中国楷膜藻科(红藻门)新记录——掌状美叶藻

掌状美叶藻(Callophyllis palmata Yamada)分布于日本,北美洲西海岸等地,最近发现在中国大连广鹿岛有分布,属于我国新记录种.掌状美叶藻属于红藻门(Rhodophyta)楷膜藻科(Kallymeniaceae)美叶藻属(Callophyllis),主要特点为藻体颜色鲜红,生有根丝细胞.该种与贴生美叶藻C.adnata区别在于直立生长,分枝顶端呈二叉状凹陷;与附着美叶藻C.adhaerens区别在于分枝幅度较宽,可达10 mm以上.     

层次分析法在雷达模拟器标绘评估中的应用

根据国际海事组织关于雷达模拟器标绘评估的要求,分析了目前标绘评估方法的不足和层次分析法在评估中的适用性.提出了标绘评估标准的层次结构和基于层次分析法的标绘评估方法,实际应用表明,该方法能对雷达模拟器标绘训练进行比较客观的评估,在一定程度上弱化了评估过程中主观判断的影响.     

基于飞思卡尔的汽车轮毂跳动量测量系统研究

详细阐述了汽车轮毂跳动量测量机控制系统的设计方案及基本工作原理,根据控制系统要求对系统的外设接口进行了分配,通过对MC9S12DP256的编程,实现了对步进电机的精确控制,完成了测头的启停以及在规定预压量内的上下、水平方向上的移动。     

基于GIS技术的城镇建设用地适宜性评价研究——以嘉兴市凤桥镇为例

以GIS为主要技术平台,从建设经济性因子和自然生态因子两个方面进行城镇建设用地适宜性评价研究,探讨了评价方法与步骤,并以嘉兴市凤桥镇为案例进行实证研究.     

底水油藏水侵量计算新方法

针对底水油藏的开发,在缺乏试井数据的情况下采用常规油藏物质平衡法以及试井分析方法均难以确定水驱控制储量,进而无法获得水体参数和特征来计算油田的水侵量。为了更加准确的预测水驱油田水侵量,本文结合生产动态资料,选择符合的水驱特征曲线计算水驱控制储量。在此基础上,考虑油环油、溶解气、水体等因素,建立物质平衡方程,通过亏空体积曲线法计算获得水侵量。利用Fetkvoitch拟稳态模型,采用试错法,优化计算水体体积和水侵系数,保证Fetkvoitch拟稳态模型求解的水侵量和亏空体积曲线法求解的水侵量最接近,得到最优的水体体积和水侵系数对未来生产动态中水侵量进行预测。运用油藏数值模拟软件建立的模型与本文提出两种的计算方法拟合结果对比可知的水体体积的误差为2.6%、水侵指数的误差为2.2%,计算结果准确,为底水油藏计算水侵量提供了可靠的依据,并为预测水侵量提供了新的方法。     

考虑压敏效应的低渗透油藏CO2辅助重力驱合理配产方法

高倾角低渗透油藏在进行水驱开发时,在油藏高部位存在大量剩余油,采收率较低,采用CO2辅助重力驱,可以充分利用高倾角的地质特征,有效提高该类油藏的采出程度。但是由于CO2对原油物性影响要远大于水对原油物性的影响,CO2驱替过程中流体的渗流过程更加复杂,因此有必要对低渗透油藏CO2重力驱合理配产优化进行研究。首先,依据油藏中任意一点压力与最小混相压力的关系,分别建立了考虑压敏效应的低渗透油藏CO2重力驱混相和非混相模型;其次,运用Python对模型进行求解,同时分析了压敏系数、地层倾角、注采井距和注气速度对油藏配产的影响;最后,结合现有工作制度法和增产倍数法,对比本模型计算结果,运用tNavigtor软件对三种方法进行采收率预测。研究结果表明：运用本文方法对油藏进行合理配产具有较好的开发效果,油藏采收率相对较高,研究成果对该类低渗油藏的开发具有较好的借鉴意义。     

Pulsar/CNS integrated navigation based on federated UKF

In order to improve the autonomous navigation capability of satellite, a pulsar/CNS (celestial navigation system) integrated navigation method based on federated unscented Kalman filter (UKF) is proposed. The celestial navigation is a mature and stable navigation method. However, its position determination performance is not satisfied due to the low accuracy of horizon sensor. Single pulsar navigation is a new navigation method, which can provide highly accurate range measurements. The major drawback of single pulsar navigation is that the system is completely unobservable. As two methods are complementary to each other, the federated UKF is used here for fusing the navigation data from single pulsar navigation and CNS. Compared to the traditional celestial navigation method and single pulsar navigation, the integrated navigation method can provide better navigation performance. The simulation results demonstrate the feasibility and effectiveness of the navigation method.     

DDFS spurious signals due to amplitude quantization in absence of phase-accumulator truncation

Spurious signals in direct digital frequency synthesizers (DDFSs) are partly caused by amplitude quantization and phase truncation, which affect their application to many wireless telecommunication systems. Thee signals are deterministic and periodic in the time domain, so they appear as line spectra in the frequency domain. Two types of spurious signals due to amplitude quantization are exactly formulated and compared in thetime and frequency domains respectively. Then the frequency spectra and power levels of the spurious signals due to amplitude quantization in the absence of phase-accumulator truncation are emphatically analyzed, and the effects of the DDFS parameter variations on the spurious signals are thoroughly studied by computer simulation. And several important conclusions are derived which can provide theoretical support for parameter choice and spurious performance evaluation in the application of DDFSs.     

High efficient moving object extraction and classification in traffic video surveillance

Moving object extraction and classification are important problems in automated video surveillance systems. A background model based on region segmentation is proposed. An adaptive single Gaussian background model is used in the stable region with gradual changes, and a nonparametric model is used in the variable region with jumping changes. A generalized agglomerative scheme is used to merge the pixels in the variable region and fill in the small interspaces. A two-threshold sequential algorithmic scheme is used to group the background samples of the variable region into distinct Gaussian distributions to accelerate the kernel density computation speed of the nonparametric model. In the feature-based object classification phase, the surveillance scene is first partitioned according to the road boundaries of different traffic directions and then re-segmented according to their scene localities. The method improves the discriminability of the features in each partition. AdaBoost method is applied to evaluate the relative importance of the features in each partition respectively and distinguish whether an object is a vehicle, a single human, a human group, or a bike. Experimental results show that the proposed method achieves higher performance in comparison with the existing method.     

Single foggy image restoration based on spatial correlation analysis of dark channel prior

Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.