独立学院计算机公共课程体系研究

针对当前独立学院计算机公共课程教学的现状及存在的问题,提出独立学院应结合自身特点,以培养应用型人才为目标,着重培养学生的计算机综合应用能力,构建分层次的1+1+X模式的非计算机专业计算机公共课程体系。     

高职网络技术基础课程教改探索

分析高职网络技术基础课程的特点及教学中的问题,介绍该课程在我校的教改实践情况。探讨引入行业软件、建立虚拟仿真实训平台、采用行业认证与形成性考核相结合的学业评价等课改举措,以此激发学生的学习兴趣,提高课程教学质量。     

独立学院本科计算机应用基础课程教改研究

为了提高教育质量,独立学院必须从自身的条件出发,进行深入的教学改革。针对计算机应用基础课程的特点,文章提出以社会需求为导向,改革教学内容;从实际出发,改进教学方法;发挥网络优势,构建立体化教学环境;加强教师队伍建设,为课程改革夯实基础。经过实践,这种做法取得了优良的效果。     

金刚石与石墨局域态密度和能带结构的第一原理分析

计算与分析电子结构对类金刚石薄膜材料的研究尤为重要.本文用第一原理分子动力学模拟,以研究金刚石和石墨的局域态密度和能带结构.第一原理计算赝势平面波法和密度泛函理论(DFT)去计算,电子交换相关能采用广义梯度近似(GGA)去描述,这种方法可以正确无误的预测半导体带隙与尺寸的关系.金刚石的禁带很宽,为绝缘体,Sp3杂化轨道在费米能级附近提供部分能态密度.石墨是零带隙半金属的内部结构根源就在于离域π键,费米能级处的能态密度几乎全部来自p能级的贡献.研究结果预测,结构变化和Sp杂化轨道产生的函数关系,是很多物理性质不同的最根本原因,而物理性质的研究则可以最直观的体现这种函数关系,可以更深入地研究金刚石和石墨这两种物质.     

An intelligent hybrid system for surface coal mine safety analysis

Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.     

Cross‐talk acceptability in natural still images for different (auto)stereoscopic display technologies

Abstract— One of the most annoying distortions in (auto)stereoscopic displays is probably cross‐talk, visible as double edges, which is mainly caused by an imperfect separation of left‐ and right‐eye images. For different types of three‐dimensional (3‐D) displays, cross‐talk is caused by different origins, which could result in different levels of perceived image distortion. To evaluate the influence of (auto)stereoscopic display technology on cross‐talk perception, optical measurements and subjective assessments were performed with three different types of 3‐D displays. It is shown with natural still images that the 3‐D display technology with the lowest luminance and contrast level tolerates the highest level of cross‐talk, while still maintaining an acceptable image‐quality level.     

基于单片机的航向和舵角一体化指针式复示器的设计

针对船舶数字化和指针式复示器直观的特点,设计了不含大变比机械齿轮和不需人工基准位置调节的具有IEC61162标准数字信号输入的航向和舵角一体化指针式复示器;分析复示器的信号流后指出,其本质是由航向外表盘、航向内表盘和舵角指针组成的三个位置随动控制系统;设计了以步进电机为执行器和以步进脉冲计数进行位置估计和在基准位置点通过霍尔元件和永久磁铁进行精确位置测量相结合的控制方案;复示器采用了C8051F023单片机,通过其片上模拟差分输入和线性霍尔元件实现了刻度盘基准位置的精确测量;通过其片上PCA和中断程序实现了电子齿轮;试验表明,该复示器设计稳定可靠,具有较高的性价比。     

EtherCAT网络数据采集系统的设计与实现

针对很多领域中数据采集量大、数据采集点分布广、间距长等问题设计了一种基于EtherCAT工业以太网的网络数据采集系统;简介了EtherCAT网络通信原理和结构,详细阐述了系统的硬件设计:以PIC单片机为主控制器,采用一片AD转换芯片并配合数个模拟量多路开关实现多路数据采集,并完成了EtherCAT主站程序、从站应用程序的设计;最后,对采集系统进行了实验验证,实验结果证实了该网络数据采集系统的实用性和可靠性。     

1925年巴黎博览会与装饰艺术运动

一次博览会、一场艺术运动,是历史的契机将这两者结合在一起,也为设计艺术的璀璨银河中留下了绝无仅有的永恒光辉。1925年巴黎装饰艺术与现代工业博览会同装饰艺术运动两者之间,历经承载、展示、传播和启迪的历程推动了世界的进步,改变了人们的生活。我们回顾历史不仅是为了去陈述,而是在历史的积淀中迎接即将到来的2010年上海世博会以及未来设计为中国带来的巨变。     

Research of neural network algorithm based on factor analysis and cluster analysis

Aiming at the large sample with high feature dimension, this paper proposes a back-propagation (BP) neural network algorithm based on factor analysis (FA) and cluster analysis (CA), which is combined with the principles of FA and CA, and the architecture of BP neural network. The new algorithm reduces the feature dimensionality of the initial data through FA to simplify the network architecture; then divides the samples into different sub-categories through CA, trains the network so as to improve the adaptability of the network. In application, it is first to classify the new samples, then using the corresponding network to predict. By an experiment, the new algorithm is significantly improved at the aspect of its prediction precision. In order to test and verify the validity of the new algorithm, we compare it with BP algorithms based on FA and CA.