Exploratory Data Analysis Applied in Mapping Multi-element Soil Geochemical Anomalies for Drill Target Definition:A Case Study from the Unpha Layered Non-magmatic Hydrothermal Pb-Zn Deposit,DPR Korea

A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.

Clustering Structure Analysis in Time-Series Data With Density-Based Clusterability Measure

Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algorithms force a structure in the data instead of discovering one.To avoid false structures in the relations of data,a novel clusterability assessment method called density-based clusterability measure is proposed in this paper.I measures the prominence of clustering structure in the data to evaluate whether a cluster analysis could produce a meaningfu insight to the relationships in the data.This is especially useful in time-series data since visualizing the structure in time-series data is hard.The performance of the clusterability measure is evalu ated against several synthetic data sets and time-series data sets which illustrate that the density-based clusterability measure can successfully indicate clustering structure of time-series data.

A New Algorithm for Generalized Least Squares Factor Analysis with a Majorization Technique

Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimation in FA. In the algorithm, a majorization step and diagonal steps are alternately iterated until convergence is reached, where Kiers and ten Berge’s (1992) majorization technique is used for the former step, and the latter ones are formulated as minimizing simple quadratic functions of diagonal matrices. This procedure is named a majorizing-diagonal (MD) algorithm. In contrast to the existing gradient approaches, differential calculus is not used and only elmentary matrix computations are required in the MD algorithm. A simuation study shows that the proposed MD algorithm recovers parameters better than the existing algorithms.

Introduction of New Method on Engineering Risk Assessment:Engineering Errors and Effects Analysis(3EA)

Construction and commissioning accidents investigation shows that engineer’s errors in basic and detailed phases are the main causes.It will be gained more efficiency of investment when a relevant method is applied for error identification and risk assessment in basic and detailed phases.Most of risk assessment methods are related to construction phase,meanwhile hidden risks that were happen in previous phases cannot be found by these methods.Although HAZOP study can be applied in detail phase but it can help to find process defections.Importance of identifying risks in basic and detailed phases is to apply preventive actions against birth and grows risks.This risk assessment method can reduce costs and improve environmental protection,safety,and reliability of designs.The main purpose of this study is to identify engineer’s errors and analyse their HSE effects.The method is applied in seven oil and gas engineering projects in Iran,raising the level of engineer’s attention to safety precautions and environmentally-friendly design,reducing the cost of improving the level of safety and environmental protection,improving environmental protection,safety,and design reliability,and improving procedures related to design process and control have been achieved.

Inter-Organizational Conflict (IOC) in Building Refurbishment Projects;an Exploratory Factor Analysis (EFA) approach

Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.

Spatio-temporal evolution and factor explanatory power analysis of urban resilience in the Yangtze River Economic Belt

Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.

New approaches to cognitive work analysis through latent variable modeling in mining operations

This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.

Study of Work-Travel Related Behavior Using Principal Component Analysis

The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.

Geographical Analysis of Lung Cancer Mortality Rate and PM2.5 Using Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth

Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.

A preliminary study on exploratory search behavior of undergraduate students in China

Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behavioral model.Design/methodology/approach: Forty-two matriculated full-time senior college students with a female-to-male ratio of 1 to 1 who majored in medical science in Jilin University participated in our experiment. The task of the experiment was to search for information about 'the influence of environmental pollution on daily life' in order to write a report about this topic. The research methods include concept map, query log analysis and questionnaire survey.Findings: The results indicate that exploratory search can significantly change the knowledge structure of searchers. As searchers were moving through different stages of the exploratory search process, they experienced cognitive changes, and their search behaviors were characterized by quick browsing, careful browsing and focused searching.Research limitations: The study used only one search topic, and there is no comparision or control group. Although we took search habits, personal thinking habits, personality characteristics and professional background into account, a more detailed study to analyze the effects of these factors on exploratory search behavior is needed in our further research.Practical implications: This study can serve as a reference for other researchers engaged in the same effort to construct the supporting system of exploratory search.Originality/value: Three methods are used to investigate the behavior characteristics during exploratory search.

