提高可移动存储设备管理系统安全运行的方案

可移动存储设备管理系统在运行时会面临攻击者采用任务管理器或第三方工具强行关闭的攻击,可能导致应用程序无法正常运行。为解决这类应用程序安全运行的问题,提出一种融合进程隐藏和进程守护技术的可移动存储设备管理系统安全运行方案。该方案利用改进的远程线程注入技术提高系统隐蔽性,利用双守护进程的两级监控体系提高系统健壮性,从而达到维护程序安全运行的目的。应用结果表明,该方案能够很好地抵抗强行关闭攻击。     

基于C语言的在线编程代码缺陷检测系统研究

C语言程序代码设计中可能会出现词法缺陷、逻辑缺陷、语法缺陷,在传统模式下主要由程序开发人员根据电子集成驱动器(Integrated Drive Electronics,IDE)编程工具、GNU编译器套件(GNU Compiler Collection,GCC)编译结果检查代码中的错误。研究设计了一种可自动检测代码缺陷的综合管理系统,其核心组成部分为知识库和代码缺陷分析器。利用GCC、开源的代码检测软件、正则表达式匹配错误模式,出具评价报告,并向编程者推荐具有针对性的学习内容,以纠正其错误的编程知识和编程习惯。     

开发者的人品问题

程序员都知道：绝大多数编程-中的问题,最终都是自己的人品问题。当遇到奇怪的问题时,我们总是喜欢怀疑系统、怀疑编译器、怀疑网络、怀疑硬件……就是不愿意怀疑自己的人品。熬过几个不眠之夜后,最终还是发现自己的代码存在人品问题。只有极少数的情况才是系统的问题。     

自己动手写IDE——NetBeans上Scala支持的实现

Scala源自瑞士洛桑联邦理工学院由Martin Odersky教授领导的编程方法实验室,是一门能运行在JVM或．Net上的编程语言。自2003年底发布1．0版本至今已经过去近5年时间,但直到最近一年来才被越来越多的人关注。     

不用代码，轻松制作《愤怒的小鸟》

随着《愤怒的小鸟》这款游戏的不断更新,许多开发者也打起了“抄袭”的主意。跟我同办公室的一个刚学编程的哥们小王某日自言自语道：“我到底什么时候才能‘开花’出自己的《愤怒的小鸟》呢？”恰好我从他身边路过,听见了这话,对他说：“这还不简单,跟我来,哥教你不用代码做‘小鸟’!”     

基于Linux系统的构建高性能服务器的研究

研究了在Linux环境下构建高性能服务器的关键技术,Reactor,Proactor事件处理模式,处理并发访问量的并发模式,考虑到现代硬件技术的发展,以空间换时间的思想构建高性能服务器,在理论研究的基础上,最后在Linux环境下设计了一个Web服务器,构建过程中充分利用了研究的高性能知识,并通过压力测试进行仿真验证,并分析仿真数据,证明构建的服务器是可以承受一定的高并发访问的。     

1秒钟的快速启动

得到业界广泛支持的Google Android平台,以其开放式设计,使每个开发者都能获取Android平台源代码及开发SDK。随着移动终端设备的普及和性能提升,未来在手持设备上的应用程序或许会超过PC上运     

ConEntity:一种基于进程的自主并发实体编程模型及其实现

本文在虚拟计算环境之上,研究支持具有自主能力、高并发的新型互联网应用开发方法,在已有的基于进程、面向并发的编程模型中引入实体建模机制,扩展出一种兼具进程和自主并发实体的程序设计模型ConEntity,并给出了形式化定义和描述.ConEntity模型具有表达性、并发性和可伸缩性的特点,能对虚拟计算环境资源高效、透明访问.通过扩展Erlang/OTP将其实现为Erlang语言设施UniAgent.本文的模型为在虚拟计算环境上快速直接构建具有自主、高并发能力实体的新型互联网应用提供了模型和语言上的支持.     

Ruby并发之谜与多语Ruby

GIL限制了Ruby的多线程并发能力。多进程是一种答案,Ruby与Erlang并用的多语编程可能是另一种答案。     

C语言编程中优化代码运行效率的方法探究

C语言是编程技术中最常见的高级程序开发语言.因其卓越的代码运行效率和良好的可移植性,C语言被广泛用于操作系统开发、计算机视觉处理、3D场景合成、人工智能等对实时性要求苛刻的软件开发领域.本文以计算机程序的运行效率为研究突破点,从高性能计算出发挖掘影响程序运行效率的因素,就C语言程序优化问题从多个方面进行深入的分析和探讨...     

