78 research outputs found
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Efficiency of evolutionary algorithms in water network pipe sizing
The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems
An integrated online radioassay data storage and analytics tool for nEXO
Large-scale low-background detectors are increasingly used in rare-event
searches as experimental collaborations push for enhanced sensitivity. However,
building such detectors, in practice, creates an abundance of radioassay data
especially during the conceptual phase of an experiment when hundreds of
materials are screened for radiopurity. A tool is needed to manage and make use
of the radioassay screening data to quantitatively assess detector design
options. We have developed a Materials Database Application for the nEXO
experiment to serve this purpose. This paper describes this database, explains
how it functions, and discusses how it streamlines the design of the
experiment
Performance of novel VUV-sensitive Silicon Photo-Multipliers for nEXO
Liquid xenon time projection chambers are promising detectors to search for
neutrinoless double beta decay (0), due to their response
uniformity, monolithic sensitive volume, scalability to large target masses,
and suitability for extremely low background operations. The nEXO collaboration
has designed a tonne-scale time projection chamber that aims to search for
0 of \ce{^{136}Xe} with projected half-life sensitivity of
~yr. To reach this sensitivity, the design goal for nEXO is
1\% energy resolution at the decay -value (~keV).
Reaching this resolution requires the efficient collection of both the
ionization and scintillation produced in the detector. The nEXO design employs
Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm
scintillation light of liquid xenon. This paper reports on the characterization
of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3
SiPMs specifically designed for nEXO, as well as new measurements on new test
samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters
(MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct
crosstalk, correlated avalanches and photon detection efficiency were measured
as a function of the applied over voltage and wavelength at liquid xenon
temperature (163~K). The results from this study are used to provide updated
estimates of the achievable energy resolution at the decay -value for the
nEXO design
E-commerce ethics and its impact on buyer repurchase intentions and loyalty: an empirical study of small and medium Egyptian businesses
The theoretical understanding of e-commerce has received much attention over the years; however, relatively little focus has been directed towards e-commerce ethics, especially the SMEs B2B e-commerce aspect. Therefore, the purpose of this paper is to develop and empirically test a framework that explains the impact of SMEs B2B e-commerce ethics on buyer repurchase intentions and loyalty. Using SEM to analyse the data collected from a sample of SME e-commerce firms in Egypt, the results indicate that buyers’ perceptions of supplier ethics construct is composed of six dimensions (security, non-deception, fulfilment/reliability, service recovery, shared value, and communication) and strongly predictive of online buyer repurchase intentions and loyalty. Furthermore, our results also show that reliability/fulfilment and non-deception are the most effective relationship-building dimensions. In addition, relationship quality has a positive effect on buyer repurchase intentions and loyalty. The results offer important implications for B2B e-commerce and are likely to stimulate further research in the area of relationship marketing
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