Utilizing sensor data to model students’ creativity in a digital environment

While creativity is essential for developing students’ broad expertise in Science, Technology, Engineering, and Math (STEM) fields, many students struggle with various aspects of being creative. Digital technologies have the unique opportunity to support the creative process by (1) recognizing elements of students’ creativity, such as when creativity is lacking (modeling step), and (2) providing tailored scaffolding based on that information (intervention step). However, to date little work exists on either of these aspects. Here, we focus on the modeling step. Specifically, we explore the utility of various sensing devices, including an eye tracker, a skin conductance bracelet, and an EEG sensor, for modeling creativity during an educational activity, namely geometry proof generation. We found reliable differences in sensor features characterizing low vs. high creativity students. We then applied machine learning to build classifiers that achieved good accuracy in distinguishing these two student groups, providing evidence that sensor features are valuable for modeling creativity.     

薄膜微型电源

介绍了新型的薄膜微型电源的工作原理、结构及制造工艺。     

Porosity distribution in highly compressible cake: Experimental and theoretical verification of the dense skin

The rate of filtration and the water content of cake are influenced by the existence of a dense skin in a highly compressible cake. The phenomenon of the dense skin has been rarely studied, and its existence has not been verified experimentally. In this study, the porosity variation in a very compressible cake is measured by using a new experimental apparatus, and with this the existence of dense skin has been established experimentally. ‘Unified theory on solid-liquid separation’, a recently developed theory, is utilized for calculating the porosity variation in a very compressible cake.     

冷中间包衬对铸坯皮下气泡的影响

对铸坯产生皮下气泡的原因进行了调查和分析。认为中间包绝热板村中的有机挥发物和残余水分是铸坯产生皮下气泡的主要原因。从中间包绝热板的配方、制造技术和装砌等方面采取改进措施，可有效减少铸坯皮下气泡。     

雕塑创作中材质肌理的运用

主要分析了材质肌理在雕塑创作中的运用，通过我对泥、木、石、金属及其肌理表现的深层次的认识与分析，结合许多实例，来说明材质肌理在雕塑创作中的重要性。     

Face detection based on skin color likelihood

We propose a face detection method based on skin color likelihood via a boosting algorithm which emphasizes skin color information while deemphasizing non-skin color information. A stochastic model is adapted to compute the similarity between a color region and the skin color. Both Haar-like features and Local Binary Pattern (LBP) features are utilized to build a cascaded classifier. The boosted classifier is implemented based on skin color emphasis to localize the face region from a color image. Based on our experiments, the proposed method shows good tolerance to face pose variation and complex background with significant improvements over classical boosting-based classifiers in terms of total error rate performance.     

综合肤色模型和多模板匹配增强Adaboost人耳检测

为克服传统的Adaboost算法出现的样本训练时间过长、过于依赖样本质量等问题,在训练不足及初始人耳定位不好的情况下,引入YCbCr肤色模型和多模板匹配技术策略对人耳进行精确定位。实验表明,改进后的人耳检测性能得到较大的提高,对动、静态人耳均能达到准确定位和检测的效果,算法的鲁棒性较好。     

基于参数查找表的肤色检测算法

针对现有模型对肤色空间刻画的不足,提出了一种基于参数查找表的肤色检测算法。该方法将肤色和非肤色看作两类模式,通过在YCbCr颜色空间统计,计算样本在不同色度下沿亮度的概率分布,分类采用贝叶斯判别规则,查找表用于存储模型参数,实现了快速查找和计算。实验中,从像素样本分类和彩色图片分割两个方面对算法的检测性能进行对比,说明其有较高的检测率和较强的鲁棒性。     

基于肤色特征的人脸检测算法的研究

通过对比面部识别技术的各种算法,本文重点研究了基于肤色特征的人脸检测算法。首先通过两种方法实现人脸的区域分割：基于相似度的方法和基于皮肤区域、头发区域的方法。前者通过相似度计算、二值化之后标记出人脸区域,后者利用颜色来检测人脸区域。人脸区域检测完毕之后再对其进行人脸特征的标注,最终实现面部检测。     

肤色模型的面部肤色区域提取

面部肤色区域提取是数字图像处理和模式识别领域的研究热点。研究了采用OpenCV分类器实现人脸检测的方法,并基于肤色区域的聚类特性,构造出一个肤色模型查找表,进而实现了面部肤色区域的提取。实验证明,这种方法具有良好的适应性和实时性。