Comparing supervised learning algorithms for Spatial Nominal Entity recognition

International audienceDiscourse may contain both named and nominal entities. Most common nouns or nominal mentions in natural language do not have a single, simple meaning but rather a number of related meanings. This form of ambiguity led to the development of a task in natural language processing known as Word Sense Disambiguation. Recognition and categorisation of named and nominal entities is an essential step for Word Sense Disambiguation methods. Up to now, named entity recognition and categorisation systems mainly focused on the annotation, categorisation and identification of named entities. This paper focuses on the annotation and the identification of spatial nominal entities. We explore the combination of Transfer Learning principle and supervised learning algorithms, in order to build a system to detect spatial nominal entities. For this purpose, different supervised learning algorithms are evaluated with three different context sizes on two manually annotated datasets built from Wikipedia articles and hiking description texts. The studied algorithms have been selected for one or more of their specific properties potentially useful in solving our problem. The results of the first phase of experiments reveal that the selected algorithms have similar performances in terms of ability to detect spatial nominal entities. The study also confirms the importance of the size of the window to describe the context, when word-embedding principle is used to represent the semantics of each word

Study of the effects of laser power and scanning speed on the microstructural morphologies and physical properties of L-PBF produced Ni52.39Ti47.61

This study examined the effect of variations in the laser power and scan speed for 52.39 at.%Ni-47.61 at.%Ti samples produced via laser powder bed fusion (L-PBF). The laser power was varied between 150W and 180 W, the scanning speeds were varied between 500 mm/s and 1000 mm/s, and other process parameters were kept constant. The resulting microstructures and physical properties of the produced samples were evaluated. In particular, the phase type and phase transformation characteristics, composition, Vickers microhardness, and microstructures were examined. It was observed that variation in the mean microhardness and relative density were not significant at a constant scan speed of 1000 mm/s, regardless of the laser power value. Samples processed at a laser power of 180W (with all other parameters kept constant) exhibited a bimodal micro- and nano structures. It was found that the samples with bimodal microstructure had a higher lattice strain, extent of B2 phase, and higher phase transformation temperatures

Resultant physical properties of as-built nitinol processed at specific volumetric energy densities and correlation with in-situ melt pool temperatures

In this study, direct comparisons between the properties of three groups of as-built nitinol (NiTi) samples fabricated using three pre-determined volumetric energy densities (VED) as calculated based on hatch spacings (VEDH = 40, 80, and 120 J/mm3), were examined. The additive manufacturing technique adopted is the powder bed fusion using a laser beam (PBF-LB), and the powder feedstock is Ni50Ti50. Although the three VEDH's increased by 100% for each sample group, each VEDH value was within the range of those recommended in the literature, as well as equivalent to 100 J/mm3 (VEDf), VED as calculated based on laser spot size. Significant differences were found between the thermal profiles and normalised thermal gradients, resulting in compositional differences, defects, phase, and phase transformation behaviour, Young's modulus, hardness, and microstructure. Thermal gradients and full-wave amplitude of the in-situ melt pool thermal radiation waveforms increased as VEDH increased. Higher VEDH's resulted in more martensitic NiTi samples with larger melt pool volume and >98% sample relative density. Austenite transformation temperatures increased with an increase in at.% Ti for each increase in VEDH, consequent on the higher normalised average melt pool temperatures. The calculated thermal gradient (normalised) was correlated to higher thermal stresses as VEDH increased, resulting in residual stress-induced weld-metal liquation microcracks. This work has demonstrated the potential of post-processed in-situ melt pool thermal radiation data, in providing insights into the physical property variations of as-built nitinol samples fabricated via PBF-LB

Effect of geometry on the coefficient of performance of Ni–Ti elastocaloric parts manufactured via powder bed fusion

This study investigates the greater coefficient of Performance (COP) exhibited by the Ni–Ti lattice geometry (LS) over the solid geometry (SS) for solid-state heating and cooling. The LS's advantageous COP can be attributed to factors including variations in phase transformation behavior, a larger surface area facilitating enhanced heat transfer, and a greater volume of water heated per cycle owing to the cavities. Moreover, the LS demands lower compression forces due to its lower mass and geometry, which contribute to its heightened energy efficiency. Remarkably, the LS achieved a maximum temperature span of 11.2 °C at 40 kN compression force, whereas the SS required 80 kN to attain a similar 12.9 °C span. Both the SS and LS showcased a non-linear correlation with compression force which was attributed to Lauder's transformation and pseudo-elastic behaviors. Additionally, the temperature span of the SS exhibited symmetrical behavior during heating-cooling cycles. Conversely, the LS displayed asymmetry, with a more substantial temperature change during the cooling phase than the heating phase