Sökning: "skalbarhet och tillförlitlighet"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden skalbarhet och tillförlitlighet.

1. 1. Volumetric Image Segmentation of Lizard Brains

   Master-uppsats, KTH/Tillämpad fysik

   Författare :Yulia Dragunova; [2023]
   Nyckelord :image segmentation; deep learning; atlas; lizard brain; micro-CT; image augmentation; bild segmentering; djupinlärning; atlas; ödelhjärna; mikro-datortomagrofi; datautökning;

   Sammanfattning : Accurate measurement brain region volumes are important in studying brain plasticity, which brings insight into the fundamental mechanisms in animal, memory, cognitive, and behavior research. The traditional methods of brain volume measurements are ellipsoid or histology. LÄS MER

3. 2. Probabilistic Multi-Modal Data Fusion and Precision Coordination for Autonomous Mobile Systems Navigation : A Predictive and Collaborative Approach to Visual-Inertial Odometry in Distributed Sensor Networks using Edge Nodes

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

   Författare :Isabella Luppi; [2023]
   Nyckelord :Distributed Sensor Networks; Point Cloud Processing; Bounding Box Fitting; Trajectory Tracking; Distributed Estimation; Predictive Estimation; Edge-Computing; Reti di Sensori Distribuiti; Elaborazione di Nuvole di Punti; Riquadri di Delimitazione; Tracciamento della Traiettoria; Stima Distribuita; Stima Predittiva; Calcolo Distribuito.; Distribuerade Sensornätverk; Bearbetning av Punktmoln; Anpassning av Begränsningsruta; Trajektorieuppföljning; Distribuerad Uppskattning; Prediktiv Uppskattning; Edge-datorbehandling;

   Sammanfattning : This research proposes a novel approach for improving autonomous mobile system navigation in dynamic and potentially occluded environments. The research introduces a tracking framework that combines data from stationary sensing units and on-board sensors, addressing challenges of computational efficiency, reliability, and scalability. LÄS MER

4. 3. Forecasting Volume of Sales During the Abnormal Time Period of COVID-19. An Investigation on How to Forecast, Where the Classical ARIMA Family of Models Fail

   Master-uppsats, KTH/Matematisk statistik

   Författare :Christina Ghawi; [2021]
   Nyckelord :Time series forecasting; ARIMA family of models; abnormal time period; extreme events; COVID-19 pandemic; time series outliers;

   Sammanfattning : During the COVID-19 pandemic, customer shopping habits have changed. Some industries experienced an abrupt shift during the pandemic outbreak while others navigate in new normal states. For some merchants, the highly-uncertain new phenomena of COVID-19 expresses as outliers in time series of volume of sales. LÄS MER

5. 4. Evaluation of Network-Layer Security Technologies for Cloud Platforms

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

   Författare :Bruno Marcel Duarte Coscia; [2020]
   Nyckelord :Overlay network; Network security; IPsec; Slack nebula; Nebula; Noise framework; Noise protocol; Överlagring Nätverk; Nätverkssäkerhet; IPsec; Slack nebula; Nebula; Noise ramverk; Noise protokoll;

   Sammanfattning : With the emergence of cloud-native applications, the need to secure networks and services creates new requirements concerning automation, manageability, and scalability across data centers. Several solutions have been developed to overcome the limitations of the conventional and well established IPsec suite as a secure tunneling solution. LÄS MER

7. 5. StackLang : Automatic Attack Simulations Against the OpenStack Cloud Environment

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

   Författare :Sara Rosander; [2020]
   Nyckelord :;

   Sammanfattning : Cloud computing is a fast-emerging technology. It is an attractive system for companies and has been embraced by many due to its benefits of economy, reliability, scalability, and guaranteed quality of service. Due to the increasing use of cloud platforms, it is important to be able to ensure its security. LÄS MER