基于C—V模型的目标检测与提取

在目标检测与提取中,传统的蛇模型和基于活动轮廓的局部区域检测方法受到初始条件或者自身的收敛性约束的影响,不仅时间花费多,而且不具备鲁棒性。本文提出一种基于C V模型的变分水平集的目标检测与提取方法,通过大量实验验证,在花费时间和鲁棒性上得到了显著的改善。     

基于灰色关联分析法的软件缺陷类型预测

灰色关联分析法是一种描述元素之间影响程度的分析法,适合于小项目数据集。小项目数据集制约着传统的软件缺陷类型的预测方法,使得预测的结果往往不够准确和可靠。因此在灰色关联分析法的基础上提出了特征子集选择、异常工程检测以及软件缺陷类型预测3种方法。通过实验的分析对比,验证了在灰色关联分析法的基础上,提出的软件缺陷类型预测方法的准确性和可靠性。     

Towards inverse modeling of turbidity currents: The inverse lock-exchange problem

A new approach is introduced for turbidite modeling, leveraging the potential of computational fluid dynamics methods to simulate the flow processes that led to turbidite formation. The practical use of numerical flow simulation for the purpose of turbidite modeling so far is hindered by the need to specify parameters and initial flow conditions that are a priori unknown. The present study proposes a method to determine optimal simulation parameters via an automated optimization process. An iterative procedure matches deposit predictions from successive flow simulations against available localized reference data, as in practice may be obtained from well logs, and aims at convergence towards the best-fit scenario. The final result is a prediction of the entire deposit thickness and local grain size distribution. The optimization strategy is based on a derivative-free, surrogate-based technique. Direct numerical simulations are performed to compute the flow dynamics. A proof of concept is successfully conducted for the simple test case of a two-dimensional lock-exchange turbidity current. The optimization approach is demonstrated to accurately retrieve the initial conditions used in a reference calculation.     

On detecting active worms with varying scan rate

Active worms have posed a major security threat to the Internet and many research efforts have focused on them. However, defending against them remains challenging due to their continuous evolution. In this paper, we study a new class of defense-oriented evolved worms, the Varying Scan Rate worm (the VSR worm in short). In order to circumvent detection by existing worm detection schemes, the VSR worm deliberately varies its scan rate according to these schemes’ weaknesses. To counteract the VSR worm, we design a new worm-detection scheme, the attack-target Distribution Entropy-based Dynamic detection scheme (DED detection for short). DED detection utilizes the attack-target distribution and robust statistical feature in conjunction with dynamic decision adaptation to distinguish worm-scan traffic from non-worm-scan traffic. We present a comparatively complete space of detection schemes and conduct extensive performance evaluations on the DED detection scheme compared with other schemes, using real-world Internet traces as background scan traffic. Our data clearly demonstrate the effectiveness of the DED detection scheme in detecting both the VSR worm and the traditional worm.     

On the estimation of adequate test set size using fault failure rates

Test set size in terms of the number of test cases is an important consideration when testing software systems. Using too few test cases might result in poor fault detection and using too many might be very expensive and suffer from redundancy. We define the failure rate of a program as the fraction of test cases in an available test pool that result in execution failure on that program. This paper investigates the relationship between failure rates and the number of test cases required to detect the faults. Our experiments based on 11 sets of C programs suggest that an accurate estimation of failure rates of potential fault(s) in a program can provide a reliable estimate of adequate test set size with respect to fault detection and should therefore be one of the factors kept in mind during test set construction. Furthermore, the model proposed herein is fairly robust to incorrect estimations in failure rates and can still provide good predictive quality. Experiments are also performed to observe the relationship between multiple faults present in the same program using the concept of a failure rate. When predicting the effectiveness against a program with multiple faults, results indicate that not knowing the number of faults in the program is not a significant concern, as the predictive quality is typically not affected adversely.     

Collision and intersection detection of two ruled surfaces using bracket method

Collision and intersection detection of surfaces is an important problem in computer graphics and robotic engineering. A key idea of our paper is to use the bracket method to derive the necessary and sufficient conditions for the collision of two ruled surfaces. Then the numerical intersection curve can be characterized. The cases for two bounded ruled surfaces are also discussed.     

抑制噪声的问题探索

本论文是探讨脉冲探测技术的,探讨了两个问题：要求实现信噪比的改善,最后形成高灵敏度的探测系统;在白噪声中探测宽度为τ的脉冲信号问题。     

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

This work constitutes a theoretical study of the edge-detection method by means of the Jensen-Shannon divergence, as proposed by the authors. The overall aim is to establish formally the suitability of the procedure of edge detection in digital images, as a step prior to segmentation. In specific, an analysis is made not only of the properties of the divergence used, but also of the method's sensitivity to the spatial variation, as well as the detection-error risk associated with the operating conditions due to the randomness of the spatial configuration of the pixels. Although the paper deals with the procedure based on the Jensen-Shannon divergence, some problems are also related to other methods based on local detection with a sliding window, and part of the study is focused to noisy and textured images.     

入侵检测系统发展简述

入侵检测系统是目前信息安全系统中的一个重要组成部分,该文简述了其二十多年的主要发展历程,对其使用的技术以及未来的发展方向进行了简要介绍。     

入侵检测系统研究分析

入侵检测是保障现代网络安全的关键技术之一。对于像军队这样对安全要求很高的网络,入侵检测技术以及系统将会起到至关重要的作用。本文对入侵检测的基本概念、方法以及发展趋势进行了分析与研究。