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O sujeito neoliberal mirim: a semântica da obediência retratada em vídeos de YouTube
(Universidade Federal de São Carlos, 2023-07-13) Calonego, Mariana; Gatti, Márcio Antonio; https://lattes.cnpq.br/0369563657842763; https://orcid.org/0000-0001-9902-2856; https://lattes.cnpq.br/1241344833528211; https://orcid.org/0000-0001-9786-5470
Considering childhood as a product of culture, his understanding requires the comprehension of social organization modes. Under the globalized logic of capitalism, subjectivities embody the neoliberal logic of performance and competitiveness. Adding technological dominance in people's daily lives, ways of working, relationships and desire undergo important transformations in contemporary times. In face of this, childhood suffers the consequences. Being assigned to children’s the role of corresponding to an overqualified place, they are expected to become, ever earlier, ready for future participation in a competitive labor market. “Already being” becomes the imperative of this moment. Access to digitality, fosters this logic and allows for a type of social participation that goes in the direction of “already being” a professional: young youtuber. In this research, we used the YouTube video platform to investigate the role of children nowadays. Based on Discourse Analysis, we analyzed videos starring children’s and identified aspects that put them in similar conditions to those of the neoliberal subject. The results of the data analysis, indicate a professionalization of the channels that, together with the present narratives in the videos, enunciate a neoliberal discourse. In addition, the dedication of the channels to a supposed transmission of conduct parameters to children, engenders the idea of a semantics of obedience, which seems to translate what is socially expected from children.
Anotação semântica baseada em ontologia aplicada em imagens médicas
(Universidade Federal de São Carlos, 2023-07-13) Pereira, Juliana Wolf; Ribeiro, Marcela Xavier; https://lattes.cnpq.br/0300141044144026; https://orcid.org/0000-0002-2323-5326; https://lattes.cnpq.br/1512389839368718; https://orcid.org/0009-0003-2314-7881
Breast cancer is one of the most common types of cancer among women in Brazil and worldwide. Early diagnosis of a breast lesion is a priority for effective treatment at lower costs, with mammography being the most used exam. In this doctoral research, was developed the MUSA method to classify and semantically annotate mammography images based on the fusion of multimodal information, providing a fuller image annotation than the current state of the art. For this, the approach includes a text mining process, an image mining process, and an ontology engineering process. With the text mining process, it is possible to establish the contextual features based on similarity and co-occurrence relations between pairs of words in the same medical report. The image mining process allows classifying a mammography image using an end-to-end deep learning strategy. In the ontology engineering process, we built the AnotaMammo ontology, composed of the annotation ontology and the Mammo domain ontology. AnotaMammo allows the semantic annotation of mammography images. The text mining results were used to generate semantic rules, included in AnotaMammo. The results of the image mining process surpassed or compared with studies published in the literature, reaching more than 92% accuracy for classifying lesions as mass or calcification. The results also demonstrate that the AnotaMammo ontology adequately performed the semantic enrichment of the classification, in addition to having adequately performed the fusion of multimodal information. Finally, the MUSA method adds information to make the result more semantic and interpretable, thus reducing the semantic gap.
O uso de algoritmos de classificação para determinar estoques de segurança
(Universidade Federal de São Carlos, 2023-07-13) Sanches, Felipe Norato; França, Celso Aparecido de; https://lattes.cnpq.br/4547836128892982; https://orcid.org/0000-0003-2235-9551; https://lattes.cnpq.br/1413814764753839
This work analyzes the application of different Artificial Neural Network algorithms with the objective of classifying candidate products for safety stock parameterization based on the purchase history of these products. The study brings discussions about the importance of the quality of the treated data and the importance of analyzing the problem, the objectives and the balance between the level of customer service, that is, the expected execution time, and the cost of inventory. K-means, affinity propagation, mean displacement and hierarchical clustering algorithms, which include the Ward and complete linkage methods, were studied. Through the application of these algorithms, it was possible to generate distribution graphs of classified points and calculate the correlation of the groups found by the different algorithms. For the presented problem, an optimal number of groups value was determined for a better classification of the products. The algorithms that showed the highest correlation were the K-means and Ward algorithms, which provided an efficient classification of data into 3 groups.
Jogando em casa na pandemia: um estudo brasileiro de crianças de 1 a 10 anos no isolamento social pelo COVID -19
(Universidade Federal de São Carlos, 2023-07-13) Pereira, Natássia Novaes; Sommerhalder, Aline; https://lattes.cnpq.br/4775432120371947; https://lattes.cnpq.br/8552051554358905
Nel 2020 molti Paesi sono stati improvvisamente sorpresi dal contagio accelerato e incontrollato del virus SARS-COV-2 (COVID-19). Nel marzo dello stesso anno, l'Organizzazione Mondiale della Sanità classificò il contagio come pandemia, dando il via a misure urgenti per controllare il contagio. In questo modo, il mondo intero ha iniziato ad adottare misure per affrontare la pandemia in modo da superarla. La presente ricerca si concentra sulla conoscenza e sull'esame del gioco dei bambini nell'isolamento sociale nelle case domestiche, a causa della pandemia. Il presente rapporto di ricerca è stato strutturato in quattro sezioni: sul gioco; sul bambino come soggetto di diritto e sull'infanzia virtuale; sull'educazione scolastica, in particolare la fase della scuola dell'infanzia e dei primi anni della scuola primaria, prendendo come base teorica la letteratura nel campo del gioco infantile e dell'educazione scolastica. Intreccia riflessioni sull'educazione a distanza e la vita quotidiana; sulla famiglia contemporanea e le sue caratteristiche relazionali e considerazioni sul rapporto tra famiglia e scuola, oltre che sulla famiglia nel contesto di una pandemia o di malattie con un'ampia gamma di contaminazioni. Questa ricerca deriva da uno studio più ampio e ha cercato di rispondere: durante il periodo di isolamento sociale, con cosa giocavano (giocano) i bambini brasiliani nelle loro residenze (case)? L'obiettivo è stato quello di identificare e descrivere, attraverso un esame del COVID-19, i giochi che si verificano nella vita quotidiana domestica dei bambini brasiliani durante l'isolamento sociale. Si tratta di uno studio quali-quantitativo che ha utilizzato un questionario online (e-survey) come strumento di raccolta, ottenendo 541 risposte da adulti, familiari di bambini. I risultati ottenuti sono stati organizzati nella prospettiva qualitativa, attraverso la domanda aperta (domanda 12) e ordinati per mezzo di assi e nell'aspetto quantitativo, i risultati sono stati organizzati attraverso un formato "grafico a torta". Lo studio ha verificato una maggiore partecipazione degli intervistati dello stato di San Paolo, che vivono in casa e fuori dai condomini chiusi. Ha anche verificato una maggiore partecipazione delle madri nelle risposte a questo sondaggio rispetto ai padri. Lo studio ha anche accertato che i bambini non hanno smesso di giocare e hanno fatto ricorso a innumerevoli attività, dentro e fuori casa, con ciò che era loro possibile. Infine, lo studio mostra un aumento, tra i partecipanti, del consumo di schermi da parte dei bambini durante la pandemia.
Partial automation of the seismic to well tie with the matching region estimation and segmented global optimization
(Universidade Federal de São Carlos, 2023-07-13) Silva, Rafael da Costa; Silva, Diego Furtado; https://lattes.cnpq.br/7662777934692986; https://orcid.org/0000-0002-5184-9413; https://lattes.cnpq.br/9614463991077343; https://orcid.org/0000-0002-9394-9869
Geophysical interpretation plays a fundamental role in the oil and gas exploration domain. Various geophysical methods can be employed to extract information about the geological configuration of rocks. The well-to-seismic tie, which involves matching well log profiles with observed seismograms, is a crucial activity in the processing and interpreting of seismic amplitudes. During the exploration phase, the seismic tie process helps the interpreter to understand the well region's seismic wavelet and the time-depth relationship. However, data noise and inherent uncertainties make the seismic tie time-consuming. This way, we propose a significant automation of the seismic tie process that estimates the probable alignment region and automatically aligns the seismic traces through segmented global optimization. The alignment region is estimated based on the velocity profile and alignment using the Dynamic Time Warping (DTW) algorithm. The three proposed methods accurately estimated the well base position in the seismic trace for most of the tested wells. Our approach performs the segmentation of the tying process by utilizing the time-depth relationship obtained from the initial alignment of synthetic and seismic traces using Constrained DTW. The segmentation of the Differential Evolution (DE) tying process increased the final correlation in all tested wells, with four achieving a correlation higher than 70% without causing unrealistic velocity variations.