878 resultados para user authentication


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The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

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We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

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The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

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This project explores the user costs and benefits of winter road closures. Severe winter weather makes travel unsafe and dramatically increases crash rates. When conditions become unsafe due to winter weather, road closures should allow users to avoid crash costs and eliminate costs associated with rescuing stranded motorists. Therefore, the benefits of road closures are the avoided safety costs. The costs of road closures are the delays that are imposed on motorists and motor carriers who would have made the trip had the road not been closed. This project investigated the costs and benefits of road closures and found that evaluating the benefits and costs is not as simple as it appears. To better understand the costs and benefits of road closures, the project investigates the literature, conducts interviews with shippers and motor carriers, and conducts case studies of road closures to determine what actually occurred on roadways during closures. The project also estimates a statistical model that relates weather severity to crash rates. Although, the statistical model is intended to illustrate the possibility to quantitatively relate measurable and predictable weather conditions to the safety performance of a roadway. In the future, weather conditions such as snow fall intensity, visibility, etc., can be used to make objective measures of the safety performance of a roadway rather than relying on subjective evaluations of field staff. The review of the literature and the interviews clearly illustrate that not all delays (increased travel time) are valued the same. Expected delays (routine delays) are valued at the generalized costs (value of the driver’s time, fuel, insurance, wear and tear on the vehicle, etc.), but unexpected delays are valued much higher because they result in interruption of synchronous activities at the trip’s destination. To reduce the costs of delays resulting from road closures, public agencies should communicate as early as possible the likelihood of a road closure.

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This paper presents the platform developed in the PANACEA project, a distributed factory that automates the stages involved in the acquisition, production, updating and maintenance of Language Resources required by Machine Translation and other Language Technologies. We adopt a set of tools that have been successfully used in the Bioinformatics field, they are adapted to the needs of our field and used to deploy web services, which can be combined to build more complex processing chains (workflows). This paper describes the platform and its different components (web services, registry, workflows, social network and interoperability). We demonstrate the scalability of the platform by carrying out a set of massive data experiments. Finally, a validation of the platform across a set of required criteria proves its usability for different types of users (non-technical users and providers).

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This paper presents a webservice architecture for Statistical Machine Translation aimed at non-technical users. A workfloweditor allows a user to combine different webservices using a graphical user interface. In the current state of this project,the webservices have been implemented for a range of sentential and sub-sententialaligners. The advantage of a common interface and a common data format allows the user to build workflows exchanging different aligners.

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The fatty acids of olive oils of distinct quality grade from the most important European Union (EU) producer countries were chemically and isotopically characterized. The analytical approach utilized combined capillary column gas chromatography-mass spectrometry (GC/MS) and the novel technique of compound-specific isotope analysis (CSIA) through gas chromatography coupled to a stable isotope ratio mass spectrometer (IRMS) via a combustion (C) interface (GC/C/IRMS). This approach provides further insights into the control of the purity and geographical origin of oils sold as cold-pressed extra virgin olive oil with certified origin appellation. The results indicate that substantial enrichment in heavy carbon isotope (C-13) of the bulk oil and of individual fatty acids are related to (1) a thermally induced degradation due to deodorization or steam washing of the olive oils and (2) the potential blend with refined olive oil or other vegetable oils. The interpretation of the data is based on principal component analysis of the fatty acids concentrations and isotopic data (delta(13)C(oil), delta(13)C(16:0), delta(13)C(18:1)) and on the delta(13)C(16:0) vs delta(13)C(18:1) covariations. The differences in the delta(13)C values of palmitic and oleic acids are discussed in terms of biosynthesis of these acids in the plant tissue and admixture of distinct oils.

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The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

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BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.

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The usual assumption when considering investment grants is that grant payments are automatic when investments are undertaken. However, evidence from case studies shows that there can exist some time lag until funds are received by granted firms. In this paper the effects of delays in grant payments on the optimal investment policy of the firm are analyzed. It is shown how these delays lead not only to a higher financing cost but to an effective reduction in the investment grant rate, and in some cases, how benefits from investment grants could be canceled due to interactions with tax effects.

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The usual assumption when considering investment grants is that grant payments are automatic when investments are undertaken. However, evidence from case studies shows that there can exist some time lag until funds are received by granted firms. In this paper the effects of delays in grant payments on the optimal investment policy of the firm are analyzed. It is shown how these delays lead not only to a higher financing cost but to an effective reduction in the investment grant rate, and in some cases, how benefits from investment grants could be canceled due to interactions with tax effects.

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This study is a concise summary of a study of trail users on the Raccoon River Valley Trail commissioned by the Dallas County Conservation Board. It provides information associated with natural and cultural resources.

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The Iowa DOT reviewed Corps of Engineers accounting records to determine the costs of operating and maintaining a 300 mile section of the Mississippi River. This document reviews the details the study.