934 resultados para Graphical passwords


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This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

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Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin.

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We compare a number of models of post War US output growth in terms of the degree and pattern of non-linearity they impart to the conditional mean, where we condition on either the previous period's growth rate, or the previous two periods' growth rates. The conditional means are estimated non-parametrically using a nearest-neighbour technique on data simulated from the models. In this way, we condense the complex, dynamic, responses that may be present in to graphical displays of the implied conditional mean.

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Monitoring nutritional intake is an important aspect of the care of older people, particularly for those at risk of malnutrition. Current practice for monitoring food intake relies on hand written food charts that have several inadequacies. We describe the design and validation of a tool for computer-assisted visual assessment of patient food and nutrient intake. To estimate food consumption, the application compares the pixels the user rubbed out against predefined graphical masks. Weight of food consumed is calculated as a percentage of pixels rubbed out against pixels in the mask. Results suggest that the application may be a useful tool for the conservative assessment of nutritional intake in hospitals.

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In the last decade, the growth of local, site-specific weather forecasts delivered by mobile phone or website represents arguably the fastest change in forecast consumption since the beginning of Television weather forecasts 60 years ago. In this study, a street-interception survey of 274 members of the public a clear first preference for narrow weather forecasts above traditional broad weather forecasts is shown for the first time, with a clear bias towards this preference for users under 40. The impact of this change on the understanding of forecast probability and intensity information is explored. While the correct interpretation of the statement ‘There is a 30% chance of rain tomorrow’ is still low in the cohort, in common with previous studies, a clear impact of age and educational attainment on understanding is shown, with those under 40 and educated to degree level or above more likely to correctly interpret it. The interpretation of rainfall intensity descriptors (‘Light’, ‘Moderate’, ‘Heavy’) by the cohort is shown to be significantly different to official and expert assessment of the same descriptors and to have large variance amongst the cohort. However, despite these key uncertainties, members of the cohort generally seem to make appropriate decisions about rainfall forecasts. There is some evidence that the decisions made are different depending on the communication format used, and the cohort expressed a clear preference for tabular over graphical weather forecast presentation.

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TESSA is a toolkit for experimenting with sensory augmentation. It includes hardware and software to facilitate rapid prototyping of interfaces that can enhance one sense using information gathered from another sense. The toolkit contains a range of sensors (e.g. ultrasonics, temperature sensors) and actuators (e.g. tactors or stereo sound), designed modularly so that inputs and outputs can be easily swapped in and out and customized using TESSA’s graphical user interface (GUI), with “real time” feedback. The system runs on a Raspberry Pi with a built-in touchscreen, providing a compact and portable form that is amenable for field trials. At CHI Interactivity, the audience will have the opportunity to experience sensory augmentation effects using this system, and design their own sensory augmentation interfaces.

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A virtual system that emulates an ARM-based processor machine has been created to replace a traditional hardware-based system for teaching assembly language. The proposed virtual system integrates, in a single environment, all the development tools necessary to deliver introductory or advanced courses on modern assembly language programming. The virtual system runs a Linux operating system in either a graphical or console mode on a Windows or Linux host machine. No software licenses or extra hardware are required to use the virtual system, thus students are free to carry their own ARM emulator with them on a USB memory stick. Institutions adopting this, or a similar virtual system, can also benefit by reducing capital investment in hardware-based development kits and enable distance learning courses.

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Empirical mode decomposition (EMD) is a data-driven method used to decompose data into oscillatory components. This paper examines to what extent the defined algorithm for EMD might be susceptible to data format. Two key issues with EMD are its stability and computational speed. This paper shows that for a given signal there is no significant difference between results obtained with single (binary32) and double (binary64) floating points precision. This implies that there is no benefit in increasing floating point precision when performing EMD on devices optimised for single floating point format, such as graphical processing units (GPUs).

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The present work describes a new tool that helps bidders improve their competitive bidding strategies. This new tool consists of an easy-to-use graphical tool that allows the use of more complex decision analysis tools in the field of Competitive Bidding. The graphic tool described here tries to move away from previous bidding models which attempt to describe the result of an auction or a tender process by means of studying each possible bidder with probability density functions. As an illustration, the tool is applied to three practical cases. Theoretical and practical conclusions on the great potential breadth of application of the tool are also presented.

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Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large-scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high-level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy-based management and policy hierarchies, combining model-based management (MBM) with system modularization. MBM employs an object-oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system-and the model-into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model-Based-Service-Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright (C) 2010 John Wiley & Sons, Ltd.

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The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

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Large-scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low-cost solution for many high-performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large-scale networks composed of biologically realistic Hodgkin-Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad-core CPU. Copyright (C) 2010 John Wiley & Sons, Ltd.

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In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

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An inquiring study of literature has been conducted, about the human colour perception (theimpression of colours). The colour has been examined, both as conscious and subconscious signal,and reasons for it’s influence have been exammed.The practical parts of the degree project have been carried out in active collaboration with thecustomer, The Association Hedemora Assistansservice (HASS), which offers handicapped persons astimulating spare time by personal assistance. A graphical profile-programme and an informationfolderhave been produced, easy received by both handicapped (with defective vision) and normallysighted persons. The graphical profile-programme was made in collaboration with the customer.Concerning the information-folder HASS took the main responsibility for the choice of photographswhile layout, text writing, colour-reproduction, original-production and connecting printing workswere made independently. The customer has shown engagement and interest and had a lot of opinionsabout the degree project, of which have been paid attention.

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This Degree Project is carried through in association with Fototext in Guthenburg. The firmsees benefits using”Soft Proof” technology for both economic and time-saving. The reasonfor ”Soft Proofing” for internal/ external production is to estimate and controll documentswithout using digital or chemical printing output.The different technical solutions to ”Soft Proof”, knowledges and facts aboutColorManagement together with PDF-workflow is going to pattern for a correct succesfull”Soft Proofing” on the monitor.Acrobat 5 in association with Photoshop 6 are effectively used in ”Soft Proofing” technic.The advance and capacity of the graphical softwares which are explained in this reporthelps the users to begin to experiment with ”Soft Proof”. Graphical firms which are interestedto begin working with ”Soft Proof” need to allready have knowledge in ICC-profilingand a practical ColorManaged workflow.