基于认识化学正向价值的教学实践——以“二氧化碳*”为例

模拟大型科普求真类节目《是真的吗？》创设学习氛围;通过基于生活生产实际的“日常灭火可否用N₂代替CO₂”“深海捕获CO₂可否调控温室效应”“石油采矿业中,向油井下注射1吨CO₂可否增产原油3~5吨”“用石灰水可否保鲜鸡蛋”等4个核心问题及3个真假难辨的小问题,引导学生从化学的正向视角深刻认识二氧化碳的性质;利用移动磁贴板设计板书,引导学生经历并建构结构化知识体系。     

关联规则增量式更新的改进算法

关联规则是数据挖掘中的重要研究内容之一，对在事务数据库不变，只对最小支持度和最小可信度进行改变的情况下，针对关联规则的维护问题，设计了一个增量式更新的改进算法AIUA。     

惯例复制与知识转移:作用机制的权变条件研究

针对惯例复制过程中与外部情景难以匹配的复制困境,分析了常规惯例复制和柔性惯例复制对知识转移的单独以及联合作用的关系悖论,对比分析作用机制在网络闭合性和环境不确定性约束下的权变性影响。以研发密集型企业为对象,运用多元回归分析进行实证检验。结果表明:网络闭合性和环境不确定性是惯例复制对知识转移的单独以及联合作用的权变条件;网络闭合性强化了常规惯例复制机制的促进作用,但限制了柔性惯例复制机制的效能发挥;环境不确定性削弱了常规惯例复制机制的促进作用,对柔性惯例复制机制的作用效果不显著;网络闭合性低或环境不确定性低时,两种惯例复制机制的联合作用相互补充,而网络闭合性高或环境不确定性高时,两种惯例复制机制相互替代。研究结论有助于揭示惯例复制的权变作用,对提升技术创新网络的知识转移效率具有重要意义。     

基于QUEST定量检测1H MRS大脑代谢物的研究

利用jMRUI时域分析软件模拟先验知识基础集定量检测¹H MRS大脑代谢物. 通过模拟短TE=28 ms的¹H MRS的多种代谢物基础集,经HLSVD奇异值分解滤除残余水峰,将先验知识应用在QUEST算法上对¹H MRS大脑代谢物信号进行定量估计. 结果显示, 基于QUEST能有效获得¹H MRS大脑代谢物的估计浓度. 表明引用先验知识基础集进行¹H MRS定量分析可克服短TE时谱线复杂和波峰重叠峰等问题,极大地提取代谢物的信息.     

大一学生化学实验室安全基础知识调查研究*

为考察大一学生化学实验室安全基础知识,对天津理工大学化学化工学院大一学生警示标识、危险化学品性质、废弃物处理及意外处置等安全知识进行问卷调查。结果表明:60.4%的学生将易燃标识与氧化剂标识混淆;在危险化学品性质和酸/碱撒漏处理方面有待加强。基于以上结果,在后续安全教育过程中,普及GHS标识及MSDS,对相关知识进行针对性的查漏补缺;充分利用线上资源,弥补线下教育因时间有限、容量有限导致的不足。     

Smoothness in Bayesian Non-parametric Regression with Wavelets

Consider the classical nonparametric regression problem y_i = f(t_i) + _ii = 1,...,n where t_i = i/n, and _i are i.i.d. zero mean normal with variance ². The aim is to estimate the true function f which is assumed to belong to the smoothness class described by the Besov space B _pq ^q . These are functions belonging to L_p with derivatives up to order s, in L_p sense. The parameter q controls a further finer degree of smoothness. In a Bayesian setting, a prior on B _pq ^q is chosen following Abramovich, Sapatinas and Silverman (1998). We show that the optimal Bayesian estimator of f is then also a.s. in B _pq ^q if the loss function is chosen to be the Besov norm of B _pq ^q . Because it is impossible to compute this optimal Bayesian estimator analytically, we propose a stochastic algorithm based on an approximation of the Bayesian risk and simulated annealing. Some simulations are presented to show that the algorithm performs well and that the new estimator is competitive when compared to the more standard posterior mean.     

On defining OLAP formulations

^** Email: vutsinas{at}upatras.gr Recently there has been increasing interest in On Line AnalyticalProcessing (OLAP) to satisfy the organizational needs of high-levelinformation delivery and advanced data analysis. The actualapplication of OLAP tools involves the use of various functions,such as the common drilling down and slicing and dicing. Usuallyeach particular OLAP function is comprehensive and intuitive.However, sophisticated use of OLAP tools requires complicatedcombinations of different OLAP functions that are not straight-forwardfor end users or designers. In this paper we attempt to enumerateand formally define OLAP functions by defining a new OLAP modelthat provides a broader view of OLAP. We demonstrate the expressiveadequacy of the new OLAP model with application examples.     

Schopenhauer's Prolegomenon to Fuzziness

Prolegomenon means something said in advance of something else. In this study, we posit that part of the work by Arthur Schopenhauer (1788–1860) can be thought of as a prolegomenon to the existing concept of fuzziness. His epistemic framework offers a comprehensive and surprisingly modern framework to study individual decision making and suggests a bridgeway from the Kantian program into the concept of fuzziness, which may have had its second prolegomenon in the work by Frege, Russell, Wittgenstein, Peirce and Black. In this context, Zadeh's seminal contribution can be regarded as the logical consequence of the Kant-Schopenhauer representation framework.     

A Novel Rule Induction Algorithm

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