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Visar resultat 1 - 5 av 1436 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Lisa Linard Pedersen; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

  3. 2. ML implementation for analyzing and estimating product prices

    Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
    Nyckelord :Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

    Sammanfattning : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. LÄS MER

  4. 3. Designprocessen och maskininlärning: Framtiden för användarcentrerad design

    Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Lisa Marie Karin Gärdhammar; [2024]
    Nyckelord :Artificial Intelligence; Machine Learning; Design process; Journey Mapping; Empathy; User experience; Customer experience; Artificiell intelligens; Maskininlärning; Designprocessen; Journey Mapping; Empati; Användarupplevelse; Kundupplevelse;

    Sammanfattning : Artificiell intelligens (AI) och i synnerhet maskininlärning (ML) har inom UX-design visat potential att förbättra designprocessen genom att exempelvis identifiera användargrupper från stora datamängder, effektivisera idégenerering och automatisera repetitiva uppgifter. Det råder dock oenighet kring hur tekniken kan integreras i designprocessen. LÄS MER

  5. 4. Log Frequency Analysis for Anomaly Detection in Cloud Environments

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Prathyusha Bendapudi; [2024]
    Nyckelord :Log Analysis; Log Frequency Patterns; anomaly detection; machine learning; cloud environments;

    Sammanfattning : Background: Log analysis has been proven to be highly beneficial in monitoring system behaviour, detecting errors and anomalies, and predicting future trends in systems and applications. However, with continuous evolution of these systems and applications, the amount of log data generated on a timely basis is increasing rapidly. LÄS MER

  7. 5. Exploring a Wearable Technology for Enhanced Learning : - a design concept

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Linus Thofte; [2024]
    Nyckelord :Exoskeleton; Haptics; Smart Glove; UX; Interaction Design; Embodied Music Cognition; Human-Machine Cooperation; Wearables; Learning System; Technology Matchmaking;

    Sammanfattning : This paper is an explorative interaction design study focusing on the development of a wearable device for enhanced learning of bodily skills. It uses a variation of technology scouting and matchmaking to explore possible technologies related to assistive technology for learning. LÄS MER