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Visar resultat 1 - 5 av 2462 uppsatser som matchar ovanstående sökkriterier.

1. 1. Feature Selection for Microarray Data via Stochastic Approximation

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Erik Rosvall; [2024-03-18]
   Nyckelord :feature selection; feature ranking; microarray data; stochastic approximation; Barzilai and Borwein method; Machine Learning; AI;

   Sammanfattning : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. LÄS MER

3. 2. The Sound of Skepticism Analyzing Climate Change Denial in Swedish Podcasts and YouTube Channels

   Kandidat-uppsats, Göteborgs universitet / / Institutionen för sociologi och arbetsvetenskap

   Författare :Victoria Vallström; [2024-02-14]
   Nyckelord :denialism; climate skepticism; social movements; countermovements; digital media; digital data; computational grounded theory; topic modeling; computational text analysis;

   Sammanfattning : This study explores Sweden's climate change denial by analyzing the spoken-word discourse of its countermovement, focusing on digital media content from Swedish parliament member Elsa Widding with an aim to provide empirical insights into the discourse of Sweden's Climate Change Countermovement (CCCM). Questions guiding this study are: What are the most prevalent topics and themes related to climate change denial and skepticism? How do they align with established categories of climate change denial, shaping the overall narrative? What mobilizing ideas and meanings are present, how are they shaped, and how do they contribute to the movement's goals? The material consists of Elsa Widding's complete audio-based "movement texts'' from 2019-2023, including YouTube content, podcasts, and appearances on Riks, totaling over 2000 minutes of audio transcribed into text via AI technology. LÄS MER

4. 3. Prevalent Discord. Exploring and estimating the prevalence of the type of user disagreement on news media Facebook posts discussing the Colombian peace process (2020-2022)

   Master-uppsats, Lunds universitet/Graduate School

   Författare :Luis Felipe Villota Macias; [2024]
   Nyckelord :Agonistic peace; antagonism; big data analytics; binary logistic regression; computational content analysis; Colombia; Colombian peace process; discord; Facebook; machine learning; peace process; public opinion and sentiment; social media; Law and Political Science; Social Sciences;

   Sammanfattning : This thesis is dedicated to exploring and understanding public reactions within negotiated peace settlements based on social media data. Concretely, to modeling public opinion and sentiment within the context of the Colombian peace process using a curated dataset of N= ~1. LÄS MER

5. 4. Optical Communication using Nanowires and Molecular Memory Systems

   Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

   Författare :Thomas Kjellberg Jensen; [2024]
   Nyckelord :neuromorphic computing; nanowire; molecular dye; DASA photoswitch; OBIC; Physics and Astronomy;

   Sammanfattning : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. LÄS MER

7. 5. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

   Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Nikolaos Staikos; [2024]
   Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

   Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER