基于J2ME技术的移动证券研究与实现

论文在研究现有移动证券方案基础上,提出了基于J2ME(Java2Platform,MicroEdition)技术的移动证券应用系统,并对系统的安全性进行了讨论。该系统的实现为证券运营商提供安全、方便、迅捷的行情,交易和个性化定制等服务提供了新的接入方式。     

分布式入侵检测系统通信模块的设计

为满足分布式入侵检测系统组件间的通信要求,文中设计了分布式入侵检测系统的通信模块。通信模块的设计参照IDWG提出的入侵检测信息交换格式和入侵检测交换协议,并借鉴了TCP／IP的思想,对传输的数据采用数据加密标准和公开密钥加密两种加密算法,提高系统通信的安全性。     

院系网站总体设计与技术细节──中山大学数学与计算科学学院网站建设

中山大学数学与计算科学学院网站构建以FRONTPAGE98为主要开发工具,以HTML和DHTML为主要开发语言,以WINDOWSNT4.0为网站服务器操作系统,以IIS3.0为WEB服务器,提供了HTTP和FTP两种服务。同时还运用了VB、JAVA、JavaScript语言为网站提供各种HTML、DHTML所无法实现的扩展功能。该文从网站的总体设计思想、设计过程与技术细节来阐述整个网站的设计过程。     

A Truncated Sum of Processing‐Times–Based Learning Model for a Two‐Machine Flowshop Scheduling Problem

Scheduling with learning effects has gained increasing attention in recent years. A well‐known learning model is called “sum‐of‐processing‐times‐based learning” in which the actual processing time of a job is a nonincreasing function of the jobs already processed. However, the actual processing time of a given job drops to zero precipitously when the normal job processing times are large. Moreover, the concept of learning process is relatively unexplored in a flowshop environment. Motivated by these observations, this article addresses a two‐machine flowshop problem with a truncated learning effect. The objective is to find an optimal schedule to minimize the total completion time. First, a branch‐and‐bound algorithm incorporating with a dominance property and four lower bounds is developed to derive the optimal solution. Then three simulated annealing algorithms are also proposed for near‐optimal solution. The experimental results indicated that the branch‐and‐bound algorithm can solve instances up to 18 jobs, and the proposed simulated annealing algorithm performs well in item of CPU time and error percentage. © 2011 Wiley Periodicals, Inc.     

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.     

Face representation using independent component analysis

This paper addresses the problem of face recognition using independent component analysis (ICA). More specifically, we are going to address two issues on face representation using ICA. First, as the independent components (ICs) are independent but not orthogonal, images outside a training set cannot be projected into these basis functions directly. In this paper, we propose a least-squares solution method using Householder Transformation to find a new representation. Second, we demonstrate that not all ICs are useful for recognition. Along this direction, we design and develop an IC selection algorithm to find a subset of ICs for recognition. Three public available databases, namely, MIT AI Laboratory, Yale University and Olivette Research Laboratory, are selected to evaluate the performance and the results are encouraging.     

虚拟手术流血模拟的GPU加速实现

目的 流血效果是虚拟手术模拟器视觉效果的重要组成部分,血流与固体交互的庞大计算量使取得实时的流血模拟效果具有很大的挑战性。提出一种基于图形处理单元(GPU)加速的虚拟手术流血效果模拟方法。方法 该方法以Müller等人提出的光滑粒子动力学(SPH)作为基础,采用温度项使粒子具有不同速度模拟血流形成的血槽,同时基于构建均匀空间网格的思想,利用通用并行计算架构(CUDA)多线程并行加速技术完成粒子控制方程的求解和血流与固体交互的计算,从而取得实时的效果。结果 实验结果表明,本文方法能够满足虚拟手术中切割表面流血和血液在器官中流动的模拟需求,在粒子个数为9000时仅需20 ms,对比于纯CPU的实现取得20.15倍的加速比,实现了大量粒子下的实时流血模拟。 结论 本文方法具有较好的灵活性和实时性的特点,可以应用于虚拟手术仿真系统之中。     

PEJA: Progressive Energy-Efficient Join Processing for Sensor Networks

Sensor networks are widely used in many applications to collaboratively collect information from the physical environment. In these applications,the exploration of the relationship and linkage of sensing data within multiple regions can be naturally expressed by joining tuples in these regions. However,the highly distributed and resource-constraint nature of the network makes join a challenging query. In this paper,we address the problem of processing join query among different regions progressively and energy-efficiently in sensor networks. The proposed algorithm PEJA(Progressive Energy-efficient Join Algorithm) adopts an event-driven strategy to output the joining results as soon as possible,and alleviates the storage shortage problem in the in-network nodes. It also installs filters in the joining regions to prune unmatchable tuples in the early processing phase,saving lots of unnecessary transmissions. Extensive experiments on both synthetic and real world data sets indicate that the PEJA scheme outperforms other join algorithms,and it is effective in reducing the number of transmissions and the delay of query results during the join processing.     

一种新型两维霍尔角度传感器研究

本文研制了一种无触点的十字型两维集成垂直霍尔器件 ,它对平行于芯片表面的磁场敏感 .当与被测转角 α的物件轴向相固连的径向永久磁铁转动时 ,平行于芯片表面的磁场分量 Bx、By大小将发生相对变化 ,以致集成的两对霍尔板输出电量也产生相应地变化 .这时传感器件给出了相对于被测量角度 α的两种信号电压 ( sinα和 cosα) ,通过 arctgn( Vx/ Vy)可求得转角 α,从而达到测量角度的目的 .测量结果表明利用该角度传感器件与 PC机组成的测量系统其测量角度的精度可达± 1°     

Detection of dimension sets in engineering drawings

This correspondence presents a system for detecting dimension sets in engineering drawings that are drawn to ANSI drafting standards. A new rule-based text/graphics separation algorithm and a model-based procedure for detecting arrowheads in any orientation have been developed. Arrowhead tracking and search methods are used to extract leaders, tails, and witness lines from segmented images containing only graphics. Text blocks and feature control frames extracted from the segmented images are than associated with their corresponding leaders to obtain complete dimension sets. Experimental results are presented