短信理财平台系统设计与实现方案

电子业务是银行中间业务的一个重要组成部分,直接关系到银行的信誉.本文根据银行业务部的短信理财系统的需求,结合现在移动梦网业务的发展,开发了短信理财系统,实现了短信理财的目标,并就系统的分析、设计和实现进行了详细的阐述.     

手机丢了,隐私怎么办?

手机丢失,相信好多人都经历过这样的事情,而现实生活当中的小偷不会像<天下无贼>里面的李冰冰只偷名牌手机,好看的还是不好看的,高档的还是便宜货,只要有机会,都会有可能成为他们的囊中物.其实对于绝大多数朋友来说,丢失手机本身倒不是用户最担心的,反而是里面所保存的通讯录、短信息、照片、视频、录音等隐私资料的丢失才是最让人担心的.从早些时候美国希尔顿家族的继承人帕丽斯希尔顿手机中隐私照片的泄露,到娱乐圈类似"艳照门"事件以及最近发生的王学兵手机丢失导致短信曝光,这一次又一次的隐私暴露事件中,折射出的是高科技时代的人权隐私的脆弱.我们不禁要问:手机丢了,隐私怎么办?……     

基于SOPC的DSP系统的研究与设计

主要研究基于SOPC的DSP系统的设计与实现.根据待实现的DSP算法的特征,利用QUARTUS中提供的丰富的功能模块和VHDL语言进行设计.经过仿真和开发板上验证,证明了采用FPGA技术的数字信号处理器的速度要远远快于一般的通用DSP,为高速数据处理与通信技术的应用提供了另外一种解决方案.     

具有未知参数的机器人-摄像机系统的自适应动态反馈跟踪控制

研究了不确定非完整移动机器人系统的跟踪问题.首先,基于视觉反馈和状态输入变换,展示了一种非完整移动机器人运动学系统的不确定链式模型.基于反步法思想和跟踪误差系统结构,给出了两个重要的新变换.然后运用李雅普诺夫直接方法和扩展巴巴拉引理设计了自适应控制律和动态反馈鲁棒控制器,以实现理想轨迹的跟踪控制.严格证明了闭环误差系统的渐近收敛性.最后,仿真结果证实了提出的控制策略有效.     

2007年计算机病毒/木马的特点分析及发展趋势预测

病毒"工业化"入侵凸显病毒经济病毒/木马背后所带来的巨大的经济利益催生了病毒"工业化"入侵的进程。2007年上半年,金山对外发布了病毒木马产业链的攻击特征,在此阶段,病毒木马的攻击通常是针对单个计算机的攻击行为。攻击的手法,一般利用社会工程欺骗的方式,发送经过伪装的木马以及通过网页挂马构造大     

以用户的需求为中心——访Cimatron总裁兼首席执行官的Zvika Naggan先生

今天,Cimatron已在全球的35个国字和地区建立了自己的分支机构或代理商.在世界范围内,从小的模具制造工厂到大公司的制造部,CimatroCAD/CAM解决方案已经成为企业装备中不可或缺的工具.Cimatron的成功来自于与用户的直接交流.Cimatron通过与世界范围内用户的合作,更好的理解用户的需求,从而为用户提供独特的解决方案.     

踏上精益之路--中国制造业的战略远征

笔者的顾问团队从学习国外经验开始,结合中国军工企业的情况,指导了某大型军工企业的工厂踏上精益旅程的实践.我们试图找到一些抽象于行业的、通用的实施精益的方法和共同的规律,希望会有助于中国制造企业踏上精益的战略征途.下面是我们的一些做法和体会.     

船舶与海洋工程产品设计的领航员

21世纪是一个海洋的世纪,海洋中生物资源、矿产资源和油气资源的开发利用,航运业的发展以及现代海军的建设,都离不开船舶与海洋工业的发展.种种迹象表明,中国的船舶工业正处在蓬勃发展的黄金时代,不久的将来中国完全有可能成为世界第一的造船大国.随着造船工业的高速发展,传统的船舶与海洋平台设计分析方法面临着巨大挑战,而浮体结构的耐波性计算和校核显得尤为突出.     

