计算机教学中学生创新能力的培养

随着计算机应用的普遍应用,计算机行业对具有创新能力人才的需求也在迅速扩大.所以在计算机教学中,培养学生的创新能力也是刻不容缓的教学改革任务.本文从创新意识、创新能力与计算机创新体现三个方面对计算机教学莘学生创新能力的培养进行分析探讨.     

一种虚拟景象合成系统技术研究

本文探讨了一种照片合成工作方式,利用电子技术获得拍摄场景中灯光以及照相机位置、焦距等信息并通过计算机接口输入,参考这些数据修改3DS文件,再利用三维软件进行真实的照片级渲染,最终合成照片作品.     

Holistic and partial facial features fusion by binary particle swarm optimization

This paper proposes a novel binary particle swarm optimization (PSO) algorithm using artificial immune system (AIS) for face recognition. Inspired by face recognition ability in human visual system (HVS), this algorithm fuses the information of the holistic and partial facial features. The holistic facial features are extracted by using principal component analysis (PCA), while the partial facial features are extracted by non-negative matrix factorization with sparseness constraints (NMFs). Linear discriminant analysis (LDA) is then applied to enhance adaptability to illumination and expression. The proposed algorithm is used to select the fusion rules by minimizing the Bayesian error cost. The fusion rules are finally applied for face recognition. Experimental results using UMIST and ORL face databases show that the proposed fusion algorithm outperforms individual algorithm based on PCA or NMFs.     

电子商务网站搜索引擎优化(SEO)策略研究

搜索引擎优化对电子商务网站推广起着重要的作用。在分析影响搜索引擎网站排名因素的基础上,总结出有利于提高电子商务网站排名的搜索引擎优化(SEO)策略。     

基于二维图像矩阵的ICA人脸识别

为了解决传统独立分量分析(ICA)在人脸识别过程中存在的高维小样本问题,同时为了提高识别效率,提出了一种基于二维图像矩阵的独立分量分析(ICA)特征提取方法.该方法将人脸图像矩阵作为训练样本,首先利用主分量分析(PCA)对训练样本进行去二阶相关和降维处理,然后对处理后的样本进行ICA特征提取,由于训练样本维数很小,因此它降低了传统ICA方法中高维小样本问题产生的识别错误率,同时减少了识别时间.在Yale人脸库和ORL人脸库上验证了该算法的有效性.     

XPE和x86嵌入式系统上并口控制的设计与实现

在介绍XPE（Windows XP Embedded）和x86嵌入式系统的基础上,引出并口控制问题,通过一个简单的实例讲述了在XPE和x86嵌入式系统平台上开发并口控制程序需要实现的硬件电路连接和软件编码问题。     

正交设计与回归分析对HDPE/LDHs制备参数的优化

利用正交设计和逐步2次回归分析的方法,研究了水滑石(LDHs)含量、螺杆转速和挤出次数对高密度聚乙烯(HDPE)/LDHs复合材料力学性能的影响。并用MATLAB对回归方程进行最优化处理,预测了复合材料在弯曲强度不低于25 MPa,缺口冲击强度不低于40 kJ/m~2条件下所得到的拉伸强度为29.558 3 MPa,并确定了此条件下的优化结果,即:LDHs含量为9.8%,螺杆转速为300 r/min,挤出次数为2次。此优化方案要好于常用的直观分析/方差分析的结果,更准确的反映实际情况,可更广泛的应用于优选试验中。     

Mixed-reality environment for frictional parameters identification in servo-pneumatic system

This paper outlines a method to identify the friction parameters for servo-pneumatic systems using a mixed-reality environment. To acquire system friction parameters accurately can be extremely difficult once the servo-system has been assembled because of its highly nonlinear nature, which causes a great difficulty in servo-pneumatic system modelling and control. In this research, a mixed-reality environment has been employed to determine the friction parameters effectively and efficiently through online identification. Traditionally, friction parameters identification can be performed manually or automatically using traditional optimization methods or modern ones such as neural networks. The advantages of the proposed method are the high accuracy in the estimated parameters, its simplicity and its speed. An experimental case study has been conducted and the results showed the accuracy and effectiveness of the proposed method.     

基于OpenGL的岩石楔形体边坡三维分析系统

随着工程应用的需要和计算机技术的发展,对岩石地质信息三维空间模型的可视化研究逐渐引起了研究人员的关注.用三维可视化技术来表现公路建设中的岩石楔形体边坡的结构和组成,可以更形象直观地研究它的动力稳定性,为公路工程处治提供科学的决策依据.讨论了岩石楔形体边坡三维分析系统的基本功能及系统结构,并分析了该系统的一些关键技术,包括三维模型多视图技术的实现、三维建模、三维交互技术等.最后给出了应用实例,结果表明,该系统具有良好的应用价值.     

One-Component Artificial Gustatory System Based on Hydrogen-Bond Organic Framework for Discrimination of Versatile Analytes

Hydrogen-bond organic frameworks (HOFs) with excellent structural and luminescent properties have emerged as a promising material for the construction of fluorescence sensors. However, designing a facile, universal and high throughput sensor with multiplex detection capacity still remains challenging. Herein, a one-component sensor array is constructed that mimics natural gustatory system for accurate and high-throughput discrimination and identification of versatile analytes. HOF as a single sensing element greatly simplifies the probe preparation in sensor array and detection procedure. Metal ions, proteins and bacteria as the model targets are rapid and accurately discriminated, presenting the universality of the system. Particularly, the system is successfully used for the classification of antibiotic mechanisms. The study expands the application scope of HOFs and provides a facile and universal system for sensing applications.