2 resultados para Inversion of gender roles

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


Relevância:

100.00% 100.00%

Publicador:

Resumo:

This dissertation has two main purposes. On the one hand, it aims at comparing the gender stereotypes presented in the television commercials in China and in Europe. Considering the cultural, historical and socio-economical differences between these two contexts, it is interesting to examine the gender role models offered and used by the advertising industry in European Union and China in order to see if the gender stereotypes are similar and to evaluate to which extent they reflect, challenge or reinforce the gender roles of the society where they are broadcasted. On the other hand, the objective of this dissertation is to establish the degree of adequateness and effectiveness of the existing regulatory framework through an analysis of the positive and negative aspects of the regulatory acts issued to safeguard a fair representation of genders in the EU Member States and in China.

Relevância:

100.00% 100.00%

Publicador:

Resumo:

Privacy issues and data scarcity in PET field call for efficient methods to expand datasets via synthetic generation of new data that cannot be traced back to real patients and that are also realistic. In this thesis, machine learning techniques were applied to 1001 amyloid-beta PET images, which had undergone a diagnosis of Alzheimer’s disease: the evaluations were 540 positive, 457 negative and 4 unknown. Isomap algorithm was used as a manifold learning method to reduce the dimensions of the PET dataset; a numerical scale-free interpolation method was applied to invert the dimensionality reduction map. The interpolant was tested on the PET images via LOOCV, where the removed images were compared with the reconstructed ones with the mean SSIM index (MSSIM = 0.76 ± 0.06). The effectiveness of this measure is questioned, since it indicated slightly higher performance for a method of comparison using PCA (MSSIM = 0.79 ± 0.06), which gave clearly poor quality reconstructed images with respect to those recovered by the numerical inverse mapping. Ten synthetic PET images were generated and, after having been mixed with ten originals, were sent to a team of clinicians for the visual assessment of their realism; no significant agreements were found either between clinicians and the true image labels or among the clinicians, meaning that original and synthetic images were indistinguishable. The future perspective of this thesis points to the improvement of the amyloid-beta PET research field by increasing available data, overcoming the constraints of data acquisition and privacy issues. Potential improvements can be achieved via refinements of the manifold learning and the inverse mapping stages during the PET image analysis, by exploring different combinations in the choice of algorithm parameters and by applying other non-linear dimensionality reduction algorithms. A final prospect of this work is the search for new methods to assess image reconstruction quality.