桥梁健康监测数据的质量评估方法研究

桥梁健康监测数据的挖掘和分析工作只有在整体数据质量符合基本要求的有效数据基础上进行,才能保障如模态参数识别、损伤识别和状态评估等后续工作的准确性。因此,基于量化改进的探索性分析方法(Exploratory Data Analysis,EDA)和相关性分析从数据完整性、准确性和一致性的角度建立了桥梁健康监测静、动态数据的质量评估方法。对某大跨度斜拉桥健康监测系统的静、动态数据进行质量评估,通过对比分析了不同评估质量的温度数据、静挠度数据和不同评估质量的主梁竖向加速度动力信号的模态参数识别的稳定图,验证了所提方法的正确性。结果表明,所提评估方法能够快速有效地判断数据质量的好坏,进而确保桥梁结构的服役性能评估和预测的准确性,有利于提高健康监测数据的可用性和效能。

铁路建设项目柔性管理及影响因素研究

研究目的:当前我国多条艰险山区铁路和高原铁路开工建设,动态多变的外部环境、多约束条件下的建设组织以及新技术带来的不确定性挑战日益严峻。为应对诸多项目复杂性因素带来的挑战,探索铁路建设项目柔性管理新范式十分必要。通过识别影响项目柔性的各种管理因素,构建具有较强韧性的铁路建设管理体系,为铁路建设项目承包商提供新的管理理念和方法。研究结论:(1)面对普遍存在的项目复杂性挑战,铁路建设项目可以推行柔性管理,调整传统“规划-控制”型管理风格,适度增强项目柔性,提高项目响应环境变化和不确定性的能力;(2)通过文献分析、专家咨询及统计分析,确定了柔性合同、BIM技术应用等8个影响因素,构建了包括团队柔性和过程柔性的铁路建设项目柔性二维因子模型,其中信息共享、团队学习和管理创新是影响铁路建设项目柔性的关键因素;(3)本研究成果可以在铁路建设管理领域推广应用,能够为铁路建设承包商推行柔性管理提供理论参考。

战略认知差异会影响企业技术创新吗?——基于文本主题分析的实证研究

在知识经济时代,知识对创新的边际贡献超过传统物质性生产要素,企业技术创新优势更多源于管理者认知的转变,而不再由异质性的资源所决定。本文探讨了行业场景中管理者的战略认知相较于行业共享信念之间的差异对技术创新的影响,同时考虑了探索式学习与知识组合多样性在其中所发挥的路径传导作用。研究结果显示:管理者的战略认知差异能够显著促进以专利申请量为表征的技术创新数量,提高以专利外部引用为表征的技术创新质量。进一步研究发现,探索式学习和知识组合多样性在战略认知差异与技术创新的关系中发挥了部分中介作用。异质性分析发现,受到来自家族权威和行政制度的干预,管理者的战略认知差异在非家族企业与非国有企业样本中表现出更为显著的技术创新效果。研究结论从战略认知差异视角拓展了技术创新的前因研究,同时为理解中国企业的创新决策逻辑、探究创新人才培养路径提供了理论参考。

县域耕地非农化时空演变特征及动态趋势研究——以安徽省为例

耕地是国家粮食安全的物质基础,把握耕地非农化的时空演变规律及动态趋势,对保障粮食供给和可持续发展具有重要意义。以安徽省为研究对象,基于ArcGIS、GeoDa和Matlab软件,提取安徽省1995—2020年耕地非农化数据,在县域尺度上,采取探索性空间数据分析方法研究耕地非农化时空演变特征,运用MarKov链分析耕地非农化的动态演变趋势,为合理管控耕地非农化提供科学依据。结果表明,安徽省耕地非农化面积高值区主要位于安徽省中部(合肥都市圈)重点发展区,低值区主要集中在安徽省北部和南部一些经济欠发达地区,空间集聚性呈先减后增再减趋势,集聚效应逐渐减弱,冷热点区在空间上形成了“块状热点集群”和“点状冷点集群”。安徽省县域耕地非农化水平的趋势主要表现为:不同等级间不够稳定,易发生转移;等级转移基本发生在相邻类型之间,较少出现“跳跃式”转移;考虑空间因素后发现,相邻县区差异化的耕地非农化水平对本县区发生等级转移的概率有不同程度的影响,随着空间溢出效应增强,维持原等级的概率越低,更易发生转移;等级转移的概率同时受空间滞后类型和初始等级的影响。

