贫燃条件下汽车尾气净化催化技术的发展与展望

本文介绍了用于贫燃发动机尾气，柴油机尾气净化催化技术的发展状况，对各种催化剂及其载体材料的性能进行了比较，提出了开发贫燃条件汽车尾气净化催化技术尚需解决的问题。     

自动协议逆向工程研究综述

全面梳理了该领域国内外相关文献,归纳分析了自动协议逆向工程的研究现状和发展趋势。为了更清晰地刻画不同方法的特点和比较异同,提出一种基于协议逆向工程输出结果的分类方法,将协议逆向方法分为侧重于协议格式提取、侧重于协议状态机推断、侧重于完整协议规范描述、侧重于其他输出结果四类,并据此进行分析和比较。基于目前的进展情况和进一步的问题剖析发现,复杂交互场景分析、链路层协议逆向、加密协议分析以及协议状态机优化等应作为自动协议逆向工程领域下一步的重点研究方向。     

P2成型机简介及Interbus-s总线故障分析

简要介绍了P2成型机各部分的结构组成及电控系统的组成、Interbus-s总线的结构特点。分析了Interbus-s总线上出现的故障情况，经排查及改进PLC程序排除了故障。     

现代塑料注射成型机的操作技术

主要介绍了现代塑料注射机的操作技术,对注射机动作选择作了较详细的介绍,也简要介绍了塑料注射成型工艺的控制原则和注射机操作的注意要点,对于注射机操作过程中可能出现的问题结合实际经验进行了分析,以期对从事塑料注射成型加工的人员有所帮助。     

Multi-label core vector machine with a zero label

Multi-label core vector machine (Rank-CVM) is an efficient and effective algorithm for multi-label classification. But there still exist two aspects to be improved: reducing training and testing computational costs further, and detecting relevant labels effectively. In this paper, we extend Rank-CVM via adding a zero label to construct its variant with a zero label, i.e., Rank-CVMz, which is formulated as the same quadratic programming form with a unit simplex constraint and non-negative ones as Rank-CVM, and then is solved by Frank–Wolfe method efficiently. Attractively, our Rank-CVMz has fewer variables to be solved than Rank-CVM, which speeds up training procedure dramatically. Further, the relevant labels are effectively detected by the zero label. Experimental results on 12 benchmark data sets demonstrate that our method achieves a competitive performance, compared with six existing multi-label algorithms according to six indicative instance-based measures. Moreover, on the average, our Rank-CVMz runs 83 times faster and has slightly fewer support vectors than its origin Rank-CVM.     

Comparing techniques for authorship attribution of source code

Attributing authorship of documents with unknown creators has been studied extensively for natural language text such as essays and literature, but less so for non‐natural languages such as computer source code. Previous attempts at attributing authorship of source code can be categorised by two attributes: the software features used for the classification, either strings of n tokens/bytes (n‐grams) or software metrics; and the classification technique that exploits those features, either information retrieval ranking or machine learning. The results of existing studies, however, are not directly comparable as all use different test beds and evaluation methodologies, making it difficult to assess which approach is superior. This paper summarises all previous techniques to source code authorship attribution, implements feature sets that are motivated by the literature, and applies information retrieval ranking methods or machine classifiers for each approach. Importantly, all approaches are tested on identical collections from varying programming languages and author types. Our conclusions are as follows: (i) ranking and machine classifier approaches are around 90% and 85% accurate, respectively, for a one‐in‐10 classification problem; (ii) the byte‐level n‐gram approach is best used with different parameters to those previously published; (iii) neural networks and support vector machines were found to be the most accurate machine classifiers of the eight evaluated; (iv) use of n‐gram features in combination with machine classifiers shows promise, but there are scalability problems that still must be overcome; and (v) approaches based on information retrieval techniques are currently more accurate than approaches based on machine learning. Copyright © 2012 John Wiley & Sons, Ltd.     

On solutions to fuzzy stochastic differential equations with local martingales

This paper deals with a class of fuzzy stochastic differential equations (FSDEs) driven by a continuous local martingale under the Lipschitzian condition. Such equations can be useful in modeling hybrid systems, where the phenomena are simultaneously subjected to two kinds of uncertainties: randomness and fuzziness. The solutions of the FSDEs are the fuzzy stochastic processes, and their uniqueness is considered to be in a strong sense. Thus, the existence and uniqueness of solutions to the FSDEs under the Lipschitzian condition is first proven. Moreover, some asymptotic properties of the solutions to the FSDEs are investigated. Finally, an illustrating example on the interest term model is provided.     

异养培养光合细菌产5-氨基乙酰丙酸发酵条件的研究

从废水处理厂的活性污泥中筛选出产5 氨基乙酰丙酸(ALA)的红假单胞菌原始菌株,可产生7 35mg/L的ALA,采用亚硝基胍(NTG)以及紫外线对该菌株进行诱变处理,得到产量为19 12mg/L的菌株C-1。在摇瓶实验过程中,对培养基组成和培养条件进行了初步优化,使菌株产ALA的能力达到了38 9mg/L。     

双质体振动机的应用——浅谈解决橡胶后处理装置地基振动的方法

以降低合成橡胶生产厂后处理装置各种振动机造成的地基振动为目的,对双质体振动机的隔振效能进行了定量分析。通过生产实践,总结了单质体振动机、非平衡型双质体振动机和对称平衡型双质体振动机的优缺点,给出了后者的设计计算数据。经综合分析和生产考核,认为采用对称平衡型双质体振动机是降低地基振、降低噪音、延长振动机的运转周期和使用寿命的最佳方法。     

基于KPCA-PSO-SVM的径流预测研究

为提高径流预测模型的准确性与稳定性,对KPCA-PSO-SVM的径流预测方法进行了研究。在分析径流影响因素的基础上,利用核主成分分析(KPCA)法对径流影响因子进行非线性特征提取,获得主成分作为支持向量机(SVM)的输入变量,建立了径流预测SVM模型,其中模型参数通过粒子群算法(PSO)进行优化。模型建立后,以新疆伊犁河雅马渡站中长期径流预测为例进行分析。预测分析结果表明,在拟合和检验阶段模型的平均相对误差分别为0.77%和7.64%,与其他预测模型比较,基于KPCA-PSO-SVM方法建立的径流预测模型有较好的预测和泛化能力,是一种行之有效的中长期径流预测方法。