,resulting in a lack of quantitative and qualitative evidence.To address this issue,we developed a portrait-based visual modeling method called+msRNAer.This method considers the spatiotemporal features of virus transmission patterns and multidimensional features of objective risk factors in communities,enabling portrait-based exploration and comparison in epidemiological analysis.We applied+msRNAer to aggregate COVID-19-related datasets in New South Wales,Australia,combining COVID-19 case number trends,geo-information,intervention events,and expert-supervised risk factors extracted from local government area-based censuses.We perfected the+msRNAer workflow with collaborative views and evaluated its feasibility,effectiveness,and usefulness through one user study and three subject-driven case studies.Positive feedback from experts indicates that+msRNAer provides a general understanding for analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical,timeline,and other factor comparisons.By adopting interactions,experts discovered functional and practical implications for potential patterns of long-standing community factors regarding the vulnerability faced by the pandemic.Experts confirmed that+msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios.

基于MS Analysis Services多维分析系统的实现

基于OLAP技术相关理论,通过分析MS Analysis Services中的多维数据集的建立和访问技术,提出了一种多维分析系统设计与实现方法,并在此基础上给出了一个从OLAP数据源结构设计到应用程序设计的实例,实现了对数据的多角度、多层次的查询及初步分析功能。

基于MS Analysis Services的OLAP系统的设计与实现

通过简要分析MSAnalysisServices及其客户端应用程序的架构 ,介绍了一个建立在MSAnalysisServices上的OLAP系统的设计与实现方法。

基于MS Analysis Services的土地利用OLAP多维分析研究

介绍了OLAP的特性及其多维分析技术。在此基础上,以广东省土地利用分类数据为例,利用M icrosoft SQL Server 2000的数据仓库组件及其中的Analysis Services模块,对其进行了OLAP多维分析研究。

用SQL Server2000 Analysis Service设计与创建多维数据集

阐述了SQLServer 2 0 0 0分析服务的功能与体系结构 ,介绍了利用分析服务构建多维数据集的全过程 :建立数据维度、存储多维数据集、处理数据爆炸和分析多维数据集。

Caries Patterns in the Primary Dentition: Cluster Analysis of a Sample of 5,169 Arizona Children 5-59 Months of Age

Aim Cluster analysis was conducted on data from 5,169 United States （U.S.） Arizona children, age＇s 5-59-months with the goal of delineating patterns of caries in the primary dentition of pre-school children without a priori pattern definitions. Methodology Cluster analyses were conducted using all data for children ages 0-4 years in aggregate： 1） for all subjects, and 2） for subjects without crowned restored teeth. Each of these two sets of analyses consisted of 8 differently specified cluster analyses as a validation procedure. Results The caries patterns identified from the clustering analysis are： 1） smooth surfaces （other than the maxillary incisor）, 2） maxillary incisor, 3） occlusal surfaces of first molars, and 4） pit and fissure surfaces of second molars. Conclusion The cluster analysis findings were consistent with results produced by multidimensional scaling. These cross-validated patterns may represent resulting disease conditions from different risks or the timing of various risk factor exposures. As such, the patterns may be useful case definitions for caries risk factor investigations in children under 60 months of age.

Multi-Vehicle Cooperative Positioning Based on Edge-Computed Multidimensional Scaling

As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning,it can not achieve lane level positioning accuracy.Motivated by the mature ranging technologies such as radar and ultra-wideband(UWB),several cooperative positioning(CP)methods have been proposed to enhance the accuracy and robustness of GPS.In this paper,we proposed a twostage CP algorithm that combines multidimensional scaling(MDS)and Procrustes analysis for vehicles with GPS information.Specifically,the optimized MDS based on the scaling by majorizing a complicated function(SMACOF)algorithm is first proposed to get the relative coordinates of vehicles which can tackle measurements of different error distributions,then Procrustes analysis is carried out to transform the relative coordinates of vehicles to their absolute coordinates based on GPS information.All the computations are performed at the mobile edge computing node(MECN)for the request of ultra-reliable and low latency communications(URLLC).Simulation results validate that the proposed algorithm can greatly improve the positioning accuracy and robustness for vehicles.

Constructing a data platform for surface defect management using a multidimensional database

Surface quality has been one of the key factors influencing the ongoing improvement of the quality of steel. Therefore,it is urgent to provide methods for efficient supervision of surface defects. This paper first expressed the main problems existing in defect management and then focused on constructing a data platform of surface defect management using a multidimensional database. Finally, some onqine applications of the platform at Baosteel were demonstrated. Results show that the constructed multidimensional database provides more structured defect data, and thus it is suitable for swift and multi-angle analysis of the defect data.

