Sökning: "Distance Learning"
Visar resultat 21 - 25 av 160 avhandlingar innehållade orden Distance Learning.
21. Offline and Online Models for Learning Pairwise Relations in Data
Sammanfattning : Pairwise relations between data points are essential for numerous machine learning algorithms. Many representation learning methods consider pairwise relations to identify the latent features and patterns in the data. This thesis, investigates learning of pairwise relations from two different perspectives: offline learning and online learning. LÄS MER
22. Letters & Bytes : Sociotechnical Studies of Distance Education
Sammanfattning : This dissertation studies the social aspects of technology in distance education trough the lens of history – in the form of correspondence education – and a possible future – in the form of a project of technical standardization, Learning Objects. The studied cases form a reflexive tool that allows the present of distance education to be seen in perspective. LÄS MER
23. Lärande genom möten : En studie av kommunikation mellan lärare och studerande i klassrumsmiljö och datorbaserad nätverksmiljö
Sammanfattning : The aim of this dissertation is to study the social interaction of teachers and students, and their reflections on this interaction. This is done in order to illuminate opportunities and constraints of communication and learning in two different environments within distance education – in the classroom and in a computer-based network environment. LÄS MER
24. Proximity and Learning in Internationalisation : Small Swedish IT firms in India
Sammanfattning : The four IT service firms of this thesis set out to interact and collaborate between their offices in Sweden and in India, some more intensely and frequently than others. In the process of their internationalisation, these small service firms find ways, or go through a process of learning how to collaborate in an international setting. LÄS MER
25. On Deep Machine Learning Based Techniques for Electric Power Systems
Sammanfattning : This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. LÄS MER