1,721,050 research outputs found
Accelerating Machine Learning Queries with Linear Algebra Query Processing
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments, leading to redundant engineering and computations. Additionally, the diverging mathematical foundations of data processing and machine learning hinder cross-optimizations by combining these two components, thereby overlooking potential opportunities to expedite predictive pipelines. In this paper, we propose an operator fusing method based on GPU-accelerated linear algebraic evaluation of relational queries. Our method leverages linear algebra computation properties to merge operators in machine learning predictions and data processing, significantly accelerating predictive pipelines by up to 317x. We perform a complexity analysis to deliver quantitative insights into the advantages of operator fusion, considering various data and model dimensions. Furthermore, we extensively evaluate matrix multiplication query processing utilizing the widely-used Star Schema Benchmark. Through comprehensive evaluations, we demonstrate the effectiveness and potential of our approach in improving the efficiency of data processing and machine learning workloads on modern hardware.Web Information System
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
DRIVE: A Distributed Economic Meta-Scheduler for the Federation of Grid and Cloud Systems
The computational landscape is littered with islands of disjoint resource providers including
commercial Clouds, private Clouds, national Grids, institutional Grids, clusters, and data centers.
These providers are independent and isolated due to a lack of communication and coordination,
they are also often proprietary without standardised interfaces, protocols, or execution environments.
The lack of standardisation and global transparency has the effect of binding consumers
to individual providers. With the increasing ubiquity of computation providers there is an opportunity
to create federated architectures that span both Grid and Cloud computing providers
effectively creating a global computing infrastructure. In order to realise this vision, secure and
scalable mechanisms to coordinate resource access are required. This thesis proposes a generic
meta-scheduling architecture to facilitate federated resource allocation in which users can provision
resources from a range of heterogeneous (service) providers.
Efficient resource allocation is difficult in large scale distributed environments due to the inherent
lack of centralised control. In a Grid model, local resource managers govern access to a
pool of resources within a single administrative domain but have only a local view of the Grid
and are unable to collaborate when allocating jobs. Meta-schedulers act at a higher level able to
submit jobs to multiple resource managers, however they are most often deployed on a per-client
basis and are therefore concerned with only their allocations, essentially competing against one
another. In a federated environment the widespread adoption of utility computing models seen in
commercial Cloud providers has re-motivated the need for economically aware meta-schedulers.
Economies provide a way to represent the different goals and strategies that exist in a competitive
distributed environment. The use of economic allocation principles effectively creates an
open service market that provides efficient allocation and incentives for participation.
The major contributions of this thesis are the architecture and prototype implementation of the
DRIVE meta-scheduler. DRIVE is a Virtual Organisation (VO) based distributed economic metascheduler
in which members of the VO collaboratively allocate services or resources. Providers
joining the VO contribute obligation services to the VO. These contributed services are in effect
membership “dues” and are used in the running of the VOs operations – for example allocation,
advertising, and general management. DRIVE is independent from a particular class of provider
(Service, Grid, or Cloud) or specific economic protocol. This independence enables allocation in
federated environments composed of heterogeneous providers in vastly different scenarios. Protocol
independence facilitates the use of arbitrary protocols based on specific requirements and
infrastructural availability. For instance, within a single organisation where internal trust exists,
users can achieve maximum allocation performance by choosing a simple economic protocol.
In a global utility Grid no such trust exists. The same meta-scheduler architecture can be used
with a secure protocol which ensures the allocation is carried out fairly in the absence of trust.
DRIVE establishes contracts between participants as the result of allocation. A contract describes
individual requirements and obligations of each party. A unique two stage contract negotiation
protocol is used to minimise the effect of allocation latency. In addition due to the co-op nature of
the architecture and the use of secure privacy preserving protocols, DRIVE can be deployed in a
distributed environment without requiring large scale dedicated resources.
This thesis presents several other contributions related to meta-scheduling and open service
markets. To overcome the perceived performance limitations of economic systems four high utilisation
strategies have been developed and evaluated. Each strategy is shown to improve occupancy,
utilisation and profit using synthetic workloads based on a production Grid trace. The
gRAVI service wrapping toolkit is presented to address the difficulty web enabling existing applications.
The gRAVI toolkit has been extended for this thesis such that it creates economically
aware (DRIVE-enabled) services that can be transparently traded in a DRIVE market without requiring
developer input. The final contribution of this thesis is the definition and architecture of
a Social Cloud – a dynamic Cloud computing infrastructure composed of virtualised resources
contributed by members of a Social network. The Social Cloud prototype is based on DRIVE
and highlights the ease in which dynamic DRIVE markets can be created and used in different
domains
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
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