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

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

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

    Abstract : 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. READ MORE

  3. 2. 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)

    University essay from Lunds universitet/Graduate School

    Author : Luis Felipe Villota Macias; [2024]
    Keywords : 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;

    Abstract : 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. READ MORE

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

    University essay from Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

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

    Abstract : 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. READ MORE

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

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Nikolaos Staikos; [2024]
    Keywords : 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;

    Abstract : 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. READ MORE

  6. 5. Evaluation of OPAL-RT Simulator through Simulation of Microgrid with High Penetration of DER

    University essay from Uppsala universitet/Elektricitetslära

    Author : Anton Grönberg; [2024]
    Keywords : Real-Time simulation; Power System Simulation; OPAL; DER;

    Abstract : This thesis was written in collaboration with the department of electrical engineering at Uppsala University. It evaluates and tests the potentials and limitations of using the OPAL-RT simulator as a tool for designing and developing control strategies used in microgrids with a high penetration of distributed energy resources. READ MORE