Defended His Thesis

Defended His Thesis-79
The first step of this research project is the implementation of a modeling approach suitable with optimization processes.It is then essential to take into account all subsystems that form the electromechanical drive, namely the LISNs, the cables, the power converter and the electric motor.The modeling approach chosen is of the direct type ; it consists of representing the electromechanical chain in the common mode base by two ports networks.

Congratulations to Melvin Wong on successfully defending his Ph D thesis on August 12, 2019. Wong completed his undergraduate degree in Computer Engineering from Nanyang Technological University in 2015.

Generative Modelling and Machine Learning Methods for Travel Behaviour Analysis Professor Ricardo Daziano, Cornell University Professor Eric J.

Nevertheless, due to their higher switching speed and voltage overshoot, WBG semiconductors used in power converters of an electromechanical chain may have some drawbacks when it comes to Electro-Magnetic Interference.

Understanding the switching behavior of WBG components is necessary in order to keep switching speed and overvoltage at a reasonable level.

In the past, three techniques have been developed for improving an SPE’s ability to adapt.

Those techniques are classified based on applications’ requirements on exact or approximate results: stream partitioning, and re-partitioning target exact, and load shedding targets approximate processing.

In this Ph D thesis, we ensure that the introduction of this emerging technology does not lead to a regression of performance at system level.

Once we establish the conducted emissions models, different filtering solutions have been used: external and internal passive filters.

Committee Alexandros Labrinidis, Department of Computer Science, University of Pittsburgh (co-chair) Panos Chrysanthis, Department of Computer Science, University of Pittsburgh (co-chair) Jack Lange, Department of Computer Science, University of Pittsburgh (member) Andy Pavlo, Department of Computer Science, Carnegie Mellon University (member) TITLE: A Procrustean Approach to Stream Processing Abstract: === START === The increasing demand for real-time data processing and the constantly growing data volume have contributed to the rapid evolution of Stream Processing Engines (SPEs), which are designed to continuously process data.

Low operational cost and timely delivery of results are both objectives of paramount importance for SPEs.


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