Length 3 Edge-Disjoint Paths Is NP-Hard

In 2003, it was claimed that the following problem was solvable in polynomial time: do there exist k edge-disjoint paths of length exactly 3 between vertices s and t in a given graph? The proof was flawed, and in this note we show that this problem is NP-hard. We use a reduction from Partial Orientation, a problem recently shown by Pálv?lgyi to be NP-hard.     

Saving Support-Checks Does Not Always Save Time

Arc-consistency algorithms are the workhorse of backtrackers that maintain arc-consistency (MAC). This paper will provide experimental evidence that, despite common belief to the contrary, it is not always necessary for a good arc-consistency algorithm to have an optimal worst-case time-complexity. Sacrificing this optimality allows MAC solvers that (1) do not need additional data structures during search, (2) have an excellent average time-complexity, and (3) have a space-complexity that improves significantly on that of MAC solvers that have optimal arc-consistency components. Results will be presented from an experimental comparison between MAC-2001, MAC-3 _d and related algorithms. MAC-2001 has an arc-consistency component with an optimal worst-case time-complexity, whereas MAC-3 _d does not. MAC-2001 requires additional data structures during search, whereas MAC-3 _d does not. MAC-3 _d has a O(e+nd) of space-complexity, where n is the number of variables, d the maximum domain size, and e the number of constraints. We shall demonstrate that MAC-2001's space-complexity is O(edmin(n,d)). Our experimental results indicate that MAC-2001 was slower than MAC-3 _d for easy and hard random problems. For real-world problems things were not as clear.     

Solving Linear Interval Systems Is NP-Hard Even If We Exclude Overflow and Underflow

Reliable Computing -     

不拿"闪跳"当借口

到现在这家公司以前,我已经跳槽多次,用时髦的说法,算一个"闪跳族". 　　至于为什么跳槽,还不是想找一个更好的工作吗?所以,父母、同学觉得我"跳"得太频时,我都不以为然--我期望人生可以像一把扑克牌,一次抓不到好牌,那就重新洗牌,重新来抓.找工作也是这样,这次不好,那就换一个.……     

不拿“闪跳”当借口

到现在这家公司以前,我已经跳槽多次,用时髦的说法,算一个“闪跳族”。     

不拿“闪跳”当借口

<正>到现在这家公司以前,我已经跳槽多次,用时髦的说法,算一个"闪跳族"。至于为什么跳槽,还不是想找一个更好的工作吗?所以,父母、同学觉得我"跳"得太频时,我都不以为然——我期望人生可以像一把扑克牌,一次抓不到好牌,那就重新洗牌,重新来抓。找工作也是这样,这次不好,那就换一个。到现在这家公司上班是我心仪已久的     

A Process That Is Not

TikiWiki is a large open source project that embraces Eric Raymond's Bazaar model. TikiWiki is highly successful, yet it adopts a process that lacks many of the characteristics that are thought to be necessary for projects of comparable size and complexity. The article discusses TikiWiki's development in the context of these characteristics.     

TEAM SIZE AND PRODUCTIVITY IN SYSTEMS DEVELOPMENT Bigger Does Not Always Mean Better

Abstract

IS managers know that the performance of individuals in systems development groups changes under various circumstances. People often have lower performance levels in groups than their individual capabilities would indicate. This article examines the effect of team size on systems development productivity and overall job performance and recommends techniques to mitigate the negative effects of large team size through the use of such tools and techniques as computer-aided software engineering and object-oriented programming.     

TEAM SIZE AND PRODUCTIVITY IN SYSTEMS DEVELOPMENT Bigger Does Not Always Mean Better

IS managers know that the performance of individuals in systems development groups changes under various circumstances. People often have lower performance levels in groups than their individual capabilities would indicate. This article examines the effect of team size on systems development productivity and overall job performance and recommends techniques to mitigate the negative effects of large team size through the use of such tools and techniques as computer-aided software engineering and object-oriented programming.     

