Essays about: "granular"

Showing result 1 - 5 of 114 essays containing the word granular.

  1. 1. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Alexander Florean; [2024]
    Keywords : Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

    Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE

  3. 2. Stability improvement to a ruthenium catalyst for partial oxidation of methane

    University essay from Lunds universitet/Kemiteknik (CI)

    Author : Melker Axelsson; [2023]
    Keywords : catalysis; reaction engineering; kinetics; partial oxidation; chemical engineering; Technology and Engineering;

    Abstract : Catalytic partial oxidation of methane (CPOM) is an energy-efficient alternative to steam reforming, the currently prevailing method for energy production from natural gas. Hulteberg Chemistry & Engineering AB has developed a catalyst for the partial oxidation of methane into syngas, for use in solid oxide fuel cells. READ MORE

  4. 3. Is two stage GAC better than one stage GAC for removing PFAS at a DWTP? : Investigation of PFAS removal from drinking water using two stage granular activated carbon (GAC) filter

    University essay from Uppsala universitet/Institutionen för geovetenskaper

    Author : Oliver Ekesiöö; [2023]
    Keywords : GAC; PFAS; drinking water treatment; two stage GAC;

    Abstract : The removal of 34 per- and polyfluoroalkyl substances (PFAS) were compared in a 1 stagegranular activated carbon (GAC) filtration to a 2 stage GAC filtration in a pilot study at adrinking water treatment plant (DWTP). The PFASs that were present in the water wereperfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluoropentanoic acid(PFPeA), perfluorohexanoic acid (PFHxA), perfluoroheptanoic acid (PFHpA), perfluorobutanesulfonic acid (PFBS), perfluoropentane sulfonic acid (PFPeS) and perfluorohexane sulfonic acid(PFHxS). READ MORE

  5. 4. Yearly distribution and composition of per- and polyfluoroalkyl substances (PFAS) in Luleå wastewater treatment plant

    University essay from Luleå tekniska universitet/Institutionen för samhällsbyggnad och naturresurser

    Author : Moa Sjöberg; [2023]
    Keywords : PFAS; WWTP; Wastewater treatment; Consumer products; Precursors;

    Abstract : PFAS (per- and polyfluoroalkyl substances) are a large group of substances that are used in a large variety of products because of their unique water and dirt repellent properties. The substances are extremely persistent and can spread over large distances in groundwater, surface water, and in the air, which makes them an environmental and a health concern. READ MORE

  6. 5. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Atena Nazem; [2023]
    Keywords : Generative Adversarial Networks; privacy-preserving language models; clinical text data; reinforcement learning; synthetic data;

    Abstract : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. READ MORE