基于EDA统计图量化的桥梁动态监测数据质量评估

探索性数据分析统计图在桥梁健康监测动态数据质量评估中已有广泛应用。为了减少人工观察统计图的主观性,通过近似度量方法实现统计图的量化分析,得到多个指标对监测数据进行快速质量评估。在运营环境激励作用下,桥梁结构动力响应具有短时线性平稳性,近似服从正态分布。以某大跨斜拉桥振动数据为研究对象,首先,绘制样本数据直方图和Q-Q图,通过观察数据分布特征预先判断数据质量,确定优、良和差3个等级。然后,分别通过KL散度和余弦相似度2种近似度量方法对样本数据直方图和Q-Q图进行量化,得到数据服从正态分布程度的指标;通过箱线图检测样本数据全局异常点,得到正常数据占比;统计分析得到量化值和先验质量等级的对应关系,确定以直方图KL散度和余弦相似度为主、以箱线图正常数据占比为辅的数据质量评估标准。最后,取部分数据为验证集,进一步验证所提方法各个指标的合理性,并给出该方法在实际工程上的应用结果。

危险货物运输驾驶人风险倾向分类及识别模型研究

为合理评估危险货物运输驾驶人驾驶过程中的风险倾向,建立危险货物运输驾驶人风险倾向聚类及辨识体系,以动态监控系统中记录的驾驶人实时违规预警数据为基础,选取可能引发交通冲突的安全关键事件为特征参数,利用探索性因子分析方法实现指标降维,提取驾驶人风险倾向主因子,并通过K means算法聚类不同风险倾向的驾驶人,最后基于聚类结果监督训练随机森林模型,辨识未知驾驶人的风险倾向。结果表明,利用选取的8类安全关键事件特征参数,可以将驾驶人风险倾向划分为攻击驾驶倾向、鲁莽驾驶倾向、驾驶分神倾向和驾驶疲劳倾向,且可以识别风险较低的驾驶人,基于随机森林模型的驾驶人风险倾向识别准确率为88.68%,可以较好地实现危险货物运输驾驶人风险倾向辨识。研究结果为危险货物运输驾驶人风险倾向分类及识别提供了方法依据。

体育彩票业网络关注度时空分异与影响因素研究

网络关注度体现了人们对某种事物的现实关注和潜在需求,为研究大数据背景下事物发展趋势提供了新的数据参考。运用指数测度、探索性空间数据分析(ESDA)和地理探测器等方法,对2011—2021年我国31个省(市、自治区)体育彩票网络关注度的时空分异特征及影响因素进行分析。结果表明:(1)在时间上,2011—2021年中国体育彩票总体呈现先上升再下降并趋于稳定的态势。(2)在空间上,中国体育彩票网络关注度总体表现为集聚—随机—再集聚分布的特征;各省份之间空间异质性与空间依赖性并存;网络关注度的冷热点区域沿“胡焕庸线”两侧分布,呈现出南多北少、东部密集西部稀疏的极化效应。(3)地区生产总值、中青年人口数量、大专及大专以上人口数、互联网宽带接入用户数和体育彩票销量是造成中国体育彩票网络关注度空间分异的核心影响因素,各个因素的影响程度在地理空间上存在一定差异。

探索性分析框架EAF的设计

实现了一个探索性分析框架原型系统EAF,使得问题的分析与相关模型独立开来,因而更具柔性。探索性分析框架是由初始输入,问题探索求解控制,输出数据综合分析等三个模块组成。其中初始输入模块主要完成分析问题背景的初始化设置,探索空间的确定,分析决策目标的确定等等功能。问题探索求解控制模块主要完成基于静态或动态优化控制机制,控制探索过程,以减少探索空间规模的工作。输出数据的综合分析模块完成收集探索计算的结果,综合分析数据,为分析人员提供决策支持,并辅助生成分析报告。