轻音乐对驾驶疲劳的双向影响

目的本实验探索驾驶负荷累积与轻音乐对驾驶疲劳的影响。方法采用2(驾驶负荷累积)×2(音乐条件)×3(模拟驾驶阶段)混合设计,对32名驾驶员被试进行模拟驾驶实验,采集驾驶员驾驶速度和他们的垂直搜索广度与瞳孔直径。结果第45-60 min时,对于无驾驶负荷累积的被试,轻音乐组车速显著快于无音乐组,轻音乐组垂直搜索广度显著大于无音乐组;对于有驾驶负荷累积的被试,轻音乐组的瞳孔直径小于无音乐组(边缘显著),轻音乐组的车速慢于无音乐组。结论轻音乐对无累积疲劳的驾驶员具有唤醒作用,加快他们的车速,扩大垂直搜索广度,对驾驶绩效具有积极的影响;轻音乐对有累积疲劳的驾驶员会产生催眠作用,缩小瞳孔直径,车速减慢,对驾驶绩效具有消极的影响。     

A primary influence vertex approach to identify driving factors in complex integrated agri-industrial systems – an example from sugarcane supply and processing systems

Integrated agri-industrial systems (IAISs), such as sugarcane supply and processing systems, are complex systems and hence generally difficult to understand and manage. The large number factors in IAISs coupled with the complex interrelationships among the factors make it challenging to identify the points of intervention for improving their overall performance. Several approaches, such as the network theory and the Theory of Constraints have been used to identify important factors in systems with variations in success. This paper demonstrates a primary influence vertex approach for identifying and ranking the factors that drive the performance of IAISs. The approach is based on comprehensive causal network analyses and was tested in four relatively diverse large-scale sugarcane milling operations in South Africa. Results from the analyses were found to be consistent with the literature and external knowledge of the milling areas as at the time of the study. It is concluded that the approach can proffer a sound basis from which deeper rooted problems in systems can be identified on an ongoing basis. It is, however, recommended that the approach should be systematically compared with other relevant methods that are used to analyse complex systems.     

基于CFD的新型风幕控尘装置的模拟研究及其应用

针对传统风幕控尘装置设备多、空间小、掘进机移动不便等诸多不足之处,⌒进行了优化设计。为确保新型风幕控尘装置的实际应用效果,指导现场防尘系统设计,确定抽出式风机风筒安设位置,依(山西某矿掘进巷道工作面1:1建立了物理几何模型,并利用计算流体动力学(CFD)进行模拟。根(湍流模型特性及流体运动特点,选取拉格朗日法离散相模型对掘进巷道粉尘浓度分布进行了模拟分析并进行现场实践。结果显示,所选物理几何模型参数设置合理,拟合精度达到预测要求;加装新型风幕控尘装置前后,粉尘浓度下降对比明显;距底板2.1 m处安设抽出式风机风筒时,系统降尘效果显著。     

船用指针式仪表自动识别方法研究

指针式仪表的自动识别为船舶设备的实时监控和信息化管理提供了有效的技术手段。本文通过计算机视觉技术对指针式表盘自动判读方法进行了研究。实现了对多种指针式仪表的同时识别,识别过程分为表盘分割、刻度识别、指针识别和仪表类型识别等几个部分,运用中心投影法和图集分类比较法等确定了仪表刻度、指针位置和仪表类别,实现了船用指针式仪表示值的自动识别,并通过试验和误差分析验证了识别方法的有效性。     

基于机器视觉的某种弹弹体硬度检测技术研究

目的 解决某种弹弹体硬度检测过程中人工读取硬度圆直径存在的问题。方法 应用材料的布氏硬度检测原理,设计基于机器视觉的某种弹弹体硬度检测装置,并制定某种弹弹体硬度的视觉检测算法。根据所提出的算法应用Maltlab实现对某种弹弹体硬度圆特征的提取和直径的计算。结果 通过T检验法对所提出的机器视觉检验方法与人工检测的结果进行对比分析,其结果为2种检测结果无差异性。结论 本文所设计的机器视觉检测装置和提出的视觉检测算法的具有较高的可靠性和正确性,可以应用于某种弹弹体的硬度检测。     

