Leveraging industrial statistics in the data revolution: The Youden Memorial Address at the 63rd Annual Fall Technical Conference

We are in the midst of a “Data Revolution” that is transforming our economy. This revolution is as large and profound as other major economic shifts from the introduction of the printing press to the Industrial Revolution. In this article, we compare the development of the field of Industrial Statistics as an outgrowth of the Machine Age to the development of the field of Data Science as an outgrowth of the Information Age. It is shown how the knowledge, skills, and abilities required for “Data Scientists” have evolved to support companies as they try to differentiate themselves in the Information Age. It is discussed how the unique skills that Industrial Statisticians possess can provide a transformative advantage to Data Scientists working in the Information Age. Advice is given on how to leverage Industrial Statistics in the midst of the Data Revolution so that we ethically and responsibly implement the tools of Data Science, address important problems, and inclusively educate future generations.     

中国大学生创造性4C认知量表修订

目的对创造性4C认知量表(CC4CS)在中国大学生中进行修订,以便探讨创造性4C理论在中国本土文化中的适用性。方法从在线大学生QQ群中招募全国各地3 360名在校大学生为被试,填写CC4CS中文版初测量表,分析其信效度。结果 (1)各项目的区分度与鉴别性较好(t=14.01~34.77,r=0.31~0.55,P均0.001)。(2)经探索性因子分析,得到与原量表一致的创造性4C结构,累积方差解释率为55.22%。(3)总量表Cronbachα系数为0.85,重测信度为0.88,各分量表的α系数在0.72~0.82之间,重测信度在0.81~0.90之间;与Lawdsei认知创造力量表和Rudowicz-Hui创造力概念调查量表的关联效度分别为0.67、0.77;各分量表与总分以及各分量表之间的相关分别在0.53~0.74、0.10~0.60之间,结构效度良好。结论 CC4CS中文版具有较好的心理测量学指标,适用于在中国文化背景下大学生的创造性4C认知测量。     

灭火器的定位和有效性辨识研究

智慧消防是智慧城市建设的重要组成部分，在消防工作创新发展中发挥重要作用。灭火器作为扑救初期火灾的最普遍、最便捷和最广泛使用的灭火设施，在初期火灾的扑救和火灾防控中发挥重要的作用，其有效性和完好性是扑救初期火灾的必要条件。基于物联网及大数据的优势，建立消防灭火设施的定位与有效性辨识系统，并介绍系统的关键技术、网络架构、技术特征。此系统可对灭火器等消防灭火设施的伺应状态、完好性、有效性等功能特性进行跟踪巡检和辨识，以实现对灭火器的实时监控和智能化管理，促进消防设施建设的完善和优化，增强灭火系统的可靠性，充分发挥智慧消防技术在智慧城市建设中的优势。     

垃圾填埋场渗滤液回灌效果的理论研究

基于前人提出的垃圾填埋场渗滤波渗流模型，通过试验初步提出了评价回灌效果的指标和回灌有效期的概念，并分别考察了回灌水质、渗流参数及填埋深度对渗滤液中污染物浓度、微生物浓度和垃圾土中有机质溶解及降解的影响。分析结果表明，回灌能促进渗滤液中COD浓度的降低并加快垃圾土中有机质的降解；提高垃圾土的溶解速度，有利于减少垃圾土的有机质含量，同时不影响COD浓度的稳定；在相同回灌水质下，填埋越深则回灌的效果越不明显。     

海洋环境下混凝土中钢筋的防腐蚀设计

海洋环境下钢筋的锈蚀是影响混凝土结构耐久性的重要原因。通过简单分析海洋环境混凝土中钢筋锈蚀机理，提出了采用钢筋阻锈剂、环氧树脂涂层钢筋、热浸镀锌钢筋、不锈钢钢筋、纤维塑料筋，外加电流阴极保护法和牺牲阳极保护法等钢筋的防腐蚀方法。并综合分析比较了这些方法的工程适用性。     

引入参照基准的使用后评价方法及其在照明改造工程中的应用

使用后评价(POE)作为国际上较为成熟的建筑评价技术,在我国照明工程实施过程中的应用和普及程度不足。照明改造工程在建筑工程类型中具有周期短、见效快的特点,更适合开展POE。本文提出了适用于照明改造工程的“引入参照基准的使用后评价方法”(POE-R),并以某校园照明改造工程为实际案例,分别在改造前后对目标建筑和参照基准建筑进行了照明参数的实地测量和使用者的POE-R问卷调查。数据分析结果表明,该照明改造工程显著提升了光环境质量,POE-R可以消除干扰变量的影响,提高POE的外部有效性和整体评价效力。     

CCHP系统综合评价指标体系的信度与效度验证

基于冷热电联供(CCHP)系统初始综合评价指标体系,结合算例,对不同配置方案下初始综合评价指标体系进行信度与效度验证,获得了CCHP系统综合评价指标体系。     

Development and validation of a scale to capture social desirability in food safety culture

The evaluation of food safety culture in a food company is influenced by human factors such as employees' tendency to respond to social desirability – a reflection of respondents' tendency to answer questions in a manner that will be viewed favorably by others. Building on previous research a self-assessment scale consisting of 18-statements (FSDRS) was developed to capture desirable responding in food safety. Statistical analyses of data collected from 816 North-American food manufacturing professionals revealed that a shortened 14-item version of the FSDRS scale provides a reliable and valid measurement of the extent to which employees deceive themselves. It is concluded that the proposed FSDRS will enrich food safety culture measurement and food safety performance.     

Constrained latent variable model predictive control for trajectory tracking and economic optimization in batch processes

A constrained latent variable model predictive control (LV-MPC) technique is proposed for trajectory tracking and economic optimization in batch processes. The controller allows the incorporation of constraints on the process variables and is designed on the basis of multi-way principal component analysis (MPCA) of a batch data array rearranged by means of a regularized batch-wise unfolding. The main advantages of LV-MPC over other MPC techniques are: (i) requirements for the dataset are rather modest (only around 10–20 batch runs are necessary), (ii) nonlinear processes can efficiently be handled algebraically through MPCA models, and (iii) the tuning procedure is simple. The LV-MPC for tracking is tested through a benchmark process used in previous LV-MPC formulations. The extension to economic LV-MPC includes an economic cost and it is based on model and trajectory updating from batch to batch to drive the process to the economic optimal region. A data-driven model validity indicator is used to ensure the prediction’s validity while the economic cost drives the process to regions with higher profit. This technique is validated through simulations in a case study.