Software transactional memories for Scala

Transactional memory is an alternative to locks for handling concurrency in multi-threaded environments. Instead of providing critical regions that only one thread can enter at a time, transactional memory records sufficient information to detect and correct for conflicts if they occur. This paper surveys the range of options for implementing software transactional memory in Scala. Where possible, we provide references to implementations that instantiate each technique. As part of this survey, we document for the first time several techniques developed in the implementation of Manchester University Transactions for Scala. We order the implementation techniques on a scale moving from the least to the most invasive in terms of modifications to the compilation and runtime environment. This shows that, while the less invasive options are easier to implement and more common, they are more verbose and invasive in the codes using them, often requiring changes to the syntax and program structure throughout the code.     

基于Scala的电影推荐系统的设计与实现

为解决在大数据环境下,网络信息快速膨胀导致的“信息过载”问题,即用户无法从海量信息中快速准确获取有用信息。提出在基于Scala语言的Spark平台下,运用基于模型的协同过滤推荐算法,通过分析样本用户对电影的评分数据,建立电影的向量模型,最后根据与实时的用户数据的对比对用户进行电影推荐。实验结果表明基于模型的协同过滤算法的电影推荐系统能够准确地为用户推荐电影信息。     

Scala Actors: Unifying thread-based and event-based programming

There is an impedance mismatch between message-passing concurrency and virtual machines, such as the JVM. VMs usually map their threads to heavyweight OS processes. Without a lightweight process abstraction, users are often forced to write parts of concurrent applications in an event-driven style which obscures control flow, and increases the burden on the programmer.In this paper we show how thread-based and event-based programming can be unified under a single actor abstraction. Using advanced abstraction mechanisms of the Scala programming language, we implement our approach on unmodified JVMs. Our programming model integrates well with the threading model of the underlying VM.     

Scala and Lift Functional Recipes for the Web

Today, there's significant interest in functional languages and frameworks that fit the Web better than imperative languages. We explore Scala, an OO-functional language on the Java virtual machine, and Lift, a framework implemented on Scala's functional features. The Scala language offers functional programming features and asynchronous message-passing concurrency alongside a statically typed model. Lift exploits this model to offer secure, higher-level abstractions to Web developers.     

Business engagement on Twitter: a path analysis

Social media services, such as Twitter, enable commercial businesses to participate actively in online word-of-mouth communication. In this project, we examined the potential influences of business engagement in online word-of-mouth communication on the level of consumers’ engagement and investigated the trajectories of a business’ online word-of-mouth message diffusion in the Twitter community. We used path analysis to examine 164,478 tweets from 96,725 individual Twitter users with regards to nine brands during a 5-week study period. We operationalized business engagement as the amount of online word-of-mouth messages from brand and the number of consumers the brand follows. We operationalized consumers’ engagement as the number of online word-of-mouth messages from consumers both connecting to the brand and having no connection with the brand as well as the number of consumers following the brand. We concluded that the business engagement on Twitter relates directly to consumers’ engagement with online word-of-mouth communication. In addition, retweeting, as an explicit way to show consumers’ response to business engagement, indicates that the influence only reaches consumers with a second-degree relationship to the brand and that the life cycle of a tweet is generally 1.5 to 4 hours at most. Our research has critical implications in terms of advancing the understanding of the business’s role in the online word-of-mouth communication and bringing insight to the analytics of social networks and online word-of-mouth message diffusion patterns.     

基于微博产业下的互联网安全问题初探

该文首先简要介绍了微博的特点、优势以及发展现状,针对微博产业在快速发展过程中所存在的各种问题进行了系统性的分析和梳理。最后该文结合微博自身特点,提出了可行的有效治理方案。     

基于序列卷积网络的Twitter情感分类

为解决传统用于文本分类等时序性问题的循环神经网络无法留住长远记忆及模型框架复杂的问题,提出一种基于序列卷积神经网络的分类模型。利用卷积的思想处理时序性问题,将因果卷积和扩张卷积结合作为卷积层来保证网络具有足够大的感受野,应用残差模块和批处理加深神经网络并消除层数增加误差增大和模型难训练的问题,用卷积层代替全连接层以改善网络特征选取的局限性。实验结果表明,序列卷积分类模型用于Twitter情感分类任务中可获得更优的分类效果,验证了卷积网络的思想可以处理时序性问题。     

Twitter summarization with social-temporal context

Twitter is one of the most popular social media platforms for online users to create and share information. Tweets are short, informal, and large-scale, which makes it difficult for online users to find reliable and useful information, arising the problem of Twitter summarization. On the one hand, tweets are short and highly unstructured, which makes traditional document summarization methods difficult to handle Twitter data. On the other hand, Twitter provides rich social-temporal context beyond texts, bringing about new opportunities. In this paper, we investigate how to exploit social-temporal context for Twitter summarization. In particular, we provide a methodology to model temporal context globally and locally, and propose a novel unsupervised summarization framework with social-temporal context for Twitter data. To assess the proposed framework, we manually label a real-world Twitter dataset. Experimental results from the dataset demonstrate the importance of social-temporal context in Twitter summarization.