嵌入式设备中虚拟显示设备的图像显示的实现

基于linux内核2.4,在没有物理显示设备情况下,通过缺页机制,实现虚拟Framebuffer。将要显示的图像转换成相应格式的图像信息,并可提取出来供显示设备显示。     

基于嵌入式系统STM32的超声波介质传输速度测试系统的设计

本测试系统由微控制器(STM32F103ZET6)、测温系统、超声波发射电路、超声波接收电路、显示系统等部分组成。先产生40KHZ的方波信号,再通过信号调整电路送到超声波发射探头。再通过对超声波接收探头采集到的回波信号进行整形并送入MCU控制器进行处理得到所需数据,并通过显示模块显示。通过温度传感器采集环境温度,并通过STM32F103ZET6控制器对采集温度传感器的信号进行处理分析,得到环境温度,并通过显示模块显示。并在不同温度下,实现了超声波在空气和水中传播速度的测量。     

基于 Framebuffer 的嵌入式 Linux 图形库设计

本文主要研究并设计出一套基于嵌入式体系结构的Linux图形库,并将其应用于项目实践中。所设计的图形库以Linux 2.6内核的Framebuffer为基础,用C语言编程封装构造而成,它具备矢量图形显示、BMP位图显示、常用字符显示、窗口显示及消息响应等基本功能。     

LCD定标器中显示时序控制模块的设计

定标器(Scaler)是用于平板显示FPD(Flat Pand Display)系统的一种高度集成的图像处理芯片,它主要负责将不同分辨率的输入图像映射到具有固定分辨率的平板显示器上,并保持图像显示的清晰和稳定。在定标器中存在一个专门的显示时序控制DTG(Display Timing Generator)模块来解决定标器中和显示有关的时序问题。首先说明显示时序控制模块和定标器中其它子模块之间的关系,然后重点对显示时序控制模块所要解决的几个时序问题进行分析,并在分析问题的基础上提出一种显示时序控制模块的实现结构,最后对显示时序控制模块进行功能验证,并给出RTL(Register Transfer Level)级的仿真波形。     

基于PIC的混合动力汽车综合信息显示仪设计

研究设计了一款以HMI串口液晶显示器为终端的基于PIC18F4580单片机以及CAN总线的混合动力汽车综合信息显示仪。该湿示仪具有电池管理系统参数显示,故障诊断显示,车辆上况显示等功能。通过软件实现预置画面与现场实时数据组合显示,并随时根据需要对显示界面进行修改和扩充。实验表明,该综合信息显示仪不仅保证了信息处理显示的实时性,并能够将表征混合动力汽车工作状态的各项数据通过数字界面,动画界面及时清晰的显示出来。     

高速采样中波形数据的图像化实时显示

为了对工业现场采样的波形进行图形化显示,采用MFC+WIN32API设计并实现了用于高速信号采样并成像显示的软件。该软件件采用位图双缓冲机制,避免了图像闪烁,采用兼容位图与直接赋值,加快了显示和刷新速度。     

中控室数字墙显示系统的设计

根据数字墙实际的显示特点,提出一种数字墙显示系统的设计方案。在显示侧配置数码管驱动电路板,电路板通过485总线接收计算机传送的显示信号,进而驱动数码管显示。计算机上的数据传送程序由VB6.0编写,通过DDE从监控软件获得显示量的实时值,并定时向每个数码管发送数据显示报文,每个数码管显示的内容及格式均可定义。数据传送程序运行在操作员站上,不需要专门的计算机,成本低,维护方便。     

CPLD在LED点阵显示器中实现字符滚动的应用

本文详细讨论并实现了CPLD在LED点阵列滚动字符显示中的应用.文中分析了滚动字符的显示原理和CPLD的特点,设计出了实现字符滚动显示的硬件电路,并结合电路和字符显示原理用VHDL语言完成了实现字符滚动显示的程序设计.然后对系统进行了软件仿真,仿真结果实现了电路功能,系统运行正常.通过适当的修改,可以实现不同速度、各种字符的显示.     

