Sökning: "quality score"

Visar resultat 1 - 5 av 393 uppsatser innehållade orden quality score.

  1. 1. Combining Value Investing with Quality Investing: Empirical Evidence from the European and Nordic Stock Markets

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Oleksii Chepil; [2024]
    Nyckelord :value investing; quality investing;

    Sammanfattning : The aim of this thesis is to explore whether stock selection based on five value metrics and six quality metrics can generate superior returns compared to the overall market. The selected markets are the Nordic one (Nasdaq OMX Nordic 120 being the benchmark) and the European one (STOXX Europe 600 being the benchmark), while the selected time period is 2001-2023 for Europe and 2010-2023 for the Nordics. LÄS MER

  3. 2. Virtual H&E Staining Using PLS Microscopy and Neural Networks

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Sally Vizins; Hanna Råhnängen; [2024]
    Nyckelord :Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

    Sammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER

  4. 3. Adherence to Treatment Advice in Patients with Heart Failure : Connections to mental health, social and socioeconomic factors

    Master-uppsats, Malmö universitet/Institutionen för vårdvetenskap (VV)

    Författare :Moa Lassbo Lundquist; [2024]
    Nyckelord :Adherence; non-adherence; self-care; heart failure; multidisciplinary teams;

    Sammanfattning : Aim: The aim of this study is to examine adherence among patients with HF and its potential association with mental health, social support and socioeconomic status.  Introduction: For patients with heart failure, self-care is strongly advised, encompassing prescribed medication intake, fluid reduction and weight control to maintain stability. LÄS MER

  5. 4. Effektivisering av SAQ 5.0 för SME:s : Att möta utmaningarna inför SAQ 5.0 hos Företag X och svenska SME:s

    Kandidat-uppsats, Jönköping University/Tekniska Högskolan

    Författare :Alexander Aronsson; [2024]
    Nyckelord :Global changes; Sustainability regulations; Suppliers to the automotive industry; Documentation in sustainability; Policies and certifications; Global Automotive Sustainability Guiding Principles; Drive Sustainability; Self-Assessment Questionnaire SAQ ; SAQ 5.0; SAQ 4.0; Environmental and quality management systems; Gap analysis; SME Small and Medium-sized Enterprises ; Hållbarhetsregleringar; Leverantörer till fordonsindustrin; Dokumentering inom hållbarhet; Policys och certifieringar; Miljö- och kvalitetsledningssystem; Gap-analys; SME Små och medelstora företag ; SAQ 4.0; SAQ 5.0;

    Sammanfattning : The current global changes and regulations in sustainability have a direct impact on suppliers to the automotive industry. Therefore, it is crucial for suppliers to the automotive industry to proactively monitor developments to avoid risking their competitiveness. LÄS MER

  7. 5. Combining Cell Painting, Gene Expression and Structure-Activity Data for Mechanism of Action Prediction

    Master-uppsats, Uppsala universitet/Nationellt resurscentrum för biologi och bioteknik

    Författare :Erik Everett Palm; [2023]
    Nyckelord :bioinformatics; deep learning; machine learning; joint model; tabular data; image data;

    Sammanfattning : The rapid progress in high-throughput omics methods and high-resolution morphological profiling, coupled with the significant advances in machine learning (ML) and deep learning (DL), has opened new avenues for tackling the notoriously difficult problem of predicting the Mechanism of Action (MoA) for a drug of clinical interest. Understanding a drug's MoA can enrich our knowledge of its biological activity, shed light on potential side effects, and serve as a predictor of clinical success. LÄS MER