928 resultados para Parallel processing (Electronic computers) - Research


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Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.

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Understanding the evolution of sociality in humans and other species requires understanding how selection on social behaviour varies with group size. However, the effects of group size are frequently obscured in the theoretical literature, which often makes assumptions that are at odds with empirical findings. In particular, mechanisms are suggested as supporting large-scale cooperation when they would in fact rapidly become ineffective with increasing group size. Here we review the literature on the evolution of helping behaviours (cooperation and altruism), and frame it using a simple synthetic model that allows us to delineate how the three main components of the selection pressure on helping must vary with increasing group size. The first component is the marginal benefit of helping to group members, which determines both direct fitness benefits to the actor and indirect fitness benefits to recipients. While this is often assumed to be independent of group size, marginal benefits are in practice likely to be maximal at intermediate group sizes for many types of collective action problems, and will eventually become very small in large groups due to the law of decreasing returns. The second component is the response of social partners on the past play of an actor, which underlies conditional behaviour under repeated social interactions. We argue that under realistic conditions on the transmission of information in a population, this response on past play decreases rapidly with increasing group size so that reciprocity alone (whether direct, indirect, or generalised) cannot sustain cooperation in very large groups. The final component is the relatedness between actor and recipient, which, according to the rules of inheritance, again decreases rapidly with increasing group size. These results explain why helping behaviours in very large social groups are limited to cases where the number of reproducing individuals is small, as in social insects, or where there are social institutions that can promote (possibly through sanctioning) large-scale cooperation, as in human societies. Finally, we discuss how individually devised institutions can foster the transition from small-scale to large-scale cooperative groups in human evolution.

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This portfolio thesis describes work undertaken by the author under the Engineering Doctorate program of the Institute for System Level Integration. It was carried out in conjunction with the sponsor company Teledyne Defence Limited. A radar warning receiver is a device used to detect and identify the emissions of radars. They were originally developed during the Second World War and are found today on a variety of military platforms as part of the platform’s defensive systems. Teledyne Defence has designed and built components and electronic subsystems for the defence industry since the 1970s. This thesis documents part of the work carried out to create Phobos, Teledyne Defence’s first complete radar warning receiver. Phobos was designed to be the first low cost radar warning receiver. This was made possible by the reuse of existing Teledyne Defence products, commercial off the shelf hardware and advanced UK government algorithms. The challenges of this integration are described and discussed, with detail given of the software architecture and the development of the embedded application. Performance of the embedded system as a whole is described and qualified within the context of a low cost system.

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Nowadays there is almost no crime committed without a trace of digital evidence, and since the advanced functionality of mobile devices today can be exploited to assist in crime, the need for mobile forensics is imperative. Many of the mobile applications available today, including internet browsers, will request the user’s permission to access their current location when in use. This geolocation data is subsequently stored and managed by that application's underlying database files. If recovered from a device during a forensic investigation, such GPS evidence and track points could hold major evidentiary value for a case. The aim of this paper is to examine and compare to what extent geolocation data is available from the iOS and Android operating systems. We focus particularly on geolocation data recovered from internet browsing applications, comparing the native Safari and Browser apps with Google Chrome, downloaded on to both platforms. All browsers were used over a period of several days at various locations to generate comparable test data for analysis. Results show considerable differences not only in the storage locations and formats, but also in the amount of geolocation data stored by different browsers and on different operating systems.

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SQL injection is a common attack method used to leverage infor-mation out of a database or to compromise a company’s network. This paper investigates four injection attacks that can be conducted against the PL/SQL engine of Oracle databases, comparing two recent releases (10g, 11g) of Oracle. The results of the experiments showed that both releases of Oracle were vulner-able to injection but that the injection technique often differed in the packages that it could be conducted in.

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This paper discusses the large-scale group project undertaken by BSc Hons Digital Forensics students at Abertay University in their penultimate year. The philosophy of the project is to expose students to the full digital crime "life cycle", from commission through investigation, preparation of formal court report and finally, to prosecution in court. In addition, the project is novel in two aspects; the "crimes" are committed by students, and the moot court proceedings, where students appear as expert witnesses for the prosecution, are led by law students acting as counsels for the prosecution and defence. To support students, assessments are staged across both semesters with staff feedback provided at critical points. Feedback from students is very positive, highlighting particularly the experience of engaging with the law students and culminating in the realistic moot court, including a challenging cross-examination. Students also commented on the usefulness of the final debrief, where the whole process and the student experience is discussed in an informal plenary meeting between DF students and staff, providing an opportunity for the perpetrators and investigators to discuss details of the "crimes", and enabling all groups to learn from all crimes and investigations. We conclude with a reflection on the challenges encountered and a discussion of planned changes.

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There is still a lack of an engineering approach for building Web systems, and the field of measuring the Web is not yet mature. In particular, there is an uncertainty in the selection of evaluation methods, and there are risks of standardizing inadequate evaluation practices. It is important to know whether we are evaluating the Web or specific website(s). We need a new categorization system, a different focus on evaluation methods, and an in-depth analysis that reveals the strengths and weaknesses of each method. As a contribution to the field of Web evaluation, this study proposes a novel approach to view and select evaluation methods based on the purpose and platforms of the evaluation. It has been shown that the choice of the appropriate evaluation method(s) depends greatly on the purpose of the evaluation.

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Recent years have seen an astronomical rise in SQL Injection Attacks (SQLIAs) used to compromise the confidentiality, authentication and integrity of organisations’ databases. Intruders becoming smarter in obfuscating web requests to evade detection combined with increasing volumes of web traffic from the Internet of Things (IoT), cloud-hosted and on-premise business applications have made it evident that the existing approaches of mostly static signature lack the ability to cope with novel signatures. A SQLIA detection and prevention solution can be achieved through exploring an alternative bio-inspired supervised learning approach that uses input of labelled dataset of numerical attributes in classifying true positives and negatives. We present in this paper a Numerical Encoding to Tame SQLIA (NETSQLIA) that implements a proof of concept for scalable numerical encoding of features to a dataset attributes with labelled class obtained from deep web traffic analysis. In the numerical attributes encoding: the model leverages proxy in the interception and decryption of web traffic. The intercepted web requests are then assembled for front-end SQL parsing and pattern matching by applying traditional Non-Deterministic Finite Automaton (NFA). This paper is intended for a technique of numerical attributes extraction of any size primed as an input dataset to an Artificial Neural Network (ANN) and statistical Machine Learning (ML) algorithms implemented using Two-Class Averaged Perceptron (TCAP) and Two-Class Logistic Regression (TCLR) respectively. This methodology then forms the subject of the empirical evaluation of the suitability of this model in the accurate classification of both legitimate web requests and SQLIA payloads.

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Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.

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Physical places are given contextual meaning by the objects and people that make up the space. Presence in physical places can be utilised to support mobile interaction by making access to media and notifications on a smartphone easier and more visible to other people. Smartphone interfaces can be extended into the physical world in a meaningful way by anchoring digital content to artefacts, and interactions situated around physical artefacts can provide contextual meaning to private manipulations with a mobile device. Additionally, places themselves are designed to support a set of tasks, and the logical structure of places can be used to organise content on the smartphone. Menus that adapt the functionality of a smartphone can support the user by presenting the tools most likely to be needed just-in-time, so that information needs can be satisfied quickly and with little cognitive effort. Furthermore, places are often shared with people whom the user knows, and the smartphone can facilitate social situations by providing access to content that stimulates conversation. However, the smartphone can disrupt a collaborative environment, by alerting the user with unimportant notifications, or sucking the user in to the digital world with attractive content that is only shown on a private screen. Sharing smartphone content on a situated display creates an inclusive and unobtrusive user experience, and can increase focus on a primary task by allowing content to be read at a glance. Mobile interaction situated around artefacts of personal places is investigated as a way to support users to access content from their smartphone while managing their physical presence. A menu that adapts to personal places is evaluated to reduce the time and effort of app navigation, and coordinating smartphone content on a situated display is found to support social engagement and the negotiation of notifications. Improving the sensing of smartphone users in places is a challenge that is out-with the scope of this thesis. Instead, interaction designers and developers should be provided with low-cost positioning tools that utilise presence in places, and enable quantitative and qualitative data to be collected in user evaluations. Two lightweight positioning tools are developed with the low-cost sensors that are currently available: The Microsoft Kinect depth sensor allows movements of a smartphone user to be tracked in a limited area of a place, and Bluetooth beacons enable the larger context of a place to be detected. Positioning experiments with each sensor are performed to highlight the capabilities and limitations of current sensing techniques for designing interactions with a smartphone. Both tools enable prototypes to be built with a rapid prototyping approach, and mobile interactions can be tested with more advanced sensing techniques as they become available. Sensing technologies are becoming pervasive, and it will soon be possible to perform reliable place detection in-the-wild. Novel interactions that utilise presence in places can support smartphone users by making access to useful functionality easy and more visible to the people who matter most in everyday life.

