点阵汉字库到PROTEL元件符号图形库的转换

本文介绍了PROTEL元件符号图形库和点阵汉字库的结构,以及怎样将点阵汉字库转换到PROTEL元件符号图形库的方法。从而提出一种在利用PROTEL设计电路原理图时,加入汉字标注的途经。     

三维目标旋转畸变不变光学相关滤波器组的设计

研究了三维目标旋转畸变不变光学相关滤波器组的设计原理，完成了滤波器组参数的计算和编码，以及光学相关识别的计算机模拟。     

V型天线的行波加载公式

本文研究了ｖ型天线上电流分布与阻抗加载的关系，导出了支持天线上行波电流的阻抗加载公式。讨论了天线张角、振子半径以及振子长度与加载量的关系和规律，说明了加载Ｖ型天线的宽带特性。文中还计算了在高斯脉冲激励下，不同加载量的天线上瞬态电流的分布，由此可以表明所导加载公式的正确性与重要性。     

多级防火墙技术研究与应用探讨

在计算机信息技术和互联网飞速发展的今天,互联网在人类的生活、工作、学习中占据着重要地位。然而计算机网络安全是其与之俱来不可避免的问题。本文将基于多级防火墙技术,分析当前计算机网络中存在的安全隐患,针对这些实际问题探讨如何有效应用多级防火墙技术,实现对计算机网络安全的维护。     

果园数据采集和监控的低功耗节点设计

针对果园种植密度大、障碍物多使得通信受阻的缺点,设计了一种适合果园数据采集和监控的低成本、低功耗的传感器节点;节点的微控制器采用低功耗ATmega128L,射频模块采用CC2420,并采用SHT11空气温湿度传感器、ISL29010光照传感器、FDS-100土壤水分传感器、Pt1000土壤温度传感器作为传感器模块,对节点的软件进行了详细设计,改进了操作系统任务调度方法,通过引入休眠机制设计了MAC层和网络层通信协议;通过将文中节点应用于南通海安市的大公镇果园试验基地,结果表明:文中设计的节点在采样周期为1 050 s时,能正常工作116天,具有低功耗和生命周期长的优点,同时其采样湿度的平均误差仅为0.213％,具有数据采集精度高的优点,能满足果园信息采集和监控的要求.     

基于GSM的故障实时报警控制系统的设计与实现

针对实时监控系统中的运行设备或装置的异常报警信息,设计了基于GSM无线通讯的微机监测系统,实现了多故障远程短信息报警功能,介绍了系统的软硬件设计及主要功能;经应用测试,系统具有宴时性强、稳定性高、投入成本低等特点,能将信息同时发送至多个移动通信终端,已成功应用于农业温室大棚监控系统的实时故障报警,系统也可方便地应用于工厂生产线、金融、交通及家庭安全等方面的远程监测.     

Optimal Path Problems with Second-Order Stochastic Dominance Constraints

This paper studies optimal path problems integrated with the concept of second order stochastic dominance. These problems arise from applications where travelers are concerned with the trade off between the risks associated with random travel time and other travel costs. Risk-averse behavior is embedded by requiring the random travel times on the optimal paths to stochastically dominate that on a benchmark path in the second order. A general linear operating cost is introduced to combine link- and path-based costs. The latter, which is the focus of the paper, is employed to address schedule costs pertinent to late and early arrival. An equivalent integer program to the problem is constructed by transforming the stochastic dominance constraint into a finite number of linear constraints. The problem is solved using both off-the-shelf solvers and specialized algorithms based on dynamic programming (DP). Although neither approach ensures satisfactory performance for general large-scale problems, the numerical experiments indicate that the DP-based approach provides a computationally feasible option to solve medium-size instances (networks with several thousand links) when correlations among random link travel times can be ignored.     

基于ANSYS混凝土重力坝流固耦合动力特性分析

以某混凝土重力坝非溢流坝段动力特性为背景,探讨流固耦合效应对结构自振特性的影响,运用大型有限元软件对结构自振特性进行分析计算,得出了流体对结构自振特性影响以及结构的固有频率,避免在运行过程中发生共振,造成对结构的破坏。     

VideoGraph: a non-linear video representation for efficient exploration

In this paper we introduce VideoGraph, a novel non-linear representation for scene structure of a video. Unlike classical linear sequential organization, VideoGraph concentrates the video content across the time line by structuring scenes and materializes with two-dimensional graph, which enables non-linear exploration on the scenes and their transitions. To construct VideoGraph, we adopt a sub-shot induced method to evaluate the spatio-temporal similarity between shot segments of video. Then, scene structure is derived by grouping similar shots and identifying the valid transitions between scenes. The final stage is to represent the scene structure using a graph with respect to scene transition topology. Our VideoGraph can provide a condensed representation in the scene level and facilitate a non-linear manner to browse videos. Experimental results are presented to demonstrate the effectiveness and efficiency by using VideoGraph to explore and access the video content.     

Learning high-dimensional correspondence via manifold learning and local approximation

The recent years have witnessed a surge of interests of learning high-dimensional correspondence, which is important for both machine learning and neural computation community. Manifold learning–based researches have been considered as one of the most promising directions. In this paper, by analyzing traditional methods, we summarized a new framework for high-dimensional correspondence learning. Within this framework, we also presented a new approach, Local Approximation Maximum Variance Unfolding. Compared with other machine learning–based methods, it could achieve higher accuracy. Besides, we also introduce how to use the proposed framework and methods in a concrete application, cross-system personalization (CSP). Promising experimental results on image alignment and CSP applications are proposed for demonstration.