Spectral element modelling of wave propagation with boundary and structural discontinuity reflections

Spectral element method is very efficient in modelling high-frequency stress wave propagation because it works in the frequency domain. It does not need to use very fine meshes in order to capture high frequency wave energy as the time domain methods do, such as finite element method. However, the conventional spectral element method requires a throw-off element to be added to the structural boundaries to act as a conduit for energy to transmit out of the system. This makes the method difficult to model wave reflection at boundaries. To overcome this limitation, imaginary spectral elements are proposed in this study, which are combined with the real structural elements to model wave reflections at structural boundaries. The efficiency and accuracy of this proposed approach is verified by comparing the numerical simulation results with measured results of one dimensional stress wave propagation in a steel bar. The method is also applied to model wave propagation in a steel bar with not only boundary reflection, but also reflections from single and multiple cracks. The reflection and transmission coefficients, which are obtained from the discrete spring model, are adopted to quantify the discontinuities. Experimental tests of wave propagation in a steel bar with one crack of different depths are also carried out. Numerical simulations and experimental results show that the proposed method is effective and reliable in modelling wave propagation in one-dimensional waveguides with reflections from boundary and structural discontinuities. The proposed method can be applied to effectively model stress wave propagation for structural damage detection.

Modeling of light propagation through biological tissues : a novel approach

An efficient numerical technique for modeling biological tissues using the radiative transfer equation is presented. Time dependence of the transient radiative transfer equation is approximated using Laguerre expansion. Azimuthal angle is discretized using the discrete ordinates method and the resulting set of ordinary differential equations is solved using the Runge-Kutta-Felhberg method.

An approximate numerical technique for characterizing optical pulse propagation in inhomogeneous biological tissue

An approximate numerical technique for modeling optical pulse propagation through weakly scattering biological tissue is developed by solving the photon transport equation in biological tissue that includes varying refractive index and varying scattering/absorption coefficients. The proposed technique involves first tracing the ray paths defined by the refractive index profile of the medium by solving the eikonal equation using a Runge-Kutta integration algorithm. The photon transport equation is solved only along these ray paths, minimizing the overall computational burden of the resulting algorithm. The main advantage of the current algorithm is that it enables to discretise the pulse propagation space adaptively by taking optical depth into account. Therefore, computational efficiency can be increased without compromising the accuracy of the algorithm.

Laguerre Runge-Kutta-Fehlberg method for simulating laser pulse propagation in biological tissue

An efficient algorithm for solving the transient radiative transfer equation for laser pulse propagation in biological tissue is presented. A Laguerre expansion is used to represent the time dependency of the incident short pulse. The Runge–Kutta– Fehlberg method is used to solve the intensity. The discrete ordinates method is used to discretize with respect to azimuthal and zenith angles. This method offers the advantages of representing the intensity with a high accuracy using only a few Laguerre polynomials, and straightforward extension to inhomogeneous media. Also, this formulation can be easily extended for solving the 2-D and 3-D transient radiative transfer equations.

The microcosmic model of worm propagation

Each year, large amounts of money and labor are spent on patching the vulnerabilities in operating systems and various popular software to prevent exploitation by worms. Modeling the propagation process can help us to devise effective strategies against those worms' spreading. This paper presents a microcosmic analysis of worm propagation procedures. Our proposed model is different from traditional methods and examines deep inside the propagation procedure among nodes in the network by concentrating on the propagation probability and time delay described by a complex matrix. Moreover, since the analysis gives a microcosmic insight into a worm's propagation, the proposed model can avoid errors that are usually concealed in the traditional macroscopic analytical models. The objectives of this paper are to address three practical aspects of preventing worm propagation: (i) where do we patch? (ii) how many nodes do we need to patch? (iii) when do we patch? We implement a series of experiments to evaluate the effects of each major component in our microcosmic model. Based on the results drawn from the experiments, for high-risk vulnerabilities, it is critical that networks reduce the number of vulnerable nodes to below 80%. We believe our microcosmic model can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

Modeling worms propagation on probability

There are the two common means for propagating worms: scanning vulnerable computers in the network and sending out malicious email attachments. Modeling the propagation of worms can help us understand how worms spread and devise effective defence strategies. Most traditional models simulate the overall scale of infected network in each time tick, making them invalid for examining deep inside the propagation procedure among individual nodes. For this reason, this paper proposes a novel probability matrix to model the propagation mechanism of the two main classes of worms (scanning and email worms) by concentrating on the propagation probability. The objective of this paper is to access the spreading and work out an effective scheme against the worms. In order to evaluate the effects of each major component in our probability model, we implement a series of experiments for both worms. From the results, the network administrators can make decision on how to reduce the number of vulnerable nodes to a certain threshold for scanning worms, and how to immunize the highly-connected node for preventing worm's propagation for email worms.

The probability model of peer-to-peer botnet propagation

Active Peer-to-Peer worms are great threat to the network security since they can propagate in automated ways and flood the Internet within a very short duration. Modeling a propagation process can help us to devise effective strategies against a worm's spread. This paper presents a study on modeling a worm's propagation probability in a P2P overlay network and proposes an optimized patch strategy for defenders. Firstly, we present a probability matrix model to construct the propagation of P2P worms. Our model involves three indispensible aspects for propagation: infected state, vulnerability distribution and patch strategy. Based on a fully connected graph, our comprehensive model is highly suited for real world cases like Code Red II. Finally, by inspecting the propagation procedure, we propose four basic tactics for defense of P2P botnets. The rationale is exposed by our simulated experiments and the results show these tactics are of effective and have considerable worth in being applied in real-world networks.

Using interaction signatures to find and label chairs and floors

The use of interaction signatures to recognize objects without considering the object's physical structure is discussed. Without object recognition, smart homes cannot make full use of video cameras because vision systems cannot provide object-related context to the human activities monitored. One important advantage of interaction signatures is that people frequently and repeatedly interact with household objects, so the system can build evidence for object locations and labels.

Locating defense positions for thwarting the propagation of topological worms

A common view for the preferable positions of thwarting worm propagation is at the highly connected nodes. However, in certain conditions, such as when some popular users (highly connected nodes in the network) have more vigilance on the malicious codes, this may not always be the truth. In this letter, we propose a measure of betweenness and closeness to locate the most suitable positions for slowing down the worm propagation. This work provides practical values to the defense of topological worms.

Modeling and defense against propagation of worms in networks

Worms are widely believed to be one of the most serious challenges in network security research. In order to prevent worms from propagating, we present a microcosmic model, which can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.