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。     

煤矿井下掘进工作面作业人员生存质量调查信效度研究及影响因素分析

采用SF-36生存质量量表对城郊煤矿井下掘进工作面的273名作业人员进行问卷调查,并采用回归分析确定其主要影响因素。分析结果表明,重测信度系数均大于0.7,显示重测信度较好;分半信度系数为0.7290.7,说明内部一致性分半信度较好;因子累积贡献为81.476%50%,体现此次量表调查具有良好的结构效度;Logistic回归分析发现年龄和工种是影响掘进工作面作业人员生存质量的主要因素,钻眼工和人力推车工是生存质量状况最差的工种。SF-36量表在煤矿井下掘进工作面作业人员生存质量调查中,显示出良好的信效度。     

数据库形式化安全策略模型建模及分析方法

目前数据库形式化安全策略模型存在抽象层次较高、缺乏对数据库状态与约束的充分描述等问题,难以辅助用户发现商用数据库设计中的微小缺陷。提出了一种基于PVS语言的数据库形式化安全策略模型建模和分析方法,该方法较以往模型能够更加贴近实际数据库,应用范围更广,安全属性描述更加完整,描述的模型具有灵活的可扩展性,并且保证了建模与验证的效率。最后,将该方法应用于数据库管理系统BeyonDB的安全策略建模分析中,帮助发现了系统若干设计缺陷,证明了方法的有效性。     

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.     

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.     

Inference control of open relational queries under closed-world semantics based on theorem proving

Relational database systems may serve to evaluate an open query under closed-world semantics. The evaluation returns an explicit output relation complemented with an often implicit statement about the completeness of that relation. The output relation is formed from all those tuples that both fit the format and satisfy the properties expressed in the query. Using first-order logic for specifying formal semantics, the output relation can be seen as a set of (ground) sentences obtained from the query formula by suitable substitutions of free variables by constants. A statement about the completeness of a relation can also explicitly be formalized as a sentence of first-order logic. Inference control for enforcing a confidentiality policy has to inspect and to possibly distort not only the sentences representing the tuples of the output relation but also the completeness sentences. Previously designed and formally verified control procedures employ theorem-proving for such inspections while iteratively considering candidates for those sentences and determining termination conditions, respectively. In this article, we outline an implementation of these control procedures and treat improvements of their runtime efficiency, in particular to overcome shortcomings of the underlying theorem prover, which is repeatedly called with an input comprising a completeness sentence of increasing size. The improvements are obtained by an equivalent rewriting of completeness sentences, exploiting the active domain or introducing new constants for combinations of the original constants, respectively, as well as by optimizing the number of such calls. Besides theoretical complexity considerations, we also present practical evaluations for some examples. These examples include queries that—without control—would return the whole underlying database relations and—with control—can be used for confidentiality-preserving data publishing.     

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。