鼠你所爱方正小鼠本S301时尚现身

从安娜苏的最新一季彩妆,到兰蔻的流光炫色唇彩,或是时尚之都巴黎飘逸的最in短裙,LV的圆点限量版手袋,过去的一段时间里,粉色绝对是时尚界最偏爱的宠儿,毫不夸张地说,靓丽、唯美而又略带张扬的粉色已经成为引导时尚的主色调,在多变的时尚界创造了又一个色彩的神话.     

猥琐人生..是这样开始的...PANST~*叫我潘——潘斯特的潘

网络的兴起,时代的改变,让许多人越来越讲求个性化,单纯的使用文字来交流沟通,已经没有办法引起年轻人的兴趣,他们有更多的主张,有更多的想法,甚至有更多的创意。于是用图形来传递信息,成了一件时尚的玩意儿。这也让网络上的漫画表情开始出现了百家争鸣,到几家独秀的局面,今天逮到的潘斯特,就是大受网友喜爱的一个。     

融入Universum学习的度量学习算法

度量学习通过更真实的刻画样本之间的距离,来提高分类和聚类的精度。GMML（Geometric Mean Metric Learning）在学习度量矩阵[A]时,使得在该度量下同类点之间的距离尽可能小,不同类点之间的距离尽可能大。GMML用来学习的训练样本均为目标类数据,而对于现实存在的为数众多的同领域非目标类数据,即Universum数据并未加以利用,不免造成信息的浪费,针对此,提出一种新的度量学习算法--融入Universum学习的GMML（U-GMML）。U-GMML期望得到一个新的度量矩阵[A],使得同类点之间的距离尽可能小,不同类点之间的距离尽可能大,且Universum数据与目标类数据的距离尽可能大,从而使得所学习的度量矩阵[A]更有利于分类。真实数据集上的实验结果验证了该算法的有效性。     

基于传感器最优配置的等价空间故障检测方法

提出一种基于传感器最优配置的等价空间故障检测方法．针对线性时不变动态系统，给出了传感器最优配置问题的描述，以及基于传感器最优配置的故障检测多目标优化问题的描述．在系统可供测量的N个变量中，选择能获得关于系统故障尽可能多信息的m个变量作为测量变量，在满足对故障具有尽可能高的灵敏度，同时对扰动等未知信号具有尽可能强的鲁棒性的条件下，使整个系统测量成本达到最低．仿真算例说明了所提出设计方法及算法的有效性．     

A structured marketplace for arbitrary services

Creating simple marketplaces with common rules, that enable the dynamic selection and consumption of functionality, is the missing link to allow small businesses to enter the cloud, not only as consumers, but also as vendors. In this paper, we present the concepts behind a hybrid service and process repository that can act as the foundation for such a marketplace, as well as a prototype that allowed us to test various real-world scenarios. The advantage of a hybrid service and process repository is that, it not only holds a flat list of services, but also exposes a generic set of use cases, that it obtains information on how specific services can be used to implement the use cases as well as information to select services at run-time according to customer’s goal functions.     

浅析目前动漫教学中存在的误区

动漫教学在当今高校教育中所占比例越来越重,然而,由于诸多方面原因,当前动漫教学过程存在一些误区。本文从动漫基础教学、动漫教学的本土原创性和动漫教学培养目标几方面入手,旨在找出造成动漫教学重借鉴轻原创、重西方轻中国、重技术轻艺术的根本原因,以提高教学水平。     

Algorithms and allegories

Much of contemporary art practice is both produced and can be read with the notion of the algorithmic as its predominate trope. Similarly one can read older art practices as working under the aegis of allegory. Of course these registers and metaphors can be used to parse a distribution of artistic and cultural production across time in multiple directions. We often think of the algorithmic as that which concerns procedure, and don’t see it as its own meaning. In this text I am interested in exploring the algorithmic as a gesture, individualized and particular, something that can reveal an interiority of a work. In this way it is perhaps akin to the allegoric, where the work proper, comprised on the surface, simultaneously holds beneath and within it something else. The algorithmic as an author|composer’s signature, might be thought of as that secret storehouse of invention. With the advent of computation and the network, more and more contemporary art and sound work turns its attention to sequencing, loops, replication, modulation, mutation, generative systems, database and interface as instruction sets or grammars, both as ways to conceptualize and to produce work. The paper looks at a wide range of stratagems in works of sound, architecture, visual arts, and film to illustrate a correspondence between the allegoric and the algorithmic. Its aim is to encourage both practitioners and theorists to engage these two notions, the allegoric and the algorithmic, as a way to consider and produce work.     