RobCoP: A Matlab Package for Robust CoPlot Analysis

The graphical representation method, Robust CoPlot, is a robust variant of the classical CoPlot method. CoPlot is an adaptation of multidimensional scaling (MDS), and is a practical tool for visual inspection and rich interpretation of multivariate data. CoPlot enables presentation of a multidimensional dataset in a two dimensions, in a manner that relations between both variables and observations to be analyzed together. It has also been used as a supplemental tool to cluster analysis, data envelopment analysis (DEA) and outlier detection methods in the literature. However, this method is very sensitive to outliers. When a multidimensional dataset contains outliers, this can lead to undesirable consequences such as the inaccurate representation of the variables. The motivation is to produce Robust CoPlot that is not unduly affected by outliers. In this study, we have presented a new MATLAB package RobCoP for generating robust graphical representation of a multidimensional dataset. This study serves a useful purpose for researchers studying the implementation of Robust CoPlot method by providing a description of the software package RobCoP;it also offers some limited information on the Robust CoPlot analysis itself. The package presented here has enough flexibility to allow a user to select an MDS type and vector correlation method to produce either classical or Robust CoPlot results.

A multidimensional examination of performances of HSR (High-Speed Rail) systems

This paper deals with a multidimensional examination of the infrastructural, technical/technological, operational, economic, social, and environmental performances of high-speed rail （HSR） systems, including their overview, analysis of some real-life cases, and limited （analytical） modeling. The infrastructural performances reflect design and geometrical characteristics of the HSR lines and stations. The technical/technological performances relate to the characteristics of rolling stock, i.e., high-speed trains, and supportive facilities and equipment, i.e., the power supply, signaling, and traffic control and management system（s）. The operational performances include the capacity and productivity of HSR lines and rolling stock, and quality of services. The economic per- formances refer to the HSR systems＇ costs, revenues, and their relationship. The social performances relate to the impacts of HSR systems on the society such as congestion, noise, and safety, and their externalities, and the effects in terms of contribution to the local and global/country social- economic development. Finally, the environmental performances of the HSR systems reflect their energy consumption and related emissions of green house gases, land use, and corresponding externalities.

Bibliometric analysis of researches of empowerment theory applied to nursing in China

Objective:To analysis the development trend and research focus of empowerment theory applied to Nursing in China.Methods:Literatures related to the objective were searched and collected from CNKI,WangFang,VIP and CBM,then Excel 2003 was used to setup the database and co-word matrix,SPSS 21.0 was utilized to make the visualized analysis by way of multivariate statistics analysis,cluster analysis and multidimensional scaling analysis.Results:Literatures with the number of 486 were selected out and 18 high frequency keywords were retrieved from 140 journals.Among the literatures,the first one was published in 2002,then a tremendous rising started since 2009,and reached the peak in 2017,mainly from the southern part of China,such as the province of Jiangsu,Guangdong,and Zhejiang.Regarding the content of the literatures,the research of intervention accounted for 61.32%,then the research of description came to the second at the ratio of 24.49%.What’s more,378(77.78%)were cited,154(31.69%)were funded.Conclusion:Nowadays,empowerment applied in the therapy of chronic disease is the focus and trend of the research of empowerment theory,and the psychological empowerment to nursing staff,as well as the constructed empowerment is going mature.In the future,more attention should be paid to the study and practice of empowerment theory,in order to vary the direction of research and enrich the theory.

维持性血液透析患者症状困扰的多维同期症状网络分析

目的调查维持性血液透析(maintenance hemodialysis,MHD)患者症状困扰现况,并构建多维同期症状网络。方法采用便利抽样法选取2023年6-9月上海市和浙江省共3家医院的512例MHD患者为研究对象,采用透析患者症状负担调查表(dialysis frequency,severity,and symptom burden index,DFSSBI)对MHD患者30项症状的发生频率、严重程度和困扰程度进行调查。使用R软件qgraph包构建多维同期症状网络模型。结果发生率排名靠前的症状分别是瘙痒(64.45%)、皮肤干燥(64.06%)、口干(56.64%)、乏力(51.76%)、入睡困难(51.37%)。症状网络分析的结果显示,症状困扰总体焦虑的强度中心性(r_(S)=8.04)、紧密中心性(r_(C)=0.0078)和桥梁症状强度(r_(bs)=5.58)最大,中介中心性最大的症状是入睡困难(r_(B)=38)。在发生频率、严重程度和困扰程度3个维度,强度中心性最大的症状均是焦虑(r_(S)=7.62、7.83、8.02);紧密中心性最大的症状分别是焦虑(r_(C)=0.0073)、烦躁(r_(C)=0.0077)、焦虑(r_(C)=0.0080);中介中心性最大的症状分别是头晕(r_(B)=52)、入睡困难(r_(B)=38)、入睡困难(r_(B)=44)。结论焦虑是MHD患者的核心症状,最容易影响其他症状,且5个心理症状(担心、悲伤、烦躁、焦虑、紧张)之间的关联性最强,入睡困难则在症状网络中起到关键的桥梁作用,提示医护人员应提高对MHD患者心理症状的关注度并关注患者自我报告症状,同时在制定护理方案时应综合评估患者的整体情况。

