建筑结构裂缝的图形仿真

本文从建筑结构中构件裂缝的概念和表征出发,面向图形对象建立裂缝仿真模型,并 从计算机图形学的角度,运用粘贴技术来处理裂缝图形。为了使裂缝更逼真,在知识 推理的基础上,本文运用了随机处理技术。     

人工智能控制理论现状分析与发展探讨

总结了人工智能控制理论在各个不同阶段的发展状况及理论的突破,介绍了人工智能控制技术在各个时期典型应用的标志成果,分析当前人工智能控制面临要解决的问题,探讨人工智能控制理论今后发展方向。     

一种新的轻量级认证系统模型

本文提出了一种新的认证系统模型,该模型改变了传统认证系统的架构,利用分布式哈希表结构,实现了一种轻量级的认证系统。通过对本系统的分析表明,该系统与现有的认证系统相比,该系统具有同等的认证安全性和良好的可靠性、扩展性以及系统性能。     

基于短信息的远程监控报警系统

本文提出了一种基于GSM短信息的远程液位监控报警系统。该系统以GSM网络为平台,利用短信息实现对远端设备的控制。本文给出了系统硬件结构和软件框图。测试结果表明,该系统工作稳定可靠,费用低廉,能真正实现远程液位监控和报警。     

可调直观式直流稳压电源设计方案

本文设计一个可调可直观显示的直流稳压电源,电路采用三端可调式集成稳压器LM317等元件,构成从OV～20V连续可调的稳压电源电路,同时利用模数（A／D）转换,单片机控制电路,通过译码驱动,实现在数码管上直观显示瞬时电压数值。具有设计电路简单,制作容易,操作方便,显示直观,性能可靠,功能完善等特点。     

Efficient Tate pairing computation using double-base chains

Pairing-based cryptosystems have developed very fast in the last few years. The efficiencies of these cryptosystems depend on the computation of the bilinear pairings, In this paper, a new efficient algorithm based on double-base chains for computing the Tate pairing is proposed for odd characteristic p 〉 3. The inherent sparseness of double-base number system reduces the computational cost for computing the Tate pairing evidently. The new algorithm is 9% faster than the previous fastest method for the embedding degree k = 6.     

触摸传感器QST108与PIC单片机的接口设计

QST108为意法半导体公司生产的电容触摸传感器,具有功能强大且易操作等特点,非常适合应用在能够对用户触摸做出响应的智能控制界面中。本文重点介绍了QST108的工作方式及主要操作命令,给出了QST108与PIC单片机的接口设计以及部分程序代码。     

A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets

Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns identifies significant event-type sequences. Such spatio-temporal sequential patterns are crucial to the investigation of spatial and temporal evolutions of phenomena in many application domains. Recent research literature has explored the sequential patterns on transaction data and trajectory analysis on moving objects. However, these methods cannot be directly applied to mining sequential patterns from a large number of spatio-temporal events. Two major research challenges still remain: 1) the definition of significance measures for spatio-temporal sequential patterns to avoid spurious ones and 2) the algorithmic design under the significance measures, which may not guarantee the downward closure property. In this paper, we propose a sequence index as the significance measure for spatio-temporal sequential patterns, which is meaningful due to its interpretability using spatial statistics. We propose a novel algorithm called Slicing-STS-miner to tackle the algorithmic design challenge using the spatial sequence index, which does not preserve the downward closure property. We compare the proposed algorithm with a simple algorithm called STS-miner that utilizes the weak monotone property of the sequence index. Performance evaluations using both synthetic and real-world data sets show that the slicing-STS-miner is an order of magnitude faster than STS-Miner for large data sets.     

Dynamic visualization of coexpression in systems genetics data

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biological networks and discover genes residing in critical positions in networks and pathways. By using a graph as a universal representation of correlation in gene expression, our system employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by compound queries, dynamic level-of-detail abstraction, and template-based fuzzy classification. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.     

Reconstruction of cellular biological structures from optical microscopy data

Developments in optical microscopy imaging have generated large high-resolution data sets that have spurred medical researchers to conduct investigations into mechanisms of disease, including cancer at cellular and subcellular levels. The work reported here demonstrates that a suitable methodology can be conceived that isolates modality-dependent effects from the larger segmentation task and that 3D reconstructions can be cognizant of shapes as evident in the available 2D planar images. In the current realization, a method based on active geodesic contours is first deployed to counter the ambiguity that exists in separating overlapping cells on the image plane. Later, another segmentation effort based on a variant of Voronoi tessellations improves the delineation of the cell boundaries using a Bayesian formulation. In the next stage, the cells are interpolated across the third dimension thereby mitigating the poor structural correlation that exists in that dimension. We deploy our methods on three separate data sets obtained from light, confocal, and phase-contrast microscopy and validate the results appropriately.