Advanced search

Showing result 1 - 5 of 126 essays matching the above criteria.

  1. 1. Off-State Stress Effects in AlGaN/GaN HEMTs : Investigation of high-voltage off-state stress impact on performance of and its retention in hybrid-drain ohmic gate AlGaN/GaN HEMTs

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

    Author : Ivan Krsic; [2023]
    Keywords : HEMT; GaN; off-state stress; memory effects; drain leakage current; dynamic RDSon; threshold voltage instabilities; charge redistribution; HEMT; GaN; stress i avslaget tillstånd; minneseffekter; läckströmmen; dynamisk RDSon; instabiliteten hos styrets tröskelspänning; omfördelningen av laddningar;

    Abstract : High electron mobility transistors (HEMTs) realized using AlxGa1-xN/GaN are relatively new technology which is prominent for high-speed and high-power applications. Some of the main problems with this technology were identified as dynamic RDSon, current collapse and threshold voltage instabilities due to the off-state stress. READ MORE

  3. 2. Unsupervised Online Anomaly Detection in Multivariate Time-Series

    University essay from Uppsala universitet/Datorteknik

    Author : Ludvig Segerholm; [2023]
    Keywords : unsupervised; online; anomaly detection; explainable ai; machine learning; mahalanobis distance;

    Abstract : 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. READ MORE

  4. 3. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

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

    Author : Luca Colasanti; [2023]
    Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

    Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE

  5. 4. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Sai Nikhil Boyapati; [2023]
    Keywords : Auto-Scaling; Auto-Scaling Recommendations; Cloud Environment; K-Nearest Neighbors; Machine Learning; Recommendation Systems; Random Forests; Support Vector Machines;

    Abstract : 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. READ MORE

  6. 5. Data Driven Modeling for Aerodynamic Coefficients

    University essay from KTH/Matematisk statistik

    Author : Erik Jonsäll; Emma Mattsson; [2023]
    Keywords : Master s thesis; System identification; Parameter estimation; Ordinary least squares; Machine learning; Aerodynamic coefficients; F18--HARV; Flight simulations.; Masteruppsats; Systemidentifiering; Parameteruppskattning; Minstakvadratmetoden; Maskininlärning; Aerodynamiska koefficienter; F18-HARV; Flygsimuleringar.;

    Abstract : Accurately modeling aerodynamic forces and moments are crucial for understanding thebehavior of an aircraft when performing various maneuvers at different flight conditions.However, this task is challenging due to complex nonlinear dependencies on manydifferent parameters. READ MORE