基于微流控的人卵母细胞特性检测

人的卵母细胞特性的研究对于临床医学具有重要意义,可以通过卵母细胞的大小对其活性进行研究。采用微流控平台与MATLAB算法相结合的方法,利用微流控器件的沟道对卵母细胞进行挤压,由于卵母细胞的活性不同对于挤压的反应也不同,活性越好的卵母细胞通过沟道时变形性越好,经检测卵母细胞有很好的活性;拍摄卵母细胞发生形变与卵母细胞通过沟道的视频,利用MATLAB程序进行图像处理得到卵母细胞的大小,测得卵母细胞的直径约为170μm。这种方法有别于传统方法,在一定程度上使用了算法识别,提高了卵母细胞分析统计的准确度,提升了工作效率。由于人的卵母细胞比较珍贵,只进行了初期实验研究,证明此方法确实可行。     

Zero-Sequence Voltage-based Method for Determination and Classification of Unloaded Overhead Line Operating Conditions at the Moment of Energization

Overhead line energization can be performed under normal or faulty conditions. The latter indicates an occurrence of a fault along the line that exists at the moment of energization. This can lead to significant over-voltages that could endanger proper line operation. The issue gets more complex to protective devices when it comes to high-resistance faults, which impair the ability of relays to react promptly and accurately. Consequently, installation of additional detection devices becomes necessary. This paper proposes a novel method that properly detects and classifies line operating conditions at the moment of energization. The method is designed to be useful for utilities and it can be considered as a low-cost, fast, and accurate detection and classification approach, suitable for dealing with both low-resistance and high-resistance faults. Through comprehensive mathematical modeling it was found that both normal and faulty conditions during line energization are accompanied by the zero-sequence voltages of specific characteristics. The differences between zero voltage sequences are reflected in harmonic content, magnitudes of dominant frequencies, and their phase angles in regard to supply voltage. These findings are taken as the method's detection and classification criteria. The validity of the proposed model is verified by simulations and by field measurements.     

Thermal and rheological effects in a classical Graetz problem using a nonlinear Robertson-Stiff fluid model

The present article elaborates the Graetz problem for the Robertson-Stiff fluid model with imposed iso-thermal conditions. The closed-form expression of Robertson-Stiff fluid velocity is obtained. Employing the classical separation of variables approach, the energy equation of the said problem is reduced into an eigenvalue problem. The solution of the eigenvalue problem is developed numerically via the MATLAB built-in algorithm BVP4C. The constants appearing in series solutions are computed by Simpson's rule. The special case of this analysis with appropriate scaling is also applicable for the Bingham, power-law, and Newtonian fluid models. The impact of the dissipation function on Nusselt numbers and mean temperature is also considered. The pictorial representation of average temp7erature and Nusselt number are discussed in the presence of the plug radius, power-law index, and Brinkman number. It is observed that the presence of the plug radius and power-law index delay the prevalence of fully developed conditions for the Nusselt number. Moreover, the local Nusselt number for channel confinement attains higher values as compared with tube confinement. The present investigation has numerous applications in the field of engineering, nanotechnology, biomedical sciences, and development of several thermal types of equipment or microfluidic devices.     

煤矿瓦斯移动抽排系统的智能控制

煤矿井下开采新的工作面之前,为了预防瓦斯突出,必须“先抽后采”。抽排系统的抽排泵在启动及运行过程中,需及时调节排放流量以保证出口瓦斯量在允许的范围内。为此,建立了一个智能控制系统,进行了MATLAB仿真,达到了预期的控制效果。     

Visual Basic与MATLAB的接口技术

VisualBasic开发用户界面简单方便 ,MATLAB是高性能的科学计算软件 ,为充分发挥各自优势 ,利用ActiveX自动化和DDE技术实现了VisualBasic与MATLAB的链接 ,并给出具体示例和详细代码 ,得到了高效便捷、功能强大的编程方法     

瓦斯涌出量灰色-RBF网络模型的建立与应用

为了减少瓦斯事故给煤矿生产带来的损失,本文在灰色模型预测煤矿瓦斯涌出量的基础上,结合神经网络理论,构建了灰色-RBF网络模型,充分利用灰色模型的"小样本、贫信息"的预测特点及RBF神经网络自学习、自适应能力特点。首先使用灰色模型对瓦斯涌出量进行初步预测,然后建立RBF网络模型进行再次预测,得到瓦斯涌出量的最终预测值;RBF网络模型的训练和预测计算用MATLAB软件完成。通过对安徽省某矿瓦斯涌出量的预测结果对比,灰色-RBF网络模型的预测误差分别为0.325和0.221,灰色模型预测误差为2.51和2.45,结果表明灰色-RBF网络模型预测明显高于单一灰色模型预测的预测精度。为煤矿瓦斯涌出量预测提供一种预测精度高的方法。     

掘进机截割头动载荷变化规律的研究

掘进机截割岩石时,需要根据不同的岩层地质条件选择合适的截割头,并调整截割参数。在MATLAB中进行动态仿真模拟,深入研究截割头载荷的变化规律。结果表明,截割头载荷随着截割头截深、截割转速、摆速或钻进速度和截割岩石硬度的不同而发生变化。为截割头的选择和截割参数的调整提供了可靠的依据。     

基于MATLAB的胶结充填材料BP神经网络质量模型

用BP神经网络的方法建立胶结充填材料质量与主要影响因素胶结剂，浓度，骨料，温度和粒级的关系模型，并用MATLAB实现对该模型的训练和系统仿真，不论用什么样的骨料和胶结剂，只要用一定的试验数据对模型进行训练，然后对拟采用的胶结充填材料进行仿真，均可得到较为可靠的目标参数。     

MATLAB编程实现ISODATA算法

ISODATA算法是一种经典的聚类算法，而MATIAB则是一种现行广泛使用的数学运算工具。首先介绍了ISODATA算法，然后详细说明了使用MATLAB语言实现ISODATA算法的过程。     

基于MATLAB遗传神经网络的实现及其在磨机故障诊断中的应用

神经网络理论的研究是从1943年研究二维神经元阈值模型开始的，经历了半个世纪的曲折发展，上个世纪80年代神经网络研究进入了第二个高潮期。正是此时，开始了神经网络在故障诊断领域中的应用研究，人工神经网络诊断技术是属于人工智能范畴的，基于神经网络的诊断系统具有知识表达，推理及很强的学习能力，神经网络在知识的表达方法上有其独特的一面、它把知队变成为网络的权值和阈值，并分布存储在整个神经网络之中。