虚拟环境中多视觉通道图形显示的实现

该文在分析虚拟环境中单视觉通道图形显示不足之处的基础上,研究了多视觉通道图形显示的一套实现方法,并给出了一个多视觉通道图形显示实例--虚拟坦克的多视觉通道图形显示。结果表明多视觉通道图形显示可以更好地增进虚拟环境的"沉浸"效果。     

LCoS显示芯片的研制

介绍LCoS显示芯片的研制。三片式投影用LCoS显示芯片的物理结构及其电路组成框图;芯片整体设计方法,运用CadenceEDA工具设计LCoS显示芯片的具体策略和相应步骤;给出了LCoS显示芯片的实际设计结果,并对其光学参数进行了测量。     

An implementation of a garment-fitting simulation system using laser scanned 3D body data

We propose a garment-fitting system for an online retail model, which uses a consumer's 3D body data for garment fitting. This system uses front and back images to model the garment and 3D laser scanned body data to model the body. In order to recognize characteristic points on the 3D body data, a moment template composed of central moments of vector angle sets on 3D body data is proposed, and an implementation combining the 3D data and garment images is reported, which includes modeling, collision detection and feedback handling. The resulting system would support an online retail business model for garments. In the proposed business model, a body data center would scan the body and store the 3D data, the simulated garment-fitting program would be provided to individual consumers for fitting on a home PC, and retail shops would exhibit garment images on their websites. In this proposed model, security of personal data and computational cost will not be an issue.     

基于多Agent的全资产可视性系统

全资产可视性(TAV)系统是实时、准确地获取和处理物流的数字化信息，并对物流活动进行有效控制的一体化综合电子信息系统，实现物流管理全过程的可视性，降低物流成本，极大地提升物流的服务水平。TAV系统是复杂系统，多主体(multi-agent)具有自治性和独立性，能主动规划自己的行为，可以有效地解决系统复杂的集成问题。结合系统特点，构建了基于多主体(multi-agent)的TAV系统体系结构，并分析了需求模型。     

IKS index: A knowledge-model driven index to estimate the capability of medical diagnosis systems to produce results

The evaluation of a medical diagnosis system can depend on several external parameters, such as experts’ opinions/criteria or the gold standard used. In addition, there are other parameters that can be measured in a medical diagnosis system, and one of these parameters in particular is the sensitivity. Sensitivity allows knowing how sensible a system is to produce results in different environments. Hence, the aim of this paper is to provide researchers with an index able to estimate a parameter very similar to common sensitivity. This would permit to know an estimation of the results relying on the modeling of the knowledge base. It would be the mathematical justification of this index that would allow estimating the aforementioned parameter. Therefore, the index would in general allow an estimation of the sensitivity without the necessity of having external feedback from experts in the field, which is one of the main lacks within the classical sensitivity metric.     

Improving network security through port switching

The latest range of network performance improvement is the use of switching technologies to isolate traffic from various systems. This is achieved by placing a system on a device called a switching bridge which, in turn, isolates traffic by only allowing packets to be sent to the port on which the system is located when a packet is actually addressed to the system in question or when the message is a group or broadcast message that would be sent to all nodes. In a typical LAN environment, systems on a network segment ‘see’.     

Gear-box fault detection using time-frequency based methods

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected. Two different time–frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen–Loeve basis. Both of them detect the gear-box fault with an acceptable detection delay of maximum 100s, which is neglectable compared with the fault developing time.     

Performance evaluation of fuzzy-based decision system for pool

An important step in any machine intelligence is to automatically and reliably decide on a solution/outcome based on the inputs given. The mapping of the inputs to an output decision often follows a set of critical rules that mimic the decision that would often be decided by a human being. In this paper, the performance of a fuzzy-based decision system for playing a game of pool is presented by comparing the results involving direct hit with two known systems. The performance is also compared to the decision that would be made by the human players. The design steps for the fuzzy-based decision system are presented using the fuzzy logic approach by employing a three-input one-output fuzzy inference system based on a set of 24 rules. The results have shown that fuzzy logic is able to accurately decide on the best move, which is as good as the human players themselves.     

A survey on cyber attacks against nonlinear state estimation in power systems of ubiquitous cities

It is well-known that critical infrastructures would be targets for cyber attacks. In this paper, we focus on the power systems (i.e. smart grids) in ubiquitous cities, where every meter is linked to an information network through wireless networking. In a smart grid system, information from smart meters would be used to perform a state estimation in real time to maintain the stability of the system. A wrong estimation may lead to disastrous consequences (e.g. suspension of electricity supply or a big financial loss). Unfortunately, quite a number of recent results showed that attacks on this estimation process are feasible by manipulating readings of only a few meters. In this paper, we focus on nonlinear state estimation which is a more realistic model and widely employed in a real power grid environment. We category cyber attacks against nonlinear state estimation, and review the mechanisms behind. State-of-the-art security measures to detect these attacks are discussed via sensor protection. Hope that the community would be able to come up with a secure system architecture for ubiquitous cities.     

Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease

In this paper, we have made medical application of a new artificial immune system named the information gain based artificial immune recognition system (IG-AIRS) which minimizes the negative effects of taking into account all attributes in calculating Euclidean distance in shape–space representation which is used in many artificial immune systems. For medical data, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress.