963 resultados para electronics
Resumo:
Phishing, a form of on-line identity theft, is a major problem worldwide, accounting for more than $7.5 Billion in losses in the US alone between 2005 and 2008. Australia was the first country to be targeted by Internet bank phishing in 2003 and continues to have a significant problem in this area. The major cyber crime groups responsible for phishing are based in Eastern Europe. They operate with a large degree of freedom due to the inherent difficulties in cross border law enforcement and the current situation in Eastern Europe, particularly in Russia and the Ukraine. They employ highly sophisticated and efficient technical tools to compromise victims and subvert bank authentication systems. However because it is difficult for them to repatriate the fraudulently obtained funds directly they employ Internet money mules in Australia to transfer the money via Western Union or Money gram. It is proposed a strategy, which firstly places more focus by Australian law enforcement upon transactions via Western Union and Money gram to detect this money laundering, would significantly impact the success of the Phishing attack model. This combined with a technical monitoring of Trojan technology and education of potential Internet money mules to avoid being duped would provide a winning strategy for the war on phishing for Australia.
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Recently, botnet, a network of compromised computers, has been recognized as the biggest threat to the Internet. The bots in a botnet communicate with the botnet owner via a communication channel called Command and Control (C & C) channel. There are three main C & C channels: Internet Relay Chat (IRC), Peer-to-Peer (P2P) and web-based protocols. By exploiting the flexibility of the Web 2.0 technology, the web-based botnet has reached a new level of sophistication. In August 2009, such botnet was found on Twitter, one of the most popular Web 2.0 services. In this paper, we will describe a new type of botnet that uses Web 2.0 service as a C & C channel and a temporary storage for their stolen information. We will then propose a novel approach to thwart this type of attack. Our method applies a unique identifier of the computer, an encryption algorithm with session keys and a CAPTCHA verification.
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Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.
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Whole System Design is increasingly being seen as one of the most cost effective ways to both increase the productivity and reduce the negative environmental impacts of an engineered system. A focus on design is critical, as the output from this stage of the project locks-in most of the economic and environmental performance of the designed system throughout its life, which can span from a few years to many decades. Indeed, it is now widely acknowledged that all designers – particularly engineers, architects and industrial designers – need to be able to understand and implement a whole system design approach. This book provides a clear design methodology, based on leading efforts in the field, and is supported by worked examples that demonstrate how advances in energy, materials and water productivity can be achieved through applying an integrated approach to sustainable engineering. Chapters 1–5 outline the approach and explain how it can be implemented to enhance the established Systems Engineering framework. Chapters 6–10 demonstrate, through detailed worked examples, the application of the approach to industrial pumping systems, passenger vehicles, electronics and computer systems, temperature control of buildings, and domestic water systems.
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In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind steganalysis.
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In this research, we introduce an approach to enhance the discriminative capability of features by employing image-to-image variation minimization. In order to minimize image-to-image variation, we will estimate the cover image from the stego image by decompressing the stego image, transforming the decompressed image and recompressing back. Since the effect of the embedding operation in an image steganography is actually a noise adding process to the image, applying these three processes will smooth out the noise and hence the estimated cover image can be obtained.
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A nonlinear finite element analysis was carried out to investigate the viscoplastic deformation of solder joints in a ball grid array (BGA) package under temperature cycle. The effects of constraint on print circuit board (PCB) and stiffness of substrate on the deformation behaviour of the solder joints were also studied. A relative damage stress was adopted to analyze the potential failure sites in the solder joints. The results indicated that high inelastic strain and strain energy density were developed in the joints close to the package center. On the other hand, high constraint and high relative damage stress were associated with the joint closest to the edge of the silicon chip. The joint closest to the edge of the silicon chip was regarded as the most susceptible failure site if cavitation instability is the dominant failure mechanism. Increase the external constraint on the print circuit board (PCB) causes a slight increase in stress triaxiality (m/eq) and relative damage stress in the joint closest to the edge of silicon die. The relative damage stress is not sensitive to the Young’s modulus of the substrate.
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A comparison of relay power minimisation subject to received signal-to-noise ratio (SNR) at the receiver and SNR maximisation subject to the total transmitted power of relays for a typical wireless network with distributed beamforming is presented. It is desirable to maximise receiver quality-of-service (QoS) and also to minimise the cost of transmission in terms of power. Hence, these two optimisation problems are very common and have been addressed separately in the literature. It is shown that SNR maximisation subject to power constraint and power minimisation subject to SNR constraint yield the same results for a typical wireless network. It proves that either one of the optimisation approaches is sufficient.
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In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.
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In extreme weather conditions, thrusters on ships and rigs may be subject to severe thrust losses caused by ventilation and in-and-out-of-water events. When a thruster ventilates, air is sucked down from the surface and into the propeller. In more severe cases, parts of or even the whole propeller can be out of the water. These losses vary rapidly with time and cause increased wear and tear in addition to reduced thruster performance. In this paper, a thrust allocation strategy is proposed to reduce the effects of thrust losses and to reduce the possibility of multiple ventilation events. This thrust allocation strategy is named antispin thrust allocation, based on the analogous behavior of antispin wheel control of cars. The proposed thrust allocation strategy is important for improving the life span of the propulsion system and the accuracy of positioning for vessels conducting station keeping in terms of dynamic positioning or thruster-assisted position mooring. Application of this strategy can result in an increase of operational time and, thus, increased profitability. The performance of the proposed allocation strategy is demonstrated with experiments on a model ship.
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In this note, we present a method to characterize the degradation in performance that arises in linear systems due to constraints imposed on the magnitude of the control signal to avoid saturation effects. We do this in the context of cheap control for tracking step signals.
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This paper considers the manoeuvring of underactuated surface vessels. The control objective is to steer the vessel to reach a manifold which encloses a waypoint. A transformation of configuration variables and a potential field are used in a Port-Hamiltonian framework to design an energy-based controller. With the proposed controller, the geometric task associated with the manoeuvring problem depends on the desired potential energy (closed-loop) and the dynamic task depends on the total energy and damping. Therefore, guidance and motion control are addressed jointly, leading to model-energy-based trajectory generation.
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This paper presents a novel control strategy for velocity tracking of Permanent Magnet Synchronous Machines (PMSM). The model of the machine is considered within the port-Hamiltonian framework and a control is designed using concepts of immersion and invariance (I&I) recently developed in the literature. The proposed controller ensures internal stability and output regulation, and it forces integral action on non-passive outputs.
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This paper discusses a method to quantify robust autonomy of Uninhabited Vehicles and Systems (UVS) in aerospace, marine, or land applications. Based on mission-vehicle specific performance criteria, we define an system utility function that can be evaluated using simulation scenarios for an envelope of environmental conditions. The results of these evaluations are used to compute a figure of merit or measure for operational efectiveness (MOE). The procedure is then augmented to consider faults and the performance of mechanisms to handle these faulty operational modes. This leads to a measure of robust autonomy (MRA). The objective of the proposed figures of merit is to assist in decision making about vehicle performance and reliability at both vehicle development stage (using simulation models) and at certification stage (using hardware-in-the-loop testing). Performance indices based on dynamic and geometric tasks associated with vehicle manoeuvring problems are proposed, and an example of a two- dimensional y scenario is provided to illustrate the use of the proposed figures of merit.
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Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.