基于联合分布的多标记迁移学习

针对现有的多标记迁移学习忽略条件分布而导致泛化能力不足的问题,设计了一种基于联合分布的多标记迁移学习（Multi-label Transfer Learning via Joint Distribution Alignment,J-MLTL）。分解原始特征生成特征子空间,在子空间中计算条件分布的权重系数,最小化跨领域数据的边际分布和条件分布差异;此外,为了防止标记内部结构信息损失,利用超图对具有多个相同标签的数据进行连接,保持领域内几何流行结构不受领域外知识结构的影响,进一步最小化领域间的分布差异。实验结果表明,相比于已有多标记迁移学习算法在分类精度方面具有显著提升。     

基于对抗式分布对齐的跨域方面级情感分析

跨领域情感分类任务旨在利用富含情感标签的源域数据对缺乏标签的目标域数据进行情感极性分析.由此,文中提出基于对抗式分布对齐的跨域方面级情感分类模型,利用方面词与上下文的交互注意力学习语义关联,基于梯度反转层的领域分类器学习共享的特征表示.利用对抗式训练扩大领域分布的对齐边界,有效缓解模糊特征导致错误分类的问题.在Seme...     

基于动态分布对齐和伪标签学习的跨项目缺陷预测

跨项目缺陷预测(cross-project defect prediction, CPDP)已经成为软件工程和数据挖掘领域的一个重要研究方向, 利用其他数据丰富项目的缺陷代码来建立预测模型, 解决了模型构建过程中的数据不足问题. 然而源项目和目标项目的代码文件之间存在的分布差异, 导致跨项目预测效果不佳. 大多数研究采用域适应方法来解决这一问题, 但是现有的方法一方面只考虑了条件分布或边缘分布对缺陷预测的影响, 忽视了其动态性; 另一方面没有选择合适的伪标签. 基于上述两个方面, 本文提出了一种基于动态分布对齐和伪标签学习的跨项目缺陷预测方法(DPLD). 具体来说, 我们通过对抗域适应方法分别在域对齐和类别对齐模块中减小项目间的边缘分布差异和条件分布差异, 并借助动态分布因子动态、定量地描述了两种分布的相对重要性. 此外, 本文也提出了一种伪标签学习方法, 通过数据间的几何相似性来增强伪标签作为真实标签的准确性. 本文在PROMISE数据集上进行了实验, F-measure和AUC的值分别提升了22.98%、15.21%, 表明了本文方法在减小项目间分布差异、提升跨项目缺陷预测性能上的有效性.     

Why CASE Is Not a Cure for Testing

Although systems development testing is a critical ingredient in the successful design of a system, it is often regarded as an unnecessary effort needed only to correct errors on poorly designed (or unlucky) systems. The author explains why testing is, in fact, the one constant element of systems development that must be performed more often and why computer-aided software engineering (CASE) does not eliminate the need for testing.     

Security Is All About Business,Not Technology

Abstract

The year 2001 has been an adventure all right: stock market dives, missed revenue and earnings targets, shocking and tragic acts of physical terrorism, massive layoffs. The playing field in the technical infrastructure and security marketplace was leveled — a scorched earth policy swept away both profits and people on most corporate balance sheets. Nothing positive to promote out of that, except one thing: business reality. And if I do see a silver lining in the cloudy quarters ahead, I think it will be more security-aware corporate spending and more efficient use of technology and people. There is no room for excess in today's economy but progress must continue in the area of security.     

融合人名知识分布特征的汉泰双语人名对齐

双语人名对齐方法研究直接影响到跨语言信息处理的效果,由于泰语与汉语的发音差异大,汉泰双语平行语料库资源有限,基于统计的音译人名对齐模型难以解决汉泰双语人名对齐问题,提出一种在音译特征基础上融合人名知识分布特征相似性的汉泰双语人名对齐方法。计算双语人名音译相似度特征,通过卡方检验等计算汉语人名与泰语人名的知识分布相似度特征,借助支持向量机学习汉泰人名翻译对的两种特征生成人名翻译对分类器,对分类器分类结果调优生成对齐结果。实验结果表明该方法在汉泰人名发音差异大和缺少双语语料资源支持的情况下取得了较好效果。