Sökning: "Adaptive Systems"
Visar resultat 6 - 10 av 442 uppsatser innehållade orden Adaptive Systems.
6. Towards Adaptive Image Resolution for Visual SLAM on Resource-constrained Devices
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Today, a large number of devices with small form factors and limited resources are being integrated with processes to perform complex tasks such as localization and mapping. One example of this are headsets used for Extended Reality. LÄS MER
7. Unsupervised Online Anomaly Detection in Multivariate Time-Series
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/DatorteknikSammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER
8. Ability Estimation Methods : An Introduction to Item Response Theory and Elo Education Systems
Kandidat-uppsats, Stockholms universitet/Statistiska institutionenSammanfattning : The foundational testing of knowledge and ability is and has always been very important. These days we can create a computerized test that can vary based on the estimated skill of the examinee. This is called an adaptive test. And the aim of this is to estimate the ability of the examinee more precisely. LÄS MER
9. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: Cloud computing’s rapid growth has highlighted the need for efficientresource allocation. While cloud platforms offer scalability and cost-effectiveness for a variety of applications, managing resources to match dynamic workloads remains a challenge. LÄS MER
10. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. LÄS MER