Sökning: "collaborative feedback."

Visar resultat 1 - 5 av 80 uppsatser innehållade orden collaborative feedback..

  1. 1. Inside the Future of Shopping Malls - Logistics Approaches for Enhancing the Collection Efficiency of Online Retail Orders from Shopping Malls by Delivery Agents

    Master-uppsats, Göteborgs universitet/Graduate School

    Författare :Julia Krajka; Kaisa Nordlund; [2023-07-03]
    Nyckelord :Urban Logistics; Retail; Shopping Malls; Gig Economy; Last Mile Delivery; E-commerce; Automation; Micro-hubs; Parcel Lockers; Consumption Behavior; Stakeholder Management;

    Sammanfattning : Background: The rise of e-commerce has revolutionized the retail industry, with consumers now able to purchase goods online and receive their orders promptly at their doorstep. The COVID-19 pandemic has accelerated this trend, leading to traditional retailers reimagining their strategies and embracing omnichannel approaches to meet the growing demand for fast deliveries. LÄS MER

  2. 2. 3D virtual space for collaborative design reviews

    Kandidat-uppsats, Högskolan i Skövde/Institutionen för ingenjörsvetenskap

    Författare :Paula Reyes Aguilera; Maria Teresa Trujillo Rufino; [2023]
    Nyckelord :;

    Sammanfattning : The PLENUM group, formed by researchers and developers of XR methods, aims to develop functions and spaces in virtual reality to improve the design environment. In the field of design reviews, although design reviews are now increasingly being conducted digitally, teams are still reliant on video conferencing software, as currently no dedicated tools are available. LÄS MER

  3. 3. Design of Video Editing Interface for Collaboration

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

    Författare :Ellen Tholsby; [2023]
    Nyckelord :video editing; collaboration; user interface design; workspace awareness; videoredigering; samarbete; design av användargränssnitt; arbetsplatsmedvetenhet;

    Sammanfattning : Video editing is a process where multiple roles are required to collaborate. Despite this, the design of video editing software does not easily support collaboration. Hence, this study investigates how the video editing workflow can be improved by designing a user interface that supports collaboration. LÄS MER

  4. 4. Leveling Up the Playing Field: Exploring the Strengths and Weaknesses of AI-Generated Content in Game Development

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

    Författare :Martin Kings; Simon Täcklind; [2023]
    Nyckelord :Game Development; AI; ChatGPT; DALL-E; Content Generation; Evaluation;

    Sammanfattning : The development of video games is a long and expensive process, and it is not uncommon for studios to require their workers to work overtime to meet deadlines, resulting in stressful work environments and reduced worker performance. Recent advancements in artificial intelligence (AI) research have people excited that perhaps this might change. LÄS MER

  5. 5. Recommending digital books to children : Acomparative study of different state-of-the-art recommendation system techniques

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

    Författare :Malvin Lundqvist; [2023]
    Nyckelord :Recommendation Systems; Collaborative Filtering; Matrix Factorization; Multi-Layer Perceptron; Neural Network-based Collaborative Filtering; Implicit Feedback; Deep Learning; Term Frequency-Inverse Document Frequency; Rekommendationssystem; Kollaborativ filtrering; Matrisfaktorisering; Flerlagersperceptron; Neurala nätverksbaserad kollaborativ filtrering; Implicit data; Djupinlärning; Termfrekvens med omvänd dokumentfrekvens;

    Sammanfattning : Collaborative filtering is a popular technique to use behavior data in the form of user’s interactions with, or ratings of, items in a system to provide personalized recommendations of items to the user. This study compares three different state-of-the-art Recommendation System models that implement this technique, Matrix Factorization, Multi-layer Perceptron and Neural Matrix Factorization, using behavior data from a digital book platform for children. LÄS MER