15,748 research outputs found
Key issues on partial least squares (PLS) in operations management research: A guide to submissions
Purpose: This work aims to systematise the use of PLS as an analysis tool via a usage guide or
recommendation for researchers to help them eliminate errors when using this tool.
Design/methodology/approach: A recent literature review about PLS and discussion with experts in
the methodology.
Findings: This article considers the current situation of PLS after intense academic debate in recent years,
and summarises recommendations to properly conduct and report a research work that uses this
methodology in its analyses. We particularly focus on how to: choose the construct type; choose the
estimation technique (PLS or CB-SEM); evaluate and report the measurement model; evaluate and report
the structural model; analyse statistical power.
Research limitations: It was impossible to cover some relevant aspects in considerable detail herein:
presenting a guided example that respects all the report recommendations presented herein to act as a
practical guide for authors; does the specification or evaluation of the measurement model differ when it
deals with first-order or second-order constructs?; how are the outcomes of the constructs interpreted
with the indicators being measured with nominal measurement levels?; is the Confirmatory Composite
Analysis approach compatible with recent proposals about the Confirmatory Tetrad Analysis (CTA)?
These themes will the object of later publications.
Originality/value: We provide a check list of the information elements that must contain any article
using PLS. Our intention is for the article to act as a guide for the researchers and possible authors who
send works to the JIEM (Journal of Industrial and Engineering Management). This guide could be used by
both editors and reviewers of JIEM, or other journals in this area, to evaluate and reduce the risk of bias
(Losilla, Oliveras, Marin-Garcia & Vives, 2018) in works using PLS as an analysis procedure
ITERL: A Wireless Adaptive System for Efficient Road Lighting
This work presents the development and construction of an adaptive street lighting system
that improves safety at intersections, which is the result of applying low-power Internet of Things
(IoT) techniques to intelligent transportation systems. A set of wireless sensor nodes using the
Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard with additional internet
protocol (IP) connectivity measures both ambient conditions and vehicle transit. These measurements
are sent to a coordinator node that collects and passes them to a local controller, which then makes
decisions leading to the streetlight being turned on and its illumination level controlled. Streetlights
are autonomous, powered by photovoltaic energy, and wirelessly connected, achieving a high degree
of energy efficiency. Relevant data are also sent to the highway conservation center, allowing it to
maintain up-to-date information for the system, enabling preventive maintenance.Consejería de Fomento y Vivienda Junta de Andalucía G-GI3002 / IDIOFondo Europeo de Desarrollo Regional G-GI3002 / IDI
Publishing performance in economics: Spanish rankings (1990-1999)
This paper contributes to the growing literature that analyses the Spanish publishing performance in Economics throughout the 1990s. Several bibliometric indicators are used in order to provide Spanish rankings (of both institutions and individual authors) based on Econlit journals. Further, lists of the ten most influential authors and articles over that period, in terms of citations, are reported.Publicad
Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad TIN2013-46801-C4-1-
Louis Feuillée y el primer meridiano
No hace mucho las Islas Canarias figuraban en los mapas y cartas de navegación con dos meridianos origen. Uno situado en algún punto indeterminado de la isla de El Hierro y el otro pasando por el Pico Teide. Aquí se cuenta la primera expedición científica enviada por la Academia Real de Ciencias de Francia para establecer la posición exacta de ambos meridianos con respecto al Observatoria Real de París. La empresa, encomendada al matemático real Louis Feuillée, contiene observaciones astronómicas y cálculos matemáticos que llevaron a la Academia a fijar, por primera vez, y de forma científica, tales meridianos
Solar Axion search with Micromegas detectors in the CAST Experiment with He as buffer gas
Axions are well motivated particles proposed in an extension of the SM as a
solution to the strong CP problem. Also, there is the category of Axion-Like
Particles (ALPs) which appear in extensions of the SM and share the same
phenomenology of the axion. Axions and ALPs are candidates to solve the Dark
Matter problem. CAST, the CERN Axion Solar Telescope is looking for solar
axions since 2003. CAST exploit the helioscope technique using a decommissioned
LHC dipole magnet in which solar axions could be reconverted into photons.
Three of the four detectors operating at CAST are of the Micromegas type. The
analysis of the data of the three Micromegas detectors during the 2011 data
taking campaign at CAST is presented in this thesis, obtaining a limit on the
coupling constant of g < 3.90 10 GeV at a
95 of confidence level, for axion masses from 1 to 1.17 eV. CAST Micromegas
detectors exploit different strategies developed for the reduction of the
background level. Moreover, different test benches have been developed in order
to understand the origin of the background. The state of art in low background
techniques is shown in the upgrades of the Micromegas detectors at CAST, which
has led to a reduction of the background in a factor 6. It translates in
an improvement of the sensitivity of CAST in a factor 2.5. Beyond CAST a
new generation axion helioscope has been proposed: IAXO-the International Axion
Observatory. IAXO will enhance the helioscope technique by exploiting all the
singularities of CAST implemented into a large superconducting toroidal magnet,
dedicated X-ray optics and ultra-low background detectors. A description of the
IAXO proposal and the study of the sensitivity of IAXO are presented in this
thesis. IAXO will surpass CAST in more than one order of magnitude, entering
into an unexplored parameter space area.Comment: PhD. Thesi
Spreadsheet as a didactic tool to teach and learn financial math
In this document we propose a methodology to teach financial mathematics, using a spreadsheet as a didactic tool. We describe the traditional education process in a specific topic of mathematics, “debt restructuring and modeling with equivalent-equation” from the theoretical explanation to design a financial simulator programmed in a spreadsheet. After this, the result will be verified and validated by the designed software.TIC, Financial mathematics, teaching-learning process, financial tools.
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