887 resultados para Computer forensic analysis


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A reference model of Fallible Endgame Play has been implemented and exercised with the chess-engine WILHELM. Past experiments have demonstrated the value of the model and the robustness of decisions based on it: experiments agree well with a Markov Model theory. Here, the reference model is exercised on the well-known endgame KBBKN.

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A reference model of Fallible Endgame Play has been implemented and exercised with the chess engine WILHELM. Various experiments have demonstrated the value of the model and the robustness of decisions based on it. Experimental results have also been compared with the theoretical predictions of a Markov model of the endgame and found to be in close agreement.

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This paper describes a novel methodology for observing and analysing collaborative design by using the concepts of cognitive dimensions related to concept-based misfit analysis. The study aims at gaining an insight into support for creative practice of graphical communication in collaborative design processes of designers while sketching within a shared white board and audio conferencing environment. Empirical data on design processes have been obtained from observation of groups of student designers solving an interior space-planning problem of a lounge-diner in a shared virtual environment. The results of the study provide recommendations for the design and development of interactive systems to support such collaborative design activities.

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Mites can be found in all imaginable terrestrial habitats, in freshwater, and in salt water. Mites can be found in our houses and furnishings, on our clothes, and even in the pores of our skin-almost every single person carries mites. Most of the time, we are unaware of them because they are small and easily overlooked, and-most of the time-they do not cause trouble. In fact, they may even proof useful, for instance in forensics. The first arthropod scavengers colonising a dead body will be flies with phoretic mites. The flies will complete their life cycle in and around the corpse, while the mites may feed on the immature stages of the flies. The mites will reproduce much faster than their carriers, offering themselves as valuable timeline markers. There are environments where insects are absent or rare or the environmental conditions impede their access to the corpse. Here, mites that are already present and mites that arrive walking, through air currents or material transfer become important. At the end of the ninetieth century, the work of Jean Pierre M,gnin became the starting point of forensic acarology. M,gnin documented his observations in 'La Faune des Cadavres' [The Fauna of Carcasses]. He was the first to list eight distinct waves of arthropods colonising human carcasses. The first wave included flies and mites, the sixth wave was composed of mites exclusively. The scope of forensic acarology goes further than mites as indicators of time of death. Mites are micro-habitat specific and might provide evidential data on movement or relocation of bodies, or locating a suspect at the scene of a crime. Because of their high diversity, wide occurrence, and abundance, mites may be of great value in the analysis of trace evidence.

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In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters.

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BCI systems require correct classification of signals interpreted from the brain for useful operation. To this end this paper investigates a method proposed in [1] to correctly classify a series of images presented to a group of subjects in [2]. We show that it is possible to use the proposed methods to correctly recognise the original stimuli presented to a subject from analysis of their EEG. Additionally we use a verification set to show that the trained classification method can be applied to a different set of data. We go on to investigate the issue of invariance in EEG signals. That is, the brain representation of similar stimuli is recognisable across different subjects. Finally we consider the usefulness of the methods investigated towards an improved BCI system and discuss how it could potentially lead to great improvements in the ease of use for the end user by offering an alternative, more intuitive control based mode of operation.

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The purpose of this study is to analyse current data continuity mechanisms employed by the target group of businesses and to identify any inadequacies in the mechanisms as a whole. The questionnaire responses indicate that 47% of respondents do perceive backup methodologies as important, with a total of 70% of respondents having some backup methodology already in place. Businesses in Moulton Park perceive the loss of data to have a significant effect upon their business’ ability to function. Only 14% of respondents indicated that loss of data on computer systems would not affect their business at all, with 54% of respondents indicating that there would be either a “major effect” (or greater) on their ability to operate. Respondents that have experienced data loss were more likely to have backup methodologies in place (53%) than respondents that had not experienced data loss (18%). Although the number of respondents clearly affected the quality and conclusiveness of the results returned, the level of backup methodologies in place appears to be proportional to the company size. Further investigation is recommended into the subject in order to validate the information gleaned from the small number of respondents.

