Sökning: "learning and memory"

Visar resultat 1 - 5 av 706 uppsatser innehållade orden learning and memory.

  1. 1. Optical Communication using Nanowires and Molecular Memory Systems

    Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

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

    Sammanfattning : 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. LÄS MER

  3. 2. Praktiska digitala medium i historieundervisningen : En översikt av forskning om hur digitalt game-based learning kan användas för att förbättra elevernas kunskap om historieämnet

    Uppsats för yrkesexamina på grundnivå, Malmö universitet/Fakulteten för lärande och samhälle (LS)

    Författare :Dennis Gullstrand; Erik Lund; [2024]
    Nyckelord :history; history didactics; history education; didactics; practical; game based learning; game; games; digital; computer; Assassin s Creed; Making History; Crusader Kings; Hearts of Iron; high school; historia; historiedidaktik; historieundervisning; undervisning; didaktik; praktiskt; game based learning; spel; digital; digitala; dator; Assassin s Creed; Making History; Crusader Kings; Hearts of Iron; gymnasie; gymnasiet; högstadium; högstadiet; grundskola;

    Sammanfattning : The traditional history educational methods mainly consists of and are focused on memory, reading, repetition and writing skills, however this paper aims to give an overview of research regarding “Game-based learning”, it’s uses in education of history, and if it can be used as a way to complement the traditional education and give history teachers the tools to make their teaching more diverse. Useful materials were found in the databases: EBSCO, IEEE Xplore och Science Direct. LÄS MER

  4. 3. Collaborative Learning in an Immersive Virtual Environment: The Effects of Context and Retrieval Practice

    Master-uppsats, Lunds universitet/Institutionen för psykologi

    Författare :Noelle Bender; [2024]
    Nyckelord :VR; collaborative Mapping; retrieval practice; contextual variation; desirable difficulty; ecological validity; Social Sciences;

    Sammanfattning : The accessibility of Virtual Reality (VR) enables the investigation of desirable difficulties originating from memory research with increased ecological validity. The two desirable difficulties include contextual variation and retrieval practice. LÄS MER

  5. 4. Exploring serial positioning effects in Claeson-Dahl's Test for verbal learning and retention – a naturalistic study

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för psykologi

    Författare :Hampus Fritz; [2024]
    Nyckelord :serial positioning effect; Claeson-Dahl’s Test for verbal learning and retention; neuropsychology; memory; word list; Seriepositionseffekten; Claeson-Dahls Test för inlärning och minne; neuropsykolog; minne; ordlista; Social Sciences;

    Sammanfattning : Serial positioning effects and the derived recency ratio has shown increasing promise as clinical tools for evaluating neurocognitive disorders. These measures have remained unexplored in Claeson-Dahl’s Test for verbal learning and retention (CDT). LÄS MER

  7. 5. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Khalid El Yaacoub; [2024]
    Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

    Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER