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Mili Turic, Stipe Celar, Srdjana Dragicevic and Linda Vickovic
Effort estimation is always quite a challenge, especially for agile software development projects. This paper describes the process of building a Bayesian network model for effort prediction in agile development. Very few studies have addressed the appli...
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Yan Wang, Lei Zhao, Longhao Qiu, Jinjin Wang and Chenmu Li
The underwater maneuvering platform generates self-noise when sailing, which shows spatial directionality to the arrays fixed on the platform. In this paper, it is called spatially colored noise (SCN). The direction of arrival (DOA) estimation results ar...
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Feilong Ding, Cheng Chi, Yu Li and Haining Huang
In passive sonars, distance and depth estimation of underwater targets is often limited by the accuracy of time delay estimations. The estimation accuracy of the existing methods of time delay estimation is limited by the uniform discrete grid (signal sa...
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Alexander Robitzsch
This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non-d...
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Egor I. Chetkin, Sergei L. Shishkin and Bogdan L. Kozyrskiy
Bayesian neural networks (BNNs) are effective tools for a variety of tasks that allow for the estimation of the uncertainty of the model. As BNNs use prior constraints on parameters, they are better regularized and less prone to overfitting, which is a s...
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