Sökning: "changing performance conditions"

Visar resultat 1 - 5 av 87 uppsatser innehållade orden changing performance conditions.

  1. 1. Creating a Context for Listening: The Choreography of Sound

    Master-uppsats, Göteborgs universitet/Högskolan för scen och musik

    Författare :Casey Moir; [2022-02-22]
    Nyckelord :listening to space; shaping space; mapping space; active listening; encouraging interactions; composing situation and sounds; spatialising performances; designing proximities and trajectories; composing movement and momentum; alternate performance spaces; changing the expectations of room; visualising sound in space; engaging spatial awareness; changing performance conditions; changing listening perspective; omnidirectional composition; experimental music composition; choreographing sound;

    Sammanfattning : My thesis is an investigation into an omnidirectional approach to composition of experimental music. This involves considering the conditions of performance as compositional aspects, in addition to composing sounds. LÄS MER

  2. 2. Real-time Human Detection using Convolutional Neural Networks with FMCW RADAR RGB data

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Anna Phan; Rogelio Medina; [2022]
    Nyckelord :Human Detection; Machine Learning; Convolutional Neural Networks; YOLO; FMCW Radar; Human Detection Evaluation; Människodetektering; Maskininlärning; Neurala faltningsnät; Djupa faltningsnät; YOLO; FMCW Radar; Utvärdering;

    Sammanfattning : Machine learning has been employed in the automotive industry together with cameras to detect objects in surround sensing technology. You Only Look Once is a state-of-the-art object detection algorithm especially suitable for real-time applications due to its speed and relatively high accuracy compared to competing methods. LÄS MER

  3. 3. Managing operations resources and processes for competitive advantage : A study on the performance of Swedish pharmaceutical companies during the COVID-19 pandemic

    Magister-uppsats, Blekinge Tekniska Högskola/Institutionen för industriell ekonomi

    Författare :Mohsin Raza; Jesper Svensson; [2022]
    Nyckelord :Operations; strategy; pharmaceutical; pandemic; attributes; digitalization;

    Sammanfattning : The outbreak of coronavirus disease 2019 (COVID-19) has caused immense challenges to businesses and people’s lives. For the pharmaceutical industry, these challenges entail changes in demand, supply chain, consumption trends, as well as a shift towards telemedicine and changes in R&D priorities. LÄS MER

  4. 4. Belief Rule-Based Workload Orchestration in Multi-access Edge Computing

    Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Mohammad Newaj Jamil; [2022]
    Nyckelord :Multi-access Edge Computing MEC ; Task Offloading; Workload Orchestrator; Belief Rule Base BRB ; Performance Evaluation;

    Sammanfattning : Multi-access Edge Computing (MEC) is a standard network architecture of edge computing, which is proposed to handle tremendous computation demands of emerging resource-intensive and latency-sensitive applications and services and accommodate Quality of Service (QoS) requirements for ever-growing users through computation offloading. Since the demand of end-users is unknown in a rapidly changing dynamic environment, processing offloaded tasks in a non-optimal server can deteriorate QoS due to high latency and increasing task failures. LÄS MER

  5. 5. Imputing connections of random gene networks from time series data using ANNs

    Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Författare :Sofia Andersson; [2022]
    Nyckelord :artificial neural networks; ANNs; gene regulatory networks; GRNs; imputation; gene regulatory network imputation; GRN imputation; CNNs; convolutional neural network; randomly generated networks; ternary classification; binary classification; network inference; Physics and Astronomy;

    Sammanfattning : This thesis presents the architecture of a convolutional neural network which is trained to impute the connections of randomly generated gene regulatory networks under varying amounts of regularisation. The generated gene networks are simulated from 10 different starting conditions for each set of connections in order to obtain multiple time series. LÄS MER