A local geopotential model for implementation of underwater passive navigation

A main aspect of underwater passive navigation is how to identify the vehicle location on an existing gravity map, and several matching algorithms as ICCP and SITAN are the most prevalent methods that many scholars are using. In this paper, a novel algorithm that is different from matching algorithms for passive navigation is developed. The algorithm implements underwater passive navigation by directly estimating the inertial errors through Kalman filter algorithm, and the key part of this implementation is a Fourier series-based local geopotential model. Firstly, the principle of local geopotential model based on Fourier series is introduced in this paper, thus the discrete gravity anomalies data can be expressed analytically with respect to geographic coordinates to establish the observation equation required in the application of Kalman filter. Whereafter, the indicated gravity anomalies can be gotten by substituting the inertial positions to existing gravity anomalies map. Finally, the classical extended Kalman filter is introduced with the differences between measured gravity and indicated gravity used as observations to optimally estimate the errors of the inertial navigation system （INS）. This navigation algorithm is tested on simulated data with encouraging results. Although this algorithm is developed for underwater navigation using gravity data, it is equally applicable to other domains, for example vehicle navigation on magnetic or terrain data.     

The Result Integration Algorithm Based on Matching Strategy

The following paper provides a new algorithm： a result integration algorithm based on matching strategy. The algorithm extracts the title and the abstract of Web pages, calculates the relevance between the query string and the Web pages, decides the Web pages accepted, rejected and sorts them out in user interfaces. The experiment results in dieate obviously that the new algorithms improve the precision of meta-search engine. This technique is very useful to metasearch engine.     

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.     

A modified image matching algorithm based on robust Hausdorff distance

Hausdorff distance measure is one of the widely adopted feature-based image matching algo- rithms due to its simplicity and accuracy. However, it is considered that its robustness still needs to be improved. In this paper, various forms of original and improved Hausdorff distance （HD） and their limitations are studied. Focusing on robust Hausdorff distance （ RHD）, an improved RHD with an adaptive outlier point threshold selection method is proposed. Furthermore, another new form of the Hausdorff distance which possesses the merits of RHD and M-HD is prsented. Finally, a recur- sire algorithm is introduced to accelerate the image matching speed of Hausdorff algorithms. Exten- sive simulation and experiment results are presented to validate the feasibility of the proposed Haus- dorff distance algorithm.     

A New Algorithm for On-Line Handwriting Signature Verification Based on Evolutionary Computation

The paper proposes an on-line signature verification algorithm, through which test sample and template signatures can be optimizedly matched, based on evolutionary computation （EC）. Firstly, the similarity of signature curve segment is defined, and shift and scale transforms are also introduced due to the randoness of on-line signature. Secondly, this paper puts forward signature verification matching algorithm after establishment of the mathematical model. Thirdly, the concrete realization of the algorithm based on EC is discussed as well. In addition, the influence of shift and scale on the matching result is fully considered in the algorithm. Finally, a computation example is given, and the matching results between the test sample curve and the template signature curve are analyzed in detail, The preliminary experiments reveal that the type of signature verification problem can be solved by EC.     

A Semantic-aware method for polymorphic signature generation

It is difficult for security experts to generate polymorphic signatures by using traditional string mining and matching techniques.A semantic-aware method is presented to generate a kind of two-level signature that includes both polymorphic semantics and string patterns.It first analyzes the characteristics of polymorphic engines and categorizes the data flows into different clusters and then uses static data flow methods to extract invariable semantic instructions.And then,it combines traditional string methods to generate the signature.In comparison with other methods,experimental results show that it may effectively reduce false positives and false negatives.     

A Single Pattern Matching Algorithm Based on Character Frequency

Based on the study of single pattern matching, MBF algorithm is proposed by imitating the string searching procedure of human. The algorithm preprocesses the pattern by using the idea of Quick Search algorithm and the already-matched pattern psefix and suffix information. In search-ing phase, the algorithm makes use of the! character using frequency and the continue-skip idea.The experiment shows that MBF algorithm is more efficient than other algorithms.     

Memory Efficient String Matching Algorithm for Network Intrusion Management System

As the core algorithm and the most time consuming part of almost every modern network intrusion management system (NIMS), string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick (AC) algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.     

Packet matching algorithm based on improving differential evolution

The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditional algorithms. The purpose of this paper is to develop a novel algorithm of packet matching based on improving differential evolutionary algorithm, which also combines with classic packets matching algorithms to improve the performance of algorithm. For the sake of objectivity, the statistics method was used to compute the fitting value. Experiments showed that this new algorithm effectively improved the performance in the speed and storage space, as compared with the traditional one. For the first time, evolutionary algorithm is used to solve the network data packet forwarding, and packets can be forwarded at the linear speed. In addition, this new algorithm is universal, so it can be adapted for many equipment.     

