Search results for "stream"

New Flow-Resistance Law for Steep Mountain Streams Based on Velocity Profile

2017

This paper deduces a new flow-resistance equation for open-channel flow applying dimensional analysis and self-similarity theory. The incomplete self-similarity hypothesis is used to establish the flow velocity distribution whose integration gives the theoretical expression of the Darcy-Weisbach friction factor. The theoretical resistance equation then is tested by the available field measurements of flow velocity, water depth, river width and bed slope carried out in 653 reaches of several Canadian mountain streams. A relationship between the G function of the velocity profile and the channel slope and the flow Froude number is also established. The analysis shows that the Darcy- Weisbach …

Flow Resistance in Step-Pool Rills

2017

Rills evolve morphologically, and the adjustment of rill channel geometry to flow affects the relationships among velocity, discharge, and slope. The resistance to flow in step-pool rills is mainly due to form-induced mechanisms and, in comparison, grain resistance is of minor significance. Previous studies on rill flow resistance have been performed exclusively for grainresistance conditions and use a stream flow equation. In this study, a new flow resistance equation, deduced by applying dimensional analysis and self-similarity theory, was applied to rill flow in step-pool channels. First, the incomplete self-similarity hypothesis was used for establishing a power flow velocity profile wh…

Rapid condensational growth of aerosol particle in air stream — numerical simulation

1998

Lambda Architecture pour une analyse à haute performance des données des réseaux sociaux

2019

In this article, we show how a Lambda Architecture can contribute to the development of a platform for collecting and analyzing, in real-time, data from Twitter. After having presented the context, detailed the needs and identified the expected specificities, we compare the Lambda and Kappa architectures and we describe the state of the art on Lambda Architecture use in different domains. We propose an adaptation of the Lambda architecture to allow the storage of data in a polystore and to take into account different types of analysis to be carried out to answer researches in social sciences and communication sciences. In these projects the objectives are to study the structure of communica…

Managed Multiculturalism in Finnish Media Initiatives

2007

This paper focuses on Finnish mainstream journalism featuring multiculturalism. Three different initiatives are analysed with a qualitative text method founded on discourse and frame analysis. Finnish mainstream journalism took a multicultural turn in the mid-990s, two decades later than in neighbouring Sweden where similar initiatives were launched in the 1970s. The paper takes a critical look at the power relations these initiatives assert or transgress, how multicultural discourses position various actors in society, and how the mainstream media encounter cultural and ethnic differences in a changing demographic situation with a positive intention.

Demos también buenas noticias

2006

Procalcitonin as a marker of Candida species detection by blood culture and polymerase chain reaction in septic patients

2014

Background: The aim of our study is to test procalcitonin (PCT) as surrogate marker of identification of Candida spp. by blood culture (BC) and real-time-polymerase chain reaction (PCR), whether alone or in association with bacteria, in septic patients.Methods: We performed a single-centre retrospective study. We reviewed the clinical charts of patients with a diagnosis of severe sepsis or septic shock treated at our general intensive care unit from March 2009 to March 2013. We analysed all diagnostic episodes consisting of BC, real-time PCR assay and dosage of PCT. We registered age, sex, white blood count, sequential organ failure assessment score and type of admission between medical or …

Special education students in transition to further education: A four-year register-based follow-up study in Finland

2016

Abstract This study examines the transition of special education students into upper secondary education in Finland. The national register-based school-level dataset comprises three compulsory school-leaving cohorts of 2004, 2006 and 2009 including all students and schools providing lower secondary education. Special education students (Tier 3) are divided into four different groups based on their curriculum adjustments. The school-level effect of special education provision is evaluated with statistical models exploiting the panel nature of the data. The results show that there are significant differences in participation in upper secondary education between the groups with different level…

Scalable Clustering by Iterative Partitioning and Point Attractor Representation

2016

Clustering very large datasets while preserving cluster quality remains a challenging data-mining task to date. In this paper, we propose an effective scalable clustering algorithm for large datasets that builds upon the concept of synchronization. Inherited from the powerful concept of synchronization, the proposed algorithm, CIPA (Clustering by Iterative Partitioning and Point Attractor Representations), is capable of handling very large datasets by iteratively partitioning them into thousands of subsets and clustering each subset separately. Using dynamic clustering by synchronization, each subset is then represented by a set of point attractors and outliers. Finally, CIPA identifies the…

A Novel Clustering Algorithm based on a Non-parametric "Anti-Bayesian" Paradigm

2015

The problem of clustering, or unsupervised classification, has been solved by a myriad of techniques, all of which depend, either directly or implicitly, on the Bayesian principle of optimal classification. To be more specific, within a Bayesian paradigm, if one is to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the distance from the corresponding means or central points in the respective distributions. When this principle is applied in clustering, one would assign an unassigned sample into the cluster whose mean is the closest, and this can be done in either a bottom-up or a top-dow…