The traditional worms such as Blaster, Code Red, Slammer and Sasser, are still infecting vulnerable machines on the internet. They will remain as significant threats due to their fast spreading nature on the internet. Various traditional worms attack pattern has been analyzed from various logs at different OSI layers such as victim logs, attacker logs and IDS alert log. These worms attack patte...

In order to solve the problem that it is difficult combine path planning with navigation rules in process of multi-ship collision avoidance wide waters, a step-by-step algorithm proposed this paper. Firstly, obstacle ship regarded as static obstacle, and carried out by using particle swarm optimization polar coordinate space combined field safety obtain turning point avoidance. Then, steering a...

Last time, we investigated the fourth-order Runge-Kutta method. We saw that the computations involved in performing this approximation were less than ideal. To create more computationally viable methods, we introduced multistep methods, in which the approximation at a given point is obtained using only the values of the differential equation to be approximated and the approximation itself at pr...

Depth maps are used in many applications, e.g. 3D television, stereo matching, segmentation, etc. Often, depth maps are available at a lower resolution compared to the corresponding image data. For these applications, depth maps must be upsampled to the image resolution. Recently, joint bilateral filters are proposed to upsample depth maps in a single step. In this solution, a high-resolution o...

Nested multi-step stochastic correction offers a possibility to improve updating algorithms for numerical simulations of lattice gauge theories with fermions. The corresponding generalisations of the two-step multi-boson (TSMB) algorithm as well as some applications with hybrid Monte Carlo (HMC) algorithms are considered.

We provide a uniform framework for learning against a recent history adversary in arbitrary repeated bimatrix games, by modeling such an agent as a Markov Decision Process. We focus on learning an optimal non-stationary policy in such an MDP over a finite horizon and adapt an existing efficient Monte Carlo based algorithm for learning optimal policies in such MDPs. We show that this new efficie...

Multi-step planning is a promising technique for solving complex manipulation problems directly in the state space of the object, however, previous formulations were too slow to be practical except on problems with small search spaces. In this paper we propose and demonstrate two optimizations for this technique that together yield a significant speed-up on a previously used benchmark problem. ...

In this paper, we propose a multi-step stacked learning model for disfluency detection. Our method incorporates refined n-gram features step by step from different word sequences. First, we detect filler words. Second, edited words are detected using n-gram features extracted from both the original text and filler filtered text. In the third step, additional n-gram features are extracted from e...

In this work we study some properties of the twofold integral and, in particular, its relation with the 2-step Choquet integral. First, we prove that the Sugeno integral can be represented as a 2-step Choquet integral. Then, we turn into the twofold integral studying some of its properties, establishing relationships between this integral and the Choquet and Sugeno ones and proving that it can ...