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Arman Kakaie, C. Guedes Soares, Ahmad Kamal Ariffin and Wonsiri Punurai
A fracture mechanics-based fatigue reliability analysis of a submarine pipeline is investigated using the Bayesian approach. The proposed framework enables the estimation of the reliability level of submarine pipelines based on limited experimental data....
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Christos Karras, Aristeidis Karras, Konstantinos C. Giotopoulos, Markos Avlonitis and Spyros Sioutas
In the context of big-data analysis, the clustering technique holds significant importance for the effective categorization and organization of extensive datasets. However, pinpointing the ideal number of clusters and handling high-dimensional data can b...
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Hongyun Zhang, Jin Liu and Jie Liu
The geometric features of ground objects can reflect the shape, contour, length, width, and pixel distribution of ground objects and have important applications in the process of object detection and recognition. However, the geometric features of object...
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Changwon Yoo, Efrain Gonzalez, Zhenghua Gong and Deodutta Roy
Every year, biomedical data is increasing at an alarming rate and is being collected from many different sources, such as hospitals (clinical Big Data), laboratories (genomic and proteomic Big Data), and the internet (online Big Data). This article prese...
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Widyo Nugroho, Christiono Utomo and Nur Iriawan
The sustainable management of the water supply system requires methodologies to monitor, repair, or replace the aging infrastructure, but more importantly, it must be able to assess the condition of the networks and predict their behavior over time. Amon...
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Wilson Tsakane Mongwe, Rendani Mbuvha and Tshilidzi Marwala
Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis?Hastings (MH) algorithm. The MH algorithm suffers fro...
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Abolfazl Shojaei Barjouei and Masoud Naseri
Environmental conditions in Arctic waters pose challenges to various offshore industrial activities. In this regard, better prediction of meteorological and oceanographic conditions contributes to addressing the challenges by developing economic plans an...
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Katleho Makatjane and Ntebogang Moroke
During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alt...
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Filippo Landi, Francesca Marsili, Noemi Friedman and Pietro Croce
In civil and mechanical engineering, Bayesian inverse methods may serve to calibrate the uncertain input parameters of a structural model given the measurements of the outputs. Through such a Bayesian framework, a probabilistic description of parameters ...
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Munekazu Motoyoshi and Yoshiki Nishi
This study estimated the amount of bilge water spilled from ships during normal operation and identified the contributing factors of the discharge by building a statistical model. To build the statistical model, we collected as much information as possib...
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