Search results for "PREDICTION"
showing 10 items of 511 documents
Understanding Prediction Limits Through Unbiased Branches
2006
The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in prediction accuracy is proportional to the frequency of unbiased branches. By using the SPECcpu2000 integer benchmarks we show that there are a significant proportion of unbiased branches which severely impact on prediction accuracy (averaging between 6% and 24% depending on the prediction context used).
Joint use of cardio-embolic and bleeding risk scores in elderly patients with atrial fibrillation
2013
Background Scores for cardio-embolic and bleeding risk in patients with atrial fibrillation are described in the literature. However, it is not clear how they co-classify elderly patients with multimorbidity, nor whether and how they affect the physician's decision on thromboprophylaxis. Methods Four scores for cardio-embolic and bleeding risks were retrospectively calculated for ⥠65 year old patients with atrial fibrillation enrolled in the REPOSI registry. The co-classification of patients according to risk categories based on different score combinations was described and the relationship between risk categories tested. The association between the antithrombotic therapy received and t…
Machine learning in management accounting research: Literature review and pathways for the future
2021
This paper explores the possibilities of machine learning (ML) methods in management accounting research and showcases one future avenue in practice by applying ML-based textual literature review to ML/AI research in accounting. The review reveals that machine learning methods in management accounting (MA) are still in their infancy, and current research in accounting has progressed in and focused mainly on three areas related to ML and AI: 1) effects on the field of accounting and the development of the accounting profession, 2) textual analysis related to accounting data/reports, and 3) prediction methods. Based on our literature review and recently published related ML research from othe…
The Stroke Riskometer (TM) App: Validation of a data collection tool and stroke risk predictor
2014
Background The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the ‘mass’ approach), the ‘high risk’ approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer™, has been developed. We aim to explore the validity of the app fo…
Prediction of river discharges at confluences based on Entropy theory and surface-velocity measurements
2022
Hydrodynamic features of the confluence zone of large rivers are complicated because of their three-dimensional flow structure. The confluence between the Rio Negro and the Rio Solimões, characterised by black and white waters, respectively, ranks among the largest river junctions on Earth. An Entropy-based investigation was carried out to assess the discharge and analyse the 2D structure of velocity distribution for large river flows relying on monitoring of near-surface velocity only. The estimated flow data where compared with in-situ ADCP data gathered across some transects of the Negro and Solimões rivers during both low and relatively high flow conditions. Results are illustrated thro…
Effects of submerged vegetation on flow and turbulence characteristics at the apex section of a meandering flume
2020
Understanding flow characteristics and turbulent structure in the presence of vegetation is important with respect to environmental processes as sediment transport and mixing of transported quantities. In the present paper attention is focused on the kinematic and turbulent processes in presence of flexible submerged vegetation. In particular, the effect of vegetation on the flux of mass distribution and the process of transport is investigated. The analysis is performed with the aid of detailed experimental data collected in a laboratory channel both in the absence and in presence of flexible and submerged vegetation. Results essentially confirms that mass exchanges in the presence of vege…
Effects of submerged vegetation on flow and turbulence characteristics at the apex bend of a meandering flume
2020
Understanding flow characteristics and turbulent structure in the presence of vegetation is important with respect to environmental processes as sediment transport and mixing of transported quantities. In the present paper attention is focused on the kinematic and turbulent processes in presence of flexible submerged vegetation. In particular, the effect of vegetation on the flux of mass distribution and the process of transport is investigated. The analysis is performed with the aid of detailed experimental data collected in a laboratory channel both in the absence and in presence of flexible and submerged vegetation. Results essentially confirms that mass exchanges in the presence of vege…
Découverte des relations dans les réseaux sociaux
2011
In recent years, social network sites exploded in popularity and become an important part of the online activities on the web. This success is related to the various services/functionalities provided by each site (ranging from media sharing, tagging, blogging, and mainly to online social networking) pushing users to subscribe to several sites and consequently to create several social networks for different purposes and contexts (professional, private, etc.). Nevertheless, current tools and sites provide limited functionalities to organize and identify relationship types within and across social networks which is required in several scenarios such as enforcing users’ privacy, and enhancing t…
A Comprehensive Check of Usle-Based Soil Loss Prediction Models at the Sparacia (South Italy) Site
2020
At first, in this paper a general definition of the event rainfall-runoff erosivity factor for the USLE-based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single-storm erosion index and b1 and b2 are coefficients, was introduced. The rainfall-runoff erosivity factors of the USLE (b1 = 0, b2 = 1), USLE-M (b1 = b2 = 1), USLE-MB (b1 ≠ 1, b2 = 1), USLE-MR (b1 = 1, b2 ≠ 1), USLE-MM (b1 = b2 ≠ 1) and USLE-M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then, the different expressions of REFe were simultaneously tested against a dataset of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predict…
A Forecasting Support System Based on Exponential Smoothing
2010
This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates computation and considerably reduces data storage requirements. Consequently, they are widely used as forecasting techniques in inventory systems and business planning. After selecting the most adequate model to replicate patterns of the time series under study, the system provides accurate forecasts which can play decisive roles in organizational planning, budgeting and performance monitoring.