激光对望远系统损伤的研究

本文对激光光束通过望远系统后光束的变化进行了分析，并对６倍望远镜进行了激光损伤和破坏的实验研究，实验结果表明，激光对望远系统的损伤破坏主要是热效应所致，损伤破坏的情况与激光的能量，波长，脉冲宽度和望远系统的结构有关。     

高精度合成地震记录制作技术研究

制作高精度的合成地震记录是精细储层描述的基础，本文在分析合成地震记录原理的基础上，从地震剖面的极性判断、平均速度的选取，反射系数的准确提取，子波的精确估算等方面对制作合成记录的要点进行了分析，通过提高以上四方面的精度，提高了制作合成地震记录的精度，并提出了一套可行的合成地震记录的检查方法。     

蛋白质与原卟啉Ⅸ及复合物发光机理探讨

对原卟啉Ⅸ（ＰｒｏｔｏｐｏｒｐｈｙｒｉｎⅨ）与蛋白质结合物的吸收、荧光的激发、发射光谱等的研究，表明了在光作用下，其可见区发光（λｍａｘ６３５ｎｍ左右）与卟啉有关，而紫外区发光（λｍａｘ４２２ｎｍ左右）与蛋白质的色氨酸残基有关，其光谱特性与临床诊断选择的癌固有荧光特征峰基本相符。该研究结果为探讨癌的发光机理积累了有益资料．     

焊前处理方式对LF6铝合金扩散焊的影响

利用Ｇｌｅｅｂｌｅ－１５００热／力模拟试验机，研究了ＬＦ６铝合金的扩散焊工艺，通过对焊接温度、压力、时间的调整和选用不同的料前处理方法，确定了最佳的扩散规范，研究结果表明：在一定的温度和时间范围内，ＬＦ６５铝合金扩散焊接头的剪切哟度随焊接温度和时间的增加而提高；化学浸蚀法比机械打磨法能更有效的去除铝合金表面的氧化膜；在现有试验条件下，得到ＬＦ６铝合金扩散焊的最佳规范参数，搭接试扩散焊接头的剪切强度     

遥感数据时空融合技术在农作物监测中的适应性研究

受卫星回访周期及云的影响,大范围研究区同一时期的Landsat卫星数据很难获取,因而国内外学者提出了遥感影像时空融合技术。以石河子为实验区,利用STARFM(Spatial and Temporal Adaptive Reflectance Fusion Model)模型融合生成了高时空分辨率TM影像,对不同作物类型真实反射率与融合影像反射率作相关性分析,分析了遥感数据时空融合技术在新疆农作物监测中的适用性。结果表明:利用STARFM模型模拟得到的融合影像与真实影像间的相关性较高,但当地物类型发生变化时,融合影像与真实影像间将存在明显的差异。地物类型变化作物融合影像反射率与真实影像反射率间的相关性较小。     

“三位一体”数字校园的设计与实现

介绍了集＂日常管理＂、＂水平评估＂、＂决策规划＂三位于一体的数字校园设计方案。通过规范基础数据,采用ESB整合各业务子系统,解决＂信息孤岛＂问题,并为状态数据采集提供便利。利用BI软件进行数据挖据,为管理者进行科学规划和决策提供数据支持。系统采用单点登录,个性化的门户展现满足了各类用户对资源和服务的需求。     

Evaluating Particle Deposition in the Artificial Groundwater Recharge Process by Physical and CT Imaging Experiments

Particle clogging in the artificial groundwater recharge process is one of the main factors influencing the artificial groundwater recharge efficiency, and particle deposition is the microscopic mechanism of the occurrence and development of particle clogging. Particle deposition in porous media changes the pore structure. The computed tomography (CT) scanning technique is a nondestructive testing method and determines the spatial distribution of pores in porous media. This study combines physical and CT scanning experiments to identify the change process of the pore structure in the artificial groundwater recharge process and compares the pore changes during recharge experiments between two columns containing different media. Porous media changes are observed with the CT scanning technique. The fractal theory is applied in the analysis of CT scan images and physical experiment results. The results of this study indicate that particle deposition can be examined by using CT scan images to obtain pore-related parameters, the internal pore structure of porous media determined through CT scan images can be applied in numerical simulation, and a mathematical model for particle deposition calculation in porous media is established. Compared to the physical experiment measurements, the spatial particle deposition information acquired with the CT scanning technique exhibits a higher accuracy and contains much more relevant data. Not only does this research reveal more clearly the particle clogging mechanism which is based on particle deposition, but also characterize, simulate and predict more accurately the development tendency of particle clogging during artificial groundwater recharge.

     

Study of the hinge thickness deviation for a 316L parallelogram flexure mechanism fabricated via selective laser melting

3D printing offers great potential for developing complex flexure mechanisms. Recently, thickness-correction factors (TCFs) were introduced to correct the thickness and stiffness deviations of powder-based metal 3D printed flexure hinges during design and analysis. However, the reasons for the different TCFs obtained in each study are not clear, resulting in a limited value of these TCFs for future design and fabrication. Herein, the influence of the porous layer of 3D printed flexure hinges on the hinge thickness is investigated. Samples of parallelogram flexure mechanisms (PFMs) were 3D printed using selective laser melting (SLM) and 316L stainless steel powder. A 3D manufacturing error analysis was completed for each PFM sample via 3D scanning, surface roughness measurement and morphological observation. The thickness of the porous layer of the flexure hinge was independent of the designed hinge thickness and remained close to the average powder particle diameter. The effective hinge thickness could be estimated by subtracting twice the value of the porous layer thickness from the designed value. Guidelines based on finite element analysis and stiffness experiments are proposed. The limitations of the presented method for evaluating the effective hinge thickness of flexure hinges 3D printed via SLM are also discussed.

     

CBR系统中一种实例相似度算法的改进

本文对CBR系统中实例相似度的算法进行了改进,在传统实例相似性算法的基础上加入实例属性缺失度因子和实例可复用性因子。因此在实例检索中考虑实例检索结果的精确度和实例的可复用度,进而使检索的精确度提高和修改难度降低,最终提高CBR系统的精确度和实用性。     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.