变频调速技术在刨煤机成套开采系统中的应用

介绍了刨煤机成套开采系统的组成及变频调速技术在该系统中的应用。变频调整技术的应用提高了传动系统的调速效率,使得传动系统能够实现无级调速,降低了刨煤机成套开采系统在启动时传动系统承受的振动载荷,解决了刨头牵引电动机因频繁启动、换向而发热的缺陷,实现了真正意义上的"软启动",提高了刨煤机成套开采系统的传动可靠性和工作安全性。     

基于机器视觉的高密度电路板缺陷检测系统

为减少高密度电路板的缺陷误报率,研究一种新型自动光学检测系统(AOI);系统采用自行研制的多色LED照明系统,利用机器视觉获取被测PCB的图像,通过图像处理软件系统快速准确地识别出各种缺陷;系统利用获取的彩色图像信息,根据各种缺陷的特征信息不同,采用OPENCV对各种缺陷的检测算法进行改进,使得系统性能有很大改进;对30块同类HDI型PCB的36300个检测点进行测试,测试结果证明,系统PCB缺陷的检出率高达99.87%,误报率只有0.32%。     

基于多目视觉的变形钢板三维测量方法

提出了一种使用4个相机测量变形钢板三维形状的方法;在没有纹理的钢板上画一些点,使用4个相机同时拍摄钢板;利用边缘检测算法找出钢板的边缘,利用特征点提取算法提取出4个图像中钢板上的特征点,并找到4个图像上精确的特征点匹配关系,然后测量出这些特征点的三维点;最后,以这些三维点为种子点向外区域增长,从而得到钢板的三维形状;实验对变形钢板进行三维测量,得到了钢板的精确的三维形状,结果验证了该方法的有效性和可行性。     

案例驱动下数据结构教材的编写

介绍数据结构的基本概念,讨论对数据结构课程的认知,提出教材编写过程中的几个要点,强调案例驱动教学模式在教材编写中的重要性,从而形成教材自身的特色。     

Orthogonal variant moments features in image analysis

Moments are statistical measures used to obtain relevant information about a certain object under study (e.g., signals, images or waveforms), e.g., to describe the shape of an object to be recognized by a pattern recognition system. Invariant moments (e.g., the Hu invariant set) are a special kind of these statistical measures designed to remain constant after some transformations, such as object rotation, scaling, translation, or image illumination changes, in order to, e.g., improve the reliability of a pattern recognition system. The classical moment invariants methodology is based on the determination of a set of transformations (or perturbations) for which the system must remain unaltered. Although very well established, the classical moment invariants theory has been mainly used for processing single static images (i.e. snapshots) and the use of image moments to analyze images sequences or video, from a dynamic point of view, has not been sufficiently explored and is a subject of much interest nowadays. In this paper, we propose the use of variant moments as an alternative to the classical approach. This approach presents clear differences compared to the classical moment invariants approach, that in specific domains have important advantages. The difference between the classical invariant and the proposed variant approach is mainly (but not solely) conceptual: invariants are sensitive to any image change or perturbation for which they are not invariant, so any unexpected perturbation will affect the measurements (i.e. is subject to uncertainty); on the contrary, a variant moment is designed to be sensitive to a specific perturbation, i.e., to measure a transformation, not to be invariant to it, and thus if the specific perturbation occurs it will be measured; hence any unexpected disturbance will not affect the objective of the measurement confronting thus uncertainty. Furthermore, given the fact that the proposed variant moments are orthogonal (i.e. uncorrelated) it is possible to considerably reduce the total inherent uncertainty. The presented approach has been applied to interesting open problems in computer vision such as shape analysis, image segmentation, tracking object deformations and object motion tracking, obtaining encouraging results and proving the effectiveness of the proposed approach.