Search results for "RED"

showing 10 items of 23890 documents

Implementing structured document production to support enterprise content management

2017

Within enterprise content management (ECM), the major goal is to develop and deploy systematic solutions for managing documents and other content items. ECM implementation concerns the development and deployment of new content management solutions and practices in an organization. Extensible Markup Language (XML) offers a standardized format for documents supporting the management and preservation of documents as structured documents. However, the deployment of XML may require a demanding standardization process, changes in work practices, and new tools for document management. Consequently, this research explores the implementation of structured document production environments. The focus …

sähköiset asiakirjatECMenterprise content managementmetadataComputingMethodologies_DOCUMENTANDTEXTPROCESSINGtiedonhallintasisällönhallintatiedonhallintajärjestelmätXMLstructured documentsrakenteiset dokumentitasiakirjahallinto
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Zasada bezpośredniości w postępowaniu odwoławczym na tle art. 452 K.P.K. z perspektywy historycznej

2019

Zasada bezpośredniości jest kwalifikowana to tzw. zasad nieskodyfikowanych. Oznacza to, że odkodowanie treści rzeczonej zasady jest możliwe w oparciu o interpretację odpowiedniej grupy przepisów. Art. 452 k.p.k. stanowi fundamentalny przepis, który odpowiada na zasadnicze pytanie dotyczqce zakresu realizowania zasady bezpośredniości w postępowaniu odwoławczym. O zakresie obowiqzywania zasady bezpośredniości w postępowaniu przed sqdem II instancji decyduje model postępowania odwoławczego, kształtowany w oparciuo obowiqzujqce granice dopuszczalnego dowodzenia w instancji odwoławczej. Na skutek przemodelowania postępowania odwoławczego z pełniqcego funkcję wyłqcznie kontrolnq w kierunku postęp…

sąd odwoławczyrulebezpośredniośćdirectnesszasadamodel postępowania odwoławczegocourt of appealmodel of appeal proceedingPROBACJA
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Dexamethasone premedication suppresses vaccine-induced immune responses against cancer

2020

ABSTRACT Glucocorticosteroids (GCS) have an established role in oncology and are administered to cancer patients in routine clinical care and in drug development trials as co-medication. Given their strong immune-suppressive activity, GCS may interfere with immune-oncology drugs. We are developing a therapeutic cancer vaccine, which is based on a liposomal formulation of tumor-antigen encoding RNA (RNA-LPX) and induces a strong T-cell response both in mice as well as in humans. In this study, we investigated in vivo in mice and in human PBMCs the effect of the commonly used long-acting GCS Dexamethasone (Dexa) on the efficacy of this vaccine format, with a particular focus on antigen-specif…

t-cell primingPremedicationmedicine.medical_treatmentImmunologyPriming (immunology)dexamethasoneglucocorticosteroidsProinflammatory cytokineMice03 medical and health sciences0302 clinical medicineImmune systemAntigenCancer immunotherapyNeoplasmsAnimalsHumansImmunology and AllergyMedicineRC254-282Original ResearchMice Inbred BALB Ccancer immunotherapybusiness.industryrna vaccineImmunityNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC581-607Mice Inbred C57BLCytokineOncology030220 oncology & carcinogenesisImmunologyt-cell vaccineFemaleCancer vaccineImmunologic diseases. AllergybusinessT-cell vaccineResearch Article030215 immunologyOncoImmunology
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How many longitudinal covariate measurements are needed for risk prediction?

2014

Abstract Objective In epidemiologic follow-up studies, many key covariates, such as smoking, use of medication, blood pressure, and cholesterol, are time varying. Because of practical and financial limitations, time-varying covariates cannot be measured continuously, but only at certain prespecified time points. We study how the number of these longitudinal measurements can be chosen cost-efficiently by evaluating the usefulness of the measurements for risk prediction. Study Design and Setting The usefulness is addressed by measuring the improvement in model discrimination between models using different amounts of longitudinal information. We use simulated follow-up data and the data from t…

ta112Models StatisticalEpidemiologyComputer scienceHazard ratiota3142Risk Assessment01 natural sciencesrisk prediction010104 statistics & probability03 medical and health sciencesstudy design0302 clinical medicineCovariateStatisticsEconometricsHumanslongitudinal measurementsLongitudinal Studies030212 general & internal medicine0101 mathematicsOlder peoplemodel discriminationForecastingJournal of Clinical Epidemiology
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Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music