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Participants' eye-gaze is generally not captured or represented in immersive collaborative virtual environment (ICVE) systems. We present EyeCVE. which uses mobile eye-trackers to drive the gaze of each participant's virtual avatar, thus supporting remote mutual eye-contact and awareness of others' gaze in a perceptually unfragmented shared virtual workspace. We detail trials in which participants took part in three-way conferences between remote CAVE (TM) systems linked via EyeCVE. Eye-tracking data was recorded and used to evaluate interaction, confirming; the system's support for the use of gaze as a communicational and management resource in multiparty conversational scenarios. We point toward subsequent investigation of eye-tracking in ICVEs for enhanced remote social-interaction and analysis.

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Semiotics is the study of signs. Application of semiotics in information systems design is based on the notion that information systems are organizations within which agents deploy signs in the form of actions according to a set of norms. An analysis of the relationships among the agents, their actions and the norms would give a better specification of the system. Distributed multimedia systems (DMMS) could be viewed as a system consisted of many dynamic, self-controlled normative agents engaging in complex interaction and processing of multimedia information. This paper reports the work of applying the semiotic approach to the design and modeling of DMMS, with emphasis on using semantic analysis under the semiotic framework. A semantic model of DMMS describing various components and their ontological dependencies is presented, which then serves as a design model and implemented in a semantic database. Benefits of using the semantic database are discussed with reference to various design scenarios.

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In this paper we present error analysis for a Monte Carlo algorithm for evaluating bilinear forms of matrix powers. An almost Optimal Monte Carlo (MAO) algorithm for solving this problem is formulated. Results for the structure of the probability error are presented and the construction of robust and interpolation Monte Carlo algorithms are discussed. Results are presented comparing the performance of the Monte Carlo algorithm with that of a corresponding deterministic algorithm. The two algorithms are tested on a well balanced matrix and then the effects of perturbing this matrix, by small and large amounts, is studied.

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Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

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The conformation of a model peptide AAKLVFF based on a fragment of the amyloid beta peptide A beta 16-20, KLVFF, is investigated in methanol and water via solution NMR experiments and Molecular dynamics computer simulations. In previous work, we have shown that AAKLVFF forms peptide nanotubes in methanol and twisted fibrils in water. Chemical shift measurements were used to investigate the solubility of the peptide as a function of concentration in methanol and water. This enabled the determination of critical aggregation concentrations, The Solubility was lower in water. In dilute solution, diffusion coefficients revealed the presence of intermediate aggregates in concentrated solution, coexisting with NMR-silent larger aggregates, presumed to be beta-sheets. In water, diffusion coefficients did not change appreciably with concentration, indicating the presence mainly of monomers, coexisting with larger aggregates in more concentrated solution. Concentration-dependent chemical shift measurements indicated a folded conformation for the monomers/intermediate aggregates in dilute methanol, with unfolding at higher concentration. In water, an antiparallel arrangement of strands was indicated by certain ROESY peak correlations. The temperature-dependent solubility of AAKLVFF in methanol was well described by a van't Hoff analysis, providing a solubilization enthalpy and entropy. This pointed to the importance of solvophobic interactions in the self-assembly process. Molecular dynamics Simulations constrained by NOE values from NMR suggested disordered reverse turn structures for the monomer, with an antiparallel twisted conformation for dimers. To model the beta-sheet structures formed at higher concentration, possible model arrangements of strands into beta-sheets with parallel and antiparallel configurations and different stacking sequences were used as the basis for MD simulations; two particular arrangements of antiparallel beta-sheets were found to be stable, one being linear and twisted and the other twisted in two directions. These structures Were used to simulate Circular dichroism spectra. The roles of aromatic stacking interactions and charge transfer effects were also examined. Simulated spectra were found to be similar to those observed experimentally.(in water or methanol) which show a maximum at 215 or 218 nm due to pi-pi* interactions, when allowance is made for a 15-18 nm red-shift that may be due to light scattering effects.