Essays about: "Information Logistic"
Showing result 1 - 5 of 239 essays containing the words Information Logistic.
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1. 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 SchoolAbstract : 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
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2. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques
University essay from Lunds universitet/Matematisk statistikAbstract : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. READ MORE
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3. Failure Probability and Lifetime Estimation for Industrial Robots : A Logistic Regression and Lifetime Analysis Approach
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : The ability to handle and process data for information extraction is getting more and more important. Using extracted data from the business to improve productivity is seen as an important part in developing the business processes. In this thesis, industrial robots and their survival times are analyzed. READ MORE
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4. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE
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5. Are AI-Photographers Ready for Hire? : Investigating the possibilities of AI generated images in journalism
University essay from Uppsala universitet/Statistiska institutionenAbstract : In today’s information era, many news outlets are competing for attention. One way to cut through the noise is to use images. Obtaining images can be both time-consuming and expen- sive for smaller news agencies. READ MORE