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Das Wort Transparenz ist aus den aktuellen, öffentlichen Debatten um Informationsfreiheit nicht mehr wegzudenken. Doch wer den Transparenzdiskurs ausschließlich auf politischer Ebene im Kontext von Whistleblowern, Wikileaks, NSA-Affäre oder Piraten-Partei verortet, verkennt, dass Transparenz, wie Han feststellt, als ein systematischer Zwang wirkt, der alle gesellschaftlichen Bereiche – also auch das Bildungswesen – erfasst und sie tiefgreifend verändert. [...] Die Hattie-Studie markiert hier einen besonderen Höhepunkt, da sie alle bisher veröffentlichten Studien an Umfang und Aufwand deutlich übertrifft und dabei den Anspruch erhebt, Lernen und Lehren sichtbar zu machen. Doch welches Recht hat der Sehende auf das Sichtbar-zu-Machende? Wer profitiert hier? Unter welchen Bedingungen kann der oder die Durch-Schaute diese Veräußerung des Selbst verweigern, d.h. seine bzw. ihre Undurchschaubarkeit geltend machen? Welche anthropologischen und gesellschaftlichen Konsequenzen folgen aus dem Anspruch, den Menschen durchschaubar zu machen? Und dürfen bzw. können wir die Preisgabe von Geheimnissen bedenkenlos fordern? Bevor diese Fragen rund um die Hattie-Studie erörtert werden, sei zum Zwecke eines tieferen Verständnisses zunächst nach der Herkunft dieses Transparenztraums und des damit verbundenen Strebens nach Durch-Sichtigkeit von Mensch und Gesellschaft gefragt. (DIPF/Orig.)

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The Internet has grown in size at rapid rates since BGP records began, and continues to do so. This has raised concerns about the scalability of the current BGP routing system, as the routing state at each router in a shortest-path routing protocol will grow at a supra-linearly rate as the network grows. The concerns are that the memory capacity of routers will not be able to keep up with demands, and that the growth of the Internet will become ever more cramped as more and more of the world seeks the benefits of being connected. Compact routing schemes, where the routing state grows only sub-linearly relative to the growth of the network, could solve this problem and ensure that router memory would not be a bottleneck to Internet growth. These schemes trade away shortest-path routing for scalable memory state, by allowing some paths to have a certain amount of bounded “stretch”. The most promising such scheme is Cowen Routing, which can provide scalable, compact routing state for Internet routing, while still providing shortest-path routing to nearly all other nodes, with only slightly stretched paths to a very small subset of the network. Currently, there is no fully distributed form of Cowen Routing that would be practical for the Internet. This dissertation describes a fully distributed and compact protocol for Cowen routing, using the k-core graph decomposition. Previous compact routing work showed the k-core graph decomposition is useful for Cowen Routing on the Internet, but no distributed form existed. This dissertation gives a distributed k-core algorithm optimised to be efficient on dynamic graphs, along with with proofs of its correctness. The performance and efficiency of this distributed k-core algorithm is evaluated on large, Internet AS graphs, with excellent results. This dissertation then goes on to describe a fully distributed and compact Cowen Routing protocol. This protocol being comprised of a landmark selection process for Cowen Routing using the k-core algorithm, with mechanisms to ensure compact state at all times, including at bootstrap; a local cluster routing process, with mechanisms for policy application and control of cluster sizes, ensuring again that state can remain compact at all times; and a landmark routing process is described with a prioritisation mechanism for announcements that ensures compact state at all times.

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Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.