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Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
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Bardia Rafieian, Pedro Hermosilla and Pere-Pau Vázquez
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim ...
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Maurizio Arena, Paolo Ambrogiani, Vincenzo Raiola, Francesco Bocchetto, Tommaso Tirelli and Martina Castaldo
The continuous pursuit of reducing weight and optimizing manufacturing processes is increasingly demanded in transportation vehicles, particularly in the aerospace field. In this context, additive manufacturing (AM) represents a well-known technique suit...
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Qingqing Li, Yuming Tao and Fanghua Jiang
In the past few years, distant retrograde orbits (DROs) have become increasingly popular due to their conspicuous stability. Nevertheless, it is this characteristic that results in the challenge to the design of transfer orbits into/out of DROs. This pap...
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