Essays about: "Network Context"

Showing result 21 - 25 of 857 essays containing the words Network Context.

1. 21. Adaptive Model-Based Temperature Monitoring for Electric Powertrains : Investigation and Comparative Analysis of Transfer Learning Approaches

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

   Author : Chenzhou Huang; [2023]
   Keywords : Transfer Learning; Condition Monitoring; Domain Adaptation; Neural Network; Powerstrain.; Siirto-oppiminen; kunnonvalvonta; verkkotunnuksen mukauttaminen; neuroverkko; voimansiirto.; Överföring lärande; tillståndsövervakning; domänanpassning; neuralt nätverk; Powerstrain;

   Abstract : In recent years, deep learning has been widely used in industry to solve many complex problems such as condition monitoring and fault diagnosis. Powertrain condition monitoring is one of the most vital and complicated problems in the automation industry since the condition of the drive affects its health, performance, and reliability. READ MORE

3. 22. Model Based Testing for Programmable Data Planes

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Gustav Rixon; [2023]
   Keywords : Model Based Testing; Programmable Data Planes; P4; Software- Defined Networking;

   Abstract : The advent of Software Defined Networking (SDN) and programmable data planes has revolutionized the networking domain, enabling the programming of networking functions down to the silicon level responsible for data packet switching. Unfortunately, while this programmability offers greater flexibility and control, it also increases the likelihood of introducing software bugs. READ MORE

4. 23. A Machine Learning Approach on Analysis of Emission Spectra for Application in XFEL Experiments

   University essay from Uppsala universitet/Institutionen för fysik och astronomi

   Author : Harald Agelii; [2023]
   Keywords : Structural biology; Machine learning; Neural networks; emission spectrum; XFEL; X-ray free electron laser; SFX; Serial femtosecond X-ray crystallography; Proteins; Diagnostics;

   Abstract : In this thesis we investigate two potential applications of machine learning in the context of X-ray imaging and spectroscopy of biological samples, particularly such using X-ray free electron lasers (XFEL). We first investigate the possibility of using an emission spectrum, recorded from a sample after being probed by an incident X-ray, as a diagnostic tool. READ MORE

5. 24. Understanding User Behaviour in a Circular Transport System : From personal choices to societal patterns

   University essay from Stockholms universitet/Stockholm Resilience Centre

   Author : Luja von Köckritz; [2023]
   Keywords : circular economy; agent-based modelling; user behaviour; behavioural decision-making; affordance theory;

   Abstract : The Circular Economy is a growing research field and policy agenda. Yet, integrating the social dimensions of sustainability into the Circular Economy remains a challenge. The significance of reactions to an implemented Circular Economy is poorly understood. READ MORE

6. 25. 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