Essays about: "edge user"

Showing result 6 - 10 of 124 essays containing the words edge user.

  1. 6. A Holistic Framework for Analyzing the Reliability of IoT Devices

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Leonardo Manca; [2023]
    Keywords : Canvas Learning Management System; Docker containers; Performance tuning Performance tuning; Internet of Things IoT ; Reliability; Failure rate; Availability; Comprehensive framework; IoT architecture; Failure modes; Reliability Block Diagram RBD ; Prestandajustering; Sakernas internet IoT ; Tillförlitlighet; Felfrekvens; Tillgänglighet; Heltäckande ramverk; IoT-arkitektur; Felfunktioner; Till-förlitlighetsblockdiagram RBD Canvas Lärplattform; Dockerbehållare; Prestandajustering;

    Abstract : In the rapidly evolving landscape of the Internet of Things (IoT), ensuring consistency and reliability becomes a top priority for a seamless user experience. In many instances, reliability is assessed through Quality of Service (QoS) metrics, sidelining traditional reliability metrics that thrive on time-dependent failure rates. READ MORE

  3. 7. Visualizing pediatric obesity data to determine treatment strategy effectiveness and improvements

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Octav Le Tullier; [2023]
    Keywords : Pediatric Obesity Treatment; Clinical Decision Support System; Health Data; Information Visualization; Interaction Design; Barnobesitas Behandling; System För Kliniskt Beslutsstöd; Hälsodata; Informationsvisualisering; Interaktionsdesign; ;

    Abstract : Pediatric obesity is skyrocketing nowadays worldwide. Therefore, helping and supporting clinicians in curing children is needed. As Health IT is soaring thanks to the emergence of a cutting-edge technology, treatments can now be followed closely and daily to give a personalized therapy. READ MORE

  4. 8. A Bayesian Bee Colony Algorithm for Hyperparameter Tuning of Stochastic SNNs : A design, development, and proposal of a stochastic spiking neural network and associated tuner

    University essay from Uppsala universitet/Signaler och system

    Author : Oskar Falkeström; [2023]
    Keywords : edge computing; edge user allocation; constraint satisfaction problem; bin packing problem; spiking neural networks; SNN; stochastic spiking neural networks; neuromorphic computing; hyperparameter tuning; swarm intellience; artificial bee colony algorithm; tree-structured Parzen estimator; stochastic optimization; Bayesian optimization.;

    Abstract : With the world experiencing a rapid increase in the number of cloud devices, continuing to ensure high-quality connections requires a reimagining of cloud. One proponent, edge computing, consists of many distributed and close-to-consumer edge servers that are hired by the service providers. READ MORE

  5. 9. Introducing GA-SSNN: A Method for Optimizing Stochastic Spiking Neural Networks : Scaling the Edge User Allocation Constraint Satisfaction Problem with Enhanced Energy and Time Efficiency

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Nathan Allard; [2023]
    Keywords : ;

    Abstract : As progress within Von Neumann-based computer architecture is being limited by the physical limits of transistor size, neuromorphic comuting has emerged as a promising area of research. Neuromorphic hardware tends to be substantially more power efficient by imitating the aspects of computations in networks of neurons in the brain. READ MORE

  6. 10. Exploring Normalizing Flow Modifications for Improved Model Expressivity

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Marcel Juschak; [2023]
    Keywords : Normalizing Flows; Motion Synthesis; Invertible Neural Networks; Glow; MoGlow; Maximum Likelihood Estimation; Generative models; normaliserande flöden; rörelsesyntes; inverterbara neurala nätverk; Glow; MoGlow; maximum likelihood-skattning generativa modeller;

    Abstract : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. READ MORE