Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

A new family of proximity graphs: Class cover catch digraphs

Motivated by issues in machine learning and statistical pattern classification, we investigate a class cover problem (CCP) with an associated family of directed graphs—class cover catch digraphs (CCCDs). CCCDs are a special case of catch digraphs. Solving the underlying CCP is equivalent to finding a smallest cardinality dominating set for the associated CCCD, which in turn provides regularization for statistical pattern classification. Some relevant properties of CCCDs are studied and a characterization of a family of CCCDs is given.     

一种新型彩色三维光学成像系统

提出一种新型三维彩色光学数字成像系统。此系统利用投影结构光对现实世界中的物体进行数字化，同时得到对应的彩色纹理。详细介绍了系统的硬件设计和软件体系结构设计，得到物体彩色纹理的两种不同方法；直接获取和从编码条纹中提取，给出了用该系统得到的实验结果并简单评价了系统的性能。此系统在反求工程、影视制作、三维游戏制作、医学应用等方面有远大的应用前景。     

基于CCD图像的火灾空间定位方法

大空间中火源的空间位置的定位,一直是火灾自动探测与自动扑救中的难点。研究了一种利用单一CCD摄像头进行火灾自动空间定位的方法。根据计算机视觉原理,利用固定在自动消防水炮末端的CCD摄像头随水炮旋转扫描时的角度、位移变化,将CCD摄像头在不同位置所拍摄的图像中火源图像坐标和火源的空间坐标建立联系,从而实现了火源空间位置的自动定位。     

风力发电机组变速恒频控制系统研究

全面介绍了一种最新应用于风力发电中的新型电机—无刷双馈电机，并分析了这种新型电机作变速恒频运行的原理并对这种电机进行了动态特性仿真研究，给出了形式简洁的控制方程和易于实现的控制方案。     

Color Zone Map in Peripheral Vision at Various Illuminance Levels

We measured the entire region of mesopic and photopic vision to determine the color zone covering the visual field with unique red, yellow, green, and blue hue components. Eight kinds of test stimuli in the natural color system (NCS) color notation system were used. These stimuli were presented at horizontal and vertical meridians, and at meridians inclined at 45° angles. The illuminance level was set at six levels: 0.01 lx-1000 lx. The evaluation method measured chromatic, white, and black components as well as the hue component of the stimuli. Results show that the color zone of the retina extended further into the periphery with increasing illuminance; the response of opponent colors y-b was shown to be greater than that of the opponent colors r-g.     

机器人头部的视觉跟踪系统研究

对运动目标进行识别和跟踪是机器人视觉的一项关键技术。提出了一种可以快速跟踪运动目标的系统设计方案,采用了双计算机处理和Memolink通信方式的机器人控制结构,以图像处理为基础,在图像经过校正之后,通过区域分割和目标识别两个步骤来确定目标的位置,并控制机器人对目标进行跟踪。实验表明,该方法具有较高的速度和准确性。     

浅谈防空夜视装备的发展

针对我军现代夜间反空袭作战的制约瓶颈——缺乏夜视装备，提出在预警领域采用被动红外周视扫描系统，在先进的火控领域采用制冷式红外热成像系统．在老式的防空火控系统上利用微光和非制冷红外技术进行改造的方案比较符合我国国情，也是比较现实和可行的。     

Non-linearity of the interactions between bottom-up and top-down signals in multistable visual perception

Summary Both bottom-up sensory information and top-down influences contribute to the perception processes. We studied the perceptual alternations of a multistable ambiguous pattern. We observed that it is possible to interfere on the process of the perception alternance by means of subliminal visual stimuli, which either contrast or second the previous perception. We investigated also the effect of the top-down volitional factor on the perceptual alternation. By using a combination of such top-down factor and bottom-up stimulation, we ascertained that a non-linear type of interaction occurs between the two above factors. Paper presented at the International Workshop ?Fluctuations in Physics and Biology: Stochastic Resonance, Signal Processing and Related Phenomena?, Elba, 5–10 June 1994.     

基于机器视觉的离散傅里叶变换目标识别方法

提出了一种基于机器视觉与离散傅里叶变换的目标特征识别方法。利用计算机图像技术采集和处理图像信号;利用离散的傅里叶变换对图像数据提取特征,能够更好的辨别数据细节,从而可通过图像的比对来实现目标的识别。该方法在对实际的静止图像进行处理与计算后,能够很好的对图像的细节变化进行识别。