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.     

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.     

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     

岩石物理横波速度曲线计算技术

横波速度是地震勘探中的重要参数。针对实际生产中缺乏横波速度测井曲线资料，利用经验公式计算精确度不高的问题，通过对横波速度计算理论模型的研究分析，选择Blot-Gassman模型法，利用岩石矿物成分、流体成分、孔隙度及密度等测井曲线进行横波速度测井曲线的计算，并对横波速度计算技术和流程进行研究。在实际工区进行了横波速度曲线计算，计算结果与实测横波吻合程度较高，误差小于10％，该技术在储层和流体识别预测的应用中取得了较好效果。     

SJ—YⅡ—5型高爆速高威力水胶炸药的研制

文章简要分析了我国目前在中硬岩石爆破中工业炸药的使用情况，介绍了山西兴安化学材料厂新研制的一种适用于硬岩爆破的高爆速、高威力水胶炸药新品种，对其性能、爆破效果、经济实用性和安全性等进行了阐述。     

一种改进的交错脉冲解速度模糊方法

研究了脉冲多普勒气象雷达中用于解速度模糊的交错脉冲方法，理论分析了时域脉冲对处理中速度估计公式的局限性，同时对该公式进行了修正。仿真结果表明，改进的交错脉冲方法具有更好的解速度模糊性能，而且易于实时处理。     

Constant thrust programming for a multistage rocket flown in vacuum with a given initial/final thrust-to-weight ratio in an arbitrary stage

The burn time and burnout velocity of a multistage rocket flown vertically in vacuum with constant thrust tangential to the flight path and a prescribed initial/final thrust-to-weight ratio in an arbitrary stage have been determined. The present paper also deals with optimal staging under given conditions of flight.     

建立速度模型的层析成像方法研究

针对目前叠前深度偏移速度模型建立中，全局反演的层析成像方法存在稳定性和走时拾取困难，以及局部反演的偏移速度分析大多存在假设条件过于苛刻等问题，通过分析，提出了利用地震同相辅的多种信息进行层析反演，并在反演中加入富有地质含义的倾角信息以增加反演过程的稳定性和收敛速度，利用类似于叠加速度谱的斜率速度谱来拾取地震同相轴的斜率，抛开了层位反演要求拾取同一同相轴这一实际应用难度很大的条件，使拾取方便，算法稳定。通过理论试算，证明了本方法的有效性。