Preschool children's collective mathematical reasoning during free outdoor play

This paper illustrates how young children (age 1–5) use mathematical properties in collective reasoning during free outdoor play. The analysis of three episodes is presented. The results from the analysis of the argumentation show that the children used a variation of mathematical products and procedures, to challenge, support and drive the reasoning forward. When needed, they utilise concrete materials to illustrate and strengthen their arguments, and as an aid in order to reach conclusions. The children also use abstract social constructs, such as jokes, as part of their reasoning.     

Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning

This paper presents a real-time segmentation algorithm to obtain moving objects from the H.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the H.264 compressed video: motion vectors associated to the macroblocks and decision modes. The algorithm uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way, so the proposed approach works with low level information but manages highly comprehensive linguistic concepts. The performance of the algorithm is improved using dynamic design of fuzzy sets that avoids merge and split problems. Experimental results for several traffic scenes demonstrate the real-time performance and the encouraging results in diverse situations.     

Representation theorems for probability functions satisfying spectrum exchangeability in inductive logic

We prove de Finetti style representation theorems covering the class of all probability functions satisfying spectrum exchangeability in polyadic inductive logic and give an application by characterizing those probability functions satisfying spectrum exchangeability which can be extended to a language with equality whilst still satisfying that property.     

Linguistic quantifiers based on Choquet integrals

The introduction of linguistic quantifiers has provided an important tool to model a large number of issues in intelligent systems. Ying [M.S. Ying, Linguistic quantifiers modeled by Sugeno integrals, Artificial Intelligence 170 (2006) 581–606] recently introduced a new framework for modeling quantifiers in natural languages in which each linguistic quantifier is represented by a family of fuzzy measures, and the truth value of a quantified proposition is evaluated by using Sugeno’s integral. Representing linguistic quantifiers by fuzzy measures, this paper evaluates linguistic quantified propositions by the Choquet integral. Some elegant logical properties of linguistic quantifiers are derived within this approach, including a prenex normal form theorem stronger than that in Ying’s model. In addition, our Choquet integral approach to the evaluation of quantified statements is compared with others, in particular with Ying’s Sugeno integral approach.     

一种多数据融合算法

针对证据理论在数据融合中存在的局限性,提出了一种新的算法,通过实例分析了这种算法的优点,最后指出了该算法存在的不足.     

Ken Kunen: Algebraist

Although better known as a set theorist, Ken Kunen did important work in algebra, particularly in quasigroup theory and loop theory. This paper describes some of this work, especially his use of automated deduction tools, with a lot of attention given to projects done in collaboration with the author.     

On recognizing proportionality: Does the ability to solve missing value proportional problems presuppose the conception of proportional reasoning?

This paper investigates the relationship between the ability of middle school students to solve missing value proportional problems and their facility in differentiating proportional relationships from non-proportional relationships. Students in low- and high-proficiency groups in mathematics took a ratio-and-proportion test involving two typical missing value proportional (MVP) and two recognizing proportionality (RP) problems. The findings revealed that while the students generally performed better on MVP problems than on RP problems, the two groups differed in their performance on MVP problems, but not on RP problems. Moreover, of those students from both the groups who successfully solved the two MVP problems, a significantly greater proportion of students in the high-proficiency group were unsuccessful in solving either of the two RP problems than those in the low-proficiency group. An analysis of performance differences between items within the same student group showed that the effect of differences in the structural components of RP problems to some extent contradicted the previous findings on the effect of differences in the structural components of MVP problems. It is hoped that these findings can shed light on what might be missing in the teaching and learning of proportional reasoning.     

溯源中国硫磺文化 提升化学核心素养*——硫元素的探索之旅

化学史在课堂中的运用越来越广泛,但采用的多是西方化学史,鲜有中国化学史。如何在化学课堂中增强文化自信、提升人文素养？针对这一问题,以人教版新教材必修第二册“硫”的教学为例,开启中国硫磺文化的探索之旅。展开清晰的时间线,梳理各朝代对硫的认识与应用,贯以中国科技兴衰史,在互动、探究、体验中发展学生的科学观念,提升学科核心素养,增强文化自信。     

基于视觉的自主车道路检测技术研究

针对结构化道路检测中基于单一特征的检测易受影响,非结构化道路检测算法对多种类型的非标准道路缺乏适应性的问题,分别提出了一种基于D-S证据理论的多视觉特征融合的车道线检测方法和一种基于增量模糊支持向量机(IFSVM)的非结构化道路在线学习检测方法。选取梯度幅度等检测算子分别设计基本概率分配函数,根据建立的分段线性道路模型进行求解,FSVM分类器通过从前先的检测结果中学习,在耗费少量计算时间与内存空间的情况下,不断再训练以增强分类器的性能。实验结果表明,该算法比单纯利用图像的边缘或颜色等特征进行道路检测具有更高的可靠性,对复杂环境下的道路检测具有较强的鲁棒性和较强的抗干扰能力。     

基于改进自适应加权的多传感器融合监测

针对加注系统多传感器测量数据融合,为满足融合的可靠性与准确性需求,提出了一种改进的自适应加权融合算法。加权融合算法的关键是如何准确判定测量数据权重值,在总结分析当前权重值判定方法优缺点的基础上,将证据理论中的修正证据距离引入测量数据间距离计算,生成融合权重值,完成传感器数据融合。通过一般算例与加注系统典型算例,对所提融合算法进行验证,结果表明算法融合效果较好、鲁棒性强,具有一定的理论意义和较好的工程实用价值。