汉语学术论文语篇特征变化多维分析

本研究通过自建学术期刊论文语料库,运用Python,对汉语学术论文语篇特征进行多维历时分析,其中包括形式特征分析、语体特征分析、庄雅度特征分析等。研究结果显示,自1980年以来,学术论文语篇特征总体呈现如下变化趋势:论文词汇密度上升,篇幅变长,信息度增强;正式度提高,庄雅度提升,表述主观程度降低。本研究对于揭示汉语学术论文语篇规律,指导学术汉语写作教学具有一定的参考价值。

基于多维度输入的水厂日取水量卷积长短期记忆网络预测

鉴于传统的单维输入卷积长短期记忆网络(CNN-LSTM)的预测精度依赖于历史数据的规律性,构建了基于多维度输入的卷积长短期记忆网络预测模型,其中采用皮尔逊相关分析来识别数据内部特征或外界环境因子相关性,在此基础上构建模型输入,并应用于两个自来水厂日取水量预测。结果表明,相较于传统单维度输入预测模型,构建的基于数据内部特征或外部环境因子的多维度输入CNN-LSTM预测导致A水厂取水量的平均绝对百分比误差分别降低了32%、17%;B水厂的平均绝对百分比误差分别降低了47%、12%,表明基于数据内部特征的多维度输入模型更高。其余评价指标也呈现类似变化;且增大水厂取水量有助于提高模型的预测精度。该模型输入分析方法可为提高预测模型精度提供有效范例。

多维邻近性对国际技术标准生存时间的影响研究——基于ITU国际技术标准生存分析

在技术快速变革和迭代的时代背景下,构建技术标准联盟是各类组织适应技术快速发展的必要手段。技术标准联盟的组织构成正在朝着跨国化和多样化发展,联盟成员间特征差异程度的提升对技术标准生存时间产生了重要影响。根据协同创新理论,基于2010—2021年ITU国际技术标准联盟的相关数据,运用生存分析方法,分析多维邻近性与技术标准生存时间的内在关联。结果表明,地理邻近性与技术邻近性能显著提高ITU国际技术标准生存时间;组织邻近性与制度邻近性对ITU国际技术标准生存时间具有显著负向影响;地理邻近性与技术邻近性、组织邻近性与制度邻近性的交互作用对ITU国际技术标准生存时间具有显著负向影响,地理邻近性与组织邻近性、地理邻近性与制度邻近性、技术邻近性与组织邻近性以及技术邻近性与制度邻近性的交互作用对ITU国际技术标准生存时间具有显著正向影响。研究有助于深化对技术标准联盟协同创新的理论解释,丰富了技术标准生存时间驱动因素的理论成果,可为我国信息和通信技术行业国际技术标准制定的管理实践提供重要参考。

多维平行六面体模型非概率可靠性灵敏度分析

可靠性灵敏度能够反映基本变量分布参数对可靠度的影响程度,为可靠性分析与优化设计提供指导。提出了一种基于多维平行六面体模型的非概率可靠性灵敏度分析方法。首先,给出基本变量域完全位于安全域时采用非概率可靠性指标,而基本变量域与安全域有交集时采用非概率失效度作为可靠性度量的原因。其次,推导结构线性系统的可靠性灵敏度解析式,并进一步探讨所提方法对结构非线性系统的适应性问题。最后,通过3个工程算例验证文中方法有效可行。

面向多维时空航班数据的渐进式可视分析方法

航班在实际运营中频繁地调整,对航空公司运营会产生不良的影响,运用可视分析方法分析历史航班的运营特征,可以发现航班计划中存在的缺陷,为航班计划调整提供支撑。该文设计面向多维时空航班数据的FlightOM-Vis系统,支持自上而下渐进式分析航班运营特征:采用多视图展示信息;融合面向数据多个维度的聚类分析方法;保留分析结果的上下文信息;提供丰富的交互工具。实验采用东方航空公司航班数据集进行验证,结果表明该系统能够协助分析人员快速挖掘隐藏在数据子集中的航班运营特征,根据可视化结果做出指导性建议。

我国人才研究特征与热点态势--基于国家社会科学基金项目分析

人才是第一资源,人才资源在经济社会发展中有着突出地位和作用。以1983—2023年295项国家社科基金人才研究项目为样本数据进行统计分析。研究表明,立项数量方面,人才研究的年度立项数量整体呈现上升趋势,主要分为平稳阶段、波动增长阶段、平稳增长阶段;学科分布方面,人才研究的交叉学科属性突出,广泛分布于23个基础学科中,主要集中在管理学、教育学、体育学3个学科;研究热点方面,以党和国家重大理论和现实问题为导向,重点关注高层次人才、科技人才、创新人才、后备人才、国际人才,形成了人才培养、人才体制机制、人才流动、人才评价等热点研究版块。存在研究力量区域分布不均衡、高层次创新型人才短缺、人才服务和推动人才发展的体制和机制仍需不断调整和创新等问题。未来,国家社科基金应加大对人才项目的支持,人才研究将朝着与深入实施人才强国战略、不断完善中国特色社会主义人才理论、解决我国人才难题等新的热点相结合的方向拓展。