Parallel programming in computational science: an introductory practical training course for computer science undergraduates at Aachen University

Parallel programming of high-performance computers has emerged as a key technology for the numerical solution of large-scale problems arising in computational science and engineering (CSE). The authors believe that principles and techniques of parallel programming are among the essential ingredients of any CSE as well as computer science curriculum. Today, opinions on the role and importance of parallel programming are diverse. Rather than seeing it as a marginal beneficial skill optionally taught at the graduate level, we understand parallel programming as crucial basic skill that should be taught as an integral part of the undergraduate computer science curriculum. A practical training course developed for computer science undergraduates at Aachen University is described. Its goal is to introduce young computer science students to different parallel programming paradigms for shared and distributed memory computers as well as to give a first exposition to the field of computational science by simple, yet carefully chosen sample problems.     

Customized Share Level Monitoring System for Users in OSN-Third Party Applications

Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as well as to the OSN. Despite paying millions of dollars as fine every year, the OSN has not done any significant changes, as data is the fuel and what it loses as fine is far less compared to the money OSN makes out of the shared data. In this work, we have discussed a wide range of possible privacy threats and solutions prevailing in OSN-Third Party Application (TPA) data sharing scenario. Our solution models the behavior of the user, as well as TPA and pinpoints the avenues of over sharing to the users, thereby limiting the privacy loss of the user.     

Selective Branch Inversion: Confidence Estimation for Branch Predictors

This paper describes a family of branch predictors that use confidence estimation to improve the performance of an underlying branch predictor. This method, referred to as Selective Branch Inversion (SBI), uses a confidence estimator to determine when the branch direction prediction is likely to be incorrect; branch decisions for these low-confidence branches are inverted. SBI with an underlying Gshare branch predictor outperforms other equal sized predictors such as the best history length Gshare predictor, as well as equally complex McFarling and Bi-Mode predictors. Our analysis shows that SBI achieves its performance through conflict detection and correction, rather than through conflict avoidance as some of the previously proposed predictors such as Bi-Mode and Agree. We also show that SBI is applicable to other underlying predictors, such as the McFarling Combined predictor. Finally we show that Dynamic Inversion Monitoring (DIM) can be used as a safeguard to turn off SBI in cases where it degrades the overall performance.     

基于Asterisk的PBX设计与实现

随着计算机处理能力的不断增强,人们开始尝试将计算机应用于企业电话交换的处理中。这样在降低成本的同时,增加了许多由计算机处理带来的附加功能。Asterisk就是这样一个可应用于企业自有电话系统的开源软件,它将一台普通的PC机变身成为一台可用于企业电话交换的机器,用较小的成本完成了通常需要昂贵的交换机才能完成的任务,同时也拥有非常多的特色功能,如互动式语音应答、语音邮件、电话详情记录、呼叫中心等等。文中叙述了Asterisk的背景技术、功能模块的设计与实现的过程,并用实例说明了功能如何被达成。     

An optimization-driven approach for computing geodesic paths on triangle meshes

There are many application scenarios where we need to refine an initial path lying on a surface to be as short as possible. A typical way to solve this problem is to iteratively shorten one segment of the path at a time. As local approaches, they are conceptually simple and easy to implement, but they converge slowly and have poor performance on large scale models. In this paper, we develop an optimization driven approach to improve the performance of computing geodesic paths. We formulate the objective function as the total length and adopt the L-BFGS solver to minimize it. Computational results show that our method converges with super-linear rate, which significantly outperforms the existing methods. Moreover, our method is flexible to handle anisotropic metric, non-uniform density function, as well as additional user-specified constraints, such as coplanar geodesics and equally-spaced geodesic helical curves, which are challenging to the existing local methods.