2011

Classification of musical audio signals according to expressed mood or emotion has evident applications to content-based music retrieval in large databases. Wrapper selection is a dimension reduction method that has been proposed for improving classification performance. However, the technique is prone to lead to overfitting of the training data, which decreases the generalizability of the obtained results. We claim that previous attempts to apply wrapper selection in the field of music information retrieval (MIR) have led to disputable conclusions about the used methods due to inadequate analysis frameworks, indicative of overfitting, and biased results. This paper presents a framework bas…

ta113Acoustics and UltrasonicsComputer sciencebusiness.industryDimensionality reductionEmotion classificationFeature selectionOverfittingMachine learningcomputer.software_genreNaive Bayes classifierFeature (machine learning)Music information retrievalGeneralizability theoryArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerIEEE Transactions on Audio, Speech, and Language Processing
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An Information system design product theory for the abstract class of integrated requirements and delivery management systems

2014

Information and Communications Technology-enabled international sourcing of software-intensive systems and services (eSourcing) is increasingly used as a means of adding value, reducing costs, sharing risks, and achieving strategic aims. To maximally reap the benefits from eSourcing and to mitigate the risks, providers and clients have to be aware of and build capabilities for the eSourcing life-cycle. China is in a position to become a superpower for eSourcing service provisioning, but most Chinese eSourcing service providers are small or medium-sized and typically work for larger intermediaries instead of end-clients, limiting their business and capabilities development. The extant litera…

ta113Class (computer programming)Process managementKnowledge managementbusiness.industryComputer scienceService providerCost reductionIntermediaryRisk analysis (business)Management systemInformation systemProduct (category theory)business
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Exact extension of the DIRECT algorithm to multiple objectives

2019

The direct algorithm has been recognized as an efficient global optimization method which has few requirements of regularity and has proven to be globally convergent in general cases. direct has been an inspiration or has been used as a component for many multiobjective optimization algorithms. We propose an exact and as genuine as possible extension of the direct method for multiple objectives, providing a proof of global convergence (i.e., a guarantee that in an infinite time the algorithm becomes everywhere dense). We test the efficiency of the algorithm on a nonlinear and nonconvex vector function. peerReviewed

ta113Computer scienceDirect methodta111multi-objective optimisationExtension (predicate logic)algorithmsMulti-objective optimizationmonitavoiteoptimointiNonlinear systemComponent (UML)Convergence (routing)algoritmitGlobal optimizationVector-valued functionAlgorithm
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Biomass estimator for NIR image with a few additional spectral band images taken from light UAS

2012

A novel way to produce biomass estimation will offer possibilities for precision farming. Fertilizer prediction maps can be made based on accurate biomass estimation generated by a novel biomass estimator. By using this knowledge, a variable rate amount of fertilizers can be applied during the growing season. The innovation consists of light UAS, a high spatial resolution camera, and VTT's novel spectral camera. A few properly selected spectral wavelengths with NIR images and point clouds extracted by automatic image matching have been used in the estimation. The spectral wavelengths were chosen from green, red, and NIR channels.

ta113Computer scienceFabry-Perotprecision farmingNear-infrared spectroscopyPoint cloudEstimatorBiomassSpectral bandsNIRBiomass estimationfertilizerestimatorWavelength/dk/atira/pure/sustainabledevelopmentgoals/zero_hungerPrecision agriculturespectral imagerSDG 2 - Zero HungerImage resolutionRemote sensingProceedings of SPIE
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Adaptive framework for network traffic classification using dimensionality reduction and clustering

2012

Information security has become a very important topic especially during the last years. Web services are becoming more complex and dynamic. This offers new possibilities for attackers to exploit vulnerabilities by inputting malicious queries or code. However, these attack attempts are often recorded in server logs. Analyzing these logs could be a way to detect intrusions either periodically or in real time. We propose a framework that preprocesses and analyzes these log files. HTTP queries are transformed to numerical matrices using n-gram analysis. The dimensionality of these matrices is reduced using principal component analysis and diffusion map methodology. Abnormal log lines can then …

ta113Computer scienceNetwork securitybusiness.industryDimensionality reductionintrusion detectionk-meansdiffusion mapServer logcomputer.software_genreanomaly detectionTraffic classificationkoneoppiminenWeb log analysis softwareAnomaly detectionData miningWeb servicetiedonlouhintaCluster analysisbusinesscomputern-grams
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DOBRO : a prediction error correcting robot under drifts

2016

We propose DOBRO, a light online learning module, which is equipped with a smart correction policy helping making decision to correct or not the given prediction depending on how likely the correction will lead to a better prediction performance. DOBRO is a standalone module requiring nothing more than a time series of prediction errors and it is flexible to be integrated into any black-box model to improve its performance under drifts. We performed evaluation in a real-world application with bus arrival time prediction problem. The obtained results show that DOBRO improved prediction performance significantly meanwhile it did not hurt the accuracy when drift does not happen.

ta113Concept driftComputer scienceMean squared prediction error02 engineering and technologyARIMAconcept drifton-line prediction error correction020204 information systems0202 electrical engineering electronic engineering information engineeringRobot020201 artificial intelligence & image processingAutoregressive integrated moving averageSimulation
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