A Parallel String Searching Algorithm for Information Filtering

Playing an increasingly important role in the security protection of the network information systems, the intrusion detection system (IDS) becomes a hotspot of research interest nowadays. However, this technology in the kernel to many of these systems, namely string searching algorithm, has not received enough attention. By utilizing the concurrent mechanisms (multithreading) provided by modern operation systems, such work can be divided symmetrically and thus improve the throughput of the corresponding application effectively. Presented in this work is a paralleled string searching algorithm—PBM, an algorithm based on the famous BoyerMoore (BM) string searching algorithm. Taken as a dividable process, the string searching work is distributed between many cooperating threads of execution in the PBM algorithm, while each of them searches the target pattern in their respective share of the target strings. As compared with the traditional string searching algorithms, the PBM algorithm can do the pattern matching work faster by increasing the data processing throughput, thus adapting better to the drastic increase in the network band width. A simplification of the PBM algorithm that can be used as a multistring searching algorithm is also suggested with supporting simulations, which is a promising approach when the number of target patterns is limited.     

一种基于CPU-GPU协同的特征码匹配机制

在网络安全系统中,提出了一种基于CPU-GPU协同的特征码匹配机制。先用每个特征码表达式的n前缀,构建一个小的DFA（有限自动机）;再在GPU上进行不完全匹配,剔除大量正常数据包,检测出可疑的数据包;然后再在CPU上对可疑数据包进行精确匹配。测试结果表明,该机制的匹配吞吐量能达到了19Gbits/s。     

产险公司资产负债管理的DFA方法实证分析

介绍了动态财务分析(DFA)这一主要适用于产险公司的资产负债管理工具.该工具运用Monte Carlo模拟方法在一系列不同情境下产生保险公司整体的财务结果.本文利用公共的DFA模型和中国市场上的实际数据参数化模型,建立起在中国市场上适用的DFA模型.在模拟过程中可以看出,DFA将外部环境等因素考虑进来,符合经营环境多变的情形;管理层可借由DFA模拟出的大量财务数据对公司经营状况进行分析,预测公司在未来几年中的财务进展状况,并由情景测试的方法来展示如何通过改变公司经营策略改善公司的经营状况及资产配置等.借助DFA模型可达到资产负债管理的目的,显示出其作为资产负债管理工具的巨大优势.     

DFA化简算法的一种改进方法

在深入研究DFA化简基本原理的基础上,首先给出现有分析算法（分割法）的形式化算法描述,然后证明了该算法存在着漏洞,并给出相应的解决方法。最后,借鉴时序逻辑门电路中原始状态表化简的方法,对现有分割算法进行修改,提出一种新的适用于任何DFA的化简算法——K次划分法。     

快速构建目录树的算法研究

通常使用DFA和ITA算法构造目录树,分别对这两种算法进行了时间复杂性分析,16组实验结果表明DFA算法快于ITA算法.     

快速构建目录树的算法研究

通常使用DFA和ITA算法构造目录树,本文分别对这两种算法进行了时间复杂性分析,16组实验结果表明DFA算法快于ITA算法。     

面向用户意图的SQL注入检测方法

Web程序安全的首要威胁是SQL注入攻击,动态分析技术可有效防御此类攻击.提出面向用户意图的检测方法,在程序发布前预先定义Web程序期望的所有数据库操作,在运行时拦截提交至数据库的操作,阻止不符合意图的操作.设计并实现描述数据库操作意图的语言SQLIDL,将开发者提供的允许操作集合解释为以确定有限自动机(DFA)表示的字符串集合,并支持表名、列名、列值及存储过程名的正则表示.在SecuriBench测试集的实验表明,该方法可有效检测现有SQL攻击模式且运行开销较小.     

用Horspool算法快速查找蒙古文单词

分析了蛮力字符串匹配算法、Boyer-Moore算法和Horspool算法的特点,给出用Horspool算法快速查找蒙古文单词的实现过程.用Horspool算法可以实现快速查找蒙古文单词的功能,并能在文本框中以选中状态显示查找到的单词.     

DFA House法的改进及在某产品DFA分析中的应用

本文对传统的ＤＦＡ Ｈｏｕｓｅ法进行了改进，把零件的定向特性，合适的抓取表面，装配后是否需要调整取向，过定位和多面接触这五种情况也作为评价产品装配友好性的指标纳入产品的ＤＦＡ分析之内，使改进后的ＤＦＡ Ｈｏｕｓｅ法更全面地反映出零部件的装配特性，增强了ＤＦＡＨｏｕｓｅ法引导设计者进行产品零部件再设计的功能，作者在某产品机器人化柔性自动装配线的研究中用改进后的ＤＦＡ Ｈｏｕｓｅ法对该产品进行了ＤＦＡ     

代码抄袭检测中串匹配算法的比较

对程序代码抄袭检测中多种字符串匹配算法的实现原理进行了描述,给出匹配算法计算相似度的公式以及相对应的时间复杂度。由于字符串匹配算法在程序代码抄袭检测中应用较为广泛,对其中的B-F（Brute-Force）朴素算法、LCS（Longest Common Subsequence）最长公共字串算法、GST（Greedy String Tiling）贪心字符串匹配算法等经典算法的总结比较是一件有意义的研究工作。     

基于字符串匹配和直方图分析的视频镜头检测算法研究

首先介绍了现有典型切变检测算法,然后提出一种改进的镜头切变检测算法,在字符串匹配算法的基础上用直方图法来进行二次检测.实验显示,这种方法解决了单独用字符串匹配算法造成的误检问题,取得了较好的镜头切变检测效果.