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.     

燃煤锅炉除尘专用滤料的开发

介绍机械制造厂燃煤锅炉的烟尘特点,分析滤料失效的原因,提出一套针对该工况的滤料解决方案。介绍针对复杂工况条件所选用的纤维种类以及复合面层原料成分配比的确定,最终选用针刺工艺加工并对该新产品的基本性能进行了测试分析。     

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

轻质滤料滤池的试验与研究

轻质滤料滤池是以比水密度略小的滤料为滤床的滤池，通过以净水厂的原水和污水处理厂的二级处理出水为过滤试验对象，所取得的结果表明：下向流轻质滤料滤池对浊度和悬浮固体（SS）的去除率分别可以达到80％和45％，而滤床的水头损失不超过15cm。因此轻质滤料滤池可以以预过滤的形式配置在过滤处理的净水和污水的处理工艺中。     

基于服务器端会话追踪的Web查询服务的研究

在探讨了Web查询服务的典型模型后,论文阐述了服务器端会话追踪机制的实现方式,设计了基于服务器端会话追踪的Web查询服务的典型解决方案。该设计方案可以较为安全地保存和维护客户的上下文信息,可靠地跟踪用户查询所处的状态,有效地实现有状态的Web查询服务。     

以一种新的距离度量作为反馈的相关跟踪方法

基于相关的模板匹配方法在图像跟踪中得到了广泛的应用,但是这种方法的主要缺点是对图像噪声非常敏感,而且由这种方法得出的相关曲面比较平坦。为了有效抑制噪声和局部遮挡对图像的影响,提出用鲁棒统计中的一个值代替相关值作为距离度量。它不是计算两幅图像的对应像素差值,而是计算两幅图像中差别不大的对应像素对的个数。实验证明这样得到的曲面相对　　收稿日期:2003 08 31;　修订日期:2003 10 28作者简介:张桂林(1944 ),男,天津人,教授,博士生导师,主要研究方向为自动识别、人体生物统计特征识别、图像处理算法与系统性能评估等。　　　　　　　要尖锐得多。当上述的距离度量应用于跟踪过程中时,模板的合理更新对跟踪非常重要。基于上述的距离度量方法,提出了一种新的模板更新策略。利用两幅图像中近似像素在整修匹配模板像素中所占的比例大小决定加权系数。这种加权策略可以自适应地根据图像序列的变化选择更新相关模板,同时在一定程度上减小模板漂移的危险。     

用DSP实现多目标实时跟踪

介绍了在 TMS3 2 0 C62 0 3上实现 4个目标的快速跟踪技术。为了提高实时性和精确度 ,采用线性汇编优化实现。1个 3 2 0× 160主窗口的 DSP平均处理时间为 2 m s,3个 60× 60副窗口的 DSP平均处理时间各为 0 .4ms,实现了复杂背景下低对比度目标的快速跟踪。实验结果证明跟踪效果良好 ,解决了以前窗口开不大、跟踪速度慢的问题     

Characteristic Features of the Optimal Processing of the Results of Measurements in the Case of a Random Observation Function

An analysis is made of the characteristic features and problems of the optimal processing of the results of measurements in the case of a random observation function utilizing a nonlinear Kalman filter. A method is proposed for increasing the convergence domain of the filter with additional processing of measurements in the frequency domain.